Hibbett, David S; Matheny, P Brandon
2009-01-01
Background Ectomycorrhizae (ECM) are symbioses formed by polyphyletic assemblages of fungi (mostly Agaricomycetes) and plants (mostly Pinaceae and angiosperms in the rosid clade). Efforts to reconstruct the evolution of the ECM habit in Agaricomycetes have yielded vastly different results, ranging from scenarios with many relatively recent origins of the symbiosis and no reversals to the free-living condition; a single ancient origin of ECM and many subsequent transitions to the free-living condition; or multiple gains and losses of the association. To test the plausibility of these scenarios, we performed Bayesian relaxed molecular clock analyses including fungi, plants, and other eukaryotes, based on the principle that a symbiosis cannot evolve prior to the origin of both partners. As we were primarily interested in the relative ages of the plants and fungi, we did not attempt to calibrate the molecular clock using the very limited fossil record of Agaricomycetes. Results Topologically constrained and unconstrained analyses suggest that the root node of the Agaricomycetes is much older than either the rosids or Pinaceae. The Agaricomycetidae, a large clade containing the Agaricales and Boletales (collectively representing 70% of Agaricomycetes), is also significantly older than the rosids. The relative age of Agaricomycetidae and Pinaceae, however, is sensitive to tree topology, and the inclusion or exclusion of the gnetophyte Welwitschia mirabilis. Conclusion The ancestor of the Agaricomycetes could not have been an ECM species because it existed long before any of its potential hosts. Within more derived clades of Agaricomycetes, there have been at least eight independent origins of ECM associations involving angiosperms, and at least six to eight origins of associations with gymnosperms. The first ECM symbioses may have involved Pinaceae, which are older than rosids, but several major clades of Agaricomycetes, such as the Boletales and Russulales, are young
Relaxation time in disordered molecular systems
Energy Technology Data Exchange (ETDEWEB)
Rocha, Rodrigo P. [Departamento de Física, Universidade Federal de Santa Catarina, 88040-900 Florianópolis-SC (Brazil); Freire, José A., E-mail: jfreire@fisica.ufpr.br [Departamento de Física, Universidade Federal do Paraná, 81531-990 Curitiba-PR (Brazil)
2015-05-28
Relaxation time is the typical time it takes for a closed physical system to attain thermal equilibrium. The equilibrium is brought about by the action of a thermal reservoir inducing changes in the system micro-states. The relaxation time is intuitively expected to increase with system disorder. We derive a simple analytical expression for this dependence in the context of electronic equilibration in an amorphous molecular system model. We find that the disorder dramatically enhances the relaxation time but does not affect its independence of the nature of the initial state.
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
Fingerprinting molecular relaxation in deformed polymers
Wang, Zhe; Lam, Christopher N.; Chen, Wei-Ren; Wang, Weiyu; Liu, Jianning; Liu, Yun; Porcar, Lionel; Stanley, Christopher B.; Zhao, Zhichen; Hong, Kunlun; Wang, Yangyang
2017-01-01
International audience; The flow and deformation of macromolecules is ubiquitous in nature and industry, and an understanding of this phenomenon at both macroscopic and microscopic length scales is of fundamental and practical importance. Here, we present the formulation of a general mathematical framework, which could be used to extract, from scattering experiments, the molecular relaxation of deformed polymers. By combining and modestly extending several key conceptual ingredients in the li...
Fingerprinting Molecular Relaxation in Deformed Polymers
Wang, Zhe; Lam, Christopher N.; Chen, Wei-Ren; Wang, Weiyu; Liu, Jianning; Liu, Yun; Porcar, Lionel; Stanley, Christopher B.; Zhao, Zhichen; Hong, Kunlun; Wang, Yangyang
2017-07-01
The flow and deformation of macromolecules is ubiquitous in nature and industry, and an understanding of this phenomenon at both macroscopic and microscopic length scales is of fundamental and practical importance. Here, we present the formulation of a general mathematical framework, which could be used to extract, from scattering experiments, the molecular relaxation of deformed polymers. By combining and modestly extending several key conceptual ingredients in the literature, we show how the anisotropic single-chain structure factor can be decomposed by spherical harmonics and experimentally reconstructed from its cross sections on the scattering planes. The resulting wave-number-dependent expansion coefficients constitute a characteristic fingerprint of the macromolecular deformation, permitting detailed examinations of polymer dynamics at the microscopic level. We apply this approach to survey a long-standing problem in polymer physics regarding the molecular relaxation in entangled polymers after a large step deformation. The classical tube theory of Doi and Edwards predicts a fast chain retraction process immediately after the deformation, followed by a slow orientation relaxation through the reptation mechanism. This chain retraction hypothesis, which is the keystone of the tube theory for macromolecular flow and deformation, is critically examined by analyzing the fine features of the two-dimensional anisotropic spectra from small-angle neutron scattering by entangled polystyrenes. We show that the unique scattering patterns associated with the chain retraction mechanism are not experimentally observed. This result calls for a fundamental revision of the current theoretical picture for nonlinear rheological behavior of entangled polymeric liquids.
Fingerprinting Molecular Relaxation in Deformed Polymers
Directory of Open Access Journals (Sweden)
Zhe Wang
2017-07-01
Full Text Available The flow and deformation of macromolecules is ubiquitous in nature and industry, and an understanding of this phenomenon at both macroscopic and microscopic length scales is of fundamental and practical importance. Here, we present the formulation of a general mathematical framework, which could be used to extract, from scattering experiments, the molecular relaxation of deformed polymers. By combining and modestly extending several key conceptual ingredients in the literature, we show how the anisotropic single-chain structure factor can be decomposed by spherical harmonics and experimentally reconstructed from its cross sections on the scattering planes. The resulting wave-number-dependent expansion coefficients constitute a characteristic fingerprint of the macromolecular deformation, permitting detailed examinations of polymer dynamics at the microscopic level. We apply this approach to survey a long-standing problem in polymer physics regarding the molecular relaxation in entangled polymers after a large step deformation. The classical tube theory of Doi and Edwards predicts a fast chain retraction process immediately after the deformation, followed by a slow orientation relaxation through the reptation mechanism. This chain retraction hypothesis, which is the keystone of the tube theory for macromolecular flow and deformation, is critically examined by analyzing the fine features of the two-dimensional anisotropic spectra from small-angle neutron scattering by entangled polystyrenes. We show that the unique scattering patterns associated with the chain retraction mechanism are not experimentally observed. This result calls for a fundamental revision of the current theoretical picture for nonlinear rheological behavior of entangled polymeric liquids.
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...... the influence of spectral properties and dimensionality of the molecular system on the algorithm efficiency. We test two algorithms, the MinMax and Lanczos, for spectral estimation from an MD trajectory, and use this to derive a practical scheme of time step adaptation in MD relaxation algorithms to improve...
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.
Caron, L.; Métivier, L.; Greff-Lefftz, M.; Fleitout, L.; Rouby, H.
2017-05-01
Glacial Isostatic Adjustment (GIA) models commonly assume a mantle with a viscoelastic Maxwell rheology and a fixed ice history model. Here, we use a Bayesian Monte Carlo approach with a Markov chain formalism to invert the global GIA signal simultaneously for the mechanical properties of the mantle and the volumes of the ice sheets, using as starting ice models two previously published ice histories. Two stress relaxing rheologies are considered: Burgers and Maxwell linear viscoelasticities. A total of 5720 global palaeo sea level records are used, covering the last 35 kyr. Our goal is not only to seek the model best fitting this data set, but also to determine and display the range of possible solutions with their respective probability of explaining the data. In all cases, our a posteriori probability maps exhibit the classic character of solutions for GIA-determined mantle viscosity with two distinct peaks. What is new in our treatment is the presence of the bi-viscous Burgers rheology and the fact that we invert rheology jointly with ice history, in combination with the greatly expanded palaeo sea level records. The solutions tend to be characterized by an upper-mantle viscosity of around 5 × 1020 Pa s with one preferred lower-mantle viscosities at 3 × 1021 Pa s and the other more than 2 × 1022 Pa s, a rather classical pairing. Best-fitting models depend upon the starting ice history and the stress relaxing law. A first peak (P1) has the highest probability only in the case with a Maxwell rheology and ice history based on ICE-5G, while the second peak (P2) is favoured for ANU-based ice history or Burgers stress relaxation. The latter solution also may satisfy lower-mantle viscosity inferences from long-term geodynamics and gravity gradient anomalies over Laurentia. P2 is also consistent with large Laurentian and Fennoscandian ice-sheet volumes at the Last Glacial Maximum (LGM) and smaller LGM Antarctic ice volume than in either ICE-5G or ANU. Exploration of
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.
Thermal relaxation of molecular oxygen in collisions with nitrogen atoms.
Andrienko, Daniil A; Boyd, Iain D
2016-07-07
Investigation of O2-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 NO2 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 N2-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
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...
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
Pérez, María Encarnación; Pol, Diego
2012-01-01
Caviidae is a diverse group of caviomorph rodents that is broadly distributed in South America and is divided into three highly divergent extant lineages: Caviinae (cavies), Dolichotinae (maras), and Hydrochoerinae (capybaras). The fossil record of Caviidae is only abundant and diverse since the late Miocene. Caviids belongs to Cavioidea sensu stricto (Cavioidea s.s.) that also includes a diverse assemblage of extinct taxa recorded from the late Oligocene to the middle Miocene of South America ("eocardiids"). A phylogenetic analysis combining morphological and molecular data is presented here, evaluating the time of diversification of selected nodes based on the calibration of phylogenetic trees with fossil taxa and the use of relaxed molecular clocks. This analysis reveals three major phases of diversification in the evolutionary history of Cavioidea s.s. The first two phases involve two successive radiations of extinct lineages that occurred during the late Oligocene and the early Miocene. The third phase consists of the diversification of Caviidae. The initial split of caviids is dated as middle Miocene by the fossil record. This date falls within the 95% higher probability distribution estimated by the relaxed Bayesian molecular clock, although the mean age estimate ages are 3.5 to 7 Myr older. The initial split of caviids is followed by an obscure period of poor fossil record (referred here as the Mayoan gap) and then by the appearance of highly differentiated modern lineages of caviids, which evidentially occurred at the late Miocene as indicated by both the fossil record and molecular clock estimates. The integrated approach used here allowed us identifying the agreements and discrepancies of the fossil record and molecular clock estimates on the timing of the major events in cavioid evolution, revealing evolutionary patterns that would not have been possible to gather using only molecular or paleontological data alone.
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.
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
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...
Magallón, Susana
2010-07-01
Long branches are potentially problematic in molecular dating because they can encompass a vast number of combinations of substitution rate and time. A long branch is suspected to have biased molecular clock estimates of the age of flowering plants (angiosperms) to be much older than their earliest fossils. This study explores the effect of the long branch subtending angiosperms in molecular dating and how different relaxed clocks react to it. Fossil angiosperm relatives, identified through a combined morphological and molecular phylogenetic analysis for living and fossil seed plants, were used to break the long angiosperm stem branch. Nucleotide sequences of angiosperm fossil relatives were simulated using a phylogeny and model parameters from living taxa and incorporated in molecular dating. Three relaxed clocks, which implement among-lineage rate heterogeneity differently, were used: penalized likelihood (using 2 different rate smoothing optimization criteria), a Bayesian rate-autocorrelated method, and a Bayesian uncorrelated method. Different clocks provided highly correlated ages across the tree. Breaking the angiosperm stem branch did not result in major age differences, except for a few sensitive nodes. Breaking the angiosperm stem branch resulted in a substantially younger age for crown angiosperms only with 1 of the 4 methods, but, nevertheless, the obtained age is considerably older than the oldest angiosperm fossils. The origin of crown angiosperms is estimated between the Upper Triassic and the early Permian. The difficulty in estimating crown angiosperm age probably lies in a combination of intrinsic and extrinsic complicating factors, including substantial molecular rate heterogeneity among lineages and through time. A more adequate molecular dating approach might combine moderate background rate heterogeneity with large changes in rate at particular points in the tree.
Accelerating convergence of molecular dynamics-based structural relaxation
DEFF Research Database (Denmark)
Christensen, Asbjørn
2005-01-01
the influence of spectral properties and dimensionality of the molecular system on the algorithm efficiency. We test two algorithms, the MinMax and Lanczos, for spectral estimation from an MD trajectory, and use this to derive a practical scheme of time step adaptation in MD relaxation algorithms to improve...... efficiency. We also discuss the implementation aspects. Secondly, we explore the final state refinement acceleration by a combination with the conjugate gradient technique, where the key ingredient is an implicit corrector step. Finally, we test the feasibility of passive Hessian matrix accumulation from...... an MD trajectory, as another route for final phase acceleration. Our suggestions may be implemented within most MD quench implementations with a few, straightforward lines of code, thus maintaining the appealing simplicity of the MD quench algorithms. In this paper, we also bridge the conceptual gap...
Spin-lattice relaxation of magnetic centers in molecular crystals at low temperature
Ho, Le Tuan Anh; Chibotaru, Liviu F.
2017-01-01
We study the spin-phonon relaxation rate of both Kramers and non-Kramers molecular magnets in strongly diluted samples at low temperature. Using the "rotational" contribution to the spin-phonon Hamiltonian, universal formulae for the relaxation rate are obtained. Intriguingly, these formulae are all entirely expressed via measurable or \\emph{ab initio} computable physical quantities. Moreover, they are also independent of the energy gaps to excited states involved in the relaxation process. T...
Molecular dynamics study on the relaxation properties of bilayered ...
Indian Academy of Sciences (India)
The influence of defects on the relaxation properties of bilayered graphene (BLG) has been studied by moleculardynamics simulation in nanometre sizes. Type and position of defects were taken into account in the calculated model. Theresults show that great changes begin to occur in the morphology after introducing ...
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.
Relaxation to the state of molecular hydrodynamics in the generalized hydrodynamics of liquids
Markiv, B.; Omelyan, I.; Tokarchuk, M.
2010-10-01
The problem of relaxation of a nonequilibrium state to the state of molecular hydrodynamics is considered for a classical system of interacting particles using the Zubarev nonequilibrium statistical operator method. The wave-vector and frequency dependencies of the dynamical structure factor and momentum-momentum transverse correlation function are investigated on the basis of the appropriate generalized transport equations. Comparison with the results of molecular hydrodynamics and molecular-dynamics simulations is given and the characteristic time intervals of the studied relaxation processes are determined.
Molecular motions in thermotropic liquid crystals studied by NMR spin-lattice relaxation
International Nuclear Information System (INIS)
Zamar, R.C.; Gonzalez, C.E.; Mensio, O.
1998-01-01
Nuclear magnetic resonance relaxation experiments with field cycling techniques proved to be a valuable tool for studying molecular motions in liquid crystals, allowing a very broad Larmor frequency variation, sufficient to separate the cooperative motions from the liquid like molecular diffusion. In new experiments combining NMR field cycling with the Jeener-Broekaert order-transfer pulse sequence, it is possible to measure the dipolar order relaxation time (T 1D ), in addition to the conventional Zeeman relaxation time (T 1Z ) in a frequency range of several decades. When applying this technique to nematic thermotropic liquid crystals, T 1D showed to depend almost exclusively on the order fluctuation of the director mechanism in the whole frequency range. This unique characteristic of T 1D makes dipolar order relaxation experiments specially useful for studying the frequency and temperature dependence of the spectral properties of the collective motions. (author)
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 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
Spin-lattice relaxation of magnetic centers in molecular crystals at low temperature
Ho, Le Tuan Anh; Chibotaru, Liviu F.
2018-01-01
We study the spin-phonon relaxation rate of both Kramers and non-Kramers molecular magnets in strongly diluted samples at low temperature. Using the "rotational" contribution to the spin-phonon Hamiltonian, universal formulas for the relaxation rate are obtained. Intriguingly, these formulas are all entirely expressed via measurable or ab initio computable physical quantities. Moreover, they are also independent of the energy gaps to excited states involved in the relaxation process. These obtained expressions for direct and Raman processes offer an easy way to determine the lowest limit of the spin-phonon relaxation of any spin system based on magnetic properties of the ground doublet only. In addition, some intriguing properties of Raman process are also found. Particularly, Raman process in Kramers system is found dependent on the magnetic field's orientation but independent of its magnitude, meanwhile, the same process in non-Kramers system is significantly reduced out of resonance, i.e., for an applied external field. Interestingly, Raman process is demonstrated to vary as T9 for both systems. Application of the theory to a recently investigated cobalt(II) complex shows that it can provide a reasonably good description for the relaxation. Based on these findings, a strategy in developing efficient single-molecule magnets by enhancing the mechanical rigidity of the molecular unit is proposed.
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
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.
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.
Ma, Qian; Dai, Jiayu; Zhao, Zengxiu
2016-10-01
The electron-ion temperature relaxation is an important non-equilibrium process in the generation of dense plasmas, particularly in Inertial Confinement Fusion. Classical molecular dynamics considers electrons as point charges, ignoring important quantum processes. We use an Electron Force Field (EFF) method to study the temperature relaxation processes, considering the nuclei as semi-classical point charges and assume electrons as Gaussian wave packets which includes the influences of the size and the radial motion of electrons. At the same time, a Pauli potential is used to describe the electronic exchange effect. At this stage, quantum effects such as exchange, tunneling can be included in this model. We compare the results from EFF and classical molecular dynamics, and find that the relaxation time is much longer with including quantum effects, which can be explained directly by the deference of collision cross sections between quantum particles and classical particles. Further, the final thermal temperature of electron and ion is different compared with classical results that the electron quantum effects cannot be neglected.
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…
Energy Technology Data Exchange (ETDEWEB)
Fattoum, A; Gmati, F; Bohli, N; Mohamed, A Belhadj [Laboratoire de Semi Conducteur et Photovoltaique, Technopole Borj Cedria, BP 95, 2050 Hammam Lif (Tunisia); Arous, M [Laboratoire des Materiaux Composites Ceramiques et Polymeres, Faculte des Sciences de Sfax (Tunisia)], E-mail: arbi_fattoum@yahoo.fr
2008-05-07
We report the results of spectral, structural and electrical investigations on plasticized polyaniline/polymethylmethacrylate blend films (PAni/PMMA), obtained by the co-dissolution method using three different molecular weights of the PMMA matrix. The use of dibuthylphtalate as a plasticizer allowed us to obtain free standing thin films. The system showed percolation behaviour with an extremely low percolation threshold, independently of the PMMA molecular weight. The ac conductivity is well described by the universal Jonscher's law. By using the dielectric modulus, we have observed a dielectric relaxation assigned to the hopping of charge carriers (polarons and bipolarons) between localized states. The characteristic frequency of this relaxation follows an Arrhenius law and the activation energy depends on the PMMA molecular weight. This relaxation is well described by a simple Debye process for the lowest PMMA molecular weight and deviates from this model when the molecular weight of the PMMA increases.
Secondary relaxations in molecular glasses and polymers studied by 2D {sup 2}H NMR
Energy Technology Data Exchange (ETDEWEB)
Micko, Bjoern; Roessler, Ernst [Experimentalphysik II, Universitaet Bayreuth (Germany); Bingemann, Dieter [Department of Chemistry, Williams College, Williamstown, MA (United States)
2008-07-01
We present a two-dimensional (2D){sup 2}H exchange NMR study, attempting to clarify the geometry of the molecular motion involved in the secondary relaxation ({beta}-process) of three glass formers: PMMA, polybutadiene and a mixture of decaline and chlorobenzene. Stimulated echo measurements of the orientational correlation function circumscribe the temperature range, in which the {beta}-process is expected to dominate the spectra. In this range we will show by comparison with the spectra of o-terphenyl, which does not show a pronounced {beta}-process, that the {beta}-process is also clearly observable in the 2D NMR spectra below and somewhat above T{sub g}, until upon further heating the structural relaxation ({alpha}-process) enters the time window of the experiment and gives rise to a convergence of the spectra. Whilst the time constants for the studied systems (obtained from dielectric spectroscopy) are very similar on the reduced temperature scale T{sub g}/T, the dielectric relaxation strength differs for each system. In contrast the 2D NMR spectra turn out to be practically identical on the T{sub g}/T scale - which implies strong similarities concerning time scale and underlying geometry of the motion. To get further insight on the reorientation angles involved, simple motional models will be compared against the spectra.
Bayesian refinement of protein structures and ensembles against SAXS data using molecular dynamics.
Shevchuk, Roman; Hub, Jochen S
2017-10-01
Small-angle X-ray scattering is an increasingly popular technique used to detect protein structures and ensembles in solution. However, the refinement of structures and ensembles against SAXS data is often ambiguous due to the low information content of SAXS data, unknown systematic errors, and unknown scattering contributions from the solvent. We offer a solution to such problems by combining Bayesian inference with all-atom molecular dynamics simulations and explicit-solvent SAXS calculations. The Bayesian formulation correctly weights the SAXS data versus prior physical knowledge, it quantifies the precision or ambiguity of fitted structures and ensembles, and it accounts for unknown systematic errors due to poor buffer matching. The method further provides a probabilistic criterion for identifying the number of states required to explain the SAXS data. The method is validated by refining ensembles of a periplasmic binding protein against calculated SAXS curves. Subsequently, we derive the solution ensembles of the eukaryotic chaperone heat shock protein 90 (Hsp90) against experimental SAXS data. We find that the SAXS data of the apo state of Hsp90 is compatible with a single wide-open conformation, whereas the SAXS data of Hsp90 bound to ATP or to an ATP-analogue strongly suggest heterogenous ensembles of a closed and a wide-open state.
Bayesian comparison of Markov models of molecular dynamics with detailed balance constraint
Bacallado, Sergio; Chodera, John D.; Pande, Vijay
2009-07-01
Discrete-space Markov models are a convenient way of describing the kinetics of biomolecules. The most common strategies used to validate these models employ statistics from simulation data, such as the eigenvalue spectrum of the inferred rate matrix, which are often associated with large uncertainties. Here, we propose a Bayesian approach, which makes it possible to differentiate between models at a fixed lag time making use of short trajectories. The hierarchical definition of the models allows one to compare instances with any number of states. We apply a conjugate prior for reversible Markov chains, which was recently introduced in the statistics literature. The method is tested in two different systems, a Monte Carlo dynamics simulation of a two-dimensional model system and molecular dynamics simulations of the terminally blocked alanine dipeptide.
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.
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.
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.
Pérez, Paulino; de Los Campos, Gustavo; Crossa, José; Gianola, Daniel
2010-01-01
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 unifi ed 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.
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.
Magnetic properties and proton spin-lattice relaxation in molecular clusters
International Nuclear Information System (INIS)
Allalen, M.
2006-01-01
In this work we studied magnetic properties of molecular magnets of the new heteropolyanion {Cu 20 }, dodecanuclear cluster {Ni 12 }, and the heterometallic {Cr 7 M} wheels, in which one of the Cr III ions of Cr 8 has been replaced by a Fe, Cu, Zn, Ni, ion with this extra-spin acts as local probe for the spin dynamics. Such systems have been synthesized recently and they are well described using the Heisenberg spin Hamiltonian with a Zeeman term of an applied magnetic field along the z-axis. Using the numerical exact diagonalization method, we have calculated the energy spectrum and the eigenstates for different compounds, and we have used them for reexamining the available experimental susceptibility data to determine the values of exchange parameters. We have studied the thermodynamic properties such magnetization, susceptibility, heat-capacity. At low temperature regions molecular magnets act as individual quantum nanomagnets and can display super-paramagnetic phenomena like macroscopic quantum tunneling, ground state degeneracy, level-crossing. A crucial issue for understanding these phenomena is the coupling between magnetic molecular levels and the environment such as nuclear spins. We have modeled the behavior of the proton spin lattice relaxation rate as a function of applied magnetic field for low temperatures as it is measured in Nuclear Magnetic Resonance (NMR) experiments. (orig.)
Accounting for calibration uncertainty: Bayesian molecular dating as a "doubly intractable" problem.
Guindon, Stéphane
2018-01-27
This study introduces a new Bayesian technique for molecular dating that explicitly accommodates for uncertainty in the phylogenetic position of calibrated nodes derived from the analysis of fossil data. The proposed approach thus defines an adequate framework for incorporating expert knowledge and/or prior information about the way fossils were collected in the inference of node ages. Although it belongs to the class of "node-dating" methods, this method shares interesting properties with "tip-dating" techniques. Yet, it alleviates some of the computational and modeling difficulties that hamper tip-dating approaches. The influence of fossil data on the probabilistic distribution of trees is the crux of the matter considered here. More specifically, among all the phylogenies that a tree model (e.g., the birth death process) generates, only a fraction of them "agree" with the fossil data. Bayesian inference under the new model requires taking this fraction into account. However, evaluating this quantity is difficult in practice. A generic solution to this issue is presented here. The proposed approach relies on a recent statistical technique, the so-called exchange algorithm, dedicated to drawing samples from "doubly intractable" distributions. A small example illustrates the problem of interest and the impact of uncertainty in the placement of calibration constraints in the phylogeny given fossil data. An analysis of land plant sequences and multiple fossils further highlights the pertinence of the proposed approach. © The Author(s) 2018. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
Karasawa, N.; Mitsutake, A.; Takano, H.
2017-12-01
Proteins implement their functionalities when folded into specific three-dimensional structures, and their functions are related to the protein structures and dynamics. Previously, we applied a relaxation mode analysis (RMA) method to protein systems; this method approximately estimates the slow relaxation modes and times via simulation and enables investigation of the dynamic properties underlying the protein structural fluctuations. Recently, two-step RMA with multiple evolution times has been proposed and applied to a slightly complex homopolymer system, i.e., a single [n ] polycatenane. This method can be applied to more complex heteropolymer systems, i.e., protein systems, to estimate the relaxation modes and times more accurately. In two-step RMA, we first perform RMA and obtain rough estimates of the relaxation modes and times. Then, we apply RMA with multiple evolution times to a small number of the slowest relaxation modes obtained in the previous calculation. Herein, we apply this method to the results of principal component analysis (PCA). First, PCA is applied to a 2-μ s molecular dynamics simulation of hen egg-white lysozyme in aqueous solution. Then, the two-step RMA method with multiple evolution times is applied to the obtained principal components. The slow relaxation modes and corresponding relaxation times for the principal components are much improved by the second RMA.
Foster, Jonathan B.; Mandel, Kaisey S.; Pineda, Jaime E.; Covey, Kevin R.; Arce, Héctor G.; Goodman, Alyssa A.
2013-01-01
We investigate the shape of the extinction law in two 1° square fields of the Perseus molecular cloud complex. We combine deep red-optical (r, i and z band) observations obtained using Megacam on the MMT with UKIRT (United Kingdom Infrared Telescope) Infrared Deep Sky Survey near-infrared (J, H and K band) data to measure the colours of background stars. We develop a new hierarchical Bayesian statistical model, including measurement error, intrinsic colour variation, spectral type and dust reddening, to simultaneously infer parameters for individual stars and characteristics of the population. We implement an efficient Markov chain Monte Carlo algorithm utilizing generalized Gibbs sampling to compute coherent probabilistic inferences. We find a strong correlation between the extinction (AV) and the slope of the extinction law (parametrized by RV). Because the majority of the extinction towards our stars comes from the Perseus molecular cloud, we interpret this correlation as evidence of grain growth at moderate optical depths. The extinction law changes from the `diffuse' value of RV ˜ 3 to the `dense cloud' value of RV ˜ 5 as the column density rises from AV = 2 to 10 mag. This relationship is similar for the two regions in our study, despite their different physical conditions, suggesting that dust grain growth is a fairly universal process.
Uncovering Molecular Relaxation Processes with Nonlinear Spectroscopies in the Deep UV
West, Brantley Andrew
Conical intersections mediate internal conversion dynamics that compete with even the fastest nuclear motions in molecular systems. Traditional kinetic models do not apply in this regime of commensurate electronic and nuclear motion because the surroundings do not maintain equilibrium throughout the relaxation process. This dissertation focuses on uncovering the physics associated with vibronic interactions at conical intersections. Of particular interest are coherent nuclear motions driven by steep excited state potential energy gradients. Technical advances have only recently made these dynamics accessible in many systems including DNA nucleobases and cyclic polyene molecules. Optical analogues of multidimensional NMR spectroscopies have recently yielded transformative insight in relaxation processes ranging from energy transfer in photosynthesis to bond making and breaking in liquids. Prior to the start of this research, such experiments had only been conducted at infrared and visible wavelengths. Applications in the ultraviolet were motivated by studies of numerous biological systems (e.g., DNA, proteins), but had been challenged by technical issues. The work presented in this dissertation combines pulse generation techniques developed in the optical physics community with spectroscopic techniques largely pioneered by physical chemists to implement two-dimensional ultraviolet spectroscopy (2DUV). This technique is applied at the shortest wavelengths and with the best signal-to-noise ratios reported to date. Sub-picosecond excited state deactivation processes provide photo stability to the DNA double helix. Vibrational energy transfer from the solute to surrounding solvent enables relaxation of the highly non-equilibrium ground state produced by fast internal conversion. In this dissertation, nonlinear spectroscopies carried out at cryogenic temperatures are used to uncover the particular nuclear modes in the solvent that primarily accept vibrational energy from
Magnetocaloric effect in Mn2-pyrazole-[Nb(CN)8] molecular magnet by relaxation calorimetry
Pełka, R.; Gajewski, M.; Miyazaki, Y.; Yamashita, S.; Nakazawa, Y.; Fitta, M.; Pinkowicz, D.; Sieklucka, B.
2016-12-01
Magnetocaloric effect in {[Mn(pyrazole)4]2[Nb(CN)8]·4 H2O}n molecular magnet is reported. It crystallizes in tetragonal I41/a space group. The compound exhibits a phase transition to a long range magnetically ordered state at TN ≈ 22.8 K. Temperature dependences of the magnetic entropy change ΔSM as well as the adiabatic temperature change ΔTad due to applied field change μ0 ΔH in the range of 0.1-9 T have been inferred from the relaxation calorimetry measurements. A systematic approximate approach has been used to determine the lattice contribution to the heat capacity. The maximum value of ΔSM for μ0 ΔH = 5 T is 6.83 J mol-1 K-1 (6.65 J kg-1 K-1) at 24.3 K. The corresponding maximum value of ΔTad is 1.4 K at 23.8 K. The temperature dependence of the exponent n characterizing the field dependence of ΔSM has been estimated. It attains the value of 0.64 at the transition temperature, which is consistent with the 3D Heisenberg universality class. A hitherto unobserved two-peak structure has been revealed in the temperature dependence of ΔTad.
Lanier, Hayley C; Olson, Link E
2009-10-01
Although several studies have recently addressed phylogenetic relationships among Asian pikas (Ochotona spp.), the North American species have been relatively neglected and their monophyly generally unquestioned or assumed. Given the high degree of intraspecific diversity in pelage and call structure, the recent identification of previously unrecognized species of pika in Asia, and the increasing evidence for multiple trans-Beringian dispersals in several small mammal lineages, the monophyly of North American pikas warrants reexamination. In addition, previous studies have applied an externally calibrated rate to examine the timing of diversification within the genus. This method has been increasingly shown to return results that, at the very least, are overly narrow in their confidence intervals, and at the worst can be entirely spurious. For this study we combined GenBank sequences from the mitochondrial genes cyt b and ND4 with newly generated sequence data from O. hyperborea and O. collaris to investigate the origin of the North American lineages and the timing of phylogenetic diversification within the genus Ochotona. Specifically, we address three goals (1) summarize and reanalyze the molecular evidence for relationships within the genus using statistically supported models of evolution; (2) add additional sequences from O. collaris and O. hyperborea to rigorously test the monophyly of North American pikas; (3) examine the timing of the diversification within the genus using relaxed molecular clock methods. We found no evidence of multiple trans-Beringian dispersals into North America, thereby supporting the traditional hypothesis of a single invasion of North America. We also provide evidence that the major splits within the genus occurred in the Miocene, and the Nearctic pikas diverged sometime before the Pleistocene.
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.
Relaxed molecular clock provides evidence for long-distance dispersal of Nothofagus (southern beech.
Directory of Open Access Journals (Sweden)
Michael Knapp
2005-01-01
Full Text Available Nothofagus (southern beech, with an 80-million-year-old fossil record, has become iconic as a plant genus whose ancient Gondwanan relationships reach back into the Cretaceous era. Closely associated with Wegener's theory of "Kontinentaldrift", Nothofagus has been regarded as the "key genus in plant biogeography". This paradigm has the New Zealand species as passengers on a Moa's Ark that rafted away from other landmasses following the breakup of Gondwana. An alternative explanation for the current transoceanic distribution of species seems almost inconceivable given that Nothofagus seeds are generally thought to be poorly suited for dispersal across large distances or oceans. Here we test the Moa's Ark hypothesis using relaxed molecular clock methods in the analysis of a 7.2-kb fragment of the chloroplast genome. Our analyses provide the first unequivocal molecular clock evidence that, whilst some Nothofagus transoceanic distributions are consistent with vicariance, trans-Tasman Sea distributions can only be explained by long-distance dispersal. Thus, our analyses support the interpretation of an absence of Lophozonia and Fuscospora pollen types in the New Zealand Cretaceous fossil record as evidence for Tertiary dispersals of Nothofagus to New Zealand. Our findings contradict those from recent cladistic analyses of biogeographic data that have concluded transoceanic Nothofagus distributions can only be explained by vicariance events and subsequent extinction. They indicate that the biogeographic history of Nothofagus is more complex than envisaged under opposing polarised views expressed in the ongoing controversy over the relevance of dispersal and vicariance for explaining plant biodiversity. They provide motivation and justification for developing more complex hypotheses that seek to explain the origins of Southern Hemisphere biota.
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
Viswanath, Shruthi; Bonomi, Massimiliano; Kim, Seung Joong; Klenchin, Vadim A; Taylor, Keenan C; Yabut, King C; Umbreit, Neil T; Van Epps, Heather A; Meehl, Janet; Jones, Michele H; Russel, Daniel; Velazquez-Muriel, Javier A; Winey, Mark; Rayment, Ivan; Davis, Trisha N; Sali, Andrej; Muller, Eric G
2017-11-07
Microtubule-organizing centers (MTOCs) form, anchor, and stabilize the polarized network of microtubules in a cell. The central MTOC is the centrosome that duplicates during the cell cycle and assembles a bipolar spindle during mitosis to capture and segregate sister chromatids. Yet, despite their importance in cell biology, the physical structure of MTOCs is poorly understood. Here we determine the molecular architecture of the core of the yeast spindle pole body (SPB) by Bayesian integrative structure modeling based on in vivo fluorescence resonance energy transfer (FRET), small-angle x-ray scattering (SAXS), x-ray crystallography, electron microscopy, and two-hybrid analysis. The model is validated by several methods that include a genetic analysis of the conserved PACT domain that recruits Spc110, a protein related to pericentrin, to the SPB. The model suggests that calmodulin can act as a protein cross-linker and Spc29 is an extended, flexible protein. The model led to the identification of a single, essential heptad in the coiled-coil of Spc110 and a minimal PACT domain. It also led to a proposed pathway for the integration of Spc110 into the SPB. © 2017 Viswanath, Bonomi, et al. This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).
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.
Influence of hydroxypropyl cellulose on molecular relaxations of epoxy-amine networks
Directory of Open Access Journals (Sweden)
Maria Inez G. Miranda
2013-01-01
Full Text Available A dynamic mechanical analysis (DMTA study was conducted on epoxy-amine networks crosslinked in the presence of low contents of hydroxypropyl cellulose (HPC. The epoxy resin chosen was diglycidylether of bisphenol-A (DGEBA and the crosslinker was 4,4'-diaminodiphenylmethane (DDM. In the glassy region, primary (α and secondary (β, γ relaxations originating from the epoxy and HPC components were well detected. Two primary relaxations of neat epoxy and epoxy/HPC systems, referred to as αepoxy and α'epoxy, could be detected, showing a particular glassy behavior for the systems studied in comparison with systems cured in bulk. The main relaxation temperature Tα (at the peak of αepoxy relaxation of the epoxy systems increased slightly with the addition of HPC. The activation energy for this transition (Tα of the epoxy-amine networks was determined both from tan δ and the peak temperatures for the loss modulus measured at various frequencies. The activation energy of the αepoxy relaxation determined from the loss modulus was more reliable than that based on tan δ. The addition of HPC lowered the activation energy of this αepoxy relaxation.
Energy Technology Data Exchange (ETDEWEB)
Bazioti, C.; Kehagias, Th.; Pavlidou, E.; Komninou, Ph.; Karakostas, Th.; Dimitrakopulos, G. P., E-mail: gdim@auth.gr [Physics Department, Aristotle University of Thessaloniki, GR 541 24 Thessaloniki (Greece); Papadomanolaki, E.; Iliopoulos, E. [Microelectronics Research Group (MRG), IESL, FORTH, P.O. Box 1385, 71110 Heraklion Crete, Greece and Physics Department, University of Crete, Heraklion Crete (Greece); Walther, T. [Department of Electronic & Electrical Engineering, University of Sheffield, Sheffield S1 3JD (United Kingdom); Smalc-Koziorowska, J. [Institute of High Pressure Physics, Polish Academy of Sciences, Sokolowska 29/37, 01-142 Warsaw (Poland)
2015-10-21
We investigate the structural properties of a series of high alloy content InGaN epilayers grown by plasma-assisted molecular beam epitaxy, employing the deposition temperature as variable under invariant element fluxes. Using transmission electron microscopy methods, distinct strain relaxation modes were observed, depending on the indium content attained through temperature adjustment. At lower indium contents, strain relaxation by V-pit formation dominated, with concurrent formation of an indium-rich interfacial zone. With increasing indium content, this mechanism was gradually substituted by the introduction of a self-formed strained interfacial InGaN layer of lower indium content, as well as multiple intrinsic basal stacking faults and threading dislocations in the rest of the film. We show that this interfacial layer is not chemically abrupt and that major plastic strain relaxation through defect introduction commences upon reaching a critical indium concentration as a result of compositional pulling. Upon further increase of the indium content, this relaxation mode was again gradually succeeded by the increase in the density of misfit dislocations at the InGaN/GaN interface, leading eventually to the suppression of the strained InGaN layer and basal stacking faults.
Rheinstädter, Maikel C; Seydel, Tilo; Salditt, Tim
2007-01-01
We report a high energy-resolution neutron backscattering study to investigate slow motions on nanosecond time scales in highly oriented solid-supported phospholipid bilayers of the model system deuterated 1,2-dimyristoyl-sn-glycero-3-phosphatidylcholine, hydrated with heavy water. Wave-vector-resolved quasielastic neutron scattering is used to determine relaxation times tau , which can be associated with different molecular components, i.e., the lipid acyl chains and the interstitial water molecules in the different phases of the model membrane system. The inelastic data are complemented by both energy-resolved and energy-integrated in situ diffraction. From a combined analysis of the inelastic data in the energy and time domains, the corresponding character of the relaxation, i.e., the exponent of the exponential decay, is also determined. From this analysis we quantify two relaxation processes. We associate the fast relaxation with translational diffusion of lipid and water molecules while the slow process likely stems from collective dynamics.
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.
Bibi, F; Vrba, E; Fack, F
2012-09-01
Given that most species that have ever existed on Earth are extinct, no evolutionary history can ever be complete without the inclusion of fossil taxa. Bovids (antelopes and relatives) are one of the most diverse clades of large mammals alive today, with over a hundred living species and hundreds of documented fossil species. With the advent of molecular phylogenetics, major advances have been made in the phylogeny of this clade; however, there has been little attempt to integrate the fossil record into the developing phylogenetic picture. We here describe a new large fossil caprin species from ca. 1.9-Ma deposits from the Middle Awash, Ethiopia. To place the new species phylogenetically, we perform a Bayesian analysis of a combined molecular (cytochrome b) and morphological (osteological) character supermatrix. We include all living species of Caprini, the new fossil species, a fossil takin from the Pliocene of Ethiopia (Budorcas churcheri), and the insular subfossil Myotragus balearicus. The combined analysis demonstrates successful incorporation of both living and fossil species within a single phylogeny based on both molecular and morphological evidence. Analysis of the combined supermatrix produces superior resolution than with either the molecular or morphological data sets considered alone. Parsimony and Bayesian analyses of the data set are also compared and shown to produce similar results. The combined phylogenetic analysis indicates that the new fossil species is nested within Capra, making it one of the earliest representatives of this clade, with implications for molecular clock calibration. Geographical optimization indicates no less than four independent dispersals into Africa by caprins since the Pliocene. © 2012 The Authors. Journal of Evolutionary Biology © 2012 European Society For Evolutionary Biology.
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.
Miyashita, Naoyuki; Yonezawa, Yasushige
2017-09-01
Robust and reliable analyses of long trajectories from molecular dynamics simulations are important for investigations of functions and mechanisms of proteins. Structural fitting is necessary for various analyses of protein dynamics, thus removing time-dependent translational and rotational movements. However, the fitting is often difficult for highly flexible molecules. Thus, to address the issues, we proposed a fitting algorithm that uses the Bayesian inference method in combination with rotational fitting-weight improvements, and the well-studied globular protein systems trpcage and lysozyme were used for investigations. The present method clearly identified rigid core regions that fluctuate less than other regions and also separated core regions from highly fluctuating regions with greater accuracy than conventional methods. Our method also provided simultaneous variance-covariance matrix elements composed of atomic coordinates, allowing us to perform principle component analysis and prepare domain cross-correlation map during molecular dynamics simulations in an on-the-fly manner.
Strain relaxation in single crystal SrTiO3 grown on Si (001) by molecular beam epitaxy
International Nuclear Information System (INIS)
Choi, Miri; Posadas, Agham; Dargis, Rytis; Shih, Chih-Kang; Demkov, Alexander A.; Triyoso, Dina H.; David Theodore, N.; Dubourdieu, Catherine; Bruley, John; Jordan-Sweet, Jean
2012-01-01
An epitaxial layer of SrTiO 3 grown directly on Si may be used as a pseudo-substrate for the integration of perovskite oxides onto silicon. When SrTiO 3 is initially grown on Si (001), it is nominally compressively strained. However, by subsequent annealing in oxygen at elevated temperature, an SiO x interlayer can be formed which alters the strain state of SrTiO 3 . We report a study of strain relaxation in SrTiO 3 films grown on Si by molecular beam epitaxy as a function of annealing time and oxygen partial pressure. Using a combination of x-ray diffraction, reflection high energy electron diffraction, and transmission electron microscopy, we describe the process of interfacial oxidation and strain relaxation of SrTiO 3 on Si (001). Understanding the process of strain relaxation of SrTiO 3 on silicon will be useful for controlling the SrTiO 3 lattice constant for lattice matching with functional oxide overlayers.
Ha, Min Young; Choi, Garam; Kim, Dong Hyun; Kim, Hyo Seok; Park, Sang Hyun; Lee, Won Bo
2017-07-01
This work studied the computational details of the Green-Kubo method with molecular dynamics (MD) simulation for thermal conductivity prediction. In MD thermal conductivity calculation, little consensus has been made about the inclusion of zero-pressure volume relaxation in the isobaric-isothermal (NpT) ensemble, which determines the simulation lattice parameters. Simulations of fcc-based structures with different lattice parameters were performed to calculate lattice thermal conductivities and phonon density of states, and the results were compared to experimental reports and ab initio results to conclude that NpT volume relaxation is crucial for accurate prediction of thermal conductivity. In addition, the relation between thermal conductivity and interatomic potential cutoff distance was also analysed in the context of lattice relaxation. The results suggested that calculated thermal conductivity is strictly dependent on the lattice parameter and essentially independent of the cutoff distance. It was also shown that reducing the cutoff distance can greatly accelerate the thermal conductivity calculation, even without sacrificing the accuracy of thermal conductivity.
Czech Academy of Sciences Publication Activity Database
Olžyńska, Agnieszka; Zań, Anna; Jurkiewicz, Piotr; Sýkora, Jan; Gröbner, G.; Langner, M.; Hof, Martin
2007-01-01
Roč. 147, č. 2 (2007), s. 69-77 ISSN 0009-3084 R&D Projects: GA AV ČR IAA400400503; GA ČR GA203/05/2308; GA ČR(CZ) GD203/05/H001; GA MŠk(CZ) LC06063 Grant - others:Swedish Research Council(SE) 621-2001-3185 Institutional research plan: CEZ:AV0Z40400503 Source of funding: V - iné verejné zdroje Keywords : solvent relaxation * 2H NMR * Patman * lipid hydration * unsaturated hydrocarbon chain Subject RIV: CF - Physical ; Theoretical Chemistry Impact factor: 2.396, year: 2007
Golysheva, Elena A.; Shevelev, Georgiy Yu.; Dzuba, Sergei A.
2017-08-01
In glassy substances and biological media, dynamical transitions are observed in neutron scattering that manifests itself as deviations of the translational mean-squared displacement, , of hydrogen atoms from harmonic dynamics. In biological media, the deviation occurs at two temperature intervals, at ˜100-150 K and at ˜170-230 K, and it is attributed to the motion of methyl groups in the former case and to the transition from harmonic to anharmonic or diffusive motions in the latter case. In this work, electron spin echo (ESE) spectroscopy—a pulsed version of electron paramagnetic resonance—is applied to study the spin relaxation of nitroxide spin probes and labels introduced in molecular glass former o-terphenyl and in protein lysozyme. The anisotropic contribution to the rate of the two-pulse ESE decay, ΔW, is induced by spin relaxation appearing because of restricted orientational stochastic molecular motion; it is proportional to τc, where is the mean-squared angle of reorientation of the nitroxide molecule around the equilibrium position and τc is the correlation time of reorientation. The ESE time window allows us to study motions with τc τc temperature dependence shows a transition near 240 K, which is in agreement with the literature data on . For spin probes of essentially different size, the obtained data were found to be close, which evidences that motion is cooperative, involving a nanocluster of several neighboring molecules. For the dry lysozyme, the τc values below 260 K were found to linearly depend on the temperature in the same way as it was observed in neutron scattering for . As spin relaxation is influenced only by stochastic motion, the harmonic motions seen in ESE must be overdamped. In the hydrated lysozyme, ESE data show transitions near 130 K for all nitroxides, near 160 K for the probe located in the hydration layer, and near 180 K for the label in the protein interior. For this system, the two latter transitions are not
Thornhill, Andrew H; Popple, Lindsay W; Carter, Richard J; Ho, Simon Y W; Crisp, Michael D
2012-04-01
The identification and application of reliable fossil calibrations represents a key component of many molecular studies of evolutionary timescales. In studies of plants, most paleontological calibrations are associated with macrofossils. However, the pollen record can also inform age calibrations if fossils matching extant pollen groups are found. Recent work has shown that pollen of the myrtle family, Myrtaceae, can be classified into a number of morphological groups that are synapomorphic with molecular groups. By assembling a data matrix of pollen morphological characters from extant and fossil Myrtaceae, we were able to measure the fit of 26 pollen fossils to a molecular phylogenetic tree using parsimony optimisation of characters. We identified eight Myrtaceidites fossils as appropriate for calibration based on the most parsimonious placements of these fossils on the tree. These fossils were used to inform age constraints in a Bayesian phylogenetic analysis of a sequence alignment comprising two sequences from the chloroplast genome (matK and ndhF) and one nuclear locus (ITS), sampled from 106 taxa representing 80 genera. Three additional analyses were calibrated by placing pollen fossils using geographic and morphological information (eight calibrations), macrofossils (five calibrations), and macrofossils and pollen fossils in combination (12 calibrations). The addition of new fossil pollen calibrations led to older crown ages than have previously been found for tribes such as Eucalypteae and Myrteae. Estimates of rate variation among lineages were affected by the choice of calibrations, suggesting that the use of multiple calibrations can improve estimates of rate heterogeneity among lineages. This study illustrates the potential of including pollen-based calibrations in molecular studies of divergence times. Copyright Â© 2011 Elsevier Inc. All rights reserved.
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
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...
Xu, Yao; Gnanasekaran, Ramachandran; Leitner, David
2012-02-01
The first step in the photocycle of many proteins involves conformational change of a chromophore or a charge transfer reaction following photoexcitation. To explore the response of the protein and solvent environment to photoexcitation of the chromophore in photoactive yellow protein (PYP) and green fluorescent protein (GFP) we carried out molecular dynamics simulations of the dielectric response and vibrational energy relaxation (VER) from the chromophore to the protein and solvent. In PYP the time scale of the protein response, mainly contributed by Tyr42 and Glu46, to photoexcitation appears prominently between 0.1 and 0.3 picoseconds. The frequency-dependent VER rate also reveals dynamic coupling between the chromophore and residues that hydrogen bond to it. Resonances in the VER rate appear at frequencies comparable to the oscillations observed in recent fluorescence decay studies. In GFP, which undergoes excited state proton transfer about 10 ps following photoexcitation that may be assisted by specific chromophore vibrations, both the protein and water molecules inside the β-barrel surrounding the chromophore mediate the dielectric response.
Allen, Jesse J; Bowser, Sage R; Damodaran, Krishnan
2014-05-07
Interactions of ionic liquids (ILs) with water are of great interest for many potential IL applications. 1-Ethyl-3-methylimidazolium (emim) acetate, in particular, has shown interesting interactions with water including hydrogen bonding and even chemical exchange. Previous studies have shown the unusual behavior of emim acetate when in the presence of 0.43 mole fraction of water, and a combination of NMR techniques is used herein to investigate the emim acetate-water system and the unusual behavior at 0.43 mole fraction of water. NMR relaxometry techniques are used to describe the effects of water on the molecular motion and interactions of emim acetate with water. A discontinuity is seen in nuclear relaxation behavior at the concentration of 0.43 mole fraction of water, and this is attributed to the formation of a hydrogen bonded network. EXSY measurements are used to determine the exchange rates between the H2 emim proton and water, which show a complex dependence on the concentration of the mixture. The findings support and expand our previous results, which suggested the presence of an extended hydrogen bonding network in the emim acetate-water system at concentrations close to 0.50 mole fraction of H2O.
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 30.2 MHz and 28.411 MHz 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 1H are polarized in the magnetic field B0 while fluorine spins 19F 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.
Nino, Daniel; Rafiei, Nafiseh; Wang, Yong; Zilman, Anton; Milstein, Joshua N
2017-05-09
Superresolved localization microscopy has the potential to serve as an accurate, single-cell technique for counting the abundance of intracellular molecules. However, the stochastic blinking of single fluorophores can introduce large uncertainties into the final count. Here we provide a theoretical foundation for applying superresolved localization microscopy to the problem of molecular counting based on the distribution of blinking events from a single fluorophore. We also show that by redundantly tagging single molecules with multiple, blinking fluorophores, the accuracy of the technique can be enhanced by harnessing the central limit theorem. The coefficient of variation then, for the number of molecules M estimated from a given number of blinks B, scales like ∼1/N l , where N l is the mean number of labels on a target. As an example, we apply our theory to the challenging problem of quantifying the cell-to-cell variability of plasmid copy number in bacteria. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.
Aliev, A. R.; Akhmedov, I. R.; Kakagasanov, M. G.; Aliev, Z. A.; Gafurov, M. M.; Rabadanov, K. Sh.; Amirov, A. M.
2018-03-01
The processes of molecular relaxation in binary crystalline systems KNO3-KClO4, KNO3-KNO2, and K2CO3-K2SO4 are studied via differential thermal analysis and Raman spectroscopy. It is found that the relaxation time of the vibrations ν1( A) of anions NO- 3 and CO2- 3 in systems KNO3-KClO4, KNO3-KNO2, and K2CO3-K2SO4 is less than that in KNO3 and K2CO3, respectively. It is shown that the increased rate of relaxation is explained by an additional relaxation mechanism presented in the system. This mechanism is associated with the excitation of vibrations of anions ClO- 4, NO- 2, and SO2- 4 and the lattice phonons that emerge. It is found that this relaxation mechanism requires correspondence of the frequency difference of these vibrations to the region of sufficiently high density of states of the phonon spectrum.
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.
Vibrational relaxation of a triatomic molecular impurity: D{sub 2}O in vitreous As{sub 2}S{sub 3}
Energy Technology Data Exchange (ETDEWEB)
Rella, C.W.; Schwettman, H.A. [Stanford Univ., CA (United States); Engholm, J.R. [Univ. of Georgia, Athens, GA (United States)] [and others
1995-12-31
Measurements of the relaxation of the D{sub 2}O stretch mode in vitreous As{sub 2}S{sub 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{sub 2}O molecule is more complex than that of diatomic molecules. The asymmetric stretch mode of D{sub 2}O has a frequency of 2680 cm{sup -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{sub 2}O concentration. A rapid relaxation rate on the order of 5 x 10{sup 9} sec{sup -1} at low temperature is found that increases with temperature. Recalling that the bending mode of the D{sub 2}O molecule has a frequency of 1170 cm{sup -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{sup -1}, which coincides with a fundamental frequency of the pyramidal building blocks of the glassy As{sub 2}S{sub 3} host. Instead, we find from the temperature dependence of the relaxation rate that the D{sub 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.
Trombitás, K; Wu, Y; McNabb, M; Greaser, M; Kellermayer, M S Z; Labeit, S; Granzier, H
2003-11-01
Titin (also known as connectin) is the main determinant of physiological levels of passive muscle force. This force is generated by the extensible I-band region of the molecule, which is constructed of the PEVK domain and tandem-immunoglobulin segments comprising serially linked immunoglobulin (Ig)-like domains. It is unresolved whether under physiological conditions Ig domains remain folded and act as "spacers" that set the sarcomere length at which the PEVK extends or whether they contribute to titin's extensibility by unfolding. Here we focused on whether Ig unfolding plays a prominent role in stress relaxation (decay of force at constant length after stretch) using mechanical and immunolabeling studies on relaxed human soleus muscle fibers and Monte Carlo simulations. Simulation experiments using Ig-domain unfolding parameters obtained in earlier single-molecule atomic force microscopy experiments recover the phenomenology of stress relaxation and predict large-scale unfolding in titin during an extended period (> approximately 20 min) of relaxation. By contrast, immunolabeling experiments failed to demonstrate large-scale unfolding. Thus, under physiological conditions in relaxed human soleus fibers, Ig domains are more stable than predicted by atomic force microscopy experiments. Ig-domain unfolding did not become more pronounced after gelsolin treatment, suggesting that the thin filament is unlikely to significantly contribute to the mechanical stability of the domains. We conclude that in human soleus fibers, Ig unfolding cannot solely explain stress relaxation.
Trombitás, K.; Wu, Y.; McNabb, M.; Greaser, M.; Kellermayer, M. S. Z.; Labeit, S.; Granzier, H.
2003-01-01
Titin (also known as connectin) is the main determinant of physiological levels of passive muscle force. This force is generated by the extensible I-band region of the molecule, which is constructed of the PEVK domain and tandem-immunoglobulin segments comprising serially linked immunoglobulin (Ig)-like domains. It is unresolved whether under physiological conditions Ig domains remain folded and act as “spacers” that set the sarcomere length at which the PEVK extends or whether they contribute to titin's extensibility by unfolding. Here we focused on whether Ig unfolding plays a prominent role in stress relaxation (decay of force at constant length after stretch) using mechanical and immunolabeling studies on relaxed human soleus muscle fibers and Monte Carlo simulations. Simulation experiments using Ig-domain unfolding parameters obtained in earlier single-molecule atomic force microscopy experiments recover the phenomenology of stress relaxation and predict large-scale unfolding in titin during an extended period (>∼20 min) of relaxation. By contrast, immunolabeling experiments failed to demonstrate large-scale unfolding. Thus, under physiological conditions in relaxed human soleus fibers, Ig domains are more stable than predicted by atomic force microscopy experiments. Ig-domain unfolding did not become more pronounced after gelsolin treatment, suggesting that the thin filament is unlikely to significantly contribute to the mechanical stability of the domains. We conclude that in human soleus fibers, Ig unfolding cannot solely explain stress relaxation. PMID:14581214
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.
Relaxation in magnetic nanostructures
International Nuclear Information System (INIS)
Novak, M.A.; Folly, W.S.D.; Sinnecker, J.P.; Soriano, S.
2005-01-01
Nanostructured magnetic materials present a wide range of magnetic relaxation phenomena. One problem in studying nanomagnetic granular materials is the strong dependence of the relaxation with the anisotropy barrier which, even for systems with narrow size distributions, brings difficulties in the analysis of the experimental data. Molecular magnetism, with the chemists' bottom-up approach to build molecular nanostructures, provides this field with some beautiful model systems, well ordered crystals of single molecule magnets, single molecule chains, molecular magnetic multilayers and others novelties to appear. Most of these systems present slow relaxation and the study of these well-characterized nanomaterials may elucidate many features that are difficult to grasp in the non molecular materials
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
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
Direct and two-phonon Orbach-Aminov type spin-lattice relaxation in molecular magnet V15
Tarantul, Alex; Tsukerblat, Boris
2011-10-01
In this article we propose a model of spin-phonon relaxation in K6[VIV 15As6O42(H2O)]-8H2O, the so called V15 cluster exhibiting the unique layered magnetic structure. The work is motivated by the recent observation of the Rabi oscillation [1] in this system and aimed to elucidate the role of spin-phonon interaction as a source of decoherence. The spin-phonon coupling is assumed to appear as a result of the modulation of the isotropic and antisymmetric (Dzyaloshinsky-Moriya) exchange interactions in the central triangular layer of vanadium ions by the acoustic lattice vibrations. The relaxation rates are estimated within the Debye model for the lattice vibrations. Within the pseudo-angular momentum representation the selection rules for the direct (one-phonon) transitions between Zeeman levels are derived and a special role of the antisymmetric exchange is underlined. The probabilities of the two-phonon Orbach-Aminov type processes are evaluated as well, while the Raman type relaxation is shown to have a negligible importance at low temperatures at which the Rabi oscillations have been detected.
Himmelmann, Lin; Metzler, Dirk
2009-09-15
For the estimation of phylogenetic trees from molecular data, it is worthwhile to take prior paleontologic knowledge into account, if available. To calibrate the branch lengths of the tree with times assigned to geo-historical events or fossils, it is necessary to select a relaxed molecular clock model to specify how mutation rates can change along the phylogeny. We present the software TreeTime for Bayesian phylogeny estimation. It can take prior information about the topology of the tree and about branching times into account. Several relaxed molecular clock models are implemented in TreeTime. TreeTime is written in C++ and designed to be efficient and extensible. TreeTime is freely available from http://evol.bio.lmu.de/statgen/software/treetime under the terms of the GNU General Public Licence (GPL, version 3 or later).
BEAST: Bayesian evolutionary analysis by sampling trees.
Drummond, Alexei J; Rambaut, Andrew
2007-11-08
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. 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. 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.
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.
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...
Indian Academy of Sciences (India)
IAS Admin
In the context of nuclear magnetic resonance (NMR), the term relaxation indicates the process by which the magnetic atomic nuclei reach thermal equilibrium with the chaotic molecular environment. In NMR, this process can be very slow, requiring between a fraction of a second to many minutes, depending on the.
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.
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
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.
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
Directory of Open Access Journals (Sweden)
Daniela Becker
2008-09-01
Full Text Available Blendas de poliamida amorfa (aPA com copolímero de estireno-acrilonitrila (SAN utilizando uma série de copolímeros de metil metacrilato-anidrido maleico (MMA-MA como agente compatibilizante foram preparadas. Estes copolímeros acrílicos são miscíveis com a fase SAN, e o anidrido maleico (MA é capaz de reagir com os grupos terminais da poliamida, levando a formação de um copolímero na interfase da blenda durante o processamento. Este estudo foca o efeito da massa molar e a concentração de anidrido maleico do compatibilizante nas propriedades de relaxação dielétrica. Os resultados mostram que tanto a concentração de anidrido maleico e a massa molar do compatibilizante influenciam a mobilidade molecular. Blendas com compatibilizantes com 5 e 10% de anidrido maleico apresentaram menor energia de ativação devido à alta mobilidade da fase SAN.Blends of amorphous polyamide (aPA with acrylonitrile/styrene copolymer (SAN using a series of methyl methacrylate-maleic anhydride (MMA-MA copolymers as compatibilizing agents were prepared. These acrylic copolymers were miscible with SAN, whereas the maleic anhydride units in the copolymers are capable to react with the polyamide end groups; this could lead to the formation of grafted copolymers at the blend interface during melt processing. This study focuses on the effects of molecular weight and concentration of the reactive maleic anhydride units of the compatibilizer on the dielectric relaxation properties. The results show that both maleic anhydride quantity and molecular weight of MMA MA influenced the dielectric relaxation properties. Blends with 5 and 10% of MA in the compatibilizer present lower activation energy due to the high mobility of SAN phase.
Magazú, S.; Migliardo, F.; Affouard, F.; Descamps, M.; Telling, M. T. F.
2010-05-01
In this work inelastic neutron scattering (INS) and quasielastic neutron scattering (QENS) data, collected at different temperature values by the OSIRIS and IRIS spectrometers at the ISIS Facility (Rutherford Appleton Laboratory, Oxford, UK) on mixtures of two glass-forming bioprotectant systems, i.e., trehalose and glycerol, as a function of concentration are presented. The data analyses show that the fast local dynamics, measured by INS, as well as the diffusive dynamics, measured by QENS, exhibit in the investigated mixtures a switching-off maximum in the same concentration range corresponding to a very low glycerol content. This effect can be accounted for by a not-ideal mixing process of the pure constituents due to an increased hydrogen bonding network strength. The experimental studies are completed by molecular dynamics simulation findings.
Nguyen, Huu Chuong; Szyja, Bartłomiej M.; Doltsinis, Nikos L.
2014-09-01
Density functional theory (DFT) based molecular dynamics simulations have been performed of a 1,4-benzenedithiol molecule attached to two gold electrodes. To model the mechanical manipulation in typical break junction and atomic force microscopy experiments, the distance between two electrodes was incrementally increased up to the rupture point. For each pulling distance, the electric conductance was calculated using the DFT nonequilibrium Green's-function approach for a statistically relevant sample of configurations extracted from the simulation. With increasing mechanical strain, the formation of monoatomic gold wires is observed. The conductance decreases by three orders of magnitude as the initial twofold coordination of the thiol sulfur to the gold is reduced to a single S-Au bond at each electrode and the order in the electrodes is destroyed. Independent of the pulling distance, the conductance was found to fluctuate by at least two orders of magnitude depending on the instantaneous junction geometry.
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.
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
Liu, Tingting; Wang, Shu; Zhu, Ming
2017-12-01
The existing molecular relaxation models based on both parallel relaxation theory and series relaxation theory cannot extract the contributions of gas compositions to acoustic relaxation absorption in mixtures. In this paper, we propose an analytical model to predict acoustic relaxation absorption and clarify composition relaxation contributions based on the rate-determining energy transfer processes in molecular relaxation in excitable gases. By combining parallel and series relaxation theory, the proposed model suggests that the vibration-translation process of the lowest vibrational mode in each composition provides the primary deexcitation path of the relaxation energy, and the rate-determining vibration-vibration processes between the lowest mode and others dominate the coupling energy transfer between different modes. Thus, each gas composition contributes directly one single relaxation process to the molecular relaxation in mixture, which can be illustrated by the decomposed acoustic relaxation absorption spectrum of the single relaxation process. The proposed model is validated by simulation results in good agreement with experimental data such as N 2 , O 2 , CO 2 , CH 4 and their mixtures.
Sour, Angélique; Jenni, Sébastien; Ortí-Suárez, Ana; Schmitt, Julie; Heitz, Valérie; Bolze, Frédéric; Loureiro de Sousa, Paulo; Po, Chrystelle; Bonnet, Célia S; Pallier, Agnès; Tóth, Éva; Ventura, Barbara
2016-05-02
A molecular theranostic agent for magnetic resonance imaging (MRI) and photodynamic therapy (PDT) consisting of four [GdDTTA](-) complexes (DTTA(4-) = diethylenetriamine-N,N,N″,N″-tetraacetate) linked to a meso-tetraphenylporphyrin core, as well as its yttrium(III) analogue, was synthesized. A variety of physicochemical methods were used to characterize the gadolinium(III) conjugate 1 both as an MRI contrast agent and as a photosensitizer. The proton relaxivity measured in H2O at 20 MHz and 25 °C, r1 = 43.7 mmol(-1) s(-1) per gadolinium center, is the highest reported for a bishydrated gadolinium(III)-based contrast agent of medium size and can be related to the rigidity of the molecule. The complex displays also a remarkable singlet oxygen quantum yield of ϕΔ = 0.45 in H2O, similar to that of a meso-tetrasulfonated porphyrin. We also evidenced the ability of the gadolinium(III) conjugate to penetrate in cancer cells with low cytotoxicity. Its phototoxicity on Hela cells was evaluated following incubation at low micromolar concentration and moderate light irradiation (21 J cm(-2)) induced 50% of cell death. Altogether, these results demonstrate the high potential of this conjugate as a theranostic agent for MRI and PDT.
2016-01-01
Over recent years, several alternative relaxed clock models have been proposed in the context of Bayesian dating. These models fall in two distinct categories: uncorrelated and autocorrelated across branches. The choice between these two classes of relaxed clocks is still an open question. More fundamentally, the true process of rate variation may have both long-term trends and short-term fluctuations, suggesting that more sophisticated clock models unfolding over multiple time scales should ultimately be developed. Here, a mixed relaxed clock model is introduced, which can be mechanistically interpreted as a rate variation process undergoing short-term fluctuations on the top of Brownian long-term trends. Statistically, this mixed clock represents an alternative solution to the problem of choosing between autocorrelated and uncorrelated relaxed clocks, by proposing instead to combine their respective merits. Fitting this model on a dataset of 105 placental mammals, using both node-dating and tip-dating approaches, suggests that the two pure clocks, Brownian and white noise, are rejected in favour of a mixed model with approximately equal contributions for its uncorrelated and autocorrelated components. The tip-dating analysis is particularly sensitive to the choice of the relaxed clock model. In this context, the classical pure Brownian relaxed clock appears to be overly rigid, leading to biases in divergence time estimation. By contrast, the use of a mixed clock leads to more recent and more reasonable estimates for the crown ages of placental orders and superorders. Altogether, the mixed clock introduced here represents a first step towards empirically more adequate models of the patterns of rate variation across phylogenetic trees. This article is part of the themed issue ‘Dating species divergences using rocks and clocks’. PMID:27325829
Marzola, Luca; Raidal, Martti
2016-11-01
Motivated by natural inflation, we propose a relaxation mechanism consistent with inflationary cosmology that explains the hierarchy between the electroweak scale and Planck scale. This scenario is based on a selection mechanism that identifies the low-scale dynamics as the one that is screened from UV physics. The scenario also predicts the near-criticality and metastability of the Standard Model (SM) vacuum state, explaining the Higgs boson mass observed at the Large Hadron Collider (LHC). Once Majorana right-handed neutrinos are introduced to provide a viable reheating channel, our framework yields a corresponding mass scale that allows for the seesaw mechanism as well as for standard thermal leptogenesis. We argue that considering singlet scalar dark matter extensions of the proposed scenario could solve the vacuum stability problem and discuss how the cosmological constant problem is possibly addressed.
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
Novikov, Vladimir P.; Tarasenko, Svetlana A.; Samdal, Svein; Vilkov, Lev V.
1998-04-01
Gas electron diffraction data are applied to determine the geometrical parameters of the 1,1-dichlorosilacyclobutane molecule using a dynamic model where the ring puckering was treated as a large amplitude motion. The structural parameters and parameters of the potential function were refined taking into account the relaxation of the molecular geometry estimated from ab initio calculations at the Hartree-Fock level of theory using a 6-311 + G∗∗ basis set. The potential function has been described as V(ϕ) = V 0[( {ϕ}/{ϕ e}) 2 - 1] 2 with the following parameters V 0 = 0.57 ± 0.32 {kcal}/{mol} and ϕe = 25.9 ± 2.6°, where ϕ is the puckering angle of the ring. The classic distribution function used for averaging the local molecular configurations was found to underestimate the value V0 by 8% as compared with the exact quantum mechanical distribution function. The geometric parameters at the minimum V( ϕ) ( r a in Å, ∠ α in degrees and errors given as three times the standard deviations including a scale error) are: r(Si-Cl ax) = 2.043(2), r(Si-Cl eq) = 2.038(2), r(Si-C) = 1.860(3), r(C-C) = 1.557(4), r(C-H) = 1.091(8), ∠ClSiCl = 105.2(8), ∠CSiC = 81.1(10), ∠SiCH eq = 118.9(54), ∠SiCH ax = 109.7(54), ∠CC 5H eq = 105.3(63), ∠CC 5H ax = 100.9(63), HC 3H = 108.0, ∠ δ(ClSiCl) = 4.1, ∠ δ(HC 3H) = 3.0, where the tilt angle δ, and ∠HC 3H are estimated from ab initio constraints. The structural parameters are compared with those obtained for related compounds. Distortions of the valence angles at the Si atom in silacyclobutanes are shown to be well explained using the VSEPR model complemented by the concept of bent bonds.
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...
Directory of Open Access Journals (Sweden)
Hoeschele Ina
2007-05-01
Full Text Available Abstract Background Requirements for successful implementation of multivariate animal threshold models including phenotypic and genotypic information are not known yet. Here simulated horse data were used to investigate the properties of multivariate estimators of genetic parameters for categorical, continuous and molecular genetic data in the context of important radiological health traits using mixed linear-threshold animal models via Gibbs sampling. The simulated pedigree comprised 7 generations and 40000 animals per generation. Additive genetic values, residuals and fixed effects for one continuous trait and liabilities of four binary traits were simulated, resembling situations encountered in the Warmblood horse. Quantitative trait locus (QTL effects and genetic marker information were simulated for one of the liabilities. Different scenarios with respect to recombination rate between genetic markers and QTL and polymorphism information content of genetic markers were studied. For each scenario ten replicates were sampled from the simulated population, and within each replicate six different datasets differing in number and distribution of animals with trait records and availability of genetic marker information were generated. (CoVariance components were estimated using a Bayesian mixed linear-threshold animal model via Gibbs sampling. Residual variances were fixed to zero and a proper prior was used for the genetic covariance matrix. Results Effective sample sizes (ESS and biases of genetic parameters differed significantly between datasets. Bias of heritability estimates was -6% to +6% for the continuous trait, -6% to +10% for the binary traits of moderate heritability, and -21% to +25% for the binary traits of low heritability. Additive genetic correlations were mostly underestimated between the continuous trait and binary traits of low heritability, under- or overestimated between the continuous trait and binary traits of moderate
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On polyhedral approximations of polytopes for learning Bayesian networks
Czech Academy of Sciences Publication Activity Database
Studený, Milan; Haws, D.C.
2013-01-01
Roč. 4, č. 1 (2013), s. 59-92 ISSN 1309-3452 R&D Projects: GA ČR GA201/08/0539 Institutional support: RVO:67985556 Keywords : Bayesian network structure * integer programming * standard imset * characteristic imset * LP relaxation Subject RIV: BA - General Mathematics http://library.utia.cas.cz/separaty/2013/MTR/studeny-on polyhedral approximations of polytopes for learning bayesian networks.pdf
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.
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
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
International Nuclear Information System (INIS)
Kasraie, Nima; Oviatt, Henry Wayne; Clarke, Geoffrey David
2011-01-01
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
Relaxation processes connected with electron localization
International Nuclear Information System (INIS)
The paper reviews a series of recent theoretical papers worked out in the Institute of Applied Radiation Chemistry, Lodz. Poland. These papers are mainly devoted to various relaxation processes connected with electron localization in irradiated disordered media as well as to the construction of the models of trapped or solvated electron. The models reviewed in this paper (the first part of the review) concern: (1) electron trap relaxation via electron tunnelling followed by molecular reorientation: (2) molecular structure of alcohol-hydrocarbon mixtures and electron localization in these matrices: (3) the glass relaxation effect on trapped electron reactions. (author)
Reynhardt, E. C.; Jurga, K.; Andrew, E. R.
Proton spin-lattice relaxation times in the laboratory frame, T1(H),have been measured as a function of frequency and temperature (333K> T > 80 K). The spin-lattice relaxation times in the rotating frame, T1 ϱ(H), have been measured at two different rotating fields while M2(H), the proton second moment, has been extracted from the shape of the FID. In addition, T 1( 31P) and T 1( 23Na) have been measured as functions of temperature at 81 and 50 MHz, respectively. The results demonstrate clearly that the water content of the compounds influences the results to a large extent. It seems that water molecules at some of the lattice sites can be removed from the structure by evacuation, while others are more tightly bound to the ADP and ATP molecules. The more loosely bound water molecules are very mobile and dominate the relaxation results in the high-temperature region via the spin-rotation and dipolar mechanisms. The more tightly bound water molecules rotate about their twofold axes and this motion, characterized by a distribution of correlation times, results in a T1(H) minimum in the low-temperature region. The results have been interpreted in terms of a Fuoss-Kirkwood distribution function. The 23Na spin-lattice relaxation rates are dominated by the quadrupolar interactions, which provide a dominating relaxation mechanism for the proton spins in the rotating frame. In the case of Na 2ATP, T1(P) is independent of the degree of hydration of the sample, but the NaADP T1(H), values are influenced strongly by a change in the water content. An X-ray determination of the lengths of the a axes of the unit cells has provided supporting evidence for the interpretation of the NMR results.
Polytomies and Bayesian phylogenetic inference.
Lewis, Paul O; Holder, Mark T; Holsinger, Kent E
2005-04-01
Bayesian phylogenetic analyses are now very popular in systematics and molecular evolution because they allow the use of much more realistic models than currently possible with maximum likelihood methods. There are, however, a growing number of examples in which large Bayesian posterior clade probabilities are associated with very short branch lengths and low values for non-Bayesian measures of support such as nonparametric bootstrapping. For the four-taxon case when the true tree is the star phylogeny, Bayesian analyses become increasingly unpredictable in their preference for one of the three possible resolved tree topologies as data set size increases. This leads to the prediction that hard (or near-hard) polytomies in nature will cause unpredictable behavior in Bayesian analyses, with arbitrary resolutions of the polytomy receiving very high posterior probabilities in some cases. We present a simple solution to this problem involving a reversible-jump Markov chain Monte Carlo (MCMC) algorithm that allows exploration of all of tree space, including unresolved tree topologies with one or more polytomies. The reversible-jump MCMC approach allows prior distributions to place some weight on less-resolved tree topologies, which eliminates misleadingly high posteriors associated with arbitrary resolutions of hard polytomies. Fortunately, assigning some prior probability to polytomous tree topologies does not appear to come with a significant cost in terms of the ability to assess the level of support for edges that do exist in the true tree. Methods are discussed for applying arbitrary prior distributions to tree topologies of varying resolution, and an empirical example showing evidence of polytomies is analyzed and discussed.
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
Baldo, M.; Grassi, A.; Guidoni, L.; Nicolini, M.; Pappalardo, G. C.; Viti, V.
The spin-lattice relaxation times ( T1) of carbon-13 resonances of the drug 2-oxopyrrolidin- 1-ylacetamide ( 2OPYAC) were determined in CDCl 3 + DMSO and H 2O solutions to investigate the internal conformational flexibility. The measured T1s for the hydrogen-bearing carbon atoms of the 2-pyrrolidone ring fragment were diagnostic of a rigid conformation with respect to the acetamide linked moiety. The model of anisotropic reorientation of a rigid body was used to analyse the measured relaxation data in terms of a single conformation. Owing to the small number of T1 data available the fitting procedure for each of the possible conformations failed. The structure corresponding to the rigid conformation was therefore considered to be the one that is strongly stabilized by internal hydrogen bonding as predicted on the basis of theoretical MO ab initio quantum chemical calculations.
Flexible Bayesian Human Fecundity Models.
Kim, Sungduk; Sundaram, Rajeshwari; Buck Louis, Germaine M; Pyper, Cecilia
2012-12-01
Human fecundity is an issue of considerable interest for both epidemiological and clinical audiences, and is dependent upon a couple's biologic capacity for reproduction coupled with behaviors that place a couple at risk for pregnancy. Bayesian hierarchical models have been proposed to better model the conception probabilities by accounting for the acts of intercourse around the day of ovulation, i.e., during the fertile window. These models can be viewed in the framework of a generalized nonlinear model with an exponential link. However, a fixed choice of link function may not always provide the best fit, leading to potentially biased estimates for probability of conception. Motivated by this, we propose a general class of models for fecundity by relaxing the choice of the link function under the generalized nonlinear model framework. We use a sample from the Oxford Conception Study (OCS) to illustrate the utility and fit of this general class of models for estimating human conception. Our findings reinforce the need for attention to be paid to the choice of link function in modeling conception, as it may bias the estimation of conception probabilities. Various properties of the proposed models are examined and a Markov chain Monte Carlo sampling algorithm was developed for implementing the Bayesian computations. The deviance information criterion measure and logarithm of pseudo marginal likelihood are used for guiding the choice of links. The supplemental material section contains technical details of the proof of the theorem stated in the paper, and contains further simulation results and analysis.
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
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
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.
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....
DEFF Research Database (Denmark)
Jensen, Finn Verner; Nielsen, Thomas Dyhre
2016-01-01
is largely due to the availability of efficient inference algorithms for answering probabilistic queries about the states of the variables in the network. Furthermore, to support the construction of Bayesian network models, learning algorithms are also available. We give an overview of the Bayesian network...
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
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…
Zygelman, B.; Lucic, Zelimir; Hudson, Eric R.
2014-01-01
Using both quantum and semi-classical methods, we calculate the rates for radiative association and charge transfer in cold collisions of Yb+ with Ca. We demonstrate the fidelity of the local optical potential method in predictions for the total radiative relaxation rates. We find a large variation in the isotope dependence of the cross sections at ultra-cold gas temperatures. However, at cold temperatures, 1 mK < T < 1 K, the effective spontaneous radiative rates for the different isotopes share a common value of about 1.5 × 10-15 cm3 s-1. It is about five orders of magnitude smaller than the chemical reaction rate measured in Rellergert et al (2011 Phys. Rev. Lett. 107 243201).
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
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.
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.
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
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...
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...
Granade, Christopher; Combes, Joshua; Cory, D. G.
2016-03-01
In recent years, Bayesian methods have been proposed as a solution to a wide range of issues in quantum state and process tomography. State-of-the-art Bayesian tomography solutions suffer from three problems: numerical intractability, a lack of informative prior distributions, and an inability to track time-dependent processes. Here, we address all three problems. First, we use modern statistical methods, as pioneered by Huszár and Houlsby (2012 Phys. Rev. A 85 052120) and by Ferrie (2014 New J. Phys. 16 093035), to make Bayesian tomography numerically tractable. Our approach allows for practical computation of Bayesian point and region estimators for quantum states and channels. Second, we propose the first priors on quantum states and channels that allow for including useful experimental insight. Finally, we develop a method that allows tracking of time-dependent states and estimates the drift and diffusion processes affecting a state. We provide source code and animated visual examples for our methods.
de la Cruz, María Luisa; Pérez, Andres; Domínguez, Mercedes; Moreno, Inmaculada; García, Nerea; Martínez, Irene; Navarro, Alejandro; Domínguez, Lucas; Álvarez, Julio
2016-08-01
Leishmaniasis, caused by Leishmania infantum , is a vector-borne zoonotic disease that is endemic to the Mediterranean basin. The potential of rabbits and hares to serve as competent reservoirs for the disease has recently been demonstrated, although assessment of the importance of their role on disease dynamics is hampered by the absence of quantitative knowledge on the accuracy of diagnostic techniques in these species. A Bayesian latent-class model was used here to estimate the sensitivity and specificity of the Immuno-fluorescence antibody test (IFAT) in serum and a Leishmania -nested PCR (Ln-PCR) in skin for samples collected from 217 rabbits and 70 hares from two different populations in the region of Madrid, Spain. A two-population model, assuming conditional independence between test results and incorporating prior information on the performance of the tests in other animal species obtained from the literature, was used. Two alternative cut-off values were assumed for the interpretation of the IFAT results: 1/50 for conservative and 1/25 for sensitive interpretation. Results suggest that sensitivity and specificity of the IFAT were around 70-80%, whereas the Ln-PCR was highly specific (96%) but had a limited sensitivity (28.9% applying the conservative interpretation and 21.3% with the sensitive one). Prevalence was higher in the rabbit population (50.5% and 72.6%, for the conservative and sensitive interpretation, respectively) than in hares (6.7% and 13.2%). Our results demonstrate that the IFAT may be a useful screening tool for diagnosis of leishmaniasis in rabbits and hares. These results will help to design and implement surveillance programmes in wild species, with the ultimate objective of early detecting and preventing incursions of the disease into domestic and human populations.
Variational Bayesian Filtering
Czech Academy of Sciences Publication Activity Database
Šmídl, Václav; Quinn, A.
2008-01-01
Roč. 56, č. 10 (2008), s. 5020-5030 ISSN 1053-587X R&D Projects: GA MŠk 1M0572 Institutional research plan: CEZ:AV0Z10750506 Keywords : Bayesian filtering * particle filtering * Variational Bayes Subject RIV: BC - Control Systems Theory Impact factor: 2.335, year: 2008 http://library.utia.cas.cz/separaty/2008/AS/smidl-variational bayesian filtering.pdf
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
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....
Delta Relaxation Enhanced Magnetic Resonance
Alford, Jamu K.
Generally speaking, targeted molecular imaging has always been difficult to perform with magnetic resonance. The difficulty does not arise with the magnetic resonance imaging (MRI) technique or equipment itself, but rather with the targeted contrast agents, which the method requires. Also referred to as activatable contrast agents, or MRI probes, targeted contrast agents are pharmaceuticals that will selectively bind to a particular biological (target) molecule. They are used to highlight a certain tissue or the difference between healthy and diseased tissue. Unfortunately, nearly all MRI probes are non-specific, causing localized increases in MR image intensity in both the unbound and target-bound states. Therefore, brightening in a conventional MRI image, following probe injection, does not positively indicate the presence of the target molecule. Herein, a novel method known as delta relaxation enhanced magnetic resonance (dreMR, pronounced "dreamer") is presented that utilizes variable magnetic field technology to produce image contrast related to the dependence of the sample's longitudinal relaxation rates upon the strength of the main magnetic field of the MRI scanner. Since only bound contrast agent shows significant magnetic field dependence, it is an indicator of the bound probe, which is in turn a marker for the target molecule. This work details the development of the dreMR method, focusing on the specialized hardware necessary to provide a clinical, static-field MRI the ability to modulate its main magnetic field throughout an MRI sequence. All modifications were performed in such a manner that the host MRI system was not degraded or permanently modified in any way. The three parts of this technology are: the insertable electromagnet, the power supply system and the control system. The insertable electromagnet modifies the magnetic field, the power system drives the electromagnet, and the control system generates the magnetic field waveform envelope and
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.
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 ...
Relaxation Techniques for Health
... combined with guided imagery and breathing exercises. Self-Hypnosis In self-hypnosis programs, people are taught to produce the relaxation ... have shown that women who were taught self-hypnosis have a decreased need for pain medicine during ...
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 Exploratory Factor Analysis
DEFF Research Database (Denmark)
Conti, Gabriella; Frühwirth-Schnatter, Sylvia; Heckman, James J.
2014-01-01
This paper develops and applies a Bayesian approach to Exploratory Factor Analysis that improves on ad hoc classical approaches. Our framework relies on dedicated factor models and simultaneously determines the number of factors, the allocation of each measurement to a unique factor, and the corr......This paper develops and applies a Bayesian approach to Exploratory Factor Analysis that improves on ad hoc classical approaches. Our framework relies on dedicated factor models and simultaneously determines the number of factors, the allocation of each measurement to a unique factor......, and the corresponding factor loadings. Classical identification criteria are applied and integrated into our Bayesian procedure to generate models that are stable and clearly interpretable. A Monte Carlo study confirms the validity of the approach. The method is used to produce interpretable low dimensional aggregates...
Berliner, M.
2017-12-01
Bayesian statistical decision theory offers a natural framework for decision-policy making in the presence of uncertainty. Key advantages of the approach include efficient incorporation of information and observations. However, in complicated settings it is very difficult, perhaps essentially impossible, to formalize the mathematical inputs needed in the approach. Nevertheless, using the approach as a template is useful for decision support; that is, organizing and communicating our analyses. Bayesian hierarchical modeling is valuable in quantifying and managing uncertainty such cases. I review some aspects of the idea emphasizing statistical model development and use in the context of sea-level rise.
Bayesian Exploratory Factor Analysis
Conti, Gabriella; Frühwirth-Schnatter, Sylvia; Heckman, James J.; Piatek, Rémi
2014-01-01
This paper develops and applies a Bayesian approach to Exploratory Factor Analysis that improves on ad hoc classical approaches. Our framework relies on dedicated factor models and simultaneously determines the number of factors, the allocation of each measurement to a unique factor, and the corresponding factor loadings. Classical identification criteria are applied and integrated into our Bayesian procedure to generate models that are stable and clearly interpretable. A Monte Carlo study confirms the validity of the approach. The method is used to produce interpretable low dimensional aggregates from a high dimensional set of psychological measurements. PMID:25431517
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...
Nuclear spin relaxation in liquids theory, experiments, and applications
Kowalewski, Jozef
2006-01-01
Nuclear magnetic resonance (NMR) is widely used across many fields because of the rich data it produces, and some of the most valuable data come from the study of nuclear spin relaxation in solution. While described to varying degrees in all major NMR books, spin relaxation is often perceived as a difficult, if not obscure, topic, and an accessible, cohesive treatment has been nearly impossible to find.Collecting relaxation theory, experimental techniques, and illustrative applications into a single volume, this book clarifies the nature of the phenomenon, shows how to study it, and explains why such studies are worthwhile. Coverage ranges from basic to rigorous theory and from simple to sophisticated experimental methods, and the level of detail is somewhat greater than most other NMR texts. Topics include cross-relaxation, multispin phenomena, relaxation studies of molecular dynamics and structure, and special topics such as relaxation in systems with quadrupolar nuclei and paramagnetic systems.Avoiding ove...
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
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.
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.
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.
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...
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...... not impose any particular assumptions on the shape of the distribution of the factors, but still secures the basic requirements for the identification of the model. We design a new sampling scheme based on marginal data augmentation for the inference of mixtures of normals with location and scale...... restrictions. This approach is augmented by the use of a retrospective sampler, to allow for the inference of a constrained Dirichlet process mixture model for the distribution of the latent factors. We carry out a simulation study to illustrate the methodology and demonstrate its benefits. Our sampler is very...
Nonlinear fractional relaxation
Indian Academy of Sciences (India)
Abstract. We define a nonlinear model for fractional relaxation phenomena. We use ε-expansion method to analyse this model. By studying the fundamental solutions of this model we find that when t → 0 the model exhibits a fast decay rate and when t → ∞ the model exhibits a power-law decay. By analysing the frequency ...
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...... in a Matlab toolbox, is demonstrated for non-negative decompositions and compared with non-negative matrix factorization.......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...
Arregui, Iñigo
2018-01-01
In contrast to the situation in a laboratory, the study of the solar atmosphere has to be pursued without direct access to the physical conditions of interest. Information is therefore incomplete and uncertain and inference methods need to be employed to diagnose the physical conditions and processes. One of such methods, solar atmospheric seismology, makes use of observed and theoretically predicted properties of waves to infer plasma and magnetic field properties. A recent development in solar atmospheric seismology consists in the use of inversion and model comparison methods based on Bayesian analysis. In this paper, the philosophy and methodology of Bayesian analysis are first explained. Then, we provide an account of what has been achieved so far from the application of these techniques to solar atmospheric seismology and a prospect of possible future extensions.
Mørup, Morten; Schmidt, Mikkel N
2012-09-01
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.
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...
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}.
Bayesian networks in reliability
Energy Technology Data Exchange (ETDEWEB)
Langseth, Helge [Department of Mathematical Sciences, Norwegian University of Science and Technology, N-7491 Trondheim (Norway)]. E-mail: helgel@math.ntnu.no; Portinale, Luigi [Department of Computer Science, University of Eastern Piedmont ' Amedeo Avogadro' , 15100 Alessandria (Italy)]. E-mail: portinal@di.unipmn.it
2007-01-15
Over the last decade, Bayesian networks (BNs) have become a popular tool for modelling many kinds of statistical problems. We have also seen a growing interest for using BNs in the reliability analysis community. In this paper we will discuss the properties of the modelling framework that make BNs particularly well suited for reliability applications, and point to ongoing research that is relevant for practitioners in reliability.
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 experimental...... 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....
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
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...
... 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 ...
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.
THEORY OF RELAXATION PROCESSES IN FERROMAGNETIC INSULATORS
Contents: Simplified description of ferromagnetic relaxation Detailed treatment of magnons Relaxation frequency calculations Summary of relaxation processes in YIG Summary of experimental results for YIG
A Comparison of Relaxation Strategies.
Matthews, Doris B.
Some researchers argue that all relaxation techniques produce a single relaxation response while others support a specific-effects hypothesis which suggests that progressive relaxation affects the musculoskeletal system and that guided imagery affects cognitive changes. Autogenics is considered a technique which is both somatic and cognitive. This…
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.
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
Effect of doping on TSD relaxation in cellulose acetate films
Indian Academy of Sciences (India)
Unknown
The peak currents, released charge and activation energies associated with the peaks are affected by AA doping. The effect of doping with acrylic acid on the discharge current indicates the formation of molecular aggregates. Keywords. TSD relaxation; cellulose acetate; acrylic acid; molecular aggregates. 1. Introduction.
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 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.
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.
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.)
Classification using Bayesian neural nets
J.C. Bioch (Cor); O. van der Meer; R. Potharst (Rob)
1995-01-01
textabstractRecently, Bayesian methods have been proposed for neural networks to solve regression and classification problems. These methods claim to overcome some difficulties encountered in the standard approach such as overfitting. However, an implementation of the full Bayesian approach to
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.
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.
Dielectric relaxation and hydrogen diffusion in amorphous silicon
Energy Technology Data Exchange (ETDEWEB)
Phillips, J.C. (AT and T Bell Labs., Murray Hill, NJ (United States))
1994-04-01
Hydrogen diffusion is technologically critical to the processing of amorphous Si for solar cell applications. It is shown that this diffusion belongs to a broad class of dielectric relaxation mechanisms which were first studied by Kohlrausch in 1847. A microscopic theory of the Kohlrausch relaxation constant [beta][sub K] is also constructed. This theory explains the values of [beta] observed in many electronic, molecular and polymeric relaxation processes. It is based on two novel concepts: Wiener sausages, from statistical mechanics, and the magic wand, from axiomatic set theory
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...... in the Gaussian approximation, reproduces the generic features of alpha relaxation........ Rev. Lett., 86 (2001) 1271]. Assuming that long-wavelength fluctuations dominate the dynamics, a model for the dielectric alpha relaxation based on the simplest coupling between the density and dipole density fields is proposed here. The model, which is solved in second-order perturbation theory...
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.
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.
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.
Progressive muscle relaxation, yoga stretching, and ABC relaxation theory.
Ghoncheh, Shahyad; Smith, Jonathan C
2004-01-01
This study compared the psychological effects of progressive muscle relaxation (PMR) and yoga stretching (hatha) exercises. Forty participants were randomly divided into two groups and taught PMR or yoga stretching exercises. Both groups practiced once a week for five weeks and were given the Smith Relaxation States Inventory before and after each session. As hypothesized, practitioners of PMR displayed higher levels of relaxation states (R-States) Physical Relaxation and Disengagement at Week 4 and higher levels of Mental Quiet and Joy as a posttraining aftereffect at Week 5. Contrary to what was hypothesized, groups did not display different levels of R-States Energized or Aware. Results suggest the value of supplementing traditional somatic conceptualizations of relaxation with the psychological approach embodied in ABC relaxation theory. Clinical and research implications are discussed. Copyright 2003 Wiley Periodicals, Inc. J Clin Psychol.
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.
Relaxing music for anxiety control.
Elliott, Dave; Polman, Remco; McGregor, Richard
2011-01-01
The purpose of this investigation was to determine the characteristics of relaxing music for anxiety control. Undergraduate students (N=84) were instructed to imagine themselves in an anxiety producing situation while listening to a selection of 30 music compositions. For each composition, level of relaxation, the factors that either enhanced or detracted from its relaxing potential and the emotional labels attached were assessed. Participants were also asked to state which music components (e.g., tempo, melody) were most conducive to relaxation. Additional information was obtained through the use of a focus group of 6 undergraduate music students. This paper presents details on the characteristics of relaxing-music for anxiety control and emotional labels attached to the relaxing compositions. Furthermore, an importance value has been attached to each of the music components under scrutiny, thus providing an indication of which music components should receive greatest attention when selecting music for anxiety control.
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.
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...... represents the spatial coordinates of the grid nodes. Knowledge of how grid nodes are depicted in the observed image is described through the observation model. The prior consists of a node prior and an arc (edge) prior, both modeled as Gaussian MRFs. The node prior models variations in the positions of grid...... nodes and the arc prior models variations in row and column spacing across the grid. Grid matching is done by placing an initial rough grid over the image and applying an ensemble annealing scheme to maximize the posterior distribution of the grid. The method can be applied to noisy images with missing...
Bayesian supervised dimensionality reduction.
Gönen, Mehmet
2013-12-01
Dimensionality reduction is commonly used as a preprocessing step before training a supervised learner. However, coupled training of dimensionality reduction and supervised learning steps may improve the prediction performance. In this paper, we introduce a simple and novel Bayesian supervised dimensionality reduction method that combines linear dimensionality reduction and linear supervised learning in a principled way. We present both Gibbs sampling and variational approximation approaches to learn the proposed probabilistic model for multiclass classification. We also extend our formulation toward model selection using automatic relevance determination in order to find the intrinsic dimensionality. Classification experiments on three benchmark data sets show that the new model significantly outperforms seven baseline linear dimensionality reduction algorithms on very low dimensions in terms of generalization performance on test data. The proposed model also obtains the best results on an image recognition task in terms of classification and retrieval performances.
Bayesian Geostatistical Design
DEFF Research Database (Denmark)
Diggle, Peter; Lophaven, Søren Nymand
2006-01-01
This paper describes the use of model-based geostatistics for choosing the set of sampling locations, collectively called the design, to be used in a geostatistical analysis. Two types of design situation are considered. These are retrospective design, which concerns the addition of sampling...... 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...... parameter values are unknown. The results show that in this situation a wide range of interpoint distances should be included in the design, and the widely used regular design is often not the best choice....
Smith, J C; Wedell, A B; Kolotylo, C J; Lewis, J E; Byers, K Y; Segin, C M
2000-06-01
ABC Relaxation Theory proposes 15 psychological relaxation-related states (R-States): Sleepiness, Disengagement, Physical Relaxation, Mental Quiet, Rested/Refreshed, At Ease/At Peace, Energized, Aware, Joy, Thankfulness and Love, Prayerfulness, Childlike Innocence, Awe and Wonder, Mystery, and Timeless/Boundless/Infinite. The present study summarizes the results of 13 separate factor analyses of immediate relaxation-related states, states associated with recalled relaxation activities, relaxation dispositions, and relaxation motivations on a combined sample of 1,904 individuals (group average ages ranged from 28-40 yr.). Four exploratory factor analyses of Smith Relaxation Inventories yielded 15 items that most consistently and exclusively load (generally at least .70) on six replicated factors. These items included happy, joyful, energized, rested, at peace, warm, limp, silent, quiet, dozing, drowsy, prayerful, mystery, distant, and indifferent. Subsequent factor analyses restricted to these items and specifying six factors were performed on 13 different data sets. Each yielded the same six-factor solution: Factor 1: Centered Positive Affect, Factor 2: Sleepiness, Factor 3: Disengagement, Factor 4: Physical Relaxation, Factor 5: Mental Quiet, and Factor 6: Spiritual. Implications for ABC Relaxation Theory are discussed.
Relaxation and Meditation with Music
ČAPKOVÁ, Jana
2011-01-01
The thesis introduces an importance of a mental hygiene and its chosen methods - relaxation and meditation with music. The theoretical part is focused on a description of the basic relaxation and meditation techniques and curative effects of music. It deals with a music therapy, its meaning, types, methods and history in terms of the importance of music healing relaxation effects on the mental, physical as well as spiritual health. The practical part includes a usage of these methods in pract...
Exploring catalyst passivation with NMR relaxation.
Robinson, Neil; Gladden, Lynn F; D'Agostino, Carmine
2017-10-26
NMR relaxation has recently emerged as a novel and non-invasive tool for probing the surface dynamics of adsorbate molecules within liquid-saturated mesoporous catalysts. The elucidation of such dynamics is of particular relevance to the study and development of solvated green catalytic processes, such as the production of chemicals and fuels from bio-resources. In this paper we develop and implement a protocol using high field 1 H NMR spin-lattice relaxation as a probe of the reorientational dynamics of liquids imbibed within mesoporous oxide materials. The observed relaxation of liquids within mesoporous materials is highly sensitive to the adsorbed surface layer, giving insight into tumbling behaviour of spin-bearing chemical environments at the pore surface. As a prototypical example of relevance to liquid-phase catalytic systems, we examine the mobility of liquid methanol within a range of common catalyst supports. In particular, through the calculation and comparison of a suitable interaction parameter, we assess and quantify changes to these surface dynamics upon replacing surface hydroxyl groups with hydrophobic alkyl chains. Our results indicate that the molecular tumbling of adsorbed methanol is enhanced upon surface passivation due to the suppression of surface-adsorbate hydrogen bonding interactions, and tends towards that of the unrestricted bulk liquid. A complex analysis in which we account for the influence of changing pore structure and surface chemistry upon passivation is discussed. The results presented highlight the use of NMR spin-lattice relaxation measurements as a non-invasive probe of molecular dynamics at surfaces of interest to liquid-phase heterogeneous catalysis.
Bayesian adaptive methods for clinical trials
Berry, Scott M; Muller, Peter
2010-01-01
Already popular in the analysis of medical device trials, adaptive Bayesian designs are increasingly being used in drug development for a wide variety of diseases and conditions, from Alzheimer's disease and multiple sclerosis to obesity, diabetes, hepatitis C, and HIV. Written by leading pioneers of Bayesian clinical trial designs, Bayesian Adaptive Methods for Clinical Trials explores the growing role of Bayesian thinking in the rapidly changing world of clinical trial analysis. The book first summarizes the current state of clinical trial design and analysis and introduces the main ideas and potential benefits of a Bayesian alternative. It then gives an overview of basic Bayesian methodological and computational tools needed for Bayesian clinical trials. With a focus on Bayesian designs that achieve good power and Type I error, the next chapters present Bayesian tools useful in early (Phase I) and middle (Phase II) clinical trials as well as two recent Bayesian adaptive Phase II studies: the BATTLE and ISP...
Relaxation Techniques for Trauma.
Scotland-Coogan, Diane; Davis, Erin
2016-01-01
Physiological symptoms of posttraumatic stress disorder (PTSD) manifest as increased arousal and reactivity seen as anger outburst, irritability, reckless behavior with no concern for consequences, hypervigilance, sleep disturbance, and problems with focus (American Psychiatric Association, 2013 ). In seeking the most beneficial treatment for PTSD, consideration must be given to the anxiety response. Relaxation techniques are shown to help address the physiological manifestations of prolonged stress. The techniques addressed by the authors in this article include mindfulness, deep breathing, yoga, and meditation. By utilizing these techniques traditional therapies can be complemented. In addition, those who are averse to the traditional evidence-based practices or for those who have tried traditional therapies without success; these alternative interventions may assist in lessening physiological manifestations of PTSD. Future research studies assessing the benefits of these treatment modalities are warranted to provide empirical evidence to support the efficacy of these treatments.
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 Inference: with ecological applications
Link, William A.; Barker, Richard J.
2010-01-01
This text provides a mathematically rigorous yet accessible and engaging introduction to Bayesian inference with relevant examples that will be of interest to biologists working in the fields of ecology, wildlife management and environmental studies as well as students in advanced undergraduate statistics.. This text opens the door to Bayesian inference, taking advantage of modern computational efficiencies and easily accessible software to evaluate complex hierarchical models.
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...
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...
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...
Biomolecules: Fluctuations and relaxations
Parak, F.; Ostermann, A.; Gassmann, A.; Scherk, C.; Chong, S.-H.; Kidera, A.; Go, N.
1999-10-01
The normal-mode refinement of X-ray crystallographic data opened a new possibility to analyze the mean-square displacements in a protein molecule. A comparison of the X-ray structure of myoglobin at several temperatures with Mössbauer data is performed. In the low-temperature regime below 180 K the iron mean-square displacements obtained by Mössbauer spectroscopy are in good agreement with a normal-mode analysis. The X-ray mean-square displacements at the position of the iron, after the motion originated from the external degrees of freedom are subtracted, have practically the same temperature dependence as those from Mössbauer spectroscopy. The difference between the X-ray mean-square displacements and those predicted by normal-mode analysis measures the distribution of molecules into conformational substates. Above 180 K the Mössbauer effect indicates fluctuations between conformational substates. The relaxation from a Fe(III) conformation to a Fe(II) conformation is shown for superoxide dismutase of Propionibacterium shermanii.
Energy Technology Data Exchange (ETDEWEB)
Baldacchini, G.; Botti, S.; Grassano, U.M.; Luty, F.
1991-10-01
The spin-lattice relaxation time in the ground state, T/sub 1/, and the spin-mixing parameter during the optical cycle, epsilon, were measured in FH(OH) and FH(CN) centers in various alkali halides (KCl, KBr, KI, CsCl, and CsBr). For a close comparison, all experiments were performed before and after the optical association of the F center and molecular ion. T/sub 1/ becomes shorter before and still more after aggregation with respect to the values measured in the pure crystal, especially at very low magnetic fields. Epsilon decreases a little in crystals doped with OH-, while it increases a lot in crystals doped with CN-. Part of these results can be interpreted within the actual knowledge of the F-center physics. Part have been used to shed some light on the various unknown aspects of the energy transfer between the excited F-center and the molecular ion.
Vinther, Jakob; Sperling, Erik A; Briggs, Derek E G; Peterson, Kevin J
2012-04-07
Aplacophorans have long been argued to be basal molluscs. We present a molecular phylogeny, including the aplacophorans Neomeniomorpha (Solenogastres) and Chaetodermomorpha (Caudofoveata), which recovered instead the clade Aculifera (Aplacophora + Polyplacophora). Our relaxed Bayesian molecular clock estimates an Early Ordovician appearance of the aculiferan crown group consistent with the presence of chiton-like molluscs with seven or eight dorsal shell plates by the Late Cambrian (approx. 501-490 Ma). Molecular, embryological and palaeontological data indicate that aplacophorans, as well as chitons, evolved from a paraphyletic assemblage of chiton-like ancestors. The recovery of cephalopods as a sister group to aculiferans suggests that the plesiomorphic condition in molluscs might be a morphology similar to that found in monoplacophorans.
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.
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
Bayesian microsaccade detection
Mihali, Andra; van Opheusden, Bas; Ma, Wei Ji
2017-01-01
Microsaccades are high-velocity fixational eye movements, with special roles in perception and cognition. The default microsaccade detection method is to determine when the smoothed eye velocity exceeds a threshold. We have developed a new method, Bayesian microsaccade detection (BMD), which performs inference based on a simple statistical model of eye positions. In this model, a hidden state variable changes between drift and microsaccade states at random times. The eye position is a biased random walk with different velocity distributions for each state. BMD generates samples from the posterior probability distribution over the eye state time series given the eye position time series. Applied to simulated data, BMD recovers the “true” microsaccades with fewer errors than alternative algorithms, especially at high noise. Applied to EyeLink eye tracker data, BMD detects almost all the microsaccades detected by the default method, but also apparent microsaccades embedded in high noise—although these can also be interpreted as false positives. Next we apply the algorithms to data collected with a Dual Purkinje Image eye tracker, whose higher precision justifies defining the inferred microsaccades as ground truth. When we add artificial measurement noise, the inferences of all algorithms degrade; however, at noise levels comparable to EyeLink data, BMD recovers the “true” microsaccades with 54% fewer errors than the default algorithm. Though unsuitable for online detection, BMD has other advantages: It returns probabilities rather than binary judgments, and it can be straightforwardly adapted as the generative model is refined. We make our algorithm available as a software package. PMID:28114483
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)
Can Black Hole Relax Unitarily?
Solodukhin, S. N.
2005-03-01
We review the way the BTZ black hole relaxes back to thermal equilibrium after a small perturbation and how it is seen in the boundary (finite volume) CFT. The unitarity requires the relaxation to be quasi-periodic. It is preserved in the CFT but is not obvious in the case of the semiclassical black hole the relaxation of which is driven by complex quasi-normal modes. We discuss two ways of modifying the semiclassical black hole geometry to maintain unitarity: the (fractal) brick wall and the worm-hole modification. In the latter case the entropy comes out correctly as well.
Dielectric relaxation of amides and tetrahydrofuran polar mixture in ...
Indian Academy of Sciences (India)
The estimated relaxation time ( τ j k 's) and dipole moment ( μ j k 's) agree well with the reported values signifying the validity of the proposed methods. Structural and associational aspects are predicted from the plot of τ j k and μ j k against x j of tetrahydrofuran to arrive at solute–solute (dimer) molecular association upto x j ...
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.
Hydrogen motions and the α-relaxation in glass- forming polymers ...
Indian Academy of Sciences (India)
forming polymers; α-relaxation; fully atomistic molecular dynamics simulations; quasi-elastic neutron scattering. PACS Nos 64.70.Pf; 61.12.Ex; 61.41.+e. The freezing of the structural (α) relaxation in a glass-forming system leads to the.
2017-01-01
for a rigid symmetric top rotor can be derived by replacing τc in eq 8 with an effective correlation time that relates the 13C–1H relaxation vector...of internal motions (θ = ε = 0°), the expression that is derived from substituting τc in eq 8 with τe reduces to the symmetric top rotor J(ω) in eq... SYMMETRIC TOP ROTOR MODELS AND THE FLEXIBLE SYMMETRIC TOP ROTOR MODEL ECBC-TR-1428 Terry J. Henderson RESEARCH AND TECHNOLOGY DIRECTORATE
Relaxation Pathways in Metallic Glasses
Gallino, Isabella; Busch, Ralf
2017-11-01
At temperatures below the glass transition temperature, physical properties of metallic glasses, such as density, viscosity, electrical resistivity or enthalpy, slowly evolve with time. This is the process of physical aging that occurs among all types of glasses and leads to structural changes at the microscopic level. Even though the relaxation pathways are ruled by thermodynamics as the glass attempts to re-attain thermodynamic equilibrium, they are steered by sluggish kinetics at the microscopic level. Understanding the structural and dynamic pathways of the relaxing glassy state is still one of the grand challenges in materials physics. We review some of the recent experimental advances made in understanding the nature of the relaxation phenomenon in metallic glasses and its implications to the macroscopic and microscopic properties changes of the relaxing glass.
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.
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.
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.)
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 ...
Relaxation processes in Aeolian transport
Directory of Open Access Journals (Sweden)
Selmani Houssem
2017-01-01
Full Text Available We investigate experimentally the relaxation process toward the equilibrium regime of saltation transport in the context of spatial inhomogeneous conditions. The relaxation length associated to this process is an important length in aeolian transport. This length stands for the distance needed for the particle flux to adapt to a change in flow conditions or in the boundary conditions at the bed. Predicting the value of this length under given conditions of transport remains an open and important issue. We conducted wind tunnel experiments to document the influence of the upstream particle flux and wind speed on the relaxation process toward the saturated transport state. In the absence of upstream particle flux, data show that the relaxation length is independent of the wind strength (except close to the threshold of transport. In contrast, in the case of a finite upstream flux, the relaxation length exhibits a clear increase with increasing air flow velocity. Moreover, in the latter the relaxation is clearly non-monotonic and presents an overshoot.
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.
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 image restoration, using configurations
DEFF Research Database (Denmark)
Thorarinsdottir, Thordis Linda
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 remaining parameters in the model is outlined for the salt and pepper noise. The inference in the model is discussed...
Bayesian image restoration, using configurations
DEFF Research Database (Denmark)
Thorarinsdottir, Thordis
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...
Bayesian variable selection in regression
Energy Technology Data Exchange (ETDEWEB)
Mitchell, T.J.; Beauchamp, J.J.
1987-01-01
This paper is concerned with the selection of subsets of ''predictor'' variables in a linear regression model for the prediction of a ''dependent'' variable. We take a Bayesian approach and assign a probability distribution to the dependent variable through a specification of prior distributions for the unknown parameters in the regression model. The appropriate posterior probabilities are derived for each submodel and methods are proposed for evaluating the family of prior distributions. Examples are given that show the application of the Bayesian methodology. 23 refs., 3 figs.
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 a...... decade's research on inference in hybrid Bayesian networks. The discussions are linked to an example model for estimating human reliability....... 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 (so-called hybrid domains). In this paper we focus on these difficulties, and summarize some of the last...
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 variable order Markov models: Towards Bayesian predictive state representations
Dimitrakakis, C.
2009-01-01
We present a Bayesian variable order Markov model that shares many similarities with predictive state representations. The resulting models are compact and much easier to specify and learn than classical predictive state representations. Moreover, we show that they significantly outperform a more
The humble Bayesian : Model checking from a fully Bayesian perspective
Morey, Richard D.; Romeijn, Jan-Willem; Rouder, Jeffrey N.
Gelman and Shalizi (2012) criticize what they call the usual story in Bayesian statistics: that the distribution over hypotheses or models is the sole means of statistical inference, thus excluding model checking and revision, and that inference is inductivist rather than deductivist. They present
Bayesian Model Averaging for Propensity Score Analysis
Kaplan, David; Chen, Jianshen
2013-01-01
The purpose of this study is to explore Bayesian model averaging in the propensity score context. Previous research on Bayesian propensity score analysis does not take into account model uncertainty. In this regard, an internally consistent Bayesian framework for model building and estimation must also account for model uncertainty. The…
Bayesian models in cognitive neuroscience: A tutorial
O'Reilly, J.X.; Mars, R.B.
2015-01-01
This chapter provides an introduction to Bayesian models and their application in cognitive neuroscience. The central feature of Bayesian models, as opposed to other classes of models, is that Bayesian models represent the beliefs of an observer as probability distributions, allowing them to
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
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
Relaxation schemes for Chebyshev spectral multigrid methods
Kang, Yimin; Fulton, Scott R.
1993-01-01
Two relaxation schemes for Chebyshev spectral multigrid methods are presented for elliptic equations with Dirichlet boundary conditions. The first scheme is a pointwise-preconditioned Richardson relaxation scheme and the second is a line relaxation scheme. The line relaxation scheme provides an efficient and relatively simple approach for solving two-dimensional spectral equations. Numerical examples and comparisons with other methods are given.
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 in levee reliability
Roscoe, K.; Hanea, A.
2015-01-01
We applied a Bayesian network to a system of levees for which the results of traditional reliability analysis showed high failure probabilities, which conflicted with the intuition and experience of those managing the levees. We made use of forty proven strength observations - high water levels with
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...... dimensionality. The built classi er is tested on standard and non-standard images...
Computational Neuropsychology and Bayesian Inference.
Parr, Thomas; Rees, Geraint; Friston, Karl J
2018-01-01
Computational theories of brain function have become very influential in neuroscience. They have facilitated the growth of formal approaches to disease, particularly in psychiatric research. In this paper, we provide a narrative review of the body of computational research addressing neuropsychological syndromes, and focus on those that employ Bayesian frameworks. Bayesian approaches to understanding brain function formulate perception and action as inferential processes. These inferences combine 'prior' beliefs with a generative (predictive) model to explain the causes of sensations. Under this view, neuropsychological deficits can be thought of as false inferences that arise due to aberrant prior beliefs (that are poor fits to the real world). This draws upon the notion of a Bayes optimal pathology - optimal inference with suboptimal priors - and provides a means for computational phenotyping. In principle, any given neuropsychological disorder could be characterized by the set of prior beliefs that would make a patient's behavior appear Bayes optimal. We start with an overview of some key theoretical constructs and use these to motivate a form of computational neuropsychology that relates anatomical structures in the brain to the computations they perform. Throughout, we draw upon computational accounts of neuropsychological syndromes. These are selected to emphasize the key features of a Bayesian approach, and the possible types of pathological prior that may be present. They range from visual neglect through hallucinations to autism. Through these illustrative examples, we review the use of Bayesian approaches to understand the link between biology and computation that is at the heart of neuropsychology.
Bansal, Shyam Sunder; Kaushal, Aditya Mohan; Bansal, Arvind Kumar
2010-11-01
The purpose of the current study was to evaluate the enthalpy relaxation behavior of valdecoxib (VLB) and etoricoxib (ETB) and their binary dispersions to derive relaxation constants and to understand their molecular mobilities. Solid dispersions of VLB and ETB were prepared with 1%, 2%, 5%, 10%, 15%, and 20% (w/w) concentrations of polyvinylpyrrolidone (PVP) in situ using differential scanning calorimetry (DSC). Enthalpy relaxation studies were carried out with isothermal storage periods of 1, 2, 4, 6, 16, and 24 hours at 40°C and 0% relative humidity (RH). PVP increased the glass transition temperature (T(g)) and decreased the enthalpy relaxation. Significant differences between two drugs were observed with respect to their relaxation behavior which may be due to differences in intermolecular interactions as predicted by Couchman-Karasz equation and molecular mobility. Kohlrausch-Williams-Watts equation was found to be inadequate in describing complex molecular relaxations in binary dispersions. The enthalpy relaxation behavior of VLB and ETB was found to be significantly different. PVP stabilized VLB significantly; however, its effect on ETB was negligible. The extent of enthalpy relaxation was found to correlate with hydrogen bonding tendency of the drug molecules. The outcome can help in rational designing of amorphous systems with optimal performance.
Free Surface Relaxations of Star Shaped Polymer Films
Energy Technology Data Exchange (ETDEWEB)
Glynos, Emmanoui; Johnson, Kyle J.; Frieberg, Bradley R.; Chremos, Alexandros; Narayanan, Suresh; Sakellariou, Georgios; Green, Peter F.
2017-11-28
The surface relaxation dynamics of supported star-shaped polymer thin films are shown to be slower than the bulk, persisting up to temperatures at least 50 degrees above the bulk glass transition temperature Tgbulk. This behavior, exhibited by star-shaped polystyrenes (SPSs) with functionality f = 8-arms and molecular weights per arm Marm < Me (Me is the entanglement molecular weight), is shown by molecular dynamics simulations to be associated with a preferential localization of these macromolecules at the free surface. This new phenomenon is in notable contrast to that of linear chain polymer thin film systems where the surface relaxations are enhanced in relation to the bulk; this enhancement persists only for a limited temperature range above the bulk Tgbulk. Evidence of the slow surface dynamics, compared to the bulk, for temperatures well above Tg and at length and time scales not associated with the glass transition has not previously been reported for polymers
Free Surface Relaxations of Star-Shaped Polymer Films
Energy Technology Data Exchange (ETDEWEB)
Glynos, Emmanouil; Johnson, Kyle J.; Frieberg, Bradley; Chremos, Alexandros; Narayanan, Suresh; Sakellariou, Georgios; Green, Peter F.
2017-11-01
The surface relaxation dynamics of supported star-shaped polymer thin films are shown to be slower than the bulk, persisting up to temperatures at least 50 K above the bulk glass transition temperature Tgbulk. This behavior, exhibited by star-shaped polystyrenes with functionality f=8 arms and molecular weights per arm Marm
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
Straub, Daniel; 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.
Bayesian methods for measures of agreement
Broemeling, Lyle D
2009-01-01
Using WinBUGS to implement Bayesian inferences of estimation and testing hypotheses, Bayesian Methods for Measures of Agreement presents useful methods for the design and analysis of agreement studies. It focuses on agreement among the various players in the diagnostic process.The author employs a Bayesian approach to provide statistical inferences based on various models of intra- and interrater agreement. He presents many examples that illustrate the Bayesian mode of reasoning and explains elements of a Bayesian application, including prior information, experimental information, the likelihood function, posterior distribution, and predictive distribution. The appendices provide the necessary theoretical foundation to understand Bayesian methods as well as introduce the fundamentals of programming and executing the WinBUGS software.Taking a Bayesian approach to inference, this hands-on book explores numerous measures of agreement, including the Kappa coefficient, the G coefficient, and intraclass correlation...
Diffusion relaxation of photoinduced gratings in polyvinyl acetate latex films
Veniaminov, A. V.; Bartsch, E.
2011-03-01
The features of the postexposure relaxation of holographic gratings recorded in inhomogeneous polyvinyl acetate latex films with photosensitive agents (photochromic molecules of fulgide dyes and phenanthrenequinone) have been considered. The diffusion coefficients and rms displacements of izomerized probe in polymer latex particles and aqueous environment are determined within the model of two diffusion states. The effective diffusion coefficient of the molecular probe, which is responsible for the relaxation of gratings, increases with an increase in their period in wet films, whereas in dry films, this parameter is independent of the grating period. In the films subjected to high-temperature treatment the effective diffusion coefficient decreases with an increase in the grating period. The successive stages of grating relaxation in latex films with phenanthrenequinone are related to the diffusion of free molecules, radicals, and polymer chains, as well as to the local displacement of macromolecular segments at distances of 5-25 nm.
Psychomotricity and Relaxation in Psychiatry
Directory of Open Access Journals (Sweden)
Janete Maximiano
2014-10-01
Full Text Available The author pretends to present with this article, the therapeutic contributions of Psychomotricity and Relaxation in Mental Health context, making only reference to adults intervention. A brief description of the body, as a biopsychosocial unity, is found in the introduction, which is followed by the explanation of conceptual and interventional models in Clinical Psychomotricity. The author makes reference to psychotherapeutic values of relaxation, giving some examples of techniques and exposing a clinical case. Finally, the author briefly describes her recent experience of Psychomotor intervention in Psychiatric Service of Hospital Fernando Fonseca.
Relaxation Oscillation and Canard Explosion
Krupa, M.; Szmolyan, P.
2001-08-01
We give a geometric analysis of relaxation oscillations and canard cycles in singularly perturbed planar vector fields. The transition from small Hopf-type cycles to large relaxation cycles, which occurs in an exponentially thin parameter interval, is described as a perturbation of a family of singular cycles. The results are obtained by means of two blow-up transformations combined with standard tools of dynamical systems theory. The efficient use of various charts is emphasized. The results are applied to the van der Pol equation.
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.
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
Bayesian phylogenetic estimation of fossil ages
Drummond, Alexei J.; Stadler, Tanja
2016-01-01
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
Bayesian Model Averaging for Propensity Score Analysis.
Kaplan, David; Chen, Jianshen
2014-01-01
This article considers Bayesian model averaging as a means of addressing uncertainty in the selection of variables in the propensity score equation. We investigate an approximate Bayesian model averaging approach based on the model-averaged propensity score estimates produced by the R package BMA but that ignores uncertainty in the propensity score. We also provide a fully Bayesian model averaging approach via Markov chain Monte Carlo sampling (MCMC) to account for uncertainty in both parameters and models. A detailed study of our approach examines the differences in the causal estimate when incorporating noninformative versus informative priors in the model averaging stage. We examine these approaches under common methods of propensity score implementation. In addition, we evaluate the impact of changing the size of Occam's window used to narrow down the range of possible models. We also assess the predictive performance of both Bayesian model averaging propensity score approaches and compare it with the case without Bayesian model averaging. Overall, results show that both Bayesian model averaging propensity score approaches recover the treatment effect estimates well and generally provide larger uncertainty estimates, as expected. Both Bayesian model averaging approaches offer slightly better prediction of the propensity score compared with the Bayesian approach with a single propensity score equation. Covariate balance checks for the case study show that both Bayesian model averaging approaches offer good balance. The fully Bayesian model averaging approach also provides posterior probability intervals of the balance indices.
Pedestrian dynamics via Bayesian networks
Venkat, Ibrahim; Khader, Ahamad Tajudin; Subramanian, K. G.
2014-06-01
Studies on pedestrian dynamics have vital applications in crowd control management relevant to organizing safer large scale gatherings including pilgrimages. Reasoning pedestrian motion via computational intelligence techniques could be posed as a potential research problem within the realms of Artificial Intelligence. In this contribution, we propose a "Bayesian Network Model for Pedestrian Dynamics" (BNMPD) to reason the vast uncertainty imposed by pedestrian motion. With reference to key findings from literature which include simulation studies, we systematically identify: What are the various factors that could contribute to the prediction of crowd flow status? The proposed model unifies these factors in a cohesive manner using Bayesian Networks (BNs) and serves as a sophisticated probabilistic tool to simulate vital cause and effect relationships entailed in the pedestrian domain.
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...... primarily for practitioners, this book does not require sophisticated mathematical skills or deep understanding of the underlying theory and methods nor does it discuss alternative technologies for reasoning under uncertainty. The theory and methods presented are illustrated through more than 140 examples...
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.
Bayesian Inference on Proportional Elections
Brunello, Gabriel Hideki Vatanabe; Nakano, Eduardo Yoshio
2015-01-01
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. PMID:25786259
Bayesian analyses of cognitive architecture.
Houpt, Joseph W; Heathcote, Andrew; Eidels, Ami
2017-06-01
The question of cognitive architecture-how cognitive processes are temporally organized-has arisen in many areas of psychology. This question has proved difficult to answer, with many proposed solutions turning out to be spurious. Systems factorial technology (Townsend & Nozawa, 1995) provided the first rigorous empirical and analytical method of identifying cognitive architecture, using the survivor interaction contrast (SIC) to determine when people are using multiple sources of information in parallel or in series. Although the SIC is based on rigorous nonparametric mathematical modeling of response time distributions, for many years inference about cognitive architecture has relied solely on visual assessment. Houpt and Townsend (2012) recently introduced null hypothesis significance tests, and here we develop both parametric and nonparametric (encompassing prior) Bayesian inference. We show that the Bayesian approaches can have considerable advantages. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
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.
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)
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
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
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.
Relaxation experiments with synchrotron radiation
Leupold, O; Bernhard, A; Gerdau, E; Jaschke, J; Ruter, HD; Shvydko, Y; Alp, EE; Hession, P; Hu, M; Sturhahn, W; Sutter, J; Toellner, T; Chumakov, AI; Metge, J; Ruffer, R
1998-01-01
Relaxation phenomena show up in standard energy domain Mossbauer spectra via line broadening. The evaluation of such spectra is in most cases done by adopting the stochastic theory mainly developed in the 60s and 70s. Due to the time structure and the polarization of the synchrotron radiation
Spin relaxation in disordered media
International Nuclear Information System (INIS)
Dzheparov, F S
2011-01-01
A review is given on theoretical grounds and typical experimental appearances of spin dynamics and relaxation in solids containing randomly distributed nuclear and/or electronic spins. Brief content is as follows. Disordered and magnetically diluted systems. General outlines of the spin transport theory. Random walks in disordered systems (RWDS). Observable values in phase spin relaxation, free induction decay (FID). Interrelation of longitudinal and transversal relaxation related to dynamics of occupancies and phases. Occupation number representation for equations of motion. Continuum media approximation and inapplicability of moment expansions. Long-range transitions vs percolation theory. Concentration expansion as a general constructive basis for analytical methods. Scaling properties of propagators. Singular point. Dynamical and kinematical memory in RWDS. Ways of regrouping of concentration expansions. CTRW and semi-phenomenology. Coherent medium approximation for nuclear relaxation via paramagnetic impurities. Combining of memory functions and cumulant expansions for calculation of FID. Path integral representations for RWDS. Numerical simulations of RWDS. Spin dynamics in magnetically diluted systems with low Zeeman and medium low dipole temperatures. Cluster expansions, regularization of dipole interactions and spectral dynamics.
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....
Reliability analysis with Bayesian networks
Zwirglmaier, Kilian Martin
2017-01-01
Bayesian networks (BNs) represent a probabilistic modeling tool with large potential for reliability engineering. While BNs have been successfully applied to reliability engineering, there are remaining issues, some of which are addressed in this work. Firstly a classification of BN elicitation approaches is proposed. Secondly two approximate inference approaches, one of which is based on discretization and the other one on sampling, are proposed. These approaches are applicable to hybrid/con...
Interim Bayesian Persuasion: First Steps
Perez, Eduardo
2015-01-01
This paper makes a first attempt at building a theory of interim Bayesian persuasion. I work in a minimalist model where a low or high type sender seeks validation from a receiver who is willing to validate high types exclusively. After learning her type, the sender chooses a complete conditional information structure for the receiver from a possibly restricted feasible set. I suggest a solution to this game that takes into account the signaling potential of the sender's choice.
Bayesian Sampling using Condition Indicators
DEFF Research Database (Denmark)
Faber, Michael H.; Sørensen, John Dalsgaard
2002-01-01
. This allows for a Bayesian formulation of the indicators whereby the experience and expertise of the inspection personnel may be fully utilized and consistently updated as frequentistic information is collected. The approach is illustrated on an example considering a concrete structure subject to corrosion....... It is shown how half-cell potential measurements may be utilized to update the probability of excessive repair after 50 years....
Computational Neuropsychology and Bayesian Inference
Directory of Open Access Journals (Sweden)
Thomas Parr
2018-02-01
Full Text Available Computational theories of brain function have become very influential in neuroscience. They have facilitated the growth of formal approaches to disease, particularly in psychiatric research. In this paper, we provide a narrative review of the body of computational research addressing neuropsychological syndromes, and focus on those that employ Bayesian frameworks. Bayesian approaches to understanding brain function formulate perception and action as inferential processes. These inferences combine ‘prior’ beliefs with a generative (predictive model to explain the causes of sensations. Under this view, neuropsychological deficits can be thought of as false inferences that arise due to aberrant prior beliefs (that are poor fits to the real world. This draws upon the notion of a Bayes optimal pathology – optimal inference with suboptimal priors – and provides a means for computational phenotyping. In principle, any given neuropsychological disorder could be characterized by the set of prior beliefs that would make a patient’s behavior appear Bayes optimal. We start with an overview of some key theoretical constructs and use these to motivate a form of computational neuropsychology that relates anatomical structures in the brain to the computations they perform. Throughout, we draw upon computational accounts of neuropsychological syndromes. These are selected to emphasize the key features of a Bayesian approach, and the possible types of pathological prior that may be present. They range from visual neglect through hallucinations to autism. Through these illustrative examples, we review the use of Bayesian approaches to understand the link between biology and computation that is at the heart of neuropsychology.
Sleep, Stress & Relaxation: Rejuvenate Body & Mind
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On the age of eukaryotes: evaluating evidence from fossils and molecular clocks.
Eme, Laura; Sharpe, Susan C; Brown, Matthew W; Roger, Andrew J
2014-08-01
Our understanding of the phylogenetic relationships among eukaryotic lineages has improved dramatically over the few past decades thanks to the development of sophisticated phylogenetic methods and models of evolution, in combination with the increasing availability of sequence data for a variety of eukaryotic lineages. Concurrently, efforts have been made to infer the age of major evolutionary events along the tree of eukaryotes using fossil-calibrated molecular clock-based methods. Here, we review the progress and pitfalls in estimating the age of the last eukaryotic common ancestor (LECA) and major lineages. After reviewing previous attempts to date deep eukaryote divergences, we present the results of a Bayesian relaxed-molecular clock analysis of a large dataset (159 proteins, 85 taxa) using 19 fossil calibrations. We show that for major eukaryote groups estimated dates of divergence, as well as their credible intervals, are heavily influenced by the relaxed molecular clock models and methods used, and by the nature and treatment of fossil calibrations. Whereas the estimated age of LECA varied widely, ranging from 1007 (943-1102) Ma to 1898 (1655-2094) Ma, all analyses suggested that the eukaryotic supergroups subsequently diverged rapidly (i.e., within 300 Ma of LECA). The extreme variability of these and previously published analyses preclude definitive conclusions regarding the age of major eukaryote clades at this time. As more reliable fossil data on eukaryotes from the Proterozoic become available and improvements are made in relaxed molecular clock modeling, we may be able to date the age of extant eukaryotes more precisely. Copyright © 2014 Cold Spring Harbor Laboratory Press; all rights reserved.
Bayesian methods applied to GWAS.
Fernando, Rohan L; Garrick, Dorian
2013-01-01
Bayesian multiple-regression methods are being successfully used for genomic prediction and selection. These regression models simultaneously fit many more markers than the number of observations available for the analysis. Thus, the Bayes theorem is used to combine prior beliefs of marker effects, which are expressed in terms of prior distributions, with information from data for inference. Often, the analyses are too complex for closed-form solutions and Markov chain Monte Carlo (MCMC) sampling is used to draw inferences from posterior distributions. This chapter describes how these Bayesian multiple-regression analyses can be used for GWAS. In most GWAS, false positives are controlled by limiting the genome-wise error rate, which is the probability of one or more false-positive results, to a small value. As the number of test in GWAS is very large, this results in very low power. Here we show how in Bayesian GWAS false positives can be controlled by limiting the proportion of false-positive results among all positives to some small value. The advantage of this approach is that the power of detecting associations is not inversely related to the number of markers.
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
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.
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.
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...
Scheufele, P M
2000-04-01
The present experiment examined relaxation using different experimental conditions to test whether the effects of individual elements of relaxation could be measured, whether specific effects were revealed, or whether relaxation resulted from a generalized "relaxation response." Sixty-seven normal, male volunteers were exposed to a stress manipulation and then to one of two relaxation (Progressive Relaxation, Music) or control (Attention Control, Silence) conditions. Measurements of attention, relaxation, and stress responses were obtained during each phase of the experiment. All four groups exhibited similar performance on behavioral measures of attention that suggested a reduction in physiological arousal following their relaxation or control condition, as well as a decreased heart rate. Progressive Relaxation, however, resulted in the greatest effects on behavioral and self-report measures of relaxation, suggesting that cognitive cues provided by stress management techniques contribute to relaxation.
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...... and differentiating these circuits in time linear in their size. We report on experimental results showing the successful compilation, and efficient inference, on relational Bayesian networks whose {\\primula}--generated propositional instances have thousands of variables, and whose jointrees have clusters...
Bayesian Posterior Distributions Without Markov Chains
Cole, Stephen R.; Chu, Haitao; Greenland, Sander; Hamra, Ghassan; Richardson, David B.
2012-01-01
Bayesian posterior parameter distributions are often simulated using Markov chain Monte Carlo (MCMC) methods. However, MCMC methods are not always necessary and do not help the uninitiated understand Bayesian inference. As a bridge to understanding Bayesian inference, the authors illustrate a transparent rejection sampling method. In example 1, they illustrate rejection sampling using 36 cases and 198 controls from a case-control study (1976–1983) assessing the relation between residential ex...
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...
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....
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).
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 learn....... An automated procedure for specifying prior distributions for the parameters in a dynamic Bayesian network is presented. It is a simple extension of the procedure for the ordinary Bayesian networks. Finally the W¨olfer?s sunspot numbers are analyzed....
Generalized approach to non-exponential relaxation
Indian Academy of Sciences (India)
Abstract. Non-exponential relaxation is a universal feature of systems as diverse as glasses, spin glasses, earthquakes, financial markets and the universe. Complex relaxation results from hierarchically constrained dynamics with the strength of the constraints being directly related to the form of the relaxation, which ...
Topological Control on the Structural Relaxation of Atomic Networks under Stress
Bauchy, Mathieu; Wang, Mengyi; Yu, Yingtian; Wang, Bu; Krishnan, N. M. Anoop; Masoero, Enrico; Ulm, Franz-Joseph; Pellenq, Roland
2017-07-01
Upon loading, atomic networks can feature delayed irreversible relaxation. However, the effect of composition and structure on relaxation remains poorly understood. Herein, relying on accelerated molecular dynamics simulations and topological constraint theory, we investigate the relationship between atomic topology and stress-induced structural relaxation, by taking the example of creep deformations in calcium silicate hydrates (C - S - H ), the binding phase of concrete. Under constant shear stress, C - S - H is found to feature delayed logarithmic shear deformations. We demonstrate that the propensity for relaxation is minimum for isostatic atomic networks, which are characterized by the simultaneous absence of floppy internal modes of relaxation and eigenstress. This suggests that topological nanoengineering could lead to the discovery of nonaging materials.
International Nuclear Information System (INIS)
Zhang, Ke-Sheng; Wang, Shu; Zhu, Ming; Ding, Yi
2013-01-01
It is still a challenge to employ the acoustic method to investigate the molecular relaxation phenomena in excitable gases. Here we present an algorithm to capture the primary relaxation processes by only measuring the sound absorption and sound speed of two operating frequencies at a single pressure, without the necessity of detecting the gas density. This algorithm is developed from the fact that the frequency-dependent sound absorption curve due to a single-relaxation process can be reconstructed from the two values of the relaxation frequency and the maximum relaxational absorption, and they can be synthesized by the acoustic measurements at two frequencies. Moreover, by acquiring the high-frequency sound speed, those two synthesized values can be used to reconstruct the sound dispersion curve. The simulations demonstrate the validity of the proposed algorithm and its robustness against errors of acoustic measurements. (paper)
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.
Hites, Lacey S.; Lundervold, Duane A.
2013-01-01
Forty-four individuals, 18-47 (MN 21.8, SD 5.63) years of age, took part in a study examining the magnitude and direction of the relationship between self-report and direct observation measures of relaxation and mindfulness. The Behavioral Relaxation Scale (BRS), a valid direct observation measure of relaxation, was used to assess relaxed behavior…
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 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
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
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....
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....
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...... settings, where cues shape expectations about a small number of upcoming stimuli and thus convey "prior" information about clearly defined objects. While operationally consistent with the experiments it seeks to describe, this view of attention as prior seems to miss many essential elements of both its...
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)
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.
Robust bayesian inference of generalized Pareto distribution ...
African Journals Online (AJOL)
Abstract. In this work, robust Bayesian estimation of the generalized Pareto distribution is proposed. The methodology is presented in terms of oscillation of posterior risks of the Bayesian estimators. By using a Monte Carlo simulation study, we show that, under a suitable generalized loss function, we can obtain a robust ...
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…
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...
Calibration in a Bayesian modelling framework
Jansen, M.J.W.; Hagenaars, T.H.J.
2004-01-01
Bayesian statistics may constitute the core of a consistent and comprehensive framework for the statistical aspects of modelling complex processes that involve many parameters whose values are derived from many sources. Bayesian statistics holds great promises for model calibration, provides the
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.; Collaboration, ALICE
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
Bayesian Network for multiple hypthesis tracking
Zajdel, W.P.; Kröse, B.J.A.; Blockeel, H.; Denecker, M.
2002-01-01
For a flexible camera-to-camera tracking of multiple objects we model the objects behavior with a Bayesian network and combine it with the multiple hypohesis framework that associates observations with objects. Bayesian networks offer a possibility to factor complex, joint distributions into a
Bayesian learning theory applied to human cognition.
Jacobs, Robert A; Kruschke, John K
2011-01-01
Probabilistic models based on Bayes' rule are an increasingly popular approach to understanding human cognition. Bayesian models allow immense representational latitude and complexity. Because they use normative Bayesian mathematics to process those representations, they define optimal performance on a given task. This article focuses on key mechanisms of Bayesian information processing, and provides numerous examples illustrating Bayesian approaches to the study of human cognition. We start by providing an overview of Bayesian modeling and Bayesian networks. We then describe three types of information processing operations-inference, parameter learning, and structure learning-in both Bayesian networks and human cognition. This is followed by a discussion of the important roles of prior knowledge and of active learning. We conclude by outlining some challenges for Bayesian models of human cognition that will need to be addressed by future research. WIREs Cogn Sci 2011 2 8-21 DOI: 10.1002/wcs.80 For further resources related to this article, please visit the WIREs website. Copyright © 2010 John Wiley & Sons, Ltd.
Properties of the Bayesian Knowledge Tracing Model
van de Sande, Brett
2013-01-01
Bayesian Knowledge Tracing is used very widely to model student learning. It comes in two different forms: The first form is the Bayesian Knowledge Tracing "hidden Markov model" which predicts the probability of correct application of a skill as a function of the number of previous opportunities to apply that skill and the model…
Plug & Play object oriented Bayesian networks
DEFF Research Database (Denmark)
Bangsø, Olav; Flores, J.; Jensen, Finn Verner
2003-01-01
and secondly, to gain efficiency during modification of an object oriented Bayesian network. To accomplish these two goals we have exploited a mechanism allowing local triangulation of instances to develop a method for updating the junction trees associated with object oriented Bayesian networks in highly...
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…
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
Modeling Diagnostic Assessments with Bayesian Networks
Almond, Russell G.; DiBello, Louis V.; Moulder, Brad; Zapata-Rivera, Juan-Diego
2007-01-01
This paper defines Bayesian network models and examines their applications to IRT-based cognitive diagnostic modeling. These models are especially suited to building inference engines designed to be synchronous with the finer grained student models that arise in skills diagnostic assessment. Aspects of the theory and use of Bayesian network models…
Online Bayesian phylogenetic inference: theoretical foundations via Sequential Monte Carlo.
Dinh, Vu; Darling, Aaron E; Matsen Iv, Frederick A
2017-12-13
Phylogenetics, the inference of evolutionary trees from molecular sequence data such as DNA, is an enterprise that yields valuable evolutionary understanding of many biological systems. Bayesian phylogenetic algorithms, which approximate a posterior distribution on trees, have become a popular if computationally expensive means of doing phylogenetics. Modern data collection technologies are quickly adding new sequences to already substantial databases. With all current techniques for Bayesian phylogenetics, computation must start anew each time a sequence becomes available, making it costly to maintain an up-to-date estimate of a phylogenetic posterior. These considerations highlight the need for an online Bayesian phylogenetic method which can update an existing posterior with new sequences. Here we provide theoretical results on the consistency and stability of methods for online Bayesian phylogenetic inference based on Sequential Monte Carlo (SMC) and Markov chain Monte Carlo (MCMC). We first show a consistency result, demonstrating that the method samples from the correct distribution in the limit of a large number of particles. Next we derive the first reported set of bounds on how phylogenetic likelihood surfaces change when new sequences are added. These bounds enable us to characterize the theoretical performance of sampling algorithms by bounding the effective sample size (ESS) with a given number of particles from below. We show that the ESS is guaranteed to grow linearly as the number of particles in an SMC sampler grows. Surprisingly, this result holds even though the dimensions of the phylogenetic model grow with each new added sequence. © The Author(s) 2017. Published by Oxford University Press, on behalf of the Society of Systematic Biologists.
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.
Relaxational dynamics of supercooled water in porous glass
International Nuclear Information System (INIS)
Zanotti, J.; Bellissent-Funel, M.; Chen, S.
1999-01-01
We have made a high-resolution quasielastic incoherent neutron scattering (QENS) study of the translational dynamics of supercooled water contained in micropores of Vycor glass at different hydration levels. QENS spectra from the confined H 2 O are analyzed in terms of the α-relaxation dynamics predicted by mode-coupling theory of supercooled liquids and by a recent computer molecular-dynamics simulation of extended simple point charge model water. We verify that the stretched exponential relaxation description of the long-time test-particle dynamics is consistent with the measured QENS spectral line shape. We are thus able to determine the wave-number dependence of magnitudes of the structural relaxation rate 1/τ and the stretch exponent β as functions of temperature and coverage. A power-law dependence of the average relaxation time on the magnitude of the scattering vector Q is observed. In the Q range studied, the exponent starts out with nearly -2.0, at room temperature, indicating a continuous diffusion, and gradually becomes less negative as the temperature is decreased to below the freezing temperature. thinsp copyright 1999 The American Physical Society
Theoretical studies of vibrational relaxation of iodine in low density liquid xenon
Brown, J.K.; Russell, D.J.; Smith, D.E.; Harris, C.B.
1987-01-01
Preliminary results of generalized Langevin and isolated binary collision (IBC) calculations for vibrational relaxation of iodine in low density liquid xenon are presented. Simple generalized Langevin simulations, using equilibrium xenon as a model solvent, fail to reproduce molecular dynamics vibrational relaxation data. This is explained, at least in part, by noting that the iodine vibrational motion perturbs the local solvent, with this perturbation resulting in dissipation of energy. Simp...
Logarithmic decay in single-particle relaxations of hydrated lysozyme powder
Lagi, Marco; Baglioni, Piero; Chen, Sow-Hsin
2009-01-01
We present the self-dynamics of protein amino acids of hydrated lysozyme powder around the physiological temperature by means of molecular dynamics (MD) simulations. The self-intermediate scattering functions (SISF) of the amino acid residue center-of-mass and of the protein hydrogen atoms display a logarithmic decay over 3 decades of time, from 2 picoseconds to 2 nanoseconds, followed by an exponential alpha-relaxation. This kind of slow dynamics resembles the relaxation scenario within the ...
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.
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.
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.
Crystal structure prediction accelerated by Bayesian optimization
Yamashita, Tomoki; Sato, Nobuya; Kino, Hiori; Miyake, Takashi; Tsuda, Koji; Oguchi, Tamio
2018-01-01
We propose a crystal structure prediction method based on Bayesian optimization. Our method is classified as a selection-type algorithm which is different from evolution-type algorithms such as an evolutionary algorithm and particle swarm optimization. Crystal structure prediction with Bayesian optimization can efficiently select the most stable structure from a large number of candidate structures with a lower number of searching trials using a machine learning technique. Crystal structure prediction using Bayesian optimization combined with random search is applied to known systems such as NaCl and Y2Co17 to discuss the efficiency of Bayesian optimization. These results demonstrate that Bayesian optimization can significantly reduce the number of searching trials required to find the global minimum structure by 30-40% in comparison with pure random search, which leads to much less computational cost.
International Nuclear Information System (INIS)
Dutuit-Fleischmann, Odile
1978-01-01
In the first section, the measurement of total deexcitation cross sections of the 3P 2,1,0 and 1 P 1 argon states by N 2 , H 2 , CO and SF 6 using a pulsed gas radiolysis technique and 600 keV electrons is discussed. The energy transfer from the resonant states 3 P 1 and 1 P 1 of argon (as excited selectively by synchrotron radiation) to the C 3 π u state of nitrogen has been studied in more detail. On the basis of these results, the different theoretical models for these reactions have been discussed. In the second section, the fluorescence of the second continuum of molecular xenon at around 1700 A, as excited by synchrotron radiation in the region of the 3P 1 1 S 0 resonance line at 1470 A, is considered. A short lived component of the fluorescence decay has been observed; this is attributed to emission at short interatomic distances from the high vibrational levels of Xe 2 + (O u + ). The emissions at the left turning point of the potential curve of the O u + state has been observed at λ > 2000 A. From these results, the potential curves for the states Xe 2 (O g + ) and Xe 2 * (O u + ) have been estimated and the Franck-Condon factors have also been calculated as a function of the wavelength of the fluorescence. (author) [fr
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
Relaxation laryngoplasty (thyroplasty tipe III)
Jiménez, Luis Humberto; Hospital Universitario San Ignacio; Barreto, Tatiana; Hospital Universitario San Ignacio
2011-01-01
Relaxation laryngoplasty is a surgical procedure that is indicated in mutational falsetto that does not respond well to voice therapy. By shortening the vocal cords, the fundamental frequency diminishes and gains a more male voice.We present the case of a male patient, with mutational dysphonia characterized with inadequate tone elevation in relation to its gender. We describe the surgical technique and its outcome. La tiroplastia de relajación está indicada en pacientes con alteraciones d...
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.)
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
Smith, Andrew B; Pisani, Davide; Mackenzie-Dodds, Jacqueline A; Stockley, Bruce; Webster, Bonnie L; Littlewood, D Timothy J
2006-10-01
The phylogenetic relationships of 46 echinoids, with representatives from 13 of the 14 ordinal-level clades and about 70% of extant families commonly recognized, have been established from 3 genes (3,226 alignable bases) and 119 morphological characters. Morphological and molecular estimates are similar enough to be considered suboptimal estimates of one another, and the combined data provide a tree that, when calibrated against the fossil record, provides paleontological estimates of divergence times and completeness of their fossil record. The order of branching on the cladogram largely agrees with the stratigraphic order of first occurrences and implies that their fossil record is more than 85% complete at family level and at a resolution of 5-Myr time intervals. Molecular estimates of divergence times derived from applying both molecular clock and relaxed molecular clock models are concordant with estimates based on the fossil record in up to 70% of cases, with most concordant results obtained using Sanderson's semiparametric penalized likelihood method and a logarithmic-penalty function. There are 3 regions of the tree where molecular and fossil estimates of divergence time consistently disagree. Comparison with results obtained when molecular divergence dates are estimated from the combined (morphology + gene) tree suggests that errors in phylogenetic reconstruction explain only one of these. In another region the error most likely lies with the paleontological estimates because taxa in this region are demonstrated to have a very poor fossil record. In the third case, morphological and paleontological evidence is much stronger, and the topology for this part of the molecular tree differs from that derived from the combined data. Here the cause of the mismatch is unclear but could be methodological, arising from marked inequality of molecular rates. Overall, the level of agreement reached between these different data and methodological approaches leads us to
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
Bayesian Approach to Inverse Problems
2008-01-01
Many scientific, medical or engineering problems raise the issue of recovering some physical quantities from indirect measurements; for instance, detecting or quantifying flaws or cracks within a material from acoustic or electromagnetic measurements at its surface is an essential problem of non-destructive evaluation. The concept of inverse problems precisely originates from the idea of inverting the laws of physics to recover a quantity of interest from measurable data.Unfortunately, most inverse problems are ill-posed, which means that precise and stable solutions are not easy to devise. Regularization is the key concept to solve inverse problems.The goal of this book is to deal with inverse problems and regularized solutions using the Bayesian statistical tools, with a particular view to signal and image estimation
Bayesian modelling of fusion diagnostics
Fischer, R.; Dinklage, A.; Pasch, E.
2003-07-01
Integrated data analysis of fusion diagnostics is the combination of different, heterogeneous diagnostics in order to improve physics knowledge and reduce the uncertainties of results. One example is the validation of profiles of plasma quantities. Integration of different diagnostics requires systematic and formalized error analysis for all uncertainties involved. The Bayesian probability theory (BPT) allows a systematic combination of all information entering the measurement descriptive model that considers all uncertainties of the measured data, calibration measurements, physical model parameters and measurement nuisance parameters. A sensitivity analysis of model parameters allows crucial uncertainties to be found, which has an impact on both diagnostic improvement and design. The systematic statistical modelling within the BPT is used for reconstructing electron density and electron temperature profiles from Thomson scattering data from the Wendelstein 7-AS stellarator. The inclusion of different diagnostics and first-principle information is discussed in terms of improvements.
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 ...
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...... sections, in addition to fully-updated examples, tables, figures, and a revised appendix. Intended primarily for practitioners, this book does not require sophisticated mathematical skills or deep understanding of the underlying theory and methods nor does it discuss alternative technologies for reasoning...... under uncertainty. The theory and methods presented are illustrated through more than 140 examples, and exercises are included for the reader to check his or her level of understanding. The techniques and methods presented on model construction and verification, modeling techniques and tricks, learning...
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...
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.
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
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.
Proton NMR relaxation of hydrated insulin powder
International Nuclear Information System (INIS)
Sanches, R.; Donoso, J.P.; Mascarenhas, S.; Panepucci, H.C.
1985-01-01
Water proton nuclear magnetic relaxation measurements were obtained for hydrated insulin powder as a function of the water content. For samples containing enough water to complete the hydration shell, the data for the spin-lattice and spin-spin relaxation times are consistent with a model in which water molecules exist in two phases, one exhibiting restricted motion and identified with water of hydration and another identified as free water with motions similar to ordinary water. For samples containing only water of hydration, a model for the spin-spin relaxation time is discussed, in which the water molecules relaxation is described in terms for four relaxation times. Estimates are obtained for these relaxation times, in good agreement with the experimental data. (Author) [pt
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....
Reduction of enthalpy relaxation in gelatine films by addition of polyols.
Díaz-Calderón, Paulo; MacNaughtan, Bill; Hill, Sandra; Mitchell, John; Enrione, Javier
2018-04-01
The aim of this study was to evaluate the effect of plasticisers with different molecular weights (glycerol and sorbitol) on the structural relaxation kinetics of bovine gelatine films stored under the glass transition temperature (Tg). Plasticisers were tested at weight fractions of 0.0, 0.06 and 0.10. Films conditioned in environments under ∼44% relative humidity gave moisture contents (w/w) in the range 0.14-0.18. The enthalpy relaxation (ΔH) was determined using differential scanning calorimetry (DSC). Samples used had Tg values in the range 24-49 °C. After removing the thermal history (30 °C above Tg, 15 min), samples were isothermally stored at 10 °C below Tg for between 2 and 80 h. The addition of plasticisers induced a significant reduction in the rate of structural relaxation. The linearisation of ΔH by plotting against the logarithm of ageing time showed a reduction in the slope of samples plasticised with both polyols. The reduction in relaxation kinetics may be related to the ability of polyols to act as enhancers of molecular packing, as recently reported using positron spectroscopy (PALS). However, a direct correlation between the relaxation kinetics and the plasticiser's molecular weight could not be established, suggesting that this phenomenon may be governed by complex molecular gelatin-plasticiser-water interactions. Copyright © 2017 Elsevier B.V. All rights reserved.
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....
[Autocontrol of muscle relaxation with vecuronium].
Sibilla, C; Zatelli, R; Marchi, M; Zago, M
1990-01-01
The optimal conditions for maintaining desired levels of muscle relaxation with vecuronium are obtained by means of the continuous infusion (I.V.) technique. A frequent correction of the infusion flow is required, since it is impossible to predict the exact amount for the muscle relaxant in single case. In order to overcome such limits the authors propose a very feasible infusion system for the self-control of muscle relaxation; furthermore they positively consider its possible daily clinical application.
Relaxation dynamics of a single DNA molecule
Goshen, E.; Zhao, W. Z.; Carmon, G.; Rosen, S.; Granek, R.; Feingold, M.
2005-06-01
The relaxation of a single DNA molecule is studied. The experimental system consists of optical tweezers and a micron-sized bead that is tethered to the bottom of the sample by a single double-stranded DNA molecule. The bead slows down the DNA relaxation from a strongly stretched configuration such that it is passing through stretched equilibrium states. This allows for a theoretical description of the relaxation trajectory, which is in good agreement with experiment.
Relaxation schemes for the shallow water equations
Delis, A. I.; Katsaounis, Th.
2003-03-01
We present a class of first and second order in space and time relaxation schemes for the shallow water (SW) equations. A new approach of incorporating the geometrical source term in the relaxation model is also presented. The schemes are based on classical relaxation models combined with Runge-Kutta time stepping mechanisms. Numerical results are presented for several benchmark test problems with or without the source term present.
Technological patterns of preventive relaxation of workings
Energy Technology Data Exchange (ETDEWEB)
Kaufman, L.L.; Bakhtin, A.F.; Zel' vyanskii, M.Sh. (Donetskaya Proektnaya Kontora (USSR))
1991-09-01
Presents stress relaxation patterns of workings. The patterns are used at horizon layouts and panel development of mine-take in stone inclines, boundary entries, mine drainage galleries and main galleries. The stress relaxation variants are: stress relaxing longwalls with complete mining with two or three winning galleries, longwalls worked by long pillars on the strike, and longwalls worked with advance mining on the strike. The individual variants differ by the ventilation system adopted.
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
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...... by evaluating and differentiating these circuits in time linear in their size. We report on experimental results showing successful compilation and efficient inference on relational Bayesian networks, whose PRIMULA--generated propositional instances have thousands of variables, and whose jointrees have clusters...
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.
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
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...... flat scalar potential directions along which the relaxation mechanism can be implemented. This fact translates into wider regions of applicability of the relaxation mechanism when compared to the Standard Model Higgs case. Our results show that, if the electroweak scale is not fundamental...... but radiatively generated, it is possible to generate the observed matter-antimatter asymmetry via the relaxation mechanism....
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
Gillani, N B; Smith, J C
2001-06-01
This study is an attempt to rigorously map the psychological effects of Zen meditation among experienced practitioners. Fifty-nine Zen meditators with at least six years of experience practiced an hour of traditional Zazen seated meditation. A control group of 24 college students spent 60 min silently reading popular magazines. Before relaxation, all participants took the Smith Relaxation States Inventory (SRSI), the Smith Relaxation Dispositions/Motivations Inventory (SRD/MI), and the Smith Relaxation Beliefs Inventory (SRBI). After practice, participants again took the SRSI. Analyses revealed that meditators are less likely to believe in God, more likely to believe in Inner Wisdom, and more likely to display the relaxation dispositions Mental Quiet, Mental Relaxation, and Timeless/Boundless/Infinite. Pre- and postsession analyses revealed that meditators showed greater increments in the relaxation states Mental Quiet, Love and Thankfulness, and Prayerfulness, as well as reduced Worry. Results support Smith's ABC Relaxation Theory.
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...
Congestion management utilizing concentric relaxation
Directory of Open Access Journals (Sweden)
Škokljev Ivan
2007-01-01
Full Text Available In the market-oriented power system environment, congestion management is a novel term connoting the power system steady state security functions. A large number of transmission transactions are dispatched in the regional day-ahead market and traverse the network adding to the power flow loading of the grid elements. Congestion is defined as a network security limit violation prospective due to transactions. Congestion management is a set of measures aimed at solving the congestion problem. This paper devises the concentric relaxation assisted approach to open access transmission network congestion management. The DC load flow symbolic simulator generates line power transfer functions. Congestion management is a systematic procedure based on linear programming. The DC load flow symbolic simulator generates all constraints and the black-box optimization library function is used to solve the problem of congestion on a sample IEEE RTS power system.
Local hysteresis in relaxation oscillators
International Nuclear Information System (INIS)
Alstroem, P.; Christiansen, B.; Levinsen, M.T.
1988-01-01
Relaxation oscillations or 'integrate and fire' phenomena are very commonly found in nature. When modulated by an external force a global hysteresis connected with chaos is often encountered. Besides this kind of hysteresis a local form is found in some systems. We describe briefly the difference and the circumstances under which to observe local hysteresis. A specific system treated in detail is the Fohlmeister model, originally derived to describe a neuronal encoder. In the limit of small damping an analytical solution is obtained. Furthermore, we derive an upper limit to the hysteresis. The results are compared to numerical calculations on the full system and agree quite well. In contrast to e.g. the driven damped pendulum equation the hysteresis is limited in size as compared to the phase-locked region. (orig.)
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 estimation and modeling: Editorial to the second special issue on Bayesian data analysis.
Chow, Sy-Miin; Hoijtink, Herbert
2017-12-01
This editorial accompanies the second special issue on Bayesian data analysis published in this journal. The emphases of this issue are on Bayesian estimation and modeling. In this editorial, we outline the basics of current Bayesian estimation techniques and some notable developments in the statistical literature, as well as adaptations and extensions by psychological researchers to better tailor to the modeling applications in psychology. We end with a discussion on future outlooks of Bayesian data analysis in psychology. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
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
Bayesian analysis for the social sciences
Jackman, Simon
2009-01-01
Bayesian methods are increasingly being used in the social sciences, as the problems encountered lend themselves so naturally to the subjective qualities of Bayesian methodology. This book provides an accessible introduction to Bayesian methods, tailored specifically for social science students. It contains lots of real examples from political science, psychology, sociology, and economics, exercises in all chapters, and detailed descriptions of all the key concepts, without assuming any background in statistics beyond a first course. It features examples of how to implement the methods using WinBUGS - the most-widely used Bayesian analysis software in the world - and R - an open-source statistical software. The book is supported by a Website featuring WinBUGS and R code, and data sets.
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.
新家, 健精
1991-01-01
© 2012 Springer Science+Business Media, LLC. All rights reserved. Article Outline: Glossary Definition of the Subject and Introduction The Bayesian Statistical Paradigm Three Examples Comparison with the Frequentist Statistical Paradigm Future Directions Bibliography
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.
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
A Bayesian concept learning approach to crowdsourcing
DEFF Research Database (Denmark)
Viappiani, P.; Zilles, S.; Hamilton, H.J.
2011-01-01
We develop a Bayesian approach to concept learning for crowdsourcing applications. A probabilistic belief over possible concept definitions is maintained and updated according to (noisy) observations from experts, whose behaviors are modeled using discrete types. We propose recommendation...
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++
A Bayesian Network Approach to Ontology Mapping
National Research Council Canada - National Science Library
Pan, Rong; Ding, Zhongli; Yu, Yang; Peng, Yun
2005-01-01
.... In this approach, the source and target ontologies are first translated into Bayesian networks (BN); the concept mapping between the two ontologies are treated as evidential reasoning between the two translated BNs...
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.
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
Two structural relaxations in protein hydration water and their dynamic crossovers
Camisasca, G.; De Marzio, M.; Corradini, D.; Gallo, P.
2016-07-01
We study the translational single particle dynamics of hydration water of lysozyme upon cooling by means of molecular dynamics simulations. We find that water close to the protein exhibits two distinct relaxations. By characterizing their behavior upon cooling, we are able to assign the first relaxation to the structural α-relaxation also present in bulk water and in other glass-forming liquids. The second, slower, relaxation can be ascribed to a dynamic coupling of hydration water motions to the fluctuations of the protein structure. Both relaxation times exhibit crossovers in the behavior upon cooling. For the α-process, we find upon cooling a crossover from a fragile behavior to a strong behavior at a temperature which is about five degrees higher than that of bulk water. The long-relaxation time appears strictly connected to the protein motion as it shows upon cooling a temperature crossover from a strong behavior with a lower activation energy to a strong behavior with a higher activation energy. The crossover temperature coincides with the temperature of the protein dynamical transition. These findings can help experimentalists to disentangle the different information coming from total correlators and to better characterize hydration water relaxations in different biomolecules.
Bayesian networks for management of industrial risk
International Nuclear Information System (INIS)
Munteanu, P.; Debache, G.; Duval, C.
2008-01-01
This article presents the outlines of Bayesian networks modelling and argues for their interest in the probabilistic studies of industrial risk and reliability. A practical case representative of this type of study is presented in support of the argumentation. The article concludes on some research tracks aiming at improving the performances of the methods relying on Bayesian networks and at widening their application area in risk management. (authors)
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.
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
Capturing Business Cycles from a Bayesian Viewpoint
大鋸, 崇
2011-01-01
This paper is a survey of empirical studies analyzing business cycles from the perspective of Bayesian econometrics. Kim and Nelson (1998) use a hybrid model; Dynamic factor model of Stock and Watson (1989) and Markov switching model of Hamilton (1989). From the point of view, it is more important dealing with non-linear and non-Gaussian econometric models, recently. Although the classical econometric approaches have difficulty in these models, the Bayesian's do easily. The fact leads heavy u...
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
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...
BIBI: Bayesian inference of breed composition.
Martínez, C A; Khare, K; Elzo, M A
2018-02-01
The aim of this paper was to develop statistical models to estimate individual breed composition based on the previously proposed idea of regressing discrete random variables corresponding to counts of reference alleles of biallelic molecular markers located across the genome on the allele frequencies of each marker in the pure (base) breeds. Some of the existing regression-based methods do not guarantee that estimators of breed composition will lie in the appropriate parameter space, and none of them account for uncertainty about allele frequencies in the pure breeds, that is, uncertainty about the design matrix. To overcome these limitations, we proposed two Bayesian generalized linear models. For each individual, both models assume that the counts of the reference allele at each marker locus follow independent Binomial distributions, use the logit link and pose a Dirichlet prior over the vector of regression coefficients (which corresponds to breed composition). This prior guarantees that point estimators of breed composition such as the posterior mean pertain to the appropriate space. The difference between these models is that model termed BIBI does not account for uncertainty about the design matrix, while model termed BIBI2 accounts for such an uncertainty by assigning independent Beta priors to the entries of this matrix. We implemented these models in a data set from the University of Florida's multibreed Angus-Brahman population. Posterior means were used as point estimators of breed composition. In addition, the ordinary least squares estimator proposed by Kuehn et al. () (OLSK) was also computed. BIBI and BIBI2 estimated breed composition more accurately than OLSK, and BIBI2 had a 7.69% improvement in accuracy as compared to BIBI. © 2017 Blackwell Verlag GmbH.
Bayesian Inference of Tumor Hypoxia
Gunawan, R.; Tenti, G.; Sivaloganathan, S.
2009-12-01
Tumor hypoxia is a state of oxygen deprivation in tumors. It has been associated with aggressive tumor phenotypes and with increased resistance to conventional cancer therapies. In this study, we report on the application of Bayesian sequential analysis in estimating the most probable value of tumor hypoxia quantification based on immunohistochemical assays of a biomarker. The `gold standard' of tumor hypoxia assessment is a direct measurement of pO2 in vivo by the Eppendorf polarographic electrode, which is an invasive technique restricted to accessible sites and living tissues. An attractive alternative is immunohistochemical staining to detect proteins expressed by cells during hypoxia. Carbonic anhydrase IX (CAIX) is an enzyme expressed on the cell membrane during hypoxia to balance the immediate extracellular microenvironment. CAIX is widely regarded as a surrogate marker of chronic hypoxia in various cancers. The study was conducted with two different experimental procedures. The first data set was a group of three patients with invasive cervical carcinomas, from which five biopsies were obtained. Each of the biopsies was fully sectioned and from each section, the proportion of CAIX-positive cells was estimated. Measurements were made by image analysis of multiple deep sections cut through these biopsies, labeled for CAIX using both immunofluorescence and immunohistochemical techniques [1]. The second data set was a group of 24 patients, also with invasive cervical carcinomas, from which two biopsies were obtained. Bayesian parameter estimation was applied to obtain a reliable inference about the proportion of CAIX-positive cells within the carcinomas, based on the available biopsies. From the first data set, two to three biopsies were found to be sufficient to infer the overall CAIX percentage in the simple form: best estimate±uncertainty. The second data-set led to a similar result in 70% of the cases. In the remaining cases Bayes' theorem warned us
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.
Philosophy and the practice of Bayesian statistics
Gelman, Andrew; Shalizi, Cosma Rohilla
2015-01-01
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. PMID:22364575
International Nuclear Information System (INIS)
Wang Rui; Wang Shaofeng; Wu Xiaozhi; Liang Xiao
2010-01-01
The method of homogeneous deformation is combined with first-principles total-energy calculations on determining third-order elastic constants and internal relaxation for monolayer graphene. We employ density functional theory (DFT) within generalized-gradient-approximation (GGA). The elastic constants are obtained from a polynomial fitted to the calculations of strain-energy and strain-stress relations. Our results agree well with recent calculations by DFT calculations, tight-binding atomistic simulations, and experiments with an atomic force microscope. The internal relaxation displacement has also been determined from ab initio calculations. The details of internal lattice relaxation by first principles are basically consistent with the previous molecular dynamics (MD) simulation. But for tiny deformation, there is an anomalous region in which the behavior of internal relaxation is backward action. In addition, we have also demonstrated that the symmetry of the relationship between the internal displacement and the infinitesimal stains can be satisfied.
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 particle...
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 with tem...
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 t...
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
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 ...
Enthalpy relaxation and annealing effect in polystyrene.
Sakatsuji, Waki; Konishi, Takashi; Miyamoto, Yoshihisa
2013-07-01
The effects of thermal history on the enthalpy relaxation in polystyrene are studied by differential scanning calorimetry. The temperature dependence of the specific heat in the liquid and the glassy states, that of relaxation time, and the exponent of the Kohlrausch-Williams-Watts function are determined by measurements of the thermal response against sinusoidal temperature variation. A phenomenological model equation previously proposed to interpret the memory effect in the frozen state is applied to the enthalpy relaxation and the evolution of entropy under a given thermal history is calculated. The annealing below the glass transition temperature produces two effects on enthalpy relaxation: the decay of excess entropy with annealing time in the early stage of annealing and the increase in relaxation time due to physical aging in the later stage. The crossover of these effects is reflected in the variation of temperature of the maximum specific heat observed in the heating process after annealing and cooling.
Stress and Relaxation in Relation to Personality
Directory of Open Access Journals (Sweden)
Harish Kumar Sharma
2011-09-01
Full Text Available Relaxation plays a significant role in facing stress. The aim of the present study is to see whether personality patterns determine an individual’s ability to relax. As a reaction to stress, coping is the best way to handle stress, which requires rational and conscious thinking. Does this ability to relax anyway facilitate coping reactions? A study was conducted on 100 college students. Results revealed that extraverts relax easily than introverts. In addition, if intelligence level is average or above average, relaxation does play a role in facilitating coping reactions. It suggests that in designing techniques of stress management, the personality and intelligence level must be taken into consideration to make techniques effective.
Babushkina, T. A.; Novikov, V. V.; Koretskaya, V. S.; Klimova, T. P.; Tsyurupa, M. P.; Blinnikova, Z. K.; Davankov, V. A.
2015-08-01
Dynamic properties of the water filling of the internal space of hypercrosslinked polystyrene networks are studied via NMR cryoporometry, spin relaxation, and diffusometry. It is found that in the temperature range of 210-240 K, where frozen water melts in the thin pores of the polymer and seems to become a viscous liquid, the main type of molecular motion is rotational and the main relaxation mechanism ( T 1) is spin-rotational interaction between protons. Above 240 K, dipole-dipole coupling is shown to become the main relaxation mechanism T 1. In the temperature range of 210-295 K, the hypercrosslinked polystyrene matrix displays a set of water spin-spin relaxation rates that suggest the structure has cavities (pores) with different sizes and different conditions for the molecular motion of water. We conclude that the shorter (tens of ms) relaxation times T 1 and T 2 of water in the polymer at the temperature above 265 K compared to free water (2-3 s) indicate features of the dynamic characteristics of water in hydrophobic pores (or thin films on the surfaces of granules) that differ from those of free water. The tortuosity coefficients of the water's path of molecular motion are found to change in a symbate manner with a change in the water content in the hypercrosslinked network.
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.
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
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.
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
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.
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.
"Swarm relaxation": Equilibrating a large ensemble of computer simulations⋆.
Malek, Shahrazad M A; Bowles, Richard K; Saika-Voivod, Ivan; Sciortino, Francesco; Poole, Peter H
2017-11-10
It is common practice in molecular dynamics and Monte Carlo computer simulations to run multiple, separately-initialized simulations in order to improve the sampling of independent microstates. Here we examine the utility of an extreme case of this strategy, in which we run a large ensemble of M independent simulations (a "swarm"), each of which is relaxed to equilibrium. We show that if M is of order [Formula: see text], we can monitor the swarm's relaxation to equilibrium, and confirm its attainment, within [Formula: see text], where [Formula: see text] is the equilibrium relaxation time. As soon as a swarm of this size attains equilibrium, the ensemble of M final microstates from each run is sufficient for the evaluation of most equilibrium properties without further sampling. This approach dramatically reduces the wall-clock time required, compared to a single long simulation, by a factor of several hundred, at the cost of an increase in the total computational effort by a small factor. It is also well suited to modern computing systems having thousands of processors, and is a viable strategy for simulation studies that need to produce high-precision results in a minimum of wall-clock time. We present results obtained by applying this approach to several test cases.
Molecular dynamics study on the relaxation properties of bilayered ...
Indian Academy of Sciences (India)
2017-08-31
Aug 31, 2017 ... arrangement of some double vacancies, which could be cre- ated either by the coalescence of two single point defects or by removing two neighbouring atoms. Grain boundaries are usu- ally formed by the 5–7 rings; with different arrangements, the grain boundary may remain flat or become inflected up to ...
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
Change in dielectric relaxation with the presence of water in highly filled composites
Directory of Open Access Journals (Sweden)
Enis Tuncer
2017-10-01
Full Text Available It is important to determine the dielectric characteristics of semiconductor encapsulation materials based on epoxy resins. We employed the dielectric spectroscopy technique to investigate the dielectric relaxation in the presence of water and how it changes the relaxation. It was observed that the dielectric relaxation of the material was significantly influenced by absorbed water, the local segmental motion (also known as Johari–Goldstein (β relaxation was influenced most by the presence of the water, it was modified by the wet sample compared to dry one, and required high activation energy. The relaxation related to the glass transition was contributed by the cooperative motion (the α-relaxation of the epoxy resin system. The α-relaxation was shifted to a low temperature in the wet sample compared to dry one. The relaxation was modeled with a clear Vogel–Fulcher–Tammann–Hesse (VFTH behavior; the Vogel temperature of the wet sample was 8K lower than the dry sample. The presence of water acts as a plasticizer for the molecular relaxation, and speed-up the cooperative process. The measured data were also used to estimate the electrical properties of the resin system by employing an effective-medium model together with a porous media continuum model by taking into account the physical properties of the system. It is already known that the influence of water in semiconductor packaging is important in sensitive applications. The presented measurements and the analysis method would be appreciated within the semiconductor packaging community to improve material selection and performance evaluation efforts.
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.
Logarithmic Decay in Single-Particle Relaxation of Hydrated Lysozyme Powder
Lagi, Marco; Baglioni, Piero; Chen, Sow-Hsin
2009-09-01
We present the self-dynamics of protein amino acids of hydrated lysozyme powder around the physiological temperature by means of molecular dynamics simulations. The self-intermediate scattering functions of the amino acid residue center of mass display a logarithmic decay over 3 decades of time, from 2 ps to 2 ns, followed by an exponential α relaxation. This kind of slow dynamics resembles the relaxation scenario within the β-relaxation time range predicted by mode coupling theory in the vicinity of higher-order singularities. These results suggest a strong analogy between the single-particle dynamics of the protein and the dynamics of colloidal, polymeric, and molecular glass-forming liquids.
Structural relaxation in dense liquids composed of anisotropic particles.
Shen, Tianqi; Schreck, Carl; Chakraborty, Bulbul; Freed, Denise E; O'Hern, Corey S
2012-10-01
We perform extensive molecular dynamics simulations of dense liquids composed of bidisperse dimer- and ellipse-shaped particles in two dimensions that interact via purely repulsive contact forces. We measure the structural relaxation times obtained from the long-time α decay of the self part of the intermediate scattering function for the translational and rotational degrees of freedom (DOF) as a function of packing fraction φ, temperature T, and aspect ratio α. We are able to collapse the packing-fraction and temperature-dependent structural relaxation times for disks, and dimers and ellipses over a wide range of α, onto a universal scaling function F(±)(|φ-φ(0)|,T,α), which is similar to that employed in previous studies of dense liquids composed of purely repulsive spherical particles in three dimensions. F(±) for both the translational and rotational DOF are characterized by the α-dependent scaling exponents μ and δ and packing fraction φ(0)(α) that signals the crossover in the scaling form F(±) from hard-particle dynamics to super-Arrhenius behavior for each aspect ratio. We find that the fragility of structural relaxation at φ(0), m(φ(0)), decreases monotonically with increasing aspect ratio for both ellipses and dimers. For α>α(p), where α(p) is the location of the peak in the packing fraction φ(J) at jamming onset, the rotational DOF are strongly coupled to the translational DOF, and the dynamic scaling exponents and φ(0) are similar for the rotational and translational DOF. For 1composed of dimer- and ellipse-shaped particles are qualitatively the same, despite the fact that zero-temperature static packings of dimers are isostatic, while static packings of ellipses are hypostatic. Thus, zero-temperature contact counting arguments do not apply to structural relaxation of dense liquids of anisotropic particles near the glass transition.
Bayesian phylogeography of the Arawak expansion in lowland South America.
Walker, Robert S; Ribeiro, Lincoln A
2011-09-07
Phylogenetic inference based on language is a vital tool for tracing the dynamics of human population expansions. The timescale of agriculture-based expansions around the world provides an informative amount of linguistic change ideal for reconstructing phylogeographies. Here we investigate the expansion of Arawak, one of the most widely dispersed language families in the Americas, scattered from the Antilles to Argentina. It has been suggested that Northwest Amazonia is the Arawak homeland based on the large number of diverse languages in the region. We generate language trees by coding cognates of basic vocabulary words for 60 Arawak languages and dialects to estimate the phylogenetic relationships among Arawak societies, while simultaneously implementing a relaxed random walk model to infer phylogeographic history. Estimates of the Arawak homeland exclude Northwest Amazonia and are bi-modal, with one potential homeland on the Atlantic seaboard and another more likely origin in Western Amazonia. Bayesian phylogeography better supports a Western Amazonian origin, and consequent dispersal to the Caribbean and across the lowlands. Importantly, the Arawak expansion carried with it not only language but also a number of cultural traits that contrast Arawak societies with other lowland cultures.
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.
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
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.
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.
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
Automated measurement of nuclear relaxation times
International Nuclear Information System (INIS)
Geist, A.G.; Mazitov, R.K.
1989-01-01
The authors describe a method for determination of nuclear relaxation times T 1 and T 2 that is based on the linear relationship between these times and the areas bounded by the relaxation curves. A circuit for automated measurement of time T 1 using a B3-35 microcalculator is presented. They have used the described method for a number of years to measure the relaxation times of various nuclei in solutions - in particular, those of 7 Li and 133 Cs in aqueous solutions. The method has proven to be highly effective and accurate and has greatly reduced the measurement time, especially in the case of long T 1
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...
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.
[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
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...
Compact vs. Exponential-Size LP Relaxations
Energy Technology Data Exchange (ETDEWEB)
Carr, R.D.; Lancia, G.
2000-09-01
In this paper we introduce by means of examples a new technique for formulating compact (i.e. polynomial-size) LP relaxations in place of exponential-size models requiring separation algorithms. In the same vein as a celebrated theorem by Groetschel, Lovasz and Schrijver, we state the equivalence of compact separation and compact optimization. Among the examples used to illustrate our technique, we introduce a new formulation for the Traveling Salesman Problem, whose relaxation we show equivalent to the subtour elimination relaxation.
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.
Dimensionality reduction in Bayesian estimation algorithms
Directory of Open Access Journals (Sweden)
G. W. Petty
2013-09-01
Full Text Available An idealized synthetic database loosely resembling 3-channel passive microwave observations of precipitation against a variable background is employed to examine the performance of a conventional Bayesian retrieval algorithm. For this dataset, algorithm performance is found to be poor owing to an irreconcilable conflict between the need to find matches in the dependent database versus the need to exclude inappropriate matches. It is argued that the likelihood of such conflicts increases sharply with the dimensionality of the observation space of real satellite sensors, which may utilize 9 to 13 channels to retrieve precipitation, for example. An objective method is described for distilling the relevant information content from N real channels into a much smaller number (M of pseudochannels while also regularizing the background (geophysical plus instrument noise component. The pseudochannels are linear combinations of the original N channels obtained via a two-stage principal component analysis of the dependent dataset. Bayesian retrievals based on a single pseudochannel applied to the independent dataset yield striking improvements in overall performance. The differences between the conventional Bayesian retrieval and reduced-dimensional Bayesian retrieval suggest that a major potential problem with conventional multichannel retrievals – whether Bayesian or not – lies in the common but often inappropriate assumption of diagonal error covariance. The dimensional reduction technique described herein avoids this problem by, in effect, recasting the retrieval problem in a coordinate system in which the desired covariance is lower-dimensional, diagonal, and unit magnitude.
Dimensionality reduction in Bayesian estimation algorithms
Petty, G. W.
2013-09-01
An idealized synthetic database loosely resembling 3-channel passive microwave observations of precipitation against a variable background is employed to examine the performance of a conventional Bayesian retrieval algorithm. For this dataset, algorithm performance is found to be poor owing to an irreconcilable conflict between the need to find matches in the dependent database versus the need to exclude inappropriate matches. It is argued that the likelihood of such conflicts increases sharply with the dimensionality of the observation space of real satellite sensors, which may utilize 9 to 13 channels to retrieve precipitation, for example. An objective method is described for distilling the relevant information content from N real channels into a much smaller number (M) of pseudochannels while also regularizing the background (geophysical plus instrument) noise component. The pseudochannels are linear combinations of the original N channels obtained via a two-stage principal component analysis of the dependent dataset. Bayesian retrievals based on a single pseudochannel applied to the independent dataset yield striking improvements in overall performance. The differences between the conventional Bayesian retrieval and reduced-dimensional Bayesian retrieval suggest that a major potential problem with conventional multichannel retrievals - whether Bayesian or not - lies in the common but often inappropriate assumption of diagonal error covariance. The dimensional reduction technique described herein avoids this problem by, in effect, recasting the retrieval problem in a coordinate system in which the desired covariance is lower-dimensional, diagonal, and unit magnitude.
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%.
How few? Bayesian statistics in injury biomechanics.
Cutcliffe, Hattie C; Schmidt, Allison L; Lucas, Joseph E; Bass, Cameron R
2012-10-01
In injury biomechanics, there are currently no general a priori estimates of how few specimens are necessary to obtain sufficiently accurate injury risk curves for a given underlying distribution. Further, several methods are available for constructing these curves, and recent methods include Bayesian survival analysis. This study used statistical simulations to evaluate the fidelity of different injury risk methods using limited sample sizes across four different underlying distributions. Five risk curve techniques were evaluated, including Bayesian techniques. For the Bayesian analyses, various prior distributions were assessed, each incorporating more accurate information. Simulated subject injury and biomechanical input values were randomly sampled from each underlying distribution, and injury status was determined by comparing these values. Injury risk curves were developed for this data using each technique for various small sample sizes; for each, analyses on 2000 simulated data sets were performed. Resulting median predicted risk values and confidence intervals were compared with the underlying distributions. Across conditions, the standard and Bayesian survival analyses better represented the underlying distributions included in this study, especially for extreme (1, 10, and 90%) risk. This study demonstrates that the value of the Bayesian analysis is the use of informed priors. As the mean of the prior approaches the actual value, the sample size necessary for good reproduction of the underlying distribution with small confidence intervals can be as small as 2. This study provides estimates of confidence intervals and number of samples to allow the selection of the most appropriate sample sizes given known information.
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).
Computationally efficient Bayesian inference for inverse problems.
Energy Technology Data Exchange (ETDEWEB)
Marzouk, Youssef M.; Najm, Habib N.; Rahn, Larry A.
2007-10-01
Bayesian statistics provides a foundation for inference from noisy and incomplete data, a natural mechanism for regularization in the form of prior information, and a quantitative assessment of uncertainty in the inferred results. Inverse problems - representing indirect estimation of model parameters, inputs, or structural components - can be fruitfully cast in this framework. Complex and computationally intensive forward models arising in physical applications, however, can render a Bayesian approach prohibitive. This difficulty is compounded by high-dimensional model spaces, as when the unknown is a spatiotemporal field. We present new algorithmic developments for Bayesian inference in this context, showing strong connections with the forward propagation of uncertainty. In particular, we introduce a stochastic spectral formulation that dramatically accelerates the Bayesian solution of inverse problems via rapid evaluation of a surrogate posterior. We also explore dimensionality reduction for the inference of spatiotemporal fields, using truncated spectral representations of Gaussian process priors. These new approaches are demonstrated on scalar transport problems arising in contaminant source inversion and in the inference of inhomogeneous material or transport properties. We also present a Bayesian framework for parameter estimation in stochastic models, where intrinsic stochasticity may be intermingled with observational noise. Evaluation of a likelihood function may not be analytically tractable in these cases, and thus several alternative Markov chain Monte Carlo (MCMC) schemes, operating on the product space of the observations and the parameters, are introduced.
Implantable magnetic relaxation sensors measure cumulative exposure to cardiac biomarkers.
Ling, Yibo; Pong, Terrence; Vassiliou, Christophoros C; Huang, Paul L; Cima, Michael J
2011-03-01
Molecular biomarkers can be used as objective indicators of pathologic processes. Although their levels often change over time, their measurement is often constrained to a single time point. Cumulative biomarker exposure would provide a fundamentally different kind of measurement to what is available in the clinic. Magnetic resonance relaxometry can be used to noninvasively monitor changes in the relaxation properties of antibody-coated magnetic particles when they aggregate upon exposure to a biomarker of interest. We used implantable devices containing such sensors to continuously profile changes in three clinically relevant cardiac biomarkers at physiological levels for up to 72 h. Sensor response differed between experimental and control groups in a mouse model of myocardial infarction and correlated with infarct size. Our prototype for a biomarker monitoring device also detected doxorubicin-induced cardiotoxicity and can be adapted to detect other molecular biomarkers with a sensitivity as low as the pg/ml range.
Directory of Open Access Journals (Sweden)
Massimo Giuliani
2013-01-01
Full Text Available Introduction. The evolutionary and demographic history of the circular recombinant form CRF02_AG in a selected retrospective group of HIV-1 infected men who have sex with men (MSM resident in Central Italy was investigated. Methods. A total of 55 HIV-1 subtype CRF02_AG pol sequences were analyzed using Bayesian methods and a relaxed molecular clock to reconstruct their dated phylogeny and estimate population dynamics. Results. Dated phylogeny indicated that the HIV-1 CRF02_AG strains currently circulating in Central Italy originated in the early 90's. Bayesian phylogenetic analysis revealed the existence of a main HIV-1 CRF02_AG clade, introduced in the area of Rome before 2000 and subsequently differentiated in two different subclades with a different date of introduction (2000 versus 2005. All the sequences within clusters were interspersed, indicating that the MSM analyzed form a close and restricted network where the individuals, also moving within different clinical centers, attend the same places to meet and exchange sex. Conclusions. It was suggested that the HIV-1 CRF02_AG epidemic entered central Italy in the early 1990s, with a similar trend observed in western Europe.
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
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...
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 t......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...... excellent agreement for the Likhtman-McLeish theory using the double reptation approximation for constraint release, if we remove the contribution of high-frequency modes to contour length fluctuations of the primitive chain....
The Irreversible Thermodynamics of Chemical Relaxation.
Schelly, Z. A.
1980-01-01
Discusses the thermodynamics of relaxation methods, considering (1) mode of perturbation of chemical equilibria, (2) enforced change of the concentrations, and (3) chemical contributions to equations of state. (CS)
Bayesian analysis of MEG visual evoked responses
Energy Technology Data Exchange (ETDEWEB)
Schmidt, D.M.; George, J.S.; Wood, C.C.
1999-04-01
The authors developed a method for analyzing neural electromagnetic data that allows probabilistic inferences to be drawn about regions of activation. The method involves the generation of a large number of possible solutions which both fir the data and prior expectations about the nature of probable solutions made explicit by a Bayesian formalism. In addition, they have introduced a model for the current distributions that produce MEG and (EEG) data that allows extended regions of activity, and can easily incorporate prior information such as anatomical constraints from MRI. To evaluate the feasibility and utility of the Bayesian approach with actual data, they analyzed MEG data from a visual evoked response experiment. They compared Bayesian analyses of MEG responses to visual stimuli in the left and right visual fields, in order to examine the sensitivity of the method to detect known features of human visual cortex organization. They also examined the changing pattern of cortical activation as a function of time.
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 modeling of unknown diseases for biosurveillance.
Shen, Yanna; Cooper, Gregory F
2009-11-14
This paper investigates Bayesian modeling of unknown causes of events in the context of disease-outbreak detection. We introduce a Bayesian approach that models and detects both (1) known diseases (e.g., influenza and anthrax) by using informative prior probabilities and (2) unknown diseases (e.g., a new, highly contagious respiratory virus that has never been seen before) by using relatively non-informative prior probabilities. We report the results of simulation experiments which support that this modeling method can improve the detection of new disease outbreaks in a population. A key contribution of this paper is that it introduces a Bayesian approach for jointly modeling both known and unknown causes of events. Such modeling has broad applicability in medical informatics, where the space of known causes of outcomes of interest is seldom complete.
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.
Can Transabdominal Sonography Predict Pelvic Relaxation?
Atoosa Adibi; Mahtab Zargham
2009-01-01
Introduction: Pelvic relaxation and cystocele is a common problem in middle to old age women. Transabdominal ultrasound (TAS) is a noninvasive, available routine procedure in many situations. We evaluated whether TAS can predict pelvic relaxation or not. "nMaterials and Methods: In a cross sectional case- control study one hundred women 30 years or older were enrolled into the study. An expert female urologist examined the cases for the presence of signs and the grading of pelvic relaxat...
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
Lagrange relaxation and Dantzig-Wolfe decomposition
DEFF Research Database (Denmark)
Vidal, Rene Victor Valqui
1989-01-01
The paper concerns a large-scale linear programming problem having a block-diagonal structure with coupling constraints. It is shown that there are deep connections between the Lagrange relaxation techniques and the Dantzig-Wolfe decomposition methods......The paper concerns a large-scale linear programming problem having a block-diagonal structure with coupling constraints. It is shown that there are deep connections between the Lagrange relaxation techniques and the Dantzig-Wolfe decomposition methods...
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.
Control of dipolar relaxation in external fields
Pasquiou, B.; Bismut, G.; Beaufils, Q.; Crubellier, A.; Maréchal, E.; Pedri, P.; Vernac, L.; Gorceix, O.; Laburthe-Tolra, B.
2010-04-01
We study dipolar relaxation in both ultracold thermal and Bose-condensed Cr atom gases. We show three different ways to control dipolar relaxation, making use of either a static magnetic field, an oscillatory magnetic field, or an optical lattice to reduce the dimensionality of the gas from three-dimensional (3D) to two-dimensional (2D). Although dipolar relaxation generally increases as a function of a static magnetic-field intensity, we find a range of nonzero magnetic-field intensities where dipolar relaxation is strongly reduced. We use this resonant reduction to accurately determine the S=6 scattering length of Cr atoms: a6=103±4a0. We compare this new measurement to another new determination of a6, which we perform by analyzing the precise spectroscopy of a Feshbach resonance in d-wave collisions, yielding a6=102.5±0.4a0. These two measurements provide, by far, the most precise determination of a6 to date. We then show that, although dipolar interactions are long-range interactions, dipolar relaxation only involves the incoming partial wave l=0 for large enough magnetic-field intensities, which has interesting consequences on the stability of dipolar Fermi gases. We then study ultracold Cr gases in a one-dimensional (1D) optical lattice resulting in a collection of independent 2D gases. We show that dipolar relaxation is modified when the atoms collide in reduced dimensionality at low magnetic-field intensities, and that the corresponding dipolar relaxation rate parameter is reduced by a factor up to 7 compared to the 3D case. Finally, we study dipolar relaxation in the presence of rf oscillating magnetic fields, and we show that both the output channel energy and the transition amplitude can be controlled by means of the rf frequency and Rabi frequency.
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...
Bayesian Inference in Polling Technique: 1992 Presidential Polls.
Satake, Eiki
1994-01-01
Explores the potential utility of Bayesian statistical methods in determining the predictability of multiple polls. Compares Bayesian techniques to the classical statistical method employed by pollsters. Considers these questions in the context of the 1992 presidential elections. (HB)
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
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.
On convex relaxation of graph isomorphism
Aflalo, Yonathan; Bronstein, Alexander; Kimmel, Ron
2015-01-01
We consider the problem of exact and inexact matching of weighted undirected graphs, in which a bijective correspondence is sought to minimize a quadratic weight disagreement. This computationally challenging problem is often relaxed as a convex quadratic program, in which the space of permutations is replaced by the space of doubly stochastic matrices. However, the applicability of such a relaxation is poorly understood. We define a broad class of friendly graphs characterized by an easily verifiable spectral property. We prove that for friendly graphs, the convex relaxation is guaranteed to find the exact isomorphism or certify its inexistence. This result is further extended to approximately isomorphic graphs, for which we develop an explicit bound on the amount of weight disagreement under which the relaxation is guaranteed to find the globally optimal approximate isomorphism. We also show that in many cases, the graph matching problem can be further harmlessly relaxed to a convex quadratic program with only n separable linear equality constraints, which is substantially more efficient than the standard relaxation involving 2n equality and n2 inequality constraints. Finally, we show that our results are still valid for unfriendly graphs if additional information in the form of seeds or attributes is allowed, with the latter satisfying an easy to verify spectral characteristic. PMID:25713342
Prediction of stress relaxation under multiaxial stresses
International Nuclear Information System (INIS)
Sandstroem, R.; Malen, K.; Otterberg, R.
1981-01-01
Computations have been made of the relaxation of residual stresses in a thick walled tube under conditions corresponding to commercial stress relief heat treatment of the nuclear reactor pressure vessel steel A533B. The distribution of residual stresses which were introduced was peaked around a given radius in the tube. The relax- ation of the equivalent stresses followed almost exactly a uniaxial behavior. The relaxation rate of the hydrostatic stress was of about the same order or slower than that of the equivalent stress. The time dependence of the hydrostatic stress was mainly controlled by the initial magnitude of hydrostatic stress whereas the degree of the constraint and thereby the boundary conditions at the tube walls had only a small influence. The relaxation rate decreased with increasing initial magnitude of the hydrostatic stress. The computed relaxation behaviour under multiaxial stress could be rationalized in terms of a developed model. This model was also suc- cessfully applied to Gott's measurements on stress relaxation during stress relief heat treatment of a welded joint between 130 mm thick plates of A533B where the stress state was highly triaxial. (Authors)
Fast relaxational motions in polycarbonate glass
International Nuclear Information System (INIS)
Saviot, L.; Duval, E.; Jal, J.F.; Dianoux, A.J.
1999-01-01
Complete text of publication follows. Inelastic neutron scattering from amorphous bis-phenol A polycarbonate was observed as a function of temperature from 15 K to 390 K (Tg = 420 K). The deduced mean square displacement and the vibrational density of states show that relaxational motions exist down to a temperature of 80 K. The relaxational scattering function, S(Q,t), can be described by two different regimes of relaxation: (1) a Debye-like process, with a characteristic time close to 1 ps, which is very weakly thermally activated; (2) a much slower process, which is thermally activated. The contribution of the fastest relaxation is related to the dynamical hole volume measured by positron annihilation lifetime spectroscopy, as already observed for the poly(methyl methacrylate) glass [1]. The dependence of the momentum transfer will be considered in order to obtain informations on the localization or diffusivity of the oberved different relaxations. This study of relaxation in a polymeric glass will be compared with a previous work [2]. (author)
Rindler fluid with weak momentum relaxation
Khimphun, Sunly; Lee, Bum-Hoon; Park, Chanyong; Zhang, Yun-Long
2018-01-01
We realize the weak momentum relaxation in Rindler fluid, which lives on the time-like cutoff surface in an accelerating frame of flat spacetime. The translational invariance is broken by massless scalar fields with weak strength. Both of the Ward identity and the momentum relaxation rate of Rindler fluid are obtained, with higher order correction in terms of the strength of momentum relaxation. The Rindler fluid with momentum relaxation could also be approached through the near horizon limit of cutoff AdS fluid with momentum relaxation, which lives on a finite time-like cutoff surface in Anti-de Sitter(AdS) spacetime, and further could be connected with the holographic conformal fluid living on AdS boundary at infinity. Thus, in the holographic Wilson renormalization group flow of the fluid/gravity correspondence with momentum relaxation, the Rindler fluid can be considered as the Infrared Radiation(IR) fixed point, and the holographic conformal fluid plays the role of the ultraviolet(UV) fixed point.
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
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...
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.
Bayesian inference and the parametric bootstrap
Efron, Bradley
2013-01-01
The parametric bootstrap can be used for the efficient computation of Bayes posterior distributions. Importance sampling formulas take on an easy form relating to the deviance in exponential families, and are particularly simple starting from Jeffreys invariant prior. Because of the i.i.d. nature of bootstrap sampling, familiar formulas describe the computational accuracy of the Bayes estimates. Besides computational methods, the theory provides a connection between Bayesian and frequentist analysis. Efficient algorithms for the frequentist accuracy of Bayesian inferences are developed and demonstrated in a model selection example. PMID:23843930
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.
Length Scales in Bayesian Automatic Adaptive Quadrature
Adam, Gh.; Adam, S.
2016-02-01
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.
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.
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.
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.
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|info:eu-repo/dai/nl/304833207; Kaplan, David; Denissen, Jaap; Asendorpf, Jens B.; Neyer, Franz J.; van Aken, Marcel A G|info:eu-repo/dai/nl/081831218
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,
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
Stress relaxation of narrow molar mass distribution polystyrene following uniaxial extension
DEFF Research Database (Denmark)
Nielsen, Jens Kromann; Rasmussen, Henrik K.; Hassager, Ole
2008-01-01
The stress in the startup of uniaxial elongational flow until steady state, followed by stress relaxation, has been measured for a narrow molar mass distribution polystyrene inelt with a molecular weight of 145 kg/mol. The experiments are conducted on a filament stretching rheometer, where a closed...... stress with the theoretically predicted stress from the Doi and Edwards model during relaxation, the stretch factors corresponding to each imposed stretch rate are obtained. These stretch factors converge to a unique envelope and eventually converge to unity for long times for all measured elongational...
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.
A Comparative Evaluation of Three Relaxation Training Procedures.
Brandon, Jeffrey E.
Comparison was made between the effectiveness of three relaxation training procedures: (1) Behavioral Relaxation Training, which consisted of training in relaxing specific parts of the body and controlling breathing; (2) Meditation (based on Benson's procedure for eliciting the relaxation response); and (3) Seashore Sounds "Attention Focusing,"…
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
Posterior Predictive Model Checking in Bayesian Networks
Crawford, Aaron
2014-01-01
This simulation study compared the utility of various discrepancy measures within a posterior predictive model checking (PPMC) framework for detecting different types of data-model misfit in multidimensional Bayesian network (BN) models. The investigated conditions were motivated by an applied research program utilizing an operational complex…
Sequential Bayesian technique: An alternative approach for ...
Indian Academy of Sciences (India)
This paper proposes a sequential Bayesian approach similar to Kalman ﬁlter for estimating reliability growth or decay of software. The main advantage of proposed method is that it shows the variation of the parameter over a time, as new failure data become available. The usefulness of the method is demonstrated with ...
Sequential Bayesian technique: An alternative approach for ...
Indian Academy of Sciences (India)
MS received 8 October 2007; revised 15 July 2008. Abstract. This paper proposes a sequential Bayesian approach similar to Kalman filter for estimating reliability growth or decay of software. The main advantage of proposed method is that it shows the variation of the parameter over a time, as new failure data become ...
Theory change and Bayesian statistical inference
Romeijn, Jan-Willem
2005-01-01
This paper addresses the problem that Bayesian statistical inference cannot accommodate theory change, and proposes a framework for dealing with such changes. It first presents a scheme for generating predictions from observations by means of hypotheses. An example shows how the hypotheses represent
Bayesian mixture models for partially verified data
DEFF Research Database (Denmark)
Kostoulas, Polychronis; Browne, William J.; Nielsen, Søren Saxmose
2013-01-01
Bayesian mixture models can be used to discriminate between the distributions of continuous test responses for different infection stages. These models are particularly useful in case of chronic infections with a long latent period, like Mycobacterium avium subsp. paratuberculosis (MAP) infection...
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.
Bayesian approach and application to operation safety
International Nuclear Information System (INIS)
Procaccia, H.; Suhner, M.Ch.
2003-01-01
The management of industrial risks requires the development of statistical and probabilistic analyses which use all the available convenient information in order to compensate the insufficient experience feedback in a domain where accidents and incidents remain too scarce to perform a classical statistical frequency analysis. The Bayesian decision approach is well adapted to this problem because it integrates both the expertise and the experience feedback. The domain of knowledge is widen, the forecasting study becomes possible and the decisions-remedial actions are strengthen thanks to risk-cost-benefit optimization analyzes. This book presents the bases of the Bayesian approach and its concrete applications in various industrial domains. After a mathematical presentation of the industrial operation safety concepts and of the Bayesian approach principles, this book treats of some of the problems that can be solved thanks to this approach: softwares reliability, controls linked with the equipments warranty, dynamical updating of databases, expertise modeling and weighting, Bayesian optimization in the domains of maintenance, quality control, tests and design of new equipments. A synthesis of the mathematical formulae used in this approach is given in conclusion. (J.S.)
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 ...
Neural network classification - A Bayesian interpretation
Wan, Eric A.
1990-01-01
The relationship between minimizing a mean squared error and finding the optimal Bayesian classifier is reviewed. This provides a theoretical interpretation for the process by which neural networks are used in classification. A number of confidence measures are proposed to evaluate the performance of the neural network classifier within a statistical framework.
Bayesian Estimation of Item Response Curves.
Tsutakawa, Robert K.; Lin, Hsin Ying
1986-01-01
Item response curves for a set of binary responses are studied from a Bayesian viewpoint of estimating the item parameters. For the two-parameter logistic model with normally distributed ability, restricted bivariate beta priors are used to illustrate the computation of the posterior mode via the EM algorithm. (Author/LMO)
Speech Segmentation Using Bayesian Autoregressive Changepoint Detector
Directory of Open Access Journals (Sweden)
P. Sovka
1998-12-01
Full Text Available This submission is devoted to the study of the Bayesian autoregressive changepoint detector (BCD and its use for speech segmentation. Results of the detector application to autoregressive signals as well as to real speech are given. BCD basic properties are described and discussed. The novel two-step algorithm consisting of cepstral analysis and BCD for automatic speech segmentation is suggested.
Bayesian networks: a combined tuning heuristic
Bolt, J.H.
2016-01-01
One of the issues in tuning an output probability of a Bayesian network by changing multiple parameters is the relative amount of the individual parameter changes. In an existing heuristic parameters are tied such that their changes induce locally a maximal change of the tuned probability. This
Exploiting structure in cooperative Bayesian games
Oliehoek, F.A.; Whiteson, S.; Spaan, M.T.J.; de Freitas, N.; Murphy, K.
2012-01-01
Cooperative Bayesian games (BGs) can model decision-making problems for teams of agents under imperfect information, but require space and computation time that is exponential in the number of agents. While agent independence has been used to mitigate these problems in perfect information settings,
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.
An Approximate Bayesian Fundamental Frequency Estimator
DEFF Research Database (Denmark)
Nielsen, Jesper Kjær; Christensen, Mads Græsbøll; Jensen, Søren Holdt
2012-01-01
Joint fundamental frequency and model order estimation is an important problem in several applications such as speech and music processing. In this paper, we develop an approximate estimation algorithm of these quantities using Bayesian inference. The inference about the fundamental frequency...
Erratum Bayesian and Dempster–Shafer fusion
Indian Academy of Sciences (India)
(1) The paper “Bayesian and Dempster–Shafer fusion” contains a mistake in Appendix A, although this has not affected anything in the body of the paper. On page 172, the authors state correctly that the matrix F is, in general, not square, but then in (A.22) they take its determinant. This confusion resulted because the ...
On local optima in learning bayesian networks
DEFF Research Database (Denmark)
Dalgaard, Jens; Kocka, Tomas; Pena, Jose
2003-01-01
This paper proposes and evaluates the k-greedy equivalence search algorithm (KES) for learning Bayesian networks (BNs) from complete data. The main characteristic of KES is that it allows a trade-off between greediness and randomness, thus exploring different good local optima. When greediness...
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.
Combining morphological analysis and Bayesian networks for ...
African Journals Online (AJOL)
... how these two computer aided methods may be combined to better facilitate modelling procedures. A simple example is presented, concerning a recent application in the field of environmental decision support. Keywords: Morphological analysis, Bayesian networks, strategic decision support. ORiON Vol. 23 (2) 2007: pp.
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.
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…
Theory Change and Bayesian Statistical Inference
Romeyn, Jan-Willem
2008-01-01
This paper addresses the problem that Bayesian statistical inference cannot accommodate theory change, and proposes a framework for dealing with such changes. It first presents a scheme for generating predictions from observations by means of hypotheses. An example shows how the hypotheses represent
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.
Default Bayesian Estimation of the Fundamental Frequency
DEFF Research Database (Denmark)
Nielsen, Jesper Kjær; Christensen, Mads Græsbøll; Jensen, Søren Holdt
2013-01-01
Joint fundamental frequency and model order esti- mation is an important problem in several applications. In this paper, a default estimation algorithm based on a minimum of prior information is presented. The algorithm is developed in a Bayesian framework, and it can be applied to both real...
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
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)
Bayesian Benefits for the Pragmatic Researcher
Wagenmakers, E.-J.; Morey, R.D.; Lee, M.D.
2016-01-01
The practical advantages of Bayesian inference are demonstrated here through two concrete examples. In the first example, we wish to learn about a criminal’s IQ: a problem of parameter estimation. In the second example, we wish to quantify and track support in favor of the null hypothesis that Adam