Molecular potentials and relaxation dynamics
International Nuclear Information System (INIS)
Karo, A.M.
1981-01-01
The use of empirical pseudopotentials, in evaluating interatomic potentials, provides an inexpensive and convenient method for obtaining highly accurate potential curves and permits the modeling of core-valence correlation, and the inclusion of relativistic effects when these are significant. Recent calculations of the X 1 Σ + and a 3 Σ + states of LiH, NaH, KH, RbH, and CsH and the X 2 Σ + states of their anions are discussed. Pseudopotentials, including core polarization terms, have been used to replace the core electrons, and this has been coupled with the development of compact, higly-optimized basis sets for the corresponding one- and two-electron atoms. Comparisons of the neutral potential curves with experiment and other ab initio calculations show good agreement (within 1000 cm -1 over most of the potential curves) with the difference curves being considerably more accurate. In the method of computer molecular dynamics, the force acting on each particle is the resultant of all interactions with other atoms in the neighborhood and is obtained as the derivative of an effective many-body potential. Exploiting the pseudopotential approach, in obtaining the appropriate potentials may be very fruitful in the future. In the molecular dynamics example considered here, the conventional sum-of-pairwise-interatomic-potentials (SPP) approximation is used with the potentials derived either from experimental spectroscopic data or from Hartree-Fock calculations. The problem is the collisional de-excitation of vibrationally excited molecular hydrogen at an Fe surface. The calculations have been carried out for an initial vibrotational state v = 8, J = 1 and a translational temperature corresponding to a gas temperature of 500 0 K. Different angles of approach and different initial random impact points on the surface have been selected. For any given collision with the wall, the molecule may pick up or lose vibrotatonal and translational energy
Zhu, Ming; Liu, Tingting; Wang, Shu; Zhang, Kesheng
2017-08-01
Existing two-frequency reconstructive methods can only capture primary (single) molecular relaxation processes in excitable gases. In this paper, we present a reconstructive method based on the novel decomposition of frequency-dependent acoustic relaxation spectra to capture the entire molecular multimode relaxation process. This decomposition of acoustic relaxation spectra is developed from the frequency-dependent effective specific heat, indicating that a multi-relaxation process is the sum of the interior single-relaxation processes. Based on this decomposition, we can reconstruct the entire multi-relaxation process by capturing the relaxation times and relaxation strengths of N interior single-relaxation processes, using the measurements of acoustic absorption and sound speed at 2N frequencies. Experimental data for the gas mixtures CO2-N2 and CO2-O2 validate our decomposition and reconstruction approach.
Bayesian estimation of multicomponent relaxation parameters in magnetic resonance fingerprinting.
McGivney, Debra; Deshmane, Anagha; Jiang, Yun; Ma, Dan; Badve, Chaitra; Sloan, Andrew; Gulani, Vikas; Griswold, Mark
2018-07-01
To estimate multiple components within a single voxel in magnetic resonance fingerprinting when the number and types of tissues comprising the voxel are not known a priori. Multiple tissue components within a single voxel are potentially separable with magnetic resonance fingerprinting as a result of differences in signal evolutions of each component. The Bayesian framework for inverse problems provides a natural and flexible setting for solving this problem when the tissue composition per voxel is unknown. Assuming that only a few entries from the dictionary contribute to a mixed signal, sparsity-promoting priors can be placed upon the solution. An iterative algorithm is applied to compute the maximum a posteriori estimator of the posterior probability density to determine the magnetic resonance fingerprinting dictionary entries that contribute most significantly to mixed or pure voxels. Simulation results show that the algorithm is robust in finding the component tissues of mixed voxels. Preliminary in vivo data confirm this result, and show good agreement in voxels containing pure tissue. The Bayesian framework and algorithm shown provide accurate solutions for the partial-volume problem in magnetic resonance fingerprinting. The flexibility of the method will allow further study into different priors and hyperpriors that can be applied in the model. Magn Reson Med 80:159-170, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.
Accelerating convergence of molecular dynamics-based structural relaxation
DEFF Research Database (Denmark)
Christensen, Asbjørn
2005-01-01
We describe strategies to accelerate the terminal stage of molecular dynamics (MD)based relaxation algorithms, where a large fraction of the computational resources are used. First, we analyze the qualitative and quantitative behavior of the QuickMin family of MD relaxation algorithms and explore...
Bayesian molecular dating: opening up the black box.
Bromham, Lindell; Duchêne, Sebastián; Hua, Xia; Ritchie, Andrew M; Duchêne, David A; Ho, Simon Y W
2018-05-01
Molecular dating analyses allow evolutionary timescales to be estimated from genetic data, offering an unprecedented capacity for investigating the evolutionary past of all species. These methods require us to make assumptions about the relationship between genetic change and evolutionary time, often referred to as a 'molecular clock'. Although initially regarded with scepticism, molecular dating has now been adopted in many areas of biology. This broad uptake has been due partly to the development of Bayesian methods that allow complex aspects of molecular evolution, such as variation in rates of change across lineages, to be taken into account. But in order to do this, Bayesian dating methods rely on a range of assumptions about the evolutionary process, which vary in their degree of biological realism and empirical support. These assumptions can have substantial impacts on the estimates produced by molecular dating analyses. The aim of this review is to open the 'black box' of Bayesian molecular dating and have a look at the machinery inside. We explain the components of these dating methods, the important decisions that researchers must make in their analyses, and the factors that need to be considered when interpreting results. We illustrate the effects that the choices of different models and priors can have on the outcome of the analysis, and suggest ways to explore these impacts. We describe some major research directions that may improve the reliability of Bayesian dating. The goal of our review is to help researchers to make informed choices when using Bayesian phylogenetic methods to estimate evolutionary rates and timescales. © 2017 Cambridge Philosophical Society.
Molecular dynamics study on the relaxation properties of bilayered ...
Indian Academy of Sciences (India)
2017-08-31
Aug 31, 2017 ... Abstract. The influence of defects on the relaxation properties of bilayered graphene (BLG) has been studied by molecular dynamics simulation in nanometre sizes. Type and position of defects were taken into account in the calculated model. The results show that great changes begin to occur in the ...
Thermal relaxation of molecular oxygen in collisions with nitrogen atoms
Energy Technology Data Exchange (ETDEWEB)
Andrienko, Daniil A., E-mail: daniila@umich.edu; Boyd, Iain D. [Department of Aerospace Engineering, University of Michigan, 1320 Beal Ave., Ann Arbor, Michigan 48108 (United States)
2016-07-07
Investigation of O{sub 2}–N collisions is performed by means of the quasi-classical trajectory method on the two lowest ab initio potential energy surfaces at temperatures relevant to hypersonic flows. A complete set of bound–bound and bound–free transition rates is obtained for each precollisional rovibrational state. Special attention is paid to the vibrational and rotational relaxations of oxygen as a result of chemically non-reactive interaction with nitrogen atoms. The vibrational relaxation of oxygen partially occurs via the formation of an intermediate NO{sub 2} complex. The efficient energy randomization results in rapid vibrational relaxation at low temperatures, compared to other molecular systems with a purely repulsive potential. The vibrational relaxation time, computed by means of master equation studies, is nearly an order of magnitude lower than the relaxation time in N{sub 2}–O collisions. The rotational nonequilibrium starts to play a significant effect at translational temperatures above 8000 K. The present work provides convenient relations for the vibrational and rotational relaxation times as well as for the quasi-steady dissociation rate coefficient and thus fills a gap in data due to a lack of experimental measurements for this system.
Stretched exponential relaxation in molecular and electronic glasses
Phillips, J. C.
1996-09-01
Stretched exponential relaxation, 0034-4885/59/9/003/img1, fits many relaxation processes in disordered and quenched electronic and molecular systems, but it is widely believed that this function has no microscopic basis, especially in the case of molecular relaxation. For electronic relaxation the appearance of the stretched exponential is often described in the context of dispersive transport, where 0034-4885/59/9/003/img2 is treated as an adjustable parameter, but in almost all cases it is generally assumed that no microscopic meaning can be assigned to 0034-4885/59/9/003/img3 even at 0034-4885/59/9/003/img4, a glass transition temperature. We show that for molecular relaxation 0034-4885/59/9/003/img5 can be understood, providing that one separates extrinsic and intrinsic effects, and that the intrinsic effects are dominated by two magic numbers, 0034-4885/59/9/003/img6 for short-range forces, and 0034-4885/59/9/003/img7 for long-range Coulomb forces, as originally observed by Kohlrausch for the decay of residual charge on a Leyden jar. Our mathematical model treats relaxation kinetics using the Lifshitz - Kac - Luttinger diffusion to traps depletion model in a configuration space of effective dimensionality, the latter being determined using axiomatic set theory and Phillips - Thorpe constraint theory. The experiments discussed include ns neutron scattering experiments, particularly those based on neutron spin echoes which measure S( Q,t) directly, and the traditional linear response measurements which span the range from 0034-4885/59/9/003/img8 to s, as collected and analysed phenomenologically by Angell, Ngai, Böhmer and others. The electronic materials discussed include a-Si:H, granular 0034-4885/59/9/003/img9, semiconductor nanocrystallites, charge density waves in 0034-4885/59/9/003/img10, spin glasses, and vortex glasses in high-temperature semiconductors. The molecular materials discussed include polymers, network glasses, electrolytes and alcohols, Van
Stretched exponential relaxation in molecular and electronic glasses
International Nuclear Information System (INIS)
Phillips, J.C.
1996-01-01
Stretched exponential relaxation, exp[-(t/τ) β ], fits many relaxation processes in disordered and quenched electronic and molecular systems, but it is widely believed that this function has no microscopic basis, especially in the case of molecular relaxation. For electronic relaxation the appearance of the stretched exponential is often described in the context of dispersive transport, where β is treated as an adjustable parameter, but in almost all cases it is generally assumed that no microscopic meaning can be assigned to 0 g , a glass transition temperature. We show that for molecular relaxation β(T g ) can be understood, providing that one separates extrinsic and intrinsic effects, and that the intrinsic effects are dominated by two magic numbers, β SR =3/5 for short-range forces, and β K =3/7 for long-range Coulomb forces, as originally observed by Kohlrausch for the decay of residual charge on a Leyden jar. Our mathematical model treats relaxation kinetics using the Lifshitz-Kac-Luttinger diffusion to traps depletion model in a configuration space of effective dimensionality, the latter being determined using axiomatic set theory and Phillips-Thorpe constraint theory. The experiments discussed include ns neutron scattering experiments, particularly those based on neutron spin echoes which measure S(Q, t) directly, and the traditional linear response measurements which span the range from μs to s, as collected and analysed phenomenologically by Angell, Ngai, Boehmer and others. The electronic materials discussed include a-Si:H, granular C 60 , semiconductor nanocrystallites, charge density waves in TaS 3 , spin glasses, and vortex glasses in high-temperature semiconductors. The molecular materials discussed include polymers, network glasses, electrolytes and alcohols, Van der Waals supercooled liquids and glasses, orientational glasses, water, fused salts, and heme proteins. In the intrinsic cases the theory of β(T g ) is often accurate to 2%, which
Stability and suppression of turbulence in relaxing molecular gas flows
Grigoryev, Yurii N
2017-01-01
This book presents an in-depth systematic investigation of a dissipative effect which manifests itself as the growth of hydrodynamic stability and suppression of turbulence in relaxing molecular gas flows. The work describes the theoretical foundations of a new way to control stability and laminar turbulent transitions in aerodynamic flows. It develops hydrodynamic models for describing thermal nonequilibrium gas flows which allow the consideration of suppression of inviscid acoustic waves in 2D shear flows. Then, nonlinear evolution of large-scale vortices and Kelvin-Helmholtz waves in relaxing shear flows are studied. Critical Reynolds numbers in supersonic Couette flows are calculated analytically and numerically within the framework of both linear and nonlinear classical energy hydrodynamic stability theories. The calculations clearly show that the relaxation process can appreciably delay the laminar-turbulent transition. The aim of the book is to show the new dissipative effect, which can be used for flo...
Stability investigations of relaxing molecular gas flows. Results and perspectives
Grigor'ev, Yurii N.; Ershov, Igor V.
2017-10-01
This article presents results of systematic investigations of a dissipative effect which manifests itself as the growth of hydrodynamic stability and suppression of turbulence in relaxing molecular gas flows. The effect can be a new way for control stability and laminar turbulent transition in aerodynamic flows. The consideration of suppression of inviscid acoustic waves in 2D shear flows is presented. Nonlinear evolution of large-scale vortices and Kelvin — Helmholtz waves in relaxing shear flows are studied. Critical Reynolds numbers in supersonic Couette flows are calculated analytically and numerically within the framework of both classical linear and nonlinear energy hydrodynamic stability theories. The calculations clearly show that the relaxation process can appreciably delay the laminar-turbulent transition. The aim of this article is to show the new dissipative effect, which can be used for flow control and laminarization.
TURBULENCE DECAY AND CLOUD CORE RELAXATION IN MOLECULAR CLOUDS
International Nuclear Information System (INIS)
Gao, Yang; Law, Chung K.; Xu, Haitao
2015-01-01
The turbulent motion within molecular clouds is a key factor controlling star formation. Turbulence supports molecular cloud cores from evolving to gravitational collapse and hence sets a lower bound on the size of molecular cloud cores in which star formation can occur. On the other hand, without a continuous external energy source maintaining the turbulence, such as in molecular clouds, the turbulence decays with an energy dissipation time comparable to the dynamic timescale of clouds, which could change the size limits obtained from Jean's criterion by assuming constant turbulence intensities. Here we adopt scaling relations of physical variables in decaying turbulence to analyze its specific effects on the formation of stars. We find that the decay of turbulence provides an additional approach for Jeans' criterion to be achieved, after which gravitational infall governs the motion of the cloud core. This epoch of turbulence decay is defined as cloud core relaxation. The existence of cloud core relaxation provides a more complete understanding of the effect of the competition between turbulence and gravity on the dynamics of molecular cloud cores and star formation
AC relaxation in the iron(8) molecular magnet
Rose, Geordie
2000-11-01
We investigate the low energy magnetic relaxation characteristics of the ``iron eight'' (Fe8) molecular magnet. Each molecule in this material contains a cluster of eight Fe 3+ ions surrounded by organic ligands. The molecules arrange themselves into a regular lattice with triclinic symmetry. At sufficiently low energies, the electronic spins of the Fe3+ ions lock together into a ``quantum rotator'' with spin S = 10. We derive a low energy effective Hamiltonian for this system, valid for temperatures less than Tc ~ 360 mK , where Tc is the temperature at which the Fe8 system crosses over into a ``quantum regime'' where relaxation characteristics become temperature independent. We show that in this regime the dominant environmental coupling is to the environmental spin bath in the molecule. We show how to explicitly calculate these couplings, given crystallographic information about the molecule, and do this for Fe8. We use this information to calculate the linewidth, topological decoherence and orthogonality blocking parameters. All of these quantities are shown to exhibit an isotope effect. We demonstrate that orthogonality blocking in Fe8 is significant and suppresses coherent tunneling. We then use our low energy effective Hamiltonian to calculate the single-molecule relaxation rate in the presence of an external magnetic field with both AC and DC components by solving the Landau-Zener problem in the presence of a nuclear spin bath. Both sawtooth and sinusoidal AC fields are analyzed. This single-molecule relaxation rate is then used as input into a master equation in order to take into account the many-molecule nature of the full system. Our results are then compared to quantum regime relaxation experiments performed on the Fe8 system.
Reliable Approximation of Long Relaxation Timescales in Molecular Dynamics
Directory of Open Access Journals (Sweden)
Wei Zhang
2017-07-01
Full Text Available Many interesting rare events in molecular systems, like ligand association, protein folding or conformational changes, occur on timescales that often are not accessible by direct numerical simulation. Therefore, rare event approximation approaches like interface sampling, Markov state model building, or advanced reaction coordinate-based free energy estimation have attracted huge attention recently. In this article we analyze the reliability of such approaches. How precise is an estimate of long relaxation timescales of molecular systems resulting from various forms of rare event approximation methods? Our results give a theoretical answer to this question by relating it with the transfer operator approach to molecular dynamics. By doing so we also allow for understanding deep connections between the different approaches.
Bayesian semiparametric regression models to characterize molecular evolution
Directory of Open Access Journals (Sweden)
Datta Saheli
2012-10-01
Full Text Available Abstract Background Statistical models and methods that associate changes in the physicochemical properties of amino acids with natural selection at the molecular level typically do not take into account the correlations between such properties. We propose a Bayesian hierarchical regression model with a generalization of the Dirichlet process prior on the distribution of the regression coefficients that describes the relationship between the changes in amino acid distances and natural selection in protein-coding DNA sequence alignments. Results The Bayesian semiparametric approach is illustrated with simulated data and the abalone lysin sperm data. Our method identifies groups of properties which, for this particular dataset, have a similar effect on evolution. The model also provides nonparametric site-specific estimates for the strength of conservation of these properties. Conclusions The model described here is distinguished by its ability to handle a large number of amino acid properties simultaneously, while taking into account that such data can be correlated. The multi-level clustering ability of the model allows for appealing interpretations of the results in terms of properties that are roughly equivalent from the standpoint of molecular evolution.
Excitation dynamics and relaxation in a molecular heterodimer
International Nuclear Information System (INIS)
Balevičius, V.; Gelzinis, A.; Abramavicius, D.; Mančal, T.; Valkunas, L.
2012-01-01
Highlights: ► Dynamics of excitation within a heterogenous molecular dimer. ► Excited states can be swapped due to different reorganization energies of monomers. ► Conventional excitonic basis becomes renormalized due to interaction with the bath. ► Relaxation is independent of mutual positioning of monomeric excited states. -- Abstract: The exciton dynamics in a molecular heterodimer is studied as a function of differences in excitation and reorganization energies, asymmetry in transition dipole moments and excited state lifetimes. The heterodimer is composed of two molecules modeled as two-level systems coupled by the resonance interaction. The system-bath coupling is taken into account as a modulating factor of the molecular excitation energy gap, while the relaxation to the ground state is treated phenomenologically. Comparison of the description of the excitation dynamics modeled using either the Redfield equations (secular and full forms) or the Hierarchical quantum master equation (HQME) is demonstrated and discussed. Possible role of the dimer as an excitation quenching center in photosynthesis self-regulation is discussed. It is concluded that the system-bath interaction rather than the excitonic effect determines the excitation quenching ability of such a dimer.
Simulations of vibrational relaxation in dense molecular fluids
International Nuclear Information System (INIS)
Holian, B.L.
1985-07-01
In the understanding of high-temperatre and -pressure chemistry in explosives, first step is the study of the transfer of energy from translational degrees of freedom into internal vibrations of the molecules. We present new methods using nonequilibrium molecular dynamics (NEMD) for measuring vibrational relaxation in a diatomic fluid, where we expect a classical treatment of many-body collisions to be relevant because of the high densities (2 to 3 times compressed compared to the normal fluid) and high temperatures (2000 to 4000 K) involved behind detonation waves. NEMD techniques are discussed, including their limitations, and qualitative results presented
Molecular order and T1-relaxation, cross-relaxation in nitroxide spin labels
Marsh, Derek
2018-05-01
Interpretation of saturation-recovery EPR experiments on nitroxide spin labels whose angular rotation is restricted by the orienting potential of the environment (e.g., membranes) currently concentrates on the influence of rotational rates and not of molecular order. Here, I consider the dependence on molecular ordering of contributions to the rates of electron spin-lattice relaxation and cross relaxation from modulation of N-hyperfine and Zeeman anisotropies. These are determined by the averages and , where θ is the angle between the nitroxide z-axis and the static magnetic field, which in turn depends on the angles that these two directions make with the director of uniaxial ordering. For saturation-recovery EPR at 9 GHz, the recovery rate constant is predicted to decrease with increasing order for the magnetic field oriented parallel to the director, and to increase slightly for the perpendicular field orientation. The latter situation corresponds to the usual experimental protocol and is consistent with the dependence on chain-labelling position in lipid bilayer membranes. An altered dependence on order parameter is predicted for saturation-recovery EPR at high field (94 GHz) that is not entirely consistent with observation. Comparisons with experiment are complicated by contributions from slow-motional components, and an unexplained background recovery rate that most probably is independent of order parameter. In general, this analysis supports the interpretation that recovery rates are determined principally by rotational diffusion rates, but experiments at other spectral positions/field orientations could increase the sensitivity to order parameter.
Generalized extended Navier-Stokes theory: Multiscale spin relaxation in molecular fluids
DEFF Research Database (Denmark)
Hansen, Jesper Schmidt
2013-01-01
This paper studies the relaxation of the molecular spin angular velocity in the framework of generalized extended Navier-Stokes theory. Using molecular dynamics simulations, it is shown that for uncharged diatomic molecules the relaxation time decreases with increasing molecular moment of inertia...
Selective excitation, relaxation, and energy channeling in molecular systems
International Nuclear Information System (INIS)
Rhodes, W.C.
1993-08-01
Research involves theoretical studies of response, relaxation, and correlated motion in time-dependent behavior of large molecular systems ranging from polyatomic molecules to protein molecules in their natural environment. Underlying theme is subsystem modulation dynamics. Main idea is that quantum mechanical correlations between components of a system develop with time, playing a major role in determining the balance between coherent and dissipative forces. Central theme is interplay of coherence and dissipation in determining the nature of dynamic structuring and energy flow in molecular transformation mechanisms. Subsystem equations of motion are being developed to show how nonlinear, dissipative dynamics of a particular subsystem arise from correlated interactions with the rest of the system (substituent groups, solvent, lattice modes, etc.); one consequence is resonance structures and networks. Quantum dynamics and thermodynamics are being applied to understand control and energy transfer mechanisms in biological functions of protein molecules; these mechanisms are both global and local. Besides the above theory, the research deals with phenomenological aspects of molecular systems
Zhu, Ming; Liu, Tingting; Zhang, Xiangqun; Li, Caiyun
2018-01-01
Recently, a decomposition method of acoustic relaxation absorption spectra was used to capture the entire molecular multimode relaxation process of gas. In this method, the acoustic attenuation and phase velocity were measured jointly based on the relaxation absorption spectra. However, fast and accurate measurements of the acoustic attenuation remain challenging. In this paper, we present a method of capturing the molecular relaxation process by only measuring acoustic velocity, without the necessity of obtaining acoustic absorption. The method is based on the fact that the frequency-dependent velocity dispersion of a multi-relaxation process in a gas is the serial connection of the dispersions of interior single-relaxation processes. Thus, one can capture the relaxation times and relaxation strengths of N decomposed single-relaxation dispersions to reconstruct the entire multi-relaxation dispersion using the measurements of acoustic velocity at 2N + 1 frequencies. The reconstructed dispersion spectra are in good agreement with experimental data for various gases and mixtures. The simulations also demonstrate the robustness of our reconstructive method.
Generalized extended Navier-Stokes theory: multiscale spin relaxation in molecular fluids.
Hansen, J S
2013-09-01
This paper studies the relaxation of the molecular spin angular velocity in the framework of generalized extended Navier-Stokes theory. Using molecular dynamics simulations, it is shown that for uncharged diatomic molecules the relaxation time decreases with increasing molecular moment of inertia per unit mass. In the regime of large moment of inertia the fast relaxation is wave-vector independent and dominated by the coupling between spin and the fluid streaming velocity, whereas for small inertia the relaxation is slow and spin diffusion plays a significant role. The fast wave-vector-independent relaxation is also observed for highly packed systems. The transverse and longitudinal spin modes have, to a good approximation, identical relaxation, indicating that the longitudinal and transverse spin viscosities have same value. The relaxation is also shown to be isomorphic invariant. Finally, the effect of the coupling in the zero frequency and wave-vector limit is quantified by a characteristic length scale; if the system dimension is comparable to this length the coupling must be included into the fluid dynamical description. It is found that the length scale is independent of moment of inertia but dependent on the state point.
Bayesian energy landscape tilting: towards concordant models of molecular ensembles.
Beauchamp, Kyle A; Pande, Vijay S; Das, Rhiju
2014-03-18
Predicting biological structure has remained challenging for systems such as disordered proteins that take on myriad conformations. Hybrid simulation/experiment strategies have been undermined by difficulties in evaluating errors from computational model inaccuracies and data uncertainties. Building on recent proposals from maximum entropy theory and nonequilibrium thermodynamics, we address these issues through a Bayesian energy landscape tilting (BELT) scheme for computing Bayesian hyperensembles over conformational ensembles. BELT uses Markov chain Monte Carlo to directly sample maximum-entropy conformational ensembles consistent with a set of input experimental observables. To test this framework, we apply BELT to model trialanine, starting from disagreeing simulations with the force fields ff96, ff99, ff99sbnmr-ildn, CHARMM27, and OPLS-AA. BELT incorporation of limited chemical shift and (3)J measurements gives convergent values of the peptide's α, β, and PPII conformational populations in all cases. As a test of predictive power, all five BELT hyperensembles recover set-aside measurements not used in the fitting and report accurate errors, even when starting from highly inaccurate simulations. BELT's principled framework thus enables practical predictions for complex biomolecular systems from discordant simulations and sparse data. Copyright © 2014 Biophysical Society. Published by Elsevier Inc. All rights reserved.
Directory of Open Access Journals (Sweden)
Vizcaíno Sergio F
2004-04-01
Full Text Available Abstract Background Comparative genomic data among organisms allow the reconstruction of their phylogenies and evolutionary time scales. Molecular timings have been recently used to suggest that environmental global change have shaped the evolutionary history of diverse terrestrial organisms. Living xenarthrans (armadillos, anteaters and sloths constitute an ideal model for studying the influence of past environmental changes on species diversification. Indeed, extant xenarthran species are relicts from an evolutionary radiation enhanced by their isolation in South America during the Tertiary era, a period for which major climate variations and tectonic events are relatively well documented. Results We applied a Bayesian approach to three nuclear genes in order to relax the molecular clock assumption while accounting for differences in evolutionary dynamics among genes and incorporating paleontological uncertainties. We obtained a molecular time scale for the evolution of extant xenarthrans and other placental mammals. Divergence time estimates provide substantial evidence for contemporaneous diversification events among independent xenarthran lineages. This correlated pattern of diversification might possibly relate to major environmental changes that occurred in South America during the Cenozoic. Conclusions The observed synchronicity between planetary and biological events suggests that global change played a crucial role in shaping the evolutionary history of extant xenarthrans. Our findings open ways to test this hypothesis further in other South American mammalian endemics like hystricognath rodents, platyrrhine primates, and didelphid marsupials.
Molecular quenching and relaxation in a plasmonic tunable system
Baffou, Guillaume; Girard, Christian; Dujardin, Erik; Colas Des Francs, Gérard; Martin, Olivier J. F.
2008-03-01
Molecular fluorescence decay is significantly modified when the emitting molecule is located near a plasmonic structure. When the lateral sizes of such structures are reduced to nanometer-scale cross sections, they can be used to accurately control and amplify the emission rate. In this Rapid Communication, we extend Green’s dyadic method to quantitatively investigate both radiative and nonradiative decay channels experienced by a single fluorescent molecule confined in an adjustable dielectric-metal nanogap. The technique produces data in excellent agreement with current experimental work.
Relaxation Estimation of RMSD in Molecular Dynamics Immunosimulations
Directory of Open Access Journals (Sweden)
Wolfgang Schreiner
2012-01-01
Full Text Available Molecular dynamics simulations have to be sufficiently long to draw reliable conclusions. However, no method exists to prove that a simulation has converged. We suggest the method of “lagged RMSD-analysis” as a tool to judge if an MD simulation has not yet run long enough. The analysis is based on RMSD values between pairs of configurations separated by variable time intervals Δt. Unless RMSD(Δt has reached a stationary shape, the simulation has not yet converged.
Molecular excitation dynamics and relaxation quantum theory and spectroscopy
Valkunas, Leonas; Mancal, Tomas
2013-01-01
Meeting the need for a work that brings together quantum theory and spectroscopy to convey excitation processes to advanced students and specialists wishing to conduct research and understand the entire field rather than just single aspects.Written by an experienced author and recognized authority in the field, this text covers numerous applications and offers examples taken from different disciplines. As a result, spectroscopists, molecular physicists, physical chemists, and biophysicists will all find this a must-have for their research. Also suitable as supplementary reading in graduate
A study of internal energy relaxation in shocks using molecular dynamics based models
International Nuclear Information System (INIS)
Li, Zheng; Parsons, Neal; Levin, Deborah A.
2015-01-01
Recent potential energy surfaces (PESs) for the N 2 + N and N 2 + N 2 systems are used in molecular dynamics (MD) to simulate rates of vibrational and rotational relaxations for conditions that occur in hypersonic flows. For both chemical systems, it is found that the rotational relaxation number increases with the translational temperature and decreases as the rotational temperature approaches the translational temperature. The vibrational relaxation number is observed to decrease with translational temperature and approaches the rotational relaxation number in the high temperature region. The rotational and vibrational relaxation numbers are generally larger in the N 2 + N 2 system. MD-quasi-classical trajectory (QCT) with the PESs is also used to calculate the V-T transition cross sections, the collision cross section, and the dissociation cross section for each collision pair. Direct simulation Monte Carlo (DSMC) results for hypersonic flow over a blunt body with the total collision cross section from MD/QCT simulations, Larsen-Borgnakke with new relaxation numbers, and the N 2 dissociation rate from MD/QCT show a profile with a decreased translational temperature and a rotational temperature close to vibrational temperature. The results demonstrate that many of the physical models employed in DSMC should be revised as fundamental potential energy surfaces suitable for high temperature conditions become available
A comparison of machine learning and Bayesian modelling for molecular serotyping.
Newton, Richard; Wernisch, Lorenz
2017-08-11
Streptococcus pneumoniae is a human pathogen that is a major cause of infant mortality. Identifying the pneumococcal serotype is an important step in monitoring the impact of vaccines used to protect against disease. Genomic microarrays provide an effective method for molecular serotyping. Previously we developed an empirical Bayesian model for the classification of serotypes from a molecular serotyping array. With only few samples available, a model driven approach was the only option. In the meanwhile, several thousand samples have been made available to us, providing an opportunity to investigate serotype classification by machine learning methods, which could complement the Bayesian model. We compare the performance of the original Bayesian model with two machine learning algorithms: Gradient Boosting Machines and Random Forests. We present our results as an example of a generic strategy whereby a preliminary probabilistic model is complemented or replaced by a machine learning classifier once enough data are available. Despite the availability of thousands of serotyping arrays, a problem encountered when applying machine learning methods is the lack of training data containing mixtures of serotypes; due to the large number of possible combinations. Most of the available training data comprises samples with only a single serotype. To overcome the lack of training data we implemented an iterative analysis, creating artificial training data of serotype mixtures by combining raw data from single serotype arrays. With the enhanced training set the machine learning algorithms out perform the original Bayesian model. However, for serotypes currently lacking sufficient training data the best performing implementation was a combination of the results of the Bayesian Model and the Gradient Boosting Machine. As well as being an effective method for classifying biological data, machine learning can also be used as an efficient method for revealing subtle biological
Narimani, Zahra; Beigy, Hamid; Ahmad, Ashar; Masoudi-Nejad, Ali; Fröhlich, Holger
2017-01-01
Inferring the structure of molecular networks from time series protein or gene expression data provides valuable information about the complex biological processes of the cell. Causal network structure inference has been approached using different methods in the past. Most causal network inference techniques, such as Dynamic Bayesian Networks and ordinary differential equations, are limited by their computational complexity and thus make large scale inference infeasible. This is specifically true if a Bayesian framework is applied in order to deal with the unavoidable uncertainty about the correct model. We devise a novel Bayesian network reverse engineering approach using ordinary differential equations with the ability to include non-linearity. Besides modeling arbitrary, possibly combinatorial and time dependent perturbations with unknown targets, one of our main contributions is the use of Expectation Propagation, an algorithm for approximate Bayesian inference over large scale network structures in short computation time. We further explore the possibility of integrating prior knowledge into network inference. We evaluate the proposed model on DREAM4 and DREAM8 data and find it competitive against several state-of-the-art existing network inference methods.
Inhomogeneous Relaxation of a Molecular Layer on an Insulator due to Compressive Stress
Bocquet, F.; Nony, L.; Mannsfeld, S. C. B.; Oison, V.; Pawlak, R.; Porte, L.; Loppacher, Ch.
2012-05-01
We discuss the inhomogeneous stress relaxation of a monolayer of hexahydroxytriphenylene (HHTP) which adopts the rare line-on-line (LOL) coincidence on KCl(001) and forms moiré patterns. The fact that the hexagonal HHTP layer is uniaxially compressed along the LOL makes this system an ideal candidate to discuss the influence of inhomogeneous stress relaxation. Our work is a combination of noncontact atomic force microscopy experiments, density functional theory and potential energy calculations, and a thorough interpretation by means of the Frenkel-Kontorova model. We show that the assumption of a homogeneous molecular layer is not valid for this organic-inorganic heteroepitaxial system since the best calculated energy configuration correlates with the experimental data only if inhomogeneous relaxations of the layer are taken into account.
Bayesian molecular design with a chemical language model
Ikebata, Hisaki; Hongo, Kenta; Isomura, Tetsu; Maezono, Ryo; Yoshida, Ryo
2017-04-01
The aim of computational molecular design is the identification of promising hypothetical molecules with a predefined set of desired properties. We address the issue of accelerating the material discovery with state-of-the-art machine learning techniques. The method involves two different types of prediction; the forward and backward predictions. The objective of the forward prediction is to create a set of machine learning models on various properties of a given molecule. Inverting the trained forward models through Bayes' law, we derive a posterior distribution for the backward prediction, which is conditioned by a desired property requirement. Exploring high-probability regions of the posterior with a sequential Monte Carlo technique, molecules that exhibit the desired properties can computationally be created. One major difficulty in the computational creation of molecules is the exclusion of the occurrence of chemically unfavorable structures. To circumvent this issue, we derive a chemical language model that acquires commonly occurring patterns of chemical fragments through natural language processing of ASCII strings of existing compounds, which follow the SMILES chemical language notation. In the backward prediction, the trained language model is used to refine chemical strings such that the properties of the resulting structures fall within the desired property region while chemically unfavorable structures are successfully removed. The present method is demonstrated through the design of small organic molecules with the property requirements on HOMO-LUMO gap and internal energy. The R package iqspr is available at the CRAN repository.
Effect of holographic grating period on its relaxation in a molecular glassy film
International Nuclear Information System (INIS)
Ozols, A; Augustovs, P; Kokars, V; Traskovskis, K; Saharov, D
2013-01-01
Holographic grating (HG) relaxation has been experimentally studied in 5,5,5-triphenylpentyl 4-((4-(bis(5,5,5-triphenylpentyl)amino) phenyl) diazenyl) benzoate molecular glassy film for HG periods (Λ) of 0.50, 2.0 and 8.6 μm. A strong effect of HG period on its relaxation is found manifesting itself differently in the volume and on the surface. The volume part of HG is fairly stable during 40 days if Λ > 0.50μm whereas the surface part of HG (most probably, surface relief grating) exhibits relaxational self-enhancement which is maximal at Λ = 8.6μm. It is proposed that thermostimulated directional mass transfer in the process of relaxation can be responsible for this relaxational self-enhancement. Weak HG recording and relatively fast HG decay takes place at Λ=0.50 μm. Therefore, effective chromophore photoorientation domain of about 0.2 μm is supposed
Dynamics of relaxation to a stationary state for interacting molecular motors
Gomes, Luiza V. F.; Kolomeisky, Anatoly B.
2018-01-01
Motor proteins are active enzymatic molecules that drive a variety of biological processes, including transfer of genetic information, cellular transport, cell motility and muscle contraction. It is known that these biological molecular motors usually perform their cellular tasks by acting collectively, and there are interactions between individual motors that specify the overall collective behavior. One of the fundamental issues related to the collective dynamics of motor proteins is the question if they function at stationary-state conditions. To investigate this problem, we analyze a relaxation to the stationary state for the system of interacting molecular motors. Our approach utilizes a recently developed theoretical framework, which views the collective dynamics of motor proteins as a totally asymmetric simple exclusion process of interacting particles, where interactions are taken into account via a thermodynamically consistent approach. The dynamics of relaxation to the stationary state is analyzed using a domain-wall method that relies on a mean-field description, which takes into account some correlations. It is found that the system quickly relaxes for repulsive interactions, while attractive interactions always slow down reaching the stationary state. It is also predicted that for some range of parameters the fastest relaxation might be achieved for a weak repulsive interaction. Our theoretical predictions are tested with Monte Carlo computer simulations. The implications of our findings for biological systems are briefly discussed.
Vibrational relaxation of a triatomic molecular impurity: D2O in vitreous As2S3
International Nuclear Information System (INIS)
Rella, C.W.; Schwettman, H.A.; Engholm, J.R.
1995-01-01
Measurements of the relaxation of the D 2 O stretch mode in vitreous As 2 S 3 are presented. Because the bending mode of the molecule offers an intra-molecular decay channel for the stretch mode, the decay scheme of the D 2 O molecule is more complex than that of diatomic molecules. The asymmetric stretch mode of D 2 O has a frequency of 2680 cm -1 . To study the relaxation of this mode we applied a pump-probe technique, using intense psec; pulses of the Stanford Free Electron Laser. Due to the small cross-section of the vibrational mode, successful efforts were made to improve the signal to noise ratio by using a laser stabilization system and a tightly focused beam to increase the intensity, by averaging the signal with a kHz repetition rate and by using samples with an optimized D 2 O concentration. A rapid relaxation rate on the order of 5 x 10 9 sec -1 at low temperature is found that increases with temperature. Recalling that the bending mode of the D 2 O molecule has a frequency of 1170 cm -1 , one would expect a decay in a third order process, involving two quanta of the bending mode plus a vibrational host quanta with a frequency of 340 cm -1 , which coincides with a fundamental frequency of the pyramidal building blocks of the glassy As 2 S 3 host. Instead, we find from the temperature dependence of the relaxation rate that the D 2 O stretching mode relaxes in a higher order process. This indicates that the relaxation dynamics of small molecules is more complex than generally assumed
Fuson, Michael M.
2017-01-01
Laboratories studying the anisotropic rotational diffusion of bromobenzene using nuclear spin relaxation and molecular dynamics simulations are described. For many undergraduates, visualizing molecular motion is challenging. Undergraduates rarely encounter laboratories that directly assess molecular motion, and so the concept remains an…
Molecular motion of micellar solutes: a 13C NMR relaxation study
International Nuclear Information System (INIS)
Stark, R.E.; Kasakevich, M.L.; Granger, J.W.
1982-01-01
A series of simple NMR relaxation experiments have been performed on nitrobenzene and aniline dissolved in the ionic detergents sodium dodecyl sulfate (SDS) and hexadecyltrimethylammonium bromide (CTAB). Using 13 C relaxation rates at various molecular sites, and comparing data obtained in organic media with those for micellar solutions, the viscosity at the solubilization site was estimated and a detailed picture of motional restrictions imposed by the micellar enviroment was derived. Viscosities of 8 to 17 cp indicate a rather fluid environment for solubilized nitrobenzene; both additives exhibit altered motional preferences in CTAB solutions only. As an aid in interpretation of the NMR data, quasi-elastic light scattering and other physical techniques have been used to evaluate the influence of organic solutes on micellar size and shape. The NMR methods are examined critically in terms of their general usefulness for studies of solubilization in detergent micelles. 48 references
Water interactions with varying molecular states of bovine casein: 2H NMR relaxation studies
International Nuclear Information System (INIS)
Kumosinski, T.F.; Pessen, H.; Prestrelski, S.J.; Farrell, H.M. Jr.
1987-01-01
The caseins occur in milk as spherical colloidal complexes of protein and salts with an average diameter of 1200 A, the casein micelles. Removal of Ca2+ is thought to result in their dissociation into smaller protein complexes stabilized by hydrophobic interactions and called submicelles. Whether these submicelles actually occur within the micelles as discrete particles interconnected by calcium phosphate salt bridges has been the subject of much controversy. A variety of physical measurements have shown that casein micelles contain an inordinately high amount of trapped water (2 to 7 g H 2 O/g protein). With this in mind it was of interest to determine if NMR relaxation measurements could detect the presence of this trapped water within the micelles, and to evaluate whether it is a continuum with picosecond correlation times or is associated in part with discrete submicellar structures with nanosecond motions. For this purpose the variations in 2 H NMR longitudinal and transverse relaxation rates of water with protein concentration were determined for bovine casein at various temperatures, under both submicellar and micellar conditions. D 2 O was used instead of H 2 O to eliminate cross-relaxation effects. From the protein concentration dependence of the relaxation rates, the second virial coefficient of the protein was obtained by nonlinear regression analysis. Using either an isotropic tumbling or an intermediate asymmetry model, degrees of hydration, v, and correlation times, tau c, were calculated for the caseins; from the latter parameter the Stokes radius, r, was obtained. Next, estimates of molecular weights were obtained from r and the partial specific volume. Values were in the range of those published from other methodologies for the submicelles
Simple molecular mechanism of heat transfer: Debye relaxation versus power-law
International Nuclear Information System (INIS)
Gall, M.; Kutner, R.
2005-01-01
We study a simple molecular model (at coarse-grain level) as a basis of irreversible heat transfer through a diathermic partition. The partition separates into two adjacent parts a box containing ideal point particles that communicate only though this partition. We provide the basic mechanism of energy transfer between the left- and right-hand side gas samples by assuming equipartition of kinetic energy of all outgoing particles colliding with the partition at a given time. We analyse and compare two essentially different cases (A) the reference one, where we assume that the border walls of the box and the diathermic partitions can randomize the direction of motion of rebounding particles, and (B) the case where we assume the mirror collisions of particles with the border walls and the partition. In both cases the rebounding of the particles from border walls is elastic. The above introduced assumptions allow us to numerically simulate and analytically consider, for example, the relaxation of temperatures of both gas samples and the entropy of the system. However, in both cases the long-time relaxation is essentially different since in case (A) it is an exponential one, while in case (B) it seems to be a power-law relaxation. The obtained results well agree in case (A) with the predictions of the phenomenological, linear theory of irreversible theory had to be developed which assumes time-dependence of heat conductivity; it describes the relaxation of the system far from equilibrium. The explanation of the results obtained in this case is, nevertheless, an intriguing problem. (author)
DEFF Research Database (Denmark)
Roed, Lisa Anita; Niss, Kristine; Jakobsen, Bo
2015-01-01
The frequency dependent specific heat has been measured under pressure for the molecular glass forming liquid 5-polyphenyl-4-ether in the viscous regime close to the glass transition. The temperature and pressure dependences of the characteristic time scale associated with the specific heat...... is compared to the equivalent time scale from dielectric spectroscopy performed under identical conditions. It is shown that the ratio between the two time scales is independent of both temperature and pressure. This observation is non-trivial and demonstrates the existence of specially simple molecular...... liquids in which different physical relaxation processes are both as function of temperature and pressure/density governed by the same underlying “inner clock.” Furthermore, the results are discussed in terms of the recent conjecture that van der Waals liquids, like the measuredliquid, comply...
Arosio, Paolo; Corti, Maurizio; Mariani, Manuel; Orsini, Francesco; Bogani, Lapo; Caneschi, Andrea; Lago, Jorge; Lascialfari, Alessandro
2015-05-01
The spin dynamics of the molecular magnetic chain [Dy(hfac)3{NIT(C6H4OPh)}] were investigated by means of the Muon Spin Relaxation (μ+SR) technique. This system consists of a magnetic lattice of alternating Dy(III) ions and radical spins, and exhibits single-chain-magnet behavior. The magnetic properties of [Dy(hfac)3{NIT(C6H4OPh)}] have been studied by measuring the magnetization vs. temperature at different applied magnetic fields (H = 5, 3500, and 16500 Oe) and by performing μ+SR experiments vs. temperature in zero field and in a longitudinal applied magnetic field H = 3500 Oe. The muon asymmetry P(t) was fitted by the sum of three components, two stretched-exponential decays with fast and intermediate relaxation times, and a third slow exponential decay. The temperature dependence of the spin dynamics has been determined by analyzing the muon longitudinal relaxation rate λinterm(T), associated with the intermediate relaxing component. The experimental λinterm(T) data were fitted with a corrected phenomenological Bloembergen-Purcell-Pound law by using a distribution of thermally activated correlation times, which average to τ = τ0 exp(Δ/kBT), corresponding to a distribution of energy barriers Δ. The correlation times can be associated with the spin freezing that occurs when the system condenses in the ground state.
International Nuclear Information System (INIS)
Arosio, Paolo; Orsini, Francesco; Corti, Maurizio; Mariani, Manuel; Bogani, Lapo; Caneschi, Andrea; Lago, Jorge; Lascialfari, Alessandro
2015-01-01
The spin dynamics of the molecular magnetic chain [Dy(hfac) 3 (NIT(C 6 H 4 OPh))] were investigated by means of the Muon Spin Relaxation (μ + SR) technique. This system consists of a magnetic lattice of alternating Dy(III) ions and radical spins, and exhibits single-chain-magnet behavior. The magnetic properties of [Dy(hfac) 3 (NIT(C 6 H 4 OPh))] have been studied by measuring the magnetization vs. temperature at different applied magnetic fields (H = 5, 3500, and 16500 Oe) and by performing μ + SR experiments vs. temperature in zero field and in a longitudinal applied magnetic field H = 3500 Oe. The muon asymmetry P(t) was fitted by the sum of three components, two stretched-exponential decays with fast and intermediate relaxation times, and a third slow exponential decay. The temperature dependence of the spin dynamics has been determined by analyzing the muon longitudinal relaxation rate λ interm (T), associated with the intermediate relaxing component. The experimental λ interm (T) data were fitted with a corrected phenomenological Bloembergen-Purcell-Pound law by using a distribution of thermally activated correlation times, which average to τ = τ 0 exp(Δ/k B T), corresponding to a distribution of energy barriers Δ. The correlation times can be associated with the spin freezing that occurs when the system condenses in the ground state
Sills, Scott; Gray, Tomoko; Overney, René M
2005-10-01
Nanoscale sliding friction involving a polystyrene melt near its glass transition temperature Tg (373 K) exhibited dissipation phenomena that provide insight into the underlying molecular relaxation processes. A dissipative length scale that shows significant parallelism with the size of cooperatively rearranging regions (CRRs) could be experimentally deduced from friction-velocity isotherms, combined with dielectric loss analysis. Upon cooling to approximately 10 K above Tg, the dissipation length Xd grew from a segmental scale of approximately 3 A to 2.1 nm, following a power-law relationship with the reduced temperature Xd approximately TR-phi. The resulting phi=1.89+/-0.08 is consistent with growth predictions for the length scale of CRRs in the heterogeneous regime of fragile glass formers. Deviations from the power-law behavior closer to Tg suggest that long-range processes, e.g., the normal mode or ultraslow Fischer modes, may couple with the alpha relaxation, leading to energy dissipation in domains of tens of nanometers.
Energy Technology Data Exchange (ETDEWEB)
Tacke, Christian
2015-07-01
Multi spin systems with spin 1/2 nuclei and dipolar coupled quadrupolar nuclei can show so called ''quadrupolar dips''. There are two main reasons for this behavior: polarization transfer and relaxation. They look quite alike and without additional research cannot be differentiated easily in most cases. These two phenomena have quite different physical and theoretical backgrounds. For no or very slow dynamics, polarization transfer will take place, which is energy conserving inside the spin system. This effect can entirely be described using quantum mechanics on the spin system. Detailed knowledge about the crystallography is needed, because this affects the relevant hamiltonians directly. For systems with fast enough dynamics, relaxation takes over, and the energy flows from the spin system to the lattice; thus a more complex theoretical description is needed. This description has to include a dynamic model, usually in the form of a spectral density function. Both models should include detailed modelling of the complete spin system. A software library was developed to be able to model complex spin systems. It allows to simulate polarization transfer or relaxation effects. NMR measurements were performed on the protonic conductor K{sub 3}H(SO{sub 4}){sub 2}. A single crystal shows sharp quadrupolar dips at room temperature. Dynamics could be excluded using relaxation measurements and literature values. Thus, a polarization transfer analysis was used to describe those dips with good agreement. As a second system, imidazolium based molecular crystals were analyzed. The quadrupolar dips were expected to be caused by polarization transfer; this was carefully analyzed and found not to be true. A relaxation based analysis shows good agreement with the measured data in the high temperature area. It leverages a two step spectral density function, which indicates two distinct dynamic processes happening in this system.
Rational extended thermodynamics of a rarefied polyatomic gas with molecular relaxation processes
Arima, Takashi; Ruggeri, Tommaso; Sugiyama, Masaru
2017-10-01
We present a more refined version of rational extended thermodynamics of rarefied polyatomic gases in which molecular rotational and vibrational relaxation processes are treated individually. In this case, we need a triple hierarchy of the moment system and the system of balance equations is closed via the maximum entropy principle. Three different types of the production terms in the system, which are suggested by a generalized BGK-type collision term in the Boltzmann equation, are adopted. In particular, the rational extended thermodynamic theory with seven independent fields (ET7) is analyzed in detail. Finally, the dispersion relation of ultrasonic wave derived from the ET7 theory is confirmed by the experimental data for CO2, Cl2, and Br2 gases.
Directory of Open Access Journals (Sweden)
Paulino Pérez
2010-09-01
Full Text Available The availability of dense molecular markers has made possible the use of genomic selection in plant and animal breeding. However, models for genomic selection pose several computational and statistical challenges and require specialized computer programs, not always available to the end user and not implemented in standard statistical software yet. The R-package BLR (Bayesian Linear Regression implements several statistical procedures (e.g., Bayesian Ridge Regression, Bayesian LASSO in a unified framework that allows including marker genotypes and pedigree data jointly. This article describes the classes of models implemented in the BLR package and illustrates their use through examples. Some challenges faced when applying genomic-enabled selection, such as model choice, evaluation of predictive ability through cross-validation, and choice of hyper-parameters, are also addressed.
Dielectric relaxation spectra of liquid crystals in relation to molecular structure
International Nuclear Information System (INIS)
Wrobel, S.
1986-07-01
The dielectric spectra obtained for some members of two homologous series, i.e. for di-alkoxyazoxybenzenes and penthyl-alkoxythiobenzoates, are discussed qualitatively on the basis of the Nordio-Rigatti-Segre diffusion model. It is additionally assumed that the molecular reorientations take place about the principal axes of the inertia tensor. The distribution of correlation times, which is strongly temperature dependent in the vicinity of the clearing point, is interpreted as being caused by fluctuations of the principal axes frame which are due to conformation changes inside the end chains. The Bauer equation is used to describe both principal molecular reorientations, i.e. the reorientations about the long and short axis, observed in liquid crystalline structure by means of dielectric relaxation methods. The energies and entropies of activation have been computed for both principal reorientations. The differences between the high frequency limit of the dielectric permittivity and the refractive index squared of liquid crystals are explained in terms of two librational motions of the molecules observed by other experimental techniques, viz. far infra-red, Raman and inelastic neutron scattering spectroscopies, and found in this work on the basis of dielectrically measured energy barriers. It has been shown qualitatively that intramolecular libratory motions greatly effect the high frequency dielectric spectrum. Finally, molecular motions in liquid crystals are divided into two types: coherent and incoherent. 127 refs., 56 figs., 17 tabs. (author)
Rapid molecular evolution of human bocavirus revealed by Bayesian coalescent inference.
Zehender, Gianguglielmo; De Maddalena, Chiara; Canuti, Marta; Zappa, Alessandra; Amendola, Antonella; Lai, Alessia; Galli, Massimo; Tanzi, Elisabetta
2010-03-01
Human bocavirus (HBoV) is a linear single-stranded DNA virus belonging to the Parvoviridae family that has recently been isolated from the upper respiratory tract of children with acute respiratory infection. All of the strains observed so far segregate into two genotypes (1 and 2) with a low level of polymorphism. Given the recent description of the infection and the lack of epidemiological and molecular data, we estimated the virus's rates of molecular evolution and population dynamics. A dataset of forty-nine dated VP2 sequences, including also eight new isolates obtained from pharyngeal swabs of Italian patients with acute respiratory tract infections, was submitted to phylogenetic analysis. The model parameters, evolutionary rates and population dynamics were co-estimated using a Bayesian Markov Chain Monte Carlo approach, and site-specific positive and negative selection was also investigated. Recombination was investigated by seven different methods and one suspected recombinant strain was excluded from further analysis. The estimated mean evolutionary rate of HBoV was 8.6x10(-4)subs/site/year, and that of the 1st+2nd codon positions was more than 15 times less than that of the 3rd codon position. Viral population dynamics analysis revealed that the two known genotypes diverged recently (mean tMRCA: 24 years), and that the epidemic due to HBoV genotype 2 grew exponentially at a rate of 1.01year(-1). Selection analysis of the partial VP2 showed that 8.5% of sites were under significant negative pressure and the absence of positive selection. Our results show that, like other parvoviruses, HBoV is characterised by a rapid evolution. The low level of polymorphism is probably due to a relatively recent divergence between the circulating genotypes and strong purifying selection acting on viral antigens.
Energy Technology Data Exchange (ETDEWEB)
Xie, Wen Jun; Yang, Yi Isaac; Gao, Yi Qin, E-mail: gaoyq@pku.edu.cn [Institute of Theoretical and Computational Chemistry, College of Chemistry and Molecular Engineering and Biodynamic Optical Imaging Center, Peking University, Beijing 100871 (China)
2015-12-14
In this study, we examine how complex ions such as oxyanions influence the dynamic properties of water and whether differences exist between simple halide anions and oxyanions. Nitrate anion is taken as an example to investigate the hydration properties of oxyanions. Reorientation relaxation of its hydration water can occur through two different routes: water can either break its hydrogen bond with the nitrate to form one with another water or switch between two oxygen atoms of the same nitrate. The latter molecular mechanism increases the residence time of oxyanion’s hydration water and thus nitrate anion slows down the translational motion of neighbouring water. But it is also a “structure breaker” in that it accelerates the reorientation relaxation of hydration water. Such a result illustrates that differences do exist between the hydration of oxyanions and simple halide anions as a result of different molecular geometries. Furthermore, the rotation of the nitrate solute is coupled with the hydrogen bond rearrangement of its hydration water. The nitrate anion can either tilt along the axis perpendicularly to the plane or rotate in the plane. We find that the two reorientation relaxation routes of the hydration water lead to different relaxation dynamics in each of the two above movements of the nitrate solute. The current study suggests that molecular geometry could play an important role in solute hydration and dynamics.
International Nuclear Information System (INIS)
Xie, Wen Jun; Yang, Yi Isaac; Gao, Yi Qin
2015-01-01
In this study, we examine how complex ions such as oxyanions influence the dynamic properties of water and whether differences exist between simple halide anions and oxyanions. Nitrate anion is taken as an example to investigate the hydration properties of oxyanions. Reorientation relaxation of its hydration water can occur through two different routes: water can either break its hydrogen bond with the nitrate to form one with another water or switch between two oxygen atoms of the same nitrate. The latter molecular mechanism increases the residence time of oxyanion’s hydration water and thus nitrate anion slows down the translational motion of neighbouring water. But it is also a “structure breaker” in that it accelerates the reorientation relaxation of hydration water. Such a result illustrates that differences do exist between the hydration of oxyanions and simple halide anions as a result of different molecular geometries. Furthermore, the rotation of the nitrate solute is coupled with the hydrogen bond rearrangement of its hydration water. The nitrate anion can either tilt along the axis perpendicularly to the plane or rotate in the plane. We find that the two reorientation relaxation routes of the hydration water lead to different relaxation dynamics in each of the two above movements of the nitrate solute. The current study suggests that molecular geometry could play an important role in solute hydration and dynamics
Vogt, Martin; Bajorath, Jürgen
2008-01-01
Bayesian classifiers are increasingly being used to distinguish active from inactive compounds and search large databases for novel active molecules. We introduce an approach to directly combine the contributions of property descriptors and molecular fingerprints in the search for active compounds that is based on a Bayesian framework. Conventionally, property descriptors and fingerprints are used as alternative features for virtual screening methods. Following the approach introduced here, probability distributions of descriptor values and fingerprint bit settings are calculated for active and database molecules and the divergence between the resulting combined distributions is determined as a measure of biological activity. In test calculations on a large number of compound activity classes, this methodology was found to consistently perform better than similarity searching using fingerprints and multiple reference compounds or Bayesian screening calculations using probability distributions calculated only from property descriptors. These findings demonstrate that there is considerable synergy between different types of property descriptors and fingerprints in recognizing diverse structure-activity relationships, at least in the context of Bayesian modeling.
Rotational dynamics in supercooled water from nuclear spin relaxation and molecular simulations.
Qvist, Johan; Mattea, Carlos; Sunde, Erik P; Halle, Bertil
2012-05-28
Structural dynamics in liquid water slow down dramatically in the supercooled regime. To shed further light on the origin of this super-Arrhenius temperature dependence, we report high-precision (17)O and (2)H NMR relaxation data for H(2)O and D(2)O, respectively, down to 37 K below the equilibrium freezing point. With the aid of molecular dynamics (MD) simulations, we provide a detailed analysis of the rotational motions probed by the NMR experiments. The NMR-derived rotational correlation time τ(R) is the integral of a time correlation function (TCF) that, after a subpicosecond librational decay, can be described as a sum of two exponentials. Using a coarse-graining algorithm to map the MD trajectory on a continuous-time random walk (CTRW) in angular space, we show that the slowest TCF component can be attributed to large-angle molecular jumps. The mean jump angle is ∼48° at all temperatures and the waiting time distribution is non-exponential, implying dynamical heterogeneity. We have previously used an analogous CTRW model to analyze quasielastic neutron scattering data from supercooled water. Although the translational and rotational waiting times are of similar magnitude, most translational jumps are not synchronized with a rotational jump of the same molecule. The rotational waiting time has a stronger temperature dependence than the translation one, consistent with the strong increase of the experimentally derived product τ(R) D(T) at low temperatures. The present CTRW jump model is related to, but differs in essential ways from the extended jump model proposed by Laage and co-workers. Our analysis traces the super-Arrhenius temperature dependence of τ(R) to the rotational waiting time. We present arguments against interpreting this temperature dependence in terms of mode-coupling theory or in terms of mixture models of water structure.
Critical thickness and strain relaxation in molecular beam epitaxy-grown SrTiO3 films
International Nuclear Information System (INIS)
Wang, Tianqi; Ganguly, Koustav; Marshall, Patrick; Xu, Peng; Jalan, Bharat
2013-01-01
We report on the study of the critical thickness and the strain relaxation in epitaxial SrTiO 3 film grown on (La 0.3 Sr 0.7 )(Al 0.65 Ta 0.35 )O 3 (001) (LSAT) substrate using the hybrid molecular beam epitaxy approach. No change in the film's lattice parameter (both the in-plane and the out-of-plane) was observed up to a film thickness of 180 nm, which is in sharp contrast to the theoretical critical thickness of ∼12 nm calculated using the equilibrium theory of strain relaxation. For film thicknesses greater than 180 nm, the out-of-plane lattice parameter was found to decrease hyperbolically in an excellent agreement with the relaxation via forming misfit dislocations. Possible mechanisms are discussed by which the elastic strain energy can be accommodated prior to forming misfit dislocations leading to such anomalously large critical thickness
International Nuclear Information System (INIS)
Perly, Bruno
1980-01-01
The objective of this research thesis is to study local conformations and mobilities of some typical homo-polypeptides by using techniques of magnetic resonance. By using these techniques, it is possible to make highly local observations of molecular elements which allows very efficient analysis of structural and dynamic properties of several biologically important compounds to be performed, and the study of their interactions. After a presentation of the general properties of the studied polypeptides, of magnetic resonance and of magnetic relaxation, the author presents some elements of macromolecular dynamics and movement models. Then, he reports the study of local conformations and structural transitions, applications of spin marking to the dynamic study of polypeptides, a dynamic study of the polypeptide skeleton under the form of statistic balls, the study of local movements of side chains by using nuclear relaxation, the study of the coupling of movements of main and side chains, and of the nuclear relaxation induced by a radical spin marker
Vibronic relaxation in molecular mixed crystals : Pentacene in naphthalene and p-terphenyl
Hesselink, Wim H.; Wiersma, Douwe A.
1981-01-01
Picosecond photon echo techniques are used to measure directly vibronic relaxation times in the first excited singlet state of pentacene in naphthalene and p-terphenyl. In regions of low (< 300 cm–1) and high (> 1000 cm–1) vibrational energy, relaxation is fast (τ <2 ps) due to direct phonon
Barba-Montoya, Jose; Dos Reis, Mario; Yang, Ziheng
2017-09-01
Fossil calibrations are the utmost source of information for resolving the distances between molecular sequences into estimates of absolute times and absolute rates in molecular clock dating analysis. The quality of calibrations is thus expected to have a major impact on divergence time estimates even if a huge amount of molecular data is available. In Bayesian molecular clock dating, fossil calibration information is incorporated in the analysis through the prior on divergence times (the time prior). Here, we evaluate three strategies for converting fossil calibrations (in the form of minimum- and maximum-age bounds) into the prior on times, which differ according to whether they borrow information from the maximum age of ancestral nodes and minimum age of descendent nodes to form constraints for any given node on the phylogeny. We study a simple example that is analytically tractable, and analyze two real datasets (one of 10 primate species and another of 48 seed plant species) using three Bayesian dating programs: MCMCTree, MrBayes and BEAST2. We examine how different calibration strategies, the birth-death process, and automatic truncation (to enforce the constraint that ancestral nodes are older than descendent nodes) interact to determine the time prior. In general, truncation has a great impact on calibrations so that the effective priors on the calibration node ages after the truncation can be very different from the user-specified calibration densities. The different strategies for generating the effective prior also had considerable impact, leading to very different marginal effective priors. Arbitrary parameters used to implement minimum-bound calibrations were found to have a strong impact upon the prior and posterior of the divergence times. Our results highlight the importance of inspecting the joint time prior used by the dating program before any Bayesian dating analysis. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.
Bayesian ensemble refinement by replica simulations and reweighting
Hummer, Gerhard; Köfinger, Jürgen
2015-12-01
We describe different Bayesian ensemble refinement methods, examine their interrelation, and discuss their practical application. With ensemble refinement, the properties of dynamic and partially disordered (bio)molecular structures can be characterized by integrating a wide range of experimental data, including measurements of ensemble-averaged observables. We start from a Bayesian formulation in which the posterior is a functional that ranks different configuration space distributions. By maximizing this posterior, we derive an optimal Bayesian ensemble distribution. For discrete configurations, this optimal distribution is identical to that obtained by the maximum entropy "ensemble refinement of SAXS" (EROS) formulation. Bayesian replica ensemble refinement enhances the sampling of relevant configurations by imposing restraints on averages of observables in coupled replica molecular dynamics simulations. We show that the strength of the restraints should scale linearly with the number of replicas to ensure convergence to the optimal Bayesian result in the limit of infinitely many replicas. In the "Bayesian inference of ensembles" method, we combine the replica and EROS approaches to accelerate the convergence. An adaptive algorithm can be used to sample directly from the optimal ensemble, without replicas. We discuss the incorporation of single-molecule measurements and dynamic observables such as relaxation parameters. The theoretical analysis of different Bayesian ensemble refinement approaches provides a basis for practical applications and a starting point for further investigations.
Fröhlich, H.; Klau, G.W.
2013-01-01
Bayesian Networks are an established computational approach for data driven network inference. However, experimental data is limited in its availability and corrupted by noise. This leads to an unavoidable uncertainty about the correct network structure. Thus sampling or bootstrap based strategies
Shete, Ganesh; Khomane, Kailas S; Bansal, Arvind Kumar
2014-01-01
The purpose of this paper was to investigate the relaxation behavior of amorphous hesperetin (HRN), using dielectric spectroscopy, and assessment of its crystallization kinetics above glass transition temperature (Tg ). Amorphous HRN exhibited both local (β-) and global (α-) relaxations. β-Relaxation was observed below Tg , whereas α-relaxation prominently emerged above Tg . β-Relaxation was found to be of Johari-Goldstein type and was correlated with α-process by coupling model. Secondly, isothermal crystallization experiments were performed at 363 K (Tg + 16.5 K), 373 K (Tg + 26.5 K), and 383 K (Tg + 36.5 K). The kinetics of crystallization, obtained from the normalized dielectric strength, was modeled using the Avrami model. Havriliak-Negami (HN) shape parameters, αHN and αHN .βHN , were analyzed during the course of crystallization to understand the dynamics of amorphous phase during the emergence of crystallites. HN shape parameters indicated that long range (α-like) were motions affected to a greater extent than short range (β-like) motions during isothermal crystallization studies at all temperature conditions. The variable behavior of α-like motions at different isothermal crystallization temperatures was attributed to evolving crystallites with time and increase in electrical conductivity with temperature. © 2013 Wiley Periodicals, Inc. and the American Pharmacists Association.
Lattice Distortion Mediated Paramagnetic Relaxation in High-Spin High-Symmetry Molecular Magnets
Garg, Anupam
1998-08-01
Field-dependent maxima in the relaxation rate of the magnetic molecules Mn12-Ac and Fe8-tacn have commonly been ascribed to some resonant tunneling phenomena. We argue instead that the relaxation is purely due to phonons. The rate maxima arise because of a Jahn-Teller-like distortion caused by the coupling of phonons to degenerate Zeeman levels of the molecule at the top of the barrier. The binding energy of the distorted intermediate states lowers the barrier height and increases the relaxation rate. A nonperturbative calculation of this effect is carried out for a model system. An approximate result for the field variation near a maximum is found to agree reasonably with experiment.
Molecular theory for nuclear magnetic relaxation in protein solutions and tissue
International Nuclear Information System (INIS)
Kimmich, R.; Nusser, W.; Gneiting, T.
1990-01-01
A model theory is presented explaining a series of striking phenomena observed with nuclear magnetic relaxation in protein systems such as solutions or tissue. The frequency, concentration and temperature dependences of proton or deuteron relaxation times of protein solutions and tissue are explained. It is concluded that the translational diffusion of water molecules along the rugged surfaces of proteins and, to a minor degree, protein backbone fluctuations are crucial processes. The rate limiting factor of macromolecular tumbling is assumed to be given by the free water content in a certain analogy to the free-volume model of Cohen ad Turnbull. There are two characteristic water mass fractions indicating the saturation of the hydration shells and the onset of protein tumbling. A closed and relatively simple set of relaxation formulas is presented. The potentially fractal nature of the diffusion of water molecules on the protein surface is discussed. (author). 43 refs.; 4 figs
International Nuclear Information System (INIS)
Nakano, Masayoshi; Kishi, Ryohei; Nitta, Tomoshige; Yamaguchi, Kizashi
2004-01-01
We investigate the relaxation effects on the quantum dynamics in a two-state molecular system interacting with a single-mode strongly amplitude-squeezed coherent field using the second-order Monte Carlo wave-function method. The molecular population inversion (collapse-revival behavior of Rabi oscillations) is known to show the echoes after each revival, which are referred to as ringing revivals, in the case of strongly squeezed coherent fields with oscillatory photon-number distributions due to the phase-space interference effect. Two types of relaxation effects, i.e., cavity relaxation (the dissipation of an internal single mode to outer mode) and molecular coherent (phase) relaxation caused by nuclear vibrations on ringing revivals are investigated from the viewpoint of the quantum-phase dynamics using the quasiprobability (Q function) distribution of a single-mode field and the off-diagonal molecular density matrix ρ elec1,2 (t). It turns out that the molecular phase relaxation attenuates both the entire revival-collapse behavior and the increase in ρ elec1,2 (t) during the quiescent region, whereas a very slight cavity relaxation particularly suppresses the echoes in ringing revivals more significantly than the first revival but hardly changes a primary variation in envelope of ρ elec1,2 (t) in the nonrelaxation case
Zhao, Yinjian
2017-09-01
Aiming at a high simulation accuracy, a Particle-Particle (PP) Coulombic molecular dynamics model is implemented to study the electron-ion temperature relaxation. In this model, the Coulomb's law is directly applied in a bounded system with two cutoffs at both short and long length scales. By increasing the range between the two cutoffs, it is found that the relaxation rate deviates from the BPS theory and approaches the LS theory and the GMS theory. Also, the effective minimum and maximum impact parameters (bmin* and bmax*) are obtained. For the simulated plasma condition, bmin* is about 6.352 times smaller than the Landau length (bC), and bmax* is about 2 times larger than the Debye length (λD), where bC and λD are used in the LS theory. Surprisingly, the effective relaxation time obtained from the PP model is very close to the LS theory and the GMS theory, even though the effective Coulomb logarithm is two times greater than the one used in the LS theory. Besides, this work shows that the PP model (commonly known as computationally expensive) is becoming practicable via GPU parallel computing techniques.
International Nuclear Information System (INIS)
Azevedo, Eduardo R. de; Becker-Guedes, Fabio; Bonagamba, Tito J.; Schmidt-Rohr, Klaus; Iowa State University, Ames, IA
2001-01-01
The dynamics in the amorphous regions of semicrystalline polymers exert important influences on mechanical properties, but have been notoriously difficult to characterize. Two new solid-state NMR techniques, PUREX (pure exchange) and CODEX (center band-only detection of exchange) NMR, make it possible to analyze the molecular motions near the glass transition in the amorphous regions of semicrystalline polymers. This is achieved by selectively suppressing the otherwise dominant signals of the static segments in the crystallites. We have applied both NMR techniques to study the slow motions near the glass transition in semicrystalline polymers (β relaxation) and in fully amorphous samples for reference. The studied polymers were isotactic poly(1-butene) (iPB1) (form I), syndiotactic and atactic polypropylenes (sPP, and aPP, respectively), as well as polyisobutylene (PIB). We have analyzed the geometry and time scale of the slow molecular motion for all samples and determined the apparent activation energies. (author)
Directory of Open Access Journals (Sweden)
Takashi Arima
2018-04-01
Full Text Available After summarizing the present status of Rational Extended Thermodynamics (RET of gases, which is an endeavor to generalize the Navier–Stokes and Fourier (NSF theory of viscous heat-conducting fluids, we develop the molecular RET theory of rarefied polyatomic gases with 15 independent fields. The theory is justified, at mesoscopic level, by a generalized Boltzmann equation in which the distribution function depends on two internal variables that take into account the energy exchange among the different molecular modes of a gas, that is, translational, rotational, and vibrational modes. By adopting the generalized Bhatnagar, Gross and Krook (BGK-type collision term, we derive explicitly the closed system of field equations with the use of the Maximum Entropy Principle (MEP. The NSF theory is derived from the RET theory as a limiting case of small relaxation times via the Maxwellian iteration. The relaxation times introduced in the theory are shown to be related to the shear and bulk viscosities and heat conductivity.
Ricci, Matteo; Berardi, Roberto; Zannoni, Claudio
2015-08-01
We investigate the switching of a biaxial nematic filling a flat cell with planar homogeneous anchoring using a coarse-grained molecular dynamics simulation. We have found that an aligning field applied across the film, and acting on specific molecular axes, can drive the reorientation of the secondary biaxial director up to one order of magnitude faster than that for the principal director. While the π/2 switching of the secondary director does not affect the alignment of the long molecular axes, the field-driven reorientation of the principal director proceeds via a concerted rotation of the long and transversal molecular axes. More importantly, while upon switching off a (relatively) weak or intermediate field, the biaxial nematic liquid crystal is always able to relax to the initial surface aligned director state; this is not the case when using fields above a certain threshold. In that case, while the secondary director always recovers the initial state, the principal one remains, occasionally, trapped in a nonuniform director state due to the formation of domain walls.
Tsukushi, I.; Yamamuro, O.; Matsuo, T.
The organic crystals of tri-O-methyl-β-cyclodextrin (TMCD) and its three clathrate compounds containing benzoic acid (BA), p-nitrobenzoic acid (NBA) and p-hydroxybenzoic acid (HBA), sucrose (SUC), salicin (SAL), phenolphthalein (PP), 1,3,5-tri-α-naphthylbenzene (TNB) were amorphized by milling with a vibrating mill for 2 ˜ 16 hours at room temperature. The amorphization was checked by differential scanning calorimetry (DSC) and X-ray powder diffraction. The heat capacities of crystals, liquid quenched glasses (LQG), and mechanically-milled amorphous solid (MMAS) of TMCD and TNB were measured with an adiabatic calorimeter in the temperature range between 12 and 375 K. For both compounds, the enthalpy relaxation of MMAS appeared in the wide temperature range below Tg and the released configurational enthalpy was much larger than that of LQG, indicating that MMAS is more disordered and strained than LQG.
Energy Technology Data Exchange (ETDEWEB)
Carriger, John F. [U.S. Environmental Protection Agency, Office of Research and Development, Gulf Ecology Division, Gulf Breeze, FL, 32561 (United States); Martin, Todd M. [U.S. Environmental Protection Agency, Office of Research and Development, Sustainable Technology Division, Cincinnati, OH, 45220 (United States); Barron, Mace G., E-mail: barron.mace@epa.gov [U.S. Environmental Protection Agency, Office of Research and Development, Gulf Ecology Division, Gulf Breeze, FL, 32561 (United States)
2016-11-15
Highlights: • A Bayesian network was developed to classify chemical mode of action (MoA). • The network was based on the aquatic toxicity MoA for over 1000 chemicals. • A Markov blanket algorithm selected a subset of theoretical molecular descriptors. • Sensitivity analyses found influential descriptors for classifying the MoAs. • Overall precision of the Bayesian MoA classification model was 80%. - Abstract: The mode of toxic action (MoA) has been recognized as a key determinant of chemical toxicity, but development of predictive MoA classification models in aquatic toxicology has been limited. We developed a Bayesian network model to classify aquatic toxicity MoA using a recently published dataset containing over one thousand chemicals with MoA assignments for aquatic animal toxicity. Two dimensional theoretical chemical descriptors were generated for each chemical using the Toxicity Estimation Software Tool. The model was developed through augmented Markov blanket discovery from the dataset of 1098 chemicals with the MoA broad classifications as a target node. From cross validation, the overall precision for the model was 80.2%. The best precision was for the AChEI MoA (93.5%) where 257 chemicals out of 275 were correctly classified. Model precision was poorest for the reactivity MoA (48.5%) where 48 out of 99 reactive chemicals were correctly classified. Narcosis represented the largest class within the MoA dataset and had a precision and reliability of 80.0%, reflecting the global precision across all of the MoAs. False negatives for narcosis most often fell into electron transport inhibition, neurotoxicity or reactivity MoAs. False negatives for all other MoAs were most often narcosis. A probabilistic sensitivity analysis was undertaken for each MoA to examine the sensitivity to individual and multiple descriptor findings. The results show that the Markov blanket of a structurally complex dataset can simplify analysis and interpretation by
International Nuclear Information System (INIS)
Brot, C.; Virlet, J.
1979-01-01
14 N and 1 H NMR relaxation times have been measured in quinuclidine in its plastic phase. These measurements rule out isotropic motion. Correlation times for several anisotropic reorientational models are calculated from these NMR data. The best agreement with the values calculated from neutron scattering experiments (preceding paper) is obtained for a model where the molecules reorient by +-90 0 jumps about the crystallographic C 4 axes with a residence time of (22.2+-2).10 -12 s, and by +-120 0 jumps about the molecular C 3 axes with a residence of (5.25+-2.8).10 -12 s, at room temperature. The activation enthalpy is 15.3 kJ.mol. -1 for the +-90 0 jumps, and higher for the +-120 0 jumps. Translational correlation times have also been measured at high temperature, below the melting point
Low-relaxation spin waves in laser-molecular-beam epitaxy grown nanosized yttrium iron garnet films
Energy Technology Data Exchange (ETDEWEB)
Lutsev, L. V., E-mail: l-lutsev@mail.ru; Korovin, A. M.; Bursian, V. E.; Gastev, S. V.; Fedorov, V. V.; Suturin, S. M.; Sokolov, N. S. [Ioffe Physical-Technical Institute, Russian Academy of Sciences, 194021 St. Petersburg (Russian Federation)
2016-05-02
Synthesis of nanosized yttrium iron garnet (Y{sub 3}Fe{sub 5}O{sub 12}, YIG) films followed by the study of ferromagnetic resonance (FMR) and spin wave propagation in these films is reported. The YIG films were grown on gadolinium gallium garnet substrates by laser molecular beam epitaxy. It has been shown that spin waves propagating in YIG deposited at 700 °C have low damping. At the frequency of 3.29 GHz, the spin-wave damping parameter is less than 3.6 × 10{sup −5}. Magnetic inhomogeneities of the YIG films give the main contribution to the FMR linewidth. The contribution of the relaxation processes to the FMR linewidth is as low as 1.2%.
MIDAS: a practical Bayesian design for platform trials with molecularly targeted agents.
Yuan, Ying; Guo, Beibei; Munsell, Mark; Lu, Karen; Jazaeri, Amir
2016-09-30
Recent success of immunotherapy and other targeted therapies in cancer treatment has led to an unprecedented surge in the number of novel therapeutic agents that need to be evaluated in clinical trials. Traditional phase II clinical trial designs were developed for evaluating one candidate treatment at a time and thus not efficient for this task. We propose a Bayesian phase II platform design, the multi-candidate iterative design with adaptive selection (MIDAS), which allows investigators to continuously screen a large number of candidate agents in an efficient and seamless fashion. MIDAS consists of one control arm, which contains a standard therapy as the control, and several experimental arms, which contain the experimental agents. Patients are adaptively randomized to the control and experimental agents based on their estimated efficacy. During the trial, we adaptively drop inefficacious or overly toxic agents and 'graduate' the promising agents from the trial to the next stage of development. Whenever an experimental agent graduates or is dropped, the corresponding arm opens immediately for testing the next available new agent. Simulation studies show that MIDAS substantially outperforms the conventional approach. The proposed design yields a significantly higher probability for identifying the promising agents and dropping the futile agents. In addition, MIDAS requires only one master protocol, which streamlines trial conduct and substantially decreases the overhead burden. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.
Directory of Open Access Journals (Sweden)
Debashis Mukherjee
2002-06-01
Full Text Available Abstract: We present in this paper two new versions of Rayleigh-SchrÃ‚Â¨odinger (RS and the Brillouin-Wigner (BW state-specific multi-reference perturbative theories (SSMRPT which stem from our state-specific multi-reference coupled-cluster formalism (SS-MRCC, developed with a complete active space (CAS. They are manifestly sizeextensive and are designed to avoid intruders. The combining coefficients cÃŽÂ¼ for the model functions ÃÂ†ÃŽÂ¼ are completely relaxed and are obtained by diagonalizing an effective operator in the model space, one root of which is the target eigenvalue of interest. By invoking suitable partitioning of the hamiltonian, very convenient perturbative versions of the formalism in both the RS and the BW forms are developed for the second order energy. The unperturbed hamiltonians for these theories can be chosen to be of both MÃÂ†ller-Plesset (MP and Epstein-Nesbet (EN type. However, we choose the corresponding Fock operator fÃŽÂ¼ for each model function ÃÂ†ÃŽÂ¼, whose diagonal elements are used to define the unperturbed hamiltonian in the MP partition. In the EN partition, we additionally include all the diagonal direct and exchange ladders. Our SS-MRPT thus utilizes a multi-partitioning strategy. Illustrative numerical applications are presented for potential energy surfaces (PES of the ground (1ÃŽÂ£+ and the first delta (1ÃŽÂ” states of CH+ which possess pronounced multi-reference character. Comparison of the results with the corresponding full CI values indicates the efficacy of our formalisms.
International Nuclear Information System (INIS)
Micotti, E.; Lascialfari, A.; Rigamonti, A.; Aldrovandi, S.; Caneschi, A.; Gatteschi, D.; Bogani, L.
2004-01-01
The spin dynamics in the helical chain Co(hfac) 2 NITPhOMe has been investigated by 1 H NMR and μSR relaxation. In the temperature range 15< T<60 K, the results are consistent with the relaxation of the homogeneous magnetization. For T≤15 K, NMR and μSR evidence a second spin relaxation mechanism, undetected by the magnetization measurements. From the analysis of these data, insights on this novel relaxation process are derived
Micotti, E.; Lascialfari, A.; Rigamonti, A.; Aldrovandi, S.; Caneschi, A.; Gatteschi, D.; Bogani, L.
2004-05-01
The spin dynamics in the helical chain Co(hfac) 2NITPhOMe has been investigated by 1H NMR and μSR relaxation. In the temperature range 15
Baranowski, M; Woźniak-Braszak, A; Jurga, K
2016-01-01
The paper presents the benefits of using fast adiabatic passage for the study of molecular dynamics in the solid state heteronuclear systems in the laboratory frame. A homemade pulse spectrometer operating at the frequency of 30.2MHz and 28.411MHz for protons and fluorines, respectively, has been enhanced with microcontroller direct digital synthesizer DDS controller [1-4]. This work briefly describes how to construct a low-cost and easy-to-assemble adiabatic extension set for homemade and commercial spectrometers based on recently very popular Arduino shields. The described set was designed for fast adiabatic generation. Timing and synchronization problems are discussed. The cross-relaxation experiments with different initial states of the two spin systems have been performed. Contrary to our previous work [5] where the steady-state NOE experiments were conducted now proton spins (1)H are polarized in the magnetic field B0 while fluorine spins (19)F are perturbed by selective saturation for a short time and then the system is allowed to evolve for a period in the absence of a saturating field. The adiabatic passage application leads to a reversal of magnetization of fluorine spins and increases the amplitude of the signal. Copyright © 2015 Elsevier Inc. All rights reserved.
International Nuclear Information System (INIS)
Lascialfari, A.; Borsa, F.; Carretta, P.; Jang, Z.H.; Borsa, F.; Gatteschi, D.
1998-01-01
Measurements of the spin-lattice relaxation rate are reported for muons and protons as a function of temperature for different values of the applied magnetic field in the Mn 12 O 12 molecular cluster. Strongly field dependent maxima in the relaxation rate versus temperature are observed below 50thinspthinspK. The results are explained in terms of thermal fluctuations of the total magnetization of the cluster among the different orientations with respect to the anisotropy axis. The lifetimes of the different m components of the total spin, S T =10 , of the molecule are obtained from the experiment and shown to be consistent with the ones expected from a spin-phonon coupling mechanism. No clear evidence for macroscopic quantum tunneling was observed in the field dependence of the proton relaxation rate at low T . copyright 1998 The American Physical Society
Bhattacharya, Sisir; Bhardwaj, Sunny P; Suryanarayanan, Raj
2014-10-01
To determine the effect of annealing on the two secondary relaxations in amorphous sucrose and in sucrose solid dispersions. Sucrose was co-lyophilized with either PVP or sorbitol, annealed for different time periods and analyzed by dielectric spectroscopy. In an earlier investigation, we had documented the effect of PVP and sorbitol on the primary and the two secondary relaxations in amorphous sucrose solid dispersions (1). Here we investigated the effect of annealing on local motions, both in amorphous sucrose and in the dispersions. The average relaxation time of the local motion (irrespective of origin) in sucrose, decreased upon annealing. However, the heterogeneity in relaxation time distribution as well as the dielectric strength decreased only for β1- (the slower relaxation) but not for β2-relaxations. The effect of annealing on β2-relaxation times was neutralized by sorbitol while PVP negated the effect of annealing on both β1- and β2-relaxations. An increase in local mobility of sucrose brought about by annealing could be negated with an additive.
Energy Technology Data Exchange (ETDEWEB)
Arosio, Paolo, E-mail: paolo.arosio@guest.unimi.it; Orsini, Francesco [Department of Physics, Università degli Studi di Milano, and INSTM, Milano (Italy); Corti, Maurizio [Department of Physics, Università degli Studi di Pavia and INSTM, Pavia (Italy); Mariani, Manuel [Department of Physics and Astronomy, Università degli Studi di Bologna, Bologna (Italy); Bogani, Lapo [Physikalisches Institut, Universität Stuttgart, Stuttgart (Germany); Caneschi, Andrea [INSTM and Department of Chemistry, University of Florence, Firenze (Italy); Lago, Jorge [Departamento de Quimica Inorganica, Universidad del Pais Vasco, Bilbao (Spain); Lascialfari, Alessandro [Department of Physics, Università degli Studi di Milano, and INSTM, Milano (Italy); Centro S3, Istituto Nanoscienze - CNR, Modena (Italy)
2015-05-07
The spin dynamics of the molecular magnetic chain [Dy(hfac){sub 3}(NIT(C{sub 6}H{sub 4}OPh))] were investigated by means of the Muon Spin Relaxation (μ{sup +}SR) technique. This system consists of a magnetic lattice of alternating Dy(III) ions and radical spins, and exhibits single-chain-magnet behavior. The magnetic properties of [Dy(hfac){sub 3}(NIT(C{sub 6}H{sub 4}OPh))] have been studied by measuring the magnetization vs. temperature at different applied magnetic fields (H = 5, 3500, and 16500 Oe) and by performing μ{sup +}SR experiments vs. temperature in zero field and in a longitudinal applied magnetic field H = 3500 Oe. The muon asymmetry P(t) was fitted by the sum of three components, two stretched-exponential decays with fast and intermediate relaxation times, and a third slow exponential decay. The temperature dependence of the spin dynamics has been determined by analyzing the muon longitudinal relaxation rate λ{sub interm}(T), associated with the intermediate relaxing component. The experimental λ{sub interm}(T) data were fitted with a corrected phenomenological Bloembergen-Purcell-Pound law by using a distribution of thermally activated correlation times, which average to τ = τ{sub 0} exp(Δ/k{sub B}T), corresponding to a distribution of energy barriers Δ. The correlation times can be associated with the spin freezing that occurs when the system condenses in the ground state.
Solomentsev, Gleb; Diehl, Carl; Akke, Mikael
2018-03-06
FKBP12 (FK506 binding protein 12 kDa) is an important drug target. Nuclear magnetic resonance (NMR) order parameters, describing amplitudes of motion on the pico- to nanosecond time scale, can provide estimates of changes in conformational entropy upon ligand binding. Here we report backbone and methyl-axis order parameters of the apo and FK506-bound forms of FKBP12, based on 15 N and 2 H NMR relaxation. Binding of FK506 to FKBP12 results in localized changes in order parameters, notably for the backbone of residues E54 and I56 and the side chains of I56, I90, and I91, all positioned in the binding site. The order parameters increase slightly upon FK506 binding, indicating an unfavorable entropic contribution to binding of TΔ S = -18 ± 2 kJ/mol at 293 K. Molecular dynamics simulations indicate a change in conformational entropy, associated with all dihedral angles, of TΔ S = -26 ± 9 kJ/mol. Both these values are significant compared to the total entropy of binding determined by isothermal titration calorimetry and referenced to a reactant concentration of 1 mM ( TΔ S = -29 ± 1 kJ/mol). Our results reveal subtle differences in the response to ligand binding compared to that of the previously studied rapamycin-FKBP12 complex, despite the high degree of structural homology between the two complexes and their nearly identical ligand-FKBP12 interactions. These results highlight the delicate dependence of protein dynamics on drug interactions, which goes beyond the view provided by static structures, and reinforce the notion that protein conformational entropy can make important contributions to the free energy of ligand binding.
Bayesian analysis in plant pathology.
Mila, A L; Carriquiry, A L
2004-09-01
ABSTRACT Bayesian methods are currently much discussed and applied in several disciplines from molecular biology to engineering. Bayesian inference is the process of fitting a probability model to a set of data and summarizing the results via probability distributions on the parameters of the model and unobserved quantities such as predictions for new observations. In this paper, after a short introduction of Bayesian inference, we present the basic features of Bayesian methodology using examples from sequencing genomic fragments and analyzing microarray gene-expressing levels, reconstructing disease maps, and designing experiments.
Energy Technology Data Exchange (ETDEWEB)
Yurasov, D. V., E-mail: Inquisitor@ipm.sci-nnov.ru [Russian Academy of Sciences, Institute for Physics of Microstructures (Russian Federation); Bobrov, A. I. [Lobachevsky State University of Nizhny Novgorod (Russian Federation); Daniltsev, V. M.; Novikov, A. V. [Russian Academy of Sciences, Institute for Physics of Microstructures (Russian Federation); Pavlov, D. A. [Lobachevsky State University of Nizhny Novgorod (Russian Federation); Skorokhodov, E. V.; Shaleev, M. V.; Yunin, P. A. [Russian Academy of Sciences, Institute for Physics of Microstructures (Russian Federation)
2015-11-15
Influence of the Ge layer thickness and annealing conditions on the parameters of relaxed Ge/Si(001) layers grown by molecular beam epitaxy via two-stage growth is investigated. The dependences of the threading dislocation density and surface roughness on the Ge layer thickness, annealing temperature and time, and the presence of a hydrogen atmosphere are obtained. As a result of optimization of the growth and annealing conditions, relaxed Ge/Si(001) layers which are thinner than 1 μm with a low threading dislocation density on the order of 10{sup 7} cm{sup –2} and a root mean square roughness of less than 1 nm are obtained.
Energy Technology Data Exchange (ETDEWEB)
Kimmich, R; Nusser, W; Gneiting, T [Ulm Universitaet (Federal Republic of Germany). Sektion Kernresonanzspektroskopie
1990-04-01
A model theory is presented explaining a series of striking phenomena observed with nuclear magnetic relaxation in protein systems such as solutions or tissue. The frequency, concentration and temperature dependences of proton or deuteron relaxation times of protein solutions and tissue are explained. It is concluded that the translational diffusion of water molecules along the rugged surfaces of proteins and, to a minor degree, protein backbone fluctuations are crucial processes. The rate limiting factor of macromolecular tumbling is assumed to be given by the free water content in a certain analogy to the free-volume model of Cohen ad Turnbull. There are two characteristic water mass fractions indicating the saturation of the hydration shells and the onset of protein tumbling. A closed and relatively simple set of relaxation formulas is presented. The potentially fractal nature of the diffusion of water molecules on the protein surface is discussed. (author). 43 refs.; 4 figs.
Strate, Anne; Neumann, Jan; Overbeck, Viviane; Bonsa, Anne-Marie; Michalik, Dirk; Paschek, Dietmar; Ludwig, Ralf
2018-05-01
We report a concerted theoretical and experimental effort to determine the reorientational dynamics as well as hydrogen bond lifetimes for the doubly ionic hydrogen bond +OH⋯O- in the ionic liquid (2-hydroxyethyl)trimethylammonium bis(trifluoromethylsulfonyl)imide [Ch][NTf2] by using a combination of NMR relaxation time experiments, density functional theory (DFT) calculations, and molecular dynamics (MD) simulations. Due to fast proton exchange, the determination of rotational correlation times is challenging. For molecular liquids, 17O-enhanced proton relaxation time experiments have been used to determine the rotational correlation times for the OH vectors in water or alcohols. As an alternative to those expensive isotopic substitution experiments, we employed a recently introduced approach which is providing access to the rotational dynamics from a single NMR deuteron quadrupolar relaxation time experiment. Here, the deuteron quadrupole coupling constants (DQCCs) are obtained from a relation between the DQCC and the δ1H proton chemical shifts determined from a set of DFT calculated clusters in combination with experimentally determined proton chemical shifts. The NMR-obtained rotational correlation times were compared to those obtained from MD simulations and then related to viscosities for testing the applicability of popular hydrodynamic models. In addition, hydrogen bond lifetimes were derived, using hydrogen bond population correlation functions computed from MD simulations. Here, two different time domains were observed: The short-time contributions to the hydrogen lifetimes and the reorientational correlation times have roughly the same size and are located in the picosecond range, whereas the long-time contributions decay with relaxation times in the nanosecond regime and are related to rather slow diffusion processes. The computed average hydrogen bond lifetime is dominated by the long-time process, highlighting the importance and longevity of
Engelhardt, Benjamin; Kschischo, Maik; Fröhlich, Holger
2017-06-01
Ordinary differential equations (ODEs) are a popular approach to quantitatively model molecular networks based on biological knowledge. However, such knowledge is typically restricted. Wrongly modelled biological mechanisms as well as relevant external influence factors that are not included into the model are likely to manifest in major discrepancies between model predictions and experimental data. Finding the exact reasons for such observed discrepancies can be quite challenging in practice. In order to address this issue, we suggest a Bayesian approach to estimate hidden influences in ODE-based models. The method can distinguish between exogenous and endogenous hidden influences. Thus, we can detect wrongly specified as well as missed molecular interactions in the model. We demonstrate the performance of our Bayesian dynamic elastic-net with several ordinary differential equation models from the literature, such as human JAK-STAT signalling, information processing at the erythropoietin receptor, isomerization of liquid α -Pinene, G protein cycling in yeast and UV-B triggered signalling in plants. Moreover, we investigate a set of commonly known network motifs and a gene-regulatory network. Altogether our method supports the modeller in an algorithmic manner to identify possible sources of errors in ODE-based models on the basis of experimental data. © 2017 The Author(s).
Lesaffre, Emmanuel
2012-01-01
The growth of biostatistics has been phenomenal in recent years and has been marked by considerable technical innovation in both methodology and computational practicality. One area that has experienced significant growth is Bayesian methods. The growing use of Bayesian methodology has taken place partly due to an increasing number of practitioners valuing the Bayesian paradigm as matching that of scientific discovery. In addition, computational advances have allowed for more complex models to be fitted routinely to realistic data sets. Through examples, exercises and a combination of introd
ZHOU, Lin
1996-01-01
In this paper I consider social choices under uncertainty. I prove that any social choice rule that satisfies independence of irrelevant alternatives, translation invariance, and weak anonymity is consistent with ex post Bayesian utilitarianism
Martínez-Lillo, José; Cano, Joan; Wernsdorfer, Wolfgang; Brechin, Euan K
2015-01-01
The energy barrier to magnetisation relaxation in single-molecule magnets (SMMs) proffers potential technological applications in high-density information storage and quantum computation. Leading candidates amongst complexes of 3d metals ions are the hexametallic family of complexes of formula [Mn6 O2 (R-sao)6 (X)2 (solvent)y ] (saoH2 =salicylaldoxime; X=mono-anion; y=4-6; R=H, Me, Et, and Ph). The recent synthesis of cationic [Mn6 ][ClO4 ]2 family members, in which the coordinating X ions we...
BEAST: Bayesian evolutionary analysis by sampling trees
Directory of Open Access Journals (Sweden)
Drummond Alexei J
2007-11-01
Full Text Available Abstract Background The evolutionary analysis of molecular sequence variation is a statistical enterprise. This is reflected in the increased use of probabilistic models for phylogenetic inference, multiple sequence alignment, and molecular population genetics. Here we present BEAST: a fast, flexible software architecture for Bayesian analysis of molecular sequences related by an evolutionary tree. A large number of popular stochastic models of sequence evolution are provided and tree-based models suitable for both within- and between-species sequence data are implemented. Results BEAST version 1.4.6 consists of 81000 lines of Java source code, 779 classes and 81 packages. It provides models for DNA and protein sequence evolution, highly parametric coalescent analysis, relaxed clock phylogenetics, non-contemporaneous sequence data, statistical alignment and a wide range of options for prior distributions. BEAST source code is object-oriented, modular in design and freely available at http://beast-mcmc.googlecode.com/ under the GNU LGPL license. Conclusion BEAST is a powerful and flexible evolutionary analysis package for molecular sequence variation. It also provides a resource for the further development of new models and statistical methods of evolutionary analysis.
2017-01-01
top rotor superimposes an effective correlation time, τe, onto a symmetric top rotor to account for internal motion. 2. THEORY The purpose...specifically describe how simple 13C relaxation theory is used to describe quantitatively simple molecular 3 motions. More-detailed accounts ...of nuclear magnetic relaxation can be found in a number of basic textbooks (i.e., Farrar and Becker, 1971; Fukushima and Roeder, 1981; Harris, 1986
Steendam, R.; Van Steenbergen, M.J.; Hennink, W.E.; Frijlink, H.W.; Lerk, C.F.
2001-01-01
Different molecular weight grades of poly(DL-lactic acid) were applied as release controlling excipients in tablets for oral drug administration. The role of molecular weight and glass transition in the mechanism of water-induced volume expansion and drug release of PDLA tablets was investigated.
Energy Technology Data Exchange (ETDEWEB)
Teichler, Helmar [Inst. Materialphysik, Univ Goettingen (Germany)
2013-07-01
In glass-forming melts the decay of structural fluctuation shows the well known transition from beta-relaxation (von-Schweidler law with exponent b) to alpha-decay (KWW law with exponent beta). Here we present results from molecular dynamics simulations for a metallic glass forming Ni0.5Zr0.5 model aimed at giving an understanding of this transition on the atomistic scale. At the considered temperature below mode coupling Tc, the dynamics of the system can be interpreted by residence of the particles in their neighbour cages and escape from the cages as rare processes. Our analysis yields that the fraction of residing particles is characterized by a hierarchical law in time, with von-Schweidler b explicitly related to the exponent of this law. In the alpha-decay regime the stretching exponent reflects, in addition, floating of the cages due to strain effects of escaped particles. Accordingly, the change from beta-relaxation to alpha-decay indicates the transition from low to large fraction of escaped particles.
International Nuclear Information System (INIS)
Colmenero, Juan; Arbe, Arantxa; Alvarez, Fernando; Monkenbusch, Michael; Richter, Dieter; Farago, Bela; Frick, Bernhard
2003-01-01
The momentum transfer dependence of the self-motion of main chain hydrogens in the α-relaxation regime of a glass forming polymer, polyisoprene, has been thoroughly investigated by a combined effort involving fully atomistic molecular dynamic simulations and quasielastic neutron scattering measurements. In this way, we have established the existence of a crossover from a Gaussian regime of sublinear diffusion to a strongly non-Gaussian regime at short distances. We show that an anomalous jump diffusion model with a distribution of jump lengths gives rise to such a crossover. This model leads to a time-dependent non-Gaussian parameter exhibiting all features revealed so far from various simulations of different glass forming systems
International Nuclear Information System (INIS)
Powers, R.; Jones, C.R.; Gorenstein, D.G.
1990-01-01
Assignment of the 1H and 31P resonances of a decamer DNA duplex, d(CGCTTAAGCG)2 was determined by two-dimensional COSY, NOESY and 1H-31P Pure Absorption phase Constant time (PAC) heteronuclear correlation spectroscopy. The solution structure of the decamer was calculated by an iterative hybrid relaxation matrix method combined with NOESY-distance restrained molecular dynamics. The distances from the 2D NOESY spectra were calculated from the relaxation rate matrix which were evaluated from a hybrid NOESY volume matrix comprising elements from the experiment and those calculated from an initial structure. The hybrid matrix-derived distances were then used in a restrained molecular dynamics procedure to obtain a new structure that better approximates the NOESY spectra. The resulting partially refined structure was then used to calculate an improved theoretical NOESY volume matrix which is once again merged with the experimental matrix until refinement is complete. JH3'-P coupling constants for each of the phosphates of the decamer were obtained from 1H-31P J-resolved selective proton flip 2D spectra. By using a modified Karplus relationship the C4'-C3'-O3'-P torsional angles were obtained. Comparison of the 31P chemical shifts and JH3'-P coupling constants of this sequence has allowed a greater insight into the various factors responsible for 31P chemical shift variations in oligonucleotides. It also provides an important probe of the sequence-dependent structural variation of the deoxyribose phosphate backbone of DNA in solution. These correlations are consistent with the hypothesis that changes in local helical structure perturb the deoxyribose phosphate backbone. The variation of the 31P chemical shift, and the degree of this variation from one base step to the next is proposed as a potential probe of local helical conformation within the DNA double helix
Non-homogeneous dynamic Bayesian networks for continuous data
Grzegorczyk, Marco; Husmeier, Dirk
Classical dynamic Bayesian networks (DBNs) are based on the homogeneous Markov assumption and cannot deal with non-homogeneous temporal processes. Various approaches to relax the homogeneity assumption have recently been proposed. The present paper presents a combination of a Bayesian network with
Bayesian non- and semi-parametric methods and applications
Rossi, Peter
2014-01-01
This book reviews and develops Bayesian non-parametric and semi-parametric methods for applications in microeconometrics and quantitative marketing. Most econometric models used in microeconomics and marketing applications involve arbitrary distributional assumptions. As more data becomes available, a natural desire to provide methods that relax these assumptions arises. Peter Rossi advocates a Bayesian approach in which specific distributional assumptions are replaced with more flexible distributions based on mixtures of normals. The Bayesian approach can use either a large but fixed number
Bogani, Lapo
2011-04-01
We offer a perspective, accessible to both chemists and physicists, of recent developments in the synthesis and characterization of molecular magnetic materials based on rare-earths and nitronyl-nitroxide radicals. We show both the rationale of the synthetic strategies and the observed behaviors. We highlight the relevance of these findings for synthetic chemists, material scientists, and physicists.
1987-01-01
Environ Corporation's relaxation system is built around a body lounge, a kind of super easy chair that incorporates sensory devices. Computer controlled enclosure provides filtered ionized air to create a feeling of invigoration, enhanced by mood changing aromas. Occupant is also surrounded by multidimensional audio and the lighting is programmed to change colors, patterns, and intensity periodically. These and other sensory stimulators are designed to provide an environment in which the learning process is stimulated, because research has proven that while an individual is in a deep state of relaxation, the mind is more receptive to new information.
Directory of Open Access Journals (Sweden)
Simon Boitard
2016-03-01
Full Text Available Inferring the ancestral dynamics of effective population size is a long-standing question in population genetics, which can now be tackled much more accurately thanks to the massive genomic data available in many species. Several promising methods that take advantage of whole-genome sequences have been recently developed in this context. However, they can only be applied to rather small samples, which limits their ability to estimate recent population size history. Besides, they can be very sensitive to sequencing or phasing errors. Here we introduce a new approximate Bayesian computation approach named PopSizeABC that allows estimating the evolution of the effective population size through time, using a large sample of complete genomes. This sample is summarized using the folded allele frequency spectrum and the average zygotic linkage disequilibrium at different bins of physical distance, two classes of statistics that are widely used in population genetics and can be easily computed from unphased and unpolarized SNP data. Our approach provides accurate estimations of past population sizes, from the very first generations before present back to the expected time to the most recent common ancestor of the sample, as shown by simulations under a wide range of demographic scenarios. When applied to samples of 15 or 25 complete genomes in four cattle breeds (Angus, Fleckvieh, Holstein and Jersey, PopSizeABC revealed a series of population declines, related to historical events such as domestication or modern breed creation. We further highlight that our approach is robust to sequencing errors, provided summary statistics are computed from SNPs with common alleles.
Directory of Open Access Journals (Sweden)
Brian W Kunkle
Full Text Available In this study we have identified key genes that are critical in development of astrocytic tumors. Meta-analysis of microarray studies which compared normal tissue to astrocytoma revealed a set of 646 differentially expressed genes in the majority of astrocytoma. Reverse engineering of these 646 genes using Bayesian network analysis produced a gene network for each grade of astrocytoma (Grade I-IV, and 'key genes' within each grade were identified. Genes found to be most influential to development of the highest grade of astrocytoma, Glioblastoma multiforme were: COL4A1, EGFR, BTF3, MPP2, RAB31, CDK4, CD99, ANXA2, TOP2A, and SERBP1. All of these genes were up-regulated, except MPP2 (down regulated. These 10 genes were able to predict tumor status with 96-100% confidence when using logistic regression, cross validation, and the support vector machine analysis. Markov genes interact with NFkβ, ERK, MAPK, VEGF, growth hormone and collagen to produce a network whose top biological functions are cancer, neurological disease, and cellular movement. Three of the 10 genes - EGFR, COL4A1, and CDK4, in particular, seemed to be potential 'hubs of activity'. Modified expression of these 10 Markov Blanket genes increases lifetime risk of developing glioblastoma compared to the normal population. The glioblastoma risk estimates were dramatically increased with joint effects of 4 or more than 4 Markov Blanket genes. Joint interaction effects of 4, 5, 6, 7, 8, 9 or 10 Markov Blanket genes produced 9, 13, 20.9, 26.7, 52.8, 53.2, 78.1 or 85.9%, respectively, increase in lifetime risk of developing glioblastoma compared to normal population. In summary, it appears that modified expression of several 'key genes' may be required for the development of glioblastoma. Further studies are needed to validate these 'key genes' as useful tools for early detection and novel therapeutic options for these tumors.
Energy Technology Data Exchange (ETDEWEB)
Micotti, E. E-mail: micotti@fisicavolta.unipv.it; Lascialfari, A.; Rigamonti, A.; Aldrovandi, S.; Caneschi, A.; Gatteschi, D.; Bogani, L
2004-05-01
The spin dynamics in the helical chain Co(hfac){sub 2}NITPhOMe has been investigated by {sup 1}H NMR and {mu}SR relaxation. In the temperature range 15
Kunkle, Brian W.; Yoo, Changwon; Roy, Deodutta
2013-01-01
In this study we have identified key genes that are critical in development of astrocytic tumors. Meta-analysis of microarray studies which compared normal tissue to astrocytoma revealed a set of 646 differentially expressed genes in the majority of astrocytoma. Reverse engineering of these 646 genes using Bayesian network analysis produced a gene network for each grade of astrocytoma (Grade I–IV), and ‘key genes’ within each grade were identified. Genes found to be most influential to development of the highest grade of astrocytoma, Glioblastoma multiforme were: COL4A1, EGFR, BTF3, MPP2, RAB31, CDK4, CD99, ANXA2, TOP2A, and SERBP1. All of these genes were up-regulated, except MPP2 (down regulated). These 10 genes were able to predict tumor status with 96–100% confidence when using logistic regression, cross validation, and the support vector machine analysis. Markov genes interact with NFkβ, ERK, MAPK, VEGF, growth hormone and collagen to produce a network whose top biological functions are cancer, neurological disease, and cellular movement. Three of the 10 genes - EGFR, COL4A1, and CDK4, in particular, seemed to be potential ‘hubs of activity’. Modified expression of these 10 Markov Blanket genes increases lifetime risk of developing glioblastoma compared to the normal population. The glioblastoma risk estimates were dramatically increased with joint effects of 4 or more than 4 Markov Blanket genes. Joint interaction effects of 4, 5, 6, 7, 8, 9 or 10 Markov Blanket genes produced 9, 13, 20.9, 26.7, 52.8, 53.2, 78.1 or 85.9%, respectively, increase in lifetime risk of developing glioblastoma compared to normal population. In summary, it appears that modified expression of several ‘key genes’ may be required for the development of glioblastoma. Further studies are needed to validate these ‘key genes’ as useful tools for early detection and novel therapeutic options for these tumors. PMID:23737970
A Bayesian Nonparametric Approach to Factor Analysis
DEFF Research Database (Denmark)
Piatek, Rémi; Papaspiliopoulos, Omiros
2018-01-01
This paper introduces a new approach for the inference of non-Gaussian factor models based on Bayesian nonparametric methods. It relaxes the usual normality assumption on the latent factors, widely used in practice, which is too restrictive in many settings. Our approach, on the contrary, does no...
Kasyanenko, Valeriy Mitrofanovich
Measuring the three-dimensional structure of molecules, dynamics of structural changes, and energy transport on a molecular scale is important for many areas of natural science. Supplementing the widely used methods of x-ray diffraction, NMR, and optical spectroscopies, a two-dimensional infrared spectroscopy (2DIR) method was introduced about a decade ago. The 2DIR method measures pair-wise interactions between vibrational modes in molecules, thus acquiring molecular structural constraints such as distances between vibrating groups and the angles between their transition dipoles. The 2DIR method has been applied to a variety of molecular systems but in studying larger molecules such as proteins and peptides the method is facing challenges associated with the congestion of their vibrational spectra and delocalized character of their vibrational modes. To help extract structural information from such spectra and make efficient use of vibrational modes separated by large distances, a novel relaxation-assisted 2DIR method (RA 2DIR) has recently been proposed, which exploits the transport of excess vibrational energy from the initially excited mode. With the goal of further development of RA 2DIR, we applied it to a variety of molecular systems, including model compounds, transition-metal complexes, and isomers. The experiments revealed several novel effects which both enhance the power of RA 2DIR and bring a deeper understanding to the fundamental process of energy transport on a molecular level. We demonstrated that RA 2DIR can enhance greatly (27-fold) the cross-peak amplitude among spatially remote modes, which leads to an increase of the range of distances accessible for structural measurements by several fold. We demonstrated that the energy transport time correlates with the intermode distance. This correlation offers a new way for identifying connectivity patterns in molecules. We developed two models of energy transport in molecules. In one, a spatial overlap
Directory of Open Access Journals (Sweden)
Sérgio L. Pereira
2008-01-01
Full Text Available Most Neotropical birds, including Pteroglossus aracaris, do not have an adequate fossil record to be used as time constraints in molecular dating. Hence, the evolutionary timeframe of the avian biota can only be inferred using alternative time constraints. We applied a Bayesian relaxed clock approach to propose an alternative interpretation for the historical biogeography of Pteroglossus based on mitochondrial DNA sequences, using different combinations of outgroups and time constraints obtained from outgroup fossils, vicariant barriers and molecular time estimates. The results indicated that outgroup choice has little effect on the Bayesian posterior distribution of divergence times within Pteroglossus , that geological and molecular time constraints seem equally suitable to estimate the Bayesian posterior distribution of divergence times for Pteroglossus , and that the fossil record alone overestimates divergence times within the fossil-lacking ingroup. The Bayesian estimates of divergence times suggest that the radiation of Pteroglossus occurred from the Late Miocene to the Pliocene (three times older than estimated by the “standard” mitochondrial rate of 2% sequence divergence per million years, likely triggered by Andean uplift, multiple episodes of marine transgressions in South America, and formation of present-day river basins. The time estimates are in agreement with other Neotropical taxa with similar geographic distributions.
International Nuclear Information System (INIS)
Bachellerie, D.
2008-12-01
The formation of H 2 in the interstellar medium, from two hydrogen atoms, is a fundamental question in astrophysics. This very exothermic reaction is indeed the first step of a series of essential reactions for the interstellar physical-chemistry that takes place on the surface of interstellar dust grains. In the warm regions of the ISM, diffuse clouds and Photodissociation regions, the invoked formation mechanism is the Eley-Rideal heterogeneous catalysis reaction, in which one H atom is initially chemisorbed. The grains have mainly carbonaceous graphitic-like composition. Previous theoretical works carried out using constrained geometries were unable to explain the formation of H 2 in the observed rovibrationnal states (v≤5). In order to take into account the degrees of freedom of all relevant atoms, we have built, from the Brenner potential, a new potential that models the graphene H-H system.With this potential, we have completed a classical molecular dynamics study of the formation of H 2 . This work has been performed for collision energies of the impinging H atoms from 0.015 eV to 0.2 eV and for surface temperature of 0, 10 and 30 K. One of the salient results is that the reaction cross section is directly related with the shape of the potential seen by the impinging H atom. Furthermore, the rovibrationnal distribution obtained by allowing the surface atoms to move is in better agreement with the one observed by astrophysicists (v≤6), the surface absorbs a large part (∼25%) of the available energy. Some works about the influence of: an additional H atom upon the surface or a possible porous structure of the grains, on the formation of H 2 are presented in appendices. (author)
Bessiere, Pierre; Ahuactzin, Juan Manuel; Mekhnacha, Kamel
2013-01-01
Probability as an Alternative to Boolean LogicWhile logic is the mathematical foundation of rational reasoning and the fundamental principle of computing, it is restricted to problems where information is both complete and certain. However, many real-world problems, from financial investments to email filtering, are incomplete or uncertain in nature. Probability theory and Bayesian computing together provide an alternative framework to deal with incomplete and uncertain data. Decision-Making Tools and Methods for Incomplete and Uncertain DataEmphasizing probability as an alternative to Boolean
International Nuclear Information System (INIS)
Marguet, Sylvie
1992-01-01
This research thesis reports the study of a styrenic laser dye, the 4-(dicyanomethylene)-2-methyl-6-[p-(dimethylamino) styryl]-4H-pyrane or DCM for the characterization of the first electronic states and of the influence of the solvent on efficiencies of different relaxation processes of the first excited state S1 of the DCM. Due to the presence of a combination of a donor group and acceptor group, this compound has interesting properties of intra-molecular charge transfer and of photo-isomerization which highly depend on solvent polarity. Two approaches have been adopted to study these complementary processes: an experimental approach (determination of rate constants of the different deactivation ways of the S1 state by measuring fluorescence quantum efficiencies, photo-isomerization quantum efficiencies, and fluorescence lifetimes of DCM in about twenty solvent of increasing polarity), and a computational approach (a CS-INDO-MRI type quantum chemistry calculation to obtain potential energy curves, charge distributions, and dipolar moments of DCM first electronic states) [fr
da Silva, Maria Cristina Rodrigues
1998-11-01
Molecular orbital methods and laser ionization mass spectrometry measurements are used to investigate the spectroscopy and relaxation dynamics of benzaldehyde following excitation to its S2(/pi/pi/sp/*) state. Energies, equilibrium geometries and vibrational frequencies of ground and low-lying excited states of benzaldehyde neutral and cation determined by ab initio calculations provide a theoretical description of the electronic spectroscopy of benzaldehyde and of the changes occurring on excitation and ionization. The S2(/pi/pi/sp/*)[/gets]S0 excitation spectrum of jet-cooled benzaldehyde acquired using two-color laser ionization mass spectrometry techniques is interpreted with the aid of these calculations. The spectrum is dominated by the origin band and by transitions involving some of the ring modes consistent with the results of the molecular orbital calculations that indicate that the major geometric changes on excitation to S2 are located in the aromatic ring. Ten fundamental vibrations of the S2(/pi/pi/sp/*) state are assigned. The dissociation dynamics of benzaldehyde into benzene and carbon monoxide following excitation to its S2(/pi/pi/sp/*) state are investigated under jet- cooled conditions by two-color laser ionization mass spectrometry using a pump-probe technique. This experimental arrangement allows monitoring the benzaldehyde reactant and the benzene product ion signals as a function of the time delay between the excitation and ionization steps. A kinetic model is proposed to explain the observed biexponential decay of the benzaldehyde signal and the single exponential growth of the benzene product signal in terms of a sequential decay of two excited states of benzaldehyde, one of which leads to formation of benzene molecules in its lowest triplet state. Reactant disappearance and product appearance rates are determined for a number of vibronic transitions of the S2 state. They are found to increase with excitation energy without any indication
DEFF Research Database (Denmark)
Jensen, Finn Verner; Nielsen, Thomas Dyhre
2016-01-01
Mathematically, a Bayesian graphical model is a compact representation of the joint probability distribution for a set of variables. The most frequently used type of Bayesian graphical models are Bayesian networks. The structural part of a Bayesian graphical model is a graph consisting of nodes...
Solar, M; Binder, K; Paul, W
2017-05-28
Molecular dynamics simulations of a chemically realistic model for 1,4-polybutadiene in a thin film geometry confined by two graphite walls are presented. Previous work on melts in the bulk has shown that the model faithfully reproduces static and dynamic properties of the real material over a wide temperature range. The present work studies how these properties change due to nano-confinement. The focus is on orientational correlations observable in nuclear magnetic resonance experiments and on the local intermediate incoherent neutron scattering function, F s (q z , z, t), for distances z from the graphite walls in the range of a few nanometers. Temperatures from about 2T g down to about 1.15T g , where T g is the glass transition temperature in the bulk, are studied. It is shown that weakly attractive forces between the wall atoms and the monomers suffice to effectively bind a polymer coil that is near the wall. For a wide regime of temperatures, the Arrhenius-like adsorption/desorption kinetics of the monomers is the slowest process, while very close to T g the Vogel-Fulcher-Tammann-like α-relaxation takes over. The α-process is modified only for z≤1.2 nm due to the density changes near the walls, less than expected from studies of coarse-grained (bead-spring-type) models. The weakness of the surface effects on the glass transition in this case is attributed to the interplay of density changes near the wall with the torsional potential. A brief discussion of pertinent experiments is given.
Molecular potentials and relaxation dynamics
International Nuclear Information System (INIS)
Karo, A.M.
1981-01-01
The use of empirical pseudopotentials, in evaluating interatomic potentials, provides an inexpensive and convenient method for obtaining highly accurate potential curves and permits the modeling of core-valence correlation, and the inclusion of relativistic effects when these are significant. As an example, recent calculations of the chi 1 Σ + and a 3 Σ + states of LiH, NaH, KH, RbH, and CsH and the chi 2 Σ + states of their anions are discussed. Pseudopotentials, including core polarization terms, have been used to replace the core electrons, and this has been coupled with the development of compact, highly-optimized basis sets for the corresponding one- and two-electron atoms. Comparisons of the neutral potential curves with experiment and other ab initio calculations show good agreement (within 1000 cm -1 over most of the potential curves) with the difference curves being considerably more accurate
Introduction to Bayesian statistics
Bolstad, William M
2017-01-01
There is a strong upsurge in the use of Bayesian methods in applied statistical analysis, yet most introductory statistics texts only present frequentist methods. Bayesian statistics has many important advantages that students should learn about if they are going into fields where statistics will be used. In this Third Edition, four newly-added chapters address topics that reflect the rapid advances in the field of Bayesian staistics. The author continues to provide a Bayesian treatment of introductory statistical topics, such as scientific data gathering, discrete random variables, robust Bayesian methods, and Bayesian approaches to inferenfe cfor discrete random variables, bionomial proprotion, Poisson, normal mean, and simple linear regression. In addition, newly-developing topics in the field are presented in four new chapters: Bayesian inference with unknown mean and variance; Bayesian inference for Multivariate Normal mean vector; Bayesian inference for Multiple Linear RegressionModel; and Computati...
Bayesian artificial intelligence
Korb, Kevin B
2010-01-01
Updated and expanded, Bayesian Artificial Intelligence, Second Edition provides a practical and accessible introduction to the main concepts, foundation, and applications of Bayesian networks. It focuses on both the causal discovery of networks and Bayesian inference procedures. Adopting a causal interpretation of Bayesian networks, the authors discuss the use of Bayesian networks for causal modeling. They also draw on their own applied research to illustrate various applications of the technology.New to the Second EditionNew chapter on Bayesian network classifiersNew section on object-oriente
Bayesian artificial intelligence
Korb, Kevin B
2003-01-01
As the power of Bayesian techniques has become more fully realized, the field of artificial intelligence has embraced Bayesian methodology and integrated it to the point where an introduction to Bayesian techniques is now a core course in many computer science programs. Unlike other books on the subject, Bayesian Artificial Intelligence keeps mathematical detail to a minimum and covers a broad range of topics. The authors integrate all of Bayesian net technology and learning Bayesian net technology and apply them both to knowledge engineering. They emphasize understanding and intuition but also provide the algorithms and technical background needed for applications. Software, exercises, and solutions are available on the authors' website.
Characteristic imsets for learning Bayesian network structure
Czech Academy of Sciences Publication Activity Database
Hemmecke, R.; Lindner, S.; Studený, Milan
2012-01-01
Roč. 53, č. 9 (2012), s. 1336-1349 ISSN 0888-613X R&D Projects: GA MŠk(CZ) 1M0572; GA ČR GA201/08/0539 Institutional support: RVO:67985556 Keywords : learning Bayesian network structure * essential graph * standard imset * characteristic imset * LP relaxation of a polytope Subject RIV: BA - General Mathematics Impact factor: 1.729, year: 2012 http://library.utia.cas.cz/separaty/2012/MTR/studeny-0382596.pdf
Relaxed Poisson cure rate models.
Rodrigues, Josemar; Cordeiro, Gauss M; Cancho, Vicente G; Balakrishnan, N
2016-03-01
The purpose of this article is to make the standard promotion cure rate model (Yakovlev and Tsodikov, ) more flexible by assuming that the number of lesions or altered cells after a treatment follows a fractional Poisson distribution (Laskin, ). It is proved that the well-known Mittag-Leffler relaxation function (Berberan-Santos, ) is a simple way to obtain a new cure rate model that is a compromise between the promotion and geometric cure rate models allowing for superdispersion. So, the relaxed cure rate model developed here can be considered as a natural and less restrictive extension of the popular Poisson cure rate model at the cost of an additional parameter, but a competitor to negative-binomial cure rate models (Rodrigues et al., ). Some mathematical properties of a proper relaxed Poisson density are explored. A simulation study and an illustration of the proposed cure rate model from the Bayesian point of view are finally presented. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Yuan, Ying; MacKinnon, David P.
2009-01-01
This article proposes Bayesian analysis of mediation effects. Compared to conventional frequentist mediation analysis, the Bayesian approach has several advantages. First, it allows researchers to incorporate prior information into the mediation analysis, thus potentially improving the efficiency of estimates. Second, under the Bayesian mediation analysis, inference is straightforward and exact, which makes it appealing for studies with small samples. Third, the Bayesian approach is conceptua...
Marsman, M.; Wagenmakers, E.-J.
2017-01-01
We illustrate the Bayesian approach to data analysis using the newly developed statistical software program JASP. With JASP, researchers are able to take advantage of the benefits that the Bayesian framework has to offer in terms of parameter estimation and hypothesis testing. The Bayesian
Kenkre, V. M.; Chase, M.
2017-08-01
The approach to equilibrium of a quantum mechanical system in interaction with a bath is studied from a practical as well as a conceptual point of view. Explicit memory functions are derived for given models of bath couplings. If the system is a harmonic oscillator representing a molecule in interaction with a reservoir, the generalized master equation derived becomes an extension into the coherent domain of the well-known Montroll-Shuler equation for vibrational relaxation and unimolecular dissociation. A generalization of the Bethe-Teller result regarding energy relaxation is found for short times. The theory has obvious applications to relaxation dynamics at ultra-short times as in observations on the femtosecond time scale and to the investigation of quantum coherence at those short times. While vibrational relaxation in chemical physics is a primary target of the study, another system of interest in condensed matter physics, an electron or hole in a lattice subjected to a strong DC electric field that gives rise to well-known Wannier-Stark ladders, is naturally addressed with the theory. Specific system-bath interactions are explored to obtain explicit details of the dynamics. General phenomenological descriptions of the reservoir are considered rather than specific microscopic realizations.
Directory of Open Access Journals (Sweden)
Nima Kasraie
2011-01-01
Full Text Available The aims of this study were to determine whether standard extracellular contrast agents of Gd(III ions in combination with a polymeric entity susceptible to hydrolytic degradation over a finite period of time, such as Hyaluronic Acid (HA, have sufficient vascular residence time to obtain comparable vascular imaging to current conventional compounds and to obtain sufficient data to show proof of concept that HA with Gd-DTPA ligands could be useful as vascular imaging agents. We assessed the dynamic relaxivity of the HA bound DTPA compounds using a custom-made phantom, as well as relaxation rates at 10.72 MHz with concentrations ranging between 0.09 and 7.96 mM in phosphate-buffered saline. Linear dependences of static longitudinal relaxation rate (R1 on concentration were found for most measured samples, and the HA samples continued to produce high signal strength after 24 hours after injection into a dialysis cassette at 3T, showing superior dynamic relaxivity values compared to conventional contrast media such as Gd-DTPA-BMA.
International Nuclear Information System (INIS)
Bolkhovityanov, Yu. B.; Deryabin, A. S.; Gutakovskii, A. K.; Kolesnikov, A. V.; Sokolov, L. V.
2007-01-01
Plastically relaxed GeSi films with the Ge fraction equal to 0.29-0.42 and thickness as large as 0.5 μm were grown on Si (001) substrates using the low-temperature (350 deg. C) buffer Si layer and Sb as a surfactant. It is shown that introduction of Sb that smoothens the film surface at the stage of pseudomorphic growth lowers the density of threading dislocations in the plastically relaxed heterostructure by 1-1.5 orders of magnitude and also reduces the final roughness of the surface. The root-mean-square value of roughness smaller than 1 nm was obtained for a film with the Ge content of 0.29 and the density of threading dislocations of about 10 6 cm -2 . It is assumed that the effect of surfactant is based on the fact that the activity of surface sources of dislocations is reduced in the presence of Sb
Non-monotonic behaviour in relaxation dynamics of image restoration
International Nuclear Information System (INIS)
Ozeki, Tomoko; Okada, Masato
2003-01-01
We have investigated the relaxation dynamics of image restoration through a Bayesian approach. The relaxation dynamics is much faster at zero temperature than at the Nishimori temperature where the pixel-wise error rate is minimized in equilibrium. At low temperature, we observed non-monotonic development of the overlap. We suggest that the optimal performance is realized through premature termination in the relaxation processes in the case of the infinite-range model. We also performed Markov chain Monte Carlo simulations to clarify the underlying mechanism of non-trivial behaviour at low temperature by checking the local field distributions of each pixel
... Find a Doctor Relaxation is the absence of tension in muscle groups and a minimum or absence ... Drill Meditation Progressive Muscle Relaxation Minimizing Shortness of Breath Visualization This information has been approved by Shelby ...
Understanding Computational Bayesian Statistics
Bolstad, William M
2011-01-01
A hands-on introduction to computational statistics from a Bayesian point of view Providing a solid grounding in statistics while uniquely covering the topics from a Bayesian perspective, Understanding Computational Bayesian Statistics successfully guides readers through this new, cutting-edge approach. With its hands-on treatment of the topic, the book shows how samples can be drawn from the posterior distribution when the formula giving its shape is all that is known, and how Bayesian inferences can be based on these samples from the posterior. These ideas are illustrated on common statistic
Bayesian statistics an introduction
Lee, Peter M
2012-01-01
Bayesian Statistics is the school of thought that combines prior beliefs with the likelihood of a hypothesis to arrive at posterior beliefs. The first edition of Peter Lee’s book appeared in 1989, but the subject has moved ever onwards, with increasing emphasis on Monte Carlo based techniques. This new fourth edition looks at recent techniques such as variational methods, Bayesian importance sampling, approximate Bayesian computation and Reversible Jump Markov Chain Monte Carlo (RJMCMC), providing a concise account of the way in which the Bayesian approach to statistics develops as wel
Relationship between Structural and Stress Relaxation in a Block-Copolymer Melt
International Nuclear Information System (INIS)
Patel, Amish J.; Narayanan, Suresh; Sandy, Alec; Mochrie, Simon G. J.; Garetz, Bruce A.; Watanabe, Hiroshi; Balsara, Nitash P.
2006-01-01
The relationship between structural relaxation on molecular length scales and macroscopic stress relaxation was explored in a disordered block-copolymer melt. Experiments show that the structural relaxation time, measured by x-ray photon correlation spectroscopy is larger than the terminal stress relaxation time, measured by rheology, by factors as large as 100. We demonstrate that the structural relaxation data are dominated by the diffusion of intact micelles while the stress relaxation data are dominated by contributions due to disordered concentration fluctuations
Relaxation dynamics following transition of solvated electrons
International Nuclear Information System (INIS)
Barnett, R.B.; Landman, U.; Nitzan, A.
1989-01-01
Relaxation dynamics following an electronic transition of an excess solvated electron in clusters and in bulk water is studied using an adiabatic simulation method. In this method the solvent evolves classically and the electron is constrained to a specified state. The coupling between the solvent and the excess electron is evaluated via the quantum expectation value of the electron--water molecule interaction potential. The relaxation following excitation (or deexcitation) is characterized by two time scales: (i) a very fast (/similar to/20--30 fs) one associated with molecular rotations in the first solvation shell about the electron, and (ii) a slower stage (/similar to/200 fs), which is of the order of the longitudinal dielectric relaxation time. The fast relaxation stage exhibits an isotope effect. The spectroscopical consequences of the relaxation dynamics are discussed
Vibrational and Rotational Energy Relaxation in Liquids
DEFF Research Database (Denmark)
Petersen, Jakob
Vibrational and rotational energy relaxation in liquids are studied by means of computer simulations. As a precursor for studying vibrational energy relaxation of a solute molecule subsequent to the formation of a chemical bond, the validity of the classical Bersohn-Zewail model for describing......, the vibrational energy relaxation of I2 subsequent to photodissociation and recombination in CCl4 is studied using classical Molecular Dynamics simulations. The vibrational relaxation times and the time-dependent I-I pair distribution function are compared to new experimental results, and a qualitative agreement...... is found in both cases. Furthermore, the rotational energy relaxation of H2O in liquid water is studied via simulations and a power-and-work analysis. The mechanism of the energy transfer from the rotationally excited H2O molecule to its water neighbors is elucidated, i.e. the energy-accepting degrees...
Ngai, K. L.; Paluch, M.
2017-12-01
Successful thermodynamic scaling of the structural alpha-relaxation time or transport coefficients of glass-forming liquids determined at various temperatures T and pressures P means the data conform to a single function of the product variable TVgamma, where V is the specific volume and gamma is a material specific constant. In the past two decades we have witnessed successful TVgamma-scaling in many molecular, polymeric, and even metallic glass-formers, and gamma is related to the slope of the repulsive part of the intermolecular potential. The advances made indicate TVgamma-scaling is an important aspect of the dynamic and thermodynamic properties of glass-formers. In this paper we show the origin of TVgamma-scaling is not from the structural alpha-relaxation time. Instead it comes from its precursor, the Johari-Goldstein beta-relaxation or the primitive relaxation of the Coupling Model and their relaxation times or tau_0 respectively. It is remarkable that all relaxation times are functions of TVgamma with the same gama, as well as the fractional exponent of the Kohlrausch correlation function of the structural alpha-relaxation. We arrive at this conclusion convincingly based on corroborative evidences from a number of experiments and molecular dynamics simulations performed on a wide variety of glass-formers and in conjunction with consistency with the predictions of the Coupling Model.
Regularities of intermediate adsorption complex relaxation
International Nuclear Information System (INIS)
Manukova, L.A.
1982-01-01
The experimental data, characterizing the regularities of intermediate adsorption complex relaxation in the polycrystalline Mo-N 2 system at 77 K are given. The method of molecular beam has been used in the investigation. The analytical expressions of change regularity in the relaxation process of full and specific rates - of transition from intermediate state into ''non-reversible'', of desorption into the gas phase and accumUlation of the particles in the intermediate state are obtained
Yuan, Ying; MacKinnon, David P.
2009-01-01
In this article, we propose Bayesian analysis of mediation effects. Compared with conventional frequentist mediation analysis, the Bayesian approach has several advantages. First, it allows researchers to incorporate prior information into the mediation analysis, thus potentially improving the efficiency of estimates. Second, under the Bayesian…
Kleibergen, F.R.; Kleijn, R.; Paap, R.
2000-01-01
We propose a novel Bayesian test under a (noninformative) Jeffreys'priorspecification. We check whether the fixed scalar value of the so-calledBayesian Score Statistic (BSS) under the null hypothesis is aplausiblerealization from its known and standardized distribution under thealternative. Unlike
Universal Mechanism of Spin Relaxation in Solids
Chudnovsky, Eugene
2006-03-01
Conventional elastic theory ignores internal local twists and torques. Meantime, spin-lattice relaxation is inherently coupled with local elastic twists through conservation of the total angular momentum (spin + lattice). This coupling gives universal lower bound (free of fitting parameters) on the relaxation of the atomic or molecular spin in a solid [1] and on the relaxation of the electron spin in a quantum dot [2]. [1] E. M. Chudnovsky, D. A. Garanin, and R. Schilling, Phys. Rev. B 72, 094426 (2005). [2] C. Calero, E. M. Chudnovsky, and D. A. Garanin, Phys. Rev. Lett. 95, 166603 (2005).
Stress relaxation of bi-disperse polystyrene melts
DEFF Research Database (Denmark)
Hengeller, Ludovica; Huang, Qian; Dorokhin, Andriy
2016-01-01
We present start-up of uniaxial extension followed by stress relaxation experiments of a bi-disperse 50 % by weight blend of 95k and 545k molecular weight polystyrene. We also show, for comparison, stress relaxation measurements of the polystyrene melts with molecular weight 95k and 545k, which...... are the components of the bi-disperse melt. The measurements show three separated relaxation regimes: a fast regime, a transition regime, and a slow regime. In the fast regime, the orientation of the long chains is frozen and the stress relaxation is due to stretch relaxation of the short chains primarily....... Conversely in the slow regime, the long chains have retracted and undergo relaxation of orientation in fully relaxed short chains....
von der Linden, Wolfgang; Dose, Volker; von Toussaint, Udo
2014-06-01
Preface; Part I. Introduction: 1. The meaning of probability; 2. Basic definitions; 3. Bayesian inference; 4. Combinatrics; 5. Random walks; 6. Limit theorems; 7. Continuous distributions; 8. The central limit theorem; 9. Poisson processes and waiting times; Part II. Assigning Probabilities: 10. Transformation invariance; 11. Maximum entropy; 12. Qualified maximum entropy; 13. Global smoothness; Part III. Parameter Estimation: 14. Bayesian parameter estimation; 15. Frequentist parameter estimation; 16. The Cramer-Rao inequality; Part IV. Testing Hypotheses: 17. The Bayesian way; 18. The frequentist way; 19. Sampling distributions; 20. Bayesian vs frequentist hypothesis tests; Part V. Real World Applications: 21. Regression; 22. Inconsistent data; 23. Unrecognized signal contributions; 24. Change point problems; 25. Function estimation; 26. Integral equations; 27. Model selection; 28. Bayesian experimental design; Part VI. Probabilistic Numerical Techniques: 29. Numerical integration; 30. Monte Carlo methods; 31. Nested sampling; Appendixes; References; Index.
Energy Technology Data Exchange (ETDEWEB)
Wang, Wei; Zhou, Qian; Dong, Yuan; Yeo, Yee-Chia, E-mail: yeo@ieee.org [Department of Electrical and Computer Engineering, National University of Singapore, Singapore 117576 (Singapore); Tok, Eng Soon [Department of Physics, National University of Singapore, Singapore 117551 (Singapore)
2015-06-08
We investigated the critical thickness (h{sub c}) for plastic relaxation of Ge{sub 1−x}Sn{sub x} grown by molecular beam epitaxy. Ge{sub 1−x}Sn{sub x} films with various Sn mole fraction x (x ≤ 0.17) and different thicknesses were grown on Ge(001). The strain relaxation of Ge{sub 1−x}Sn{sub x} films and the h{sub c} were investigated by high-resolution x-ray diffraction and reciprocal space mapping. It demonstrates that the measured h{sub c} values of Ge{sub 1−x}Sn{sub x} layers are as much as an order of magnitude larger than that predicted by the Matthews and Blakeslee (M-B) model. The People and Bean (P-B) model was also used to predict the h{sub c} values in Ge{sub 1−x}Sn{sub x}/Ge system. The measured h{sub c} values for various Sn content follow the trend, but slightly larger than that predicted by the P-B model.
Structure-based bayesian sparse reconstruction
Quadeer, Ahmed Abdul
2012-12-01
Sparse signal reconstruction algorithms have attracted research attention due to their wide applications in various fields. In this paper, we present a simple Bayesian approach that utilizes the sparsity constraint and a priori statistical information (Gaussian or otherwise) to obtain near optimal estimates. In addition, we make use of the rich structure of the sensing matrix encountered in many signal processing applications to develop a fast sparse recovery algorithm. The computational complexity of the proposed algorithm is very low compared with the widely used convex relaxation methods as well as greedy matching pursuit techniques, especially at high sparsity. © 1991-2012 IEEE.
Mechanical relaxation in glasses
International Nuclear Information System (INIS)
Hiki, Y.
2004-01-01
The basic properties of glasses and the characteristics of mechanical relaxation in glasses were briefly reviewed, and then our studies concerned were presented. Experimental methods adopted were viscosity, internal friction, ultrasonic attenuation, and Brillouin scattering measurements. The specimens used were several kinds of inorganic, organic, and metallic glasses. The measurements were mainly carried out from the room temperature up to the glass transition temperature, and the relaxation time was determined as a function of temperature. The 'double relaxation' composed of two Arrhenius-type relaxations was observed in many materials. In both relaxations, the 'compensation effect' showing a correlation of the pre-exponential factor and the activation energy was observed. These results were explained by considering the 'complex relaxation' due to cooperative motions of atoms or group of atoms. Values of activation energy near the glass transition determined by the various experimental methods were compared with each other
Albert, Jim
2009-01-01
There has been a dramatic growth in the development and application of Bayesian inferential methods. Some of this growth is due to the availability of powerful simulation-based algorithms to summarize posterior distributions. There has been also a growing interest in the use of the system R for statistical analyses. R's open source nature, free availability, and large number of contributor packages have made R the software of choice for many statisticians in education and industry. Bayesian Computation with R introduces Bayesian modeling by the use of computation using the R language. The earl
Dlubek, G; Shaikh, M Q; Rätzke, K; Paluch, M; Faupel, F
2010-06-16
Positron annihilation lifetime spectroscopy (PALS) is employed to characterize the temperature dependence of the free volume in two van der Waals liquids: 1, 1'-bis(p-methoxyphenyl)cyclohexane (BMPC) and 1, 1'-di(4-methoxy-5-methylphenyl)cyclohexane (BMMPC). From the PALS spectra analysed with the routine LifeTime9.0, the size (volume) distribution of local free volumes (subnanometer size holes), its mean, [v(h)], and mean dispersion, σ(h), were calculated. A comparison with the macroscopic volume from pressure-volume-temperature (PV T) experiments delivered the hole density and the specific hole free volume and a complete characterization of the free volume microstructure in that sense. These data are used in correlation with structural (α) relaxation data from broad-band dielectric spectroscopy (BDS) in terms of the Cohen-Grest and Cohen-Turnbull free volume models. An extension of the latter model allows us to quantify deviations between experiments and theory and an attempt to systematize these in terms of T(g) or of the fragility. The experimental data for several fragile and less fragile glass formers are involved in the final discussion. It was concluded that, for large differences in the fragility of different glass formers, the positron lifetime mirrors clearly the different character of these materials. For small differences in the fragility, additional properties like the character of bonds and chemical structure of the material may affect size, distribution and thermal behaviour of the free volume.
Energy Technology Data Exchange (ETDEWEB)
Dlubek, G [ITA Institute for Innovative Technologies, Koethen/Halle, Wiesenring 4, D-06120 Lieskau (Germany); Shaikh, M Q; Raetzke, K; Faupel, F [Faculty of Engineering, Institute for Materials Science, Christian-Albrechts University of Kiel, Kaiserstrasse 2, D-24143 Kiel (Germany); Paluch, M, E-mail: guenter.dlubek@gmx.d [Institute of Physics, Silesian University, Uniwersytecka 4, 40-007 Katowice (Poland)
2010-06-16
Positron annihilation lifetime spectroscopy (PALS) is employed to characterize the temperature dependence of the free volume in two van der Waals liquids: 1, 1'-bis(p-methoxyphenyl)cyclohexane (BMPC) and 1, 1'-di(4-methoxy-5-methylphenyl)cyclohexane (BMMPC). From the PALS spectra analysed with the routine LifeTime9.0, the size (volume) distribution of local free volumes (subnanometer size holes), its mean, (v{sub h}), and mean dispersion, {sigma}{sub h}, were calculated. A comparison with the macroscopic volume from pressure-volume-temperature (PV T) experiments delivered the hole density and the specific hole free volume and a complete characterization of the free volume microstructure in that sense. These data are used in correlation with structural ({alpha}) relaxation data from broad-band dielectric spectroscopy (BDS) in terms of the Cohen-Grest and Cohen-Turnbull free volume models. An extension of the latter model allows us to quantify deviations between experiments and theory and an attempt to systematize these in terms of T{sub g} or of the fragility. The experimental data for several fragile and less fragile glass formers are involved in the final discussion. It was concluded that, for large differences in the fragility of different glass formers, the positron lifetime mirrors clearly the different character of these materials. For small differences in the fragility, additional properties like the character of bonds and chemical structure of the material may affect size, distribution and thermal behaviour of the free volume.
Bayesian data analysis for newcomers.
Kruschke, John K; Liddell, Torrin M
2018-02-01
This article explains the foundational concepts of Bayesian data analysis using virtually no mathematical notation. Bayesian ideas already match your intuitions from everyday reasoning and from traditional data analysis. Simple examples of Bayesian data analysis are presented that illustrate how the information delivered by a Bayesian analysis can be directly interpreted. Bayesian approaches to null-value assessment are discussed. The article clarifies misconceptions about Bayesian methods that newcomers might have acquired elsewhere. We discuss prior distributions and explain how they are not a liability but an important asset. We discuss the relation of Bayesian data analysis to Bayesian models of mind, and we briefly discuss what methodological problems Bayesian data analysis is not meant to solve. After you have read this article, you should have a clear sense of how Bayesian data analysis works and the sort of information it delivers, and why that information is so intuitive and useful for drawing conclusions from data.
Relaxation characteristics of hastelloy X
International Nuclear Information System (INIS)
Suzuki, Kazuhiko
1980-02-01
Relaxation diagrams of Hastelloy X (relaxation curves, relaxation design diagrams, etc.) were generated from the creep constitutive equation of Hastelloy X, using inelastic stress analysis code TEPICC-J. These data are in good agreement with experimental relaxation data of ORNL-5479. Three typical inelastic stress analyses were performed for various relaxation behaviors of the high-temperature structures. An attempt was also made to predict these relaxation behaviors by the relaxation curves. (author)
Bayesian methods for data analysis
Carlin, Bradley P.
2009-01-01
Approaches for statistical inference Introduction Motivating Vignettes Defining the Approaches The Bayes-Frequentist Controversy Some Basic Bayesian Models The Bayes approach Introduction Prior Distributions Bayesian Inference Hierarchical Modeling Model Assessment Nonparametric Methods Bayesian computation Introduction Asymptotic Methods Noniterative Monte Carlo Methods Markov Chain Monte Carlo Methods Model criticism and selection Bayesian Modeling Bayesian Robustness Model Assessment Bayes Factors via Marginal Density Estimation Bayes Factors
Noncausal Bayesian Vector Autoregression
DEFF Research Database (Denmark)
Lanne, Markku; Luoto, Jani
We propose a Bayesian inferential procedure for the noncausal vector autoregressive (VAR) model that is capable of capturing nonlinearities and incorporating effects of missing variables. In particular, we devise a fast and reliable posterior simulator that yields the predictive distribution...
Statistics: a Bayesian perspective
National Research Council Canada - National Science Library
Berry, Donald A
1996-01-01
...: it is the only introductory textbook based on Bayesian ideas, it combines concepts and methods, it presents statistics as a means of integrating data into the significant process, it develops ideas...
Fox, Gerardus J.A.; van den Berg, Stéphanie Martine; Veldkamp, Bernard P.; Irwing, P.; Booth, T.; Hughes, D.
2015-01-01
In educational and psychological studies, psychometric methods are involved in the measurement of constructs, and in constructing and validating measurement instruments. Assessment results are typically used to measure student proficiency levels and test characteristics. Recently, Bayesian item
Bayesian Networks An Introduction
Koski, Timo
2009-01-01
Bayesian Networks: An Introduction provides a self-contained introduction to the theory and applications of Bayesian networks, a topic of interest and importance for statisticians, computer scientists and those involved in modelling complex data sets. The material has been extensively tested in classroom teaching and assumes a basic knowledge of probability, statistics and mathematics. All notions are carefully explained and feature exercises throughout. Features include:.: An introduction to Dirichlet Distribution, Exponential Families and their applications.; A detailed description of learni
Maeda, Shin-ichi
2014-01-01
Dropout is one of the key techniques to prevent the learning from overfitting. It is explained that dropout works as a kind of modified L2 regularization. Here, we shed light on the dropout from Bayesian standpoint. Bayesian interpretation enables us to optimize the dropout rate, which is beneficial for learning of weight parameters and prediction after learning. The experiment result also encourages the optimization of the dropout.
TEACHING NEUROMUSCULAR RELAXATION.
NORRIS, JEANNE E.; STEINHAUS, ARTHUR H.
THIS STUDY ATTEMPTED TO FIND OUT WHETHER (1) THE METHODS FOR ATTAINING NEUROMUSCULAR RELAXATION THAT HAVE PROVED FRUITFUL IN THE ONE-TO-ONE RELATIONSHIP OF THE CLINIC CAN BE SUCCESSFULLY ADAPTED TO THE TEACHER-CLASS RELATIONSHIP OF THE CLASSROOM AND GYMNASIUM, AND (2) NEUROMUSCULAR RELAXATION CAN BE TAUGHT SUCCESSFULLY BY AN APPROPRIATELY TRAINED…
Relaxation of Anisotropic Glasses
DEFF Research Database (Denmark)
Deubener, Joachim; Martin, Birgit; Wondraczek, Lothar
2004-01-01
. When the load was removed at room temperature a permanent optical anisotropy (birefringence) was observed only perpendicular to cylinder axis and the pressure direction indicating complete elimination of thermal stresses. Relaxation of structural anisotropy was studied from reheating experiments using...... the energy release, thermo-mechanical and optical relaxation behaviour are drawn....
Relaxation techniques for stress
... raise your heart rate. This is called the stress response. Relaxation techniques can help your body relax and lower your blood pressure ... also many other types of breathing techniques you can learn. In many cases, you do not need much ... including those that cause stress. Meditation has been practiced for thousands of years, ...
Ghosh, Sujit K
2010-01-01
Bayesian methods are rapidly becoming popular tools for making statistical inference in various fields of science including biology, engineering, finance, and genetics. One of the key aspects of Bayesian inferential method is its logical foundation that provides a coherent framework to utilize not only empirical but also scientific information available to a researcher. Prior knowledge arising from scientific background, expert judgment, or previously collected data is used to build a prior distribution which is then combined with current data via the likelihood function to characterize the current state of knowledge using the so-called posterior distribution. Bayesian methods allow the use of models of complex physical phenomena that were previously too difficult to estimate (e.g., using asymptotic approximations). Bayesian methods offer a means of more fully understanding issues that are central to many practical problems by allowing researchers to build integrated models based on hierarchical conditional distributions that can be estimated even with limited amounts of data. Furthermore, advances in numerical integration methods, particularly those based on Monte Carlo methods, have made it possible to compute the optimal Bayes estimators. However, there is a reasonably wide gap between the background of the empirically trained scientists and the full weight of Bayesian statistical inference. Hence, one of the goals of this chapter is to bridge the gap by offering elementary to advanced concepts that emphasize linkages between standard approaches and full probability modeling via Bayesian methods.
Bayesian phylogeography finds its roots.
Directory of Open Access Journals (Sweden)
Philippe Lemey
2009-09-01
Full Text Available As a key factor in endemic and epidemic dynamics, the geographical distribution of viruses has been frequently interpreted in the light of their genetic histories. Unfortunately, inference of historical dispersal or migration patterns of viruses has mainly been restricted to model-free heuristic approaches that provide little insight into the temporal setting of the spatial dynamics. The introduction of probabilistic models of evolution, however, offers unique opportunities to engage in this statistical endeavor. Here we introduce a Bayesian framework for inference, visualization and hypothesis testing of phylogeographic history. By implementing character mapping in a Bayesian software that samples time-scaled phylogenies, we enable the reconstruction of timed viral dispersal patterns while accommodating phylogenetic uncertainty. Standard Markov model inference is extended with a stochastic search variable selection procedure that identifies the parsimonious descriptions of the diffusion process. In addition, we propose priors that can incorporate geographical sampling distributions or characterize alternative hypotheses about the spatial dynamics. To visualize the spatial and temporal information, we summarize inferences using virtual globe software. We describe how Bayesian phylogeography compares with previous parsimony analysis in the investigation of the influenza A H5N1 origin and H5N1 epidemiological linkage among sampling localities. Analysis of rabies in West African dog populations reveals how virus diffusion may enable endemic maintenance through continuous epidemic cycles. From these analyses, we conclude that our phylogeographic framework will make an important asset in molecular epidemiology that can be easily generalized to infer biogeogeography from genetic data for many organisms.
The relaxation time approximation
International Nuclear Information System (INIS)
Gairola, R.P.; Indu, B.D.
1991-01-01
A plausible approximation has been made to estimate the relaxation time from a knowledge of the transition probability of phonons from one state (r vector, q vector) to other state (r' vector, q' vector), as a result of collision. The relaxation time, thus obtained, shows a strong dependence on temperature and weak dependence on the wave vector. In view of this dependence, relaxation time has been expressed in terms of a temperature Taylor's series in the first Brillouin zone. Consequently, a simple model for estimating the thermal conductivity is suggested. the calculations become much easier than the Callaway model. (author). 14 refs
Bayesian networks with examples in R
Scutari, Marco
2014-01-01
Introduction. The Discrete Case: Multinomial Bayesian Networks. The Continuous Case: Gaussian Bayesian Networks. More Complex Cases. Theory and Algorithms for Bayesian Networks. Real-World Applications of Bayesian Networks. Appendices. Bibliography.
Dielectric Relaxation Studies of Alkyl Methacrylate–Phenol Mixtures ...
African Journals Online (AJOL)
The Kirkwood correlation factor and the excess inverse relaxation time were determined and they yield information on the molecular interactions occurring in the systems. The values of the static permittivity and the relaxation time increase with an increase in the percentage of phenol in the mixtures. KEYWORDS: Dielectric ...
Stress relaxation in viscous soft spheres.
Boschan, Julia; Vasudevan, Siddarth A; Boukany, Pouyan E; Somfai, Ellák; Tighe, Brian P
2017-10-04
We report the results of molecular dynamics simulations of stress relaxation tests in athermal viscous soft sphere packings close to their unjamming transition. By systematically and simultaneously varying both the amplitude of the applied strain step and the pressure of the initial condition, we access both linear and nonlinear response regimes and control the distance to jamming. Stress relaxation in viscoelastic solids is characterized by a relaxation time τ* that separates short time scales, where viscous loss is substantial, from long time scales, where elastic storage dominates and the response is essentially quasistatic. We identify two distinct plateaus in the strain dependence of the relaxation time, one each in the linear and nonlinear regimes. The height of both plateaus scales as an inverse power law with the distance to jamming. By probing the time evolution of particle velocities during relaxation, we further identify a correlation between mechanical relaxation in the bulk and the degree of non-affinity in the particle velocities on the micro scale.
Bayesian methods in reliability
Sander, P.; Badoux, R.
1991-11-01
The present proceedings from a course on Bayesian methods in reliability encompasses Bayesian statistical methods and their computational implementation, models for analyzing censored data from nonrepairable systems, the traits of repairable systems and growth models, the use of expert judgment, and a review of the problem of forecasting software reliability. Specific issues addressed include the use of Bayesian methods to estimate the leak rate of a gas pipeline, approximate analyses under great prior uncertainty, reliability estimation techniques, and a nonhomogeneous Poisson process. Also addressed are the calibration sets and seed variables of expert judgment systems for risk assessment, experimental illustrations of the use of expert judgment for reliability testing, and analyses of the predictive quality of software-reliability growth models such as the Weibull order statistics.
CSIR Research Space (South Africa)
Rosman, Benjamin
2016-02-01
Full Text Available Keywords Policy Reuse · Reinforcement Learning · Online Learning · Online Bandits · Transfer Learning · Bayesian Optimisation · Bayesian Decision Theory. 1 Introduction As robots and software agents are becoming more ubiquitous in many applications.... The agent has access to a library of policies (pi1, pi2 and pi3), and has previously experienced a set of task instances (τ1, τ2, τ3, τ4), as well as samples of the utilities of the library policies on these instances (the black dots indicate the means...
Green--Kubo formula for collisional relaxation
International Nuclear Information System (INIS)
Visscher, P.B.
1988-01-01
In this paper we generalize the Green--Kubo method (usually used for obtaining formulas for transport coefficients involving conserved densities) to relaxation processes occurring during collisions, such as the transfer of energy from vibrational to translational modes in a molecular fluid. We show that the relaxation rate can be calculated without evaluating time correlation functions over long times, and can in fact be written as a sum over collisions which makes the relation between the Green--Kubo method and approximate independent-collision models much clearer
Bayesian methods for hackers probabilistic programming and Bayesian inference
Davidson-Pilon, Cameron
2016-01-01
Bayesian methods of inference are deeply natural and extremely powerful. However, most discussions of Bayesian inference rely on intensely complex mathematical analyses and artificial examples, making it inaccessible to anyone without a strong mathematical background. Now, though, Cameron Davidson-Pilon introduces Bayesian inference from a computational perspective, bridging theory to practice–freeing you to get results using computing power. Bayesian Methods for Hackers illuminates Bayesian inference through probabilistic programming with the powerful PyMC language and the closely related Python tools NumPy, SciPy, and Matplotlib. Using this approach, you can reach effective solutions in small increments, without extensive mathematical intervention. Davidson-Pilon begins by introducing the concepts underlying Bayesian inference, comparing it with other techniques and guiding you through building and training your first Bayesian model. Next, he introduces PyMC through a series of detailed examples a...
Bayesian logistic regression analysis
Van Erp, H.R.N.; Van Gelder, P.H.A.J.M.
2012-01-01
In this paper we present a Bayesian logistic regression analysis. It is found that if one wishes to derive the posterior distribution of the probability of some event, then, together with the traditional Bayes Theorem and the integrating out of nuissance parameters, the Jacobian transformation is an
Korattikara, A.; Rathod, V.; Murphy, K.; Welling, M.; Cortes, C.; Lawrence, N.D.; Lee, D.D.; Sugiyama, M.; Garnett, R.
2015-01-01
We consider the problem of Bayesian parameter estimation for deep neural networks, which is important in problem settings where we may have little data, and/ or where we need accurate posterior predictive densities p(y|x, D), e.g., for applications involving bandits or active learning. One simple
Bayesian Geostatistical Design
DEFF Research Database (Denmark)
Diggle, Peter; Lophaven, Søren Nymand
2006-01-01
locations to, or deletion of locations from, an existing design, and prospective design, which consists of choosing positions for a new set of sampling locations. We propose a Bayesian design criterion which focuses on the goal of efficient spatial prediction whilst allowing for the fact that model...
Bayesian statistical inference
Directory of Open Access Journals (Sweden)
Bruno De Finetti
2017-04-01
Full Text Available This work was translated into English and published in the volume: Bruno De Finetti, Induction and Probability, Biblioteca di Statistica, eds. P. Monari, D. Cocchi, Clueb, Bologna, 1993.Bayesian statistical Inference is one of the last fundamental philosophical papers in which we can find the essential De Finetti's approach to the statistical inference.
DEFF Research Database (Denmark)
Hartelius, Karsten; Carstensen, Jens Michael
2003-01-01
A method for locating distorted grid structures in images is presented. The method is based on the theories of template matching and Bayesian image restoration. The grid is modeled as a deformable template. Prior knowledge of the grid is described through a Markov random field (MRF) model which r...
Bayesian Independent Component Analysis
DEFF Research Database (Denmark)
Winther, Ole; Petersen, Kaare Brandt
2007-01-01
In this paper we present an empirical Bayesian framework for independent component analysis. The framework provides estimates of the sources, the mixing matrix and the noise parameters, and is flexible with respect to choice of source prior and the number of sources and sensors. Inside the engine...
Bayesian Exponential Smoothing.
Forbes, C.S.; Snyder, R.D.; Shami, R.S.
2000-01-01
In this paper, a Bayesian version of the exponential smoothing method of forecasting is proposed. The approach is based on a state space model containing only a single source of error for each time interval. This model allows us to improve current practices surrounding exponential smoothing by providing both point predictions and measures of the uncertainty surrounding them.
Bayesian optimization for materials science
Packwood, Daniel
2017-01-01
This book provides a short and concise introduction to Bayesian optimization specifically for experimental and computational materials scientists. After explaining the basic idea behind Bayesian optimization and some applications to materials science in Chapter 1, the mathematical theory of Bayesian optimization is outlined in Chapter 2. Finally, Chapter 3 discusses an application of Bayesian optimization to a complicated structure optimization problem in computational surface science. Bayesian optimization is a promising global optimization technique that originates in the field of machine learning and is starting to gain attention in materials science. For the purpose of materials design, Bayesian optimization can be used to predict new materials with novel properties without extensive screening of candidate materials. For the purpose of computational materials science, Bayesian optimization can be incorporated into first-principles calculations to perform efficient, global structure optimizations. While re...
Relaxation of the magnetization in magnetic molecules
Carretta, S.; Bianchi, A.; Liviotti, E.; Santini, P.; Amoretti, G.
2006-04-01
Several mechanisms characterize the relaxation dynamics in magnetic molecules. We investigate two of them, spin-lattice coupling and incoherent quantum tunneling. The effect of the phonon heat bath is studied by analyzing the exponential time decay of the autocorrelation of the magnetization. We show that in ferromagnetic (Cu6) and antiferromagnetic (Fe6) molecular rings this decay is characterized by a single characteristic time. At very low temperature, relaxation through incoherent quantum tunneling may occur in nanomagnets such as Fe8 or Ni4. The mixing between levels with different values of the total spin (S mixing) greatly influences this mechanism. In particular, we demonstrate that a fourth-order anisotropy term O44, required to interpret experimental electron paramagnetic resonance and relaxation data in Ni4, naturally arises when S mixing is considered in calculations.
Excited-state relaxation of some aminoquinolines
Directory of Open Access Journals (Sweden)
2006-01-01
Full Text Available The absorption and fluorescence spectra, fluorescence quantum yields and lifetimes, and fluorescence rate constants ( k f of 2-amino-3-( 2 ′ -benzoxazolylquinoline (I, 2-amino-3-( 2 ′ -benzothiazolylquinoline (II, 2-amino-3-( 2 ′ -methoxybenzothiazolyl-quinoline (III, 2-amino-3-( 2 ′ -benzothiazolylbenzoquinoline (IV at different temperatures have been measured. The shortwavelength shift of fluorescence spectra of compounds studied (23–49 nm in ethanol as the temperature decreases (the solvent viscosity increases points out that the excited-state relaxation process takes place. The rate of this process depends essentially on the solvent viscosity, but not the solvent polarity. The essential increasing of fluorescence rate constant k f (up to about 7 times as the solvent viscosity increases proves the existence of excited-state structural relaxation consisting in the mutual internal rotation of molecular fragments of aminoquinolines studied, followed by the solvent orientational relaxation.
Relaxed Binaural LCMV Beamforming
Koutrouvelis, A.; Hendriks, R.C.; Heusdens, R.; Jensen, Jesper Rindom
2017-01-01
In this paper, we propose a new binaural beamforming technique, which can be seen as a relaxation of the linearly constrained minimum variance (LCMV) framework. The proposed method can achieve simultaneous noise reduction and exact binaural cue preservation of the target source, similar to the
Charge Relaxation Dynamics of an Electrolytic Nanocapacitor
2015-01-01
Understanding ion relaxation dynamics in overlapping electric double layers (EDLs) is critical for the development of efficient nanotechnology-based electrochemical energy storage, electrochemomechanical energy conversion, and bioelectrochemical sensing devices as well as the controlled synthesis of nanostructured materials. Here, a lattice Boltzmann (LB) method is employed to simulate an electrolytic nanocapacitor subjected to a step potential at t = 0 for various degrees of EDL overlap, solvent viscosities, ratios of cation-to-anion diffusivity, and electrode separations. The use of a novel continuously varying and Galilean-invariant molecular-speed-dependent relaxation time (MSDRT) with the LB equation recovers a correct microscopic description of the molecular-collision phenomena and enhances the stability of the LB algorithm. Results for large EDL overlaps indicated oscillatory behavior for the ionic current density, in contrast to monotonic relaxation to equilibrium for low EDL overlaps. Further, at low solvent viscosities and large EDL overlaps, anomalous plasmalike spatial oscillations of the electric field were observed that appeared to be purely an effect of nanoscale confinement. Employing MSDRT in our simulations enabled modeling of the fundamental physics of the transient charge relaxation dynamics in electrochemical systems operating away from equilibrium wherein Nernst–Einstein relation is known to be violated. PMID:25678941
Probability and Bayesian statistics
1987-01-01
This book contains selected and refereed contributions to the "Inter national Symposium on Probability and Bayesian Statistics" which was orga nized to celebrate the 80th birthday of Professor Bruno de Finetti at his birthplace Innsbruck in Austria. Since Professor de Finetti died in 1985 the symposium was dedicated to the memory of Bruno de Finetti and took place at Igls near Innsbruck from 23 to 26 September 1986. Some of the pa pers are published especially by the relationship to Bruno de Finetti's scientific work. The evolution of stochastics shows growing importance of probability as coherent assessment of numerical values as degrees of believe in certain events. This is the basis for Bayesian inference in the sense of modern statistics. The contributions in this volume cover a broad spectrum ranging from foundations of probability across psychological aspects of formulating sub jective probability statements, abstract measure theoretical considerations, contributions to theoretical statistics an...
DEFF Research Database (Denmark)
Mørup, Morten; Schmidt, Mikkel N
2012-01-01
Many networks of scientific interest naturally decompose into clusters or communities with comparatively fewer external than internal links; however, current Bayesian models of network communities do not exert this intuitive notion of communities. We formulate a nonparametric Bayesian model...... for community detection consistent with an intuitive definition of communities and present a Markov chain Monte Carlo procedure for inferring the community structure. A Matlab toolbox with the proposed inference procedure is available for download. On synthetic and real networks, our model detects communities...... consistent with ground truth, and on real networks, it outperforms existing approaches in predicting missing links. This suggests that community structure is an important structural property of networks that should be explicitly modeled....
Vogel-Fulcher dependence of relaxation rates in a nematic monomer and elastomer
Shenoy, D.; Filippov, S.; Aliev, F.; Keller, P.; Thomsen, D.; Ratna, B.
2000-12-01
Dielectric relaxation spectroscopy is used to study the relaxation processes in a nematic monomer and the corresponding cross-linked polymer nematic liquid crystal (elastomer). In the frequency window 10 mHz to 2 GHz the monomer liquid crystal shows a single relaxation whereas the polymer exhibits three relaxation processes, two of which are quantitatively analyzed. The temperature dependence of relaxation times in both the monomer and polymer follows a Vogel-Fulcher behavior. The relaxation processes are identified with specific molecular motions and activation energies are calculated in a linear approximation for comparison with literature data.
Approximate Bayesian recursive estimation
Czech Academy of Sciences Publication Activity Database
Kárný, Miroslav
2014-01-01
Roč. 285, č. 1 (2014), s. 100-111 ISSN 0020-0255 R&D Projects: GA ČR GA13-13502S Institutional support: RVO:67985556 Keywords : Approximate parameter estimation * Bayesian recursive estimation * Kullback–Leibler divergence * Forgetting Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 4.038, year: 2014 http://library.utia.cas.cz/separaty/2014/AS/karny-0425539.pdf
DEFF Research Database (Denmark)
Antoniou, Constantinos; Harrison, Glenn W.; Lau, Morten I.
2015-01-01
A large literature suggests that many individuals do not apply Bayes’ Rule when making decisions that depend on them correctly pooling prior information and sample data. We replicate and extend a classic experimental study of Bayesian updating from psychology, employing the methods of experimenta...... economics, with careful controls for the confounding effects of risk aversion. Our results show that risk aversion significantly alters inferences on deviations from Bayes’ Rule....
Energy Technology Data Exchange (ETDEWEB)
Andrews, Stephen A. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Sigeti, David E. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2017-11-15
These are a set of slides about Bayesian hypothesis testing, where many hypotheses are tested. The conclusions are the following: The value of the Bayes factor obtained when using the median of the posterior marginal is almost the minimum value of the Bayes factor. The value of τ^{2} which minimizes the Bayes factor is a reasonable choice for this parameter. This allows a likelihood ratio to be computed with is the least favorable to H_{0}.
Introduction to Bayesian statistics
Koch, Karl-Rudolf
2007-01-01
This book presents Bayes' theorem, the estimation of unknown parameters, the determination of confidence regions and the derivation of tests of hypotheses for the unknown parameters. It does so in a simple manner that is easy to comprehend. The book compares traditional and Bayesian methods with the rules of probability presented in a logical way allowing an intuitive understanding of random variables and their probability distributions to be formed.
Bayesian ARTMAP for regression.
Sasu, L M; Andonie, R
2013-10-01
Bayesian ARTMAP (BA) is a recently introduced neural architecture which uses a combination of Fuzzy ARTMAP competitive learning and Bayesian learning. Training is generally performed online, in a single-epoch. During training, BA creates input data clusters as Gaussian categories, and also infers the conditional probabilities between input patterns and categories, and between categories and classes. During prediction, BA uses Bayesian posterior probability estimation. So far, BA was used only for classification. The goal of this paper is to analyze the efficiency of BA for regression problems. Our contributions are: (i) we generalize the BA algorithm using the clustering functionality of both ART modules, and name it BA for Regression (BAR); (ii) we prove that BAR is a universal approximator with the best approximation property. In other words, BAR approximates arbitrarily well any continuous function (universal approximation) and, for every given continuous function, there is one in the set of BAR approximators situated at minimum distance (best approximation); (iii) we experimentally compare the online trained BAR with several neural models, on the following standard regression benchmarks: CPU Computer Hardware, Boston Housing, Wisconsin Breast Cancer, and Communities and Crime. Our results show that BAR is an appropriate tool for regression tasks, both for theoretical and practical reasons. Copyright © 2013 Elsevier Ltd. All rights reserved.
Bayesian theory and applications
Dellaportas, Petros; Polson, Nicholas G; Stephens, David A
2013-01-01
The development of hierarchical models and Markov chain Monte Carlo (MCMC) techniques forms one of the most profound advances in Bayesian analysis since the 1970s and provides the basis for advances in virtually all areas of applied and theoretical Bayesian statistics. This volume guides the reader along a statistical journey that begins with the basic structure of Bayesian theory, and then provides details on most of the past and present advances in this field. The book has a unique format. There is an explanatory chapter devoted to each conceptual advance followed by journal-style chapters that provide applications or further advances on the concept. Thus, the volume is both a textbook and a compendium of papers covering a vast range of topics. It is appropriate for a well-informed novice interested in understanding the basic approach, methods and recent applications. Because of its advanced chapters and recent work, it is also appropriate for a more mature reader interested in recent applications and devel...
On real statistics of relaxation in gases
Kuzovlev, Yu. E.
2016-02-01
By example of a particle interacting with ideal gas, it is shown that the statistics of collisions in statistical mechanics at any value of the gas rarefaction parameter qualitatively differ from that conjugated with Boltzmann's hypothetical molecular chaos and kinetic equation. In reality, the probability of collisions of the particle in itself is random. Because of that, the relaxation of particle velocity acquires a power-law asymptotic behavior. An estimate of its exponent is suggested on the basis of simple kinematic reasons.
... For Consumers Consumer Information by Audience For Women Hair Dye and Hair Relaxers Share Tweet Linkedin Pin it More sharing ... products. If you have a bad reaction to hair dyes and relaxers, you should: Stop using the ...
Experiments in paramagnetic relaxation
International Nuclear Information System (INIS)
Lijphart, E.E.
1976-01-01
This thesis presents two attempts to improve the resolving power of the relaxation measurement technique. The first attempt reconsiders the old technique of steady state saturation. When used in conjunction with the pulse technique, it offers the possibility of obtaining additional information about the system in which all-time derivatives are zero; in addition, non-linear effects may be distinguished from each other. The second attempt involved a systematic study of only one system: Cu in the Tutton salts (K and Rb). The systematic approach, the high accuracy of the measurement and the sheer amount of experimental data for varying temperature, magnetic field and concentration made it possible in this case to separate the prevailing relaxation mechanisms reliably
Relaxation from particle production
Energy Technology Data Exchange (ETDEWEB)
Hook, Anson; Marques-Tavares, Gustavo [Stanford Institute for Theoretical Physics, Stanford University, Stanford, CA 94305 (United States)
2016-12-20
We consider using particle production as a friction force by which to implement a “Relaxion” solution to the electroweak hierarchy problem. Using this approach, we are able to avoid superplanckian field excursions and avoid any conflict with the strong CP problem. The relaxation mechanism can work before, during or after inflation allowing for inflationary dynamics to play an important role or to be completely decoupled.
Magnetic relaxation in anisotropic magnets
DEFF Research Database (Denmark)
Lindgård, Per-Anker
1971-01-01
The line shape and the kinematic and thermodynamic slowing down of the critical and paramagnetic relaxation in axially anisotropic materials are discussed. Kinematic slowing down occurs only in the longitudinal relaxation function. The thermodynamic slowing down occurs in either the transverse...... or longitudinal relaxation function depending on the sign of the axial anisotropy....
Momentum constraint relaxation
International Nuclear Information System (INIS)
Marronetti, Pedro
2006-01-01
Full relativistic simulations in three dimensions invariably develop runaway modes that grow exponentially and are accompanied by violations of the Hamiltonian and momentum constraints. Recently, we introduced a numerical method (Hamiltonian relaxation) that greatly reduces the Hamiltonian constraint violation and helps improve the quality of the numerical model. We present here a method that controls the violation of the momentum constraint. The method is based on the addition of a longitudinal component to the traceless extrinsic curvature A ij -tilde, generated by a vector potential w i , as outlined by York. The components of w i are relaxed to solve approximately the momentum constraint equations, slowly pushing the evolution towards the space of solutions of the constraint equations. We test this method with simulations of binary neutron stars in circular orbits and show that it effectively controls the growth of the aforementioned violations. We also show that a full numerical enforcement of the constraints, as opposed to the gentle correction of the momentum relaxation scheme, results in the development of instabilities that stop the runs shortly
Anomalous behavior of secondary dielectric relaxation in polypropylene glycols
Energy Technology Data Exchange (ETDEWEB)
Grzybowska, K; Grzybowski, A; Ziolo, J; Rzoska, S J; Paluch, M [Institute of Physics, Silesian University, Uniwersytecka 4, 40-007 Katowice (Poland)
2007-09-19
A surprising slow down in the dielectric secondary {gamma}-relaxation with temperature increasing near the glass transition is confirmed for several polypropylene glycols. The peculiar behavior diminishes as the molecular weight grows. The minimal model (Dyre and Olsen 2003 Phys. Rev. Lett. 91 155703) is applied successfully to describe the temperature dependences of the {gamma}-relaxation times. The minimal model parameters are analyzed for different molecular weights. A molecular explanation of the {gamma}-process anomaly for polypropylene glycols is proposed on the basis of the minimal model prediction.
Magnetic relaxation in analytical, coordination and bioinorganic chemistry
International Nuclear Information System (INIS)
Mikhajlov, O.
1982-01-01
Nuclear magnetic relaxation is a special type of nuclear magnetic resonance in which the rate is measured of energy transfer between the excited nuclei and their molecular medium (spin-lattice relaxation) or the whole nuclear spin system (spin-spin relaxation). Nuclear magnetic relaxation relates to nuclei with a spin of 1/2, primarily H 1 1 , and is mainly measured in water solutions. It is suitable for (1) analytical chemistry because the relaxation time rapidly reduces in the presence of paramagnetic ions, (2) the study of complex compounds, (3) the study of biochemical reactions in the presence of different metal ions. It is also suitable for testing the composition of a flowing liquid. Its disadvantage is that it requires complex and expensive equipment. (Ha)
Bayesian nonparametric data analysis
Müller, Peter; Jara, Alejandro; Hanson, Tim
2015-01-01
This book reviews nonparametric Bayesian methods and models that have proven useful in the context of data analysis. Rather than providing an encyclopedic review of probability models, the book’s structure follows a data analysis perspective. As such, the chapters are organized by traditional data analysis problems. In selecting specific nonparametric models, simpler and more traditional models are favored over specialized ones. The discussed methods are illustrated with a wealth of examples, including applications ranging from stylized examples to case studies from recent literature. The book also includes an extensive discussion of computational methods and details on their implementation. R code for many examples is included in on-line software pages.
Congdon, Peter
2014-01-01
This book provides an accessible approach to Bayesian computing and data analysis, with an emphasis on the interpretation of real data sets. Following in the tradition of the successful first edition, this book aims to make a wide range of statistical modeling applications accessible using tested code that can be readily adapted to the reader's own applications. The second edition has been thoroughly reworked and updated to take account of advances in the field. A new set of worked examples is included. The novel aspect of the first edition was the coverage of statistical modeling using WinBU
Bayesian approach to inverse statistical mechanics
Habeck, Michael
2014-05-01
Inverse statistical mechanics aims to determine particle interactions from ensemble properties. This article looks at this inverse problem from a Bayesian perspective and discusses several statistical estimators to solve it. In addition, a sequential Monte Carlo algorithm is proposed that draws the interaction parameters from their posterior probability distribution. The posterior probability involves an intractable partition function that is estimated along with the interactions. The method is illustrated for inverse problems of varying complexity, including the estimation of a temperature, the inverse Ising problem, maximum entropy fitting, and the reconstruction of molecular interaction potentials.
Inference in hybrid Bayesian networks
DEFF Research Database (Denmark)
Lanseth, Helge; Nielsen, Thomas Dyhre; Rumí, Rafael
2009-01-01
Since the 1980s, Bayesian Networks (BNs) have become increasingly popular for building statistical models of complex systems. This is particularly true for boolean systems, where BNs often prove to be a more efficient modelling framework than traditional reliability-techniques (like fault trees...... decade's research on inference in hybrid Bayesian networks. The discussions are linked to an example model for estimating human reliability....
Searching Algorithm Using Bayesian Updates
Caudle, Kyle
2010-01-01
In late October 1967, the USS Scorpion was lost at sea, somewhere between the Azores and Norfolk Virginia. Dr. Craven of the U.S. Navy's Special Projects Division is credited with using Bayesian Search Theory to locate the submarine. Bayesian Search Theory is a straightforward and interesting application of Bayes' theorem which involves searching…
Bayesian Data Analysis (lecture 2)
CERN. Geneva
2018-01-01
framework but we will also go into more detail and discuss for example the role of the prior. The second part of the lecture will cover further examples and applications that heavily rely on the bayesian approach, as well as some computational tools needed to perform a bayesian analysis.
Bayesian Data Analysis (lecture 1)
CERN. Geneva
2018-01-01
framework but we will also go into more detail and discuss for example the role of the prior. The second part of the lecture will cover further examples and applications that heavily rely on the bayesian approach, as well as some computational tools needed to perform a bayesian analysis.
Relaxation of coupled nuclear spin systems
International Nuclear Information System (INIS)
Koenigsberger, E.
1985-05-01
The subject of the present work is the relaxation behaviour of scalarly coupled spin-1/2 systems. In the theoretical part the semiclassical Redfield equations are used. Dipolar (D), Chemical Shift Anisotropy (CSA) and Random Field (RF) interactions are considered as relaxation mechanisms. Cross correlations of dipolar interactions of different nuclei pairs and those between the D and the CSA mechanisms are important. The model of anisotropic molecular rotational relaxation and the extreme narrowing approximation are used to obtain the spectral density functions. The longitudinal relaxation data are analyzed into normal modes following Werbelow and Grant. The time evolution of normal modes is derived for the AX system with D-CSA cross terms. In the experimental part the hypothesis of dimerization in the cinnamic acid and the methyl cinnamate - AMX systems with DD cross terms - is corroborated by T 1 -time measurements and a calculation of the diffusion constants. In pentachlorobenzene - an AX system - taking into account of D-CSA cross terms enables the complete determination of movements anosotropy and the determination of the sign of the indirect coupling constant 1 Jsub(CH). (G.Q.)
Nuclear spin-lattice relaxation in carbon nanostructures
Energy Technology Data Exchange (ETDEWEB)
Panich, A.M., E-mail: pan@bgu.ac.i [Department of Physics, Ben-Gurion University of the Negev, P.O. Box 653, Beer Sheva 84105 (Israel); Sergeev, N.A. [Institute of Physics, University of Szczecin, 70-451 Szczecin (Poland)
2010-04-15
Interpretation of nuclear spin-lattice relaxation data in the carbon nanostructures is usually based on the analysis of fluctuations of dipole-dipole interactions of nuclear spins and anisotropic electron-nuclear interactions responsible for chemical shielding, which are caused by molecular dynamics. However, many nanocarbon systems such as fullerene and nanotube derivatives, nanodiamonds and carbon onions reveal noticeable amount of paramagnetic defects with unpaired electrons originating from dangling bonds. The interaction between nuclear and electron spins strongly influences the nuclear spin-lattice relaxation, but usually is not taken into account, thus the relaxation data are not correctly interpreted. Here we report on the temperature dependent NMR spectra and spin-lattice relaxation measurements of intercalated fullerenes C{sub 60}(MF{sub 6}){sub 2} (M=As and Sb), where nuclear relaxation is caused by both molecular rotation and interaction between nuclei and unpaired electron spins. We present a detailed theoretical analysis of the spin-lattice relaxation data taking into account both these contributions. Good agreement between the experimental data and calculations is obtained. The developed approach would be useful in interpreting the NMR relaxation data in different nanostructures and their intercalation compounds.
The Bayesian Covariance Lasso.
Khondker, Zakaria S; Zhu, Hongtu; Chu, Haitao; Lin, Weili; Ibrahim, Joseph G
2013-04-01
Estimation of sparse covariance matrices and their inverse subject to positive definiteness constraints has drawn a lot of attention in recent years. The abundance of high-dimensional data, where the sample size ( n ) is less than the dimension ( d ), requires shrinkage estimation methods since the maximum likelihood estimator is not positive definite in this case. Furthermore, when n is larger than d but not sufficiently larger, shrinkage estimation is more stable than maximum likelihood as it reduces the condition number of the precision matrix. Frequentist methods have utilized penalized likelihood methods, whereas Bayesian approaches rely on matrix decompositions or Wishart priors for shrinkage. In this paper we propose a new method, called the Bayesian Covariance Lasso (BCLASSO), for the shrinkage estimation of a precision (covariance) matrix. We consider a class of priors for the precision matrix that leads to the popular frequentist penalties as special cases, develop a Bayes estimator for the precision matrix, and propose an efficient sampling scheme that does not precalculate boundaries for positive definiteness. The proposed method is permutation invariant and performs shrinkage and estimation simultaneously for non-full rank data. Simulations show that the proposed BCLASSO performs similarly as frequentist methods for non-full rank data.
Bayesian dynamic mediation analysis.
Huang, Jing; Yuan, Ying
2017-12-01
Most existing methods for mediation analysis assume that mediation is a stationary, time-invariant process, which overlooks the inherently dynamic nature of many human psychological processes and behavioral activities. In this article, we consider mediation as a dynamic process that continuously changes over time. We propose Bayesian multilevel time-varying coefficient models to describe and estimate such dynamic mediation effects. By taking the nonparametric penalized spline approach, the proposed method is flexible and able to accommodate any shape of the relationship between time and mediation effects. Simulation studies show that the proposed method works well and faithfully reflects the true nature of the mediation process. By modeling mediation effect nonparametrically as a continuous function of time, our method provides a valuable tool to help researchers obtain a more complete understanding of the dynamic nature of the mediation process underlying psychological and behavioral phenomena. We also briefly discuss an alternative approach of using dynamic autoregressive mediation model to estimate the dynamic mediation effect. The computer code is provided to implement the proposed Bayesian dynamic mediation analysis. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
Approximate Bayesian computation.
Directory of Open Access Journals (Sweden)
Mikael Sunnåker
Full Text Available Approximate Bayesian computation (ABC constitutes a class of computational methods rooted in Bayesian statistics. In all model-based statistical inference, the likelihood function is of central importance, since it expresses the probability of the observed data under a particular statistical model, and thus quantifies the support data lend to particular values of parameters and to choices among different models. For simple models, an analytical formula for the likelihood function can typically be derived. However, for more complex models, an analytical formula might be elusive or the likelihood function might be computationally very costly to evaluate. ABC methods bypass the evaluation of the likelihood function. In this way, ABC methods widen the realm of models for which statistical inference can be considered. ABC methods are mathematically well-founded, but they inevitably make assumptions and approximations whose impact needs to be carefully assessed. Furthermore, the wider application domain of ABC exacerbates the challenges of parameter estimation and model selection. ABC has rapidly gained popularity over the last years and in particular for the analysis of complex problems arising in biological sciences (e.g., in population genetics, ecology, epidemiology, and systems biology.
Bayesian inference with ecological applications
Link, William A
2009-01-01
This text is written to provide a mathematically sound but accessible and engaging introduction to Bayesian inference specifically for environmental scientists, ecologists and wildlife biologists. It emphasizes the power and usefulness of Bayesian methods in an ecological context. The advent of fast personal computers and easily available software has simplified the use of Bayesian and hierarchical models . One obstacle remains for ecologists and wildlife biologists, namely the near absence of Bayesian texts written specifically for them. The book includes many relevant examples, is supported by software and examples on a companion website and will become an essential grounding in this approach for students and research ecologists. Engagingly written text specifically designed to demystify a complex subject Examples drawn from ecology and wildlife research An essential grounding for graduate and research ecologists in the increasingly prevalent Bayesian approach to inference Companion website with analyt...
Bayesian Inference on Gravitational Waves
Directory of Open Access Journals (Sweden)
Asad Ali
2015-12-01
Full Text Available The Bayesian approach is increasingly becoming popular among the astrophysics data analysis communities. However, the Pakistan statistics communities are unaware of this fertile interaction between the two disciplines. Bayesian methods have been in use to address astronomical problems since the very birth of the Bayes probability in eighteenth century. Today the Bayesian methods for the detection and parameter estimation of gravitational waves have solid theoretical grounds with a strong promise for the realistic applications. This article aims to introduce the Pakistan statistics communities to the applications of Bayesian Monte Carlo methods in the analysis of gravitational wave data with an overview of the Bayesian signal detection and estimation methods and demonstration by a couple of simplified examples.
Communication: Relaxation-limited electronic currents in extended reservoir simulations
Gruss, Daniel; Smolyanitsky, Alex; Zwolak, Michael
2017-10-01
Open-system approaches are gaining traction in the simulation of charge transport in nanoscale and molecular electronic devices. In particular, "extended reservoir" simulations, where explicit reservoir degrees of freedom are present, allow for the computation of both real-time and steady-state properties but require relaxation of the extended reservoirs. The strength of this relaxation, γ, influences the conductance, giving rise to a "turnover" behavior analogous to Kramers turnover in chemical reaction rates. We derive explicit, general expressions for the weak and strong relaxation limits. For weak relaxation, the conductance increases linearly with γ and every electronic state of the total explicit system contributes to the electronic current according to its "reduced" weight in the two extended reservoir regions. Essentially, this represents two conductors in series—one at each interface with the implicit reservoirs that provide the relaxation. For strong relaxation, a "dual" expression-one with the same functional form-results, except now proportional to 1/γ and dependent on the system of interest's electronic states, reflecting that the strong relaxation is localizing electrons in the extended reservoirs. Higher order behavior (e.g., γ2 or 1/γ2) can occur when there is a gap in the frequency spectrum. Moreover, inhomogeneity in the frequency spacing can give rise to a pseudo-plateau regime. These findings yield a physically motivated approach to diagnosing numerical simulations and understanding the influence of relaxation, and we examine their occurrence in both simple models and a realistic, fluctuating graphene nanoribbon.
Variational formulation of relaxed and multi-region relaxed magnetohydrodynamics
Dewar, R. L.; Yoshida, Z.; Bhattacharjee, A.; Hudson, S. R.
2015-12-01
> Ideal magnetohydrodynamics (IMHD) is strongly constrained by an infinite number of microscopic constraints expressing mass, entropy and magnetic flux conservation in each infinitesimal fluid element, the latter preventing magnetic reconnection. By contrast, in the Taylor relaxation model for formation of macroscopically self-organized plasma equilibrium states, all these constraints are relaxed save for the global magnetic fluxes and helicity. A Lagrangian variational principle is presented that leads to a new, fully dynamical, relaxed magnetohydrodynamics (RxMHD), such that all static solutions are Taylor states but also allows state with flow. By postulating that some long-lived macroscopic current sheets can act as barriers to relaxation, separating the plasma into multiple relaxation regions, a further generalization, multi-region relaxed magnetohydrodynamics (MRxMHD) is developed.
Borsboom, D.; Haig, B.D.
2013-01-01
Unlike most other statistical frameworks, Bayesian statistical inference is wedded to a particular approach in the philosophy of science (see Howson & Urbach, 2006); this approach is called Bayesianism. Rather than being concerned with model fitting, this position in the philosophy of science
Tangarife, Walter; Tobioka, Kohsaku; Ubaldi, Lorenzo; Volansky, Tomer
2018-02-01
The cosmological relaxation of the electroweak scale has been proposed as a mechanism to address the hierarchy problem of the Standard Model. A field, the relaxion, rolls down its potential and, in doing so, scans the squared mass parameter of the Higgs, relaxing it to a parametrically small value. In this work, we promote the relaxion to an inflaton. We couple it to Abelian gauge bosons, thereby introducing the necessary dissipation mechanism which slows down the field in the last stages. We describe a novel reheating mechanism, which relies on the gauge-boson production leading to strong electro-magnetic fields, and proceeds via the vacuum production of electron-positron pairs through the Schwinger effect. We refer to this mechanism as Schwinger reheating. We discuss the cosmological dynamics of the model and the phenomenological constraints from CMB and other experiments. We find that a cutoff close to the Planck scale may be achieved. In its minimal form, the model does not generate sufficient curvature perturbations and additional ingredients, such as a curvaton field, are needed.
A Robust Bayesian Truth Serum for Small Populations
Parkes, David C.; Witkowski, Jens
2012-01-01
Peer prediction mechanisms allow the truthful elicitation of private signals (e.g., experiences, or opinions) in regard to a true world state when this ground truth is unobservable. The original peer prediction method is incentive compatible for any number of agents n >= 2, but relies on a common prior, shared by all agents and the mechanism. The Bayesian Truth Serum (BTS) relaxes this assumption. While BTS still assumes that agents share a common prior, this prior need not be known to the me...
Modern problems of relaxation gas dynamics
International Nuclear Information System (INIS)
Losev, S.A.; Osipov, A.I.
1985-01-01
Some of the dynamical characteristics of relaxation processes are studied. Unfortunately, many dynamical characteristics of relaxation processes, necessary for the solution of important scientific and applied problems, are not known. These problems require further development of experimental methods of the study of nonequilibrium gas. It is known, that gas systems are shifted from the equilibrium by different methods: by acoustic and shock wav es, by means of gas expansion in nozzles and jets, by powerful radiations (laser, first of all), by electric discharges, in burning and combustion devices, etc. Non-equilibrium gas is produced in installations of continuum, impulse and periodic regime. Molecular beams, shock tubes (especially with nozzles), flow and jet installations, aerodynamical tubes, plasmatrons, vessels with a gas, influenced by the strong radiation, burners and combustion devices, where the study of non-euilibrium gas is helpful to solve the problems of the determination of kinetic equations and constants of physico-chemical kinetics
International Nuclear Information System (INIS)
Rajabalinejad, M.
2010-01-01
To reduce cost of Monte Carlo (MC) simulations for time-consuming processes, Bayesian Monte Carlo (BMC) is introduced in this paper. The BMC method reduces number of realizations in MC according to the desired accuracy level. BMC also provides a possibility of considering more priors. In other words, different priors can be integrated into one model by using BMC to further reduce cost of simulations. This study suggests speeding up the simulation process by considering the logical dependence of neighboring points as prior information. This information is used in the BMC method to produce a predictive tool through the simulation process. The general methodology and algorithm of BMC method are presented in this paper. The BMC method is applied to the simplified break water model as well as the finite element model of 17th Street Canal in New Orleans, and the results are compared with the MC and Dynamic Bounds methods.
Bayesian nonparametric hierarchical modeling.
Dunson, David B
2009-04-01
In biomedical research, hierarchical models are very widely used to accommodate dependence in multivariate and longitudinal data and for borrowing of information across data from different sources. A primary concern in hierarchical modeling is sensitivity to parametric assumptions, such as linearity and normality of the random effects. Parametric assumptions on latent variable distributions can be challenging to check and are typically unwarranted, given available prior knowledge. This article reviews some recent developments in Bayesian nonparametric methods motivated by complex, multivariate and functional data collected in biomedical studies. The author provides a brief review of flexible parametric approaches relying on finite mixtures and latent class modeling. Dirichlet process mixture models are motivated by the need to generalize these approaches to avoid assuming a fixed finite number of classes. Focusing on an epidemiology application, the author illustrates the practical utility and potential of nonparametric Bayes methods.
Book review: Bayesian analysis for population ecology
Link, William A.
2011-01-01
Brian Dennis described the field of ecology as “fertile, uncolonized ground for Bayesian ideas.” He continued: “The Bayesian propagule has arrived at the shore. Ecologists need to think long and hard about the consequences of a Bayesian ecology. The Bayesian outlook is a successful competitor, but is it a weed? I think so.” (Dennis 2004)
Current trends in Bayesian methodology with applications
Upadhyay, Satyanshu K; Dey, Dipak K; Loganathan, Appaia
2015-01-01
Collecting Bayesian material scattered throughout the literature, Current Trends in Bayesian Methodology with Applications examines the latest methodological and applied aspects of Bayesian statistics. The book covers biostatistics, econometrics, reliability and risk analysis, spatial statistics, image analysis, shape analysis, Bayesian computation, clustering, uncertainty assessment, high-energy astrophysics, neural networking, fuzzy information, objective Bayesian methodologies, empirical Bayes methods, small area estimation, and many more topics.Each chapter is self-contained and focuses on
Bayesian image restoration, using configurations
Thorarinsdottir, Thordis
2006-01-01
In this paper, we develop a Bayesian procedure for removing noise from images that can be viewed as noisy realisations of random sets in the plane. The procedure utilises recent advances in configuration theory for noise free random sets, where the probabilities of observing the different boundary configurations are expressed in terms of the mean normal measure of the random set. These probabilities are used as prior probabilities in a Bayesian image restoration approach. Estimation of the re...
Bayesian Networks and Influence Diagrams
DEFF Research Database (Denmark)
Kjærulff, Uffe Bro; Madsen, Anders Læsø
Probabilistic networks, also known as Bayesian networks and influence diagrams, have become one of the most promising technologies in the area of applied artificial intelligence, offering intuitive, efficient, and reliable methods for diagnosis, prediction, decision making, classification......, troubleshooting, and data mining under uncertainty. Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis provides a comprehensive guide for practitioners who wish to understand, construct, and analyze intelligent systems for decision support based on probabilistic networks. Intended...
Dielectric relaxation studies of dilute solutions of amides
Energy Technology Data Exchange (ETDEWEB)
Malathi, M.; Sabesan, R.; Krishnan, S
2003-11-15
The dielectric constants and dielectric losses of formamide, acetamide, N-methyl acetamide, acetanilide and N,N-dimethyl acetamide in dilute solutions of 1,4-dioxan/benzene have been measured at 308 K using 9.37 GHz, dielectric relaxation set up. The relaxation time for the over all rotation {tau}{sub (1)} and that for the group rotation {tau}{sub (2)} of (the molecules were determined using Higasi's method. The activation energies for the processes of dielectric relaxation and viscous flow were determined by using Eyring's rate theory. From relaxation time behaviour of amides in non-polar solvent, solute-solvent and solute-solute type of molecular association is proposed.
Electron spin relaxation in cryptochrome-based magnetoreception
DEFF Research Database (Denmark)
Kattnig, Daniel R; Solov'yov, Ilia A; Hore, P J
2016-01-01
The magnetic compass sense of migratory birds is thought to rely on magnetically sensitive radical pairs formed photochemically in cryptochrome proteins in the retina. An important requirement of this hypothesis is that electron spin relaxation is slow enough for the Earth's magnetic field to have...... this question for a structurally characterized model cryptochrome expected to share many properties with the putative avian receptor protein. To this end we combine all-atom molecular dynamics simulations, Bloch-Redfield relaxation theory and spin dynamics calculations to assess the effects of spin relaxation...... on the performance of the protein as a compass sensor. Both flavin-tryptophan and flavin-Z˙ radical pairs are studied (Z˙ is a radical with no hyperfine interactions). Relaxation is considered to arise from modulation of hyperfine interactions by librational motions of the radicals and fluctuations in certain...
Relaxation and transport properties of liquid n-triacontane
International Nuclear Information System (INIS)
Kondratyuk, N D; Lankin, A V; Norman, G E; Stegailov, V V
2015-01-01
Molecular modelling is used to calculate transport properties and to study relaxation of liquid n-triacontane (C 30 H 62 ). The problem is important in connection with the behavior of liquid isolators in a pre-breakdown state. Two all-atom models and a united-atom model are used. Shear viscosity is calculated using the Green-Kubo formula. The force fields are compared with each other using the following criteria: the required time for one molecular dynamics step, the compliance of the main physical and transport properties with experimental values. The problem of the system equilibration is considered. The united-atom potential is used to model the n-triacontane liquid with an initial directional orientation. The time of relaxation to the disordered state, when all molecules orientations are randomized, are obtained. The influence of the molecules orientations on the shear viscosity value and the shear viscosity relaxation are treated. (paper)
Bayesian seismic AVO inversion
Energy Technology Data Exchange (ETDEWEB)
Buland, Arild
2002-07-01
A new linearized AVO inversion technique is developed in a Bayesian framework. The objective is to obtain posterior distributions for P-wave velocity, S-wave velocity and density. Distributions for other elastic parameters can also be assessed, for example acoustic impedance, shear impedance and P-wave to S-wave velocity ratio. The inversion algorithm is based on the convolutional model and a linearized weak contrast approximation of the Zoeppritz equation. The solution is represented by a Gaussian posterior distribution with explicit expressions for the posterior expectation and covariance, hence exact prediction intervals for the inverted parameters can be computed under the specified model. The explicit analytical form of the posterior distribution provides a computationally fast inversion method. Tests on synthetic data show that all inverted parameters were almost perfectly retrieved when the noise approached zero. With realistic noise levels, acoustic impedance was the best determined parameter, while the inversion provided practically no information about the density. The inversion algorithm has also been tested on a real 3-D dataset from the Sleipner Field. The results show good agreement with well logs but the uncertainty is high. The stochastic model includes uncertainties of both the elastic parameters, the wavelet and the seismic and well log data. The posterior distribution is explored by Markov chain Monte Carlo simulation using the Gibbs sampler algorithm. The inversion algorithm has been tested on a seismic line from the Heidrun Field with two wells located on the line. The uncertainty of the estimated wavelet is low. In the Heidrun examples the effect of including uncertainty of the wavelet and the noise level was marginal with respect to the AVO inversion results. We have developed a 3-D linearized AVO inversion method with spatially coupled model parameters where the objective is to obtain posterior distributions for P-wave velocity, S
Improved dynamical scaling analysis using the kernel method for nonequilibrium relaxation.
Echinaka, Yuki; Ozeki, Yukiyasu
2016-10-01
The dynamical scaling analysis for the Kosterlitz-Thouless transition in the nonequilibrium relaxation method is improved by the use of Bayesian statistics and the kernel method. This allows data to be fitted to a scaling function without using any parametric model function, which makes the results more reliable and reproducible and enables automatic and faster parameter estimation. Applying this method, the bootstrap method is introduced and a numerical discrimination for the transition type is proposed.
Relaxed states with plasma flow
International Nuclear Information System (INIS)
Avinash, K.; Taylor, J.B.
1991-01-01
In the theory of relaxation, a turbulent plasma reaches a state of minimum energy subject to constant magnetic helicity. In this state the plasma velocity is zero. Attempts have been made by introducing a number of different constraints, to obtain relaxed states with plasma flow. It is shown that these alternative constraints depend on two self-helicities, one for ions, and one for electrons. However, whereas there are strong arguments for the effective invariance of the original magnetic-helicity, these arguments do not apply to the self-helicities. Consequently the existence of relaxed states with flow remains in doubt. (author)
A model for the generic alpha relaxation in viscous liquids
DEFF Research Database (Denmark)
Dyre, Jeppe
2005-01-01
Dielectric measurements on molecular liquids just above the glass transition indicate that alpha relaxation is characterized by a generic high-frequency loss varying as one over square root of frequency, whereas deviations from this come from one or more low-lying beta processes [Olsen et al., Phys...
Bayesian networks improve causal environmental ...
Rule-based weight of evidence approaches to ecological risk assessment may not account for uncertainties and generally lack probabilistic integration of lines of evidence. Bayesian networks allow causal inferences to be made from evidence by including causal knowledge about the problem, using this knowledge with probabilistic calculus to combine multiple lines of evidence, and minimizing biases in predicting or diagnosing causal relationships. Too often, sources of uncertainty in conventional weight of evidence approaches are ignored that can be accounted for with Bayesian networks. Specifying and propagating uncertainties improve the ability of models to incorporate strength of the evidence in the risk management phase of an assessment. Probabilistic inference from a Bayesian network allows evaluation of changes in uncertainty for variables from the evidence. The network structure and probabilistic framework of a Bayesian approach provide advantages over qualitative approaches in weight of evidence for capturing the impacts of multiple sources of quantifiable uncertainty on predictions of ecological risk. Bayesian networks can facilitate the development of evidence-based policy under conditions of uncertainty by incorporating analytical inaccuracies or the implications of imperfect information, structuring and communicating causal issues through qualitative directed graph formulations, and quantitatively comparing the causal power of multiple stressors on value
Bayesian Latent Class Analysis Tutorial.
Li, Yuelin; Lord-Bessen, Jennifer; Shiyko, Mariya; Loeb, Rebecca
2018-01-01
This article is a how-to guide on Bayesian computation using Gibbs sampling, demonstrated in the context of Latent Class Analysis (LCA). It is written for students in quantitative psychology or related fields who have a working knowledge of Bayes Theorem and conditional probability and have experience in writing computer programs in the statistical language R . The overall goals are to provide an accessible and self-contained tutorial, along with a practical computation tool. We begin with how Bayesian computation is typically described in academic articles. Technical difficulties are addressed by a hypothetical, worked-out example. We show how Bayesian computation can be broken down into a series of simpler calculations, which can then be assembled together to complete a computationally more complex model. The details are described much more explicitly than what is typically available in elementary introductions to Bayesian modeling so that readers are not overwhelmed by the mathematics. Moreover, the provided computer program shows how Bayesian LCA can be implemented with relative ease. The computer program is then applied in a large, real-world data set and explained line-by-line. We outline the general steps in how to extend these considerations to other methodological applications. We conclude with suggestions for further readings.
Kernel Bayesian ART and ARTMAP.
Masuyama, Naoki; Loo, Chu Kiong; Dawood, Farhan
2018-02-01
Adaptive Resonance Theory (ART) is one of the successful approaches to resolving "the plasticity-stability dilemma" in neural networks, and its supervised learning model called ARTMAP is a powerful tool for classification. Among several improvements, such as Fuzzy or Gaussian based models, the state of art model is Bayesian based one, while solving the drawbacks of others. However, it is known that the Bayesian approach for the high dimensional and a large number of data requires high computational cost, and the covariance matrix in likelihood becomes unstable. This paper introduces Kernel Bayesian ART (KBA) and ARTMAP (KBAM) by integrating Kernel Bayes' Rule (KBR) and Correntropy Induced Metric (CIM) to Bayesian ART (BA) and ARTMAP (BAM), respectively, while maintaining the properties of BA and BAM. The kernel frameworks in KBA and KBAM are able to avoid the curse of dimensionality. In addition, the covariance-free Bayesian computation by KBR provides the efficient and stable computational capability to KBA and KBAM. Furthermore, Correntropy-based similarity measurement allows improving the noise reduction ability even in the high dimensional space. The simulation experiments show that KBA performs an outstanding self-organizing capability than BA, and KBAM provides the superior classification ability than BAM, respectively. Copyright © 2017 Elsevier Ltd. All rights reserved.
Energy Technology Data Exchange (ETDEWEB)
Wang, Xianlong, E-mail: WangXianlong@uestc.edu.cn, E-mail: pbeckman@brynmawr.edu [Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, 4 North Jianshe Rd., 2nd Section, Chengdu 610054 (China); Mallory, Frank B. [Department of Chemistry, Bryn Mawr College, 101 North Merion Ave., Bryn Mawr, Pennsylvania 19010-2899 (United States); Mallory, Clelia W. [Department of Chemistry, Bryn Mawr College, 101 North Merion Ave., Bryn Mawr, Pennsylvania 19010-2899 (United States); Department of Chemistry, University of Pennsylvania, Philadelphia, Pennsylvania 19104-6323 (United States); Odhner, Hosanna R.; Beckmann, Peter A., E-mail: WangXianlong@uestc.edu.cn, E-mail: pbeckman@brynmawr.edu [Department of Physics, Bryn Mawr College, 101 North Merion Ave., Bryn Mawr, Pennsylvania 19010-2899 (United States)
2014-05-21
We report ab initio density functional theory electronic structure calculations of rotational barriers for t-butyl groups and their constituent methyl groups both in the isolated molecules and in central molecules in clusters built from the X-ray structure in four t-butyl aromatic compounds. The X-ray structures have been reported previously. We also report and interpret the temperature dependence of the solid state {sup 1}H nuclear magnetic resonance spin-lattice relaxation rate at 8.50, 22.5, and 53.0 MHz in one of the four compounds. Such experiments for the other three have been reported previously. We compare the computed barriers for methyl group and t-butyl group rotation in a central target molecule in the cluster with the activation energies determined from fitting the {sup 1}H NMR spin-lattice relaxation data. We formulate a dynamical model for the superposition of t-butyl group rotation and the rotation of the t-butyl group's constituent methyl groups. The four compounds are 2,7-di-t-butylpyrene, 1,4-di-t-butylbenzene, 2,6-di-t-butylnaphthalene, and 3-t-butylchrysene. We comment on the unusual ground state orientation of the t-butyl groups in the crystal of the pyrene and we comment on the unusually high rotational barrier of these t-butyl groups.
Interactive Instruction in Bayesian Inference
DEFF Research Database (Denmark)
Khan, Azam; Breslav, Simon; Hornbæk, Kasper
2018-01-01
An instructional approach is presented to improve human performance in solving Bayesian inference problems. Starting from the original text of the classic Mammography Problem, the textual expression is modified and visualizations are added according to Mayer’s principles of instruction. These pri......An instructional approach is presented to improve human performance in solving Bayesian inference problems. Starting from the original text of the classic Mammography Problem, the textual expression is modified and visualizations are added according to Mayer’s principles of instruction....... These principles concern coherence, personalization, signaling, segmenting, multimedia, spatial contiguity, and pretraining. Principles of self-explanation and interactivity are also applied. Four experiments on the Mammography Problem showed that these principles help participants answer the questions...... that an instructional approach to improving human performance in Bayesian inference is a promising direction....
Probability biases as Bayesian inference
Directory of Open Access Journals (Sweden)
Andre; C. R. Martins
2006-11-01
Full Text Available In this article, I will show how several observed biases in human probabilistic reasoning can be partially explained as good heuristics for making inferences in an environment where probabilities have uncertainties associated to them. Previous results show that the weight functions and the observed violations of coalescing and stochastic dominance can be understood from a Bayesian point of view. We will review those results and see that Bayesian methods should also be used as part of the explanation behind other known biases. That means that, although the observed errors are still errors under the be understood as adaptations to the solution of real life problems. Heuristics that allow fast evaluations and mimic a Bayesian inference would be an evolutionary advantage, since they would give us an efficient way of making decisions. %XX In that sense, it should be no surprise that humans reason with % probability as it has been observed.
Bayesian analysis of CCDM models
Jesus, J. F.; Valentim, R.; Andrade-Oliveira, F.
2017-09-01
Creation of Cold Dark Matter (CCDM), in the context of Einstein Field Equations, produces a negative pressure term which can be used to explain the accelerated expansion of the Universe. In this work we tested six different spatially flat models for matter creation using statistical criteria, in light of SNe Ia data: Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC) and Bayesian Evidence (BE). These criteria allow to compare models considering goodness of fit and number of free parameters, penalizing excess of complexity. We find that JO model is slightly favoured over LJO/ΛCDM model, however, neither of these, nor Γ = 3αH0 model can be discarded from the current analysis. Three other scenarios are discarded either because poor fitting or because of the excess of free parameters. A method of increasing Bayesian evidence through reparameterization in order to reducing parameter degeneracy is also developed.
Bayesian analysis of CCDM models
Energy Technology Data Exchange (ETDEWEB)
Jesus, J.F. [Universidade Estadual Paulista (Unesp), Câmpus Experimental de Itapeva, Rua Geraldo Alckmin 519, Vila N. Sra. de Fátima, Itapeva, SP, 18409-010 Brazil (Brazil); Valentim, R. [Departamento de Física, Instituto de Ciências Ambientais, Químicas e Farmacêuticas—ICAQF, Universidade Federal de São Paulo (UNIFESP), Unidade José Alencar, Rua São Nicolau No. 210, Diadema, SP, 09913-030 Brazil (Brazil); Andrade-Oliveira, F., E-mail: jfjesus@itapeva.unesp.br, E-mail: valentim.rodolfo@unifesp.br, E-mail: felipe.oliveira@port.ac.uk [Institute of Cosmology and Gravitation—University of Portsmouth, Burnaby Road, Portsmouth, PO1 3FX United Kingdom (United Kingdom)
2017-09-01
Creation of Cold Dark Matter (CCDM), in the context of Einstein Field Equations, produces a negative pressure term which can be used to explain the accelerated expansion of the Universe. In this work we tested six different spatially flat models for matter creation using statistical criteria, in light of SNe Ia data: Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC) and Bayesian Evidence (BE). These criteria allow to compare models considering goodness of fit and number of free parameters, penalizing excess of complexity. We find that JO model is slightly favoured over LJO/ΛCDM model, however, neither of these, nor Γ = 3α H {sub 0} model can be discarded from the current analysis. Three other scenarios are discarded either because poor fitting or because of the excess of free parameters. A method of increasing Bayesian evidence through reparameterization in order to reducing parameter degeneracy is also developed.
Relaxed states of tokamak plasmas
International Nuclear Information System (INIS)
Kucinski, M.Y.; Okano, V.
1993-01-01
The relaxed states of tokamak plasmas are studied. It is assumed that the plasma relaxes to a quasi-steady state which is characterized by a minimum entropy production rate, compatible with a number of prescribed conditions and pressure balance. A poloidal current arises naturally due to the anisotropic resistivity. The minimum entropy production theory is applied, assuming the pressure equilibrium as fundamental constraint on the final state. (L.C.J.A.)
Negative magnetic relaxation in superconductors
Directory of Open Access Journals (Sweden)
Krasnoperov E.P.
2013-01-01
Full Text Available It was observed that the trapped magnetic moment of HTS tablets or annuli increases in time (negative relaxation if they are not completely magnetized by a pulsed magnetic field. It is shown, in the framework of the Bean critical-state model, that the radial temperature gradient appearing in tablets or annuli during a pulsed field magnetization can explain the negative magnetic relaxation in the superconductor.
Relaxation effects in ferrous complexes
International Nuclear Information System (INIS)
Nicolini, C.; Mathieu, J.P.; Chappert, J.
1976-01-01
The slow relaxation mechanism of the Fe 2+ ion in the tri-fluorinated TF(acac) and hexafluorinated HF(acac) complexes of Fe(II) acetylacetonate was investigated. The 300K and 77K Moessbauer spectra for TF(acac) consist in a slightly asymmetric quadrupole doublet. On the contrary, at 4.2K the higher energy line is strongly widened; that is typical of a slowing down in the electron relaxation frequency [fr
Learning Bayesian networks for discrete data
Liang, Faming; Zhang, Jian
2009-01-01
Bayesian networks have received much attention in the recent literature. In this article, we propose an approach to learn Bayesian networks using the stochastic approximation Monte Carlo (SAMC) algorithm. Our approach has two nice features. Firstly
Bayesian Network Induction via Local Neighborhoods
National Research Council Canada - National Science Library
Margaritis, Dimitris
1999-01-01
.... We present an efficient algorithm for learning Bayesian networks from data. Our approach constructs Bayesian networks by first identifying each node's Markov blankets, then connecting nodes in a consistent way...
Can a significance test be genuinely Bayesian?
Pereira, Carlos A. de B.; Stern, Julio Michael; Wechsler, Sergio
2008-01-01
The Full Bayesian Significance Test, FBST, is extensively reviewed. Its test statistic, a genuine Bayesian measure of evidence, is discussed in detail. Its behavior in some problems of statistical inference like testing for independence in contingency tables is discussed.
Bayesian modeling using WinBUGS
Ntzoufras, Ioannis
2009-01-01
A hands-on introduction to the principles of Bayesian modeling using WinBUGS Bayesian Modeling Using WinBUGS provides an easily accessible introduction to the use of WinBUGS programming techniques in a variety of Bayesian modeling settings. The author provides an accessible treatment of the topic, offering readers a smooth introduction to the principles of Bayesian modeling with detailed guidance on the practical implementation of key principles. The book begins with a basic introduction to Bayesian inference and the WinBUGS software and goes on to cover key topics, including: Markov Chain Monte Carlo algorithms in Bayesian inference Generalized linear models Bayesian hierarchical models Predictive distribution and model checking Bayesian model and variable evaluation Computational notes and screen captures illustrate the use of both WinBUGS as well as R software to apply the discussed techniques. Exercises at the end of each chapter allow readers to test their understanding of the presented concepts and all ...
Holographic grating relaxation technique for soft matter science
Energy Technology Data Exchange (ETDEWEB)
Lesnichii, Vasilii, E-mail: vasilii.lesnichii@physchem.uni-freiburg.de [Institute of Physical Chemistry, Albertstraße 21, Institute of Macromolecular Chemistry, Stefan-Meier-Str. 31, Albert-Ludwigs Universität, Freiburg im Breisgau 79104 (Germany); ITMO University, Kronverksky prospekt 49, Saint-Petersburg 197101 (Russian Federation); Kiessling, Andy [Institute of Physical Chemistry, Albertstraße 21, Institute of Macromolecular Chemistry, Stefan-Meier-Str. 31, Albert-Ludwigs Universität, Freiburg im Breisgau 79104 (Germany); Current address: Illinois Institute of Technology, 10 West 33rd Street, Chicago,IL60616 (United States); Bartsch, Eckhard [Institute of Physical Chemistry, Albertstraße 21, Institute of Macromolecular Chemistry, Stefan-Meier-Str. 31, Albert-Ludwigs Universität, Freiburg im Breisgau 79104 (Germany); Veniaminov, Andrey, E-mail: veniaminov@phoi.ifmo.ru [ITMO University, Kronverksky prospekt 49, Saint-Petersburg 197101 (Russian Federation)
2016-06-17
The holographic grating relaxation technique also known as forced Rayleigh scattering consists basically in writing a holographic grating in the specimen of interest and monitoring its diffraction efficiency as a function of time, from which valuable information on mass or heat transfer and photoinduced transformations can be extracted. In a more detailed view, the shape of the relaxation curve and the relaxation rate as a function of the grating period were found to be affected by the architecture of diffusing species (molecular probes) that constitute the grating, as well as that of the environment they diffuse in, thus making it possible to access and study spatial heterogeneity of materials and different modes of e.g., polymer motion. Minimum displacements and spatial domains approachable by the technique are in nanometer range, well below spatial periods of holographic gratings. In the present paper, several cases of holographic relaxation in heterogeneous media and complex motions are exemplified. Nano- to micro-structures or inhomogeneities comparable in spatial scale with holographic gratings manifest themselves in relaxation experiments via non-exponential decay (stepwise or stretched), spatial-period-dependent apparent diffusion coefficient, or unusual dependence of diffusion coefficient on molecular volume of diffusing probes.
Relaxation Dynamics of Nanoparticle-Tethered Polymer Chains
Kim, Sung A
2015-09-08
© 2015 American Chemical Society. Relaxation dynamics of nanoparticle-tethered cis-1,4-polyisoprene (PI) are investigated using dielectric spectroscopy and rheometry. A model system composed of polymer chains densely grafted to spherical SiO2 nanoparticles to form self-suspended suspensions facilitates detailed studies of slow global chain and fast segmental mode dynamics under surface and geometrical confinement-from experiments performed in bulk materials. We report that unentangled polymer molecules tethered to nanoparticles relax far more slowly than their tethered entangled counterparts. Specifically, at fixed grafting density we find, counterintuitively, that increasing the tethered polymer molecular weight up to values close to the entanglement molecular weight speeds up chain relaxation dynamics. Decreasing the polymer grafting density for a fixed molecular weight has the opposite effect: it dramatically slows down chain relaxation, increases interchain coupling, and leads to a transition in rheological response from simple fluid behavior to viscoelastic fluid behavior for tethered PI chains that are unentangled by conventional measures. Increasing the measurement temperature produces an even stronger elastic response and speeds up molecular relaxation at a rate that decreases with grafting density and molecular weight. These observations are discussed in terms of chain confinement driven by crowding between particles and by the existence of an entropic attractive force produced by the space-filling constraint on individual chains in a self-suspended material. Our results indicate that the entropic force between densely grafted polymer molecules couples motions of individual chains in an analogous manner to reversible cross-links in associating polymers.
Inference in hybrid Bayesian networks
International Nuclear Information System (INIS)
Langseth, Helge; Nielsen, Thomas D.; Rumi, Rafael; Salmeron, Antonio
2009-01-01
Since the 1980s, Bayesian networks (BNs) have become increasingly popular for building statistical models of complex systems. This is particularly true for boolean systems, where BNs often prove to be a more efficient modelling framework than traditional reliability techniques (like fault trees and reliability block diagrams). However, limitations in the BNs' calculation engine have prevented BNs from becoming equally popular for domains containing mixtures of both discrete and continuous variables (the so-called hybrid domains). In this paper we focus on these difficulties, and summarize some of the last decade's research on inference in hybrid Bayesian networks. The discussions are linked to an example model for estimating human reliability.
3D Bayesian contextual classifiers
DEFF Research Database (Denmark)
Larsen, Rasmus
2000-01-01
We extend a series of multivariate Bayesian 2-D contextual classifiers to 3-D by specifying a simultaneous Gaussian distribution for the feature vectors as well as a prior distribution of the class variables of a pixel and its 6 nearest 3-D neighbours.......We extend a series of multivariate Bayesian 2-D contextual classifiers to 3-D by specifying a simultaneous Gaussian distribution for the feature vectors as well as a prior distribution of the class variables of a pixel and its 6 nearest 3-D neighbours....
Bayesian methods for proteomic biomarker development
Directory of Open Access Journals (Sweden)
Belinda Hernández
2015-12-01
In this review we provide an introduction to Bayesian inference and demonstrate some of the advantages of using a Bayesian framework. We summarize how Bayesian methods have been used previously in proteomics and other areas of bioinformatics. Finally, we describe some popular and emerging Bayesian models from the statistical literature and provide a worked tutorial including code snippets to show how these methods may be applied for the evaluation of proteomic biomarkers.
Bayesian networks and food security - An introduction
Stein, A.
2004-01-01
This paper gives an introduction to Bayesian networks. Networks are defined and put into a Bayesian context. Directed acyclical graphs play a crucial role here. Two simple examples from food security are addressed. Possible uses of Bayesian networks for implementation and further use in decision
Plug & Play object oriented Bayesian networks
DEFF Research Database (Denmark)
Bangsø, Olav; Flores, J.; Jensen, Finn Verner
2003-01-01
been shown to be quite suitable for dynamic domains as well. However, processing object oriented Bayesian networks in practice does not take advantage of their modular structure. Normally the object oriented Bayesian network is transformed into a Bayesian network and, inference is performed...... dynamic domains. The communication needed between instances is achieved by means of a fill-in propagation scheme....
A Bayesian framework for risk perception
van Erp, H.R.N.
2017-01-01
We present here a Bayesian framework of risk perception. This framework encompasses plausibility judgments, decision making, and question asking. Plausibility judgments are modeled by way of Bayesian probability theory, decision making is modeled by way of a Bayesian decision theory, and relevancy
Topology of Collisionless Relaxation
Pakter, Renato; Levin, Yan
2013-04-01
Using extensive molecular dynamics simulations we explore the fine-grained phase space structure of systems with long-range interactions. We find that if the initial phase space particle distribution has no holes, the final stationary distribution will also contain a compact simply connected region. The microscopic holes created by the filamentation of the initial distribution function are always restricted to the outer regions of the phase space. In general, for complex multilevel distributions it is very difficult to a priori predict the final stationary state without solving the full dynamical evolution. However, we show that, for multilevel initial distributions satisfying a generalized virial condition, it is possible to predict the particle distribution in the final stationary state using Casimir invariants of the Vlasov dynamics.
Nuclear quadrupole relaxation and viscosity in liquid metals
International Nuclear Information System (INIS)
Schirmacher, W.
1976-01-01
It is shown that the nuclear quadrupole relaxation rate due to the molecular motions in liquid metals is related to the shear and bulk viscosity and hence to the absorption coefficient of ultrasound. Application of the 'extended liquid phonon' model of Ortoleva and Nelkin - which is the third of a series of continued-fraction-approximations for the van Hove neutron scattering function - gives a relation to the self diffusion constant. The predictions of the theory concerning the temperature dependence are compared with quadrupole relaxation measurements of Riegel et al. and Kerlin et al. in liquid gallium. Agreement is found only with the data of Riegel et al. (orig.) [de
Non-exponential dynamic relaxation in strongly nonequilibrium nonideal plasmas
International Nuclear Information System (INIS)
Morozov, I V; Norman, G E
2003-01-01
Relaxation of kinetic energy to the equilibrium state is simulated by the molecular dynamics method for nonideal two-component non-degenerate plasmas. Three limiting examples of initial states of strongly nonequilibrium plasma are considered: zero electron velocities, zero ion velocities and zero velocities of both electrons and ions. The initial non-exponential stage, its duration τ nB and subsequent exponential stages of the relaxation process are studied for a wide range of the nonideality parameter and the ion mass
Methyl group rotation and nuclear relaxation at low temperatures
International Nuclear Information System (INIS)
Zweers, A.E.
1976-01-01
This thesis deals with the proton spin-lattice relaxation of some methyl group compounds at liquid helium temperatures. In these molecular crystals, an energy difference between the ground and first rotational state of the methyl group occurs, the so-called tunnelling splitting, which is of the order of a few degrees Kelvin. This means that the high temperature approximation is inappropriate for the description of the occupation densities of the two lowest rotational levels. A description of the properties of the methyl group in connection with relaxation
Bayesian NL interpretation and learning
Zeevat, H.
2011-01-01
Everyday natural language communication is normally successful, even though contemporary computational linguistics has shown that NL is characterised by very high degree of ambiguity and the results of stochastic methods are not good enough to explain the high success rate. Bayesian natural language
Bayesian image restoration, using configurations
DEFF Research Database (Denmark)
Thorarinsdottir, Thordis
configurations are expressed in terms of the mean normal measure of the random set. These probabilities are used as prior probabilities in a Bayesian image restoration approach. Estimation of the remaining parameters in the model is outlined for salt and pepper noise. The inference in the model is discussed...
Bayesian image restoration, using configurations
DEFF Research Database (Denmark)
Thorarinsdottir, Thordis Linda
2006-01-01
configurations are expressed in terms of the mean normal measure of the random set. These probabilities are used as prior probabilities in a Bayesian image restoration approach. Estimation of the remaining parameters in the model is outlined for the salt and pepper noise. The inference in the model is discussed...
Differentiated Bayesian Conjoint Choice Designs
Z. Sándor (Zsolt); M. Wedel (Michel)
2003-01-01
textabstractPrevious conjoint choice design construction procedures have produced a single design that is administered to all subjects. This paper proposes to construct a limited set of different designs. The designs are constructed in a Bayesian fashion, taking into account prior uncertainty about
Bayesian Networks and Influence Diagrams
DEFF Research Database (Denmark)
Kjærulff, Uffe Bro; Madsen, Anders Læsø
Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis, Second Edition, provides a comprehensive guide for practitioners who wish to understand, construct, and analyze intelligent systems for decision support based on probabilistic networks. This new edition contains six new...
Bayesian Sampling using Condition Indicators
DEFF Research Database (Denmark)
Faber, Michael H.; Sørensen, John Dalsgaard
2002-01-01
of condition indicators introduced by Benjamin and Cornell (1970) a Bayesian approach to quality control is formulated. The formulation is then extended to the case where the quality control is based on sampling of indirect information about the condition of the components, i.e. condition indicators...
Bayesian Classification of Image Structures
DEFF Research Database (Denmark)
Goswami, Dibyendu; Kalkan, Sinan; Krüger, Norbert
2009-01-01
In this paper, we describe work on Bayesian classi ers for distinguishing between homogeneous structures, textures, edges and junctions. We build semi-local classiers from hand-labeled images to distinguish between these four different kinds of structures based on the concept of intrinsic dimensi...
Bayesian estimates of linkage disequilibrium
Directory of Open Access Journals (Sweden)
Abad-Grau María M
2007-06-01
Full Text Available Abstract Background The maximum likelihood estimator of D' – a standard measure of linkage disequilibrium – is biased toward disequilibrium, and the bias is particularly evident in small samples and rare haplotypes. Results This paper proposes a Bayesian estimation of D' to address this problem. The reduction of the bias is achieved by using a prior distribution on the pair-wise associations between single nucleotide polymorphisms (SNPs that increases the likelihood of equilibrium with increasing physical distances between pairs of SNPs. We show how to compute the Bayesian estimate using a stochastic estimation based on MCMC methods, and also propose a numerical approximation to the Bayesian estimates that can be used to estimate patterns of LD in large datasets of SNPs. Conclusion Our Bayesian estimator of D' corrects the bias toward disequilibrium that affects the maximum likelihood estimator. A consequence of this feature is a more objective view about the extent of linkage disequilibrium in the human genome, and a more realistic number of tagging SNPs to fully exploit the power of genome wide association studies.
3-D contextual Bayesian classifiers
DEFF Research Database (Denmark)
Larsen, Rasmus
In this paper we will consider extensions of a series of Bayesian 2-D contextual classification pocedures proposed by Owen (1984) Hjort & Mohn (1984) and Welch & Salter (1971) and Haslett (1985) to 3 spatial dimensions. It is evident that compared to classical pixelwise classification further...
Bayesian Alternation During Tactile Augmentation
Directory of Open Access Journals (Sweden)
Caspar Mathias Goeke
2016-10-01
Full Text Available A large number of studies suggest that the integration of multisensory signals by humans is well described by Bayesian principles. However, there are very few reports about cue combination between a native and an augmented sense. In particular, we asked the question whether adult participants are able to integrate an augmented sensory cue with existing native sensory information. Hence for the purpose of this study we build a tactile augmentation device. Consequently, we compared different hypotheses of how untrained adult participants combine information from a native and an augmented sense. In a two-interval forced choice (2 IFC task, while subjects were blindfolded and seated on a rotating platform, our sensory augmentation device translated information on whole body yaw rotation to tactile stimulation. Three conditions were realized: tactile stimulation only (augmented condition, rotation only (native condition, and both augmented and native information (bimodal condition. Participants had to choose one out of two consecutive rotations with higher angular rotation. For the analysis, we fitted the participants’ responses with a probit model and calculated the just notable difference (JND. Then we compared several models for predicting bimodal from unimodal responses. An objective Bayesian alternation model yielded a better prediction (χred2 = 1.67 than the Bayesian integration model (χred2= 4.34. Slightly higher accuracy showed a non-Bayesian winner takes all model (χred2= 1.64, which either used only native or only augmented values per subject for prediction. However the performance of the Bayesian alternation model could be substantially improved (χred2= 1.09 utilizing subjective weights obtained by a questionnaire. As a result, the subjective Bayesian alternation model predicted bimodal performance most accurately among all tested models. These results suggest that information from augmented and existing sensory modalities in
Topics in Bayesian statistics and maximum entropy
International Nuclear Information System (INIS)
Mutihac, R.; Cicuttin, A.; Cerdeira, A.; Stanciulescu, C.
1998-12-01
Notions of Bayesian decision theory and maximum entropy methods are reviewed with particular emphasis on probabilistic inference and Bayesian modeling. The axiomatic approach is considered as the best justification of Bayesian analysis and maximum entropy principle applied in natural sciences. Particular emphasis is put on solving the inverse problem in digital image restoration and Bayesian modeling of neural networks. Further topics addressed briefly include language modeling, neutron scattering, multiuser detection and channel equalization in digital communications, genetic information, and Bayesian court decision-making. (author)
Bayesian analysis of rare events
Energy Technology Data Exchange (ETDEWEB)
Straub, Daniel, E-mail: straub@tum.de; Papaioannou, Iason; Betz, Wolfgang
2016-06-01
In many areas of engineering and science there is an interest in predicting the probability of rare events, in particular in applications related to safety and security. Increasingly, such predictions are made through computer models of physical systems in an uncertainty quantification framework. Additionally, with advances in IT, monitoring and sensor technology, an increasing amount of data on the performance of the systems is collected. This data can be used to reduce uncertainty, improve the probability estimates and consequently enhance the management of rare events and associated risks. Bayesian analysis is the ideal method to include the data into the probabilistic model. It ensures a consistent probabilistic treatment of uncertainty, which is central in the prediction of rare events, where extrapolation from the domain of observation is common. We present a framework for performing Bayesian updating of rare event probabilities, termed BUS. It is based on a reinterpretation of the classical rejection-sampling approach to Bayesian analysis, which enables the use of established methods for estimating probabilities of rare events. By drawing upon these methods, the framework makes use of their computational efficiency. These methods include the First-Order Reliability Method (FORM), tailored importance sampling (IS) methods and Subset Simulation (SuS). In this contribution, we briefly review these methods in the context of the BUS framework and investigate their applicability to Bayesian analysis of rare events in different settings. We find that, for some applications, FORM can be highly efficient and is surprisingly accurate, enabling Bayesian analysis of rare events with just a few model evaluations. In a general setting, BUS implemented through IS and SuS is more robust and flexible.
Nuclear spin relaxation due to chemical shift anisotropy of gas-phase 129Xe.
Hanni, Matti; Lantto, Perttu; Vaara, Juha
2011-08-14
Nuclear spin relaxation provides detailed dynamical information on molecular systems and materials. Here, first-principles modeling of the chemical shift anisotropy (CSA) relaxation time for the prototypic monoatomic (129)Xe gas is carried out, both complementing and predicting the results of NMR measurements. Our approach is based on molecular dynamics simulations combined with pre-parametrized ab initio binary nuclear shielding tensors, an "NMR force field". By using the Redfield relaxation formalism, the simulated CSA time correlation functions lead to spectral density functions that, for the first time, quantitatively determine the experimental spin-lattice relaxation times T(1). The quality requirements on both the Xe-Xe interaction potential and binary shielding tensor are investigated in the context of CSA T(1). Persistent dimers Xe(2) are found to be responsible for the CSA relaxation mechanism in the low-density limit of the gas, completely in line with the earlier experimental findings.
Peeling mode relaxation ELM model
International Nuclear Information System (INIS)
Gimblett, C. G.
2006-01-01
This paper discusses an approach to modelling Edge Localised Modes (ELMs) in which toroidal peeling modes are envisaged to initiate a constrained relaxation of the tokamak outer region plasma. Relaxation produces both a flattened edge current profile (which tends to further destabilise a peeling mode), and a plasma-vacuum negative current sheet which has a counteracting stabilising influence; the balance that is struck between these two effects determines the radial extent (rE) of the ELM relaxed region. The model is sensitive to the precise position of the mode rational surfaces to the plasma surface and hence there is a 'deterministic scatter' in the results that has an accord with experimental data. The toroidal peeling stability criterion involves the edge pressure, and using this in conjunction with predictions of rE allows us to evaluate the ELM energy losses and compare with experiment. Predictions of trends with the edge safety factor and collisionality are also made
Bayesian phylogenetic estimation of fossil ages.
Drummond, Alexei J; Stadler, Tanja
2016-07-19
Recent advances have allowed for both morphological fossil evidence and molecular sequences to be integrated into a single combined inference of divergence dates under the rule of Bayesian probability. In particular, the fossilized birth-death tree prior and the Lewis-Mk model of discrete morphological evolution allow for the estimation of both divergence times and phylogenetic relationships between fossil and extant taxa. We exploit this statistical framework to investigate the internal consistency of these models by producing phylogenetic estimates of the age of each fossil in turn, within two rich and well-characterized datasets of fossil and extant species (penguins and canids). We find that the estimation accuracy of fossil ages is generally high with credible intervals seldom excluding the true age and median relative error in the two datasets of 5.7% and 13.2%, respectively. The median relative standard error (RSD) was 9.2% and 7.2%, respectively, suggesting good precision, although with some outliers. In fact, in the two datasets we analyse, the phylogenetic estimate of fossil age is on average less than 2 Myr from the mid-point age of the geological strata from which it was excavated. The high level of internal consistency found in our analyses suggests that the Bayesian statistical model employed is an adequate fit for both the geological and morphological data, and provides evidence from real data that the framework used can accurately model the evolution of discrete morphological traits coded from fossil and extant taxa. We anticipate that this approach will have diverse applications beyond divergence time dating, including dating fossils that are temporally unconstrained, testing of the 'morphological clock', and for uncovering potential model misspecification and/or data errors when controversial phylogenetic hypotheses are obtained based on combined divergence dating analyses.This article is part of the themed issue 'Dating species divergences using
gamma. -relaxation process in crystallizable polymers
Energy Technology Data Exchange (ETDEWEB)
Mindiyarov, Kh G; Zelenev, Yu V; Bartenev, G M [Birskij Gosudarstvennyj Pedagogicheskij Inst. (USSR)
1975-07-01
In the present paper, with the aid of radiothermoluminescence technique ..gamma..-relaxation processes are investigated, which are conditioned by molecular mobility and are associated with defects in the crystalline structure of polymers PEh, PP, and elastomers PIB, NK, SKD, SKI exposed to ..gamma..-rays of Co/sup 60/ at a dose rate of 1 Mrad. The shape of the thermoluminescence curve, i.e. the luminescence intensity in the ..cap alpha.. - ..gamma..-maxima, their relationship, position with respect to temperature are strongly dependent on the degree of crystallinity, on the thermal and mechanical prehistory. In highly crystalline samples of PEh and PP ..cap alpha..-maximum may be absent. Dependence has been studied of the luminescence intensity in the ..cap alpha..- and ..gamma..-maxima (Isub(..cap alpha..)/Isub(..gamma..)) on the crystallization temperature; the curve passes through the minimum when the crystallization rate is maximum. The relationship Isub(..gamma..)re of crystallinity degree.
F19 relaxation in non-magnetic hexafluorides
International Nuclear Information System (INIS)
Rigny, P.
1969-01-01
The interesting properties of the fluorine magnetic resonance in the hexafluorides of molybdenum, tungsten and uranium, are very much due to large anisotropies of the chemical shift tensors. In the solid phases these anisotropies, the values of which are deduced from line shape studies, allow one to show that the molecules undergo hindered rotations about the metal atom. The temperature and frequency dependence of the fluorine longitudinal relaxation times shows that the relaxation is due to the molecular motion. The dynamical parameters of this motion are then deduced from the complete study of the fluorine relaxation in the rotating frame. In the liquid phases, the existence of anisotropies allows an estimation of the different contributions to the relaxation. In particular, the frequency and temperature dependence of the relaxation shows it to be dominated by the spin-rotation interaction. We have shown that the strength of this interaction can be deduced from the chemical shifts, and the angle through which the molecule rotates quasi-freely can be determined. In the hexafluorides, this angle is roughly one radian at 70 C, and with the help of this value, the friction coefficients which describe the intermolecular interactions are discussed. (author) [fr
Bayesian tomography by interacting Markov chains
Romary, T.
2017-12-01
In seismic tomography, we seek to determine the velocity of the undergound from noisy first arrival travel time observations. In most situations, this is an ill posed inverse problem that admits several unperfect solutions. Given an a priori distribution over the parameters of the velocity model, the Bayesian formulation allows to state this problem as a probabilistic one, with a solution under the form of a posterior distribution. The posterior distribution is generally high dimensional and may exhibit multimodality. Moreover, as it is known only up to a constant, the only sensible way to addressthis problem is to try to generate simulations from the posterior. The natural tools to perform these simulations are Monte Carlo Markov chains (MCMC). Classical implementations of MCMC algorithms generally suffer from slow mixing: the generated states are slow to enter the stationary regime, that is to fit the observations, and when one mode of the posterior is eventually identified, it may become difficult to visit others. Using a varying temperature parameter relaxing the constraint on the data may help to enter the stationary regime. Besides, the sequential nature of MCMC makes them ill fitted toparallel implementation. Running a large number of chains in parallel may be suboptimal as the information gathered by each chain is not mutualized. Parallel tempering (PT) can be seen as a first attempt to make parallel chains at different temperatures communicate but only exchange information between current states. In this talk, I will show that PT actually belongs to a general class of interacting Markov chains algorithm. I will also show that this class enables to design interacting schemes that can take advantage of the whole history of the chain, by authorizing exchanges toward already visited states. The algorithms will be illustrated with toy examples and an application to first arrival traveltime tomography.
Energy Technology Data Exchange (ETDEWEB)
Schubert, Alexander, E-mail: schubert@irsamc.ups-tlse.fr; Meier, Christoph [Laboratoire Collisions Agrégats et Réactivité, IRSAMC, UMR CNRS 5589, Université Paul Sabatier, 31062 Toulouse (France); Falvo, Cyril [Institut des Sciences Moléculaires d’Orsay (ISMO), CNRS, Univ. Paris-Sud, Université Paris-Saclay, 91405 Orsay (France)
2016-08-07
We present mixed quantum-classical simulations on relaxation and dephasing of vibrationally excited carbon monoxide within a protein environment. The methodology is based on a vibrational surface hopping approach treating the vibrational states of CO quantum mechanically, while all remaining degrees of freedom are described by means of classical molecular dynamics. The CO vibrational states form the “surfaces” for the classical trajectories of protein and solvent atoms. In return, environmentally induced non-adiabatic couplings between these states cause transitions describing the vibrational relaxation from first principles. The molecular dynamics simulation yields a detailed atomistic picture of the energy relaxation pathways, taking the molecular structure and dynamics of the protein and its solvent fully into account. Using the ultrafast photolysis of CO in the hemoprotein FixL as an example, we study the relaxation of vibrationally excited CO and evaluate the role of each of the FixL residues forming the heme pocket.
Relaxation properties in classical diamagnetism
Carati, A.; Benfenati, F.; Galgani, L.
2011-06-01
It is an old result of Bohr that, according to classical statistical mechanics, at equilibrium a system of electrons in a static magnetic field presents no magnetization. Thus a magnetization can occur only in an out of equilibrium state, such as that produced through the Foucault currents when a magnetic field is switched on. It was suggested by Bohr that, after the establishment of such a nonequilibrium state, the system of electrons would quickly relax back to equilibrium. In the present paper, we study numerically the relaxation to equilibrium in a modified Bohr model, which is mathematically equivalent to a billiard with obstacles, immersed in a magnetic field that is adiabatically switched on. We show that it is not guaranteed that equilibrium is attained within the typical time scales of microscopic dynamics. Depending on the values of the parameters, one has a relaxation either to equilibrium or to a diamagnetic (presumably metastable) state. The analogy with the relaxation properties in the Fermi Pasta Ulam problem is also pointed out.
Onsager relaxation of toroidal plasmas
International Nuclear Information System (INIS)
Samain, A.; Nguyen, F.
1997-01-01
The slow relaxation of isolated toroidal plasmas towards their thermodynamical equilibrium is studied in an Onsager framework based on the entropy metric. The basic tool is a variational principle, equivalent to the kinetic equation, involving the profiles of density, temperature, electric potential, electric current. New minimization procedures are proposed to obtain entropy and entropy production rate functionals. (author)
Anisotropic spin relaxation in graphene
Tombros, N.; Tanabe, S.; Veligura, A.; Jozsa, C.; Popinciuc, M.; Jonkman, H. T.; van Wees, B. J.
2008-01-01
Spin relaxation in graphene is investigated in electrical graphene spin valve devices in the nonlocal geometry. Ferromagnetic electrodes with in-plane magnetizations inject spins parallel to the graphene layer. They are subject to Hanle spin precession under a magnetic field B applied perpendicular
Stochastic and Chaotic Relaxation Oscillations
Grasman, J.; Roerdink, J.B.T.M.
1988-01-01
For relaxation oscillators stochastic and chaotic dynamics are investigated. The effect of random perturbations upon the period is computed. For an extended system with additional state variables chaotic behavior can be expected. As an example, the Van der Pol oscillator is changed into a
Tensions relaxation in Zircaloy-4
International Nuclear Information System (INIS)
Cuniberti, A.M.; Picasso, A.C.
1990-01-01
Traction and stress relaxation studies were performed on polycrystalline Zry-4 at room temperature. The effect of loading velocity on the plastic behaviour of the material is discussed, analysing log σ vs. log dε/dt at different deformation levels. The contribution introduced by the testing machine was taken into account in data evaluation. (Author). 7 refs., 3 figs., 3 tabs
Bayesian estimation methods in metrology
International Nuclear Information System (INIS)
Cox, M.G.; Forbes, A.B.; Harris, P.M.
2004-01-01
In metrology -- the science of measurement -- a measurement result must be accompanied by a statement of its associated uncertainty. The degree of validity of a measurement result is determined by the validity of the uncertainty statement. In recognition of the importance of uncertainty evaluation, the International Standardization Organization in 1995 published the Guide to the Expression of Uncertainty in Measurement and the Guide has been widely adopted. The validity of uncertainty statements is tested in interlaboratory comparisons in which an artefact is measured by a number of laboratories and their measurement results compared. Since the introduction of the Mutual Recognition Arrangement, key comparisons are being undertaken to determine the degree of equivalence of laboratories for particular measurement tasks. In this paper, we discuss the possible development of the Guide to reflect Bayesian approaches and the evaluation of key comparison data using Bayesian estimation methods
Deep Learning and Bayesian Methods
Directory of Open Access Journals (Sweden)
Prosper Harrison B.
2017-01-01
Full Text Available A revolution is underway in which deep neural networks are routinely used to solve diffcult problems such as face recognition and natural language understanding. Particle physicists have taken notice and have started to deploy these methods, achieving results that suggest a potentially significant shift in how data might be analyzed in the not too distant future. We discuss a few recent developments in the application of deep neural networks and then indulge in speculation about how such methods might be used to automate certain aspects of data analysis in particle physics. Next, the connection to Bayesian methods is discussed and the paper ends with thoughts on a significant practical issue, namely, how, from a Bayesian perspective, one might optimize the construction of deep neural networks.
Bayesian inference on proportional elections.
Directory of Open Access Journals (Sweden)
Gabriel Hideki Vatanabe Brunello
Full Text Available Polls for majoritarian voting systems usually show estimates of the percentage of votes for each candidate. However, proportional vote systems do not necessarily guarantee the candidate with the most percentage of votes will be elected. Thus, traditional methods used in majoritarian elections cannot be applied on proportional elections. In this context, the purpose of this paper was to perform a Bayesian inference on proportional elections considering the Brazilian system of seats distribution. More specifically, a methodology to answer the probability that a given party will have representation on the chamber of deputies was developed. Inferences were made on a Bayesian scenario using the Monte Carlo simulation technique, and the developed methodology was applied on data from the Brazilian elections for Members of the Legislative Assembly and Federal Chamber of Deputies in 2010. A performance rate was also presented to evaluate the efficiency of the methodology. Calculations and simulations were carried out using the free R statistical software.
BAYESIAN IMAGE RESTORATION, USING CONFIGURATIONS
Directory of Open Access Journals (Sweden)
Thordis Linda Thorarinsdottir
2011-05-01
Full Text Available In this paper, we develop a Bayesian procedure for removing noise from images that can be viewed as noisy realisations of random sets in the plane. The procedure utilises recent advances in configuration theory for noise free random sets, where the probabilities of observing the different boundary configurations are expressed in terms of the mean normal measure of the random set. These probabilities are used as prior probabilities in a Bayesian image restoration approach. Estimation of the remaining parameters in the model is outlined for salt and pepper noise. The inference in the model is discussed in detail for 3 X 3 and 5 X 5 configurations and examples of the performance of the procedure are given.
Relaxation model of radiation-induced conductivity in polymers
Zhutayeva, Yu. R.; Khatipov, S. A.
1999-05-01
The paper suggests a relaxation model of radiation-induced conductivity (RIC) in polymers. According to the model, the transfer of charges generated in the polymer volume by ionizing radiation takes place with the participation of molecular relaxation processes. The mechanism of electron transport consists in the transfer of the charge directly between traps when they draw close to one another due to the rotation of macromolecule segments. The numerical solutions of the corresponding kinetic equations for different distribution functions Q( τ) of the times of molecular relaxation and for different functions of the probability P( τ, τ') of charge transfer in the `overlapping' regions of the diffusion spheres of the segments are analyzed. The relaxation model provides an explanation of the non-Arrhenius behavior of the RIC temperature dependence, the power dependence of RIC on the dose rate with a power index in the interval 0.5-1.0, the appearance of maxima in the curves of the RIC temporal dependence and their irreversible character in the region of large dose rates (more than 1 Gy/s). The model can be used for interpreting polymer RIC in conditions of kinetic mobility of macromolecules.
Space Shuttle RTOS Bayesian Network
Morris, A. Terry; Beling, Peter A.
2001-01-01
With shrinking budgets and the requirements to increase reliability and operational life of the existing orbiter fleet, NASA has proposed various upgrades for the Space Shuttle that are consistent with national space policy. The cockpit avionics upgrade (CAU), a high priority item, has been selected as the next major upgrade. The primary functions of cockpit avionics include flight control, guidance and navigation, communication, and orbiter landing support. Secondary functions include the provision of operational services for non-avionics systems such as data handling for the payloads and caution and warning alerts to the crew. Recently, a process to selection the optimal commercial-off-the-shelf (COTS) real-time operating system (RTOS) for the CAU was conducted by United Space Alliance (USA) Corporation, which is a joint venture between Boeing and Lockheed Martin, the prime contractor for space shuttle operations. In order to independently assess the RTOS selection, NASA has used the Bayesian network-based scoring methodology described in this paper. Our two-stage methodology addresses the issue of RTOS acceptability by incorporating functional, performance and non-functional software measures related to reliability, interoperability, certifiability, efficiency, correctness, business, legal, product history, cost and life cycle. The first stage of the methodology involves obtaining scores for the various measures using a Bayesian network. The Bayesian network incorporates the causal relationships between the various and often competing measures of interest while also assisting the inherently complex decision analysis process with its ability to reason under uncertainty. The structure and selection of prior probabilities for the network is extracted from experts in the field of real-time operating systems. Scores for the various measures are computed using Bayesian probability. In the second stage, multi-criteria trade-off analyses are performed between the scores
Multiview Bayesian Correlated Component Analysis
DEFF Research Database (Denmark)
Kamronn, Simon Due; Poulsen, Andreas Trier; Hansen, Lars Kai
2015-01-01
are identical. Here we propose a hierarchical probabilistic model that can infer the level of universality in such multiview data, from completely unrelated representations, corresponding to canonical correlation analysis, to identical representations as in correlated component analysis. This new model, which...... we denote Bayesian correlated component analysis, evaluates favorably against three relevant algorithms in simulated data. A well-established benchmark EEG data set is used to further validate the new model and infer the variability of spatial representations across multiple subjects....
Sleep, Stress & Relaxation: Rejuvenate Body & Mind
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Bayesian Option Pricing Framework with Stochastic Volatility for FX Data
Directory of Open Access Journals (Sweden)
Ying Wang
2016-12-01
Full Text Available The application of stochastic volatility (SV models in the option pricing literature usually assumes that the market has sufficient option data to calibrate the model’s risk-neutral parameters. When option data are insufficient or unavailable, market practitioners must estimate the model from the historical returns of the underlying asset and then transform the resulting model into its risk-neutral equivalent. However, the likelihood function of an SV model can only be expressed in a high-dimensional integration, which makes the estimation a highly challenging task. The Bayesian approach has been the classical way to estimate SV models under the data-generating (physical probability measure, but the transformation from the estimated physical dynamic into its risk-neutral counterpart has not been addressed. Inspired by the generalized autoregressive conditional heteroskedasticity (GARCH option pricing approach by Duan in 1995, we propose an SV model that enables us to simultaneously and conveniently perform Bayesian inference and transformation into risk-neutral dynamics. Our model relaxes the normality assumption on innovations of both return and volatility processes, and our empirical study shows that the estimated option prices generate realistic implied volatility smile shapes. In addition, the volatility premium is almost flat across strike prices, so adding a few option data to the historical time series of the underlying asset can greatly improve the estimation of option prices.
A Bayesian perspective on Markovian dynamics and the fluctuation theorem
Virgo, Nathaniel
2013-08-01
One of E. T. Jaynes' most important achievements was to derive statistical mechanics from the maximum entropy (MaxEnt) method. I re-examine a relatively new result in statistical mechanics, the Evans-Searles fluctuation theorem, from a MaxEnt perspective. This is done in the belief that interpreting such results in Bayesian terms will lead to new advances in statistical physics. The version of the fluctuation theorem that I will discuss applies to discrete, stochastic systems that begin in a non-equilibrium state and relax toward equilibrium. I will show that for such systems the fluctuation theorem can be seen as a consequence of the fact that the equilibrium distribution must obey the property of detailed balance. Although the principle of detailed balance applies only to equilibrium ensembles, it puts constraints on the form of non-equilibrium trajectories. This will be made clear by taking a novel kind of Bayesian perspective, in which the equilibrium distribution is seen as a prior over the system's set of possible trajectories. Non-equilibrium ensembles are calculated from this prior using Bayes' theorem, with the initial conditions playing the role of the data. I will also comment on the implications of this perspective for the question of how to derive the second law.
An Adaptively Accelerated Bayesian Deblurring Method with Entropy Prior
Directory of Open Access Journals (Sweden)
Yong-Hoon Kim
2008-05-01
Full Text Available The development of an efficient adaptively accelerated iterative deblurring algorithm based on Bayesian statistical concept has been reported. Entropy of an image has been used as a Ã¢Â€ÂœpriorÃ¢Â€Â distribution and instead of additive form, used in conventional acceleration methods an exponent form of relaxation constant has been used for acceleration. Thus the proposed method is called hereafter as adaptively accelerated maximum a posteriori with entropy prior (AAMAPE. Based on empirical observations in different experiments, the exponent is computed adaptively using first-order derivatives of the deblurred image from previous two iterations. This exponent improves speed of the AAMAPE method in early stages and ensures stability at later stages of iteration. In AAMAPE method, we also consider the constraint of the nonnegativity and flux conservation. The paper discusses the fundamental idea of the Bayesian image deblurring with the use of entropy as prior, and the analytical analysis of superresolution and the noise amplification characteristics of the proposed method. The experimental results show that the proposed AAMAPE method gives lower RMSE and higher SNR in 44% lesser iterations as compared to nonaccelerated maximum a posteriori with entropy prior (MAPE method. Moreover, AAMAPE followed by wavelet wiener filtering gives better result than the state-of-the-art methods.
DPpackage: Bayesian Semi- and Nonparametric Modeling in R
Directory of Open Access Journals (Sweden)
Alejandro Jara
2011-04-01
Full Text Available Data analysis sometimes requires the relaxation of parametric assumptions in order to gain modeling flexibility and robustness against mis-specification of the probability model. In the Bayesian context, this is accomplished by placing a prior distribution on a function space, such as the space of all probability distributions or the space of all regression functions. Unfortunately, posterior distributions ranging over function spaces are highly complex and hence sampling methods play a key role. This paper provides an introduction to a simple, yet comprehensive, set of programs for the implementation of some Bayesian nonparametric and semiparametric models in R, DPpackage. Currently, DPpackage includes models for marginal and conditional density estimation, receiver operating characteristic curve analysis, interval-censored data, binary regression data, item response data, longitudinal and clustered data using generalized linear mixed models, and regression data using generalized additive models. The package also contains functions to compute pseudo-Bayes factors for model comparison and for eliciting the precision parameter of the Dirichlet process prior, and a general purpose Metropolis sampling algorithm. To maximize computational efficiency, the actual sampling for each model is carried out using compiled C, C++ or Fortran code.
The relaxational behaviour of poly-(vinylidene fluoride) before and after gamma-irradiation
International Nuclear Information System (INIS)
Callens, A.
The main purpose of this work was to investigate how molecular chain reorganization may affect the physical property of polymers. This may be done by the analysis of the as received and post-irradiation relaxation spectra of the semi-crystalline linear chain polymer polyvinylidene fluoride (PVDF), which has been gamma-irradiated up to doses of 1 grad. The effects of the irradiation on the material are primarly main chain cross-linking production of unsaturated bonds and crystallite degradation. To reach a complete interpretation of the relaxation spectra, it is necessary to incorporate a third phase into the analysis besides the amorphous viscoelastic region (AVR) and the crystalline viscoelastic region (CVR), the intermediate phase. The amorphous phase (AVR) is at the origin of the relaxation effects occurring in the temperature region below room temperature. The saturation like behaviour of the cross-linking in the amorphous phase is at the origin of the intensity decrease, temperature shift and peak broadening of the beta relaxation. There is a large amount of evidence that in the neighbourhood of the beta relaxation, relaxation effects are created through irradiation, as mainly revealed by TSD-spectra (thermalloy stimulated depolarisation). The intensity of the gamma relaxation, gradually increases with dose, which has been attributed to the production of disordered chain from the debris of radiation enhanced crystallite destruction. The relaxation effect, occuring at the temperatures between AVR and CVR, is assigned to the long amorphous chain segments attached partly to the crystallites, mainly from the consideration of the similarity of the dose enhanced decrease in intensity of both beta and βsub(μ)-effects. The increase with dose of the intensity of the α1 relaxation, which has been classified within CVR, confirms the grainboundary hypothesis. The second component of CVR (α2 relaxation) is due to relaxation effects of molecular chains belonging to the
12th Brazilian Meeting on Bayesian Statistics
Louzada, Francisco; Rifo, Laura; Stern, Julio; Lauretto, Marcelo
2015-01-01
Through refereed papers, this volume focuses on the foundations of the Bayesian paradigm; their comparison to objectivistic or frequentist Statistics counterparts; and the appropriate application of Bayesian foundations. This research in Bayesian Statistics is applicable to data analysis in biostatistics, clinical trials, law, engineering, and the social sciences. EBEB, the Brazilian Meeting on Bayesian Statistics, is held every two years by the ISBrA, the International Society for Bayesian Analysis, one of the most active chapters of the ISBA. The 12th meeting took place March 10-14, 2014 in Atibaia. Interest in foundations of inductive Statistics has grown recently in accordance with the increasing availability of Bayesian methodological alternatives. Scientists need to deal with the ever more difficult choice of the optimal method to apply to their problem. This volume shows how Bayes can be the answer. The examination and discussion on the foundations work towards the goal of proper application of Bayesia...
A Bayesian model for binary Markov chains
Directory of Open Access Journals (Sweden)
Belkheir Essebbar
2004-02-01
Full Text Available This note is concerned with Bayesian estimation of the transition probabilities of a binary Markov chain observed from heterogeneous individuals. The model is founded on the Jeffreys' prior which allows for transition probabilities to be correlated. The Bayesian estimator is approximated by means of Monte Carlo Markov chain (MCMC techniques. The performance of the Bayesian estimates is illustrated by analyzing a small simulated data set.
The effect of the Magnus force on skyrmion relaxation dynamics
Brown, Barton L.; Täuber, Uwe C.; Pleimling, Michel
2018-01-01
We perform systematic Langevin molecular dynamics simulations of interacting skyrmions in thin films. The interplay between Magnus force, repulsive skyrmion-skyrmion interaction and thermal noise yields different regimes during non-equilibrium relaxation. In the noise-dominated regime the Magnus force enhances the disordering effects of the thermal noise. In the Magnus-force-dominated regime, the Magnus force cooperates with the skyrmion-skyrmion interaction to yield a dynamic regime with slo...
Vibrational energy relaxation: proposed pathway of fast local chromatin denaturation
International Nuclear Information System (INIS)
Harder, D.; Greinert, R.
2002-01-01
The molecular mechanism responsible for the a component of exchange-type chromosome aberrations, of chromosome fragmentation and of reproductive cell death is one of the unsolved issues of radiation biology. Under review is whether vibrational energy relaxation in the constitutive biopolymers of chromatin, induced by inelastic energy deposition events and mediated via highly excited vibrational states, may provide a pathway of fast local chromatin denaturation, thereby producing the severe DNA lesion able to interact chemically with other, non-damaged chromatin. (author)
Identification of structural relaxation in the dielectric response of water
DEFF Research Database (Denmark)
Hansen, Jesper Schmidt; Kisliuk, Alexander; Solokov, Alexei P.
2016-01-01
One century ago pioneering dielectric results obtained for water and n-alcohols triggered the advent of molecular rotation diffusion theory considered by Debye to describe the primary dielectric absorption in these liquids. Comparing dielectric, viscoelastic, and light scattering results, we...... unambiguously demonstrate that the structural relaxation appears only as a high-frequency shoulder in the dielectric spectra of water. In contrast, the main dielectric peak is related to a supramolecular structure, analogous to the Debye-like peak observed in monoalcohols....
Relaxation Techniques to Manage IBS Symptoms
... for 15–20 seconds and then begin again. Progressive Muscle Relaxation This method of relaxation focuses on ... helpful, please consider supporting IFFGD with a small tax- deductible donation. Make Donation Adapted from IFFGD Publication # ...
Relaxation and Distraction in Experimental Desensitization.
Weir, R. O.; Marshall, W. L.
1980-01-01
Compared experimental desensitization with a procedure that replaced relaxation with a distraction task and with an approach that combined both relaxation and distraction. Desensitization generally was more effective than the other two procedures. (Author)
Relaxation as a Factor in Semantic Desensitization
Bechtel, James E.; McNamara, J. Regis
1975-01-01
Relaxation and semantic desensitization were used to alleviate the fear of phobic females. Results showed that semantic desensitization, alone or in combination with relaxation, failed to modify the evaluative meanings evoked by the feared object. (SE)
3rd Bayesian Young Statisticians Meeting
Lanzarone, Ettore; Villalobos, Isadora; Mattei, Alessandra
2017-01-01
This book is a selection of peer-reviewed contributions presented at the third Bayesian Young Statisticians Meeting, BAYSM 2016, Florence, Italy, June 19-21. The meeting provided a unique opportunity for young researchers, M.S. students, Ph.D. students, and postdocs dealing with Bayesian statistics to connect with the Bayesian community at large, to exchange ideas, and to network with others working in the same field. The contributions develop and apply Bayesian methods in a variety of fields, ranging from the traditional (e.g., biostatistics and reliability) to the most innovative ones (e.g., big data and networks).
Plasmon-mediated energy relaxation in graphene
Energy Technology Data Exchange (ETDEWEB)
Ferry, D. K. [School of Electrical, Computer, and Energy Engineering, Arizona State University, Tempe, Arizona 85287-5706 (United States); Somphonsane, R. [Department of Physics, King Mongkut' s Institute of Technology, Ladkrabang, Bangkok 10520 (Thailand); Ramamoorthy, H.; Bird, J. P. [Department of Electrical Engineering, University at Buffalo, the State University of New York, Buffalo, New York 14260-1500 (United States)
2015-12-28
Energy relaxation of hot carriers in graphene is studied at low temperatures, where the loss rate may differ significantly from that predicted for electron-phonon interactions. We show here that plasmons, important in the relaxation of energetic carriers in bulk semiconductors, can also provide a pathway for energy relaxation in transport experiments in graphene. We obtain a total loss rate to plasmons that results in energy relaxation times whose dependence on temperature and density closely matches that found experimentally.
Nonlinear Relaxation in Population Dynamics
Cirone, Markus A.; de Pasquale, Ferdinando; Spagnolo, Bernardo
We analyze the nonlinear relaxation of a complex ecosystem composed of many interacting species. The ecological system is described by generalized Lotka-Volterra equations with a multiplicative noise. The transient dynamics is studied in the framework of the mean field theory and with random interaction between the species. We focus on the statistical properties of the asymptotic behaviour of the time integral of the ith population and on the distribution of the population and of the local field.
Structural relaxation: low temperature properties
International Nuclear Information System (INIS)
Cruz, F. de la
1984-01-01
We discuss the changes in transport and superconducting properties of amorphous Zr 70 Cu 30 , induced by thermal relaxation. The experimental results are used to investigate the relation between the microscopic parameters and the observed physical properties. It is shown that the density of eletronic states determines the shift Tc as well as the variation of the electrical resistivity. It is necessary to assume strong hybridization between s and d bands to understand the eletrodynamic response of the superconductor. (Author) [pt
Chang, Zhiwei; Halle, Bertil
2013-10-14
In complex biological or colloidal samples, magnetic relaxation dispersion (MRD) experiments using the field-cycling technique can characterize molecular motions on time scales ranging from nanoseconds to microseconds, provided that a rigorous theory of nuclear spin relaxation is available. In gels, cross-linked proteins, and biological tissues, where an immobilized macromolecular component coexists with a mobile solvent phase, nuclear spins residing in solvent (or cosolvent) species relax predominantly via exchange-mediated orientational randomization (EMOR) of anisotropic nuclear (electric quadrupole or magnetic dipole) couplings. The physical or chemical exchange processes that dominate the MRD typically occur on a time scale of microseconds or longer, where the conventional perturbation theory of spin relaxation breaks down. There is thus a need for a more general relaxation theory. Such a theory, based on the stochastic Liouville equation (SLE) for the EMOR mechanism, is available for a single quadrupolar spin I = 1. Here, we present the corresponding theory for a dipole-coupled spin-1/2 pair. To our knowledge, this is the first treatment of dipolar MRD outside the motional-narrowing regime. Based on an analytical solution of the spatial part of the SLE, we show how the integral longitudinal relaxation rate can be computed efficiently. Both like and unlike spins, with selective or non-selective excitation, are treated. For the experimentally important dilute regime, where only a small fraction of the spin pairs are immobilized, we obtain simple analytical expressions for the auto-relaxation and cross-relaxation rates which generalize the well-known Solomon equations. These generalized results will be useful in biophysical studies, e.g., of intermittent protein dynamics. In addition, they represent a first step towards a rigorous theory of water (1)H relaxation in biological tissues, which is a prerequisite for unravelling the molecular basis of soft
The Effects of Suggestibility on Relaxation.
Rickard, Henry C.; And Others
1985-01-01
Selected undergraduates (N=32) on the basis of Creative Imagination Scale scores and randomly assigned high and low suggestibility subjects to progressive relaxation (PR) and suggestions of relaxation (SR) training modes. Results revealed a significant pre-post relaxation effect, and main efffects for both suggestibility and training mode. (NRB)
Arresting relaxation in Pickering Emulsions
Atherton, Tim; Burke, Chris
2015-03-01
Pickering emulsions consist of droplets of one fluid dispersed in a host fluid and stabilized by colloidal particles absorbed at the fluid-fluid interface. Everyday materials such as crude oil and food products like salad dressing are examples of these materials. Particles can stabilize non spherical droplet shapes in these emulsions through the following sequence: first, an isolated droplet is deformed, e.g. by an electric field, increasing the surface area above the equilibrium value; additional particles are then adsorbed to the interface reducing the surface tension. The droplet is then allowed to relax toward a sphere. If more particles were adsorbed than can be accommodated by the surface area of the spherical ground state, relaxation of the droplet is arrested at some non-spherical shape. Because the energetic cost of removing adsorbed colloids exceeds the interfacial driving force, these configurations can remain stable over long timescales. In this presentation, we present a computational study of the ordering present in anisotropic droplets produced through the mechanism of arrested relaxation and discuss the interplay between the geometry of the droplet, the dynamical process that produced it, and the structure of the defects observed.
Vibrational relaxation in OCS mixtures
International Nuclear Information System (INIS)
Simpson, C.J.S.M.; Gait, P.D.; Simmie, J.M.
1976-01-01
Experimental measurements are reported of vibrational relaxation times which may be used to show whether there is near resonant vibration-rotation energy transfer between OCS and H 2 , D 2 or HD. Vibrational relaxation times have been measured in OCS and OCS mixtures over the temperature range 360 to 1000 K using a shock tube and a laser schlieren system. The effectiveness of the additives in reducing the relaxation time of OCS is in the order 4 He 3 He 2 2 and HD. Along this series the effect of an increase in temperature changes from the case of speeding up the rate with 4 He to retarding it with D 2 , HD and H 2 . There is no measurable difference in the effectiveness of n-D 2 and o-D 2 and little, or no, difference between n-H 2 and p-H 2 . Thus the experimental results do not give clear evidence for rotational-vibration energy transfer between hydrogen and OCS. This contrasts with the situation for CO 2 + H 2 mixtures. (author)
International Nuclear Information System (INIS)
Spies, G.O.; Lortz, D.; Kaiser, R.
2001-01-01
Taylor's theory of relaxed toroidal plasmas (states of lowest energy with fixed total magnetic helicity) is extended to include a vacuum between the plasma and the wall. In the extended variational problem, one prescribes, in addition to the helicity and the magnetic fluxes whose conservation follows from the perfect conductivity of the wall, the fluxes whose conservation follows from the assumption that the plasma-vacuum interface is also perfectly conducting (if the wall is a magnetic surface, then one has the toroidal and the poloidal flux in the vacuum). Vanishing of the first energy variation implies a pressureless free-boundary magnetohydrostatic equilibrium with a Beltrami magnetic field in the plasma, and in general with a surface current in the interface. Positivity of the second variation implies that the equilibrium is stable according to ideal magnetohydrodynamics, that it is a relaxed state according to Taylor's theory if the interface is replaced by a wall, and that the surface current is nonzero (at least if there are no closed magnetic field lines in the interface). The plane slab, with suitable boundary conditions to simulate a genuine torus, is investigated in detail. The relaxed state has the same double symmetry as the vessel if, and only if, the prescribed helicity is in an interval that depends on the prescribed fluxes. This interval is determined in the limit of a thin slab
Regularized Label Relaxation Linear Regression.
Fang, Xiaozhao; Xu, Yong; Li, Xuelong; Lai, Zhihui; Wong, Wai Keung; Fang, Bingwu
2018-04-01
Linear regression (LR) and some of its variants have been widely used for classification problems. Most of these methods assume that during the learning phase, the training samples can be exactly transformed into a strict binary label matrix, which has too little freedom to fit the labels adequately. To address this problem, in this paper, we propose a novel regularized label relaxation LR method, which has the following notable characteristics. First, the proposed method relaxes the strict binary label matrix into a slack variable matrix by introducing a nonnegative label relaxation matrix into LR, which provides more freedom to fit the labels and simultaneously enlarges the margins between different classes as much as possible. Second, the proposed method constructs the class compactness graph based on manifold learning and uses it as the regularization item to avoid the problem of overfitting. The class compactness graph is used to ensure that the samples sharing the same labels can be kept close after they are transformed. Two different algorithms, which are, respectively, based on -norm and -norm loss functions are devised. These two algorithms have compact closed-form solutions in each iteration so that they are easily implemented. Extensive experiments show that these two algorithms outperform the state-of-the-art algorithms in terms of the classification accuracy and running time.
Ultrafast Librational Relaxation of H2O in Liquid Water
DEFF Research Database (Denmark)
Petersen, Jakob; Møller, Klaus Braagaard; Rey, Rossend
2013-01-01
The ultrafast librational (hindered rotational) relaxation of a rotationally excited H2O molecule in pure liquid water is investigated by means of classical nonequilibrium molecular dynamics simulations and a power and work analysis. This analysis allows the mechanism of the energy transfer from...... the excited H2O to its water neighbors, which occurs on a sub-100 fs time scale, to be followed in molecular detail, i.e., to determine which water molecules receive the energy and in which degrees of freedom. It is found that the dominant energy flow is to the four hydrogen-bonded water partners in the first...
Spin-lattice relaxation in phosphorescent triplet state molecules
International Nuclear Information System (INIS)
Verbeek, P.J.F.
1979-01-01
The present thesis contains the results of a study of spin-lattice relaxation (SLR) in the photo-excited triplet state of aromatic molecules, dissolved in a molecular host crystal. It appears that SLR in phosphorescent triplet state molecules often is related to the presence of so-called (pseudo) localized phonons in the molecular mixed crystals. These local phonons can be thought to correspond with vibrations (librations) of the guest molecule in the force field of the surrounding host molecules. Since the intermolecular forces are relatively weak, the frequencies corresponding with these vibrations are relatively low and usually are of the order of 10-30 cm -1 . (Auth.)
Bayesian Methods and Universal Darwinism
Campbell, John
2009-12-01
Bayesian methods since the time of Laplace have been understood by their practitioners as closely aligned to the scientific method. Indeed a recent Champion of Bayesian methods, E. T. Jaynes, titled his textbook on the subject Probability Theory: the Logic of Science. Many philosophers of science including Karl Popper and Donald Campbell have interpreted the evolution of Science as a Darwinian process consisting of a `copy with selective retention' algorithm abstracted from Darwin's theory of Natural Selection. Arguments are presented for an isomorphism between Bayesian Methods and Darwinian processes. Universal Darwinism, as the term has been developed by Richard Dawkins, Daniel Dennett and Susan Blackmore, is the collection of scientific theories which explain the creation and evolution of their subject matter as due to the Operation of Darwinian processes. These subject matters span the fields of atomic physics, chemistry, biology and the social sciences. The principle of Maximum Entropy states that Systems will evolve to states of highest entropy subject to the constraints of scientific law. This principle may be inverted to provide illumination as to the nature of scientific law. Our best cosmological theories suggest the universe contained much less complexity during the period shortly after the Big Bang than it does at present. The scientific subject matter of atomic physics, chemistry, biology and the social sciences has been created since that time. An explanation is proposed for the existence of this subject matter as due to the evolution of constraints in the form of adaptations imposed on Maximum Entropy. It is argued these adaptations were discovered and instantiated through the Operations of a succession of Darwinian processes.
Bayesian flood forecasting methods: A review
Han, Shasha; Coulibaly, Paulin
2017-08-01
Over the past few decades, floods have been seen as one of the most common and largely distributed natural disasters in the world. If floods could be accurately forecasted in advance, then their negative impacts could be greatly minimized. It is widely recognized that quantification and reduction of uncertainty associated with the hydrologic forecast is of great importance for flood estimation and rational decision making. Bayesian forecasting system (BFS) offers an ideal theoretic framework for uncertainty quantification that can be developed for probabilistic flood forecasting via any deterministic hydrologic model. It provides suitable theoretical structure, empirically validated models and reasonable analytic-numerical computation method, and can be developed into various Bayesian forecasting approaches. This paper presents a comprehensive review on Bayesian forecasting approaches applied in flood forecasting from 1999 till now. The review starts with an overview of fundamentals of BFS and recent advances in BFS, followed with BFS application in river stage forecasting and real-time flood forecasting, then move to a critical analysis by evaluating advantages and limitations of Bayesian forecasting methods and other predictive uncertainty assessment approaches in flood forecasting, and finally discusses the future research direction in Bayesian flood forecasting. Results show that the Bayesian flood forecasting approach is an effective and advanced way for flood estimation, it considers all sources of uncertainties and produces a predictive distribution of the river stage, river discharge or runoff, thus gives more accurate and reliable flood forecasts. Some emerging Bayesian forecasting methods (e.g. ensemble Bayesian forecasting system, Bayesian multi-model combination) were shown to overcome limitations of single model or fixed model weight and effectively reduce predictive uncertainty. In recent years, various Bayesian flood forecasting approaches have been
Bayesian inference for Hawkes processes
DEFF Research Database (Denmark)
Rasmussen, Jakob Gulddahl
The Hawkes process is a practically and theoretically important class of point processes, but parameter-estimation for such a process can pose various problems. In this paper we explore and compare two approaches to Bayesian inference. The first approach is based on the so-called conditional...... intensity function, while the second approach is based on an underlying clustering and branching structure in the Hawkes process. For practical use, MCMC (Markov chain Monte Carlo) methods are employed. The two approaches are compared numerically using three examples of the Hawkes process....
Bayesian inference for Hawkes processes
DEFF Research Database (Denmark)
Rasmussen, Jakob Gulddahl
2013-01-01
The Hawkes process is a practically and theoretically important class of point processes, but parameter-estimation for such a process can pose various problems. In this paper we explore and compare two approaches to Bayesian inference. The first approach is based on the so-called conditional...... intensity function, while the second approach is based on an underlying clustering and branching structure in the Hawkes process. For practical use, MCMC (Markov chain Monte Carlo) methods are employed. The two approaches are compared numerically using three examples of the Hawkes process....
Numeracy, frequency, and Bayesian reasoning
Directory of Open Access Journals (Sweden)
Gretchen B. Chapman
2009-02-01
Full Text Available Previous research has demonstrated that Bayesian reasoning performance is improved if uncertainty information is presented as natural frequencies rather than single-event probabilities. A questionnaire study of 342 college students replicated this effect but also found that the performance-boosting benefits of the natural frequency presentation occurred primarily for participants who scored high in numeracy. This finding suggests that even comprehension and manipulation of natural frequencies requires a certain threshold of numeracy abilities, and that the beneficial effects of natural frequency presentation may not be as general as previously believed.
Feenstra, K Anton; Peter, Christine; Scheek, Ruud M; van Gunsteren, Wilfred F; Mark, Alan E
Three methods for calculating nuclear magnetic resonance cross-relaxation rates from molecular dynamics simulations of small flexible molecules have been compared in terms of their ability to reproduce relaxation data obtained experimentally and to produce consistent descriptions of the system. The
DEFF Research Database (Denmark)
Guillot, Gilles; Carpentier-Skandalis, Alexandra
2011-01-01
We study the accuracy of a Bayesian supervised method used to cluster individuals into genetically homogeneous groups on the basis of dominant or codominant molecular markers. We provide a formula relating an error criterion to the number of loci used and the number of clusters. This formula...
Ngai, K L; Habasaki, J; Prevosto, D; Capaccioli, S; Paluch, Marian
2012-07-21
By now it is well established that the structural α-relaxation time, τ(α), of non-associated small molecular and polymeric glass-formers obey thermodynamic scaling. In other words, τ(α) is a function Φ of the product variable, ρ(γ)/T, where ρ is the density and T the temperature. The constant γ as well as the function, τ(α) = Φ(ρ(γ)/T), is material dependent. Actually this dependence of τ(α) on ρ(γ)/T originates from the dependence on the same product variable of the Johari-Goldstein β-relaxation time, τ(β), or the primitive relaxation time, τ(0), of the coupling model. To support this assertion, we give evidences from various sources itemized as follows. (1) The invariance of the relation between τ(α) and τ(β) or τ(0) to widely different combinations of pressure and temperature. (2) Experimental dielectric and viscosity data of glass-forming van der Waals liquids and polymer. (3) Molecular dynamics simulations of binary Lennard-Jones (LJ) models, the Lewis-Wahnström model of ortho-terphenyl, 1,4 polybutadiene, a room temperature ionic liquid, 1-ethyl-3-methylimidazolium nitrate, and a molten salt 2Ca(NO(3))(2)·3KNO(3) (CKN). (4) Both diffusivity and structural relaxation time, as well as the breakdown of Stokes-Einstein relation in CKN obey thermodynamic scaling by ρ(γ)/T with the same γ. (5) In polymers, the chain normal mode relaxation time, τ(N), is another function of ρ(γ)/T with the same γ as segmental relaxation time τ(α). (6) While the data of τ(α) from simulations for the full LJ binary mixture obey very well the thermodynamic scaling, it is strongly violated when the LJ interaction potential is truncated beyond typical inter-particle distance, although in both cases the repulsive pair potentials coincide for some distances.
Sandpile model for relaxation in complex systems
International Nuclear Information System (INIS)
Vazquez, A.; Sotolongo-Costa, O.; Brouers, F.
1997-10-01
The relaxation in complex systems is, in general, nonexponential. After an initial rapid decay the system relaxes slowly following a long time tail. In the present paper a sandpile moderation of the relaxation in complex systems is analysed. Complexity is introduced by a process of avalanches in the Bethe lattice and a feedback mechanism which leads to slower decay with increasing time. In this way, some features of relaxation in complex systems: long time tails relaxation, aging, and fractal distribution of characteristic times, are obtained by simple computer simulations. (author)
Bayesian analysis of magnetic island dynamics
International Nuclear Information System (INIS)
Preuss, R.; Maraschek, M.; Zohm, H.; Dose, V.
2003-01-01
We examine a first order differential equation with respect to time used to describe magnetic islands in magnetically confined plasmas. The free parameters of this equation are obtained by employing Bayesian probability theory. Additionally, a typical Bayesian change point is solved in the process of obtaining the data
Learning dynamic Bayesian networks with mixed variables
DEFF Research Database (Denmark)
Bøttcher, Susanne Gammelgaard
This paper considers dynamic Bayesian networks for discrete and continuous variables. We only treat the case, where the distribution of the variables is conditional Gaussian. We show how to learn the parameters and structure of a dynamic Bayesian network and also how the Markov order can be learned...
Using Bayesian Networks to Improve Knowledge Assessment
Millan, Eva; Descalco, Luis; Castillo, Gladys; Oliveira, Paula; Diogo, Sandra
2013-01-01
In this paper, we describe the integration and evaluation of an existing generic Bayesian student model (GBSM) into an existing computerized testing system within the Mathematics Education Project (PmatE--Projecto Matematica Ensino) of the University of Aveiro. This generic Bayesian student model had been previously evaluated with simulated…
Using Bayesian belief networks in adaptive management.
J.B. Nyberg; B.G. Marcot; R. Sulyma
2006-01-01
Bayesian belief and decision networks are relatively new modeling methods that are especially well suited to adaptive-management applications, but they appear not to have been widely used in adaptive management to date. Bayesian belief networks (BBNs) can serve many purposes for practioners of adaptive management, from illustrating system relations conceptually to...
Bayesian Decision Theoretical Framework for Clustering
Chen, Mo
2011-01-01
In this thesis, we establish a novel probabilistic framework for the data clustering problem from the perspective of Bayesian decision theory. The Bayesian decision theory view justifies the important questions: what is a cluster and what a clustering algorithm should optimize. We prove that the spectral clustering (to be specific, the…
Robust Bayesian detection of unmodelled bursts
International Nuclear Information System (INIS)
Searle, Antony C; Sutton, Patrick J; Tinto, Massimo; Woan, Graham
2008-01-01
We develop a Bayesian treatment of the problem of detecting unmodelled gravitational wave bursts using the new global network of interferometric detectors. We also compare this Bayesian treatment with existing coherent methods, and demonstrate that the existing methods make implicit assumptions on the distribution of signals that make them sub-optimal for realistic signal populations
Bayesian models: A statistical primer for ecologists
Hobbs, N. Thompson; Hooten, Mevin B.
2015-01-01
Bayesian modeling has become an indispensable tool for ecological research because it is uniquely suited to deal with complexity in a statistically coherent way. This textbook provides a comprehensive and accessible introduction to the latest Bayesian methods—in language ecologists can understand. Unlike other books on the subject, this one emphasizes the principles behind the computations, giving ecologists a big-picture understanding of how to implement this powerful statistical approach.Bayesian Models is an essential primer for non-statisticians. It begins with a definition of probability and develops a step-by-step sequence of connected ideas, including basic distribution theory, network diagrams, hierarchical models, Markov chain Monte Carlo, and inference from single and multiple models. This unique book places less emphasis on computer coding, favoring instead a concise presentation of the mathematical statistics needed to understand how and why Bayesian analysis works. It also explains how to write out properly formulated hierarchical Bayesian models and use them in computing, research papers, and proposals.This primer enables ecologists to understand the statistical principles behind Bayesian modeling and apply them to research, teaching, policy, and management.Presents the mathematical and statistical foundations of Bayesian modeling in language accessible to non-statisticiansCovers basic distribution theory, network diagrams, hierarchical models, Markov chain Monte Carlo, and moreDeemphasizes computer coding in favor of basic principlesExplains how to write out properly factored statistical expressions representing Bayesian models
Particle identification in ALICE: a Bayesian approach
Adam, J.; Adamova, D.; Aggarwal, M. M.; Rinella, G. Aglieri; Agnello, M.; Agrawal, N.; Ahammed, Z.; Ahn, S. U.; Aiola, S.; Akindinov, A.; Alam, S. N.; Albuquerque, D. S. D.; Aleksandrov, D.; Alessandro, B.; Alexandre, D.; Alfaro Molina, R.; Alici, A.; Alkin, A.; Almaraz, J. R. M.; Alme, J.; Alt, T.; Altinpinar, S.; Altsybeev, I.; Alves Garcia Prado, C.; Andrei, C.; Andronic, A.; Anguelov, V.; Anticic, T.; Antinori, F.; Antonioli, P.; Aphecetche, L.; Appelshaeuser, H.; Arcelli, S.; Arnaldi, R.; Arnold, O. W.; Arsene, I. C.; Arslandok, M.; Audurier, B.; Augustinus, A.; Averbeck, R.; Azmi, M. D.; Badala, A.; Baek, Y. W.; Bagnasco, S.; Bailhache, R.; Bala, R.; Balasubramanian, S.; Baldisseri, A.; Baral, R. C.; Barbano, A. M.; Barbera, R.; Barile, F.; Barnafoeldi, G. G.; Barnby, L. S.; Barret, V.; Bartalini, P.; Barth, K.; Bartke, J.; Bartsch, E.; Basile, M.; Bastid, N.; Bathen, B.; Batigne, G.; Camejo, A. Batista; Batyunya, B.; Batzing, P. C.; Bearden, I. G.; Beck, H.; Bedda, C.; Behera, N. K.; Belikov, I.; Bellini, F.; Bello Martinez, H.; Bellwied, R.; Belmont, R.; Belmont-Moreno, E.; Belyaev, V.; Benacek, P.; Bencedi, G.; Beole, S.; Berceanu, I.; Bercuci, A.; Berdnikov, Y.; Berenyi, D.; Bertens, R. A.; Berzano, D.; Betev, L.; Bhasin, A.; Bhat, I. R.; Bhati, A. K.; Bhattacharjee, B.; Bhom, J.; Bianchi, L.; Bianchi, N.; Bianchin, C.; Bielcik, J.; Bielcikova, J.; Bilandzic, A.; Biro, G.; Biswas, R.; Biswas, S.; Bjelogrlic, S.; Blair, J. T.; Blau, D.; Blume, C.; Bock, F.; Bogdanov, A.; Boggild, H.; Boldizsar, L.; Bombara, M.; Book, J.; Borel, H.; Borissov, A.; Borri, M.; Bossu, F.; Botta, E.; Bourjau, C.; Braun-Munzinger, P.; Bregant, M.; Breitner, T.; Broker, T. A.; Browning, T. A.; Broz, M.; Brucken, E. J.; Bruna, E.; Bruno, G. E.; Budnikov, D.; Buesching, H.; Bufalino, S.; Buncic, P.; Busch, O.; Buthelezi, Z.; Butt, J. B.; Buxton, J. T.; Cabala, J.; Caffarri, D.; Cai, X.; Caines, H.; Diaz, L. Calero; Caliva, A.; Calvo Villar, E.; Camerini, P.; Carena, F.; Carena, W.; Carnesecchi, F.; Castellanos, J. Castillo; Castro, A. J.; Casula, E. A. R.; Sanchez, C. Ceballos; Cepila, J.; Cerello, P.; Cerkala, J.; Chang, B.; Chapeland, S.; Chartier, M.; Charvet, J. L.; Chattopadhyay, S.; Chattopadhyay, S.; Chauvin, A.; Chelnokov, V.; Cherney, M.; Cheshkov, C.; Cheynis, B.; Barroso, V. Chibante; Chinellato, D. D.; Cho, S.; Chochula, P.; Choi, K.; Chojnacki, M.; Choudhury, S.; Christakoglou, P.; Christensen, C. H.; Christiansen, P.; Chujo, T.; Cicalo, C.; Cifarelli, L.; Cindolo, F.; Cleymans, J.; Colamaria, F.; Colella, D.; Collu, A.; Colocci, M.; Balbastre, G. Conesa; del Valle, Z. Conesa; Connors, M. E.; Contreras, J. G.; Cormier, T. M.; Morales, Y. Corrales; Cortes Maldonado, I.; Cortese, P.; Cosentino, M. R.; Costa, F.; Crochet, P.; Cruz Albino, R.; Cuautle, E.; Cunqueiro, L.; Dahms, T.; Dainese, A.; Danisch, M. C.; Danu, A.; Das, I.; Das, S.; Dash, A.; Dash, S.; De, S.; De Caro, A.; de Cataldo, G.; de Conti, C.; de Cuveland, J.; De Falco, A.; De Gruttola, D.; De Marco, N.; De Pasquale, S.; Deisting, A.; Deloff, A.; Denes, E.; Deplano, C.; Dhankher, P.; Di Bari, D.; Di Mauro, A.; Di Nezza, P.; Corchero, M. A. Diaz; Dietel, T.; Dillenseger, P.; Divia, R.; Djuvsland, O.; Dobrin, A.; Gimenez, D. Domenicis; Doenigus, B.; Dordic, O.; Drozhzhova, T.; Dubey, A. K.; Dubla, A.; Ducroux, L.; Dupieux, P.; Ehlers, R. J.; Elia, D.; Endress, E.; Engel, H.; Epple, E.; Erazmus, B.; Erdemir, I.; Erhardt, F.; Espagnon, B.; Estienne, M.; Esumi, S.; Eum, J.; Evans, D.; Evdokimov, S.; Eyyubova, G.; Fabbietti, L.; Fabris, D.; Faivre, J.; Fantoni, A.; Fasel, M.; Feldkamp, L.; Feliciello, A.; Feofilov, G.; Ferencei, J.; Fernandez Tellez, A.; Ferreiro, E. G.; Ferretti, A.; Festanti, A.; Feuillard, V. J. G.; Figiel, J.; Figueredo, M. A. S.; Filchagin, S.; Finogeev, D.; Fionda, F. M.; Fiore, E. M.; Fleck, M. G.; Floris, M.; Foertsch, S.; Foka, P.; Fokin, S.; Fragiacomo, E.; Francescon, A.; Frankenfeld, U.; Fronze, G. G.; Fuchs, U.; Furget, C.; Furs, A.; Girard, M. Fusco; Gaardhoje, J. J.; Gagliardi, M.; Gago, A. M.; Gallio, M.; Gangadharan, D. R.; Ganoti, P.; Gao, C.; Garabatos, C.; Garcia-Solis, E.; Gargiulo, C.; Gasik, P.; Gauger, E. F.; Germain, M.; Gheata, A.; Gheata, M.; Gianotti, P.; Giubellino, P.; Giubilato, P.; Gladysz-Dziadus, E.; Glaessel, P.; Gomez Coral, D. M.; Ramirez, A. Gomez; Gonzalez, A. S.; Gonzalez, V.; Gonzalez-Zamora, P.; Gorbunov, S.; Goerlich, L.; Gotovac, S.; Grabski, V.; Grachov, O. A.; Graczykowski, L. K.; Graham, K. L.; Grelli, A.; Grigoras, A.; Grigoras, C.; Grigoriev, V.; Grigoryan, A.; Grigoryan, S.; Grinyov, B.; Grion, N.; Gronefeld, J. M.; Grosse-Oetringhaus, J. F.; Grosso, R.; Guber, F.; Guernane, R.; Guerzoni, B.; Gulbrandsen, K.; Gunji, T.; Gupta, A.; Haake, R.; Haaland, O.; Hadjidakis, C.; Haiduc, M.; Hamagaki, H.; Hamar, G.; Hamon, J. C.; Harris, J. W.; Harton, A.; Hatzifotiadou, D.; Hayashi, S.; Heckel, S. T.; Hellbaer, E.; Helstrup, H.; Herghelegiu, A.; Herrera Corral, G.; Hess, B. A.; Hetland, K. F.; Hillemanns, H.; Hippolyte, B.; Horak, D.; Hosokawa, R.; Hristov, P.; Humanic, T. J.; Hussain, N.; Hussain, T.; Hutter, D.; Hwang, D. S.; Ilkaev, R.; Inaba, M.; Incani, E.; Ippolitov, M.; Irfan, M.; Ivanov, M.; Ivanov, V.; Izucheev, V.; Jacazio, N.; Jadhav, M. B.; Jadlovska, S.; Jadlovsky, J.; Jahnke, C.; Jakubowska, M. J.; Jang, H. J.; Janik, M. A.; Jayarathna, P. H. S. Y.; Jena, C.; Jena, S.; Bustamante, R. T. Jimenez; Jones, P. G.; Jusko, A.; Kalinak, P.; Kalweit, A.; Kamin, J.; Kaplin, V.; Kar, S.; Uysal, A. Karasu; Karavichev, O.; Karavicheva, T.; Karayan, L.; Karpechev, E.; Kebschull, U.; Keidel, R.; Keijdener, D. L. D.; Keil, M.; Khan, M. Mohisin; Khan, P.; Khan, S. A.; Khanzadeev, A.; Kharlov, Y.; Kileng, B.; Kim, D. W.; Kim, D. J.; Kim, D.; Kim, J. S.; Kim, M.; Kim, T.; Kirsch, S.; Kisel, I.; Kiselev, S.; Kisiel, A.; Kiss, G.; Klay, J. L.; Klein, C.; Klein-Boesing, C.; Klewin, S.; Kluge, A.; Knichel, M. L.; Knospe, A. G.; Kobdaj, C.; Kofarago, M.; Kollegger, T.; Kolojvari, A.; Kondratiev, V.; Kondratyeva, N.; Kondratyuk, E.; Konevskikh, A.; Kopcik, M.; Kostarakis, P.; Kour, M.; Kouzinopoulos, C.; Kovalenko, O.; Kovalenko, V.; Kowalski, M.; Meethaleveedu, G. Koyithatta; Kralik, I.; Kravcakova, A.; Krivda, M.; Krizek, F.; Kryshen, E.; Krzewicki, M.; Kubera, A. M.; Kucera, V.; Kuijer, P. G.; Kumar, J.; Kumar, L.; Kumar, S.; Kurashvili, P.; Kurepin, A.; Kurepin, A. B.; Kuryakin, A.; Kweon, M. J.; Kwon, Y.; La Pointe, S. L.; La Rocca, P.; Ladron de Guevara, P.; Lagana Fernandes, C.; Lakomov, I.; Langoy, R.; Lara, C.; Lardeux, A.; Lattuca, A.; Laudi, E.; Lea, R.; Leardini, L.; Lee, G. R.; Lee, S.; Lehas, F.; Lemmon, R. C.; Lenti, V.; Leogrande, E.; Monzon, I. Leon; Leon Vargas, H.; Leoncino, M.; Levai, P.; Lien, J.; Lietava, R.; Lindal, S.; Lindenstruth, V.; Lippmann, C.; Lisa, M. A.; Ljunggren, H. M.; Lodato, D. F.; Loenne, P. I.; Loginov, V.; Loizides, C.; Lopez, X.; Torres, E. Lopez; Lowe, A.; Luettig, P.; Lunardon, M.; Luparello, G.; Lutz, T. H.; Maevskaya, A.; Mager, M.; Mahajan, S.; Mahmood, S. M.; Maire, A.; Majka, R. D.; Malaev, M.; Maldonado Cervantes, I.; Malinina, L.; Mal'Kevich, D.; Malzacher, P.; Mamonov, A.; Manko, V.; Manso, F.; Manzari, V.; Marchisone, M.; Mares, J.; Margagliotti, G. V.; Margotti, A.; Margutti, J.; Marin, A.; Markert, C.; Marquard, M.; Martin, N. A.; Blanco, J. Martin; Martinengo, P.; Martinez, M. I.; Garcia, G. Martinez; Pedreira, M. Martinez; Mas, A.; Masciocchi, S.; Masera, M.; Masoni, A.; Mastroserio, A.; Matyja, A.; Mayer, C.; Mazer, J.; Mazzoni, M. A.; Mcdonald, D.; Meddi, F.; Melikyan, Y.; Menchaca-Rocha, A.; Meninno, E.; Perez, J. Mercado; Meres, M.; Miake, Y.; Mieskolainen, M. M.; Mikhaylov, K.; Milano, L.; Milosevic, J.; Mischke, A.; Mishra, A. N.; Miskowiec, D.; Mitra, J.; Mitu, C. M.; Mohammadi, N.; Mohanty, B.; Molnar, L.; Montano Zetina, L.; Montes, E.; De Godoy, D. A. Moreira; Moreno, L. A. P.; Moretto, S.; Morreale, A.; Morsch, A.; Muccifora, V.; Mudnic, E.; Muehlheim, D.; Muhuri, S.; Mukherjee, M.; Mulligan, J. D.; Munhoz, M. G.; Munzer, R. H.; Murakami, H.; Murray, S.; Musa, L.; Musinsky, J.; Naik, B.; Nair, R.; Nandi, B. K.; Nania, R.; Nappi, E.; Naru, M. U.; Natal da Luz, H.; Nattrass, C.; Navarro, S. R.; Nayak, K.; Nayak, R.; Nayak, T. K.; Nazarenko, S.; Nedosekin, A.; Nellen, L.; Ng, F.; Nicassio, M.; Niculescu, M.; Niedziela, J.; Nielsen, B. S.; Nikolaev, S.; Nikulin, S.; Nikulin, V.; Noferini, F.; Nomokonov, P.; Nooren, G.; Noris, J. C. C.; Norman, J.; Nyanin, A.; Nystrand, J.; Oeschler, H.; Oh, S.; Oh, S. K.; Ohlson, A.; Okatan, A.; Okubo, T.; Olah, L.; Oleniacz, J.; Oliveira Da Silva, A. C.; Oliver, M. H.; Onderwaater, J.; Oppedisano, C.; Orava, R.; Oravec, M.; Ortiz Velasquez, A.; Oskarsson, A.; Otwinowski, J.; Oyama, K.; Ozdemir, M.; Pachmayer, Y.; Pagano, D.; Pagano, P.; Paic, G.; Pal, S. K.; Pan, J.; Papikyan, V.; Pappalardo, G. S.; Pareek, P.; Park, W. J.; Parmar, S.; Passfeld, A.; Paticchio, V.; Patra, R. N.; Paul, B.; Pei, H.; Peitzmann, T.; Da Costa, H. Pereira; Peresunko, D.; Lara, C. E. Perez; Lezama, E. Perez; Peskov, V.; Pestov, Y.; Petracek, V.; Petrov, V.; Petrovici, M.; Petta, C.; Piano, S.; Pikna, M.; Pillot, P.; Pimentel, L. O. D. L.; Pinazza, O.; Pinsky, L.; Piyarathna, D. B.; Ploskon, M.; Planinic, M.; Pluta, J.; Pochybova, S.; Podesta-Lerma, P. L. M.; Poghosyan, M. G.; Polichtchouk, B.; Poljak, N.; Poonsawat, W.; Pop, A.; Porteboeuf-Houssais, S.; Porter, J.; Pospisil, J.; Prasad, S. K.; Preghenella, R.; Prino, F.; Pruneau, C. A.; Pshenichnov, I.; Puccio, M.; Puddu, G.; Pujahari, P.; Punin, V.; Putschke, J.; Qvigstad, H.; Rachevski, A.; Raha, S.; Rajput, S.; Rak, J.; Rakotozafindrabe, A.; Ramello, L.; Rami, F.; Raniwala, R.; Raniwala, S.; Raesaenen, S. S.; Rascanu, B. T.; Rathee, D.; Read, K. F.; Redlich, K.; Reed, R. J.; Reichelt, P.; Reidt, F.; Ren, X.; Renfordt, R.; Reolon, A. R.; Reshetin, A.; Reygers, K.; Riabov, V.; Ricci, R. A.; Richert, T.; Richter, M.; Riedler, P.; Riegler, W.; Riggi, F.; Ristea, C.; Rocco, E.; Rodriguez Cahuantzi, M.; Manso, A. Rodriguez; Roed, K.; Rogochaya, E.; Rohr, D.; Roehrich, D.; Ronchetti, F.; Ronflette, L.; Rosnet, P.; Rossi, A.; Roukoutakis, F.; Roy, A.; Roy, C.; Roy, P.; Montero, A. J. Rubio; Rui, R.; Russo, R.; Ryabinkin, E.; Ryabov, Y.; Rybicki, A.; Saarinen, S.; Sadhu, S.; Sadovsky, S.; Safarik, K.; Sahlmuller, B.; Sahoo, P.; Sahoo, R.; Sahoo, S.; Sahu, P. K.; Saini, J.; Sakai, S.; Saleh, M. A.; Salzwedel, J.; Sambyal, S.; Samsonov, V.; Sandor, L.; Sandoval, A.; Sano, M.; Sarkar, D.; Sarkar, N.; Sarma, P.; Scapparone, E.; Scarlassara, F.; Schiaua, C.; Schicker, R.; Schmidt, C.; Schmidt, H. R.; Schuchmann, S.; Schukraft, J.; Schulc, M.; Schutz, Y.; Schwarz, K.; Schweda, K.; Scioli, G.; Scomparin, E.; Scott, R.; Sefcik, M.; Seger, J. E.; Sekiguchi, Y.; Sekihata, D.; Selyuzhenkov, I.; Senosi, K.; Senyukov, S.; Serradilla, E.; Sevcenco, A.; Shabanov, A.; Shabetai, A.; Shadura, O.; Shahoyan, R.; Shahzad, M. I.; Shangaraev, A.; Sharma, M.; Sharma, M.; Sharma, N.; Sheikh, A. I.; Shigaki, K.; Shou, Q.; Shtejer, K.; Sibiriak, Y.; Siddhanta, S.; Sielewicz, K. M.; Siemiarczuk, T.; Silvermyr, D.; Silvestre, C.; Simatovic, G.; Simonetti, G.; Singaraju, R.; Singh, R.; Singha, S.; Singhal, V.; Sinha, B. C.; Sinha, T.; Sitar, B.; Sitta, M.; Skaali, T. B.; Slupecki, M.; Smirnov, N.; Snellings, R. J. M.; Snellman, T. W.; Song, J.; Song, M.; Song, Z.; Soramel, F.; Sorensen, S.; de Souza, R. D.; Sozzi, F.; Spacek, M.; Spiriti, E.; Sputowska, I.; Spyropoulou-Stassinaki, M.; Stachel, J.; Stan, I.; Stankus, P.; Stenlund, E.; Steyn, G.; Stiller, J. H.; Stocco, D.; Strmen, P.; Suaide, A. A. P.; Sugitate, T.; Suire, C.; Suleymanov, M.; Suljic, M.; Sultanov, R.; Sumbera, M.; Sumowidagdo, S.; Szabo, A.; Szanto de Toledo, A.; Szarka, I.; Szczepankiewicz, A.; Szymanski, M.; Tabassam, U.; Takahashi, J.; Tambave, G. J.; Tanaka, N.; Tarhini, M.; Tariq, M.; Tarzila, M. G.; Tauro, A.; Tejeda Munoz, G.; Telesca, A.; Terasaki, K.; Terrevoli, C.; Teyssier, B.; Thaeder, J.; Thakur, D.; Thomas, D.; Tieulent, R.; Timmins, A. R.; Toia, A.; Trogolo, S.; Trombetta, G.; Trubnikov, V.; Trzaska, W. H.; Tsuji, T.; Tumkin, A.; Turrisi, R.; Tveter, T. S.; Ullaland, K.; Uras, A.; Usai, G. L.; Utrobicic, A.; Vala, M.; Palomo, L. Valencia; Vallero, S.; Van Der Maarel, J.; Van Hoorne, J. W.; van Leeuwen, M.; Vanat, T.; Vyvre, P. Vande; Varga, D.; Vargas, A.; Vargyas, M.; Varma, R.; Vasileiou, M.; Vasiliev, A.; Vauthier, A.; Vechernin, V.; Veen, A. M.; Veldhoen, M.; Velure, A.; Vercellin, E.; Vergara Limon, S.; Vernet, R.; Verweij, M.; Vickovic, L.; Viesti, G.; Viinikainen, J.; Vilakazi, Z.; Baillie, O. Villalobos; Villatoro Tello, A.; Vinogradov, A.; Vinogradov, L.; Vinogradov, Y.; Virgili, T.; Vislavicius, V.; Viyogi, Y. P.; Vodopyanov, A.; Voelkl, M. A.; Voloshin, K.; Voloshin, S. A.; Volpe, G.; von Haller, B.; Vorobyev, I.; Vranic, D.; Vrlakova, J.; Vulpescu, B.; Wagner, B.; Wagner, J.; Wang, H.; Watanabe, D.; Watanabe, Y.; Weiser, D. F.; Westerhoff, U.; Whitehead, A. M.; Wiechula, J.; Wikne, J.; Wilk, G.; Wilkinson, J.; Williams, M. C. S.; Windelband, B.; Winn, M.; Yang, H.; Yano, S.; Yasin, Z.; Yokoyama, H.; Yoo, I. -K.; Yoon, J. H.; Yurchenko, V.; Yushmanov, I.; Zaborowska, A.; Zaccolo, V.; Zaman, A.; Zampolli, C.; Zanoli, H. J. C.; Zaporozhets, S.; Zardoshti, N.; Zarochentsev, A.; Zavada, P.; Zaviyalov, N.; Zbroszczyk, H.; Zgura, I. S.; Zhalov, M.; Zhang, C.; Zhao, C.; Zhigareva, N.; Zhou, Y.; Zhou, Z.; Zhu, H.; Zichichi, A.; Zimmermann, A.; Zimmermann, M. B.; Zinovjev, G.; Zyzak, M.
2016-01-01
We present a Bayesian approach to particle identification (PID) within the ALICE experiment. The aim is to more effectively combine the particle identification capabilities of its various detectors. After a brief explanation of the adopted methodology and formalism, the performance of the Bayesian
Advances in Bayesian Modeling in Educational Research
Levy, Roy
2016-01-01
In this article, I provide a conceptually oriented overview of Bayesian approaches to statistical inference and contrast them with frequentist approaches that currently dominate conventional practice in educational research. The features and advantages of Bayesian approaches are illustrated with examples spanning several statistical modeling…
Compiling Relational Bayesian Networks for Exact Inference
DEFF Research Database (Denmark)
Jaeger, Manfred; Darwiche, Adnan; Chavira, Mark
2006-01-01
We describe in this paper a system for exact inference with relational Bayesian networks as defined in the publicly available PRIMULA tool. The system is based on compiling propositional instances of relational Bayesian networks into arithmetic circuits and then performing online inference...
Compiling Relational Bayesian Networks for Exact Inference
DEFF Research Database (Denmark)
Jaeger, Manfred; Chavira, Mark; Darwiche, Adnan
2004-01-01
We describe a system for exact inference with relational Bayesian networks as defined in the publicly available \\primula\\ tool. The system is based on compiling propositional instances of relational Bayesian networks into arithmetic circuits and then performing online inference by evaluating...
The relationships between suggestibility, influenceability, and relaxability.
Polczyk, Romuald; Frey, Olga; Szpitalak, Malwina
2013-01-01
This research explores the relationships between relaxability and various aspects of suggestibility and influenceability. The Jacobson Progressive Muscle Relaxation procedure was used to induce relaxation. Tests of direct suggestibility, relating to the susceptibility of overt suggestions, and indirect suggestibility, referring to indirect hidden influence, as well as self-description questionnaires on suggestibility and the tendency to comply were used. Thayer's Activation-Deactivation Adjective Check List, measuring various kinds of activation and used as a pre- and posttest, determined the efficacy of the relaxation procedure. Indirect, direct, and self-measured suggestibility proved to be positively related to the ability to relax, measured by Thayer's subscales relating to emotions. Compliance was not related to relaxability. The results are discussed in terms of the aspects of relaxation training connected with suggestibility.
BELM: Bayesian extreme learning machine.
Soria-Olivas, Emilio; Gómez-Sanchis, Juan; Martín, José D; Vila-Francés, Joan; Martínez, Marcelino; Magdalena, José R; Serrano, Antonio J
2011-03-01
The theory of extreme learning machine (ELM) has become very popular on the last few years. ELM is a new approach for learning the parameters of the hidden layers of a multilayer neural network (as the multilayer perceptron or the radial basis function neural network). Its main advantage is the lower computational cost, which is especially relevant when dealing with many patterns defined in a high-dimensional space. This brief proposes a bayesian approach to ELM, which presents some advantages over other approaches: it allows the introduction of a priori knowledge; obtains the confidence intervals (CIs) without the need of applying methods that are computationally intensive, e.g., bootstrap; and presents high generalization capabilities. Bayesian ELM is benchmarked against classical ELM in several artificial and real datasets that are widely used for the evaluation of machine learning algorithms. Achieved results show that the proposed approach produces a competitive accuracy with some additional advantages, namely, automatic production of CIs, reduction of probability of model overfitting, and use of a priori knowledge.
BAYESIAN BICLUSTERING FOR PATIENT STRATIFICATION.
Khakabimamaghani, Sahand; Ester, Martin
2016-01-01
The move from Empirical Medicine towards Personalized Medicine has attracted attention to Stratified Medicine (SM). Some methods are provided in the literature for patient stratification, which is the central task of SM, however, there are still significant open issues. First, it is still unclear if integrating different datatypes will help in detecting disease subtypes more accurately, and, if not, which datatype(s) are most useful for this task. Second, it is not clear how we can compare different methods of patient stratification. Third, as most of the proposed stratification methods are deterministic, there is a need for investigating the potential benefits of applying probabilistic methods. To address these issues, we introduce a novel integrative Bayesian biclustering method, called B2PS, for patient stratification and propose methods for evaluating the results. Our experimental results demonstrate the superiority of B2PS over a popular state-of-the-art method and the benefits of Bayesian approaches. Our results agree with the intuition that transcriptomic data forms a better basis for patient stratification than genomic data.
Bayesian Nonparametric Longitudinal Data Analysis.
Quintana, Fernando A; Johnson, Wesley O; Waetjen, Elaine; Gold, Ellen
2016-01-01
Practical Bayesian nonparametric methods have been developed across a wide variety of contexts. Here, we develop a novel statistical model that generalizes standard mixed models for longitudinal data that include flexible mean functions as well as combined compound symmetry (CS) and autoregressive (AR) covariance structures. AR structure is often specified through the use of a Gaussian process (GP) with covariance functions that allow longitudinal data to be more correlated if they are observed closer in time than if they are observed farther apart. We allow for AR structure by considering a broader class of models that incorporates a Dirichlet Process Mixture (DPM) over the covariance parameters of the GP. We are able to take advantage of modern Bayesian statistical methods in making full predictive inferences and about characteristics of longitudinal profiles and their differences across covariate combinations. We also take advantage of the generality of our model, which provides for estimation of a variety of covariance structures. We observe that models that fail to incorporate CS or AR structure can result in very poor estimation of a covariance or correlation matrix. In our illustration using hormone data observed on women through the menopausal transition, biology dictates the use of a generalized family of sigmoid functions as a model for time trends across subpopulation categories.
Nuclear relaxation and critical fluctuations in membranes containing cholesterol
McConnell, Harden
2009-04-01
Nuclear resonance frequencies in bilayer membranes depend on lipid composition. Our calculations describe the combined effects of composition fluctuations and diffusion on nuclear relaxation near a miscibility critical point. Both tracer and gradient diffusion are included. The calculations involve correlation functions and a correlation length ξ =ξ0T/(T -Tc), where T -Tc is temperature above the critical temperature and ξ0 is a parameter of molecular length. Several correlation functions are examined, each of which is related in some degree to the Ising model correlation function. These correlation functions are used in the calculation of transverse deuterium relaxation rates in magic angle spinning and quadrupole echo experiments. The calculations are compared with experiments that report maxima in deuterium and proton nuclear relaxation rates at the critical temperature [Veatch et al., Proc. Nat. Acad. Sci. U.S.A. 104, 17650 (2007)]. One Ising-model-related correlation function yields a maximum 1/T2 relaxation rate at the critical temperature for both magic angle spinning and quadrupole echo experiments. The calculated rates at the critical temperature are close to the experimental rates. The rate maxima involve relatively rapid tracer diffusion in a static composition gradient over distances of up to 10-100 nm.
Rouse mode analysis of chain relaxation in polymer nanocomposites.
Kalathi, Jagannathan T; Kumar, Sanat K; Rubinstein, Michael; Grest, Gary S
2015-05-28
Large-scale molecular dynamics simulations are used to study the internal relaxations of chains in nanoparticle (NP)/polymer composites. We examine the Rouse modes of the chains, a quantity that is closest in spirit to the self-intermediate scattering function, typically determined in an (incoherent) inelastic neutron scattering experiment. Our simulations show that for weakly interacting mixtures of NPs and polymers, the effective monomeric relaxation rates are faster than in a neat melt when the NPs are smaller than the entanglement mesh size. In this case, the NPs serve to reduce both the monomeric friction and the entanglements in the polymer melt, as in the case of a polymer-solvent system. However, for NPs larger than half the entanglement mesh size, the effective monomer relaxation is essentially unaffected for low NP concentrations. Even in this case, we observe a strong reduction in chain entanglements for larger NP loadings. Thus, the role of NPs is to always reduce the number of entanglements, with this effect only becoming pronounced for small NPs or for high concentrations of large NPs. Our studies of the relaxation of single chains resonate with recent neutron spin echo (NSE) experiments, which deduce a similar entanglement dilution effect.
Dielectric and mechanical relaxation in isooctylcyanobiphenyl (8*OCB)
Energy Technology Data Exchange (ETDEWEB)
Pawlus, S; Mierzwa, M; Paluch, M; Rzoska, S J [Institute of Physics, University of Silesia, Uniwersytecka 4, 40-007 Katowice (Poland); Roland, C M, E-mail: michal.mierzwa@us.edu.p [Chemistry Division, Naval Research Laboratory, Code 6120, Washington, DC 20375-5342 (United States)
2010-06-16
The dynamics of isooctylcyanobiphenyl (8*OCB) was characterized using dielectric and mechanical spectroscopies. This isomer of the liquid crystalline octylcyanobiphenyl (8OCB) vitrifies during cooling or on application of pressure, exhibiting the typical features of glass-forming liquids: non-Debye relaxation function, non-Arrhenius temperature dependence of the relaxation times, {tau}{sub {alpha}}, a dynamic crossover at T {approx} 1.6T{sub g}. This crossover is evidenced by changes in the behavior of both the peak shape and the temperature dependence of {tau}{sub {alpha}}. The primary relaxation time at the crossover, 2 ns at ambient pressure, is the smallest value reported to date for any molecular liquid or polymer. Interestingly, at all temperatures below this crossover, {tau}{sub {alpha}}and the dc conductivity remain coupled (i.e., conform to the Debye-Stokes-Einstein relation). Two secondary relaxations are observed in the glassy state, one of which is identified as the Johari-Goldstein process. Unlike the case for 8OCB, no liquid crystalline phase could be attained for 8*OCB, demonstrating that relatively small differences in chemical structure can effect substantial changes in the intermolecular potential.
2nd Bayesian Young Statisticians Meeting
Bitto, Angela; Kastner, Gregor; Posekany, Alexandra
2015-01-01
The Second Bayesian Young Statisticians Meeting (BAYSM 2014) and the research presented here facilitate connections among researchers using Bayesian Statistics by providing a forum for the development and exchange of ideas. WU Vienna University of Business and Economics hosted BAYSM 2014 from September 18th to 19th. The guidance of renowned plenary lecturers and senior discussants is a critical part of the meeting and this volume, which follows publication of contributions from BAYSM 2013. The meeting's scientific program reflected the variety of fields in which Bayesian methods are currently employed or could be introduced in the future. Three brilliant keynote lectures by Chris Holmes (University of Oxford), Christian Robert (Université Paris-Dauphine), and Mike West (Duke University), were complemented by 24 plenary talks covering the major topics Dynamic Models, Applications, Bayesian Nonparametrics, Biostatistics, Bayesian Methods in Economics, and Models and Methods, as well as a lively poster session ...
Bayesian natural language semantics and pragmatics
Zeevat, Henk
2015-01-01
The contributions in this volume focus on the Bayesian interpretation of natural languages, which is widely used in areas of artificial intelligence, cognitive science, and computational linguistics. This is the first volume to take up topics in Bayesian Natural Language Interpretation and make proposals based on information theory, probability theory, and related fields. The methodologies offered here extend to the target semantic and pragmatic analyses of computational natural language interpretation. Bayesian approaches to natural language semantics and pragmatics are based on methods from signal processing and the causal Bayesian models pioneered by especially Pearl. In signal processing, the Bayesian method finds the most probable interpretation by finding the one that maximizes the product of the prior probability and the likelihood of the interpretation. It thus stresses the importance of a production model for interpretation as in Grice's contributions to pragmatics or in interpretation by abduction.
Compaction and relaxation of biofilms
Valladares Linares, R.
2015-06-18
Operation of membrane systems for water treatment can be seriously hampered by biofouling. A better characterization of biofilms in membrane systems and their impact on membrane performance may help to develop effective biofouling control strategies. The objective of this study was to determine the occurrence, extent and timescale of biofilm compaction and relaxation (decompaction), caused by permeate flux variations. The impact of permeate flux changes on biofilm thickness, structure and stiffness was investigated in situ and non-destructively with optical coherence tomography using membrane fouling monitors operated at a constant crossflow velocity of 0.1 m s−1 with permeate production. The permeate flux was varied sequentially from 20 to 60 and back to 20 L m−2 h−1. The study showed that the average biofilm thickness on the membrane decreased after elevating the permeate flux from 20 to 60 L m−2 h−1 while the biofilm thickness increased again after restoring the original flux of 20 L m−2 h−1, indicating the occurrence of biofilm compaction and relaxation. Within a few seconds after the flux change, the biofilm thickness was changed and stabilized, biofilm compaction occurred faster than the relaxation after restoring the original permeate flux. The initial biofilm parameters were not fully reinstated: the biofilm thickness was reduced by 21%, biofilm stiffness had increased and the hydraulic biofilm resistance was elevated by 16%. Biofilm thickness was related to the hydraulic biofilm resistance. Membrane performance losses are related to the biofilm thickness, density and morphology, which are influenced by (variations in) hydraulic conditions. A (temporarily) permeate flux increase caused biofilm compaction, together with membrane performance losses. The impact of biofilms on membrane performance can be influenced (increased and reduced) by operational parameters. The article shows that a (temporary) pressure increase leads to more
Multiplied effect of heat and radiation in chemical stress relaxation
International Nuclear Information System (INIS)
Ito, Masayuki
1981-01-01
About the deterioration of rubber due to radiation, useful knowledge can be obtained by the measurement of chemical stress relaxation. As an example, the rubber coating of cables in a reactor containment vessel is estimated to be irradiated by weak radiation at the temperature between 60 and 90 deg C for about 40 years. In such case, it is desirable to establish the method of accelerated test of the deterioration. The author showed previously that the law of time-dose rate conversion holds in the case of radiation. In this study, the chemical stress relaxation to rubber was measured by the simultaneous application of heat and radiation, and it was found that there was the multiplied effect of heat and radiation in the stress relaxation speed. Therefore the factor of multiplication of heat and radiation was proposed to describe quantitatively the degree of the multiplied effect. The chloroprene rubber used was offered by Hitachi Cable Co., Ltd. The experimental method and the results are reported. The multiplication of heat and radiation is not caused by the direct cut of molecular chains by radiation, instead, it is based on the temperature dependence of various reaction rates at which the activated species reached the cut of molecular chains through complex reaction mechanism and the temperature dependence of the diffusion rate of oxygen in rubber. (Kako, I.)
Ultrasonic relaxations in borate glasses
International Nuclear Information System (INIS)
D'Angelo, G.; Tripodo, G.; Carini, G.; Cosio, E.; Bartolotta, A.; Di Marco, G.
2004-01-01
The attenuation and velocity of ultrasonic waves of frequencies in the range from 10 to 70 MHz have been measured in M 2 O-B 2 O 3 borate glasses (M: Li or Ag) as a function of temperature between 15 and 350 K. The velocity of sound waves decreases with increasing temperature in all the glasses, the decrease as the temperature is increased is larger in glasses containing silver than in those with lithium. A broad relaxation peak characterises the attenuation behaviour of the lithium and silver borate glasses at temperatures below 100 K and is paralleled by a corresponding dispersive behaviour of the sound velocity. Above 100 K, the ultrasonic velocity shows a nearly linear behaviour regulated by the vibrational anharmonicity, which decreases with increasing content of modifier oxide and is smaller in lithium than in silver borates. These results suggest that the relaxation of structural defects and the anharmonicity of borate glasses are strongly affected by two parameters: the number of bridging bonds per network forming ion and the polarising power of network modifier ions which occupy sites in the existing interstices
Statistical mechanics of violent relaxation
International Nuclear Information System (INIS)
Shu, F.H.
1978-01-01
We reexamine the foundations of Lynden-Bell's statistical mechanical discussion of violent relaxation in collisionless stellar systems. We argue that Lynden-Bell's formulation in terms of a continuum description introduces unnecessary complications, and we consider a more conventional formulation in terms of particles. We then find the exclusion principle discovered by Lynden-Bell to be quantitatively important only at phase densities where two-body encounters are no longer negligible. Since the edynamical basis for the exclusion principle vanishes in such cases anyway, Lynden-Bell statistics always reduces in practice to Maxwell-Boltzmann statistics when applied to stellar systems. Lynden-Bell also found the equilibrium distribution function generally to be a sum of Maxwellians with velocity dispersions dependent on the phase density at star formation. We show that this difficulty vanishes in the particulate description for an encounterless stellar system as long as stars of different masses are initially well mixed in phase space. Our methods also demonstrate the equivalence between Gibbs's formalism which uses the microcanonical ensemble and Boltzmann's formalism which uses a coarse-grained continuum description. In addition, we clarify the concept of irreversible behavior on a macroscopic scale for an encounterless stellar system. Finally, we comment on the use of unusual macroscopic constraints to simulate the effects of incomplete relaxation
Glass transition and relaxation dynamics of propylene glycol-water solutions confined in clay
Elamin, Khalid; Björklund, Jimmy; Nyhlén, Fredrik; Yttergren, Madeleine; Mârtensson, Lena; Swenson, Jan
2014-07-01
The molecular dynamics of aqueous solutions of propylene glycol (PG) and propylene glycol methylether (PGME) confined in a two-dimensional layer-structured Na-vermiculite clay has been studied by broadband dielectric spectroscopy and differential scanning calorimetry. As typical for liquids in confined geometries the intensity of the cooperative α-relaxation becomes considerably more suppressed than the more local β-like relaxation processes. In fact, at high water contents the calorimetric glass transition and related structural α-relaxation cannot even be observed, due to the confinement. Thus, the intensity of the viscosity related α-relaxation is dramatically reduced, but its time scale as well as the related glass transition temperature Tg are for both systems only weakly influenced by the confinement. In the case of the PGME-water solutions it is an important finding since in the corresponding bulk system a pronounced non-monotonic concentration dependence of the glass transition related dynamics has been observed due to the growth of hydrogen bonded relaxing entities of water bridging between PGME molecules [J. Sjöström, J. Mattsson, R. Bergman, and J. Swenson, Phys. Chem. B 115, 10013 (2011)]. The present results suggest that the same type of structural entities are formed in the quasi-two-dimensional space between the clay platelets. It is also observed that the main water relaxation cannot be distinguished from the β-relaxation of PG or PGME in the concentration range up to intermediate water contents. This suggests that these two processes are coupled and that the water molecules affect the time scale of the β-relaxation. However, this is most likely true also for the corresponding bulk solutions, which exhibit similar time scales of this combined relaxation process below Tg. Finally, it is found that at higher water contents the water relaxation does not merge with, or follow, the α-relaxation above Tg, but instead crosses the α-relaxation
A Bayesian Reflection on Surfaces
Directory of Open Access Journals (Sweden)
David R. Wolf
1999-10-01
Full Text Available Abstract: The topic of this paper is a novel Bayesian continuous-basis field representation and inference framework. Within this paper several problems are solved: The maximally informative inference of continuous-basis fields, that is where the basis for the field is itself a continuous object and not representable in a finite manner; the tradeoff between accuracy of representation in terms of information learned, and memory or storage capacity in bits; the approximation of probability distributions so that a maximal amount of information about the object being inferred is preserved; an information theoretic justification for multigrid methodology. The maximally informative field inference framework is described in full generality and denoted the Generalized Kalman Filter. The Generalized Kalman Filter allows the update of field knowledge from previous knowledge at any scale, and new data, to new knowledge at any other scale. An application example instance, the inference of continuous surfaces from measurements (for example, camera image data, is presented.
Attention in a bayesian framework
DEFF Research Database (Denmark)
Whiteley, Louise Emma; Sahani, Maneesh
2012-01-01
, and include both selective phenomena, where attention is invoked by cues that point to particular stimuli, and integrative phenomena, where attention is invoked dynamically by endogenous processing. However, most previous Bayesian accounts of attention have focused on describing relatively simple experimental...... selective and integrative roles, and thus cannot be easily extended to complex environments. We suggest that the resource bottleneck stems from the computational intractability of exact perceptual inference in complex settings, and that attention reflects an evolved mechanism for approximate inference which...... can be shaped to refine the local accuracy of perception. We show that this approach extends the simple picture of attention as prior, so as to provide a unified and computationally driven account of both selective and integrative attentional phenomena....
On Bayesian System Reliability Analysis
Energy Technology Data Exchange (ETDEWEB)
Soerensen Ringi, M
1995-05-01
The view taken in this thesis is that reliability, the probability that a system will perform a required function for a stated period of time, depends on a person`s state of knowledge. Reliability changes as this state of knowledge changes, i.e. when new relevant information becomes available. Most existing models for system reliability prediction are developed in a classical framework of probability theory and they overlook some information that is always present. Probability is just an analytical tool to handle uncertainty, based on judgement and subjective opinions. It is argued that the Bayesian approach gives a much more comprehensive understanding of the foundations of probability than the so called frequentistic school. A new model for system reliability prediction is given in two papers. The model encloses the fact that component failures are dependent because of a shared operational environment. The suggested model also naturally permits learning from failure data of similar components in non identical environments. 85 refs.
Nonparametric Bayesian inference in biostatistics
Müller, Peter
2015-01-01
As chapters in this book demonstrate, BNP has important uses in clinical sciences and inference for issues like unknown partitions in genomics. Nonparametric Bayesian approaches (BNP) play an ever expanding role in biostatistical inference from use in proteomics to clinical trials. Many research problems involve an abundance of data and require flexible and complex probability models beyond the traditional parametric approaches. As this book's expert contributors show, BNP approaches can be the answer. Survival Analysis, in particular survival regression, has traditionally used BNP, but BNP's potential is now very broad. This applies to important tasks like arrangement of patients into clinically meaningful subpopulations and segmenting the genome into functionally distinct regions. This book is designed to both review and introduce application areas for BNP. While existing books provide theoretical foundations, this book connects theory to practice through engaging examples and research questions. Chapters c...
On Bayesian System Reliability Analysis
International Nuclear Information System (INIS)
Soerensen Ringi, M.
1995-01-01
The view taken in this thesis is that reliability, the probability that a system will perform a required function for a stated period of time, depends on a person's state of knowledge. Reliability changes as this state of knowledge changes, i.e. when new relevant information becomes available. Most existing models for system reliability prediction are developed in a classical framework of probability theory and they overlook some information that is always present. Probability is just an analytical tool to handle uncertainty, based on judgement and subjective opinions. It is argued that the Bayesian approach gives a much more comprehensive understanding of the foundations of probability than the so called frequentistic school. A new model for system reliability prediction is given in two papers. The model encloses the fact that component failures are dependent because of a shared operational environment. The suggested model also naturally permits learning from failure data of similar components in non identical environments. 85 refs
Bayesian estimation in homodyne interferometry
International Nuclear Information System (INIS)
Olivares, Stefano; Paris, Matteo G A
2009-01-01
We address phase-shift estimation by means of squeezed vacuum probe and homodyne detection. We analyse Bayesian estimator, which is known to asymptotically saturate the classical Cramer-Rao bound to the variance, and discuss convergence looking at the a posteriori distribution as the number of measurements increases. We also suggest two feasible adaptive methods, acting on the squeezing parameter and/or the homodyne local oscillator phase, which allow us to optimize homodyne detection and approach the ultimate bound to precision imposed by the quantum Cramer-Rao theorem. The performances of our two-step methods are investigated by means of Monte Carlo simulated experiments with a small number of homodyne data, thus giving a quantitative meaning to the notion of asymptotic optimality.
Bayesian Kernel Mixtures for Counts.
Canale, Antonio; Dunson, David B
2011-12-01
Although Bayesian nonparametric mixture models for continuous data are well developed, there is a limited literature on related approaches for count data. A common strategy is to use a mixture of Poissons, which unfortunately is quite restrictive in not accounting for distributions having variance less than the mean. Other approaches include mixing multinomials, which requires finite support, and using a Dirichlet process prior with a Poisson base measure, which does not allow smooth deviations from the Poisson. As a broad class of alternative models, we propose to use nonparametric mixtures of rounded continuous kernels. An efficient Gibbs sampler is developed for posterior computation, and a simulation study is performed to assess performance. Focusing on the rounded Gaussian case, we generalize the modeling framework to account for multivariate count data, joint modeling with continuous and categorical variables, and other complications. The methods are illustrated through applications to a developmental toxicity study and marketing data. This article has supplementary material online.
Bayesian networks in educational assessment
Almond, Russell G; Steinberg, Linda S; Yan, Duanli; Williamson, David M
2015-01-01
Bayesian inference networks, a synthesis of statistics and expert systems, have advanced reasoning under uncertainty in medicine, business, and social sciences. This innovative volume is the first comprehensive treatment exploring how they can be applied to design and analyze innovative educational assessments. Part I develops Bayes nets’ foundations in assessment, statistics, and graph theory, and works through the real-time updating algorithm. Part II addresses parametric forms for use with assessment, model-checking techniques, and estimation with the EM algorithm and Markov chain Monte Carlo (MCMC). A unique feature is the volume’s grounding in Evidence-Centered Design (ECD) framework for assessment design. This “design forward” approach enables designers to take full advantage of Bayes nets’ modularity and ability to model complex evidentiary relationships that arise from performance in interactive, technology-rich assessments such as simulations. Part III describes ECD, situates Bayes nets as ...
International Nuclear Information System (INIS)
Chopin, C.; Spanjaard, D.; Hartmann-Boutron, F.
1975-01-01
Previous perturbation treatments of paramagnetic relaxation effects in γγ PAC were limited to the case of very short electronic relaxation times. This limitation is circumvented by invoking a new perturbation theory recently elaborated by Hirst and others for handling relaxation effects in Moessbauer spectra. Under the assumption of spherical electronic relaxation the perturbation factors are computed as functions of certain relaxation parameters which are directly related to the microscopic relaxation Hamiltonian. The results are compared to those of the stochastic theory of Scherer and Blume [fr
Memory effects in the relaxation of a confined granular gas
Brey, J. Javier; de Soria, M. I. García; Maynar, P.; Buzón, V.
2014-09-01
The accuracy of a model to describe the horizontal dynamics of a confined quasi-two-dimensional system of inelastic hard spheres is discussed by comparing its predictions for the relaxation of the temperature in a homogenous system with molecular dynamics simulation results for the original system. A reasonably good agreement is found. Next the model is used to investigate the peculiarities of the nonlinear evolution of the temperature when the parameter controlling the energy injection is instantaneously changed while the system was relaxing. This can be considered as a nonequilibrium generalization of the Kovacs effect. It is shown that, in the low-density limit, the effect can be accurately described by using a simple kinetic theory based on the first Sonine approximation for the one-particle distribution function. Some possible experimental implications are indicated.
Cross relaxation in nitroxide spin labels
DEFF Research Database (Denmark)
Marsh, Derek
2016-01-01
Cross relaxation, and mI-dependence of the intrinsic electron spin-lattice relaxation rate We, are incorporated explicitly into the rate equations for the electron-spin population differences that govern the saturation behaviour of 14N- and 15N-nitroxide spin labels. Both prove important in spin......-label EPR and ELDOR, particularly for saturation recovery studies. Neither for saturation recovery, nor for CW-saturation EPR and CW-ELDOR, can cross relaxation be described simply by increasing the value of We, the intrinsic spin-lattice relaxation rate. Independence of the saturation recovery rates from...... the hyperfine line pumped or observed follows directly from solution of the rate equations including cross relaxation, even when the intrinsic spin-lattice relaxation rate We is mI-dependent....
Robust bayesian analysis of an autoregressive model with ...
African Journals Online (AJOL)
In this work, robust Bayesian analysis of the Bayesian estimation of an autoregressive model with exponential innovations is performed. Using a Bayesian robustness methodology, we show that, using a suitable generalized quadratic loss, we obtain optimal Bayesian estimators of the parameters corresponding to the ...
Structural relaxation in annealed hyperquenched basaltic glasses
DEFF Research Database (Denmark)
Guo, Xiaoju; Mauro, John C.; Potuzak, M.
2012-01-01
The enthalpy relaxation behavior of hyperquenched (HQ) and annealed hyperquenched (AHQ) basaltic glass is investigated through calorimetric measurements. The results reveal a common onset temperature of the glass transition for all the HQ and AHQ glasses under study, indicating that the primary...... relaxation is activated at the same temperature regardless of the initial departure from equilibrium. The analysis of secondary relaxation at different annealing temperatures provides insights into the enthalpy recovery of HQ glasses....
Bayesian models a statistical primer for ecologists
Hobbs, N Thompson
2015-01-01
Bayesian modeling has become an indispensable tool for ecological research because it is uniquely suited to deal with complexity in a statistically coherent way. This textbook provides a comprehensive and accessible introduction to the latest Bayesian methods-in language ecologists can understand. Unlike other books on the subject, this one emphasizes the principles behind the computations, giving ecologists a big-picture understanding of how to implement this powerful statistical approach. Bayesian Models is an essential primer for non-statisticians. It begins with a definition of probabili
Mechanisms of relaxation and spin decoherence in nanomagnets
van Tol, Johan
Relaxation in spin systems is of great interest with respect to various possible applications like quantum information processing and storage, spintronics, and dynamic nuclear polarization (DNP). The implementation of high frequencies and fields is crucial in the study of systems with large zero-field splitting or large interactions, as for example molecular magnets and low dimensional magnetic materials. Here we will focus on the implementation of pulsed Electron Paramagnetic Resonance (ERP) at multiple frequencies of 10, 95, 120, 240, and 336 GHz, and the relaxation and decoherence processes as a function of magnetic field and temperature. Firstly, at higher frequencies the direct single-phonon spin-lattice relaxation (SLR) is considerably enhanced, and will more often than not be the dominant relaxation mechanism at low temperatures, and can be much faster than at lower fields and frequencies. In principle the measurement of the SLR rates as a function of the frequency provides a means to map the phonon density of states. Secondly, the high electron spin polarization at high fields has a strong influence on the spin fluctuations in relatively concentrated spin systems, and the contribution of the electron-electron dipolar interactions to the coherence rate can be partially quenched at low temperatures. This not only allows the study of relatively concentrated spin systems by pulsed EPR (as for example magnetic nanoparticles and molecular magnets), it enables the separation of the contribution of the fluctuations of the electron spin system from other decoherence mechanisms. Besides choice of temperature and field, several strategies in sample design, pulse sequences, or clock transitions can be employed to extend the coherence time in nanomagnets. A review will be given of the decoherence mechanisms with an attempt at a quantitative comparison of experimental rates with theory.
Influence of E-beam irradiation on dielectric relaxation of recycled polypropylene
International Nuclear Information System (INIS)
Fazilova, Z.; Gafurov, U.; Tolstov, A.
2004-01-01
Full text: The dielectric relaxation connected with molecular groups and polymer chain mobility for un-irradiated and e-beam irradiated recycled polypropylene was investigated. It was studied films of samples produced from virgin (initial) and e- beam irradiated of the polymer granules (E-beam source with 5 MeV energy). The dielectric losses were measured with temperature increasing and decreasing regime. The losses were measured with E8-4 bridge help (the frequency is 1kH). Heating velocity was 2 grad/min. The dielectric losses did not appeared in minus temperature region for the initial polypropylene samples. The measurement in temperature increasing and decreasing shows that the relaxation peak at ∼ 35 o C for un-irradiated and ∼70 o C for irradiated polymer samples connected with macromolecular segments mobility with water molecular groups participation. The main relaxation peak (higher 100 o C) shifts after e-beam irradiation is result of the cross-links formation. ) The peak connected with macromolecular segments mobility in polymer amorphous regions (β-relaxation process). In irradiated polypropylene on IR spectroscopy data oxygen molecular groups is increased. The molecular groupings form inter-molecular hydrogen bonds. The intermolecular bonds also hindered molecular groups and macromolecular mobility. The e-beam stimulated cross-links formation was confirmed by method of sol-gel analyses. The work was supported by STCU Fund (Project No 3009)
A Bayesian approach to meta-analysis of plant pathology studies.
Mila, A L; Ngugi, H K
2011-01-01
Bayesian statistical methods are used for meta-analysis in many disciplines, including medicine, molecular biology, and engineering, but have not yet been applied for quantitative synthesis of plant pathology studies. In this paper, we illustrate the key concepts of Bayesian statistics and outline the differences between Bayesian and classical (frequentist) methods in the way parameters describing population attributes are considered. We then describe a Bayesian approach to meta-analysis and present a plant pathological example based on studies evaluating the efficacy of plant protection products that induce systemic acquired resistance for the management of fire blight of apple. In a simple random-effects model assuming a normal distribution of effect sizes and no prior information (i.e., a noninformative prior), the results of the Bayesian meta-analysis are similar to those obtained with classical methods. Implementing the same model with a Student's t distribution and a noninformative prior for the effect sizes, instead of a normal distribution, yields similar results for all but acibenzolar-S-methyl (Actigard) which was evaluated only in seven studies in this example. Whereas both the classical (P = 0.28) and the Bayesian analysis with a noninformative prior (95% credibility interval [CRI] for the log response ratio: -0.63 to 0.08) indicate a nonsignificant effect for Actigard, specifying a t distribution resulted in a significant, albeit variable, effect for this product (CRI: -0.73 to -0.10). These results confirm the sensitivity of the analytical outcome (i.e., the posterior distribution) to the choice of prior in Bayesian meta-analyses involving a limited number of studies. We review some pertinent literature on more advanced topics, including modeling of among-study heterogeneity, publication bias, analyses involving a limited number of studies, and methods for dealing with missing data, and show how these issues can be approached in a Bayesian framework
Dielectric Relaxation of Water: Theory and Experiment
International Nuclear Information System (INIS)
Adhikari, Narayan Prasad; Paudyal, Harihar; Johri, Manoj
2010-06-01
We have studied the hydrogen bond dynamics and methods for evaluation of probability and relaxation time for hydrogen bond network. Further, dielectric relaxation time has been calculated by using a diagonalization procedure by obtaining eigen values (inverse of relaxation time) of a master equation framed on the basis of Fokker-Planck equations. Microwave cavity spectrometer has been described to make measurements of relaxation time. Slater's perturbation equations are given for the analysis of the data. A comparison of theoretical and experimental data shows that there is a need for improvements in the theoretical model and experimental techniques to provide exact information about structural properties of water. (author)
Pair plasma relaxation time scales.
Aksenov, A G; Ruffini, R; Vereshchagin, G V
2010-04-01
By numerically solving the relativistic Boltzmann equations, we compute the time scale for relaxation to thermal equilibrium for an optically thick electron-positron plasma with baryon loading. We focus on the time scales of electromagnetic interactions. The collisional integrals are obtained directly from the corresponding QED matrix elements. Thermalization time scales are computed for a wide range of values of both the total-energy density (over 10 orders of magnitude) and of the baryonic loading parameter (over 6 orders of magnitude). This also allows us to study such interesting limiting cases as the almost purely electron-positron plasma or electron-proton plasma as well as intermediate cases. These results appear to be important both for laboratory experiments aimed at generating optically thick pair plasmas as well as for astrophysical models in which electron-positron pair plasmas play a relevant role.
Relaxing Chosen-Ciphertext Security
DEFF Research Database (Denmark)
Canetti, Ran; Krawczyk, Hugo; Nielsen, Jesper Buus
2003-01-01
Security against adaptive chosen ciphertext attacks (or, CCA security) has been accepted as the standard requirement from encryption schemes that need to withstand active attacks. In particular, it is regarded as the appropriate security notion for encryption schemes used as components within...... general protocols and applications. Indeed, CCA security was shown to suffice in a large variety of contexts. However, CCA security often appears to be somewhat too strong: there exist encryption schemes (some of which come up naturally in practice) that are not CCA secure, but seem sufficiently secure...... “for most practical purposes.” We propose a relaxed variant of CCA security, called Replayable CCA (RCCA) security. RCCA security accepts as secure the non-CCA (yet arguably secure) schemes mentioned above; furthermore, it suffices for most existing applications of CCA security. We provide three...
Nuclear magnetic relaxation by the dipolar EMOR mechanism: Multi-spin systems
Chang, Zhiwei; Halle, Bertil
2017-08-01
In aqueous systems with immobilized macromolecules, including biological tissues, the longitudinal spin relaxation of water protons is primarily induced by exchange-mediated orientational randomization (EMOR) of intra- and intermolecular magnetic dipole-dipole couplings. Starting from the stochastic Liouville equation, we have previously developed a rigorous EMOR relaxation theory for dipole-coupled two-spin and three-spin systems. Here, we extend the stochastic Liouville theory to four-spin systems and use these exact results as a guide for constructing an approximate multi-spin theory, valid for spin systems of arbitrary size. This so-called generalized stochastic Redfield equation (GSRE) theory includes the effects of longitudinal-transverse cross-mode relaxation, which gives rise to an inverted step in the relaxation dispersion profile, and coherent spin mode transfer among solid-like spins, which may be regarded as generalized spin diffusion. The GSRE theory is compared to an existing theory, based on the extended Solomon equations, which does not incorporate these phenomena. Relaxation dispersion profiles are computed from the GSRE theory for systems of up to 16 protons, taken from protein crystal structures. These profiles span the range from the motional narrowing limit, where the coherent mode transfer plays a major role, to the ultra-slow motion limit, where the zero-field rate is closely related to the strong-collision limit of the dipolar relaxation rate. Although a quantitative analysis of experimental data is beyond the scope of this work, it is clear from the magnitude of the predicted relaxation rate and the shape of the relaxation dispersion profile that the dipolar EMOR mechanism is the principal cause of water-1H low-field longitudinal relaxation in aqueous systems of immobilized macromolecules, including soft biological tissues. The relaxation theory developed here therefore provides a basis for molecular-level interpretation of endogenous soft
Curie-type paramagnetic NMR relaxation in the aqueous solution of Ni(II).
Mareš, Jiří; Hanni, Matti; Lantto, Perttu; Lounila, Juhani; Vaara, Juha
2014-04-21
Ni(2+)(aq) has been used for many decades as a model system for paramagnetic nuclear magnetic resonance (pNMR) relaxation studies. More recently, its magnetic properties and also nuclear magnetic relaxation rates have been studied computationally. We have calculated electron paramagnetic resonance and NMR parameters using quantum-mechanical (QM) computation of molecular dynamics snapshots, obtained using a polarizable empirical force field. Statistical averages of hyperfine coupling, g- and zero-field splitting tensors, as well as the pNMR shielding terms, are compared to the available experimental and computational data. In accordance with our previous work, the isotropic hyperfine coupling as well as nuclear shielding values agree well with experimental measurements for the (17)O nuclei of water molecules in the first solvation shell of the nickel ion, whereas larger deviations are found for (1)H centers. We report, for the first time, the Curie-type contribution to the pNMR relaxation rate using QM calculations together with Redfield relaxation theory. The Curie relaxation mechanism is analogous to chemical shift anisotropy relaxation, well-known in diamagnetic NMR. Due to the predominance of other types of paramagnetic relaxation mechanisms for this system, it is possible to extract the Curie term only computationally. The Curie mechanism alone would result in around 16 and 20 s(-1) of relaxation rates (R1 and R2 respectively) for the (1)H nuclei of water molecules bonded to the Ni(2+) center, in a magnetic field of 11.7 T. The corresponding (17)O relaxation rates are around 33 and 38 s(-1). We also report the Curie contribution to the relaxation rate for molecules beyond the first solvation shell in a 1 M solution of Ni(2+) in water.
Markov state modeling and dynamical coarse-graining via discrete relaxation path sampling.
Fačkovec, B; Vanden-Eijnden, E; Wales, D J
2015-07-28
A method is derived to coarse-grain the dynamics of complex molecular systems to a Markov jump process (MJP) describing how the system jumps between cells that fully partition its state space. The main inputs are relaxation times for each pair of cells, which are shown to be robust with respect to positioning of the cell boundaries. These relaxation times can be calculated via molecular dynamics simulations performed in each cell separately and are used in an efficient estimator for the rate matrix of the MJP. The method is illustrated through applications to Sinai billiards and a cluster of Lennard-Jones discs.
Bayesian adaptive methods for clinical trials
National Research Council Canada - National Science Library
Berry, Scott M
2011-01-01
.... One is that Bayesian approaches implemented with the majority of their informative content coming from the current data, and not any external prior informa- tion, typically have good frequentist properties (e.g...
A Bayesian approach to model uncertainty
International Nuclear Information System (INIS)
Buslik, A.
1994-01-01
A Bayesian approach to model uncertainty is taken. For the case of a finite number of alternative models, the model uncertainty is equivalent to parameter uncertainty. A derivation based on Savage's partition problem is given
Structure-based bayesian sparse reconstruction
Quadeer, Ahmed Abdul; Al-Naffouri, Tareq Y.
2012-01-01
Sparse signal reconstruction algorithms have attracted research attention due to their wide applications in various fields. In this paper, we present a simple Bayesian approach that utilizes the sparsity constraint and a priori statistical
An Intuitive Dashboard for Bayesian Network Inference
International Nuclear Information System (INIS)
Reddy, Vikas; Farr, Anna Charisse; Wu, Paul; Mengersen, Kerrie; Yarlagadda, Prasad K D V
2014-01-01
Current Bayesian network software packages provide good graphical interface for users who design and develop Bayesian networks for various applications. However, the intended end-users of these networks may not necessarily find such an interface appealing and at times it could be overwhelming, particularly when the number of nodes in the network is large. To circumvent this problem, this paper presents an intuitive dashboard, which provides an additional layer of abstraction, enabling the end-users to easily perform inferences over the Bayesian networks. Unlike most software packages, which display the nodes and arcs of the network, the developed tool organises the nodes based on the cause-and-effect relationship, making the user-interaction more intuitive and friendly. In addition to performing various types of inferences, the users can conveniently use the tool to verify the behaviour of the developed Bayesian network. The tool has been developed using QT and SMILE libraries in C++
Learning Bayesian networks for discrete data
Liang, Faming
2009-02-01
Bayesian networks have received much attention in the recent literature. In this article, we propose an approach to learn Bayesian networks using the stochastic approximation Monte Carlo (SAMC) algorithm. Our approach has two nice features. Firstly, it possesses the self-adjusting mechanism and thus avoids essentially the local-trap problem suffered by conventional MCMC simulation-based approaches in learning Bayesian networks. Secondly, it falls into the class of dynamic importance sampling algorithms; the network features can be inferred by dynamically weighted averaging the samples generated in the learning process, and the resulting estimates can have much lower variation than the single model-based estimates. The numerical results indicate that our approach can mix much faster over the space of Bayesian networks than the conventional MCMC simulation-based approaches. © 2008 Elsevier B.V. All rights reserved.
An Intuitive Dashboard for Bayesian Network Inference
Reddy, Vikas; Charisse Farr, Anna; Wu, Paul; Mengersen, Kerrie; Yarlagadda, Prasad K. D. V.
2014-03-01
Current Bayesian network software packages provide good graphical interface for users who design and develop Bayesian networks for various applications. However, the intended end-users of these networks may not necessarily find such an interface appealing and at times it could be overwhelming, particularly when the number of nodes in the network is large. To circumvent this problem, this paper presents an intuitive dashboard, which provides an additional layer of abstraction, enabling the end-users to easily perform inferences over the Bayesian networks. Unlike most software packages, which display the nodes and arcs of the network, the developed tool organises the nodes based on the cause-and-effect relationship, making the user-interaction more intuitive and friendly. In addition to performing various types of inferences, the users can conveniently use the tool to verify the behaviour of the developed Bayesian network. The tool has been developed using QT and SMILE libraries in C++.
Bayesian optimization for computationally extensive probability distributions.
Tamura, Ryo; Hukushima, Koji
2018-01-01
An efficient method for finding a better maximizer of computationally extensive probability distributions is proposed on the basis of a Bayesian optimization technique. A key idea of the proposed method is to use extreme values of acquisition functions by Gaussian processes for the next training phase, which should be located near a local maximum or a global maximum of the probability distribution. Our Bayesian optimization technique is applied to the posterior distribution in the effective physical model estimation, which is a computationally extensive probability distribution. Even when the number of sampling points on the posterior distributions is fixed to be small, the Bayesian optimization provides a better maximizer of the posterior distributions in comparison to those by the random search method, the steepest descent method, or the Monte Carlo method. Furthermore, the Bayesian optimization improves the results efficiently by combining the steepest descent method and thus it is a powerful tool to search for a better maximizer of computationally extensive probability distributions.
Correct Bayesian and frequentist intervals are similar
International Nuclear Information System (INIS)
Atwood, C.L.
1986-01-01
This paper argues that Bayesians and frequentists will normally reach numerically similar conclusions, when dealing with vague data or sparse data. It is shown that both statistical methodologies can deal reasonably with vague data. With sparse data, in many important practical cases Bayesian interval estimates and frequentist confidence intervals are approximately equal, although with discrete data the frequentist intervals are somewhat longer. This is not to say that the two methodologies are equally easy to use: The construction of a frequentist confidence interval may require new theoretical development. Bayesians methods typically require numerical integration, perhaps over many variables. Also, Bayesian can easily fall into the trap of over-optimism about their amount of prior knowledge. But in cases where both intervals are found correctly, the two intervals are usually not very different. (orig.)
Implementing the Bayesian paradigm in risk analysis
International Nuclear Information System (INIS)
Aven, T.; Kvaloey, J.T.
2002-01-01
The Bayesian paradigm comprises a unified and consistent framework for analyzing and expressing risk. Yet, we see rather few examples of applications where the full Bayesian setting has been adopted with specifications of priors of unknown parameters. In this paper, we discuss some of the practical challenges of implementing Bayesian thinking and methods in risk analysis, emphasizing the introduction of probability models and parameters and associated uncertainty assessments. We conclude that there is a need for a pragmatic view in order to 'successfully' apply the Bayesian approach, such that we can do the assignments of some of the probabilities without adopting the somewhat sophisticated procedure of specifying prior distributions of parameters. A simple risk analysis example is presented to illustrate ideas
An overview on Approximate Bayesian computation*
Directory of Open Access Journals (Sweden)
Baragatti Meïli
2014-01-01
Full Text Available Approximate Bayesian computation techniques, also called likelihood-free methods, are one of the most satisfactory approach to intractable likelihood problems. This overview presents recent results since its introduction about ten years ago in population genetics.
Bayesian probability theory and inverse problems
International Nuclear Information System (INIS)
Kopec, S.
1994-01-01
Bayesian probability theory is applied to approximate solving of the inverse problems. In order to solve the moment problem with the noisy data, the entropic prior is used. The expressions for the solution and its error bounds are presented. When the noise level tends to zero, the Bayesian solution tends to the classic maximum entropy solution in the L 2 norm. The way of using spline prior is also shown. (author)
A Bayesian classifier for symbol recognition
Barrat , Sabine; Tabbone , Salvatore; Nourrissier , Patrick
2007-01-01
URL : http://www.buyans.com/POL/UploadedFile/134_9977.pdf; International audience; We present in this paper an original adaptation of Bayesian networks to symbol recognition problem. More precisely, a descriptor combination method, which enables to improve significantly the recognition rate compared to the recognition rates obtained by each descriptor, is presented. In this perspective, we use a simple Bayesian classifier, called naive Bayes. In fact, probabilistic graphical models, more spec...
Bayesian Modeling of a Human MMORPG Player
Synnaeve, Gabriel; Bessière, Pierre
2011-03-01
This paper describes an application of Bayesian programming to the control of an autonomous avatar in a multiplayer role-playing game (the example is based on World of Warcraft). We model a particular task, which consists of choosing what to do and to select which target in a situation where allies and foes are present. We explain the model in Bayesian programming and show how we could learn the conditional probabilities from data gathered during human-played sessions.
Variations on Bayesian Prediction and Inference
2016-05-09
inference 2.2.1 Background There are a number of statistical inference problems that are not generally formulated via a full probability model...problem of inference about an unknown parameter, the Bayesian approach requires a full probability 1. REPORT DATE (DD-MM-YYYY) 4. TITLE AND...the problem of inference about an unknown parameter, the Bayesian approach requires a full probability model/likelihood which can be an obstacle
Bayesian target tracking based on particle filter
Institute of Scientific and Technical Information of China (English)
无
2005-01-01
For being able to deal with the nonlinear or non-Gaussian problems, particle filters have been studied by many researchers. Based on particle filter, the extended Kalman filter (EKF) proposal function is applied to Bayesian target tracking. Markov chain Monte Carlo (MCMC) method, the resampling step, etc novel techniques are also introduced into Bayesian target tracking. And the simulation results confirm the improved particle filter with these techniques outperforms the basic one.
MCMC for parameters estimation by bayesian approach
International Nuclear Information System (INIS)
Ait Saadi, H.; Ykhlef, F.; Guessoum, A.
2011-01-01
This article discusses the parameter estimation for dynamic system by a Bayesian approach associated with Markov Chain Monte Carlo methods (MCMC). The MCMC methods are powerful for approximating complex integrals, simulating joint distributions, and the estimation of marginal posterior distributions, or posterior means. The MetropolisHastings algorithm has been widely used in Bayesian inference to approximate posterior densities. Calibrating the proposal distribution is one of the main issues of MCMC simulation in order to accelerate the convergence.
Bayesian Networks for Modeling Dredging Decisions
2011-10-01
years, that algorithms have been developed to solve these problems efficiently. Most modern Bayesian network software uses junction tree (a.k.a. join... software was used to develop the network . This is by no means an exhaustive list of Bayesian network applications, but it is representative of recent...characteristic node (SCN), state- defining node ( SDN ), effect node (EFN), or value node. The five types of nodes can be described as follows: ERDC/EL TR-11
Fully probabilistic design of hierarchical Bayesian models
Czech Academy of Sciences Publication Activity Database
Quinn, A.; Kárný, Miroslav; Guy, Tatiana Valentine
2016-01-01
Roč. 369, č. 1 (2016), s. 532-547 ISSN 0020-0255 R&D Projects: GA ČR GA13-13502S Institutional support: RVO:67985556 Keywords : Fully probabilistic design * Ideal distribution * Minimum cross-entropy principle * Bayesian conditioning * Kullback-Leibler divergence * Bayesian nonparametric modelling Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 4.832, year: 2016 http://library.utia.cas.cz/separaty/2016/AS/karny-0463052.pdf
A Bayesian Method for Weighted Sampling
Lo, Albert Y.
1993-01-01
Bayesian statistical inference for sampling from weighted distribution models is studied. Small-sample Bayesian bootstrap clone (BBC) approximations to the posterior distribution are discussed. A second-order property for the BBC in unweighted i.i.d. sampling is given. A consequence is that BBC approximations to a posterior distribution of the mean and to the sampling distribution of the sample average, can be made asymptotically accurate by a proper choice of the random variables that genera...
National Research Council Canada - National Science Library
Scheufele, Peter
1999-01-01
...) suggested that stress management techniques have specific effects A compromise position suggests that the specific effects of relaxation techniques are superimposed upon a general relaxation response...
Vibrational relaxation in liquids: Comparisons between gas phase and liquid phase theories
International Nuclear Information System (INIS)
Russell, D.J.
1990-12-01
The vibrational relaxation of iodine in liquid xenon was studied to understand what processes are important in determining the density dependence of the vibrational relaxation. This examination will be accomplished by taking simple models and comparing the results to both experimental outcomes and the predictions of molecular dynamics simulations. The vibration relaxation of iodine is extremely sensitive to the iodine potential. The anharmonicity of iodine causes vibrational relaxation to be much faster at the top of the iodine well compared to the vibrational relaxation at the bottom. A number of models are used in order to test the ability of the Isolated Binary Collision theory's ability to predict the density dependence of the vibrational relaxation of iodine in liquid xenon. The models tested vary from the simplest incorporating only the fact that the solvent occupies volume to models that incorporate the short range structure of the liquid in the radial distribution function. None of the models tested do a good job of predicting the actual relaxation rate for a given density. This may be due to a possible error in the choice of potentials to model the system
Philosophy and the practice of Bayesian statistics.
Gelman, Andrew; Shalizi, Cosma Rohilla
2013-02-01
A substantial school in the philosophy of science identifies Bayesian inference with inductive inference and even rationality as such, and seems to be strengthened by the rise and practical success of Bayesian statistics. We argue that the most successful forms of Bayesian statistics do not actually support that particular philosophy but rather accord much better with sophisticated forms of hypothetico-deductivism. We examine the actual role played by prior distributions in Bayesian models, and the crucial aspects of model checking and model revision, which fall outside the scope of Bayesian confirmation theory. We draw on the literature on the consistency of Bayesian updating and also on our experience of applied work in social science. Clarity about these matters should benefit not just philosophy of science, but also statistical practice. At best, the inductivist view has encouraged researchers to fit and compare models without checking them; at worst, theorists have actively discouraged practitioners from performing model checking because it does not fit into their framework. © 2012 The British Psychological Society.
Relaxation property of the fractional Brownian particle
International Nuclear Information System (INIS)
Wang Litan; Lung, C.W.
1988-08-01
Dynamic susceptibility of a diffusion system associated with the fractional Brownian motion (fBm) was examined for the fractal property of the Non-Debye relaxation process. The comparisons between fBm and other approaches were made. Anomalous diffusion and the Non-Debye relaxation processes were discussed with this approach. (author). 8 refs, 1 fig
Lifshitz quasinormal modes and relaxation from holography
Sybesma, Watse|info:eu-repo/dai/nl/369283074; Vandoren, Stefan|info:eu-repo/dai/nl/304830739
2015-01-01
We obtain relaxation times for field theories with Lifshitz scaling and with holographic duals Einstein-Maxwell-Dilaton gravity theories. This is done by computing quasinormal modes of a bulk scalar field in the presence of Lifshitz black branes. We determine the relation between relaxation time and
Superparamagnetic relaxation of weakly interacting particles
DEFF Research Database (Denmark)
Mørup, Steen; Tronc, Elisabeth
1994-01-01
The influence of particle interactions on the superparamagnetic relaxation time has been studied by Mossbauer spectroscopy in samples of maghemite (gamma-Fe2O3) particles with different particle sizes and particle separations. It is found that the relaxation time decreases with decreasing particl...
Models of Flux Tubes from Constrained Relaxation
Indian Academy of Sciences (India)
tribpo
J. Astrophys. Astr. (2000) 21, 299 302. Models of Flux Tubes from Constrained Relaxation. Α. Mangalam* & V. Krishan†, Indian Institute of Astrophysics, Koramangala,. Bangalore 560 034, India. *e mail: mangalam @ iiap. ernet. in. † e mail: vinod@iiap.ernet.in. Abstract. We study the relaxation of a compressible plasma to ...
Superparamagnetic relaxation in alpha-Fe particles
DEFF Research Database (Denmark)
Bødker, Franz; Mørup, Steen; Pedersen, Michael Stanley
1998-01-01
The superparamagnetic relaxation time of carbon-supported alpha-Fe particles with an average size of 3.0 Mm has been studied over a large temperature range by the use of Mossbauer spectroscopy combined with AC and DC magnetization measurements. It is found that the relaxation time varies...
Baryogenesis via Elementary Goldstone Higgs Relaxation
DEFF Research Database (Denmark)
Gertov, Helene; Pearce, Lauren; Sannino, Francesco
2016-01-01
We extend the relaxation mechanism to the Elementary Goldstone Higgs framework. Besides studying the allowed parameter space of the theory we add the minimal ingredients needed for the framework to be phenomenologically viable. The very nature of the extended Higgs sector allows to consider very ...... but radiatively generated, it is possible to generate the observed matter-antimatter asymmetry via the relaxation mechanism....
Stress relaxation under cyclic electron irradiation
International Nuclear Information System (INIS)
Bystrov, L.N.; Reznitskij, M.E.
1990-01-01
The kinetics of deformation process in a relaxating sample under 2 MeV electron cyclic irradiation was studied experimentally. The Al-Mg alloys with controllable and different (in dislocation density precipitate presence and their character) structure were used in experiments. It was established that after the beam was switched on the deformation rate increased sharply and then, during prolonged irradiation, in a gradual manner. After the switching-off the relaxation rate decreases by jumps up to values close to extrapolated rates of pre-radiation relaxation. The exhibition of these effects with radiation switching-off and switchin-on is dependent on the initial rate of thermal relaxation, the test temperature, the preliminary cold deformation and the dominating deformation dislocation mechanism. The preliminary cold deformation and test temperature elevation slightly decrease the effect of instantaneous relaxation acceleration with the irradiation switch-on. 17 refs., 5 figs
Anomalous enthalpy relaxation in vitreous silica
DEFF Research Database (Denmark)
Yue, Yuanzheng
2015-01-01
scans. It is known that the liquid fragility (i.e., the speed of the viscous slow-down of a supercooled liquid at its Tg during cooling) has impact on enthalpy relaxation in glass. Here, we find that vitreous silica (as a strong system) exhibits striking anomalies in both glass transition and enthalpy...... relaxation compared to fragile oxide systems. The anomalous enthalpy relaxation of vitreous silica is discovered by performing the hyperquenching-annealing-calorimetry experiments. We argue that the strong systems like vitreous silica and vitreous Germania relax in a structurally cooperative manner, whereas...... the fragile ones do in a structurally independent fashion. We discuss the origin of the anomalous enthalpy relaxation in the HQ vitreous silica....
Cross-relaxation solid state lasers
International Nuclear Information System (INIS)
Antipenko, B.M.
1989-01-01
Cross-relaxation functional diagrams provide a high quantum efficiency for pumping bands of solid state laser media and a low waste heat. A large number of the cross-relaxation mechanisms for decay rare earth excited states in crystals have been investigated. These investigations have been a starting-point for development of the cross-relaxation solid state lasers. For example, the cross-relaxation interactions, have been used for the laser action development of LiYF 4 :Gd-Tb. These interactions are important elements of the functional diagrams of the 2 μm Ho-doped media sensitized with Er and Tm and the 3 μm Er-doped media. Recently, new efficient 2 μm laser media with cross-relaxation pumping diagrams have been developed. Physical aspects of these media are the subject of this paper. A new concept of the Er-doped medium, sensitized with Yb, is illustrated
Effect of the Magnus force on skyrmion relaxation dynamics
Brown, Barton L.; Täuber, Uwe C.; Pleimling, Michel
2018-01-01
We perform systematic Langevin molecular dynamics simulations of interacting skyrmions in thin films. The interplay between the Magnus force, the repulsive skyrmion-skyrmion interaction, and the thermal noise yields different regimes during nonequilibrium relaxation. In the noise-dominated regime, the Magnus force enhances the disordering effects of the thermal noise. In the Magnus-force-dominated regime, the Magnus force cooperates with the skyrmion-skyrmion interaction to yield a dynamic regime with slow decaying correlations. These two regimes are characterized by different values of the aging exponent. In general, the Magnus force accelerates the approach to the steady state.
EXONEST: The Bayesian Exoplanetary Explorer
Directory of Open Access Journals (Sweden)
Kevin H. Knuth
2017-10-01
Full Text Available The fields of astronomy and astrophysics are currently engaged in an unprecedented era of discovery as recent missions have revealed thousands of exoplanets orbiting other stars. While the Kepler Space Telescope mission has enabled most of these exoplanets to be detected by identifying transiting events, exoplanets often exhibit additional photometric effects that can be used to improve the characterization of exoplanets. The EXONEST Exoplanetary Explorer is a Bayesian exoplanet inference engine based on nested sampling and originally designed to analyze archived Kepler Space Telescope and CoRoT (Convection Rotation et Transits planétaires exoplanet mission data. We discuss the EXONEST software package and describe how it accommodates plug-and-play models of exoplanet-associated photometric effects for the purpose of exoplanet detection, characterization and scientific hypothesis testing. The current suite of models allows for both circular and eccentric orbits in conjunction with photometric effects, such as the primary transit and secondary eclipse, reflected light, thermal emissions, ellipsoidal variations, Doppler beaming and superrotation. We discuss our new efforts to expand the capabilities of the software to include more subtle photometric effects involving reflected and refracted light. We discuss the EXONEST inference engine design and introduce our plans to port the current MATLAB-based EXONEST software package over to the next generation Exoplanetary Explorer, which will be a Python-based open source project with the capability to employ third-party plug-and-play models of exoplanet-related photometric effects.
Maximum entropy and Bayesian methods
International Nuclear Information System (INIS)
Smith, C.R.; Erickson, G.J.; Neudorfer, P.O.
1992-01-01
Bayesian probability theory and Maximum Entropy methods are at the core of a new view of scientific inference. These 'new' ideas, along with the revolution in computational methods afforded by modern computers allow astronomers, electrical engineers, image processors of any type, NMR chemists and physicists, and anyone at all who has to deal with incomplete and noisy data, to take advantage of methods that, in the past, have been applied only in some areas of theoretical physics. The title workshops have been the focus of a group of researchers from many different fields, and this diversity is evident in this book. There are tutorial and theoretical papers, and applications in a very wide variety of fields. Almost any instance of dealing with incomplete and noisy data can be usefully treated by these methods, and many areas of theoretical research are being enhanced by the thoughtful application of Bayes' theorem. Contributions contained in this volume present a state-of-the-art overview that will be influential and useful for many years to come
Magnetic Resonance Fingerprinting with short relaxation intervals.
Amthor, Thomas; Doneva, Mariya; Koken, Peter; Sommer, Karsten; Meineke, Jakob; Börnert, Peter
2017-09-01
The aim of this study was to investigate a technique for improving the performance of Magnetic Resonance Fingerprinting (MRF) in repetitive sampling schemes, in particular for 3D MRF acquisition, by shortening relaxation intervals between MRF pulse train repetitions. A calculation method for MRF dictionaries adapted to short relaxation intervals and non-relaxed initial spin states is presented, based on the concept of stationary fingerprints. The method is applicable to many different k-space sampling schemes in 2D and 3D. For accuracy analysis, T 1 and T 2 values of a phantom are determined by single-slice Cartesian MRF for different relaxation intervals and are compared with quantitative reference measurements. The relevance of slice profile effects is also investigated in this case. To further illustrate the capabilities of the method, an application to in-vivo spiral 3D MRF measurements is demonstrated. The proposed computation method enables accurate parameter estimation even for the shortest relaxation intervals, as investigated for different sampling patterns in 2D and 3D. In 2D Cartesian measurements, we achieved a scan acceleration of more than a factor of two, while maintaining acceptable accuracy: The largest T 1 values of a sample set deviated from their reference values by 0.3% (longest relaxation interval) and 2.4% (shortest relaxation interval). The largest T 2 values showed systematic deviations of up to 10% for all relaxation intervals, which is discussed. The influence of slice profile effects for multislice acquisition is shown to become increasingly relevant for short relaxation intervals. In 3D spiral measurements, a scan time reduction of 36% was achieved, maintaining the quality of in-vivo T1 and T2 maps. Reducing the relaxation interval between MRF sequence repetitions using stationary fingerprint dictionaries is a feasible method to improve the scan efficiency of MRF sequences. The method enables fast implementations of 3D spatially
Inverse problems in the Bayesian framework
International Nuclear Information System (INIS)
Calvetti, Daniela; Somersalo, Erkki; Kaipio, Jari P
2014-01-01
The history of Bayesian methods dates back to the original works of Reverend Thomas Bayes and Pierre-Simon Laplace: the former laid down some of the basic principles on inverse probability in his classic article ‘An essay towards solving a problem in the doctrine of chances’ that was read posthumously in the Royal Society in 1763. Laplace, on the other hand, in his ‘Memoirs on inverse probability’ of 1774 developed the idea of updating beliefs and wrote down the celebrated Bayes’ formula in the form we know today. Although not identified yet as a framework for investigating inverse problems, Laplace used the formalism very much in the spirit it is used today in the context of inverse problems, e.g., in his study of the distribution of comets. With the evolution of computational tools, Bayesian methods have become increasingly popular in all fields of human knowledge in which conclusions need to be drawn based on incomplete and noisy data. Needless to say, inverse problems, almost by definition, fall into this category. Systematic work for developing a Bayesian inverse problem framework can arguably be traced back to the 1980s, (the original first edition being published by Elsevier in 1987), although articles on Bayesian methodology applied to inverse problems, in particular in geophysics, had appeared much earlier. Today, as testified by the articles in this special issue, the Bayesian methodology as a framework for considering inverse problems has gained a lot of popularity, and it has integrated very successfully with many traditional inverse problems ideas and techniques, providing novel ways to interpret and implement traditional procedures in numerical analysis, computational statistics, signal analysis and data assimilation. The range of applications where the Bayesian framework has been fundamental goes from geophysics, engineering and imaging to astronomy, life sciences and economy, and continues to grow. There is no question that Bayesian
Vibrational relaxation and energy transfer of matrix isolated HCl and DCl
Energy Technology Data Exchange (ETDEWEB)
Wiesenfeld, J.M.
1977-12-01
Vibrational kinetic and spectroscopic studies have been performed on matrix-isolated HCl and DCl between 9 and 20 K. Vibrational relaxation rates for v = 2 and v = 1 were measured by a tunable infrared laser-induced, time-resolved fluorescence technique. In an Ar matrix, vibrational decay times are faster than radiative and it is found that HCl relaxes about 35 times more rapidly than CCl, in spite of the fact that HCl must transfer more energy to the lattice than DCl. This result is explained by postulating that the rate-determining step for vibrational relaxation produces a highly rotationally excited guest in a V yield R step; rotational relaxation into lattice phonons follows rapidly. HCl v = 1, but not v = 2, excitation rapidly diffuses through the sample by a resonant dipole-dipole vibrational energy transfer process. Molecular complexes, and in particular the HCl dimer, relax too rapidly for direct observation, less than or approximately 1 ..mu..s, and act as energy sinks in the energy diffusion process. The temperature dependence for all these processes is weak--less than a factor of two between 9 and 20 K. Vibrational relaxation of HCl in N/sub 2/ and O/sub 2/ matrices is unobservable, presumably due to rapid V yield V transfer to the host. A V yield R binary collision model for relaxation in solids is successful in explaining the HCl(DCl)/Ar results as well as results of other experimenters. The model considers relaxation to be the result of ''collisions'' due to molecular motion in quantized lattice normal modes--gas phase potential parameters can fit the matrix kinetic data.
Vibrational relaxation and energy transfer of matrix isolated HCl and DCl
International Nuclear Information System (INIS)
Wiesenfeld, J.M.
1977-12-01
Vibrational kinetic and spectroscopic studies have been performed on matrix-isolated HCl and DCl between 9 and 20 K. Vibrational relaxation rates for v = 2 and v = 1 were measured by a tunable infrared laser-induced, time-resolved fluorescence technique. In an Ar matrix, vibrational decay times are faster than radiative and it is found that HCl relaxes about 35 times more rapidly than CCl, in spite of the fact that HCl must transfer more energy to the lattice than DCl. This result is explained by postulating that the rate-determining step for vibrational relaxation produces a highly rotationally excited guest in a V yield R step; rotational relaxation into lattice phonons follows rapidly. HCl v = 1, but not v = 2, excitation rapidly diffuses through the sample by a resonant dipole-dipole vibrational energy transfer process. Molecular complexes, and in particular the HCl dimer, relax too rapidly for direct observation, less than or approximately 1 μs, and act as energy sinks in the energy diffusion process. The temperature dependence for all these processes is weak--less than a factor of two between 9 and 20 K. Vibrational relaxation of HCl in N 2 and O 2 matrices is unobservable, presumably due to rapid V yield V transfer to the host. A V yield R binary collision model for relaxation in solids is successful in explaining the HCl(DCl)/Ar results as well as results of other experimenters. The model considers relaxation to be the result of ''collisions'' due to molecular motion in quantized lattice normal modes--gas phase potential parameters can fit the matrix kinetic data
Brownian relaxation of an inelastic sphere in air
Energy Technology Data Exchange (ETDEWEB)
Bird, G. A., E-mail: gab@gab.com.au [University of Sydney, Sydney, NSW 2006 (Australia)
2016-06-15
The procedures that are used to calculate the forces and moments on an aerodynamic body in the rarefied gas of the upper atmosphere are applied to a small sphere of the size of an aerosol particle at sea level. While the gas-surface interaction model that provides accurate results for macroscopic bodies may not be appropriate for bodies that are comprised of only about a thousand atoms, it provides a limiting case that is more realistic than the elastic model. The paper concentrates on the transfer of energy from the air to an initially stationary sphere as it acquires Brownian motion. Individual particle trajectories vary wildly, but a clear relaxation process emerges from an ensemble average over tens of thousands of trajectories. The translational and rotational energies in equilibrium Brownian motion are determined. Empirical relationships are obtained for the mean translational and rotational relaxation times, the mean initial power input to the particle, the mean rates of energy transfer between the particle and air, and the diffusivity. These relationships are functions of the ratio of the particle mass to an average air molecule mass and the Knudsen number, which is the ratio of the mean free path in the air to the particle diameter. The ratio of the molecular radius to the particle radius also enters as a correction factor. The implications of Brownian relaxation for the second law of thermodynamics are discussed.
Automated NMR relaxation dispersion data analysis using NESSY
Directory of Open Access Journals (Sweden)
Gooley Paul R
2011-10-01
Full Text Available Abstract Background Proteins are dynamic molecules with motions ranging from picoseconds to longer than seconds. Many protein functions, however, appear to occur on the micro to millisecond timescale and therefore there has been intense research of the importance of these motions in catalysis and molecular interactions. Nuclear Magnetic Resonance (NMR relaxation dispersion experiments are used to measure motion of discrete nuclei within the micro to millisecond timescale. Information about conformational/chemical exchange, populations of exchanging states and chemical shift differences are extracted from these experiments. To ensure these parameters are correctly extracted, accurate and careful analysis of these experiments is necessary. Results The software introduced in this article is designed for the automatic analysis of relaxation dispersion data and the extraction of the parameters mentioned above. It is written in Python for multi platform use and highest performance. Experimental data can be fitted to different models using the Levenberg-Marquardt minimization algorithm and different statistical tests can be used to select the best model. To demonstrate the functionality of this program, synthetic data as well as NMR data were analyzed. Analysis of these data including the generation of plots and color coded structures can be performed with minimal user intervention and using standard procedures that are included in the program. Conclusions NESSY is easy to use open source software to analyze NMR relaxation data. The robustness and standard procedures are demonstrated in this article.
Sedative and muscle relaxant activities of diterpenoids from Phlomidoschema parviflorum
Directory of Open Access Journals (Sweden)
Abdur Rauf
Full Text Available Abstract Phlomidoschema parviflorum (Benth. Vved. (Basionym: Stachys parviflora Benth. Lamiaceae, have significance medicinal importance as it is used in number of health disorders including diarrhea, fever, sore mouth and throat, internal bleeding, weaknesses of the liver and heart genital tumors, sclerosis of the spleen, inflammatory tumors and cancerous ulcers. The present contribution deals with the sedative and muscle relaxant like effects of diterpenoids trivially named stachysrosane and stachysrosane, isolated from the ethyl acetate soluble fraction of P. parviflorum. Both compounds (at 5, 10 and 15 mg/kg, i.p were assessed for their in vivo sedative and muscle relaxant activity in open field and inclined plane test, respectively. The geometries of both compounds were optimized with density functional theory. The molecular docking of both compounds were performed with receptor gamma aminobutyric acid. Both compounds showed marked activity in a dose dependent manner. The docking studies showed that both compounds interact strongly with important residues in receptor gamma aminobutyric acid. The reported data demonstrate that both compounds exhibited significant sedative and muscle relaxant-like effects in animal models, which opens a door for novel therapeutic applications.
Relaxation and physical aging in network glasses: a review.
Micoulaut, Matthieu
2016-06-01
Recent progress in the description of glassy relaxation and aging are reviewed for the wide class of network-forming materials such as GeO2, Ge x Se1-x , silicates (SiO2-Na2O) or borates (B2O3-Li2O), all of which have an important usefulness in domestic, geological or optoelectronic applications. A brief introduction of the glass transition phenomenology is given, together with the salient features that are revealed both from theory and experiments. Standard experimental methods used for the characterization of the slowing down of the dynamics are reviewed. We then discuss the important role played by aspects of network topology and rigidity for the understanding of the relaxation of the glass transition, while also permitting analytical predictions of glass properties from simple and insightful models based on the network structure. We also emphasize the great utility of computer simulations which probe the dynamics at the molecular level, and permit the calculation of various structure-related functions in connection with glassy relaxation and the physics of aging which reveal the non-equilibrium nature of glasses. We discuss the notion of spatial variations of structure which leads to the concept of 'dynamic heterogeneities', and recent results in relation to this important topic for network glasses are also reviewed.
Excitation relaxation and structure of TPPS4 J-aggregates
International Nuclear Information System (INIS)
Kelbauskas, L.; Bagdonas, S.; Dietel, W.; Rotomskis, R.
2003-01-01
The energy relaxation kinetics and the structure of the J-aggregates of water-soluble porphyrin 5,10,15,20-tetrasulphonatophenyl porphine (TPPS 4 ) were investigated in aqueous medium by means of time-resolved fluorescence spectroscopy and confocal laser-scanning fluorescence microscopy. The excitation of the J-aggregates, at excitation intensities higher than ∼10 15 photons/cm 2 per pulse, results in a remarkable decrease of the fluorescence quantum yield and in the appearance of an additional, non-exponential energy relaxation channel with a decay constant that depends on the excitation intensity. This relaxation mechanism was attributed to the exciton single-singlet annihilation. The exciton lifetime in the absence of the annihilation was calculated to be ∼150 ps. Using exciton annihilation theory, the exciton migration within the J-aggregates could be characterized by determining the exciton diffusion constant (1.8±0.9) 10 -3 cm 2 /s and the hopping time (1.2±0.6) ps. Using the experimental data, the size of the J-aggregate could be evaluated and was seen to yield at least 20 TPPS 4 molecules per aggregate. It was shown by means of confocal fluorescence laser scanning microscopy that TPPS 4 does self-associate in polyvinyl alcohol (PVA) at acidic pH forming molecular macro-assemblies on a scale of ∼1 μm in PVA matrices
Bayesian quantification of thermodynamic uncertainties in dense gas flows
International Nuclear Information System (INIS)
Merle, X.; Cinnella, P.
2015-01-01
A Bayesian inference methodology is developed for calibrating complex equations of state used in numerical fluid flow solvers. Precisely, the input parameters of three equations of state commonly used for modeling the thermodynamic behavior of the so-called dense gas flows, – i.e. flows of gases characterized by high molecular weights and complex molecules, working in thermodynamic conditions close to the liquid–vapor saturation curve – are calibrated by means of Bayesian inference from reference aerodynamic data for a dense gas flow over a wing section. Flow thermodynamic conditions are such that the gas thermodynamic behavior strongly deviates from that of a perfect gas. In the aim of assessing the proposed methodology, synthetic calibration data – specifically, wall pressure data – are generated by running the numerical solver with a more complex and accurate thermodynamic model. The statistical model used to build the likelihood function includes a model-form inadequacy term, accounting for the gap between the model output associated to the best-fit parameters and the true phenomenon. Results show that, for all of the relatively simple models under investigation, calibrations lead to informative posterior probability density distributions of the input parameters and improve the predictive distribution significantly. Nevertheless, calibrated parameters strongly differ from their expected physical values. The relationship between this behavior and model-form inadequacy is discussed. - Highlights: • Development of a Bayesian inference procedure for calibrating dense-gas flow solvers. • Complex thermodynamic models calibrated by using aerodynamic data for the flow. • Preliminary Sobol analysis used to reduce parameter space. • Piecewise polynomial surrogate model constructed to reduce computational cost. • Calibration results show the crucial role played by model-form inadequacies
Relaxing a large cosmological constant
International Nuclear Information System (INIS)
Bauer, Florian; Sola, Joan; Stefancic, Hrvoje
2009-01-01
The cosmological constant (CC) problem is the biggest enigma of theoretical physics ever. In recent times, it has been rephrased as the dark energy (DE) problem in order to encompass a wider spectrum of possibilities. It is, in any case, a polyhedric puzzle with many faces, including the cosmic coincidence problem, i.e. why the density of matter ρ m is presently so close to the CC density ρ Λ . However, the oldest, toughest and most intriguing face of this polyhedron is the big CC problem, namely why the measured value of ρ Λ at present is so small as compared to any typical density scale existing in high energy physics, especially taking into account the many phase transitions that our Universe has undergone since the early times, including inflation. In this Letter, we propose to extend the field equations of General Relativity by including a class of invariant terms that automatically relax the value of the CC irrespective of the initial size of the vacuum energy in the early epochs. We show that, at late times, the Universe enters an eternal de Sitter stage mimicking a tiny positive cosmological constant. Thus, these models could be able to solve the big CC problem without fine-tuning and have also a bearing on the cosmic coincidence problem. Remarkably, they mimic the ΛCDM model to a large extent, but they still leave some characteristic imprints that should be testable in the next generation of experiments.
Hashim, Hairul Anuar; Hanafi Ahmad Yusof, Hazwani
2011-06-01
This study was designed to compare the effects of two different relaxation techniques, namely progressive muscle relaxation (PMR) and autogenic relaxation (AGR) on moods of young soccer players. sixteen adolescent athletes (mean age: 14.1 ± 1.3) received either PMR or AGR training. Using Profile of Mood States- Adolescents, their mood states were measured one week before relaxation training, before the first relaxation session, and after the twelfth relaxation session. Mixed ANOVA revealed no significant interaction effects and no significant main effects in any of the subscales. However, significant main effects for testing sessions were found for confusion, depression, fatigue, and tension subscales. Post hoc tests revealed post-intervention reductions in the confusion, depression, fatigue, and tension subscale scores. These two relaxation techniques induce equivalent mood responses and may be used to regulate young soccer players' mood states.
Hashim, Hairul Anuar; Hanafi@Ahmad Yusof, Hazwani
2011-01-01
Purpose This study was designed to compare the effects of two different relaxation techniques, namely progressive muscle relaxation (PMR) and autogenic relaxation (AGR) on moods of young soccer players. Methods Sixteen adolescent athletes (mean age: 14.1 ± 1.3) received either PMR or AGR training. Using Profile of Mood States- Adolescents, their mood states were measured one week before relaxation training, before the first relaxation session, and after the twelfth relaxation session. Results Mixed ANOVA revealed no significant interaction effects and no significant main effects in any of the subscales. However, significant main effects for testing sessions were found for confusion, depression, fatigue, and tension subscales. Post hoc tests revealed post-intervention reductions in the confusion, depression, fatigue, and tension subscale scores. Conclusion These two relaxation techniques induce equivalent mood responses and may be used to regulate young soccer players’ mood states. PMID:22375225
Gunji, Yukio-Pegio; Shinohara, Shuji; Haruna, Taichi; Basios, Vasileios
2017-02-01
To overcome the dualism between mind and matter and to implement consciousness in science, a physical entity has to be embedded with a measurement process. Although quantum mechanics have been regarded as a candidate for implementing consciousness, nature at its macroscopic level is inconsistent with quantum mechanics. We propose a measurement-oriented inference system comprising Bayesian and inverse Bayesian inferences. While Bayesian inference contracts probability space, the newly defined inverse one relaxes the space. These two inferences allow an agent to make a decision corresponding to an immediate change in their environment. They generate a particular pattern of joint probability for data and hypotheses, comprising multiple diagonal and noisy matrices. This is expressed as a nondistributive orthomodular lattice equivalent to quantum logic. We also show that an orthomodular lattice can reveal information generated by inverse syllogism as well as the solutions to the frame and symbol-grounding problems. Our model is the first to connect macroscopic cognitive processes with the mathematical structure of quantum mechanics with no additional assumptions. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
Energy Technology Data Exchange (ETDEWEB)
Weise, K.
2004-06-01
Recent metrological developments concerning measurement uncertainty, founded on Bayesian statistics, give rise to a revision of several parts of the DIN 25482 and ISO 11929 standard series. These series stipulate detection limits and decision thresholds for ionizing-radiation measurements. Part 3 and, respectively, part 4 of them deal with measurements by use of linear-scale analogue ratemeters. A normal frequency distribution of the momentary ratemeter indication for a fixed count rate value is assumed. The actual distribution, which is first calculated numerically by solving an integral equation, differs, however, considerably from the normal distribution although this one represents an approximation of it for sufficiently large values of the count rate to be measured. As is shown, this similarly holds true for the Bayesian probability distribution of the count rate for sufficiently large given measured values indicated by the ratemeter. This distribution follows from the first one mentioned by means of the Bayes theorem. Its expectation value and variance are needed for the standards to be revised on the basis of Bayesian statistics. Simple expressions are given by the present standards for estimating these parameters and for calculating the detection limit and the decision threshold. As is also shown, the same expressions can similarly be used as sufficient approximations by the revised standards if, roughly, the present indicated value exceeds the reciprocal ratemeter relaxation time constant. (orig.)
Electron spin relaxation can enhance the performance of a cryptochrome-based magnetic compass sensor
DEFF Research Database (Denmark)
Kattnig, Daniel R; Sowa, Jakub K; Solov'yov, Ilia A
2016-01-01
thaliana cryptochrome 1 were obtained from molecular dynamics (MD) simulations and used to calculate the spin relaxation caused by modulation of the exchange and dipolar interactions. We find that intermediate spin relaxation rates afford substantial enhancements in the sensitivity of the reaction yields....... Here we argue that certain spin relaxation mechanisms can enhance its performance. We focus on the flavin-tryptophan radical pair in cryptochrome, currently the only candidate magnetoreceptor molecule. Correlation functions for fluctuations in the distance between the two radicals in Arabidopsis...... to an Earth-strength magnetic field. Supported by calculations using toy radical pair models, we argue that these enhancements could be consistent with the molecular dynamics and magnetic interactions in avian cryptochromes....
NMR relaxation induced by iron oxide particles: testing theoretical models.
Gossuin, Y; Orlando, T; Basini, M; Henrard, D; Lascialfari, A; Mattea, C; Stapf, S; Vuong, Q L
2016-04-15
Superparamagnetic iron oxide particles find their main application as contrast agents for cellular and molecular magnetic resonance imaging. The contrast they bring is due to the shortening of the transverse relaxation time T 2 of water protons. In order to understand their influence on proton relaxation, different theoretical relaxation models have been developed, each of them presenting a certain validity domain, which depends on the particle characteristics and proton dynamics. The validation of these models is crucial since they allow for predicting the ideal particle characteristics for obtaining the best contrast but also because the fitting of T 1 experimental data by the theory constitutes an interesting tool for the characterization of the nanoparticles. In this work, T 2 of suspensions of iron oxide particles in different solvents and at different temperatures, corresponding to different proton diffusion properties, were measured and were compared to the three main theoretical models (the motional averaging regime, the static dephasing regime, and the partial refocusing model) with good qualitative agreement. However, a real quantitative agreement was not observed, probably because of the complexity of these nanoparticulate systems. The Roch theory, developed in the motional averaging regime (MAR), was also successfully used to fit T 1 nuclear magnetic relaxation dispersion (NMRD) profiles, even outside the MAR validity range, and provided a good estimate of the particle size. On the other hand, the simultaneous fitting of T 1 and T 2 NMRD profiles by the theory was impossible, and this occurrence constitutes a clear limitation of the Roch model. Finally, the theory was shown to satisfactorily fit the deuterium T 1 NMRD profile of superparamagnetic particle suspensions in heavy water.
Bayesian analogy with relational transformations.
Lu, Hongjing; Chen, Dawn; Holyoak, Keith J
2012-07-01
How can humans acquire relational representations that enable analogical inference and other forms of high-level reasoning? Using comparative relations as a model domain, we explore the possibility that bottom-up learning mechanisms applied to objects coded as feature vectors can yield representations of relations sufficient to solve analogy problems. We introduce Bayesian analogy with relational transformations (BART) and apply the model to the task of learning first-order comparative relations (e.g., larger, smaller, fiercer, meeker) from a set of animal pairs. Inputs are coded by vectors of continuous-valued features, based either on human magnitude ratings, normed feature ratings (De Deyne et al., 2008), or outputs of the topics model (Griffiths, Steyvers, & Tenenbaum, 2007). Bootstrapping from empirical priors, the model is able to induce first-order relations represented as probabilistic weight distributions, even when given positive examples only. These learned representations allow classification of novel instantiations of the relations and yield a symbolic distance effect of the sort obtained with both humans and other primates. BART then transforms its learned weight distributions by importance-guided mapping, thereby placing distinct dimensions into correspondence. These transformed representations allow BART to reliably solve 4-term analogies (e.g., larger:smaller::fiercer:meeker), a type of reasoning that is arguably specific to humans. Our results provide a proof-of-concept that structured analogies can be solved with representations induced from unstructured feature vectors by mechanisms that operate in a largely bottom-up fashion. We discuss potential implications for algorithmic and neural models of relational thinking, as well as for the evolution of abstract thought. Copyright 2012 APA, all rights reserved.
Bayesian tomographic reconstruction of microsystems
International Nuclear Information System (INIS)
Salem, Sofia Fekih; Vabre, Alexandre; Mohammad-Djafari, Ali
2007-01-01
The microtomography by X ray transmission plays an increasingly dominating role in the study and the understanding of microsystems. Within this framework, an experimental setup of high resolution X ray microtomography was developed at CEA-List to quantify the physical parameters related to the fluids flow in microsystems. Several difficulties rise from the nature of experimental data collected on this setup: enhanced error measurements due to various physical phenomena occurring during the image formation (diffusion, beam hardening), and specificities of the setup (limited angle, partial view of the object, weak contrast).To reconstruct the object we must solve an inverse problem. This inverse problem is known to be ill-posed. It therefore needs to be regularized by introducing prior information. The main prior information we account for is that the object is composed of a finite known number of different materials distributed in compact regions. This a priori information is introduced via a Gauss-Markov field for the contrast distributions with a hidden Potts-Markov field for the class materials in the Bayesian estimation framework. The computations are done by using an appropriate Markov Chain Monte Carlo (MCMC) technique.In this paper, we present first the basic steps of the proposed algorithms. Then we focus on one of the main steps in any iterative reconstruction method which is the computation of forward and adjoint operators (projection and backprojection). A fast implementation of these two operators is crucial for the real application of the method. We give some details on the fast computation of these steps and show some preliminary results of simulations
MAP estimators and their consistency in Bayesian nonparametric inverse problems
Dashti, M.
2013-09-01
We consider the inverse problem of estimating an unknown function u from noisy measurements y of a known, possibly nonlinear, map applied to u. We adopt a Bayesian approach to the problem and work in a setting where the prior measure is specified as a Gaussian random field μ0. We work under a natural set of conditions on the likelihood which implies the existence of a well-posed posterior measure, μy. Under these conditions, we show that the maximum a posteriori (MAP) estimator is well defined as the minimizer of an Onsager-Machlup functional defined on the Cameron-Martin space of the prior; thus, we link a problem in probability with a problem in the calculus of variations. We then consider the case where the observational noise vanishes and establish a form of Bayesian posterior consistency for the MAP estimator. We also prove a similar result for the case where the observation of can be repeated as many times as desired with independent identically distributed noise. The theory is illustrated with examples from an inverse problem for the Navier-Stokes equation, motivated by problems arising in weather forecasting, and from the theory of conditioned diffusions, motivated by problems arising in molecular dynamics. © 2013 IOP Publishing Ltd.
MAP estimators and their consistency in Bayesian nonparametric inverse problems
International Nuclear Information System (INIS)
Dashti, M; Law, K J H; Stuart, A M; Voss, J
2013-01-01
We consider the inverse problem of estimating an unknown function u from noisy measurements y of a known, possibly nonlinear, map G applied to u. We adopt a Bayesian approach to the problem and work in a setting where the prior measure is specified as a Gaussian random field μ 0 . We work under a natural set of conditions on the likelihood which implies the existence of a well-posed posterior measure, μ y . Under these conditions, we show that the maximum a posteriori (MAP) estimator is well defined as the minimizer of an Onsager–Machlup functional defined on the Cameron–Martin space of the prior; thus, we link a problem in probability with a problem in the calculus of variations. We then consider the case where the observational noise vanishes and establish a form of Bayesian posterior consistency for the MAP estimator. We also prove a similar result for the case where the observation of G(u) can be repeated as many times as desired with independent identically distributed noise. The theory is illustrated with examples from an inverse problem for the Navier–Stokes equation, motivated by problems arising in weather forecasting, and from the theory of conditioned diffusions, motivated by problems arising in molecular dynamics. (paper)
Bayesian assignment of gene ontology terms to gene expression experiments.
Sykacek, P
2012-09-15
Gene expression assays allow for genome scale analyses of molecular biological mechanisms. State-of-the-art data analysis provides lists of involved genes, either by calculating significance levels of mRNA abundance or by Bayesian assessments of gene activity. A common problem of such approaches is the difficulty of interpreting the biological implication of the resulting gene lists. This lead to an increased interest in methods for inferring high-level biological information. A common approach for representing high level information is by inferring gene ontology (GO) terms which may be attributed to the expression data experiment. This article proposes a probabilistic model for GO term inference. Modelling assumes that gene annotations to GO terms are available and gene involvement in an experiment is represented by a posterior probabilities over gene-specific indicator variables. Such probability measures result from many Bayesian approaches for expression data analysis. The proposed model combines these indicator probabilities in a probabilistic fashion and provides a probabilistic GO term assignment as a result. Experiments on synthetic and microarray data suggest that advantages of the proposed probabilistic GO term inference over statistical test-based approaches are in particular evident for sparsely annotated GO terms and in situations of large uncertainty about gene activity. Provided that appropriate annotations exist, the proposed approach is easily applied to inferring other high level assignments like pathways. Source code under GPL license is available from the author. peter.sykacek@boku.ac.at.
Bayesian assignment of gene ontology terms to gene expression experiments
Sykacek, P.
2012-01-01
Motivation: Gene expression assays allow for genome scale analyses of molecular biological mechanisms. State-of-the-art data analysis provides lists of involved genes, either by calculating significance levels of mRNA abundance or by Bayesian assessments of gene activity. A common problem of such approaches is the difficulty of interpreting the biological implication of the resulting gene lists. This lead to an increased interest in methods for inferring high-level biological information. A common approach for representing high level information is by inferring gene ontology (GO) terms which may be attributed to the expression data experiment. Results: This article proposes a probabilistic model for GO term inference. Modelling assumes that gene annotations to GO terms are available and gene involvement in an experiment is represented by a posterior probabilities over gene-specific indicator variables. Such probability measures result from many Bayesian approaches for expression data analysis. The proposed model combines these indicator probabilities in a probabilistic fashion and provides a probabilistic GO term assignment as a result. Experiments on synthetic and microarray data suggest that advantages of the proposed probabilistic GO term inference over statistical test-based approaches are in particular evident for sparsely annotated GO terms and in situations of large uncertainty about gene activity. Provided that appropriate annotations exist, the proposed approach is easily applied to inferring other high level assignments like pathways. Availability: Source code under GPL license is available from the author. Contact: peter.sykacek@boku.ac.at PMID:22962488
Superradiance from crystals of molecular nanomagnets.
Chudnovsky, E M; Garanin, D A
2002-10-07
We show that crystals of molecular nanomagnets can exhibit giant magnetic relaxation due to the Dicke superradiance of electromagnetic waves. Rigorous theory is presented that combines superradiance with the Landau-Zener effect.
Non-parametric Bayesian networks: Improving theory and reviewing applications
International Nuclear Information System (INIS)
Hanea, Anca; Morales Napoles, Oswaldo; Ababei, Dan
2015-01-01
Applications in various domains often lead to high dimensional dependence modelling. A Bayesian network (BN) is a probabilistic graphical model that provides an elegant way of expressing the joint distribution of a large number of interrelated variables. BNs have been successfully used to represent uncertain knowledge in a variety of fields. The majority of applications use discrete BNs, i.e. BNs whose nodes represent discrete variables. Integrating continuous variables in BNs is an area fraught with difficulty. Several methods that handle discrete-continuous BNs have been proposed in the literature. This paper concentrates only on one method called non-parametric BNs (NPBNs). NPBNs were introduced in 2004 and they have been or are currently being used in at least twelve professional applications. This paper provides a short introduction to NPBNs, a couple of theoretical advances, and an overview of applications. The aim of the paper is twofold: one is to present the latest improvements of the theory underlying NPBNs, and the other is to complement the existing overviews of BNs applications with the NPNBs applications. The latter opens the opportunity to discuss some difficulties that applications pose to the theoretical framework and in this way offers some NPBN modelling guidance to practitioners. - Highlights: • The paper gives an overview of the current NPBNs methodology. • We extend the NPBN methodology by relaxing the conditions of one of its fundamental theorems. • We propose improvements of the data mining algorithm for the NPBNs. • We review the professional applications of the NPBNs.
Relaxation of polarized nuclei in superconducting rhodium
DEFF Research Database (Denmark)
Knuuttila, T.A.; Tuoriniemi, J.T.; Lefmann, K.
2000-01-01
Nuclear spin lattice relaxation rates were measured in normal and superconducting (sc) rhodium with nuclear polarizations up to p = 0.55. This was sufficient to influence the sc state of Rh, whose T, and B-c, are exceptionally low. Because B-c ... is unchanged, the nuclear spin entropy was fully sustained across the sc transition. The relaxation in the sc state was slower at all temperatures without the coherence enhancement close to T-c. Nonzero nuclear polarization strongly reduced the difference between the relaxation rates in the sc and normal...
Spin relaxation in nanowires by hyperfine coupling
International Nuclear Information System (INIS)
Echeverria-Arrondo, C.; Sherman, E.Ya.
2012-01-01
Hyperfine interactions establish limits on spin dynamics and relaxation rates in ensembles of semiconductor quantum dots. It is the confinement of electrons which determines nonzero hyperfine coupling and leads to the spin relaxation. As a result, in nanowires one would expect the vanishing of this effect due to extended electron states. However, even for relatively clean wires, disorder plays a crucial role and makes electron localization sufficient to cause spin relaxation on the time scale of the order of 10 ns. (copyright 2012 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim) (orig.)
Le Chatelier's principle with multiple relaxation channels
Gilmore, R.; Levine, R. D.
1986-05-01
Le Chatelier's principle is discussed within the constrained variational approach to thermodynamics. The formulation is general enough to encompass systems not in thermal (or chemical) equilibrium. Particular attention is given to systems with multiple constraints which can be relaxed. The moderation of the initial perturbation increases as additional constraints are removed. This result is studied in particular when the (coupled) relaxation channels have widely different time scales. A series of inequalities is derived which describes the successive moderation as each successive relaxation channel opens up. These inequalities are interpreted within the metric-geometry representation of thermodynamics.
Collisional relaxation of electron tail distribution
International Nuclear Information System (INIS)
Yamagiwa, Mitsuru; Okamoto, Masao.
1985-05-01
Relaxation due to the Coulomb collisions of the electron velocity distribution function with a high energy tail is investigated in detail. In the course of the relaxation, a 'saddle' point can be created in velocity space owing to upsilon -3 dependence of the deflection rate and a positive slope or a 'dip' appears in the tail direction. The time evolution of the electron tail is studied analytically. A comparison is made with numerical results by using a Fokker-Planck code. Also discussed is the kinetic instability concerned with the positive slope during the relaxation. (author)
Nuclear magnetic resonance relaxation in multiple sclerosis
DEFF Research Database (Denmark)
Larsson, H B; Barker, G J; MacKay, A
1998-01-01
OBJECTIVES: The theory of relaxation processes and their measurements are described. An overview is presented of the literature on relaxation time measurements in the normal and the developing brain, in experimental diseases in animals, and in patients with multiple sclerosis. RESULTS...... AND CONCLUSION: Relaxation time measurements provide insight into development of multiple sclerosis plaques, especially the occurrence of oedema, demyelination, and gliosis. There is also evidence that normal appearing white matter in patients with multiple sclerosis is affected. What is now needed are fast...
Stress Relaxation in Entangled Polymer Melts
DEFF Research Database (Denmark)
Hou, Ji-Xuan; Svaneborg, Carsten; Everaers, Ralf
2010-01-01
We present an extensive set of simulation results for the stress relaxation in equilibrium and step-strained bead-spring polymer melts. The data allow us to explore the chain dynamics and the shear relaxation modulus, G(t), into the plateau regime for chains with Z=40 entanglements...... and into the terminal relaxation regime for Z=10. Using the known (Rouse) mobility of unentangled chains and the melt entanglement length determined via the primitive path analysis of the microscopic topological state of our systems, we have performed parameter-free tests of several different tube models. We find...
Slow relaxation in weakly open rational polygons.
Kokshenev, Valery B; Vicentini, Eduardo
2003-07-01
The interplay between the regular (piecewise-linear) and irregular (vertex-angle) boundary effects in nonintegrable rational polygonal billiards (of m equal sides) is discussed. Decay dynamics in polygons (of perimeter P(m) and small opening Delta) is analyzed through the late-time survival probability S(m) approximately equal t(-delta). Two distinct slow relaxation channels are established. The primary universal channel exhibits relaxation of regular sliding orbits, with delta=1. The secondary channel is given by delta>1 and becomes open when m>P(m)/Delta. It originates from vertex order-disorder dual effects and is due to relaxation of chaoticlike excitations.
[A study on Korean concepts of relaxation].
Park, J S
1992-01-01
Relaxation technique is an independent nursing intervention used in various stressful situations. The concept of relaxation must be explored for the meaning given by the people in their traditional thought and philosophy. Korean relaxation technique, wanting to become culturally acceptable and effective, is learning to recognize and develop Korean concepts, experiences, and musics of relaxation. This study was aimed at discovering Korean concepts, experiences and musics of relaxation and contributing the development of the relaxation technique for Korean people. The subjects were 59 nursing students, 39 hospitalized patients, 61 housewives, 21 rural residents and 16 researchers. Data were collected from September 4th to October 24th, 1991 by interviews or questionnaires. The data analysis was done by qualitative research method, and validity assured by conformation of the concept and category by 2 nursing scientists who had written a Master's thesis on the relaxation technique. The results of the study were summarized as follows; 1. The meaning of the relaxation concept; From 298 statements, 107 concepts were extracted and then 5 categories "Physical domain", "Psychological domain", "Complex domain", "Situation", and "environment" were organized. 'Don't have discomforts, 'don't have muscle tension', 'don't have energy (him in Korean)', 'don't have activities' subcategories were included in "Physical domain". 'Don't have anxiety', 'feel good', 'emotional stability', 'don't have wordly thoughts', 'feel one's brain muddled', 'loss of desire' subcategories were included in "physical domain" 'Comfort body and mind', 'don't have tension of body and mind', 'be sagged' 'liveliness of thoughts' subcategories were included in "Complex domain". 'Rest', 'sleep', 'others' subcategories were included in "Situation domain". And 'quite environment' & 'comfortable environment' subcategories were included in "Environmental domain". 2. The experiences of the relaxation; From 151
Objective Bayesianism and the Maximum Entropy Principle
Directory of Open Access Journals (Sweden)
Jon Williamson
2013-09-01
Full Text Available Objective Bayesian epistemology invokes three norms: the strengths of our beliefs should be probabilities; they should be calibrated to our evidence of physical probabilities; and they should otherwise equivocate sufficiently between the basic propositions that we can express. The three norms are sometimes explicated by appealing to the maximum entropy principle, which says that a belief function should be a probability function, from all those that are calibrated to evidence, that has maximum entropy. However, the three norms of objective Bayesianism are usually justified in different ways. In this paper, we show that the three norms can all be subsumed under a single justification in terms of minimising worst-case expected loss. This, in turn, is equivalent to maximising a generalised notion of entropy. We suggest that requiring language invariance, in addition to minimising worst-case expected loss, motivates maximisation of standard entropy as opposed to maximisation of other instances of generalised entropy. Our argument also provides a qualified justification for updating degrees of belief by Bayesian conditionalisation. However, conditional probabilities play a less central part in the objective Bayesian account than they do under the subjective view of Bayesianism, leading to a reduced role for Bayes’ Theorem.
A default Bayesian hypothesis test for mediation.
Nuijten, Michèle B; Wetzels, Ruud; Matzke, Dora; Dolan, Conor V; Wagenmakers, Eric-Jan
2015-03-01
In order to quantify the relationship between multiple variables, researchers often carry out a mediation analysis. In such an analysis, a mediator (e.g., knowledge of a healthy diet) transmits the effect from an independent variable (e.g., classroom instruction on a healthy diet) to a dependent variable (e.g., consumption of fruits and vegetables). Almost all mediation analyses in psychology use frequentist estimation and hypothesis-testing techniques. A recent exception is Yuan and MacKinnon (Psychological Methods, 14, 301-322, 2009), who outlined a Bayesian parameter estimation procedure for mediation analysis. Here we complete the Bayesian alternative to frequentist mediation analysis by specifying a default Bayesian hypothesis test based on the Jeffreys-Zellner-Siow approach. We further extend this default Bayesian test by allowing a comparison to directional or one-sided alternatives, using Markov chain Monte Carlo techniques implemented in JAGS. All Bayesian tests are implemented in the R package BayesMed (Nuijten, Wetzels, Matzke, Dolan, & Wagenmakers, 2014).
Classifying emotion in Twitter using Bayesian network
Surya Asriadie, Muhammad; Syahrul Mubarok, Mohamad; Adiwijaya
2018-03-01
Language is used to express not only facts, but also emotions. Emotions are noticeable from behavior up to the social media statuses written by a person. Analysis of emotions in a text is done in a variety of media such as Twitter. This paper studies classification of emotions on twitter using Bayesian network because of its ability to model uncertainty and relationships between features. The result is two models based on Bayesian network which are Full Bayesian Network (FBN) and Bayesian Network with Mood Indicator (BNM). FBN is a massive Bayesian network where each word is treated as a node. The study shows the method used to train FBN is not very effective to create the best model and performs worse compared to Naive Bayes. F1-score for FBN is 53.71%, while for Naive Bayes is 54.07%. BNM is proposed as an alternative method which is based on the improvement of Multinomial Naive Bayes and has much lower computational complexity compared to FBN. Even though it’s not better compared to FBN, the resulting model successfully improves the performance of Multinomial Naive Bayes. F1-Score for Multinomial Naive Bayes model is 51.49%, while for BNM is 52.14%.
Empirical Bayesian inference and model uncertainty
International Nuclear Information System (INIS)
Poern, K.
1994-01-01
This paper presents a hierarchical or multistage empirical Bayesian approach for the estimation of uncertainty concerning the intensity of a homogeneous Poisson process. A class of contaminated gamma distributions is considered to describe the uncertainty concerning the intensity. These distributions in turn are defined through a set of secondary parameters, the knowledge of which is also described and updated via Bayes formula. This two-stage Bayesian approach is an example where the modeling uncertainty is treated in a comprehensive way. Each contaminated gamma distributions, represented by a point in the 3D space of secondary parameters, can be considered as a specific model of the uncertainty about the Poisson intensity. Then, by the empirical Bayesian method each individual model is assigned a posterior probability
Bayesian Inference Methods for Sparse Channel Estimation
DEFF Research Database (Denmark)
Pedersen, Niels Lovmand
2013-01-01
This thesis deals with sparse Bayesian learning (SBL) with application to radio channel estimation. As opposed to the classical approach for sparse signal representation, we focus on the problem of inferring complex signals. Our investigations within SBL constitute the basis for the development...... of Bayesian inference algorithms for sparse channel estimation. Sparse inference methods aim at finding the sparse representation of a signal given in some overcomplete dictionary of basis vectors. Within this context, one of our main contributions to the field of SBL is a hierarchical representation...... analysis of the complex prior representation, where we show that the ability to induce sparse estimates of a given prior heavily depends on the inference method used and, interestingly, whether real or complex variables are inferred. We also show that the Bayesian estimators derived from the proposed...
Bayesian Methods for Radiation Detection and Dosimetry
Groer, Peter G
2002-01-01
We performed work in three areas: radiation detection, external and internal radiation dosimetry. In radiation detection we developed Bayesian techniques to estimate the net activity of high and low activity radioactive samples. These techniques have the advantage that the remaining uncertainty about the net activity is described by probability densities. Graphs of the densities show the uncertainty in pictorial form. Figure 1 below demonstrates this point. We applied stochastic processes for a method to obtain Bayesian estimates of 222Rn-daughter products from observed counting rates. In external radiation dosimetry we studied and developed Bayesian methods to estimate radiation doses to an individual with radiation induced chromosome aberrations. We analyzed chromosome aberrations after exposure to gammas and neutrons and developed a method for dose-estimation after criticality accidents. The research in internal radiation dosimetry focused on parameter estimation for compartmental models from observed comp...
Bayesian estimation of dose rate effectiveness
International Nuclear Information System (INIS)
Arnish, J.J.; Groer, P.G.
2000-01-01
A Bayesian statistical method was used to quantify the effectiveness of high dose rate 137 Cs gamma radiation at inducing fatal mammary tumours and increasing the overall mortality rate in BALB/c female mice. The Bayesian approach considers both the temporal and dose dependence of radiation carcinogenesis and total mortality. This paper provides the first direct estimation of dose rate effectiveness using Bayesian statistics. This statistical approach provides a quantitative description of the uncertainty of the factor characterising the dose rate in terms of a probability density function. The results show that a fixed dose from 137 Cs gamma radiation delivered at a high dose rate is more effective at inducing fatal mammary tumours and increasing the overall mortality rate in BALB/c female mice than the same dose delivered at a low dose rate. (author)
Relaxation processes during amorphous metal alloys heating
International Nuclear Information System (INIS)
Malinochka, E.Ya.; Durachenko, A.M.; Borisov, V.T.
1982-01-01
Behaviour of Te+15 at.%Ge and Fe+13 at.%P+7 at.%C amorphous metal alloys during heating has been studied using the method of differential scanning calorimetry (DSC) as the most convenient one for determination of the value of heat effects, activation energies, temperature ranges of relaxation processes. Thermal effects corresponding to high-temperature relaxation processes taking place during amorphous metal alloys (AMA) heating are detected. The change of ratio of relaxation peaks values on DSC curves as a result of AMA heat treatment can be explained by the presence of a number of levels of inner energy in amorphous system, separated with potential barriers, the heights of which correspond to certain activation energies of relaxation processes
The relaxation of plasmas with dust particles
International Nuclear Information System (INIS)
Chutov, Yu.I.; Kravchenko, A.Yu.; Schram, P.P.J.M.
1997-01-01
Various parameters of relaxing plasmas with dust particles including the electron and ion energy distributions function are numerically simulated at various parameters of the dust particles using the PIC method and taking into account the dynamics of the dust particle charge without the assumption about the equilibrium of electrons and ions. Coulomb collisions are taken into account in the framework of the method of stochastic differential equations. The relaxation of bounded plasma clouds expanding into a vacuum as well as the relaxation of a uniform plasma, in which dust particles appear at some initial time, are investigated. The obtained results show that the relaxation of plasmas can be accompanied by a deviation of the ion distribution function from equilibrium as well as a change of the mean energy of electrons and ions because of the dependence of the collection of electrons and ions by dust particles on their energy. (author)
Multiscale dipole relaxation in dielectric materials
DEFF Research Database (Denmark)
Hansen, Jesper Schmidt
2016-01-01
Dipole relaxation from thermally induced perturbations is investigated on different length scales for dielectric materials. From the continuum dynamical equations for the polarisation, expressions for the transverse and longitudinal dipole autocorrelation functions are derived in the limit where ...
Generalized approach to non-exponential relaxation
Indian Academy of Sciences (India)
Non-exponential relaxation is a universal feature of systems as diverse as glasses, spin ... which changes from a simple exponential to a stretched exponential and a power law by increasing the constraints in the system. ... Current Issue
Oxygen-17 relaxation in aqueous agarose gels
International Nuclear Information System (INIS)
Ablett, S.; Lillford, P.J.
1977-01-01
Nuclear magnetic relaxation of oxygen-17 in H 2 17 O enriched agarose gels shows that existing explanations of water behaviour are oversimplified. Satisfactory models must include at least three proton phases, two of which involve water molecules. (Auth.)
Proton NMR relaxivity of blood samples in the presence of some gadolinium and dysprosium compounds
International Nuclear Information System (INIS)
Coroiu, I.; Darabont, Al.; Bogdan, M.
1999-01-01
The use of some new compounds in MRI tissue and blood characterisation based on nuclear spin relaxation time measurements cannot be sustained until the molecular sources of these variations are understood. Tissues and blood are complex molecular systems with complex NMR properties. A better comprehension of the molecular basis of relaxation offers the possibility to predict the changes expected for a given pathology. The purpose of this contribution is to evidence the different relaxation characteristics of some gadolinium and dysprosium compounds in the presence and absence of the blood and to give a possible explanation about the molecular processes that cause occurrence of changes. Some gadolinium and dysprosium compounds such as: Gd-CIT (gadolinium citrate), Dy-DTPA (DTPA-diethylenetriamine pentaacetic acid), iron oxide - gadolinium oxide (or dysprosium oxide)- dextran complexes were prepared. The longitudinal T 1 -1 and transverse T 2 -1 'relaxation rates' measurements have been carried out as a function of molar concentrations. All measurements have been made at room temperature (about 25 deg.C) and the proton Larmor frequency ν o = 90 MHz. The pulsed NMR spectrometer utilised was a commercial Bruker SXP4/100 spectrometer. Transverse relaxation rate measurements have been made using the Carr-Purcell method, while longitudinal relaxation rate measurements using the inversion recovery pulse sequence, 180 angle-τ-90 angle. The accuracy was about 2-3% for the longitudinal relaxation rates and about 5-7% for the transverse relaxation rates. R 1 and R 2 relaxivities, in mM -1 s -1 were determined from the least square determination of the slopes of plots 1/T 1,2 versus compound molar concentration, using at least five independent measurements at several concentrations between 0 and 2 mM. Increased R 2 relaxivity observed for dysprosium compounds in the blood presence can be explained by PRE effect. The largest gain in R 2 relaxivity seems to imply a noncovalent
A nonparametric Bayesian approach for genetic evaluation in ...
African Journals Online (AJOL)
South African Journal of Animal Science ... the Bayesian and Classical models, a Bayesian procedure is provided which allows these random ... data from the Elsenburg Dormer sheep stud and data from a simulation experiment are utilized. >
Bayesian disease mapping: hierarchical modeling in spatial epidemiology
National Research Council Canada - National Science Library
Lawson, Andrew
2013-01-01
.... Exploring these new developments, Bayesian Disease Mapping: Hierarchical Modeling in Spatial Epidemiology, Second Edition provides an up-to-date, cohesive account of the full range of Bayesian disease mapping methods and applications...
Sparse reconstruction using distribution agnostic bayesian matching pursuit
Masood, Mudassir; Al-Naffouri, Tareq Y.
2013-01-01
A fast matching pursuit method using a Bayesian approach is introduced for sparse signal recovery. This method performs Bayesian estimates of sparse signals even when the signal prior is non-Gaussian or unknown. It is agnostic on signal statistics
Relaxation and hypnosis in pediatric dental patients.
Peretz, B
1996-01-01
Relaxation and hypnosis are methods which, may solve the problem of extreme dental anxiety, when all other methods, behavioral or pharmacological may not be used. A simple definition of hypnosis is suggestion and repetition. Suggestion is the process whereby an individual accepts a proposition put to him by another, without having the slightest logical reason for doing so. Relaxation is one method of inducing hypnosis. A case of using hypnosis on an 11-year-old boy is described.
Ghost lines in Moessbauer relaxation spectra
International Nuclear Information System (INIS)
Price, D.C.
1985-01-01
The appearance in Moessbauer relaxation spectra of 'ghost' lines, which are narrow lines that do not correspond to transitions between real hyperfine energy levels of the resonant system, is examined. It is shown that in many cases of interest, the appearance of these 'ghost' lines can be interpreted in terms of the relaxational averaging of one or more of the static interactions of the ion. (orig.)
Dynamics of helicity transport and Taylor relaxation
International Nuclear Information System (INIS)
Diamond, P.H.; Malkov, M.
2003-01-01
A simple model of the dynamics of Taylor relaxation is derived using symmetry principles alone. No statistical closure approximations are invoked or detailed plasma model properties assumed. Notably, the model predicts several classes of nondiffusive helicity transport phenomena, including traveling nonlinear waves and superdiffusive turbulent pulses. A universal expression for the scaling of the effective magnetic Reynolds number of a system undergoing Taylor relaxation is derived. Some basic properties of intermittency in helicity transport are examined
The Bayesian Approach to Association
Arora, N. S.
2017-12-01
The Bayesian approach to Association focuses mainly on quantifying the physics of the domain. In the case of seismic association for instance let X be the set of all significant events (above some threshold) and their attributes, such as location, time, and magnitude, Y1 be the set of detections that are caused by significant events and their attributes such as seismic phase, arrival time, amplitude etc., Y2 be the set of detections that are not caused by significant events, and finally Y be the set of observed detections We would now define the joint distribution P(X, Y1, Y2, Y) = P(X) P(Y1 | X) P(Y2) I(Y = Y1 + Y2) ; where the last term simply states that Y1 and Y2 are a partitioning of Y. Given the above joint distribution the inference problem is simply to find the X, Y1, and Y2 that maximizes posterior probability P(X, Y1, Y2| Y) which reduces to maximizing P(X) P(Y1 | X) P(Y2) I(Y = Y1 + Y2). In this expression P(X) captures our prior belief about event locations. P(Y1 | X) captures notions of travel time, residual error distributions as well as detection and mis-detection probabilities. While P(Y2) captures the false detection rate of our seismic network. The elegance of this approach is that all of the assumptions are stated clearly in the model for P(X), P(Y1|X) and P(Y2). The implementation of the inference is merely a by-product of this model. In contrast some of the other methods such as GA hide a number of assumptions in the implementation details of the inference - such as the so called "driver cells." The other important aspect of this approach is that all seismic knowledge including knowledge from other domains such as infrasound and hydroacoustic can be included in the same model. So, we don't need to separately account for misdetections or merge seismic and infrasound events as a separate step. Finally, it should be noted that the objective of automatic association is to simplify the job of humans who are publishing seismic bulletins based on this
Energy Technology Data Exchange (ETDEWEB)
Rigny, P [Commissariat a l' Energie Atomique, Saclay (France). Centre d' Etudes Nucleaires
1967-12-01
The interesting properties of the fluorine magnetic resonance in the hexafluorides of molybdenum, tungsten and uranium, are very much due to large anisotropies of the chemical shift tensors. In the solid phases these anisotropies, the values of which are deduced from line shape studies, allow one to show that the molecules undergo hindered rotations about the metal atom. The temperature and frequency dependence of the fluorine longitudinal relaxation times shows that the relaxation is due to the molecular motion. The dynamical parameters of this motion are then deduced from the complete study of the fluorine relaxation in the rotating frame. In the liquid phases, the existence of anisotropies allows an estimation of the different contributions to the relaxation. In particular, the frequency and temperature dependence of the relaxation shows it to be dominated by the spin-rotation interaction. We have shown that the strength of this interaction can be deduced from the chemical shifts, and the angle through which the molecule rotates quasi-freely can be determined. In the hexafluorides, this angle is roughly one radian at 70 C, and with the help of this value, the friction coefficients which describe the intermolecular interactions are discussed. (author) [French] Les proprietes de la resonance magnetique des fluors dans les hexafluorures de molybdene, tungstene et uranium sont influencees par l'existence de deplacements chimiques tres anisotropes. Dans les phases solides, la valeur de cette anisotropie peut etre determinee par l'analyse des formes de raies et son existence permet de montrer que les molecules sont en rotation empechee autour de leur atome central. L'etude du temps de relaxation longitudinal en fonction de la temperature et de la frequence montre que la relaxation est due aux mouvements moleculaires, aux plus hautes temperatures. Les proprietes dynamiques du mouvement sont obtenues par l'etude complete de la relaxation spin-reseau dans le referentiel
Strain relaxation and ambipolar electrical transport in GaAs/InSb core-shell nanowires.
Rieger, Torsten; Zellekens, Patrick; Demarina, Natalia; Hassan, Ali Al; Hackemüller, Franz Josef; Lüth, Hans; Pietsch, Ullrich; Schäpers, Thomas; Grützmacher, Detlev; Lepsa, Mihail Ion
2017-11-30
The growth, crystal structure, strain relaxation and room temperature transport characteristics of GaAs/InSb core-shell nanowires grown using molecular beam epitaxy are investigated. Due to the large lattice mismatch between GaAs and InSb of 14%, a transition from island-based to layer-like growth occurs during the formation of the shell. High resolution transmission electron microscopy in combination with geometric phase analyses as well as X-ray diffraction with synchrotron radiation are used to investigate the strain relaxation and prove the existence of different dislocations relaxing the strain on zinc blende and wurtzite core-shell nanowire segments. While on the wurtzite phase only Frank partial dislocations are found, the strain on the zinc blende phase is relaxed by dislocations with perfect, Shockley partial and Frank partial dislocations. Even for ultrathin shells of about 2 nm thickness, the strain caused by the high lattice mismatch between GaAs and InSb is relaxed almost completely. Transfer characteristics of the core-shell nanowires show an ambipolar conductance behavior whose strength strongly depends on the dimensions of the nanowires. The interpretation is given based on an electronic band profile which is calculated for completely relaxed core/shell structures. The peculiarities of the band alignment in this situation implies simultaneously occupied electron and hole channels in the InSb shell. The ambipolar behavior is then explained by the change of carrier concentration in both channels by the gate voltage.
Welch, K.; Mousavi, S.; Lundberg, B.; Strømme, M.
2005-09-01
A newly developed method for determining the frequency-dependent complex Young's modulus was employed to analyze the mechanical response of compacted microcrystalline cellulose, sorbitol, ethyl cellulose and starch for frequencies up to 20 kHz. A Debye-like relaxation was observed in all the studied pharmaceutical excipient materials and a comparison with corresponding dielectric spectroscopy data was made. The location in frequency of the relaxation peak was shown to correlate to the measured tensile strength of the tablets, and the relaxation was interpreted as the vibrational response of the interparticle hydrogen and van der Waals bindings in the tablets. Further, the measured relaxation strength, holding information about the energy loss involved in the relaxation processes, showed that the weakest material in terms of tensile strength, starch, is the material among the four tested ones that is able to absorb the most energy within its structure when exposed to external perturbations inducing vibrations in the studied frequency range. The results indicate that mechanical relaxation analysis performed over relatively broad frequency ranges should be useful for predicting material properties of importance for the functionality of a material in applications such as, e.g., drug delivery, drug storage and handling, and also for clarifying the origin of hitherto unexplained molecular processes.
International Nuclear Information System (INIS)
Bieri, Michael; D’Auvergne, Edward J.; Gooley, Paul R.
2011-01-01
Investigation of protein dynamics on the ps-ns and μs-ms timeframes provides detailed insight into the mechanisms of enzymes and the binding properties of proteins. Nuclear magnetic resonance (NMR) is an excellent tool for studying protein dynamics at atomic resolution. Analysis of relaxation data using model-free analysis can be a tedious and time consuming process, which requires good knowledge of scripting procedures. The software relaxGUI was developed for fast and simple model-free analysis and is fully integrated into the software package relax. It is written in Python and uses wxPython to build the graphical user interface (GUI) for maximum performance and multi-platform use. This software allows the analysis of NMR relaxation data with ease and the generation of publication quality graphs as well as color coded images of molecular structures. The interface is designed for simple data analysis and management. The software was tested and validated against the command line version of relax.
Bieri, Michael; d'Auvergne, Edward J; Gooley, Paul R
2011-06-01
Investigation of protein dynamics on the ps-ns and μs-ms timeframes provides detailed insight into the mechanisms of enzymes and the binding properties of proteins. Nuclear magnetic resonance (NMR) is an excellent tool for studying protein dynamics at atomic resolution. Analysis of relaxation data using model-free analysis can be a tedious and time consuming process, which requires good knowledge of scripting procedures. The software relaxGUI was developed for fast and simple model-free analysis and is fully integrated into the software package relax. It is written in Python and uses wxPython to build the graphical user interface (GUI) for maximum performance and multi-platform use. This software allows the analysis of NMR relaxation data with ease and the generation of publication quality graphs as well as color coded images of molecular structures. The interface is designed for simple data analysis and management. The software was tested and validated against the command line version of relax.
Relaxation of synchronization on complex networks.
Son, Seung-Woo; Jeong, Hawoong; Hong, Hyunsuk
2008-07-01
We study collective synchronization in a large number of coupled oscillators on various complex networks. In particular, we focus on the relaxation dynamics of the synchronization, which is important from the viewpoint of information transfer or the dynamics of system recovery from a perturbation. We measure the relaxation time tau that is required to establish global synchronization by varying the structural properties of the networks. It is found that the relaxation time in a strong-coupling regime (K>Kc) logarithmically increases with network size N , which is attributed to the initial random phase fluctuation given by O(N-1/2) . After elimination of the initial-phase fluctuation, the relaxation time is found to be independent of the system size; this implies that the local interaction that depends on the structural connectivity is irrelevant in the relaxation dynamics of the synchronization in the strong-coupling regime. The relaxation dynamics is analytically derived in a form independent of the system size, and it exhibits good consistency with numerical simulations. As an application, we also explore the recovery dynamics of the oscillators when perturbations enter the system.
Relaxation strain measurements in cellular dislocation structures
International Nuclear Information System (INIS)
Tsai, C.Y.; Quesnel, D.J.
1984-01-01
The conventional picture of what happens during a stress relaxation usually involves imagining the response of a single dislocation to a steadily decreasing stress. The velocity of this dislocation decreases with decreasing stress in such a way that we can measure the stress dependence of the dislocation velocity. Analysis of the data from a different viewpoint enables us to calculate the apparent activation volume for the motion of the dislocation under the assumption of thermally activated glie. Conventional thinking about stress relaxation, however, does not consider the eventual fate of this dislocation. If the stress relaxes to a low enough level, it is clear that the dislocation must stop. This is consistent with the idea that we can determine the stress dependence of the dislocation velocity from relaxation data only for those cases where the dislocation's velocity is allowed to approach zero asymptotically, in short, for those cases where the dislocation never stops. This conflict poses a dilemma for the experimentalist. In real crystals, however, obstacles impede the dislocation's progress so that those dislocations which are stopped at a given stress will probably never resume motion under the influence of the steadily declining stress present during relaxation. Thus one could envision stress relaxation as a process of exhaustion of mobile dislocations, rather than a process of decreasing dislocation velocity. Clearly both points of view have merit and in reality both mechanisms contribute to the phenomena
Bayesian uncertainty analyses of probabilistic risk models
International Nuclear Information System (INIS)
Pulkkinen, U.
1989-01-01
Applications of Bayesian principles to the uncertainty analyses are discussed in the paper. A short review of the most important uncertainties and their causes is provided. An application of the principle of maximum entropy to the determination of Bayesian prior distributions is described. An approach based on so called probabilistic structures is presented in order to develop a method of quantitative evaluation of modelling uncertainties. The method is applied to a small example case. Ideas for application areas for the proposed method are discussed
Justifying Objective Bayesianism on Predicate Languages
Directory of Open Access Journals (Sweden)
Jürgen Landes
2015-04-01
Full Text Available Objective Bayesianism says that the strengths of one’s beliefs ought to be probabilities, calibrated to physical probabilities insofar as one has evidence of them, and otherwise sufficiently equivocal. These norms of belief are often explicated using the maximum entropy principle. In this paper we investigate the extent to which one can provide a unified justification of the objective Bayesian norms in the case in which the background language is a first-order predicate language, with a view to applying the resulting formalism to inductive logic. We show that the maximum entropy principle can be motivated largely in terms of minimising worst-case expected loss.
Motion Learning Based on Bayesian Program Learning
Directory of Open Access Journals (Sweden)
Cheng Meng-Zhen
2017-01-01
Full Text Available The concept of virtual human has been highly anticipated since the 1980s. By using computer technology, Human motion simulation could generate authentic visual effect, which could cheat human eyes visually. Bayesian Program Learning train one or few motion data, generate new motion data by decomposing and combining. And the generated motion will be more realistic and natural than the traditional one.In this paper, Motion learning based on Bayesian program learning allows us to quickly generate new motion data, reduce workload, improve work efficiency, reduce the cost of motion capture, and improve the reusability of data.
Nonparametric Bayesian Modeling of Complex Networks
DEFF Research Database (Denmark)
Schmidt, Mikkel Nørgaard; Mørup, Morten
2013-01-01
an infinite mixture model as running example, we go through the steps of deriving the model as an infinite limit of a finite parametric model, inferring the model parameters by Markov chain Monte Carlo, and checking the model?s fit and predictive performance. We explain how advanced nonparametric models......Modeling structure in complex networks using Bayesian nonparametrics makes it possible to specify flexible model structures and infer the adequate model complexity from the observed data. This article provides a gentle introduction to nonparametric Bayesian modeling of complex networks: Using...
Length Scales in Bayesian Automatic Adaptive Quadrature
Directory of Open Access Journals (Sweden)
Adam Gh.
2016-01-01
Full Text Available Two conceptual developments in the Bayesian automatic adaptive quadrature approach to the numerical solution of one-dimensional Riemann integrals [Gh. Adam, S. Adam, Springer LNCS 7125, 1–16 (2012] are reported. First, it is shown that the numerical quadrature which avoids the overcomputing and minimizes the hidden floating point loss of precision asks for the consideration of three classes of integration domain lengths endowed with specific quadrature sums: microscopic (trapezoidal rule, mesoscopic (Simpson rule, and macroscopic (quadrature sums of high algebraic degrees of precision. Second, sensitive diagnostic tools for the Bayesian inference on macroscopic ranges, coming from the use of Clenshaw-Curtis quadrature, are derived.
Bayesian parameter estimation in probabilistic risk assessment
International Nuclear Information System (INIS)
Siu, Nathan O.; Kelly, Dana L.
1998-01-01
Bayesian statistical methods are widely used in probabilistic risk assessment (PRA) because of their ability to provide useful estimates of model parameters when data are sparse and because the subjective probability framework, from which these methods are derived, is a natural framework to address the decision problems motivating PRA. This paper presents a tutorial on Bayesian parameter estimation especially relevant to PRA. It summarizes the philosophy behind these methods, approaches for constructing likelihood functions and prior distributions, some simple but realistic examples, and a variety of cautions and lessons regarding practical applications. References are also provided for more in-depth coverage of various topics
Bayesian estimation and tracking a practical guide
Haug, Anton J
2012-01-01
A practical approach to estimating and tracking dynamic systems in real-worl applications Much of the literature on performing estimation for non-Gaussian systems is short on practical methodology, while Gaussian methods often lack a cohesive derivation. Bayesian Estimation and Tracking addresses the gap in the field on both accounts, providing readers with a comprehensive overview of methods for estimating both linear and nonlinear dynamic systems driven by Gaussian and non-Gaussian noices. Featuring a unified approach to Bayesian estimation and tracking, the book emphasizes the derivation
Acrolein relaxes mouse isolated tracheal smooth muscle via a TRPA1-dependent mechanism.
Cheah, Esther Y; Burcham, Philip C; Mann, Tracy S; Henry, Peter J
2014-05-01
Airway sensory C-fibres express TRPA1 channels which have recently been identified as a key chemosensory receptor for acrolein, a toxic and highly prevalent component of smoke. TRPA1 likely plays an intermediary role in eliciting a range of effects induced by acrolein including cough and neurogenic inflammation. Currently, it is not known whether acrolein-induced activation of TRPA1 produces other airway effects including relaxation of mouse airway smooth muscle. The aims of this study were to examine the effects of acrolein on airway smooth muscle tone in mouse isolated trachea, and to characterise the cellular and molecular mechanisms underpinning the effects of acrolein. Isometric tension recording studies were conducted on mouse isolated tracheal segments to characterise acrolein-induced relaxation responses. Release of the relaxant PGE₂ was measured by EIA to examine its role in the response. Use of selective antagonists/inhibitors permitted pharmacological characterisation of the molecular and cellular mechanisms underlying this relaxation response. Acrolein induced dose-dependent relaxation responses in mouse isolated tracheal segments. Importantly, these relaxation responses were significantly inhibited by the TRPA1 antagonists AP-18 and HC-030031, an NK₁ receptor antagonist RP-67580, and the EP₂ receptor antagonist PF-04418948, whilst completely abolished by the non-selective COX inhibitor indomethacin. Acrolein also caused rapid PGE₂ release which was suppressed by HC-030031. In summary, acrolein induced a novel bronchodilator response in mouse airways. Pharmacologic studies indicate that acrolein-induced relaxation likely involves interplay between TRPA1-expressing airway sensory C-fibres, NK₁ receptor-expressing epithelial cells, and EP₂-receptor expressing airway smooth muscle cells. Copyright © 2014 Elsevier Inc. All rights reserved.
String-like collective motion in the α- and β-relaxation of a coarse-grained polymer melt
Pazmiño Betancourt, Beatriz A.; Starr, Francis W.; Douglas, Jack F.
2018-03-01
Relaxation in glass-forming liquids occurs as a multi-stage hierarchical process involving cooperative molecular motion. First, there is a "fast" relaxation process dominated by the inertial motion of the molecules whose amplitude grows upon heating, followed by a longer time α-relaxation process involving both large-scale diffusive molecular motion and momentum diffusion. Our molecular dynamics simulations of a coarse-grained glass-forming polymer melt indicate that the fast, collective motion becomes progressively suppressed upon cooling, necessitating large-scale collective motion by molecular diffusion for the material to relax approaching the glass-transition. In each relaxation regime, the decay of the collective intermediate scattering function occurs through collective particle exchange motions having a similar geometrical form, and quantitative relationships are derived relating the fast "stringlet" collective motion to the larger scale string-like collective motion at longer times, which governs the temperature-dependent activation energies associated with both thermally activated molecular diffusion and momentum diffusion.
A Fast Iterative Bayesian Inference Algorithm for Sparse Channel Estimation
DEFF Research Database (Denmark)
Pedersen, Niels Lovmand; Manchón, Carles Navarro; Fleury, Bernard Henri
2013-01-01
representation of the Bessel K probability density function; a highly efficient, fast iterative Bayesian inference method is then applied to the proposed model. The resulting estimator outperforms other state-of-the-art Bayesian and non-Bayesian estimators, either by yielding lower mean squared estimation error...
A Gentle Introduction to Bayesian Analysis : Applications to Developmental Research
Van de Schoot, Rens; Kaplan, David; Denissen, Jaap; Asendorpf, Jens B.; Neyer, Franz J.; van Aken, Marcel A G
2014-01-01
Bayesian statistical methods are becoming ever more popular in applied and fundamental research. In this study a gentle introduction to Bayesian analysis is provided. It is shown under what circumstances it is attractive to use Bayesian estimation, and how to interpret properly the results. First,
A gentle introduction to Bayesian analysis : Applications to developmental research
van de Schoot, R.; Kaplan, D.; Denissen, J.J.A.; Asendorpf, J.B.; Neyer, F.J.; van Aken, M.A.G.
2014-01-01
Bayesian statistical methods are becoming ever more popular in applied and fundamental research. In this study a gentle introduction to Bayesian analysis is provided. It is shown under what circumstances it is attractive to use Bayesian estimation, and how to interpret properly the results. First,
A default Bayesian hypothesis test for ANOVA designs
Wetzels, R.; Grasman, R.P.P.P.; Wagenmakers, E.J.
2012-01-01
This article presents a Bayesian hypothesis test for analysis of variance (ANOVA) designs. The test is an application of standard Bayesian methods for variable selection in regression models. We illustrate the effect of various g-priors on the ANOVA hypothesis test. The Bayesian test for ANOVA
Prior approval: the growth of Bayesian methods in psychology.
Andrews, Mark; Baguley, Thom
2013-02-01
Within the last few years, Bayesian methods of data analysis in psychology have proliferated. In this paper, we briefly review the history or the Bayesian approach to statistics, and consider the implications that Bayesian methods have for the theory and practice of data analysis in psychology.
International Nuclear Information System (INIS)
Yang, Xu-Sheng; Wang, Yun-Jiang; Wang, Guo-Yong; Zhai, Hui-Ru; Dai, L.H.; Zhang, Tong-Yi
2016-01-01
In the present work, stress relaxation tests, high-resolution transmission electron microscopy (HRTEM), and molecular dynamics (MD) simulations were conducted on coarse-grained (cg), nanograined (ng), and nanotwinned (nt) copper at temperatures of 22 °C (RT), 30 °C, 40 °C, 50 °C, and 75 °C. The comprehensive investigations provide sufficient information for the building-up of a formula to describe the time, stress, and temperature-dependent deformation and clarify the relationship among the strain rate sensitivity parameter, stress exponent, and activation volume. The typically experimental curves of logarithmic plastic strain rate versus stress exhibited a three staged relaxation process from a linear high stress relaxation region to a subsequent nonlinear stress relaxation region and finally to a linear low stress relaxation region, which only showed-up at the test temperatures higher than 22 °C, 22 °C, and 30 °C, respectively, in the tested cg-, ng-, and nt-Cu specimens. The values of stress exponent, stress-independent activation energy, and activation volume were determined from the experimental data in the two linear regions. The determined activation parameters, HRTEM images, and MD simulations consistently suggest that dislocation-mediated plastic deformation is predominant in all tested cg-, ng-, and nt-Cu specimens in the initial linear high stress relaxation region at the five relaxation temperatures, whereas in the linear low stress relaxation region, the grain boundary (GB) diffusion-associated deformation is dominant in the ng- and cg-Cu specimens, while twin boundary (TB) migration, i.e., twinning and detwinning with parallel partial dislocations, governs the time, stress, and temperature-dependent deformation in the nt-Cu specimens.
Molecular phylogenetics and historical biogeography of Rhinolophus bats.
Stoffberg, Samantha; Jacobs, David S; Mackie, Iain J; Matthee, Conrad A
2010-01-01
The phylogenetic relationships within the horseshoe bats (genus Rhinolophus) are poorly resolved, particularly at deeper levels within the tree. We present a better-resolved phylogenetic hypothesis for 30 rhinolophid species based on parsimony and Bayesian analyses of the mitochondrial cytochrome b gene and three nuclear introns (TG, THY and PRKC1). Strong support was found for the existence of two geographic clades within the monophyletic Rhinolophidae: an African group and an Oriental assemblage. The relaxed Bayesian clock method indicated that the two rhinolophid clades diverged approximately 35 million years ago and results from Dispersal Vicariance (DIVA) analysis suggest that the horseshoe bats arose in Asia and subsequently dispersed into Europe and Africa.
Effect of alkali ion on relaxation properties of binary alkali-borate glasses
International Nuclear Information System (INIS)
Lomovskoj, V.A.; Bartenev, G.M.
1992-01-01
Method of relaxation spectrometry were used to analyze the data on internal friction spectra of lithium, sodium, potassium and rubidium alkali-borate glasses in wide range of temperatures and frequencies. The nature of two relaxation processes was clarified: β m -process, related with mobility of alkaline metal cations, and α-process (vitrification), conditioned by system transformation from viscous-flow to vitreous state. It is shown that atomic-molecular mechanism of vitrification process changes when passing from vitreous B 2 O 3 to alkali-borate glasses
Rander, D. N.; Joshi, Y. S.; Kanse, K. S.; Kumbharkhane, A. C.
2016-01-01
The measurements of complex dielectric permittivity of xylitol-water mixtures have been carried out in the frequency range of 10 MHz-30 GHz using a time domain reflectometry technique. Measurements have been done at six temperatures from 0 to 25 °C and at different weight fractions of xylitol (0 xylitol-water can be well described by Cole-Davidson model having an asymmetric distribution of relaxation times. The dielectric parameters such as static dielectric constant and relaxation time for the mixtures have been evaluated. The molecular interaction between xylitol and water molecules is discussed using the Kirkwood correlation factor ( g eff ) and thermodynamic parameter.
Bayesian Meta-Analysis of Coefficient Alpha
Brannick, Michael T.; Zhang, Nanhua
2013-01-01
The current paper describes and illustrates a Bayesian approach to the meta-analysis of coefficient alpha. Alpha is the most commonly used estimate of the reliability or consistency (freedom from measurement error) for educational and psychological measures. The conventional approach to meta-analysis uses inverse variance weights to combine…
Bayesian decision theory : A simple toy problem
van Erp, H.R.N.; Linger, R.O.; van Gelder, P.H.A.J.M.
2016-01-01
We give here a comparison of the expected outcome theory, the expected utility theory, and the Bayesian decision theory, by way of a simple numerical toy problem in which we look at the investment willingness to avert a high impact low probability event. It will be found that for this toy problem
Optimal Detection under the Restricted Bayesian Criterion
Directory of Open Access Journals (Sweden)
Shujun Liu
2017-07-01
Full Text Available This paper aims to find a suitable decision rule for a binary composite hypothesis-testing problem with a partial or coarse prior distribution. To alleviate the negative impact of the information uncertainty, a constraint is considered that the maximum conditional risk cannot be greater than a predefined value. Therefore, the objective of this paper becomes to find the optimal decision rule to minimize the Bayes risk under the constraint. By applying the Lagrange duality, the constrained optimization problem is transformed to an unconstrained optimization problem. In doing so, the restricted Bayesian decision rule is obtained as a classical Bayesian decision rule corresponding to a modified prior distribution. Based on this transformation, the optimal restricted Bayesian decision rule is analyzed and the corresponding algorithm is developed. Furthermore, the relation between the Bayes risk and the predefined value of the constraint is also discussed. The Bayes risk obtained via the restricted Bayesian decision rule is a strictly decreasing and convex function of the constraint on the maximum conditional risk. Finally, the numerical results including a detection example are presented and agree with the theoretical results.
Heuristics as Bayesian inference under extreme priors.
Parpart, Paula; Jones, Matt; Love, Bradley C
2018-05-01
Simple heuristics are often regarded as tractable decision strategies because they ignore a great deal of information in the input data. One puzzle is why heuristics can outperform full-information models, such as linear regression, which make full use of the available information. These "less-is-more" effects, in which a relatively simpler model outperforms a more complex model, are prevalent throughout cognitive science, and are frequently argued to demonstrate an inherent advantage of simplifying computation or ignoring information. In contrast, we show at the computational level (where algorithmic restrictions are set aside) that it is never optimal to discard information. Through a formal Bayesian analysis, we prove that popular heuristics, such as tallying and take-the-best, are formally equivalent to Bayesian inference under the limit of infinitely strong priors. Varying the strength of the prior yields a continuum of Bayesian models with the heuristics at one end and ordinary regression at the other. Critically, intermediate models perform better across all our simulations, suggesting that down-weighting information with the appropriate prior is preferable to entirely ignoring it. Rather than because of their simplicity, our analyses suggest heuristics perform well because they implement strong priors that approximate the actual structure of the environment. We end by considering how new heuristics could be derived by infinitely strengthening the priors of other Bayesian models. These formal results have implications for work in psychology, machine learning and economics. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.
A strongly quasiconvex PAC-Bayesian bound
DEFF Research Database (Denmark)
Thiemann, Niklas; Igel, Christian; Wintenberger, Olivier
2017-01-01
We propose a new PAC-Bayesian bound and a way of constructing a hypothesis space, so that the bound is convex in the posterior distribution and also convex in a trade-off parameter between empirical performance of the posterior distribution and its complexity. The complexity is measured by the Ku...
Multisnapshot Sparse Bayesian Learning for DOA
DEFF Research Database (Denmark)
Gerstoft, Peter; Mecklenbrauker, Christoph F.; Xenaki, Angeliki
2016-01-01
The directions of arrival (DOA) of plane waves are estimated from multisnapshot sensor array data using sparse Bayesian learning (SBL). The prior for the source amplitudes is assumed independent zero-mean complex Gaussian distributed with hyperparameters, the unknown variances (i.e., the source...
Approximate Bayesian evaluations of measurement uncertainty
Possolo, Antonio; Bodnar, Olha
2018-04-01
The Guide to the Expression of Uncertainty in Measurement (GUM) includes formulas that produce an estimate of a scalar output quantity that is a function of several input quantities, and an approximate evaluation of the associated standard uncertainty. This contribution presents approximate, Bayesian counterparts of those formulas for the case where the output quantity is a parameter of the joint probability distribution of the input quantities, also taking into account any information about the value of the output quantity available prior to measurement expressed in the form of a probability distribution on the set of possible values for the measurand. The approximate Bayesian estimates and uncertainty evaluations that we present have a long history and illustrious pedigree, and provide sufficiently accurate approximations in many applications, yet are very easy to implement in practice. Differently from exact Bayesian estimates, which involve either (analytical or numerical) integrations, or Markov Chain Monte Carlo sampling, the approximations that we describe involve only numerical optimization and simple algebra. Therefore, they make Bayesian methods widely accessible to metrologists. We illustrate the application of the proposed techniques in several instances of measurement: isotopic ratio of silver in a commercial silver nitrate; odds of cryptosporidiosis in AIDS patients; height of a manometer column; mass fraction of chromium in a reference material; and potential-difference in a Zener voltage standard.
Inverse Problems in a Bayesian Setting
Matthies, Hermann G.
2016-02-13
In a Bayesian setting, inverse problems and uncertainty quantification (UQ)—the propagation of uncertainty through a computational (forward) model—are strongly connected. In the form of conditional expectation the Bayesian update becomes computationally attractive. We give a detailed account of this approach via conditional approximation, various approximations, and the construction of filters. Together with a functional or spectral approach for the forward UQ there is no need for time-consuming and slowly convergent Monte Carlo sampling. The developed sampling-free non-linear Bayesian update in form of a filter is derived from the variational problem associated with conditional expectation. This formulation in general calls for further discretisation to make the computation possible, and we choose a polynomial approximation. After giving details on the actual computation in the framework of functional or spectral approximations, we demonstrate the workings of the algorithm on a number of examples of increasing complexity. At last, we compare the linear and nonlinear Bayesian update in form of a filter on some examples.
Error probabilities in default Bayesian hypothesis testing
Gu, Xin; Hoijtink, Herbert; Mulder, J,
2016-01-01
This paper investigates the classical type I and type II error probabilities of default Bayes factors for a Bayesian t test. Default Bayes factors quantify the relative evidence between the null hypothesis and the unrestricted alternative hypothesis without needing to specify prior distributions for
Bayesian Averaging is Well-Temperated
DEFF Research Database (Denmark)
Hansen, Lars Kai
2000-01-01
Bayesian predictions are stochastic just like predictions of any other inference scheme that generalize from a finite sample. While a simple variational argument shows that Bayes averaging is generalization optimal given that the prior matches the teacher parameter distribution the situation is l...
Robust bayesian inference of generalized Pareto distribution ...
African Journals Online (AJOL)
En utilisant une etude exhaustive de Monte Carlo, nous prouvons que, moyennant une fonction perte generalisee adequate, on peut construire un estimateur Bayesien robuste du modele. Key words: Bayesian estimation; Extreme value; Generalized Fisher information; Gener- alized Pareto distribution; Monte Carlo; ...
Evidence Estimation for Bayesian Partially Observed MRFs
Chen, Y.; Welling, M.
2013-01-01
Bayesian estimation in Markov random fields is very hard due to the intractability of the partition function. The introduction of hidden units makes the situation even worse due to the presence of potentially very many modes in the posterior distribution. For the first time we propose a
Inverse Problems in a Bayesian Setting
Matthies, Hermann G.; Zander, Elmar; Rosić, Bojana V.; Litvinenko, Alexander; Pajonk, Oliver
2016-01-01
In a Bayesian setting, inverse problems and uncertainty quantification (UQ)—the propagation of uncertainty through a computational (forward) model—are strongly connected. In the form of conditional expectation the Bayesian update becomes computationally attractive. We give a detailed account of this approach via conditional approximation, various approximations, and the construction of filters. Together with a functional or spectral approach for the forward UQ there is no need for time-consuming and slowly convergent Monte Carlo sampling. The developed sampling-free non-linear Bayesian update in form of a filter is derived from the variational problem associated with conditional expectation. This formulation in general calls for further discretisation to make the computation possible, and we choose a polynomial approximation. After giving details on the actual computation in the framework of functional or spectral approximations, we demonstrate the workings of the algorithm on a number of examples of increasing complexity. At last, we compare the linear and nonlinear Bayesian update in form of a filter on some examples.
A Bayesian perspective on some replacement strategies
International Nuclear Information System (INIS)
Mazzuchi, Thomas A.; Soyer, Refik
1996-01-01
In this paper we present a Bayesian decision theoretic approach for determining optimal replacement strategies. This approach enables us to formally incorporate, express, and update our uncertainty when determining optimal replacement strategies. We develop relevant expressions for both the block replacement protocol with minimal repair and the age replacement protocol and illustrate the use of our approach with real data
Comparison between Fisherian and Bayesian approach to ...
African Journals Online (AJOL)
... of its simplicity and optimality properties is normally used for two group cases. However, Bayesian approach is found to be better than Fisher's approach because of its low misclassification error rate. Keywords: variance-covariance matrices, centroids, prior probability, mahalanobis distance, probability of misclassification ...
BAYESIAN ESTIMATION OF THERMONUCLEAR REACTION RATES
Energy Technology Data Exchange (ETDEWEB)
Iliadis, C.; Anderson, K. S. [Department of Physics and Astronomy, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599-3255 (United States); Coc, A. [Centre de Sciences Nucléaires et de Sciences de la Matière (CSNSM), CNRS/IN2P3, Univ. Paris-Sud, Université Paris–Saclay, Bâtiment 104, F-91405 Orsay Campus (France); Timmes, F. X.; Starrfield, S., E-mail: iliadis@unc.edu [School of Earth and Space Exploration, Arizona State University, Tempe, AZ 85287-1504 (United States)
2016-11-01
The problem of estimating non-resonant astrophysical S -factors and thermonuclear reaction rates, based on measured nuclear cross sections, is of major interest for nuclear energy generation, neutrino physics, and element synthesis. Many different methods have been applied to this problem in the past, almost all of them based on traditional statistics. Bayesian methods, on the other hand, are now in widespread use in the physical sciences. In astronomy, for example, Bayesian statistics is applied to the observation of extrasolar planets, gravitational waves, and Type Ia supernovae. However, nuclear physics, in particular, has been slow to adopt Bayesian methods. We present astrophysical S -factors and reaction rates based on Bayesian statistics. We develop a framework that incorporates robust parameter estimation, systematic effects, and non-Gaussian uncertainties in a consistent manner. The method is applied to the reactions d(p, γ ){sup 3}He, {sup 3}He({sup 3}He,2p){sup 4}He, and {sup 3}He( α , γ ){sup 7}Be, important for deuterium burning, solar neutrinos, and Big Bang nucleosynthesis.
Non-Linear Approximation of Bayesian Update
Litvinenko, Alexander
2016-01-01
We develop a non-linear approximation of expensive Bayesian formula. This non-linear approximation is applied directly to Polynomial Chaos Coefficients. In this way, we avoid Monte Carlo sampling and sampling error. We can show that the famous Kalman Update formula is a particular case of this update.
Comprehension and computation in Bayesian problem solving
Directory of Open Access Journals (Sweden)
Eric D. Johnson
2015-07-01
Full Text Available Humans have long been characterized as poor probabilistic reasoners when presented with explicit numerical information. Bayesian word problems provide a well-known example of this, where even highly educated and cognitively skilled individuals fail to adhere to mathematical norms. It is widely agreed that natural frequencies can facilitate Bayesian reasoning relative to normalized formats (e.g. probabilities, percentages, both by clarifying logical set-subset relations and by simplifying numerical calculations. Nevertheless, between-study performance on transparent Bayesian problems varies widely, and generally remains rather unimpressive. We suggest there has been an over-focus on this representational facilitator (i.e. transparent problem structures at the expense of the specific logical and numerical processing requirements and the corresponding individual abilities and skills necessary for providing Bayesian-like output given specific verbal and numerical input. We further suggest that understanding this task-individual pair could benefit from considerations from the literature on mathematical cognition, which emphasizes text comprehension and problem solving, along with contributions of online executive working memory, metacognitive regulation, and relevant stored knowledge and skills. We conclude by offering avenues for future research aimed at identifying the stages in problem solving at which correct versus incorrect reasoners depart, and how individual difference might influence this time point.
A Bayesian Approach to Interactive Retrieval
Tague, Jean M.
1973-01-01
A probabilistic model for interactive retrieval is presented. Bayesian statistical decision theory principles are applied: use of prior and sample information about the relationship of document descriptions to query relevance; maximization of expected value of a utility function, to the problem of optimally restructuring search strategies in an…
Encoding dependence in Bayesian causal networks
Bayesian networks (BNs) represent complex, uncertain spatio-temporal dynamics by propagation of conditional probabilities between identifiable states with a testable causal interaction model. Typically, they assume random variables are discrete in time and space with a static network structure that ...
Forecasting nuclear power supply with Bayesian autoregression
International Nuclear Information System (INIS)
Beck, R.; Solow, J.L.
1994-01-01
We explore the possibility of forecasting the quarterly US generation of electricity from nuclear power using a Bayesian autoregression model. In terms of forecasting accuracy, this approach compares favorably with both the Department of Energy's current forecasting methodology and their more recent efforts using ARIMA models, and it is extremely easy and inexpensive to implement. (author)
Hierarchical Bayesian Models of Subtask Learning
Anglim, Jeromy; Wynton, Sarah K. A.
2015-01-01
The current study used Bayesian hierarchical methods to challenge and extend previous work on subtask learning consistency. A general model of individual-level subtask learning was proposed focusing on power and exponential functions with constraints to test for inconsistency. To study subtask learning, we developed a novel computer-based booking…
Non-Linear Approximation of Bayesian Update
Litvinenko, Alexander
2016-06-23
We develop a non-linear approximation of expensive Bayesian formula. This non-linear approximation is applied directly to Polynomial Chaos Coefficients. In this way, we avoid Monte Carlo sampling and sampling error. We can show that the famous Kalman Update formula is a particular case of this update.