Molecular Relaxation in Liquids
Bagchi, Biman
2012-01-01
This book brings together many different relaxation phenomena in liquids under a common umbrella and provides a unified view of apparently diverse phenomena. It aligns recent experimental results obtained with modern techniques with recent theoretical developments. Such close interaction between experiment and theory in this area goes back to the works of Einstein, Smoluchowski, Kramers' and de Gennes. Development of ultrafast laser spectroscopy recently allowed study of various relaxation processes directly in the time domain, with time scales going down to picosecond (ps) and femtosecond (fs
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)
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 X1Σ+ and a3Σ+ states of LiH, NaH, KH, RbH, and CsH and the X2Σ+ 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 5000K. 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
NMR spin-lattice relaxation in molecular rotor systems
Wzietek, P
2015-01-01
A general expression is derived for the dipolar NMR spin-lattice relaxation rate $1/T_1$ of a system exhibiting Brownian dynamics in a discrete and finite configuration space. It is shown that this approach can be particularly useful to model the proton relaxation rate in molecular rotors.
Vďačný, Peter
2015-08-01
The class Litostomatea comprises a diverse assemblage of free-living and endosymbiotic ciliates. To understand diversification dynamic of litostomateans, divergence times of their main groups were estimated with the Bayesian molecular dating, a technique allowing relaxation of molecular clock and incorporation of flexible calibration points. The class Litostomatea very likely emerged during the Cryogenian around 680 Mya. The origin of the subclass Rhynchostomatia is dated to about 415 Mya, while that of the subclass Haptoria to about 654 Mya. The order Pleurostomatida, emerging about 556 Mya, was recognized as the oldest group within the subclass Haptoria. The order Spathidiida appeared in the Paleozoic about 442 Mya. The three remaining haptorian orders evolved in the Paleozoic/Mesozoic periods: Didiniida about 419 Mya, Lacrymariida about 269 Mya, and Haptorida about 194 Mya. The subclass Trichostomatia originated from a spathidiid ancestor in the Mesozoic about 260 Mya. A further goal of this study was to investigate the impact of various settings on posterior divergence time estimates. The root placement and tree topology as well as the priors of the rate-drift model, birth-death process and nucleotide substitution rate, had no significant effect on calculation of posterior divergence time estimates. However, removal of calibration points could significantly change time estimates at some nodes. PMID:26204556
Vďačný, Peter
2015-08-01
The class Litostomatea comprises a diverse assemblage of free-living and endosymbiotic ciliates. To understand diversification dynamic of litostomateans, divergence times of their main groups were estimated with the Bayesian molecular dating, a technique allowing relaxation of molecular clock and incorporation of flexible calibration points. The class Litostomatea very likely emerged during the Cryogenian around 680 Mya. The origin of the subclass Rhynchostomatia is dated to about 415 Mya, while that of the subclass Haptoria to about 654 Mya. The order Pleurostomatida, emerging about 556 Mya, was recognized as the oldest group within the subclass Haptoria. The order Spathidiida appeared in the Paleozoic about 442 Mya. The three remaining haptorian orders evolved in the Paleozoic/Mesozoic periods: Didiniida about 419 Mya, Lacrymariida about 269 Mya, and Haptorida about 194 Mya. The subclass Trichostomatia originated from a spathidiid ancestor in the Mesozoic about 260 Mya. A further goal of this study was to investigate the impact of various settings on posterior divergence time estimates. The root placement and tree topology as well as the priors of the rate-drift model, birth-death process and nucleotide substitution rate, had no significant effect on calculation of posterior divergence time estimates. However, removal of calibration points could significantly change time estimates at some nodes.
Free-volume hole relaxation in molecularly oriented glassy polymers
Xia, Zhiyong; Trexler, Morgana; Wu, Fei; Jean, Yan-Ching; Van Horn, J. David
2014-02-01
The free-volume hole relaxation in polycarbonate and poly(methyl methacrylate) with different levels of molecular orientation was studied by positron annihilation lifetime spectroscopy at variable pressures. The molecular orientation was achieved through a simple shear process performed at different temperatures and extrusion rates. It has been demonstrated that the β relaxation is largely responsible for the free-volume hole anisotropy after simple shear orientation. Upon the removal of mechanical force, the deformation of the free volume is mostly reversible at temperatures much lower than the glass transition. No strong correlation between macroscopic deformation and the free-volume hole deformation was found regardless of molecular orientation.
C60 molecular dynamics studied by muon spin relaxation
International Nuclear Information System (INIS)
In muonium-substituted organic radicals, the muon spin can serve as a probe of molecular dynamics. The motional perturbation induces transitions between the coupled spin states of muon and unpaired electron. Studies of the resultant muon spin relaxation in C60Mu, the species formed by muon implantation in solid C60, yield the correlation time characteristic of the reorientational motion
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...... 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...
Experimentally Constrained Molecular Relaxation: The case of hydrogenated amorphous silicon
Biswas, Parthapratim; Atta-Fynn, Raymond; Drabold, David A.
2007-01-01
We have extended our experimentally constrained molecular relaxation technique (P. Biswas {\\it et al}, Phys. Rev. B {\\bf 71} 54204 (2005)) to hydrogenated amorphous silicon: a 540-atom model with 7.4 % hydrogen and a 611-atom model with 22 % hydrogen were constructed. Starting from a random configuration, using physically relevant constraints, {\\it ab initio} interactions and the experimental static structure factor, we construct realistic models of hydrogenated amorphous silicon. Our models ...
Low-temperature magnetization relaxation in magnetic molecular solids
Energy Technology Data Exchange (ETDEWEB)
Vijayaraghavan, Avinash; Garg, Anupam, E-mail: agarg@northwestern.edu
2013-08-15
The low temperature relaxation of the magnetization in molecular magnetic solids such as Fe{sub 8} is studied using Monte Carlo simulations. A set of rate equations is then developed to understand the simulations, and the results are compared. The simulations show that the magnetization of an initially saturated sample deviates as a square-root in time at short times, as observed experimentally, and this law is derived from the rate equations analytically. -- Highlights: •A novel set of non-linear rate equations for the coupled evolution of the magnetization and dipole field distribution. •An analytic derivation of the short-time square root in time behavior of the magnetization relaxation. •Agreement between theory and simulations without further fitting parameters.
Excitation dynamics and relaxation in a molecular heterodimer
Energy Technology Data Exchange (ETDEWEB)
Balevicius, V.; Gelzinis, A. [Department of Theoretical Physics, Faculty of Physics, Vilnius University, Sauletekio Avenue 9, build. 3, LT-10222 Vilnius (Lithuania); Center for Physical Sciences and Technology, Institute of Physics, Savanoriu Avenue 231, LT-02300 Vilnius (Lithuania); Abramavicius, D. [Department of Theoretical Physics, Faculty of Physics, Vilnius University, Sauletekio Avenue 9, build. 3, LT-10222 Vilnius (Lithuania); State Key Laboratory of Supramolecular Structure and Materials, Jilin University, 2699 Qianjin Street, Changchun 130012 (China); Mancal, T. [Faculty of Mathematics and Physics, Charles University in Prague, Ke Karlovu 5, CZ-121 16 Prague 2 (Czech Republic); Valkunas, L., E-mail: leonas.valkunas@ff.vu.lt [Department of Theoretical Physics, Faculty of Physics, Vilnius University, Sauletekio Avenue 9, build. 3, LT-10222 Vilnius (Lithuania); Center for Physical Sciences and Technology, Institute of Physics, Savanoriu Avenue 231, LT-02300 Vilnius (Lithuania)
2012-08-24
Highlights: Black-Right-Pointing-Pointer Dynamics of excitation within a heterogenous molecular dimer. Black-Right-Pointing-Pointer Excited states can be swapped due to different reorganization energies of monomers. Black-Right-Pointing-Pointer Conventional excitonic basis becomes renormalized due to interaction with the bath. Black-Right-Pointing-Pointer Relaxation is independent of mutual positioning of monomeric excited states. -- Abstract: The exciton dynamics in a molecular heterodimer is studied as a function of differences in excitation and reorganization energies, asymmetry in transition dipole moments and excited state lifetimes. The heterodimer is composed of two molecules modeled as two-level systems coupled by the resonance interaction. The system-bath coupling is taken into account as a modulating factor of the molecular excitation energy gap, while the relaxation to the ground state is treated phenomenologically. Comparison of the description of the excitation dynamics modeled using either the Redfield equations (secular and full forms) or the Hierarchical quantum master equation (HQME) is demonstrated and discussed. Possible role of the dimer as an excitation quenching center in photosynthesis self-regulation is discussed. It is concluded that the system-bath interaction rather than the excitonic effect determines the excitation quenching ability of such a dimer.
Zhu, Tianqi; Dos Reis, Mario; Yang, Ziheng
2015-03-01
Genetic sequence data provide information about the distances between species or branch lengths in a phylogeny, but not about the absolute divergence times or the evolutionary rates directly. Bayesian methods for dating species divergences estimate times and rates by assigning priors on them. In particular, the prior on times (node ages on the phylogeny) incorporates information in the fossil record to calibrate the molecular tree. Because times and rates are confounded, our posterior time estimates will not approach point values even if an infinite amount of sequence data are used in the analysis. In a previous study we developed a finite-sites theory to characterize the uncertainty in Bayesian divergence time estimation in analysis of large but finite sequence data sets under a strict molecular clock. As most modern clock dating analyses use more than one locus and are conducted under relaxed clock models, here we extend the theory to the case of relaxed clock analysis of data from multiple loci (site partitions). Uncertainty in posterior time estimates is partitioned into three sources: Sampling errors in the estimates of branch lengths in the tree for each locus due to limited sequence length, variation of substitution rates among lineages and among loci, and uncertainty in fossil calibrations. Using a simple but analogous estimation problem involving the multivariate normal distribution, we predict that as the number of loci ([Formula: see text]) goes to infinity, the variance in posterior time estimates decreases and approaches the infinite-data limit at the rate of 1/[Formula: see text], and the limit is independent of the number of sites in the sequence alignment. We then confirmed the predictions by using computer simulation on phylogenies of two or three species, and by analyzing a real genomic data set for six primate species. Our results suggest that with the fossil calibrations fixed, analyzing multiple loci or site partitions is the most effective way
Bayesian molecular phylogenetics: estimation of divergence dates and hypothesis testing
Aris-Brosou, S.
2002-01-01
With the advent of automated sequencing, sequence data are now available to help us understand the functioning of our genome, as well as its history. To date,powerful methods such as maximum likelihood have been used to estimate its mode and tempo of evolution and its branching pattern. However, these methods appear to have some limitations. The purpose of this thesis is to examine these issues in light of Bayesian modelling, taking advantage of some recent advances in Bayesian compu...
Theoretical Studies of the Relaxation Matrix for Molecular Systems
Ma, Qiancheng; Boulet, C.
2016-06-01
The phenomenon of collisional transfer of intensity due to line mixing has an increasing importance for atmospheric monitoring. From a theoretical point of view, all relevant information about the collisional processes is contained in the relaxation matrix where the diagonal elements give half-widths and shifts, and the off-diagonal elements correspond to line interferences. For simple systems such as those consisting of diatom-atom or diatom-diatom, accurate fully quantum calculations based on interaction potentials are feasible. However, fully quantum calculations become unrealistic for more complex systems. On the other hand, the semi-classical Robert-Bonamy formalism, which has been widely used to calculate half-widths and shifts for decades, fails in calculating the off-diagonal matrix elements resulting from applying the isolated line approximation. As a result, in order to simulate atmospheric spectra where the effects from line mixing are important, semi-empirical fitting or scaling laws such as the energy corrected sudden (ECS) and the infinite order sudden (IOS) models are commonly used. Recently, we have found that in developing this semi-classical line shape theory, to rely on the isolated line approximation is not necessary. By eliminating this unjustified assumption, and accurately evaluating matrix elements of the exponential operators, we have developed a more capable formalism that enables one not only to reduce uncertainties for calculated half-widths and shifts, but also to calculate the whole relaxation matrix. This implies that we can address the line mixing with the semi-classical theory based on interaction potentials between molecular absorber and molecular perturber. We have applied this formalism for Raman and infrared spectra of linear and asymmetric-top molecules. Recently, the method has been extended into symmetric-tops with inverse symmetry such as the NH3 molecule. Our calculated half-widths of NH3 lines in the νb{1} and the pure
Iwaoka, Nobuyuki; Hagita, Katsumi; Takano, Hiroshi
2014-03-01
On the basis of relaxation mode analysis (RMA), we present an efficient method to estimate the linear viscoelasticity of polymer melts in a molecular dynamics (MD) simulation. Slow relaxation phenomena appeared in polymer melts cause a problem that a calculation of the stress relaxation function in MD simulations, especially in the terminal time region, requires large computational efforts. Relaxation mode analysis is a method that systematically extracts slow relaxation modes and rates of the polymer chain from the time correlation of its conformations. We show the computational cost may be drastically reduced by combining a direct calculation of the stress relaxation function based on the Green-Kubo formula with the relaxation rates spectra estimated by RMA. N. I. acknowledges the Graduate School Doctoral Student Aid Program from Keio University.
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...... 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...... 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...
Bayesian molecular clock dating of species divergences in the genomics era.
dos Reis, Mario; Donoghue, Philip C J; Yang, Ziheng
2016-02-01
Five decades have passed since the proposal of the molecular clock hypothesis, which states that the rate of evolution at the molecular level is constant through time and among species. This hypothesis has become a powerful tool in evolutionary biology, making it possible to use molecular sequences to estimate the geological ages of species divergence events. With recent advances in Bayesian clock dating methodology and the explosive accumulation of genetic sequence data, molecular clock dating has found widespread applications, from tracking virus pandemics and studying the macroevolutionary process of speciation and extinction to estimating a timescale for life on Earth.
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. PMID:24125208
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.
Rotational relaxation of molecular ions in a buffer gas
Pérez-Ríos, Jesús; Robicheaux, F.
2016-09-01
The scattering properties regarding the rotational degrees of freedom of a molecular ion in the presence of a buffer gas of helium are investigated. This study is undertaken within the framework of the infinite-order sudden approximation for rotational transitions, which is shown to be applicable to a large variety of molecular ions in a buffer gas of helium at fairly low temperatures. The results derived from the present approach have potential applications in cold chemistry and molecular quantum logic spectroscopy.
Molecular mobility of amorphous S-flurbiprofen: a dielectric relaxation spectroscopy approach.
Rodrigues, A C; Viciosa, M T; Danède, F; Affouard, F; Correia, N T
2014-01-01
Amorphous S-flurbiprofen was obtained by the melt quench/cooling method. Dielectric measurements performed in the isochronal mode, conventional and temperature modulated differential scanning calorimetry (TMDSC) studies showed a glass transition, recrystallization, and melting. The different parameters characterizing the complex molecular dynamics of amorphous S-flurbiprofen that can have influence on crystallization and stability were comprehensively characterized by dielectric relaxation spectroscopy experiments (isothermal mode) covering a wide temperature (183 to 408 K) and frequency range (10(-1) to 10(6) Hz): width of the α-relaxation (βKWW), temperature dependence of α-relaxation times (τα), fragility index (m), relation of the α-relaxation with the β-secondary relaxation, and the breakdown of the Debye-Stokes-Einstein (DSE) relationship between the structural relaxation time and dc-conductivity (σdc) at deep undercooling close to Tg. The β-relaxation, observed in the glassy as well as in the supercooled state was identified as the genuine Johari-Goldstein process, attributed to localized motions and regarded as the precursor of the α-relaxation as suggested in the coupling model. A separation of about 6 decades between the α- and β-relaxation was observed at Tg; this decoupling decreased on increasing temperature, and both processes merged at Tαβ = 295 K. The temperature dependence of the α-relaxation time, τα, was described by two Vogel-Fulcher-Tammann-Hesse equations, which intercept at a crossover temperature, TB = 290 K, close to the splitting temperature between the α- and β-relaxation. From the low temperature VFTH equation, a Tg(DRS) = 265.2 was estimated (at τα =100 s) in good agreement with the calorimetric value (Tg,onset,TMDSC = 265.6 K), and a fragility or steepness index m = 113 was calculated allowing to classify S-flurbiprofen as a fragile glass former. The α-relaxation spectra were found to be characterized by a
Petculescu, Andi G; Lueptow, Richard M
2005-06-17
Identifying molecular relaxation processes in excitable gases remains challenging. An algorithm that reconstructs the primary relaxation processes is presented. Based on measurements of acoustic attenuation and sound speed at two frequencies, it synthesizes the entire frequency dependence of the complex effective specific heat of the gas, which is the macroscopic "footprint" of relaxation effects. The algorithm is based on the fact that for a simple relaxation process, such as occurs in many polyatomic gases at temperatures around 300 K, the effective specific heat traces a semicircle in the complex plane as a function of frequency. Knowing the high-frequency or instantaneous value of the specific heat provides the capability to not only sense the presence, but also infer the nature and, for mixtures of unlike-symmetry molecules, the concentration of foreign molecules leaking in a host gas. PMID:16090508
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)
Recent potential energy surfaces (PESs) for the N2 + N and N2 + N2 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 N2 + N2 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 N2 dissociation rate from MD/QCT show a profile with a decreased translational temperature and a rotational temperature close to vibrational temperature. The results demonstrate that many of the physical models employed in DSMC should be revised as fundamental potential energy surfaces suitable for high temperature conditions become available
A study of internal energy relaxation in shocks using molecular dynamics based models
Energy Technology Data Exchange (ETDEWEB)
Li, Zheng, E-mail: zul107@psu.edu; Parsons, Neal, E-mail: neal.parsons@cd-adapco.com [Department of Aerospace Engineering, The Pennsylvania State University, University Park, Pennsylvania 16802 (United States); Levin, Deborah A., E-mail: deblevin@illinois.edu [Department of Aerospace Engineering, University of Illinois Urbana-Champaign, Urbana, Illinois 61801-2935 (United States)
2015-10-14
Recent potential energy surfaces (PESs) for the N{sub 2} + N and N{sub 2} + N{sub 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{sub 2} + N{sub 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{sub 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.
Aso, Y; Yoshioka, S; Kojima, S
2000-03-01
Isothermal crystallization of amorphous nifedipine, phenobarbital, and flopropione was studied at temperatures above and below their glass transition temperatures (T(g)). A sharp decrease in the crystallization rate with decreasing temperature was observed for phenobarbital and flopropione, such that no crystallization was observed at temperatures 20-30 degrees C lower than their T(g) within ordinary experimental time periods. In contrast, the crystallization rate of nifedipine decreased moderately with decreasing temperature, and considerable crystallization was observed at 40 degrees C below its T(g) within 4 months. The molecular mobility of these amorphous drugs was assessed by enthalpy relaxation and (1)H-NMR relaxation measurements. The enthalpy relaxation time of nifedipine was smaller than that of phenobarbital or flopropinone at the same T - T(g) values, suggesting higher molecular mobility of nifedipine. The spin-lattice relaxation time in the rotating frame (T(1rho)) decreased markedly at temperature above T(g). The slope of the Arrhenius type plot of the T(1rho) for nifedipine protons changed at about 10 degrees C below the T(g), whereas the slope for phenobarbital protons became discontinuous at about 10 degrees C above the T(g). Even at temperatures below its T(g), the spin-spin relaxation process of nifedipine could be described by the sum of its Gaussian relaxation, which is characteristic of solid protons, and its Lorentzian relaxation, which is characteristic of protons with higher mobility. In contrast, no Lorentzian relaxation was observed for phenobarbital or flopropione at temperatures below their T(g). These results also suggest that nifedipine has higher molecular mobility than phenobarbital and flopropione at temperatures below T(g). The faster crystallization of nifedipine than that of phenobarbital or flopropione observed at temperatures below its T(g) may be partly ascribed to its higher molecular mobility at these temperatures.
Rottler, Jörg
2016-08-01
Relaxation times in polymer glasses are computed with molecular dynamics simulations of a coarse-grained polymer model during creep and constant strain rate deformation. The dynamics is governed by a competition between physical aging that increases relaxation times and applied load or strain rate which accelerates dynamics. We compare the simulation results quantitatively to two recently developed theories of polymer deformation, which treat aging and rejuvenation in an additive manner. Through stress release and strain rate reversal simulations, we then show that the quantity governing mechanical rejuvenation is the rate of irreversible work performed on the polymer.
Molecular Dynamics Simulation on Charge Transfer Relaxation between Myoglobin and Water
Institute of Scientific and Technical Information of China (English)
CHENG Wei; ZHANG Feng-Shou; ZHANG Bo-Yang; ZHOU Hong-Yu
2007-01-01
Dynamical processes of myoglobin after photon-excited charge transfer between Fe ion and surrounding water anion ale simulated by a molecular dynamics model.The roles of Coulomb interaction effect and water effect in the relaxation process are discussed.It is found that the relaxations before and after charge transfer are similar.Strong Coulomb interactions and less water mobility decrease Coulomb energy fluctuations.An extra transferred charge of Fe ion has impact on water packing with a distance up to 0.86nm.
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.
MOLECULAR DYNAMICS SIMULATION OF THE RELAXATION OF A FULLY EXTENDED POLYETHYLENE CHAIN
Institute of Scientific and Technical Information of China (English)
Yan Chen; Xiao-zhen Yang; Mao Xu; Ren-yuan Qian
1999-01-01
Molecular dynamics simulation of the relaxation at 300 K of a fully extended polyethylene chain of 800 CH2 units has been carried out by following the changes in morphology, van der Waals energy, radius of gyration in the sense of mechanics and gyration radius in the sense of Flory, population of trans-conformation and orientation factor. The relaxation went through three stages: (1) relaxation from the morphology of a straight rod of 100 nm length to the morphology close to a random coil of gyration radius 5.9nm in 110 ps; (2) collapse of the morphology of a coil to a highly compact globule close to a sphere of gyration radius 1.3 nm after 178 ps as the result of intersegmental van der Waals attractive interactions; (3)lateral ordering of the folded chain segments in the globule without appreciable changes in the chain dimension up to 1600 ps, the time limit of present simulation. Nearly complete relaxation of local segmental orientation was performed much faster than the relaxation of globule chain orientation even for a single chain of low degree of polymerization and at a temperature some 155℃ above its Tg. The lateral ordering of the chain segments during the period 178 to 680 ps of the simulation time was found to obey the Avrami equation with an Avrami index of 1.44.
International Nuclear Information System (INIS)
The incoherent intermediate scattering function Sinc(Q,t) of polybutadiene (PB) and polyisobutylene (PIB) is measured on the neutron backscattering instrument IN16 in the ns-time range and in a temperature and pressure range where the observed relaxation is ascribed to segmental relaxation. Sinc(Q,t) at atmospheric pressure Patm, for PB at T=300 K and for PIB at T=368 K, shows a characteristic momentum transfer (Q) dependence, if fitted by a single stretched exponential relaxation process Sinc(Q,t)=A(Q)exp(-t/τKWW)β with fixed β=0.45 for PB and β=0.55 for PIB. For both polymers the Q-dependence of the relaxation time τKWW(Q) in the range 0.2 A-1-1 is compatible with a crossover from a power law τKWW(Q)∼Q-2/β at low Q to τKWW(Q)∼Q-2 at high Q. Application of pressure results for both polymers in an extension of the Q-2-range towards lower Q. A variation of the molecular weight (390w-2 behaviour. For Mwg we find relaxations at higher energy (0.1-1 meV) which we ascribe tentatively to end-of-chain motions. Furthermore, we show for PB the possibility to separate thermal and density effects onto Sinc(Q,t) by controlling pressure along different thermodynamic paths
Valentini, Paolo; Zhang, Chonglin; Schwartzentruber, Thomas E.
2012-10-01
We study the rotational relaxation process in nitrogen using all-atom molecular dynamics (MD) simulations and direct simulation Monte Carlo (DSMC). The intermolecular model used in the MD simulations is shown to (i) reproduce very well the shear viscosity of nitrogen over a wide range of temperatures, (ii) predict the near-equilibrium rotational collision number in good agreement with published trajectory calculations done on ab initio potential energy surfaces, and (iii) produce shock wave profiles in excellent accordance with the experimental measurements. We find that the rotational relaxation process is dependent not only on the near-equilibrium temperature (i.e., when systems relax to equilibrium after a small perturbation), but more importantly on both the magnitude and direction of the initial deviation from the equilibrium state. The comparison between MD and DSMC, based on the Borgnakke-Larsen model, for shock waves (both at low and high temperatures) and one-dimensional expansions shows that a judicious choice of a constant Zrot can produce DSMC results which are in relatively good agreement with MD. However, the selection of the rotational collision number is case-specific, depending not only on the temperature range, but more importantly on the type of flow (compression or expansion), with significant limitations for more complex simulations characterized both by expansion and compression zones. Parker's model, parametrized for nitrogen, overpredicts Zrot for temperatures above about 300 K. It is also unable to describe the dependence of the relaxation process on the direction to equilibrium. Finally, we present a demonstrative cell-based formulation of a rotational relaxation model to illustrate how, by including the key physics obtained from the MD data (dependence of the relaxation process on both the rotational and the translational state of the gas), the agreement between MD and DSMC solutions is drastically improved.
(14)N NQR, relaxation and molecular dynamics of the explosive TNT.
Smith, John A S; Rowe, Michael D; Althoefer, Kaspar; Peirson, Neil F; Barras, Jamie
2015-10-01
Multiple pulse sequences are widely used for signal enhancement in NQR detection applications. Since the various (14)N NQR relaxation times, signal decay times and frequency of each NQR line have a major influence on detection sequence performance, it is important to characterise these parameters and their temperature variation, as fully as possible. In this paper we discuss such measurements for a number of the ν+ and ν- NQR lines of monoclinic and orthorhombic TNT and relate the temperature variation results to molecular dynamics. The temperature variation of the (14)N spin-lattice relaxation times T1 is interpreted as due to hindered rotation of the NO2 group about the C-NO2 bond with an activation energy of 89 kJ mol(-1) for the ortho and para groups of monoclinic TNT and 70 kJ mol(-1) for the para group of orthorhombic TNT.
DEFF Research Database (Denmark)
Roed, Lisa Anita; Niss, Kristine; Jakobsen, Bo
2015-01-01
liquids in which different physical relaxation processes are both as function of temperature and pressure/density governed by the same underlying “inner clock.” Furthermore, the results are discussed in terms of the recent conjecture that van der Waals liquids, like the measuredliquid, comply to the......The frequency dependent specific heat has been measured under pressure for the molecular glass forming liquid 5-polyphenyl-4-ether in the viscous regime close to the glass transition. The temperature and pressure dependences of the characteristic time scale associated with the specific heat is...
Dielectric relaxation in ionic liquid/dipolar solvent binary mixtures: A semi-molecular theory.
Daschakraborty, Snehasis; Biswas, Ranjit
2016-03-14
A semi-molecular theory is developed here for studying dielectric relaxation (DR) in binary mixtures of ionic liquids (ILs) with common dipolar solvents. Effects of ion translation on DR time scale, and those of ion rotation on conductivity relaxation time scale are explored. Two different models for the theoretical calculations have been considered: (i) separate medium approach, where molecularities of both the IL and dipolar solvent molecules are retained, and (ii) effective medium approach, where the added dipolar solvent molecules are assumed to combine with the dipolar ions of the IL, producing a fictitious effective medium characterized via effective dipole moment, density, and diameter. Semi-molecular expressions for the diffusive DR times have been derived which incorporates the effects of wavenumber dependent orientational static correlations, ion dynamic structure factors, and ion translation. Subsequently, the theory has been applied to the binary mixtures of 1-butyl-3-methylimidazolium tetrafluoroborate ([Bmim][BF4]) with water (H2O), and acetonitrile (CH3CN) for which experimental DR data are available. On comparison, predicted DR time scales show close agreement with the measured DR times at low IL mole fractions (x(IL)). At higher IL concentrations (x(IL) > 0.05), the theory over-estimates the relaxation times and increasingly deviates from the measurements with x(IL), deviation being the maximum for the neat IL by almost two orders of magnitude. The theory predicts negligible contributions to this deviation from the x(IL) dependent collective orientational static correlations. The drastic difference between DR time scales for IL/solvent mixtures from theory and experiments arises primarily due to the use of the actual molecular volume (V(mol)(dip)) for the rotating dipolar moiety in the present theory and suggests that only a fraction of V(mol)(dip) is involved at high x(IL). Expectedly, nice agreement between theory and experiments appears when
Dielectric relaxation in ionic liquid/dipolar solvent binary mixtures: A semi-molecular theory
Daschakraborty, Snehasis; Biswas, Ranjit
2016-03-01
A semi-molecular theory is developed here for studying dielectric relaxation (DR) in binary mixtures of ionic liquids (ILs) with common dipolar solvents. Effects of ion translation on DR time scale, and those of ion rotation on conductivity relaxation time scale are explored. Two different models for the theoretical calculations have been considered: (i) separate medium approach, where molecularities of both the IL and dipolar solvent molecules are retained, and (ii) effective medium approach, where the added dipolar solvent molecules are assumed to combine with the dipolar ions of the IL, producing a fictitious effective medium characterized via effective dipole moment, density, and diameter. Semi-molecular expressions for the diffusive DR times have been derived which incorporates the effects of wavenumber dependent orientational static correlations, ion dynamic structure factors, and ion translation. Subsequently, the theory has been applied to the binary mixtures of 1-butyl-3-methylimidazolium tetrafluoroborate ([Bmim][BF4]) with water (H2O), and acetonitrile (CH3CN) for which experimental DR data are available. On comparison, predicted DR time scales show close agreement with the measured DR times at low IL mole fractions (xIL). At higher IL concentrations (xIL > 0.05), the theory over-estimates the relaxation times and increasingly deviates from the measurements with xIL, deviation being the maximum for the neat IL by almost two orders of magnitude. The theory predicts negligible contributions to this deviation from the xIL dependent collective orientational static correlations. The drastic difference between DR time scales for IL/solvent mixtures from theory and experiments arises primarily due to the use of the actual molecular volume ( Vmol dip ) for the rotating dipolar moiety in the present theory and suggests that only a fraction of Vmol dip is involved at high xIL. Expectedly, nice agreement between theory and experiments appears when experimental
A directional rotational relaxation model for nitrogen using molecular dynamics simulation
Valentini, Paolo; Zhang, Chongling; Schwartzentruber, Thomas E.
2012-11-01
We use Molecular Dynamics (MD) simulation to investigate rotational relaxation in nitrogen from a first-principles perspective. The rotational relaxation process is found to be dependent not only on the near-equilibrium temperature, but more importantly on both the magnitude and direction of the initial deviation from the equilibrium state. Although this dependence has been previously recognized, it is here investigated systematically. The comparison between MD and Direct Simulation Monte Carlo (DSMC), based on the Larsen-Borgnakke model, for shock waves (both at low and high temperatures) and onedimensional expansions shows that a judicious choice of a constant Zrot can produce DSMC results which are in relatively good agreement with MD. However, the selection of the rotational collision number is case-specific, depending not only on the temperature range, but more importantly on the type of flow (compression or expansion). Parker's model, with the commonly used parameters for nitrogen suggested by Lordi and Mates, overpredicts the magnitude of Zrot for temperatures above about 300 K. Finally, based on the MD data, a preliminary formulation for a novel directional rotational relaxation model, which includes a dependence on both the rotational and the translational state of the gas, is presented.
Conversion of an atomic to a molecular argon ion and low pressure argon relaxation
M, N. Stankov; A, P. Jovanović; V, Lj Marković; S, N. Stamenković
2016-01-01
The dominant process in relaxation of DC glow discharge between two plane parallel electrodes in argon at pressure 200 Pa is analyzed by measuring the breakdown time delay and by analytical and numerical models. By using the approximate analytical model it is found that the relaxation in a range from 20 to 60 ms in afterglow is dominated by ions, produced by atomic-to-molecular conversion of Ar+ ions in the first several milliseconds after the cessation of the discharge. This conversion is confirmed by the presence of double-Gaussian distribution for the formative time delay, as well as conversion maxima in a set of memory curves measured in different conditions. Finally, the numerical one-dimensional (1D) model for determining the number densities of dominant particles in stationary DC glow discharge and two-dimensional (2D) model for the relaxation are used to confirm the previous assumptions and to determine the corresponding collision and transport coefficients of dominant species and processes. Project supported by the Ministry of Education, Science and Technological Development of the Republic of Serbia (Grant No. ON171025).
Directory of Open Access Journals (Sweden)
Madhuchhanda Bhattacharjee
Full Text Available Both molecular marker and gene expression data were considered alone as well as jointly to serve as additive predictors for two pathogen-activity-phenotypes in real recombinant inbred lines of soybean. For unobserved phenotype prediction, we used a bayesian hierarchical regression modeling, where the number of possible predictors in the model was controlled by different selection strategies tested. Our initial findings were submitted for DREAM5 (the 5th Dialogue on Reverse Engineering Assessment and Methods challenge and were judged to be the best in sub-challenge B3 wherein both functional genomic and genetic data were used to predict the phenotypes. In this work we further improve upon this previous work by considering various predictor selection strategies and cross-validation was used to measure accuracy of in-data and out-data predictions. The results from various model choices indicate that for this data use of both data types (namely functional genomic and genetic simultaneously improves out-data prediction accuracy. Adequate goodness-of-fit can be easily achieved with more complex models for both phenotypes, since the number of potential predictors is large and the sample size is not small. We also further studied gene-set enrichment (for continuous phenotype in the biological process in question and chromosomal enrichment of the gene set. The methodological contribution of this paper is in exploration of variable selection techniques to alleviate the problem of over-fitting. Different strategies based on the nature of covariates were explored and all methods were implemented under the bayesian hierarchical modeling framework with indicator-based covariate selection. All the models based in careful variable selection procedure were found to produce significant results based on permutation test.
Inhibited, Explosive and Anisotropic Relaxation in a Gas of Molecular Super-Rotors
Khodorkovsky, Yuri; Hartmann, Jean-Michel; Averbukh, Ilya Sh
2015-01-01
Recently, several femtosecond laser techniques have been developed that are capable of bringing gas molecules to extremely fast rotation in a very short time, while keeping their translational motion intact and relatively slow. We investigate collisional equilibration dynamics of this new state of molecular gases, and find that it follows a remarkable generic scenario. The route to equilibrium starts with a durable metastable 'gyroscopic stage', in the course of which the molecules maintain their fast rotation and orientation of the angular momentum through many collisions. The inhibited rotational-translational relaxation is characterized by a persistent anisotropy in the molecular angular distribution, and is manifested in the long-lasting optical birefringence, and anisotropic diffusion in the gas. After a certain induction time, the 'gyroscopic stage' is abruptly terminated by a self-accelerating explosive rotational-translational energy exchange leading the gas towards the final thermal equilibrium. We i...
Indian Academy of Sciences (India)
J Colmenero; A Arbe; F Alvarez; A Narros; D Richter; M Monkenbush; B Farago
2004-07-01
The combination of molecular dynamics simulations and neutron scattering measurements on three different glass-forming polymers (polyisoprene, poly(vinyl ethylene) and polybutadiene) has allowed to establish the existence of a crossover from Gaussian to non-Gaussian behavior for the incoherent scattering function in the -relaxation regime. The deviation from Gaussian behavior observed can be reproduced assuming the existence of a distribution of discrete jump lengths underlying the sublinear diffusion of the atomic motions during the structural relaxation.
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.
Dielectric relaxation spectra of liquid crystals in relation to molecular structure
International Nuclear Information System (INIS)
The dielectric spectra obtained for some members of two homologous series, i.e. for di-alkoxyazoxybenzenes and penthyl-alkoxythiobenzoates, are discussed qualitatively on the basis of the Nordio-Rigatti-Segre diffusion model. It is additionally assumed that the molecular reorientations take place about the principal axes of the inertia tensor. The distribution of correlation times, which is strongly temperature dependent in the vicinity of the clearing point, is interpreted as being caused by fluctuations of the principal axes frame which are due to conformation changes inside the end chains. The Bauer equation is used to describe both principal molecular reorientations, i.e. the reorientations about the long and short axis, observed in liquid crystalline structure by means of dielectric relaxation methods. The energies and entropies of activation have been computed for both principal reorientations. The differences between the high frequency limit of the dielectric permittivity and the refractive index squared of liquid crystals are explained in terms of two librational motions of the molecules observed by other experimental techniques, viz. far infra-red, Raman and inelastic neutron scattering spectroscopies, and found in this work on the basis of dielectrically measured energy barriers. It has been shown qualitatively that intramolecular libratory motions greatly effect the high frequency dielectric spectrum. Finally, molecular motions in liquid crystals are divided into two types: coherent and incoherent. 127 refs., 56 figs., 17 tabs. (author)
Indian Academy of Sciences (India)
A C Ribeiro; P J Sebastiao; C Cruz
2003-08-01
We present in this work a review concerning wide frequency range 1 proton NMR relaxation studies performed in compounds exhibiting columnar mesophases, namely the Colho mesophase in the case of a liquid crystal of discotic molecules and the h mesophase in the case of a liquid crystal of biforked molecules. These NMR relaxation studies were performed combining conventional and fast ﬁeld cycling NMR techniques in a frequency range between 100 Hz and 300 MHz. The possibility of probing such a large frequency range has provided a way to effectively distinguish the inﬂuence, on the 1 relaxation proﬁles, of the different molecular movements observed in this type of mesophases. In addition, we present a comparison between the molecular dynamics in columnar (h) and lamellar (SmC) mesophases exhibited by the same biforked compound.
Bayesian ensemble refinement by replica simulations and reweighting
Hummer, Gerhard; Köfinger, Jürgen
2015-12-01
We describe different Bayesian ensemble refinement methods, examine their interrelation, and discuss their practical application. With ensemble refinement, the properties of dynamic and partially disordered (bio)molecular structures can be characterized by integrating a wide range of experimental data, including measurements of ensemble-averaged observables. We start from a Bayesian formulation in which the posterior is a functional that ranks different configuration space distributions. By maximizing this posterior, we derive an optimal Bayesian ensemble distribution. For discrete configurations, this optimal distribution is identical to that obtained by the maximum entropy "ensemble refinement of SAXS" (EROS) formulation. Bayesian replica ensemble refinement enhances the sampling of relevant configurations by imposing restraints on averages of observables in coupled replica molecular dynamics simulations. We show that the strength of the restraints should scale linearly with the number of replicas to ensure convergence to the optimal Bayesian result in the limit of infinitely many replicas. In the "Bayesian inference of ensembles" method, we combine the replica and EROS approaches to accelerate the convergence. An adaptive algorithm can be used to sample directly from the optimal ensemble, without replicas. We discuss the incorporation of single-molecule measurements and dynamic observables such as relaxation parameters. The theoretical analysis of different Bayesian ensemble refinement approaches provides a basis for practical applications and a starting point for further investigations.
Bayesian ensemble refinement by replica simulations and reweighting.
Hummer, Gerhard; Köfinger, Jürgen
2015-12-28
We describe different Bayesian ensemble refinement methods, examine their interrelation, and discuss their practical application. With ensemble refinement, the properties of dynamic and partially disordered (bio)molecular structures can be characterized by integrating a wide range of experimental data, including measurements of ensemble-averaged observables. We start from a Bayesian formulation in which the posterior is a functional that ranks different configuration space distributions. By maximizing this posterior, we derive an optimal Bayesian ensemble distribution. For discrete configurations, this optimal distribution is identical to that obtained by the maximum entropy "ensemble refinement of SAXS" (EROS) formulation. Bayesian replica ensemble refinement enhances the sampling of relevant configurations by imposing restraints on averages of observables in coupled replica molecular dynamics simulations. We show that the strength of the restraints should scale linearly with the number of replicas to ensure convergence to the optimal Bayesian result in the limit of infinitely many replicas. In the "Bayesian inference of ensembles" method, we combine the replica and EROS approaches to accelerate the convergence. An adaptive algorithm can be used to sample directly from the optimal ensemble, without replicas. We discuss the incorporation of single-molecule measurements and dynamic observables such as relaxation parameters. The theoretical analysis of different Bayesian ensemble refinement approaches provides a basis for practical applications and a starting point for further investigations.
Energy Technology Data Exchange (ETDEWEB)
Xie, Wen Jun; Yang, Yi Isaac; Gao, Yi Qin, E-mail: gaoyq@pku.edu.cn [Institute of Theoretical and Computational Chemistry, College of Chemistry and Molecular Engineering and Biodynamic Optical Imaging Center, Peking University, Beijing 100871 (China)
2015-12-14
In this study, we examine how complex ions such as oxyanions influence the dynamic properties of water and whether differences exist between simple halide anions and oxyanions. Nitrate anion is taken as an example to investigate the hydration properties of oxyanions. Reorientation relaxation of its hydration water can occur through two different routes: water can either break its hydrogen bond with the nitrate to form one with another water or switch between two oxygen atoms of the same nitrate. The latter molecular mechanism increases the residence time of oxyanion’s hydration water and thus nitrate anion slows down the translational motion of neighbouring water. But it is also a “structure breaker” in that it accelerates the reorientation relaxation of hydration water. Such a result illustrates that differences do exist between the hydration of oxyanions and simple halide anions as a result of different molecular geometries. Furthermore, the rotation of the nitrate solute is coupled with the hydrogen bond rearrangement of its hydration water. The nitrate anion can either tilt along the axis perpendicularly to the plane or rotate in the plane. We find that the two reorientation relaxation routes of the hydration water lead to different relaxation dynamics in each of the two above movements of the nitrate solute. The current study suggests that molecular geometry could play an important role in solute hydration and dynamics.
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.
Critical thickness and strain relaxation in molecular beam epitaxy-grown SrTiO3 films
Wang, Tianqi; Ganguly, Koustav; Marshall, Patrick; Xu, Peng; Jalan, Bharat
2013-11-01
We report on the study of the critical thickness and the strain relaxation in epitaxial SrTiO3 film grown on (La0.3Sr0.7)(Al0.65Ta0.35)O3 (001) (LSAT) substrate using the hybrid molecular beam epitaxy approach. No change in the film's lattice parameter (both the in-plane and the out-of-plane) was observed up to a film thickness of 180 nm, which is in sharp contrast to the theoretical critical thickness of ˜12 nm calculated using the equilibrium theory of strain relaxation. For film thicknesses greater than 180 nm, the out-of-plane lattice parameter was found to decrease hyperbolically in an excellent agreement with the relaxation via forming misfit dislocations. Possible mechanisms are discussed by which the elastic strain energy can be accommodated prior to forming misfit dislocations leading to such anomalously large critical thickness.
Nuclear Spin Relaxation and Molecular Interactions of a Novel Triazolium-Based Ionic Liquid
Energy Technology Data Exchange (ETDEWEB)
Allen, Jesse J; Schneider, Yanika; Kail, Brian W; Luebke, David R; Nulwala, Hunaid; Damodaran, Krishnan
2013-04-11
Nuclear spin relaxation, small-angle X-ray scattering (SAXS), and electrospray ionization mass spectrometry (ESI-MS) techniques are used to determine supramolecular arrangement of 3-methyl-1-octyl-4-phenyl-1H-triazol-1,2,3-ium bis(trifluoromethanesulfonyl)imide [OMPhTz][Tf{sub 2}N], an example of a triazolium-based ionic liquid. The results obtained showed first-order thermodynamic dependence for nuclear spin relaxation of the anion. First-order relaxation dependence is interpreted as through-bond dipolar relaxation. Greater than first-order dependence was found in the aliphatic protons, aromatic carbons (including nearest neighbors), and carbons at the end of the aliphatic tail. Greater than first order thermodynamic dependence of spin relaxation rates is interpreted as relaxation resulting from at least one mechanism additional to through-bond dipolar relaxation. In rigid portions of the cation, an additional spin relaxation mechanism is attributed to anisotropic effects, while greater than first order thermodynamic dependence of the octyl side chain’s spin relaxation rates is attributed to cation–cation interactions. Little interaction between the anion and the cation was observed by spin relaxation studies or by ESI-MS. No extended supramolecular structure was observed in this study, which was further supported by MS and SAXS. nuclear Overhauser enhancement (NOE) factors are used in conjunction with spin–lattice relaxation time (T{sub 1}) measurements to calculate rotational correlation times for C–H bonds (the time it takes for the vector represented by the bond between the two atoms to rotate by one radian). The rotational correlation times are used to represent segmental reorientation dynamics of the cation. A combination of techniques is used to determine the segmental interactions and dynamics of this example of a triazolium-based ionic liquid.
Institute of Scientific and Technical Information of China (English)
Hou Quan-Wen; Cao Bing-Yang
2012-01-01
The phonon relaxation and heat conduction in one-dimensional Fermi-Pasta-Ulam (FPU) β lattices are studied by using molecular dynamics simulations.The phonon relaxation rate,which dominates the length dependence of the FPU β lattice,is first calculated from the energy autocorrelation function for different modes at various temperatures through equilibrium molecular dynamics simulations.We find that the relaxation rate as a function of wave number k is proportional to k1.688,which leads to a N0.41 divergence of the thermal conductivity in the framework of Green-Kubo relation.This is also in good agreement with the data obtained by non-equilibrium molecular dynamics simulations which estimate the length dependence exponent of the thermal conductivity as 0.415.Our results confirm the N2/5divergence in one-dimensional FPU β lattices.The effects of the heat flux on the thermal conductivity are also studied by imposing different temperature differences on the two ends of the lattices.We find that the thermal conductivity is insensitive to the heat flux under our simulation conditions.It implies that the linear response theory is applicable towards the heat conduction in one-dimensional FPUβ lattices.
Energy Technology Data Exchange (ETDEWEB)
Liu, Qing; Shi, Chaowei [Hefei National Laboratory for Physical Sciences at The Microscale and School of Life Sciences, University of Science and Technology of China, Hefei, Anhui, 230026 (China); Yu, Lu [Hefei National Laboratory for Physical Sciences at The Microscale and School of Life Sciences, University of Science and Technology of China, Hefei, Anhui, 230026 (China); High Magnetic Field Laboratory, Chinese Academy of Science, Hefei, Anhui, 230031 (China); Zhang, Longhua [Hefei National Laboratory for Physical Sciences at The Microscale and School of Life Sciences, University of Science and Technology of China, Hefei, Anhui, 230026 (China); Xiong, Ying, E-mail: yxiong73@ustc.edu.cn [Hefei National Laboratory for Physical Sciences at The Microscale and School of Life Sciences, University of Science and Technology of China, Hefei, Anhui, 230026 (China); Tian, Changlin, E-mail: cltian@ustc.edu.cn [Hefei National Laboratory for Physical Sciences at The Microscale and School of Life Sciences, University of Science and Technology of China, Hefei, Anhui, 230026 (China); High Magnetic Field Laboratory, Chinese Academy of Science, Hefei, Anhui, 230031 (China)
2015-02-13
Internal backbone dynamic motions are essential for different protein functions and occur on a wide range of time scales, from femtoseconds to seconds. Molecular dynamic (MD) simulations and nuclear magnetic resonance (NMR) spin relaxation measurements are valuable tools to gain access to fast (nanosecond) internal motions. However, there exist few reports on correlation analysis between MD and NMR relaxation data. Here, backbone relaxation measurements of {sup 15}N-labeled SH3 (Src homology 3) domain proteins in aqueous buffer were used to generate general order parameters (S{sup 2}) using a model-free approach. Simultaneously, 80 ns MD simulations of SH3 domain proteins in a defined hydrated box at neutral pH were conducted and the general order parameters (S{sup 2}) were derived from the MD trajectory. Correlation analysis using the Gromos force field indicated that S{sup 2} values from NMR relaxation measurements and MD simulations were significantly different. MD simulations were performed on models with different charge states for three histidine residues, and with different water models, which were SPC (simple point charge) water model and SPC/E (extended simple point charge) water model. S{sup 2} parameters from MD simulations with charges for all three histidines and with the SPC/E water model correlated well with S{sup 2} calculated from the experimental NMR relaxation measurements, in a site-specific manner. - Highlights: • Correlation analysis between NMR relaxation measurements and MD simulations. • General order parameter (S{sup 2}) as common reference between the two methods. • Different protein dynamics with different Histidine charge states in neutral pH. • Different protein dynamics with different water models.
Influence of hydroxypropyl cellulose on molecular relaxations of epoxy-amine networks
Maria Inez G. Miranda; Dimitrios Samios; Liane de L. Freitas; Clara I. D. Bica
2013-01-01
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, refe...
Inhomogeneous relaxation of a molecular layer on an insulator due to compressive stress
Bocquet, Franck; Nony, Laurent; Mannsfeld, Stefan; Oison, Vincent; Pawlak, Rémy; Porte, Louis; Loppacher, Christian
2012-01-01
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, of density functional theory and potential energy calcula...
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.
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. PMID:24186540
Molecular structure-property correlations from optical nonlinearity and thermal-relaxation dynamics.
Bhattacharyya, Indrajit; Priyadarshi, Shekhar; Goswami, Debabrata
2009-02-01
We apply ultrafast single beam Z-scan technique to measure saturation absorption coefficients and nonlinear-refraction coefficients of primary alcohols at 1560 nm. The nonlinear effects result from vibronic transitions and cubic nonlinear-refraction. To measure the pure total third-order nonlinear susceptibility, we removed thermal effects with a frequency optimized optical-chopper. Our measurements of thermal-relaxation dynamics of alcohols, from 1560 nm thermal lens pump and 780 nm probe experiments revealed faster and slower thermal-relaxation timescales, respectively, from conduction and convection. The faster timescale accurately predicts thermal-diffusivity, which decreases linearly with alcohol chain-lengths since thermal-relaxation is slower in heavier molecules. The relation between thermal-diffusivity and alcohol chain-length confirms structure-property relationship.
Rotational relaxation in molecular hydrogen and deuterium: Theory versus acoustic experiments
Energy Technology Data Exchange (ETDEWEB)
Montero, S., E-mail: emsalvador@iem.cfmac.csic.es [Laboratory of Molecular Fluid Dynamics @ Instituto de Estructura de la Materia, CSIC, Serrano 121, 28006 Madrid (Spain); Pérez-Ríos, J. [Physics Department, Purdue University, West Lafayette, Indiana 47907 (United States)
2014-09-21
An explicit formulation of the rotational relaxation time in terms of state-to-state rate coefficients associated to inelastic collisions is reported. The state-to-state rates needed for the detailed interpretation of relaxation in H{sub 2} and D{sub 2}, including isotopic variant mixtures, have been calculated by solving the close-coupling Schrödinger equations using the H{sub 2}–H{sub 2} potential energy surface by Diep and Johnson [J. Chem. Phys. 112, 4465 (2000)]. Relaxation related quantities (rotational effective cross section, bulk viscosity, relaxation time, and collision number) calculated from first principles agree reasonably well with acoustic absorption experimental data on H{sub 2} and D{sub 2} between 30 and 293 K. This result confirms at once the proposed formulation, and the validation of the H{sub 2}–H{sub 2} potential energy surface employed, since no approximations have been introduced in the dynamics. Accordingly, the state-to-state rates derived from Diep and Johnson potential energy surface appear to be overestimated by up to 10% for H{sub 2}, and up to 30% for D{sub 2} at T = 300 K, showing a better agreement at lower temperatures.
Gill, Michelle L.; Palmer, Arthur G.
2014-01-01
The present work demonstrates that NMR spin relaxation rate constants for molecules interconverting between states with different diffusion tensors can be modeled theoretically by combining orientational correlation functions for exchanging spherical molecules with locally isotropic approximations for the diffusion anisotropic tensors. The resulting expressions are validated by comparison with correlation functions obtained by Monte Carlo simulations and are accurate for moderate degrees of d...
Rotational relaxation in molecular hydrogen and deuterium: Theory versus acoustic experiments
International Nuclear Information System (INIS)
An explicit formulation of the rotational relaxation time in terms of state-to-state rate coefficients associated to inelastic collisions is reported. The state-to-state rates needed for the detailed interpretation of relaxation in H2 and D2, including isotopic variant mixtures, have been calculated by solving the close-coupling Schrödinger equations using the H2–H2 potential energy surface by Diep and Johnson [J. Chem. Phys. 112, 4465 (2000)]. Relaxation related quantities (rotational effective cross section, bulk viscosity, relaxation time, and collision number) calculated from first principles agree reasonably well with acoustic absorption experimental data on H2 and D2 between 30 and 293 K. This result confirms at once the proposed formulation, and the validation of the H2–H2 potential energy surface employed, since no approximations have been introduced in the dynamics. Accordingly, the state-to-state rates derived from Diep and Johnson potential energy surface appear to be overestimated by up to 10% for H2, and up to 30% for D2 at T = 300 K, showing a better agreement at lower temperatures
Faux, David A.; McDonald, Peter J.
2016-01-01
A model linking the molecular-scale dynamics of fluids confined to nano-pores to nuclear magnetic resonance (NMR) relaxation rates is proposed. The model is fit to experimental NMR dispersions for water and oil in an oil shale assuming that each fluid is characterised by three time constants and L\\'{e}vy statistics. Results yield meaningful and consistent intra-pore dynamical time constants, insight into diffusion mechanisms and pore morphology. The model is applicable to a wide range of poro...
Critical thickness and strain relaxation in molecular beam epitaxy-grown SrTiO{sub 3} films
Energy Technology Data Exchange (ETDEWEB)
Wang, Tianqi; Ganguly, Koustav; Marshall, Patrick; Xu, Peng; Jalan, Bharat [Department of Chemical Engineering and Materials Science, University of Minnesota, Minneapolis, Minnesota 55455 (United States)
2013-11-18
We report on the study of the critical thickness and the strain relaxation in epitaxial SrTiO{sub 3} film grown on (La{sub 0.3}Sr{sub 0.7})(Al{sub 0.65}Ta{sub 0.35})O{sub 3} (001) (LSAT) substrate using the hybrid molecular beam epitaxy approach. No change in the film's lattice parameter (both the in-plane and the out-of-plane) was observed up to a film thickness of 180 nm, which is in sharp contrast to the theoretical critical thickness of ∼12 nm calculated using the equilibrium theory of strain relaxation. For film thicknesses greater than 180 nm, the out-of-plane lattice parameter was found to decrease hyperbolically in an excellent agreement with the relaxation via forming misfit dislocations. Possible mechanisms are discussed by which the elastic strain energy can be accommodated prior to forming misfit dislocations leading to such anomalously large critical thickness.
Nonlinear relaxation dynamics in elastic networks and design principles of molecular machines
Togashi, Y.; A. Mikhailov
2007-01-01
Analyzing nonlinear conformational relaxation dynamics in elastic networks corresponding to two classical motor proteins, we find that they respond by well defined internal mechanical motions to various initial deformations and that these motions are robust against external perturbations. We show that this behavior is not characteristic for random elastic networks. However, special network architectures with such properties can be designed by evolutionary optimization methods. Using them, an ...
MIDAS: a practical Bayesian design for platform trials with molecularly targeted agents.
Yuan, Ying; Guo, Beibei; Munsell, Mark; Lu, Karen; Jazaeri, Amir
2016-09-30
Recent success of immunotherapy and other targeted therapies in cancer treatment has led to an unprecedented surge in the number of novel therapeutic agents that need to be evaluated in clinical trials. Traditional phase II clinical trial designs were developed for evaluating one candidate treatment at a time and thus not efficient for this task. We propose a Bayesian phase II platform design, the multi-candidate iterative design with adaptive selection (MIDAS), which allows investigators to continuously screen a large number of candidate agents in an efficient and seamless fashion. MIDAS consists of one control arm, which contains a standard therapy as the control, and several experimental arms, which contain the experimental agents. Patients are adaptively randomized to the control and experimental agents based on their estimated efficacy. During the trial, we adaptively drop inefficacious or overly toxic agents and 'graduate' the promising agents from the trial to the next stage of development. Whenever an experimental agent graduates or is dropped, the corresponding arm opens immediately for testing the next available new agent. Simulation studies show that MIDAS substantially outperforms the conventional approach. The proposed design yields a significantly higher probability for identifying the promising agents and dropping the futile agents. In addition, MIDAS requires only one master protocol, which streamlines trial conduct and substantially decreases the overhead burden. Copyright © 2016 John Wiley & Sons, Ltd. PMID:27112322
Gill, Michelle L; Palmer, Arthur G
2014-09-25
The present work demonstrates that NMR spin relaxation rate constants for molecules interconverting between states with different diffusion tensors can be modeled theoretically by combining orientational correlation functions for exchanging spherical molecules with locally isotropic approximations for the diffusion anisotropic tensors. The resulting expressions are validated by comparison with correlation functions obtained by Monte Carlo simulations and are accurate for moderate degrees of diffusion anisotropy typically encountered in investigations of globular proteins. The results are complementary to an elegant, but more complex, formalism that is accurate for all degrees of diffusion anisotropy [Ryabov, Y.; Clore, G. M.; Schwieters, C. D. J. Chem. Phys. 2012, 136, 034108]. PMID:25167331
Molecular structure-property correlations from optical nonlinearity and thermal-relaxation dynamics
Bhattacharyya, Indrajit; Priyadarshi, Shekhar; Goswami, Debabrata
2009-01-01
We apply ultrafast single beam Z-scan technique to measure saturation absorption coefficients and nonlinear-refraction coefficients of primary alcohols at 1560 nm. The nonlinear effects result from vibronic transitions and cubic nonlinear-refraction. To measure the pure total third-order nonlinear susceptibility, we removed thermal effects with a frequency optimized optical-chopper. Our measurements of thermal-relaxation dynamics of alcohols, from 1560 nm thermal lens pump and 780 nm probe ex...
Smith, Grant D.; Bedrov, Dmitry; Paul, Wolfgang
2004-09-01
The dynamic coherent structure factor Scoh(q,t) for a 1,4-polybutadiene (PBD) melt has been investigated using atomistic molecular dynamics simulations. The relaxation of Scoh(q,t) at q=1.44 Å-1 and q=2.72 Å-1, corresponding to the first and second peaks in the static structure factor for PBD, was studied in detail over a wide range of temperature. It was found that time-temperature superposition holds for the α-relaxation for both q values over a wide temperature range and that the α-relaxation can be well described by a stretched (Kohlrauch-William-Watts) exponential with temperature independent but q dependent amplitude and stretching exponent. The α-relaxation times for both q values were found to exhibit the same non-Arrhenius temperature dependence, indicating that the same physical processes are responsible for relaxation on both length scales. The α-relaxation time was found to depend strongly upon the dynamical range of data utilized in determining the relaxation time, accounting for qualitative discrepancies between α-relaxation times reported here and those extracted for PBD from experimentally measured Scoh(q,t).
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.
Low-relaxation spin waves in laser-molecular-beam epitaxy grown nanosized yttrium iron garnet films
Lutsev, L. V.; Korovin, A. M.; Bursian, V. E.; Gastev, S. V.; Fedorov, V. V.; Suturin, S. M.; Sokolov, N. S.
2016-05-01
Synthesis of nanosized yttrium iron garnet (Y3Fe5O12, YIG) films followed by the study of ferromagnetic resonance (FMR) and spin wave propagation in these films is reported. The YIG films were grown on gadolinium gallium garnet substrates by laser molecular beam epitaxy. It has been shown that spin waves propagating in YIG deposited at 700 °C have low damping. At the frequency of 3.29 GHz, the spin-wave damping parameter is less than 3.6 × 10-5. Magnetic inhomogeneities of the YIG films give the main contribution to the FMR linewidth. The contribution of the relaxation processes to the FMR linewidth is as low as 1.2%.
Accelerating molecular simulations of proteins using Bayesian inference on weak information
Perez, Alberto; MacCallum, Justin L.; Dill, Ken A.
2015-01-01
Atomistic molecular dynamics (MD) simulations of protein molecules are too computationally expensive to predict most native structures from amino acid sequences. Here, we integrate “weak” external knowledge into folding simulations to predict protein structures, given their sequence. For example, we instruct the computer “to form a hydrophobic core,” “to form good secondary structures,” or “to seek a compact state.” This kind of information has been too combinatoric, nonspecific, and vague to help guide MD simulations before. Within atomistic replica-exchange molecular dynamics (REMD), we develop a statistical mechanical framework, modeling using limited data with coarse physical insight(s) (MELD + CPI), for harnessing weak information. As a test, we apply MELD + CPI to predict the native structures of 20 small proteins. MELD + CPI samples to within less than 3.2 Å from native for all 20 and correctly chooses the native structures (<4 Å) for 15 of them, including ubiquitin, a millisecond folder. MELD + CPI is up to five orders of magnitude faster than brute-force MD, satisfies detailed balance, and should scale well to larger proteins. MELD + CPI may be useful where physics-based simulations are needed to study protein mechanisms and populations and where we have some heuristic or coarse physical knowledge about states of interest. PMID:26351667
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...
Directory of Open Access Journals (Sweden)
Debashis Mukherjee
2002-06-01
Full Text Available Abstract: We present in this paper two new versions of Rayleigh-SchrÃ‚Â¨odinger (RS and the Brillouin-Wigner (BW state-specific multi-reference perturbative theories (SSMRPT which stem from our state-specific multi-reference coupled-cluster formalism (SS-MRCC, developed with a complete active space (CAS. They are manifestly sizeextensive and are designed to avoid intruders. The combining coefficients cÃŽÂ¼ for the model functions ÃÂ†ÃŽÂ¼ are completely relaxed and are obtained by diagonalizing an effective operator in the model space, one root of which is the target eigenvalue of interest. By invoking suitable partitioning of the hamiltonian, very convenient perturbative versions of the formalism in both the RS and the BW forms are developed for the second order energy. The unperturbed hamiltonians for these theories can be chosen to be of both MÃÂ†ller-Plesset (MP and Epstein-Nesbet (EN type. However, we choose the corresponding Fock operator fÃŽÂ¼ for each model function ÃÂ†ÃŽÂ¼, whose diagonal elements are used to define the unperturbed hamiltonian in the MP partition. In the EN partition, we additionally include all the diagonal direct and exchange ladders. Our SS-MRPT thus utilizes a multi-partitioning strategy. Illustrative numerical applications are presented for potential energy surfaces (PES of the ground (1ÃŽÂ£+ and the first delta (1ÃŽÂ” states of CH+ which possess pronounced multi-reference character. Comparison of the results with the corresponding full CI values indicates the efficacy of our formalisms.
Trerayapiwat, Kasidet; Ricke, Nathan; Cohen, Peter; Poblete, Alex; Rudel, Holly; Eustis, Soren N
2016-08-10
This work explores the relationship between theoretically predicted excitation energies and experimental molar absorption spectra as they pertain to environmental aquatic photochemistry. An overview of pertinent Quantum Chemical descriptions of sunlight-driven electronic transitions in organic pollutants is presented. Second, a combined molecular dynamics (MD), time-dependent density functional theory (TD-DFT) analysis of the ultraviolet to visible (UV-Vis) absorption spectra of six model organic compounds is presented alongside accurate experimental data. The functional relationship between the experimentally observed molar absorption spectrum and the discrete quantum transitions is examined. A rigorous comparison of the accuracy of the theoretical transition energies (ΔES0→Sn) and oscillator strength (fS0→Sn) is afforded by the probabilistic convolution and deconvolution procedure described. This method of deconvolution of experimental spectra using a Gaussian Mixture Model combined with Bayesian Information Criteria (BIC) to determine the mean (μ) and standard deviation (σ) as well as the number of observed singlet to singlet transition energy state distributions. This procedure allows a direct comparison of the one-electron (quantum) transitions that are the result of quantum chemical calculations and the ensemble of non-adiabatic quantum states that produce the macroscopic effect of a molar absorption spectrum. Poor agreement between the vertical excitation energies produced from TD-DFT calculations with five different functionals (CAM-B3LYP, PBE0, M06-2X, BP86, and LC-BLYP) suggest a failure of the theory to capture the low energy, environmentally important, electronic transitions in our model organic pollutants. However, the method of explicit-solvation of the organic solute using the quantum Effective Fragment Potential (EFP) in a density functional molecular dynamics trajectory simulation shows promise as a robust model of the hydrated organic
Progress in the study of molecular organized assemblies by dielectric relaxation spectroscopy
Institute of Scientific and Technical Information of China (English)
无
2006-01-01
Because dielectric spectroscopy covers a great many problems in physical and chemical systems occurring in an extremely wide frequency range, the study of this method plays an important role in physical chemistry. As an effective tool to detect inner properties of substance systems, the dielectric spectroscopy method is widely used in chemical systems and has been dramatically developed in recent decade. This review paper describes the applications of the dielectric spectroscopy in the chemical field, and main concentrations are focused on the micelle, microemulsion and other so-called molecular organized assemblies. Some dielectric principles and models proposed for these systems are introduced. In addition, recent technical developments in dielectric spectroscopy and developing trend of this method in other chemical systems are reviewed.
Relaxing the Molecular Clock to Different Degrees for Different Substitution Types.
Lee, Hui-Jie; Rodrigue, Nicolas; Thorne, Jeffrey L
2015-08-01
Rates of molecular evolution can vary over time. Diverse statistical techniques for divergence time estimation have been developed to accommodate this variation. These typically require that all sequence (or codon) positions at a locus change independently of one another. They also generally assume that the rates of different types of nucleotide substitutions vary across a phylogeny in the same way. This permits divergence time estimation procedures to employ an instantaneous rate matrix with relative rates that do not differ among branches. However, previous studies have suggested that some substitution types (e.g., CpG to TpG changes in mammals) are more clock-like than others. As has been previously noted, this is biologically plausible given the mutational mechanism of CpG to TpG changes. Through stochastic mapping of sequence histories from context-independent substitution models, our approach allows for context-dependent nucleotide substitutions to change their relative rates over time. We apply our approach to the analysis of a 0.15 Mb intergenic region from eight primates. In accord with previous findings, we find comparatively little rate variation over time for CpG to TpG substitutions but we find more for other substitution types. We conclude by discussing the limitations and prospects of our approach.
International Nuclear Information System (INIS)
Total cross sections for the positive and negative fragments resulting from dissociative collisions with He of vibrationally relaxed H3+, D3+, and HD2+ molecular ions have been measured in the energy range 3-9.8 keV. The measured absolute total-cross-section values are more than one order of magnitude smaller than those previously reported with the molecular ions without vibrational relaxation. When the cross sections are plotted as a function of the projectile speed and normalized to compensate for the relative fragment yield, the values for the production of deuterium fragments are higher than those for hydrogen ions in the energy range of the present study. These results are consistent with the theoretical predictions for the behavior of triatomic molecular ions with high rovibrational excitation
Inferring Genotype of DNA Molecular Marker by Bayesian Theorem%应用贝叶斯理论推断DNA分子标记基因型
Institute of Scientific and Technical Information of China (English)
莫惠栋; 姜长鉴
2002-01-01
引入贝叶斯理论用以从DNA分子标记的表现型(电泳谱带)推断其基因型(DNA来源).结果表明,根据标记座位独立假定而确定的遗传信息不完全标记的基因型概率,与根据邻近的遗传信息完全标记的基因型和有关重组率算得的相应贝叶斯概率,通常都有很大的差异.所以在进行数量性状基因定位和标记辅助选择等工作之前,应当计算每一个体基因组上所有遗传信息不完全座位的有关基因型的贝叶斯概率.文中列出计算未知基因型的贝叶斯概率的详细过程,也讨论了贝叶斯概率的若干推广应用.%Bayesian theorem is applied to infer the DNA molecular marker genotype(DNA chain type) from its phenotype (electrophoresis band type). The results indicated that large differences often present in the genotype probability of a molecular marker with incomplete genetic information when it is obtained from the assumption of independence among markers as compared with that inferred from the genotypes of the flanking markers with the complete genetic information and the recombination fractions among them based on the Bayesian theorem. Therefore, before utilizing the marker information, such as in mapping quantitative trait loci (QTL), marker assisted selection (MAS) etc., Bayesian probability of the genotype for all markers with incomplete genetic information must be calculated over the whole genome for every individual. This study provides detailed procedure for the calculation of the Bayesian probability of the unknown genotype. Several extensions were also discussed for the application of the Bayesian theorem.
Dutt, G. B.; Sachdeva, A.
2003-05-01
Rotational relaxation of three organic solutes, coumarin 6 (C6), 2,5-dimethyl-1, 4-dioxo3,6-diphenylpyrrolo[3,4-c]pyrrole (DMDPP), and nile red (NR), that are similar in size but distinct in shape has been studied in a nonpolar solvent, squalane as a function of temperature to find out how the mechanical friction experienced by the solute molecule is influenced by its shape. It has been observed that C6 rotates slowest followed by NR and DMDPP. The results are analyzed using Stokes-Einstein-Debye (SED) hydrodynamic theory and also quasihydrodynamic theories of Gierer and Wirtz, and Dote, Kivelson, and Schwartz. Analysis of the data using the SED theory reveals that the measured reorientation times of C6 and DMDPP follow subslip behavior whereas those of NR are found to match slip predictions. While no single model could mimic the observed trend even in a qualitative manner, the reorientation times of C6 and DMDPP when normalized by their respective shape factors and boundary-condition parameters can be scaled on a common curve over the entire range of temperature studied. The probable reasons for the distinctive rotational behavior of NR as compared to C6 and DMDPP are explained in terms of its molecular shape and how this in turn influences the boundary-condition parameter are discussed.
Allen, Jesse J; Bowser, Sage R; Damodaran, Krishnan
2014-05-01
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. PMID:24654003
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.
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.
Relaxation phenomena in disordered systems
Sciortino, F.; Tartaglia, P.
1997-02-01
In this article we discuss how the assumptions of self-similarity imposed on the distribution of independently relaxing modes, as well as on their amplitude and characteristic times, manifest in the global relaxation phenomena. We also review recent applications of such approach to the description of relaxation phenomena in microemulsions and molecular glasses.
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
Draper, D.
2001-01-01
© 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
Institute of Scientific and Technical Information of China (English)
Druzhinina I S; Kubicek C P
2004-01-01
@@ The Hypocrea lixii/Trichoderma harzianum species aggregate contains a group of taxa (H. lixii/T.harzianum , T. aggressivum , T. tomentosum , T. cerinum , T. velutinum , H. tawa ) of which some (e. g. T. harzianum) are important for biocontrol of plant pathogenic fungi in agriculture, whereas others are aggressive pathogens of Agaricus spp. and Pleurotus spp. in mushroom farms (T. aggressivum), or opportunistic pathogens of immunocompromised mammals including humans (T. harzianum). We characterized the evolutionary properties of three genomic regions in Hypocrea/Trichoderma: the internal transcribed spacer regions ITS1 and 2 of rDNA, the large intron of translation elongation factor 1-alpha (tef1a), and a portion of the large exon of the endochitinase 42 gene (ech42 ), selected the best model which describes the evolution of every fragment, tested the molecular clock hypothesis and made an estimation of the usability of the combined three fragments data matrix for the phylogenetic analysis of the genus as a whole as well as on the level of the holomorphic H. liaxii/T. harzianum species clade and separate clonal lineages. To this end, we applied Bayesian phylogenetic inferences to 124 sequences of ITS1 and 2 and of the large tef1a intron, and to 64 ech42 gene sequences to resolve the evolution of H. lixii/T. harzianum with respect to the position of other taxa with closely related phenotypes. The resulting phylogram clearly identified T.aggressivum, T. velutinum, H. tawa, T. cerinum and T. tomentosum as phylogenetic species, and in addition identified three new unknown phylogenetic species as members of this clacle. The clear distinction between T. tomentosum and T. cerinum was not recognized in all trees, but was supported by multivariate analysis of phenotype micro arrays. In contrast, H. lixii/T. harzianum did not form a single phylogenetic species in this study, as its monophyly was not supported in any analysis. Strains morphologically identified as H. lixii
Strain relaxation in GaN/AlxGa1-xN superlattices grown by plasma-assisted molecular-beam epitaxy
International Nuclear Information System (INIS)
We have investigated the misfit relaxation process in GaN/AlxGa1-xN (x = 0.1, 0.3, 0.44) superlattices (SL) deposited by plasma-assisted molecular beam epitaxy. The SLs under consideration were designed to achieve intersubband absorption in the mid-infrared spectral range. We have considered the case of growth on GaN (tensile stress) and on AlGaN (compressive stress) buffer layers, both deposited on GaN-on-sapphire templates. Using GaN buffer layers, the SL remains almost pseudomorphic for x = 0.1, 0.3, with edge-type threading dislocation densities below 9 x 108 cm-2 to 2 x 109 cm-2. Increasing the Al mole fraction to 0.44, we observe an enhancement of misfit relaxation resulting in dislocation densities above 1010 cm-2. In the case of growth on AlGaN, strain relaxation is systematically stronger, with the corresponding increase in the dislocation density. In addition to the average relaxation trend of the SL, in situ measurements indicate a periodic fluctuation of the in-plane lattice parameter, which is explained by the different elastic response of the GaN and AlGaN surfaces to the Ga excess at the growth front. The results are compared with GaN/AlN SLs designed for near-infrared intersubband absorption.
Energy Technology Data Exchange (ETDEWEB)
Yurasov, D. V., E-mail: Inquisitor@ipm.sci-nnov.ru [Russian Academy of Sciences, Institute for Physics of Microstructures (Russian Federation); Bobrov, A. I. [Lobachevsky State University of Nizhny Novgorod (Russian Federation); Daniltsev, V. M.; Novikov, A. V. [Russian Academy of Sciences, Institute for Physics of Microstructures (Russian Federation); Pavlov, D. A. [Lobachevsky State University of Nizhny Novgorod (Russian Federation); Skorokhodov, E. V.; Shaleev, M. V.; Yunin, P. A. [Russian Academy of Sciences, Institute for Physics of Microstructures (Russian Federation)
2015-11-15
Influence of the Ge layer thickness and annealing conditions on the parameters of relaxed Ge/Si(001) layers grown by molecular beam epitaxy via two-stage growth is investigated. The dependences of the threading dislocation density and surface roughness on the Ge layer thickness, annealing temperature and time, and the presence of a hydrogen atmosphere are obtained. As a result of optimization of the growth and annealing conditions, relaxed Ge/Si(001) layers which are thinner than 1 μm with a low threading dislocation density on the order of 10{sup 7} cm{sup –2} and a root mean square roughness of less than 1 nm are obtained.
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.
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
Non-homogeneous dynamic Bayesian networks for continuous data
Grzegorczyk, Marco; Husmeier, Dirk
2011-01-01
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 c
Beckmann, Peter A.; Rheingold, Arnold L.
2016-04-01
The dynamics of methyl (CH3) and fluoromethyl (CF3) groups in organic molecular (van der Waals) solids can be exploited to survey their local environments. We report solid state 1H and 19F spin-lattice relaxation experiments in polycrystalline 3-trifluoromethoxycinnamic acid, along with an X-ray diffraction determination of the molecular and crystal structure, to investigate the intramolecular and intermolecular interactions that determine the properties that characterize the CF3 reorientation. The molecule is of no particular interest; it simply provides a motionless backbone (on the nuclear magnetic resonance (NMR) time scale) to investigate CF3 reorientation occurring on the NMR time scale. The effects of 19F-19F and 19F-1H spin-spin dipolar interactions on the complicated nonexponential NMR relaxation provide independent inputs into determining a model for CF3 reorientation. As such, these experiments provide much more information than when only one spin species (usually 1H) is present. In Sec. IV, which can be read immediately after the Introduction without reading the rest of the paper, we compare the barrier to CH3 and CF3 reorientation in seven organic solids and separate this barrier into intramolecular and intermolecular components.
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.
Simkovitch, R.; Akulov, K.; Erez, Y.; Amdursky, N.; Gepshtein, R.; Schwartz, T.; Huppert, D.
2015-09-01
Steady-state and time-resolved UV-Vis spectroscopy techniques were employed to study the non-radiative process of Auramine-O (AuO). We focused our attention on the ultrafast nonradiative decay of Auramine-O in water and on the acid effect on Auramine-O spectroscopy. We found that weak acids like formic acid shorten the excited-state decay times of both the emission and the transient pump-probe spectra of Auramine-O. We found three time domains in the relaxation of the excited states back to the ground state. In mixtures of acetic and formic acids, the three decay times associated with the relaxation process are shorter in the presence of formic acid in Auramine-O solutions. We qualitatively explain the very large non-radiative rate in water and in formic-acetic acid mixtures by a protic nonradiative model proposed by Sobolewski and Domcke. The steady-state emission spectrum of AuO adsorbed on insulin fibrils consists of two bands assigned to protonated and deprotonated forms and the emission intensity increases by three orders of magnitude. We conclude that the nonradiative process prevails in the liquid state, whereas when AuO is adsorbed on fibrils the nonradiative rate is reduced by three orders of magnitude and thus enables a slow ESPT process to occur.
Coffey, W. T.; Déjardin, P. M.; Walsh, M. E.
1999-03-01
Exact solutions obtained by Gross [J. Chem. Phys. 23, 1415 (1955)] and Sack [Proc. Phys. Soc. London, Sect. B 70, 402 (1957)] for the complex polarizability of assemblies of nonelectrically interacting rotators subjected to a variety of collisions and various approximations to that quantity, specifically the Rocard equation are reappraised in view of recent attempts to use a variety of forms of that equation for the interpretation of far infrared resonance absorption spectra. It is shown that for small values of the inertial parameter (heavy damping) the Rocard equation yields a really good approximation for the complex polarizability only for the small collision model considered by Gross and Sack. In the case of large inertial parameter values it is emphasized by means of plots of the complex polarizability that such an approximation always exhibits behavior characteristic of a sharply resonant system, i.e., a pronounced absorption peak well in excess of the Debye peak and a strongly negative real part, while the exact complex polarizability spectrum for the same parameter values merely displays inertia corrected Debye relaxation. Therefore, an explanation of the resonant term other than that based on a Rocard equation with a large inertial parameter must be sought as that equation strictly applies to inertia corrected Debye (heavily damped) relaxation only. The application of the itinerant oscillator model and the three variable Mori theory to the problem is discussed in view of this conclusion.
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. Mo
Relaxed Poisson cure rate models.
Rodrigues, Josemar; Cordeiro, Gauss M; Cancho, Vicente G; Balakrishnan, N
2016-03-01
The purpose of this article is to make the standard promotion cure rate model (Yakovlev and Tsodikov, ) more flexible by assuming that the number of lesions or altered cells after a treatment follows a fractional Poisson distribution (Laskin, ). It is proved that the well-known Mittag-Leffler relaxation function (Berberan-Santos, ) is a simple way to obtain a new cure rate model that is a compromise between the promotion and geometric cure rate models allowing for superdispersion. So, the relaxed cure rate model developed here can be considered as a natural and less restrictive extension of the popular Poisson cure rate model at the cost of an additional parameter, but a competitor to negative-binomial cure rate models (Rodrigues et al., ). Some mathematical properties of a proper relaxed Poisson density are explored. A simulation study and an illustration of the proposed cure rate model from the Bayesian point of view are finally presented. PMID:26686485
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
Energy Technology Data Exchange (ETDEWEB)
Das, Anuradha; Das, Suman; Biswas, Ranjit, E-mail: ranjit@bose.res.in [Chemical, Biological and Macromolecular Sciences, S. N. Bose National Centre for Basic Sciences, Block-JD, Sector-III, Salt Lake, Kolkata, West Bengal 700098 (India)
2015-01-21
Temperature dependent relaxation dynamics, particle motion characteristics, and heterogeneity aspects of deep eutectic solvents (DESs) made of acetamide (CH{sub 3}CONH{sub 2}) and urea (NH{sub 2}CONH{sub 2}) have been investigated by employing time-resolved fluorescence measurements and all-atom molecular dynamics simulations. Three different compositions (f) for the mixture [fCH{sub 3}CONH{sub 2} + (1 − f)NH{sub 2}CONH{sub 2}] have been studied in a temperature range of 328-353 K which is ∼120-145 K above the measured glass transition temperatures (∼207 K) of these DESs but much lower than the individual melting temperature of either of the constituents. Steady state fluorescence emission measurements using probe solutes with sharply different lifetimes do not indicate any dependence on excitation wavelength in these metastable molten systems. Time-resolved fluorescence anisotropy measurements reveal near-hydrodynamic coupling between medium viscosity and rotation of a dissolved dipolar solute. Stokes shift dynamics have been found to be too fast to be detected by the time-resolution (∼70 ps) employed, suggesting extremely rapid medium polarization relaxation. All-atom simulations reveal Gaussian distribution for particle displacements and van Hove correlations, and significant overlap between non-Gaussian (α{sub 2}) and new non-Gaussian (γ) heterogeneity parameters. In addition, no stretched exponential relaxations have been detected in the simulated wavenumber dependent acetamide dynamic structure factors. All these results are in sharp contrast to earlier observations for ionic deep eutectics with acetamide [Guchhait et al., J. Chem. Phys. 140, 104514 (2014)] and suggest a fundamental difference in interaction and dynamics between ionic and non-ionic deep eutectic solvent systems.
International Nuclear Information System (INIS)
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.
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.
Fleischmann, C.; Lieten, R. R.; Hermann, P.; Hönicke, P.; Beckhoff, B.; Seidel, F.; Richard, O.; Bender, H.; Shimura, Y.; Zaima, S.; Uchida, N.; Temst, K.; Vandervorst, W.; Vantomme, A.
2016-08-01
Strained Ge1-xSnx thin films have recently attracted a lot of attention as promising high mobility or light emitting materials for future micro- and optoelectronic devices. While they can be grown nowadays with high crystal quality, the mechanism by which strain energy is relieved upon thermal treatments remains speculative. To this end, we investigated the evolution (and the interplay) of composition, strain, and morphology of strained Ge0.94Sn0.06 films with temperature. We observed a diffusion-driven formation of Sn-enriched islands (and their self-organization) as well as surface depressions (pits), resulting in phase separation and (local) reduction in strain energy, respectively. Remarkably, these compositional and morphological instabilities were found to be the dominating mechanisms to relieve energy, implying that the relaxation via misfit generation and propagation is not intrinsic to compressively strained Ge0.94Sn0.06 films grown by molecular beam epitaxy.
Dassler, K.; Roohi, F.; Lohrke, J.; Pison, U.; Ide, A.; Remmele, S.; Hütter, H.; Pietsch, H.; Schütz, G.
2012-01-01
The aim of our preclinical study was to investigate the minimum requirements for obtaining sensitive molecular MRI for use in tumor evaluations under optimal conditions. The well-vascularized F9 teratocarcinoma tumor model, which exhibits high levels of the highly accessible target CD105/endoglin, w
Andrade, Tomás; Gentle, Simon
2015-01-01
Momentum relaxation can be built into many holographic models without sacrificing homogeneity of the bulk solution. In this paper we study two such models: one in which translational invariance is broken in the dual theory by spatially-dependent sources for massless scalar fields and another that features an additional neutral scalar field. We turn on a charged scalar field in order to explore the condensation of a charged scalar operator in the dual theories. After demonstrating that the rel...
Introduction to Bayesian statistics
Bolstad, William M
2016-01-01
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...
International Nuclear Information System (INIS)
A joint study of the rotational dynamics and free volume in amorphous 1-propanol (1-PrOH) as a prototypical monohydroxy alcohol by electron spin resonance (ESR) or positron annihilation lifetime spectroscopy (PALS), respectively, is reported. The dynamic parameters of the molecular spin probe 2,2,6,6-tetramethyl-1-piperidinyloxy (TEMPO) and the annihilation ones of the atomic ortho-positronium (o-Ps) probe as a function of temperature are compared. A number of coincidences between various effects in the ESR and PALS responses at the corresponding characteristic ESR and PALS temperatures were found suggesting a common origin of the underlying dynamic processes that were identified using viscosity (VISC) in terms of the two-order parameter (TOP) model and broadband dielectric spectroscopy (BDS) data. (paper)
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
Institute of Scientific and Technical Information of China (English)
Guo Hao-Min; Wen Long; Zhao Zhi-Fei; Bu Shao-Jiang; Li Xin-Hua; Wang Yu-Qi
2012-01-01
We investigated the quantum dots-templated growth of a (0001) GaN film on a c-plane sapphire substrate.The growth was carried out in a radio-frequency molecular beam epitaxy system.The enlargement and coalescence of grains on the GaN quantum dots template was observed in the atom force microscopy images,as well as the more ideal surface morphology of the GaN epitaxial film on the quantum dots template compared with the one on the A(l)N buffer.The Ga polarity was confirmed by the reflected high energy electron diffraction patterns and the Raman spectra.The significant strain relaxation in the quantum dots-templated GaN film was calculated based on the Raman spectra and the X-ray rocking curves. Meanwhile,the threading dislocation density in the quantum dots-templated film was estimated to be 7.1 × 107 cm-2,which was significantly suppressed compared with that of the A(l)N-buffered GaN film.The roomtemperature Hall measurement showed an electron mobility of up to 1860 cm2/V· s in the two-dimensional electron gas at the interface of the Al0.25Ga0.75N/GaN heterojunction.
Institute of Scientific and Technical Information of China (English)
林生军; 黄印; 谢东日; 闵道敏; 王威望; 杨柳青; 李盛涛
2016-01-01
环氧树脂是电力设备中广泛应用的一种绝缘材料,其介电性能受到分子链运动特性的影响.本文制备了直径为50 mm、厚度为1 mm的环氧树脂试样,采用差示扫描量热仪和宽频介电谱仪测试了环氧树脂的玻璃化转变温度和介电特性.实验结果表明,环氧树脂的玻璃化转变温度为105◦C,在玻璃化转变温度以上,高频段出现了由分子链段运动造成的松弛过程,低频段出现了由载流子在材料中迁移造成的直流电导过程.发现环氧树脂不同尺寸分子链段的松弛时间不同,其松弛时间分布较宽,计算得到了分子链段在不同温度下的松弛时间分布特性.分子链松弛峰频率和直流电导随温度的变化关系服从Vogel-Tammann-Fulcher公式.拟合实验结果得到分子链松弛峰频率和直流电导的Vogel温度和强度系数.由Vogel温度计算得到了与差示扫描量热测试结果一致的玻璃化转变温度,约为102◦C.结果表明玻璃化转变温度以上环氧树脂的自由体积增大,分子链段有足够的空间来响应外电场从而产生分子链松弛极化,载流子有足够的能量在材料中迁移形成电导.%Epoxy resin is widely used as a polymeric insulating material in power equipment, such as gas-insulated switchgear and gas-insulated lines. The motions of molecular chains or segmental chains in a polymeric insulating material can af-fect the material properties, such as dielectric relaxation, charge transport, breakdown, and glass transition temperature. Molecular or segmental chains may form dipoles, and their motions can contribute to dielectric relaxation properties. Molecular or segmental chains with different scales have different relaxation time constants. Their motions affect dielec-tric relaxation processes in different frequency ranges. The motions of molecular or segmental chains are also affected by temperature, since the magnitudes of motions are restricted by free volume
Andrade, Tomas
2014-01-01
Momentum relaxation can be built into many holographic models without sacrificing homogeneity of the bulk solution. In this paper we study two such models: one in which translational invariance is broken in the dual theory by spatially-dependent sources for massless scalar fields and another that features an additional neutral scalar field. We turn on a charged scalar field in order to explore the condensation of a charged scalar operator in the dual theories. After demonstrating that the relaxed superconductors we construct are thermodynamically relevant, we find that the finite DC electrical conductivity of the normal phase is replaced by a superfluid pole in the broken phase. Moreover, when the normal phase possesses a Drude behaviour at low frequencies, the optical conductivity of the broken phase at low frequencies can be described by a two-fluid model that is a sum of a Drude peak and a superfluid pole, as was found recently for inhomogeneous holographic superconductors. We also study cases in which thi...
Gelman, Andrew; Stern, Hal S; Dunson, David B; Vehtari, Aki; Rubin, Donald B
2013-01-01
FUNDAMENTALS OF BAYESIAN INFERENCEProbability and InferenceSingle-Parameter Models Introduction to Multiparameter Models Asymptotics and Connections to Non-Bayesian ApproachesHierarchical ModelsFUNDAMENTALS OF BAYESIAN DATA ANALYSISModel Checking Evaluating, Comparing, and Expanding ModelsModeling Accounting for Data Collection Decision AnalysisADVANCED COMPUTATION Introduction to Bayesian Computation Basics of Markov Chain Simulation Computationally Efficient Markov Chain Simulation Modal and Distributional ApproximationsREGRESSION MODELS Introduction to Regression Models Hierarchical Linear
Yuan, Ying; MacKinnon, David P.
2009-01-01
This article proposes Bayesian analysis of mediation effects. Compared to conventional frequentist mediation analysis, the Bayesian approach has several advantages. First, it allows researchers to incorporate prior information into the mediation analysis, thus potentially improving the efficiency of estimates. Second, under the Bayesian mediation analysis, inference is straightforward and exact, which makes it appealing for studies with small samples. Third, the Bayesian approach is conceptua...
Bayesian Games with Intentions
Bjorndahl, Adam; Halpern, Joseph Y.; Pass, Rafael
2016-01-01
We show that standard Bayesian games cannot represent the full spectrum of belief-dependent preferences. However, by introducing a fundamental distinction between intended and actual strategies, we remove this limitation. We define Bayesian games with intentions, generalizing both Bayesian games and psychological games, and prove that Nash equilibria in psychological games correspond to a special class of equilibria as defined in our setting.
DEFF Research Database (Denmark)
Jensen, Finn Verner; Nielsen, Thomas Dyhre
2016-01-01
Mathematically, a Bayesian graphical model is a compact representation of the joint probability distribution for a set of variables. The most frequently used type of Bayesian graphical models are Bayesian networks. The structural part of a Bayesian graphical model is a graph consisting of nodes...... and edges. The nodes represent variables, which may be either discrete or continuous. An edge between two nodes A and B indicates a direct influence between the state of A and the state of B, which in some domains can also be interpreted as a causal relation. The wide-spread use of Bayesian networks...... 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...
Bayesian inference of the metazoan phylogeny
DEFF Research Database (Denmark)
Glenner, Henrik; Hansen, Anders J; Sørensen, Martin V;
2004-01-01
been the only feasible combined approach but is highly sensitive to long-branch attraction. Recent development of stochastic models for discrete morphological characters and computationally efficient methods for Bayesian inference has enabled combined molecular and morphological data analysis...... with rigorous statistical approaches less prone to such inconsistencies. We present the first statistically founded analysis of a metazoan data set based on a combination of morphological and molecular data and compare the results with a traditional parsimony analysis. Interestingly, the Bayesian analyses...... such as the ecdysozoans and lophotrochozoans. Parsimony, on the contrary, shows conflicting results, with morphology being congruent to the Bayesian results and the molecular data set producing peculiarities that are largely reflected in the combined 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
Grzegorczyk, Marco; Husmeier, Dirk
2013-01-01
To relax the homogeneity assumption of classical dynamic Bayesian networks (DBNs), various recent studies have combined DBNs with multiple changepoint processes. The underlying assumption is that the parameters associated with time series segments delimited by multiple changepoints are a priori inde
Frühwirth-Schnatter, Sylvia
1990-01-01
In the paper at hand we apply it to Bayesian statistics to obtain "Fuzzy Bayesian Inference". In the subsequent sections we will discuss a fuzzy valued likelihood function, Bayes' theorem for both fuzzy data and fuzzy priors, a fuzzy Bayes' estimator, fuzzy predictive densities and distributions, and fuzzy H.P.D .-Regions. (author's abstract)
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…
von der Linden, Wolfgang; Dose, Volker; von Toussaint, Udo
2014-06-01
Preface; Part I. Introduction: 1. The meaning of probability; 2. Basic definitions; 3. Bayesian inference; 4. Combinatrics; 5. Random walks; 6. Limit theorems; 7. Continuous distributions; 8. The central limit theorem; 9. Poisson processes and waiting times; Part II. Assigning Probabilities: 10. Transformation invariance; 11. Maximum entropy; 12. Qualified maximum entropy; 13. Global smoothness; Part III. Parameter Estimation: 14. Bayesian parameter estimation; 15. Frequentist parameter estimation; 16. The Cramer-Rao inequality; Part IV. Testing Hypotheses: 17. The Bayesian way; 18. The frequentist way; 19. Sampling distributions; 20. Bayesian vs frequentist hypothesis tests; Part V. Real World Applications: 21. Regression; 22. Inconsistent data; 23. Unrecognized signal contributions; 24. Change point problems; 25. Function estimation; 26. Integral equations; 27. Model selection; 28. Bayesian experimental design; Part VI. Probabilistic Numerical Techniques: 29. Numerical integration; 30. Monte Carlo methods; 31. Nested sampling; Appendixes; References; Index.
Directory of Open Access Journals (Sweden)
Nima Kasraie
2011-01-01
Full Text Available The aims of this study were to determine whether standard extracellular contrast agents of Gd(III ions in combination with a polymeric entity susceptible to hydrolytic degradation over a finite period of time, such as Hyaluronic Acid (HA, have sufficient vascular residence time to obtain comparable vascular imaging to current conventional compounds and to obtain sufficient data to show proof of concept that HA with Gd-DTPA ligands could be useful as vascular imaging agents. We assessed the dynamic relaxivity of the HA bound DTPA compounds using a custom-made phantom, as well as relaxation rates at 10.72 MHz with concentrations ranging between 0.09 and 7.96 mM in phosphate-buffered saline. Linear dependences of static longitudinal relaxation rate (R1 on concentration were found for most measured samples, and the HA samples continued to produce high signal strength after 24 hours after injection into a dialysis cassette at 3T, showing superior dynamic relaxivity values compared to conventional contrast media such as Gd-DTPA-BMA.
International Nuclear Information System (INIS)
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
Thermal relaxation and mechanical relaxation of rice gel
Institute of Scientific and Technical Information of China (English)
丁玉琴; 赵思明; 熊善柏
2008-01-01
Rice gel was prepared by simulating the production processes of Chinese local rice noodles,and the properties of thermal relaxation and mechanical relaxation during gelatinization were studied by differential scanning calorimetry(DSC) measurement and dynamic rheometer.The results show that during gelatinization,the molecular chains of rice starch undergo the thermal relaxation and mechanical relaxation.During the first heating and high temperature holding processes,the starch crystallites in the rice slurry melt,and the polymer chains stretch and interact,then viscoelastic gel forms.The cooling and low temperatures holding processes result in reinforced networks and decrease the viscoelasticity of the gel.During the second heating,the remaining starch crystallites further melt,the network is reinforced,and the viscoelasticity increases.The viscoelasticity,the molecular conformation and texture of the gel are adjusted by changing the temperature,and finally construct the gel with the textural characteristics of Chinese local rice noodle.
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.
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.
Granade, Christopher; Cory, D G
2015-01-01
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 solve all three problems. First, we use modern statistical methods, as pioneered by Husz\\'ar and Houlsby and by Ferrie, 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 informative priors on quantum states and channels. Finally, we develop a method that allows online 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.
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...
Bayesian Lensing Shear Measurement
Bernstein, Gary M
2013-01-01
We derive an estimator of weak gravitational lensing shear from background galaxy images that avoids noise-induced biases through a rigorous Bayesian treatment of the measurement. The Bayesian formalism requires a prior describing the (noiseless) distribution of the target galaxy population over some parameter space; this prior can be constructed from low-noise images of a subsample of the target population, attainable from long integrations of a fraction of the survey field. We find two ways to combine this exact treatment of noise with rigorous treatment of the effects of the instrumental point-spread function and sampling. The Bayesian model fitting (BMF) method assigns a likelihood of the pixel data to galaxy models (e.g. Sersic ellipses), and requires the unlensed distribution of galaxies over the model parameters as a prior. The Bayesian Fourier domain (BFD) method compresses galaxies to a small set of weighted moments calculated after PSF correction in Fourier space. It requires the unlensed distributi...
... related breathing difficulties. Learn some ways to control breathing and some techniques to help you reach a greater level of relaxation during your day: Diaphragmatic Breathing Minimizing Shortness of Breath Instant Relaxation Drill Meditation ...
Institute of Scientific and Technical Information of China (English)
LI ZhiQiang; GUO BaoCheng; LI JunBing; HE ShunPing; CHEN YiYu
2008-01-01
The genus Sinocyclocheilus is distributed in Yun-Gui Plateau and its surrounding region only, within more than 10 cave species showing different degrees of degeneration of eyes and pigmentation with wonderful adaptations. To present, published morphological and molecular phylogenetic hypotheses of Sinocyclocheilus from prior works are very different and the relationships within the genus are still far from clear. We obtained the sequences of cytochrome b (cyt b) and NADH dehydrogenase subunit 4 (ND4) of 34 species within Sinocyclocheilus, which represent the most dense taxon sampling to date. We performed Bayesian mixed models analyses with this data set. Under this phylogenetic framework, we estimated the divergence times of recovered clades using different methods under relaxed molecular clock. Our phyloegentic results supported the monophyly of Sinocyclocheilus and showed that this genus could be subdivided into 6 major clades. In addition, an earlier finding demonstrating the polyphyletic of cave species and the most basal position of S. jii was corroborated. Relaxed divergence-time estimation suggested that Sinocyclocheilus originated at the late Miocene, about 11 million years ago (Ma), which is older than what have been assumed.
Malicious Bayesian Congestion Games
Gairing, Martin
2008-01-01
In this paper, we introduce malicious Bayesian congestion games as an extension to congestion games where players might act in a malicious way. In such a game each player has two types. Either the player is a rational player seeking to minimize her own delay, or - with a certain probability - the player is malicious in which case her only goal is to disturb the other players as much as possible. We show that such games do in general not possess a Bayesian Nash equilibrium in pure strategies (i.e. a pure Bayesian Nash equilibrium). Moreover, given a game, we show that it is NP-complete to decide whether it admits a pure Bayesian Nash equilibrium. This result even holds when resource latency functions are linear, each player is malicious with the same probability, and all strategy sets consist of singleton sets. For a slightly more restricted class of malicious Bayesian congestion games, we provide easy checkable properties that are necessary and sufficient for the existence of a pure Bayesian Nash equilibrium....
International Nuclear Information System (INIS)
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 −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). (paper)
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.
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...
Protein dynamics from nuclear magnetic relaxation.
Charlier, Cyril; Cousin, Samuel F; Ferrage, Fabien
2016-05-01
Nuclear magnetic resonance is a ubiquitous spectroscopic tool to explore molecules with atomic resolution. Nuclear magnetic relaxation is intimately connected to molecular motions. Many methods and models have been developed to measure and interpret the characteristic rates of nuclear magnetic relaxation in proteins. These approaches shed light on a rich and diverse range of motions covering timescales from picoseconds to seconds. Here, we introduce some of the basic concepts upon which these approaches are built and provide a series of illustrations.
Relaxation processes in mixed gas dynamic lasers
Energy Technology Data Exchange (ETDEWEB)
Soloukhin, R.I.; Fomin, N.A.
1978-12-01
With the solution of gasdynamic and CO/sub 2/--N/sub 2/ vibrational relaxation equations, analysis was made of vibrational energy losses associated with relaxation processes in an inverted molecular system with selective thermal excitation and supersonic flow mixing of the pumping and radiative gas components. Optimum operation conditions were determined, and a possibility of regimes with low vibrational losses was found to be feasible at available specific energies up to 200 J/g.
Bayesian ensemble refinement by replica simulations and reweighting
Hummer, Gerhard
2015-01-01
We describe different Bayesian ensemble refinement methods, examine their interrelation, and discuss their practical application. With ensemble refinement, the properties of dynamic and partially disordered (bio)molecular structures can be characterized by integrating a wide range of experimental data, including measurements of ensemble-averaged observables. We start from a Bayesian formulation in which the posterior is a functional that ranks different configuration space distributions. By maximizing this posterior, we derive an optimal Bayesian ensemble distribution. For discrete configurations, this optimal distribution is identical to that obtained by the maximum entropy "ensemble refinement of SAXS" (EROS) formulation. Bayesian replica ensemble refinement enhances the sampling of relevant configurations by imposing restraints on averages of observables in coupled replica molecular dynamics simulations. We find that the strength of the restraint scales with the number of replicas and we show that this sca...
Institute of Scientific and Technical Information of China (English)
Toshiro SHIBANO; Paul M VANHOUTTE
2003-01-01
AIM: To determine whether or not low molecular G-proteins are involved in the endothelium-dependent relaxations to bradykinin. METHODS: The effects of botulinum ADP-ribosyltranferase C3 were studied in porcine coronary arteries and endothelial cells. RESULTS: Incubation of membrane fractions isolated from endothelial cells with the enzyme and 32p-NAD resulted in the ribosylation of the proteins with molecular weight of 24-25 kDa. Radio labelling of these proteins was suppressed in the presence of guanosine 5t-O-(3-thiotriphosphate) (GTP-yS), a hydrolysis-resistant analog of GTP. In the isolated arteries, ADP-ribosyltransferase C3 attenuated the relaxations tobradykinin during contractions with prostaglandin F2α in the presence of tween 80 (non ionic detergent), but not in the absence of tween 80. CONCLUSION: Low molecular weight G-proteins of the Rho family contribute to the mechanism of relaxation induced by bradykinin.
Approximate Bayesian Computation in Large Scale Structure: constraining the galaxy-halo connection
Hahn, ChangHoon; Vakili, Mohammadjavad; Walsh, Kilian; Hearin, Andrew P.; Hogg, David W.; Cambpell, Duncan
2016-01-01
The standard approaches to Bayesian parameter inference in large scale structure (LSS) assume a Gaussian functional form (chi-squared form) for the likelihood. They are also typically restricted to measurements such as the two point correlation function. Likelihood free inferences such as Approximate Bayesian Computation (ABC) make inference possible without assuming any functional form for the likelihood, thereby relaxing the assumptions and restrictions of the standard approach. Instead it ...
Bayesian least squares deconvolution
Ramos, A Asensio
2015-01-01
Aims. To develop a fully Bayesian least squares deconvolution (LSD) that can be applied to the reliable detection of magnetic signals in noise-limited stellar spectropolarimetric observations using multiline techniques. Methods. We consider LSD under the Bayesian framework and we introduce a flexible Gaussian Process (GP) prior for the LSD profile. This prior allows the result to automatically adapt to the presence of signal. We exploit several linear algebra identities to accelerate the calculations. The final algorithm can deal with thousands of spectral lines in a few seconds. Results. We demonstrate the reliability of the method with synthetic experiments and we apply it to real spectropolarimetric observations of magnetic stars. We are able to recover the magnetic signals using a small number of spectral lines, together with the uncertainty at each velocity bin. This allows the user to consider if the detected signal is reliable. The code to compute the Bayesian LSD profile is freely available.
Bayesian least squares deconvolution
Asensio Ramos, A.; Petit, P.
2015-11-01
Aims: We develop a fully Bayesian least squares deconvolution (LSD) that can be applied to the reliable detection of magnetic signals in noise-limited stellar spectropolarimetric observations using multiline techniques. Methods: We consider LSD under the Bayesian framework and we introduce a flexible Gaussian process (GP) prior for the LSD profile. This prior allows the result to automatically adapt to the presence of signal. We exploit several linear algebra identities to accelerate the calculations. The final algorithm can deal with thousands of spectral lines in a few seconds. Results: We demonstrate the reliability of the method with synthetic experiments and we apply it to real spectropolarimetric observations of magnetic stars. We are able to recover the magnetic signals using a small number of spectral lines, together with the uncertainty at each velocity bin. This allows the user to consider if the detected signal is reliable. The code to compute the Bayesian LSD profile is freely available.
Hybrid Batch Bayesian Optimization
Azimi, Javad; Fern, Xiaoli
2012-01-01
Bayesian Optimization aims at optimizing an unknown non-convex/concave function that is costly to evaluate. We are interested in application scenarios where concurrent function evaluations are possible. Under such a setting, BO could choose to either sequentially evaluate the function, one input at a time and wait for the output of the function before making the next selection, or evaluate the function at a batch of multiple inputs at once. These two different settings are commonly referred to as the sequential and batch settings of Bayesian Optimization. In general, the sequential setting leads to better optimization performance as each function evaluation is selected with more information, whereas the batch setting has an advantage in terms of the total experimental time (the number of iterations). In this work, our goal is to combine the strength of both settings. Specifically, we systematically analyze Bayesian optimization using Gaussian process as the posterior estimator and provide a hybrid algorithm t...
Loredo, T J
2004-01-01
I describe a framework for adaptive scientific exploration based on iterating an Observation--Inference--Design cycle that allows adjustment of hypotheses and observing protocols in response to the results of observation on-the-fly, as data are gathered. The framework uses a unified Bayesian methodology for the inference and design stages: Bayesian inference to quantify what we have learned from the available data and predict future data, and Bayesian decision theory to identify which new observations would teach us the most. When the goal of the experiment is simply to make inferences, the framework identifies a computationally efficient iterative ``maximum entropy sampling'' strategy as the optimal strategy in settings where the noise statistics are independent of signal properties. Results of applying the method to two ``toy'' problems with simulated data--measuring the orbit of an extrasolar planet, and locating a hidden one-dimensional object--show the approach can significantly improve observational eff...
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...
Energy Technology Data Exchange (ETDEWEB)
Wang, Wei; Zhou, Qian; Dong, Yuan; Yeo, Yee-Chia, E-mail: yeo@ieee.org [Department of Electrical and Computer Engineering, National University of Singapore, Singapore 117576 (Singapore); Tok, Eng Soon [Department of Physics, National University of Singapore, Singapore 117551 (Singapore)
2015-06-08
We investigated the critical thickness (h{sub c}) for plastic relaxation of Ge{sub 1−x}Sn{sub x} grown by molecular beam epitaxy. Ge{sub 1−x}Sn{sub x} films with various Sn mole fraction x (x ≤ 0.17) and different thicknesses were grown on Ge(001). The strain relaxation of Ge{sub 1−x}Sn{sub x} films and the h{sub c} were investigated by high-resolution x-ray diffraction and reciprocal space mapping. It demonstrates that the measured h{sub c} values of Ge{sub 1−x}Sn{sub x} layers are as much as an order of magnitude larger than that predicted by the Matthews and Blakeslee (M-B) model. The People and Bean (P-B) model was also used to predict the h{sub c} values in Ge{sub 1−x}Sn{sub x}/Ge system. The measured h{sub c} values for various Sn content follow the trend, but slightly larger than that predicted by the P-B model.
Bayesian multiple target tracking
Streit, Roy L
2013-01-01
This second edition has undergone substantial revision from the 1999 first edition, recognizing that a lot has changed in the multiple target tracking field. One of the most dramatic changes is in the widespread use of particle filters to implement nonlinear, non-Gaussian Bayesian trackers. This book views multiple target tracking as a Bayesian inference problem. Within this framework it develops the theory of single target tracking, multiple target tracking, and likelihood ratio detection and tracking. In addition to providing a detailed description of a basic particle filter that implements
Bayesian and frequentist inequality tests
David M. Kaplan; Zhuo, Longhao
2016-01-01
Bayesian and frequentist criteria are fundamentally different, but often posterior and sampling distributions are asymptotically equivalent (and normal). We compare Bayesian and frequentist hypothesis tests of inequality restrictions in such cases. For finite-dimensional parameters, if the null hypothesis is that the parameter vector lies in a certain half-space, then the Bayesian test has (frequentist) size $\\alpha$; if the null hypothesis is any other convex subspace, then the Bayesian test...
DPpackage: Bayesian Semi- and Nonparametric Modeling in R
Alejandro Jara; Timothy Hanson; Quintana, Fernando A.; Peter Müller; Rosner, Gary L.
2011-01-01
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 r...
Kobryn, A E; Hirata, F
2005-01-01
We present results of theoretical study and numerical calculation of the dynamics of molecular liquids based on combination of the memory equation formalism and the reference interaction site model - RISM. Memory equations for the site-site intermediate scattering functions are studied in the mode-coupling approximation for the first order memory kernels, while equilibrium properties such as site-site static structure factors are deduced from RISM. The results include the temperature-density(pressure) dependence of translational diffusion coefficients D and orientational relaxation times t for acetonitrile in water, methanol in water and methanol in acetonitrile, all in the limit of infinite dilution. Calculations are performed over the range of temperatures and densities employing the SPC/E model for water and optimized site-site potentials for acetonitrile and methanol. The theory is able to reproduce qualitatively all main features of temperature and density dependences of D and t observed in real and comp...
A. Korattikara; V. Rathod; K. Murphy; M. Welling
2015-01-01
We consider the problem of Bayesian parameter estimation for deep neural networks, which is important in problem settings where we may have little data, and/ or where we need accurate posterior predictive densities p(y|x, D), e.g., for applications involving bandits or active learning. One simple ap
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
Loredo, Thomas J.
2004-04-01
I describe a framework for adaptive scientific exploration based on iterating an Observation-Inference-Design cycle that allows adjustment of hypotheses and observing protocols in response to the results of observation on-the-fly, as data are gathered. The framework uses a unified Bayesian methodology for the inference and design stages: Bayesian inference to quantify what we have learned from the available data and predict future data, and Bayesian decision theory to identify which new observations would teach us the most. When the goal of the experiment is simply to make inferences, the framework identifies a computationally efficient iterative ``maximum entropy sampling'' strategy as the optimal strategy in settings where the noise statistics are independent of signal properties. Results of applying the method to two ``toy'' problems with simulated data-measuring the orbit of an extrasolar planet, and locating a hidden one-dimensional object-show the approach can significantly improve observational efficiency in settings that have well-defined nonlinear models. I conclude with a list of open issues that must be addressed to make Bayesian adaptive exploration a practical and reliable tool for optimizing scientific exploration.
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...
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...
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...
Energy Technology Data Exchange (ETDEWEB)
Rumpel, Sigrun; Becker, Stefan; Zweckstetter, Markus [Max Planck Institute for Biophysical Chemistry, Department for NMR-based Structural Biology (Germany)], E-mail: mzwecks@gwdg.de
2008-01-15
Structure determination of homooligomeric proteins by NMR spectroscopy is difficult due to the lack of chemical shift perturbation data, which is very effective in restricting the binding interface in heterooligomeric systems, and the difficulty of obtaining a sufficient number of intermonomer distance restraints. Here we solved the high-resolution solution structure of the 15.4 kDa homodimer CylR2, the regulator of cytolysin production from Enterococcus faecalis, which deviates by 1.1 A from the previously determined X-ray structure. We studied the influence of different experimental information such as long-range distances derived from paramagnetic relaxation enhancement, residual dipolar couplings, symmetry restraints and intermonomer Nuclear Overhauser Effect restraints on the accuracy of the derived structure. In addition, we show that it is useful to combine experimental information with methods of ab initio docking when the available experimental data are not sufficient to obtain convergence to the correct homodimeric structure. In particular, intermonomer distances may not be required when residual dipolar couplings are compared to values predicted on the basis of the charge distribution and the shape of ab initio docking solutions.
Energy Technology Data Exchange (ETDEWEB)
Iuchi, Satoru; Koga, Nobuaki [Graduate School of Information Science, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8601 (Japan)
2015-12-31
A model electronic Hamiltonian of [Fe(bpy){sub 3}]{sup 2+}, which was recently refined for use in molecular dynamics simulations, is reviewed with some additional results. In particular, the quality of the refined model Hamiltonian is examined in terms of the vibrational frequencies and solvation structures of the lowest singlet and quintet states.
International Nuclear Information System (INIS)
A model electronic Hamiltonian of [Fe(bpy)3]2+, which was recently refined for use in molecular dynamics simulations, is reviewed with some additional results. In particular, the quality of the refined model Hamiltonian is examined in terms of the vibrational frequencies and solvation structures of the lowest singlet and quintet states
How does the relaxation of a supercooled liquid depend on its microscopic dynamics?
Gleim, Tobias; Kob, Walter; Binder, Kurt
1998-01-01
Using molecular dynamics computer simulations we investigate how the relaxation dynamics of a simple supercooled liquid with Newtonian dynamics differs from the one with a stochastic dynamics. We find that, apart from the early beta-relaxation regime, the two dynamics give rise to the same relaxation behavior. The increase of the relaxation times of the system upon cooling, the details of the alpha-relaxation, as well as the wave vector dependence of the Edwards-Anderson-parameters are indepe...
Charge relaxation dynamics of an electrolytic nanocapacitor
Thakore, Vaibhav
2013-01-01
Understanding ion relaxation dynamics in overlapping electric double layers (EDLs) is critical for the development of efficient nanotechnology based electrochemical energy storage, electrochemomechanical energy conversion and bioelectrochemical sensing devices besides controlled synthesis of nanostructured materials. Here, using Lattice Boltzmann (LB) method, we present results from the simulations of an electrolytic nanocapacitor subjected to a step potential at t = 0 for various degrees of EDL overlap, solvent viscosities, ratios of cation to anion diffusivity and electrode separations. A continuously varying molecular speed dependent relaxation time, proposed for use with the LB equation, recovers the correct microscopic description of molecular collision phenomena and holds promise for enhancing the stability of the LB algorithm. Results for large EDL overlap showed oscillatory behavior for ionic current densities in contrast to monotonic relaxation to equilibrium for low EDL overlap. Further, at low solv...
实时脉冲光声法用于分子弛豫时间的测定%Real-time pulsed photoacoustics-molecular relaxation time measurements
Institute of Scientific and Technical Information of China (English)
Markushev Dragan; Rabasovic Mihailo; Lukic Mladena; Cojbasic Zarko; Todorovic Dragan
2013-01-01
脉冲光声光谱法一个重要的应用是确定气体分子的振动—平动弛豫时间τV-T.因激光光束的空间分布R(r)对光声测量有显著影响,我们发展了同时测定R(r)和τV-T的方法.本方法基于光声脉冲的实时信号和一种用于光声成像的数学运算法则.本文讨论了智能计算用于多原子气体分子的R(r)和τV-T同时和实时测定的可能性.进一步利用前馈多层神经网络的离线批训练法,结合一个理论光声信号对R(r)和τV-T进行了同时和实时分析.本方法可明显缩短确定上述参数所需时间.%Determination of the vibrational-to-translational relaxation time rv-T in gases is one of the applications of pulsed photoacoustic spectroscopy.Because the spatial profile of the laser beam R (r)can significantly influence the accuracy of the photoacoustic measurements,we developed the method for simultaneous determination of the R(r)and τv T.It is based on the temporal shape of the photoacoustic pulse and utilizes a mathematical algorithm developed for photoacoustic tomography.The possibilities of computational intelligence application for simultaneous and real-time determination of R(r)and rv-T values of polyatomic molecules in gases by pulsed photoacoustic are also discussed.Feed forward multilayer perception networks are trained in an offline batch training regime to estimate simultaneously,and in real-time,R(r) (profile shape class) and τv T from a given (theoretical) photoacoustic signals.Proposed method significantly shortens the time required for the simultaneous determination of the afore mentioned quantities.
Probability and Bayesian statistics
1987-01-01
This book contains selected and refereed contributions to the "Inter national Symposium on Probability and Bayesian Statistics" which was orga nized to celebrate the 80th birthday of Professor Bruno de Finetti at his birthplace Innsbruck in Austria. Since Professor de Finetti died in 1985 the symposium was dedicated to the memory of Bruno de Finetti and took place at Igls near Innsbruck from 23 to 26 September 1986. Some of the pa pers are published especially by the relationship to Bruno de Finetti's scientific work. The evolution of stochastics shows growing importance of probability as coherent assessment of numerical values as degrees of believe in certain events. This is the basis for Bayesian inference in the sense of modern statistics. The contributions in this volume cover a broad spectrum ranging from foundations of probability across psychological aspects of formulating sub jective probability statements, abstract measure theoretical considerations, contributions to theoretical statistics an...
DEFF Research Database (Denmark)
Mørup, Morten; Schmidt, Mikkel N
2012-01-01
Many networks of scientific interest naturally decompose into clusters or communities with comparatively fewer external than internal links; however, current Bayesian models of network communities do not exert this intuitive notion of communities. We formulate a nonparametric Bayesian model...... for community detection consistent with an intuitive definition of communities and present a Markov chain Monte Carlo procedure for inferring the community structure. A Matlab toolbox with the proposed inference procedure is available for download. On synthetic and real networks, our model detects communities...... consistent with ground truth, and on real networks, it outperforms existing approaches in predicting missing links. This suggests that community structure is an important structural property of networks that should be explicitly modeled....
Brody, Samuel; Lapata, Mirella
2009-01-01
Sense induction seeks to automatically identify word senses directly from a corpus. A key assumption underlying previous work is that the context surrounding an ambiguous word is indicative of its meaning. Sense induction is thus typically viewed as an unsupervised clustering problem where the aim is to partition a word’s contexts into different classes, each representing a word sense. Our work places sense induction in a Bayesian context by modeling the contexts of the ambiguous word as samp...
Bayesian Generalized Rating Curves
Helgi Sigurðarson 1985
2014-01-01
A rating curve is a curve or a model that describes the relationship between water elevation, or stage, and discharge in an observation site in a river. The rating curve is fit from paired observations of stage and discharge. The rating curve then predicts discharge given observations of stage and this methodology is applied as stage is substantially easier to directly observe than discharge. In this thesis a statistical rating curve model is proposed working within the framework of Bayesian...
Efficient Bayesian Phase Estimation
Wiebe, Nathan; Granade, Chris
2016-07-01
We introduce a new method called rejection filtering that we use to perform adaptive Bayesian phase estimation. Our approach has several advantages: it is classically efficient, easy to implement, achieves Heisenberg limited scaling, resists depolarizing noise, tracks time-dependent eigenstates, recovers from failures, and can be run on a field programmable gate array. It also outperforms existing iterative phase estimation algorithms such as Kitaev's method.
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...
Wiegerinck, Wim; Schoenaker, Christiaan; Duane, Gregory
2016-04-01
Recently, methods for model fusion by dynamically combining model components in an interactive ensemble have been proposed. In these proposals, fusion parameters have to be learned from data. One can view these systems as parametrized dynamical systems. We address the question of learnability of dynamical systems with respect to both short term (vector field) and long term (attractor) behavior. In particular we are interested in learning in the imperfect model class setting, in which the ground truth has a higher complexity than the models, e.g. due to unresolved scales. We take a Bayesian point of view and we define a joint log-likelihood that consists of two terms, one is the vector field error and the other is the attractor error, for which we take the L1 distance between the stationary distributions of the model and the assumed ground truth. In the context of linear models (like so-called weighted supermodels), and assuming a Gaussian error model in the vector fields, vector field learning leads to a tractable Gaussian solution. This solution can then be used as a prior for the next step, Bayesian attractor learning, in which the attractor error is used as a log-likelihood term. Bayesian attractor learning is implemented by elliptical slice sampling, a sampling method for systems with a Gaussian prior and a non Gaussian likelihood. Simulations with a partially observed driven Lorenz 63 system illustrate the approach.
Relaxation Techniques for Health
... hasn't been shown to relieve labor pain. Depression An evaluation of 15 studies concluded that relaxation ... links Twitter Read our disclaimer about external links Facebook Read our disclaimer about external links YouTube Read ...
International Nuclear Information System (INIS)
The experimental and theoretical two-dimensional nuclear Overhauser effect spectra, double-quantum-filtered COSY experiments, and molecular mechanics calculations on the self-complementary decamer [d-(5'ATATATATAT3')]2 presented here indicate that the duplex as a time-average assumes a wrinkled D conformation (B DNA family) with a hydration tunnel in the minor groove. Formation of the tunnel is favored by non-bonded and electrostatic interchain sugar-phosphate and ion-DNA interactions in the minor groove. The size of the tunnel in the DNA perfectly accomodates three types of water molecules - one bridging interstrand N3 atoms of adenine, another water molecule bridging interstrand O2 atoms of thymine bases and another water molecule bridging the above mentioned two water molecules. 31 refs.; 3 figs.; 2 tabs
Perturbations and quantum relaxation
Kandhadai, Adithya
2016-01-01
We investigate whether small perturbations can cause relaxation to quantum equilibrium over very long timescales. We consider in particular a two-dimensional harmonic oscillator, which can serve as a model of a field mode on expanding space. We assume an initial wave function with small perturbations to the ground state. We present evidence that the trajectories are highly confined so as to preclude relaxation to equilibrium even over very long timescales. Cosmological implications are briefly discussed.
Bayesian optimization for materials design
Frazier, Peter I.; Wang, Jialei
2015-01-01
We introduce Bayesian optimization, a technique developed for optimizing time-consuming engineering simulations and for fitting machine learning models on large datasets. Bayesian optimization guides the choice of experiments during materials design and discovery to find good material designs in as few experiments as possible. We focus on the case when materials designs are parameterized by a low-dimensional vector. Bayesian optimization is built on a statistical technique called Gaussian pro...
Bayesian Posteriors Without Bayes' Theorem
Hill, Theodore P
2012-01-01
The classical Bayesian posterior arises naturally as the unique solution of several different optimization problems, without the necessity of interpreting data as conditional probabilities and then using Bayes' Theorem. For example, the classical Bayesian posterior is the unique posterior that minimizes the loss of Shannon information in combining the prior and the likelihood distributions. These results, direct corollaries of recent results about conflations of probability distributions, reinforce the use of Bayesian posteriors, and may help partially reconcile some of the differences between classical and Bayesian statistics.
Siwko, Magdalena E; Corni, Stefano
2013-04-28
Proteins immobilized on inorganic surfaces are important in technological fields such as biosensors, enzymatic biofuel cells and biomolecular electronics. In these frameworks, it has been demonstrated that some proteins are able to keep their functionality, although the latter may be somewhat modified by the interaction with the surface. Cytochrome C, an heme-based electron transfer protein, has been found to be able to exchange electrons with the gold surface on which it is immobilized, but some deviations from the expected electron transfer rates were evidenced [C. A. Bortolotti, et al., J. Phys. Chem. C 2007, 111, 12100-12105]. In this work we have used molecular dynamics simulations of (native and mutated) yeast cytochrome C supported on Au(111) to investigate the microscopic picture behind the experimental behavior of the molecule. In particular, we have focused on the structural re-arrangements due to the interactions with the surface. We found that, despite being secondary-structure preserving, they can profoundly affect protein-surface electronic coupling and, in turn, electron transfer rates, explaining experimental findings. The conformational flexibility of the protein in the region of the protein-surface bond is thus pivotal in determining the resulting ET functionality of the immobilized protein.
A Bayesian variable selection procedure for ranking overlapping gene sets
DEFF Research Database (Denmark)
Skarman, Axel; Mahdi Shariati, Mohammad; Janss, Luc;
2012-01-01
variable selection to differential expression to prioritize the molecular and genetic pathways involved in the responses to Escherichia coli infection in Danish Holstein cows. Results We used a Bayesian variable selection method to prioritize Kyoto Encyclopedia of Genes and Genomes pathways. We used our......Background Genome-wide expression profiling using microarrays or sequence-based technologies allows us to identify genes and genetic pathways whose expression patterns influence complex traits. Different methods to prioritize gene sets, such as the genes in a given molecular pathway, have been...... described. In many cases, these methods test one gene set at a time, and therefore do not consider overlaps among the pathways. Here, we present a Bayesian variable selection method to prioritize gene sets that overcomes this limitation by considering all gene sets simultaneously. We applied Bayesian...
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
Computationally efficient Bayesian tracking
Aughenbaugh, Jason; La Cour, Brian
2012-06-01
In this paper, we describe the progress we have achieved in developing a computationally efficient, grid-based Bayesian fusion tracking system. In our approach, the probability surface is represented by a collection of multidimensional polynomials, each computed adaptively on a grid of cells representing state space. Time evolution is performed using a hybrid particle/grid approach and knowledge of the grid structure, while sensor updates use a measurement-based sampling method with a Delaunay triangulation. We present an application of this system to the problem of tracking a submarine target using a field of active and passive sonar buoys.
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.
Bayesian Geostatistical Design
DEFF Research Database (Denmark)
Diggle, Peter; Lophaven, Søren Nymand
2006-01-01
locations to, or deletion of locations from, an existing design, and prospective design, which consists of choosing positions for a new set of sampling locations. We propose a Bayesian design criterion which focuses on the goal of efficient spatial prediction whilst allowing for the fact that model......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...
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...
Inference in hybrid Bayesian networks
DEFF Research Database (Denmark)
Lanseth, Helge; Nielsen, Thomas Dyhre; Rumí, Rafael;
2009-01-01
Since the 1980s, Bayesian Networks (BNs) have become increasingly popular for building statistical models of complex systems. This is particularly true for boolean systems, where BNs often prove to be a more efficient modelling framework than traditional reliability-techniques (like fault trees...... decade's research on inference in hybrid Bayesian networks. The discussions are linked to an example model for estimating human reliability....
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.
Hydrogen relaxation in lutetium
Vajda, P.; Daou, J.N.; Moser, P.
1983-01-01
The internal friction and the dynamic modulus have been measured between 4.2 and 470 K in the system α-LuH(D)x, with x = 0 to 0.2. In well annealed specimens, an (H)-peak is observed at 215-225 K, which has a linearly x-dependent amplitude and exhibits an isotope effect on its activation energy and relaxation time. It is attributed to a Snoek-like relaxation of H-H pairs reorienting in the Lu-lattice. The isotope effect is interpreted in a model of tunnelling from different excited levels for...
Implementing Bayesian Vector Autoregressions Implementing Bayesian Vector Autoregressions
Directory of Open Access Journals (Sweden)
Richard M. Todd
1988-03-01
Full Text Available Implementing Bayesian Vector Autoregressions This paper discusses how the Bayesian approach can be used to construct a type of multivariate forecasting model known as a Bayesian vector autoregression (BVAR. In doing so, we mainly explain Doan, Littermann, and Sims (1984 propositions on how to estimate a BVAR based on a certain family of prior probability distributions. indexed by a fairly small set of hyperparameters. There is also a discussion on how to specify a BVAR and set up a BVAR database. A 4-variable model is used to iliustrate the BVAR approach.
Relaxation techniques for stress
Chronic stress can be bad for your body and mind. In can put you at risk for health problems such as high blood pressure, stomachaches, headaches, anxiety, and depression. Using relaxation techniques can help you feel calm. These exercises can also help you ...
Dynamic Bayesian diffusion estimation
Dedecius, K
2012-01-01
The rapidly increasing complexity of (mainly wireless) ad-hoc networks stresses the need of reliable distributed estimation of several variables of interest. The widely used centralized approach, in which the network nodes communicate their data with a single specialized point, suffers from high communication overheads and represents a potentially dangerous concept with a single point of failure needing special treatment. This paper's aim is to contribute to another quite recent method called diffusion estimation. By decentralizing the operating environment, the network nodes communicate just within a close neighbourhood. We adopt the Bayesian framework to modelling and estimation, which, unlike the traditional approaches, abstracts from a particular model case. This leads to a very scalable and universal method, applicable to a wide class of different models. A particularly interesting case - the Gaussian regressive model - is derived as an example.
Book review: Bayesian analysis for population ecology
Link, William A.
2011-01-01
Brian Dennis described the field of ecology as “fertile, uncolonized ground for Bayesian ideas.” He continued: “The Bayesian propagule has arrived at the shore. Ecologists need to think long and hard about the consequences of a Bayesian ecology. The Bayesian outlook is a successful competitor, but is it a weed? I think so.” (Dennis 2004)
Current trends in Bayesian methodology with applications
Upadhyay, Satyanshu K; Dey, Dipak K; Loganathan, Appaia
2015-01-01
Collecting Bayesian material scattered throughout the literature, Current Trends in Bayesian Methodology with Applications examines the latest methodological and applied aspects of Bayesian statistics. The book covers biostatistics, econometrics, reliability and risk analysis, spatial statistics, image analysis, shape analysis, Bayesian computation, clustering, uncertainty assessment, high-energy astrophysics, neural networking, fuzzy information, objective Bayesian methodologies, empirical Bayes methods, small area estimation, and many more topics.Each chapter is self-contained and focuses on
... 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 product. ...
Irregular-Time Bayesian Networks
Ramati, Michael
2012-01-01
In many fields observations are performed irregularly along time, due to either measurement limitations or lack of a constant immanent rate. While discrete-time Markov models (as Dynamic Bayesian Networks) introduce either inefficient computation or an information loss to reasoning about such processes, continuous-time Markov models assume either a discrete state space (as Continuous-Time Bayesian Networks), or a flat continuous state space (as stochastic dif- ferential equations). To address these problems, we present a new modeling class called Irregular-Time Bayesian Networks (ITBNs), generalizing Dynamic Bayesian Networks, allowing substantially more compact representations, and increasing the expressivity of the temporal dynamics. In addition, a globally optimal solution is guaranteed when learning temporal systems, provided that they are fully observed at the same irregularly spaced time-points, and a semiparametric subclass of ITBNs is introduced to allow further adaptation to the irregular nature of t...
Kinetic Actviation Relaxation Technique
Béland, Laurent Karim; El-Mellouhi, Fedwa; Joly, Jean-François; Mousseau, Normand
2011-01-01
We present a detailed description of the kinetic Activation-Relaxation Technique (k-ART), an off-lattice, self-learning kinetic Monte Carlo algorithm with on-the-fly event search. Combining a topological classification for local environments and event generation with ART nouveau, an efficient unbiased sampling method for finding transition states, k-ART can be applied to complex materials with atoms in off-lattice positions or with elastic deformations that cannot be handled with standard KMC approaches. In addition to presenting the various elements of the algorithm, we demonstrate the general character of k-ART by applying the algorithm to three challenging systems: self-defect annihilation in c-Si, self-interstitial diffusion in Fe and structural relaxation in amorphous silicon.
Experiments in paramagnetic relaxation
International Nuclear Information System (INIS)
This thesis presents two attempts to improve the resolving power of the relaxation measurement technique. The first attempt reconsiders the old technique of steady state saturation. When used in conjunction with the pulse technique, it offers the possibility of obtaining additional information about the system in which all-time derivatives are zero; in addition, non-linear effects may be distinguished from each other. The second attempt involved a systematic study of only one system: Cu in the Tutton salts (K and Rb). The systematic approach, the high accuracy of the measurement and the sheer amount of experimental data for varying temperature, magnetic field and concentration made it possible in this case to separate the prevailing relaxation mechanisms reliably
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…
Nonlinear fractional relaxation
Indian Academy of Sciences (India)
A Tofighi
2012-04-01
We deﬁne a nonlinear model for fractional relaxation phenomena. We use -expansion method to analyse this model. By studying the fundamental solutions of this model we ﬁnd that when → 0 the model exhibits a fast decay rate and when → ∞ the model exhibits a power-law decay. By analysing the frequency response we ﬁnd a logarithmic enhancement for the relative ratio of susceptibility.
Relaxation from particle production
Hook, Anson
2016-01-01
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.
Neuronanatomy, neurology and Bayesian networks
Bielza Lozoya, Maria Concepcion
2014-01-01
Bayesian networks are data mining models with clear semantics and a sound theoretical foundation. In this keynote talk we will pinpoint a number of neuroscience problems that can be addressed using Bayesian networks. In neuroanatomy, we will show computer simulation models of dendritic trees and classification of neuron types, both based on morphological features. In neurology, we will present the search for genetic biomarkers in Alzheimer's disease and the prediction of health-related qualit...
Microscopic origin of shear relaxation in a model viscoelastic liquid.
Ashwin, J; Sen, Abhijit
2015-02-01
An atomistic description of shear stress relaxation in a viscoelastic liquid is developed from first principles through accurate molecular dynamic simulations in a model Yukawa system. It is shown that the relaxation time τ(M)(ex) of the excess part of the shear stress autocorrelation function provides a correct measure of the relaxation process. Below a certain critical value Γ(c) of the Coulomb coupling strength, the lifetime of local atomic connectivity τ(LC) converges to τ(M)(ex) and is the microscopic origin of the relaxation. At Γ≫Γ(c), i.e., in the potential energy dominated regime, τ(M)(ex)→τ(M) (the Maxwell relaxation time) and can, therefore, fully account for the elastic or "solidlike" behavior. Our results can help provide a better fundamental understanding of viscoelastic behavior in a variety of strongly coupled systems such as dusty plasmas, colloids, and non-Newtonian fluids.
Dale Poirier
2008-01-01
This paper provides Bayesian rationalizations for White’s heteroskedastic consistent (HC) covariance estimator and various modifications of it. An informed Bayesian bootstrap provides the statistical framework.
Dynamic Batch Bayesian Optimization
Azimi, Javad; Fern, Xiaoli
2011-01-01
Bayesian optimization (BO) algorithms try to optimize an unknown function that is expensive to evaluate using minimum number of evaluations/experiments. Most of the proposed algorithms in BO are sequential, where only one experiment is selected at each iteration. This method can be time inefficient when each experiment takes a long time and more than one experiment can be ran concurrently. On the other hand, requesting a fix-sized batch of experiments at each iteration causes performance inefficiency in BO compared to the sequential policies. In this paper, we present an algorithm that asks a batch of experiments at each time step t where the batch size p_t is dynamically determined in each step. Our algorithm is based on the observation that the sequence of experiments selected by the sequential policy can sometimes be almost independent from each other. Our algorithm identifies such scenarios and request those experiments at the same time without degrading the performance. We evaluate our proposed method us...
Nonparametric Bayesian Classification
Coram, M A
2002-01-01
A Bayesian approach to the classification problem is proposed in which random partitions play a central role. It is argued that the partitioning approach has the capacity to take advantage of a variety of large-scale spatial structures, if they are present in the unknown regression function $f_0$. An idealized one-dimensional problem is considered in detail. The proposed nonparametric prior uses random split points to partition the unit interval into a random number of pieces. This prior is found to provide a consistent estimate of the regression function in the $\\L^p$ topology, for any $1 \\leq p < \\infty$, and for arbitrary measurable $f_0:[0,1] \\rightarrow [0,1]$. A Markov chain Monte Carlo (MCMC) implementation is outlined and analyzed. Simulation experiments are conducted to show that the proposed estimate compares favorably with a variety of conventional estimators. A striking resemblance between the posterior mean estimate and the bagged CART estimate is noted and discussed. For higher dimensions, a ...
A Bayesian variable selection procedure to rank overlapping gene sets
Directory of Open Access Journals (Sweden)
Skarman Axel
2012-05-01
Full Text Available Abstract Background Genome-wide expression profiling using microarrays or sequence-based technologies allows us to identify genes and genetic pathways whose expression patterns influence complex traits. Different methods to prioritize gene sets, such as the genes in a given molecular pathway, have been described. In many cases, these methods test one gene set at a time, and therefore do not consider overlaps among the pathways. Here, we present a Bayesian variable selection method to prioritize gene sets that overcomes this limitation by considering all gene sets simultaneously. We applied Bayesian variable selection to differential expression to prioritize the molecular and genetic pathways involved in the responses to Escherichia coli infection in Danish Holstein cows. Results We used a Bayesian variable selection method to prioritize Kyoto Encyclopedia of Genes and Genomes pathways. We used our data to study how the variable selection method was affected by overlaps among the pathways. In addition, we compared our approach to another that ignores the overlaps, and studied the differences in the prioritization. The variable selection method was robust to a change in prior probability and stable given a limited number of observations. Conclusions Bayesian variable selection is a useful way to prioritize gene sets while considering their overlaps. Ignoring the overlaps gives different and possibly misleading results. Additional procedures may be needed in cases of highly overlapping pathways that are hard to prioritize.
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...
Ultrafast vibrational energy relaxation of the water bridge.
Piatkowski, Lukasz; Wexler, Adam D; Fuchs, Elmar C; Schoenmaker, Hinco; Bakker, Huib J
2012-05-14
We report the energy relaxation of the OH stretch vibration of HDO molecules contained in an HDO:D(2)O water bridge using femtosecond mid-infrared pump-probe spectroscopy. We found that the vibrational lifetime is shorter (~630 ± 50 fs) than for HDO molecules in bulk HDO:D(2)O (~740 ± 40 fs). In contrast, the thermalization dynamics following the vibrational relaxation are much slower (~1.5 ± 0.4 ps) than in bulk HDO:D(2)O (~250 ± 90 fs). These differences in energy relaxation dynamics strongly indicate that the water bridge and bulk water differ on a molecular scale.
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
Lee, Chiho; Son, Hyewon; Park, Sungnam
2016-09-15
Hydrogen bonds (H-bonds) play an important role in determining the structures and dynamics of molecular systems. In this work, we investigated the effect of H-bonds on the vibrational population relaxation and orientational relaxation dynamics of HN3 and N3(-) in methanol (CH3OH) and N,N-dimethyl sulfoxide (DMSO) using polarization-controlled infrared pump-probe spectroscopy and quantum chemical calculations. Our detailed analysis of experimental and computational results reveals that both vibrational population relaxation and orientational relaxation dynamics of HN3 and N3(-) in CH3OH and DMSO are substantially dependent on the strength of the H-bonds between the probing solute and its surrounding solvent. Especially in the case of N3(-) in CH3OH, the vibrational population relaxation of N3(-) is found to occur by a direct intermolecular vibrational energy transfer to CH3OH due to large vibrational coupling strength. The orientational relaxation dynamics of HN3 and N3(-), which are well fit by a biexponential function, are analyzed by the wobbling-in-a-cone model and extended Debye-Stokes-Einstein equation. Depending on the intermolecular interactions, the slow overall orientational relaxation occurs under slip, stick, and superstick boundary conditions. For HN3 and N3(-) in CH3OH and DMSO, the vibrational population relaxation becomes faster but the orientational relaxation becomes slower as the H-bond strength is increased. Our current results imply that H-bonds have significant effects on the vibrational population relaxation and orientational relaxation dynamics of a small solute whose size is comparable to the size of the solvent. PMID:27537433
Attention in a bayesian framework
DEFF Research Database (Denmark)
Whiteley, Louise Emma; Sahani, Maneesh
2012-01-01
The behavioral phenomena of sensory attention are thought to reflect the allocation of a limited processing resource, but there is little consensus on the nature of the resource or why it should be limited. Here we argue that a fundamental bottleneck emerges naturally within Bayesian models...... of perception, and use this observation to frame a new computational account of the need for, and action of, attention - unifying diverse attentional phenomena in a way that goes beyond previous inferential, probabilistic and Bayesian models. Attentional effects are most evident in cluttered environments......, 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...
Probability biases as Bayesian inference
Directory of Open Access Journals (Sweden)
Andre; C. R. Martins
2006-11-01
Full Text Available In this article, I will show how several observed biases in human probabilistic reasoning can be partially explained as good heuristics for making inferences in an environment where probabilities have uncertainties associated to them. Previous results show that the weight functions and the observed violations of coalescing and stochastic dominance can be understood from a Bayesian point of view. We will review those results and see that Bayesian methods should also be used as part of the explanation behind other known biases. That means that, although the observed errors are still errors under the be understood as adaptations to the solution of real life problems. Heuristics that allow fast evaluations and mimic a Bayesian inference would be an evolutionary advantage, since they would give us an efficient way of making decisions. %XX In that sense, it should be no surprise that humans reason with % probability as it has been observed.
Bayesian Methods and Universal Darwinism
Campbell, John
2010-01-01
Bayesian methods since the time of Laplace have been understood by their practitioners as closely aligned to the scientific method. Indeed a recent champion of Bayesian methods, E. T. Jaynes, titled his textbook on the subject Probability Theory: the Logic of Science. Many philosophers of science including Karl Popper and Donald Campbell have interpreted the evolution of Science as a Darwinian process consisting of a 'copy with selective retention' algorithm abstracted from Darwin's theory of Natural Selection. Arguments are presented for an isomorphism between Bayesian Methods and Darwinian processes. Universal Darwinism, as the term has been developed by Richard Dawkins, Daniel Dennett and Susan Blackmore, is the collection of scientific theories which explain the creation and evolution of their subject matter as due to the operation of Darwinian processes. These subject matters span the fields of atomic physics, chemistry, biology and the social sciences. The principle of Maximum Entropy states that system...
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 ...
Tang, An-Min; Tang, Nian-Sheng
2015-02-28
We propose a semiparametric multivariate skew-normal joint model for multivariate longitudinal and multivariate survival data. One main feature of the posited model is that we relax the commonly used normality assumption for random effects and within-subject error by using a centered Dirichlet process prior to specify the random effects distribution and using a multivariate skew-normal distribution to specify the within-subject error distribution and model trajectory functions of longitudinal responses semiparametrically. A Bayesian approach is proposed to simultaneously obtain Bayesian estimates of unknown parameters, random effects and nonparametric functions by combining the Gibbs sampler and the Metropolis-Hastings algorithm. Particularly, a Bayesian local influence approach is developed to assess the effect of minor perturbations to within-subject measurement error and random effects. Several simulation studies and an example are presented to illustrate the proposed methodologies. PMID:25404574
Bayesian test and Kuhn's paradigm
Institute of Scientific and Technical Information of China (English)
Chen Xiaoping
2006-01-01
Kuhn's theory of paradigm reveals a pattern of scientific progress,in which normal science alternates with scientific revolution.But Kuhn underrated too much the function of scientific test in his pattern,because he focuses all his attention on the hypothetico-deductive schema instead of Bayesian schema.This paper employs Bayesian schema to re-examine Kuhn's theory of paradigm,to uncover its logical and rational components,and to illustrate the tensional structure of logic and belief,rationality and irrationality,in the process of scientific revolution.
Perception, illusions and Bayesian inference.
Nour, Matthew M; Nour, Joseph M
2015-01-01
Descriptive psychopathology makes a distinction between veridical perception and illusory perception. In both cases a perception is tied to a sensory stimulus, but in illusions the perception is of a false object. This article re-examines this distinction in light of new work in theoretical and computational neurobiology, which views all perception as a form of Bayesian statistical inference that combines sensory signals with prior expectations. Bayesian perceptual inference can solve the 'inverse optics' problem of veridical perception and provides a biologically plausible account of a number of illusory phenomena, suggesting that veridical and illusory perceptions are generated by precisely the same inferential mechanisms.
3D Bayesian contextual classifiers
DEFF Research Database (Denmark)
Larsen, Rasmus
2000-01-01
We extend a series of multivariate Bayesian 2-D contextual classifiers to 3-D by specifying a simultaneous Gaussian distribution for the feature vectors as well as a prior distribution of the class variables of a pixel and its 6 nearest 3-D neighbours.......We extend a series of multivariate Bayesian 2-D contextual classifiers to 3-D by specifying a simultaneous Gaussian distribution for the feature vectors as well as a prior distribution of the class variables of a pixel and its 6 nearest 3-D neighbours....
Bayesian methods for proteomic biomarker development
Directory of Open Access Journals (Sweden)
Belinda Hernández
2015-12-01
In this review we provide an introduction to Bayesian inference and demonstrate some of the advantages of using a Bayesian framework. We summarize how Bayesian methods have been used previously in proteomics and other areas of bioinformatics. Finally, we describe some popular and emerging Bayesian models from the statistical literature and provide a worked tutorial including code snippets to show how these methods may be applied for the evaluation of proteomic biomarkers.
Rupp, Wolf; Simon, Karl-Heinz; Bohnert, Michael
2009-01-01
Complete relaxation can be achieved by floating in a darkened, sound-proof relaxation tank filled with salinated water kept at body temperature. Under these conditions, meditation exercises up to self-hypnosis may lead to deep relaxation with physical and mental revitalization. A user manipulated his tank, presumably to completely cut off all optical and acoustic stimuli and accidentally also covered the ventilation hole. The man was found dead in his relaxation tank. The findings suggested lack of oxygen as the cause of death.
Bayesian variable order Markov models: Towards Bayesian predictive state representations
C. Dimitrakakis
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 st
Bayesian variable selection and data integration for biological regulatory networks
Jensen, Shane T; Chen, Guang; Stoeckert, Jr, Christian J.
2007-01-01
A substantial focus of research in molecular biology are gene regulatory networks: the set of transcription factors and target genes which control the involvement of different biological processes in living cells. Previous statistical approaches for identifying gene regulatory networks have used gene expression data, ChIP binding data or promoter sequence data, but each of these resources provides only partial information. We present a Bayesian hierarchical model that integrates all three dat...
Bayesian networks and food security - An introduction
Stein, A.
2004-01-01
This paper gives an introduction to Bayesian networks. Networks are defined and put into a Bayesian context. Directed acyclical graphs play a crucial role here. Two simple examples from food security are addressed. Possible uses of Bayesian networks for implementation and further use in decision sup
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…
A Bayesian Nonparametric Approach to Test Equating
Karabatsos, George; Walker, Stephen G.
2009-01-01
A Bayesian nonparametric model is introduced for score equating. It is applicable to all major equating designs, and has advantages over previous equating models. Unlike the previous models, the Bayesian model accounts for positive dependence between distributions of scores from two tests. The Bayesian model and the previous equating models are…
Coherent effects and relaxation processes in liquid potassium
International Nuclear Information System (INIS)
The coherent dynamic structure factor of liquid potassium has been obtained from inelastic neutron scattering data at temperatures of 340, 440 and 550 K. The parts of dispersion curves for collective excitations have been plotted and some of their characteristics have been analysed. Represented in relative units, our experimental points are in an agreement with the ones for liquid rubidium and cesium. The molecular memory effects are described within a framework of theoretical representations of a spatial dispersion for the relaxation parameter of non-Markovian process. It has been found that molecular memory effects are important for relaxation processes which are represented in inelastic both coherent and incoherent neutron scattering. (orig.)
Bayesian Classification of Image Structures
DEFF Research Database (Denmark)
Goswami, Dibyendu; Kalkan, Sinan; Krüger, Norbert
2009-01-01
In this paper, we describe work on Bayesian classi ers for distinguishing between homogeneous structures, textures, edges and junctions. We build semi-local classiers from hand-labeled images to distinguish between these four different kinds of structures based on the concept of intrinsic dimensi...
Bayesian Agglomerative Clustering with Coalescents
Teh, Yee Whye; Daumé III, Hal; Roy, Daniel
2009-01-01
We introduce a new Bayesian model for hierarchical clustering based on a prior over trees called Kingman's coalescent. We develop novel greedy and sequential Monte Carlo inferences which operate in a bottom-up agglomerative fashion. We show experimentally the superiority of our algorithms over others, and demonstrate our approach in document clustering and phylolinguistics.
Bayesian NL interpretation and learning
H. Zeevat
2011-01-01
Everyday natural language communication is normally successful, even though contemporary computational linguistics has shown that NL is characterised by very high degree of ambiguity and the results of stochastic methods are not good enough to explain the high success rate. Bayesian natural language
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 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...
Bayesian stable isotope mixing models
In this paper we review recent advances in Stable Isotope Mixing Models (SIMMs) and place them into an over-arching Bayesian statistical framework which allows for several useful extensions. SIMMs are used to quantify the proportional contributions of various sources to a mixtur...
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...
3-D contextual Bayesian classifiers
DEFF Research Database (Denmark)
Larsen, Rasmus
In this paper we will consider extensions of a series of Bayesian 2-D contextual classification pocedures proposed by Owen (1984) Hjort & Mohn (1984) and Welch & Salter (1971) and Haslett (1985) to 3 spatial dimensions. It is evident that compared to classical pixelwise classification further...
Bayesian image restoration, using configurations
DEFF Research Database (Denmark)
Thorarinsdottir, Thordis
configurations are expressed in terms of the mean normal measure of the random set. These probabilities are used as prior probabilities in a Bayesian image restoration approach. Estimation of the remaining parameters in the model is outlined for salt and pepper noise. The inference in the model is discussed...
Bayesian image restoration, using configurations
DEFF Research Database (Denmark)
Thorarinsdottir, Thordis Linda
2006-01-01
configurations are expressed in terms of the mean normal measure of the random set. These probabilities are used as prior probabilities in a Bayesian image restoration approach. Estimation of the remaining parameters in the model is outlined for the salt and pepper noise. The inference in the model is discussed...
Bayesian Analysis of Experimental Data
Directory of Open Access Journals (Sweden)
Lalmohan Bhar
2013-10-01
Full Text Available Analysis of experimental data from Bayesian point of view has been considered. Appropriate methodology has been developed for application into designed experiments. Normal-Gamma distribution has been considered for prior distribution. Developed methodology has been applied to real experimental data taken from long term fertilizer experiments.
Magnetic relaxation in anisotropic magnets
DEFF Research Database (Denmark)
Lindgård, Per-Anker
1971-01-01
The line shape and the kinematic and thermodynamic slowing down of the critical and paramagnetic relaxation in axially anisotropic materials are discussed. Kinematic slowing down occurs only in the longitudinal relaxation function. The thermodynamic slowing down occurs in either the transverse or...
Topics in Bayesian statistics and maximum entropy
International Nuclear Information System (INIS)
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...
Plug & Play object oriented Bayesian networks
DEFF Research Database (Denmark)
Bangsø, Olav; Flores, J.; Jensen, Finn Verner
2003-01-01
Object oriented Bayesian networks have proven themselves useful in recent years. The idea of applying an object oriented approach to Bayesian networks has extended their scope to larger domains that can be divided into autonomous but interrelated entities. Object oriented Bayesian networks have...... been shown to be quite suitable for dynamic domains as well. However, processing object oriented Bayesian networks in practice does not take advantage of their modular structure. Normally the object oriented Bayesian network is transformed into a Bayesian network and, inference is performed...... by constructing a junction tree from this network. In this paper we propose a method for translating directly from object oriented Bayesian networks to junction trees, avoiding the intermediate translation. We pursue two main purposes: firstly, to maintain the original structure organized in an instance tree...
Structural relaxation in viscous metallic liquids
Energy Technology Data Exchange (ETDEWEB)
Meyer, A. [National Inst. of Standards and Technology (BFRL), Gaithersburg, MD (United States)]|[Technische Univ. Muenchen, Muenchen (Germany); Wuttke, J.; Petry, W. [Technische Univ. Muenchen, Muenchen (Germany); Schober, H. [Institut Max von Laue - Paul Langevin (ILL), 38 - Grenoble (France); Randl, O.G. [Manufacture Michelin, Clermont-Ferrand (France)
1999-11-01
Recently, metallic alloys have been found that exhibit extremely large viscosities in the liquid state. These liquids can be quenched into bulk metallic glasses at relatively modest cooling rates. In contrast to simple metals the structural relaxation of these systems show a two step decay in the liquid state. This behaviour has long been known for molecular or ionic glass formers in their under-cooled liquid state. Applying an analysis previously used for the glass formers (mode-coupling theory) a full quantitative description of the neutron data is obtained for these metallic liquids. (authors) 3 refs., 2 figs.
Flexible Bayesian Nonparametric Priors and Bayesian Computational Methods
Zhu, Weixuan
2016-01-01
The definition of vectors of dependent random probability measures is a topic of interest in Bayesian nonparametrics. They represent dependent nonparametric prior distributions that are useful for modelling observables for which specific covariate values are known. Our first contribution is the introduction of novel multivariate vectors of two-parameter Poisson-Dirichlet process. The dependence is induced by applying a L´evy copula to the marginal L´evy intensities. Our attenti...
Bayesian versus 'plain-vanilla Bayesian' multitarget statistics
Mahler, Ronald P. S.
2004-08-01
Finite-set statistics (FISST) is a direct generalization of single-sensor, single-target Bayes statistics to the multisensor-multitarget realm, based on random set theory. Various aspects of FISST are being investigated by several research teams around the world. In recent years, however, a few partisans have claimed that a "plain-vanilla Bayesian approach" suffices as down-to-earth, "straightforward," and general "first principles" for multitarget problems. Therefore, FISST is mere mathematical "obfuscation." In this and a companion paper I demonstrate the speciousness of these claims. In this paper I summarize general Bayes statistics, what is required to use it in multisensor-multitarget problems, and why FISST is necessary to make it practical. Then I demonstrate that the "plain-vanilla Bayesian approach" is so heedlessly formulated that it is erroneous, not even Bayesian denigrates FISST concepts while unwittingly assuming them, and has resulted in a succession of algorithms afflicted by inherent -- but less than candidly acknowledged -- computational "logjams."
Can Black Hole Relax Unitarily?
Solodukhin, S N
2004-01-01
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.
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.
Variational formulation of relaxed and multi-region relaxed magnetohydrodynamics
Dewar, Robert L.; Yoshida, Zensho; Bhattacharjee, Amitava; Hudson, Stuart R.
2015-01-01
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 global magnetic fluxes and helicity. A Lagrangian variational principle is presented that ...
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 approach to rough set
Marwala, Tshilidzi
2007-01-01
This paper proposes an approach to training rough set models using Bayesian framework trained using Markov Chain Monte Carlo (MCMC) method. The prior probabilities are constructed from the prior knowledge that good rough set models have fewer rules. Markov Chain Monte Carlo sampling is conducted through sampling in the rough set granule space and Metropolis algorithm is used as an acceptance criteria. The proposed method is tested to estimate the risk of HIV given demographic data. The results obtained shows that the proposed approach is able to achieve an average accuracy of 58% with the accuracy varying up to 66%. In addition the Bayesian rough set give the probabilities of the estimated HIV status as well as the linguistic rules describing how the demographic parameters drive the risk of HIV.
Bayesian priors for transiting planets
Kipping, David M
2016-01-01
As astronomers push towards discovering ever-smaller transiting planets, it is increasingly common to deal with low signal-to-noise ratio (SNR) events, where the choice of priors plays an influential role in Bayesian inference. In the analysis of exoplanet data, the selection of priors is often treated as a nuisance, with observers typically defaulting to uninformative distributions. Such treatments miss a key strength of the Bayesian framework, especially in the low SNR regime, where even weak a priori information is valuable. When estimating the parameters of a low-SNR transit, two key pieces of information are known: (i) the planet has the correct geometric alignment to transit and (ii) the transit event exhibits sufficient signal-to-noise to have been detected. These represent two forms of observational bias. Accordingly, when fitting transits, the model parameter priors should not follow the intrinsic distributions of said terms, but rather those of both the intrinsic distributions and the observational ...
Bayesian Source Separation and Localization
Knuth, K H
1998-01-01
The problem of mixed signals occurs in many different contexts; one of the most familiar being acoustics. The forward problem in acoustics consists of finding the sound pressure levels at various detectors resulting from sound signals emanating from the active acoustic sources. The inverse problem consists of using the sound recorded by the detectors to separate the signals and recover the original source waveforms. In general, the inverse problem is unsolvable without additional information. This general problem is called source separation, and several techniques have been developed that utilize maximum entropy, minimum mutual information, and maximum likelihood. In previous work, it has been demonstrated that these techniques can be recast in a Bayesian framework. This paper demonstrates the power of the Bayesian approach, which provides a natural means for incorporating prior information into a source model. An algorithm is developed that utilizes information regarding both the statistics of the amplitudes...
Bayesian Inference for Radio Observations
Lochner, Michelle; Zwart, Jonathan T L; Smirnov, Oleg; Bassett, Bruce A; Oozeer, Nadeem; Kunz, Martin
2015-01-01
(Abridged) New telescopes like the Square Kilometre Array (SKA) will push into a new sensitivity regime and expose systematics, such as direction-dependent effects, that could previously be ignored. Current methods for handling such systematics rely on alternating best estimates of instrumental calibration and models of the underlying sky, which can lead to inaccurate uncertainty estimates and biased results because such methods ignore any correlations between parameters. These deconvolution algorithms produce a single image that is assumed to be a true representation of the sky, when in fact it is just one realisation of an infinite ensemble of images compatible with the noise in the data. In contrast, here we report a Bayesian formalism that simultaneously infers both systematics and science. Our technique, Bayesian Inference for Radio Observations (BIRO), determines all parameters directly from the raw data, bypassing image-making entirely, by sampling from the joint posterior probability distribution. Thi...
A Bayesian Nonparametric IRT Model
Karabatsos, George
2015-01-01
This paper introduces a flexible Bayesian nonparametric Item Response Theory (IRT) model, which applies to dichotomous or polytomous item responses, and which can apply to either unidimensional or multidimensional scaling. This is an infinite-mixture IRT model, with person ability and item difficulty parameters, and with a random intercept parameter that is assigned a mixing distribution, with mixing weights a probit function of other person and item parameters. As a result of its flexibility...
Elements of Bayesian experimental design
Energy Technology Data Exchange (ETDEWEB)
Sivia, D.S. [Rutherford Appleton Lab., Oxon (United Kingdom)
1997-09-01
We consider some elements of the Bayesian approach that are important for optimal experimental design. While the underlying principles used are very general, and are explained in detail in a recent tutorial text, they are applied here to the specific case of characterising the inferential value of different resolution peakshapes. This particular issue was considered earlier by Silver, Sivia and Pynn (1989, 1990a, 1990b), and the following presentation confirms and extends the conclusions of their analysis.
Bayesian kinematic earthquake source models
Minson, S. E.; Simons, M.; Beck, J. L.; Genrich, J. F.; Galetzka, J. E.; Chowdhury, F.; Owen, S. E.; Webb, F.; Comte, D.; Glass, B.; Leiva, C.; Ortega, F. H.
2009-12-01
Most coseismic, postseismic, and interseismic slip models are based on highly regularized optimizations which yield one solution which satisfies the data given a particular set of regularizing constraints. This regularization hampers our ability to answer basic questions such as whether seismic and aseismic slip overlap or instead rupture separate portions of the fault zone. We present a Bayesian methodology for generating kinematic earthquake source models with a focus on large subduction zone earthquakes. Unlike classical optimization approaches, Bayesian techniques sample the ensemble of all acceptable models presented as an a posteriori probability density function (PDF), and thus we can explore the entire solution space to determine, for example, which model parameters are well determined and which are not, or what is the likelihood that two slip distributions overlap in space. Bayesian sampling also has the advantage that all a priori knowledge of the source process can be used to mold the a posteriori ensemble of models. Although very powerful, Bayesian methods have up to now been of limited use in geophysical modeling because they are only computationally feasible for problems with a small number of free parameters due to what is called the "curse of dimensionality." However, our methodology can successfully sample solution spaces of many hundreds of parameters, which is sufficient to produce finite fault kinematic earthquake models. Our algorithm is a modification of the tempered Markov chain Monte Carlo (tempered MCMC or TMCMC) method. In our algorithm, we sample a "tempered" a posteriori PDF using many MCMC simulations running in parallel and evolutionary computation in which models which fit the data poorly are preferentially eliminated in favor of models which better predict the data. We present results for both synthetic test problems as well as for the 2007 Mw 7.8 Tocopilla, Chile earthquake, the latter of which is constrained by InSAR, local high
Bayesian Stable Isotope Mixing Models
Parnell, Andrew C.; Phillips, Donald L.; Bearhop, Stuart; Semmens, Brice X.; Ward, Eric J.; Moore, Jonathan W.; Andrew L Jackson; Inger, Richard
2012-01-01
In this paper we review recent advances in Stable Isotope Mixing Models (SIMMs) and place them into an over-arching Bayesian statistical framework which allows for several useful extensions. SIMMs are used to quantify the proportional contributions of various sources to a mixture. The most widely used application is quantifying the diet of organisms based on the food sources they have been observed to consume. At the centre of the multivariate statistical model we propose is a compositional m...
Bayesian Network--Response Regression
WANG, LU; Durante, Daniele; Dunson, David B.
2016-01-01
There is an increasing interest in learning how human brain networks vary with continuous traits (e.g., personality, cognitive abilities, neurological disorders), but flexible procedures to accomplish this goal are limited. We develop a Bayesian semiparametric model, which combines low-rank factorizations and Gaussian process priors to allow flexible shifts of the conditional expectation for a network-valued random variable across the feature space, while including subject-specific random eff...
Bayesian segmentation of hyperspectral images
Mohammadpour, Adel; Mohammad-Djafari, Ali
2007-01-01
In this paper we consider the problem of joint segmentation of hyperspectral images in the Bayesian framework. The proposed approach is based on a Hidden Markov Modeling (HMM) of the images with common segmentation, or equivalently with common hidden classification label variables which is modeled by a Potts Markov Random Field. We introduce an appropriate Markov Chain Monte Carlo (MCMC) algorithm to implement the method and show some simulation results.
Bayesian segmentation of hyperspectral images
Mohammadpour, Adel; Féron, Olivier; Mohammad-Djafari, Ali
2004-11-01
In this paper we consider the problem of joint segmentation of hyperspectral images in the Bayesian framework. The proposed approach is based on a Hidden Markov Modeling (HMM) of the images with common segmentation, or equivalently with common hidden classification label variables which is modeled by a Potts Markov Random Field. We introduce an appropriate Markov Chain Monte Carlo (MCMC) algorithm to implement the method and show some simulation results.
Bayesian analysis of contingency tables
Gómez Villegas, Miguel A.; González Pérez, Beatriz
2005-01-01
The display of the data by means of contingency tables is used in different approaches to statistical inference, for example, to broach the test of homogeneity of independent multinomial distributions. We develop a Bayesian procedure to test simple null hypotheses versus bilateral alternatives in contingency tables. Given independent samples of two binomial distributions and taking a mixed prior distribution, we calculate the posterior probability that the proportion of successes in the first...
Bayesian estimation of turbulent motion
Héas, P.; Herzet, C.; Mémin, E.; Heitz, D.; P. D. Mininni
2013-01-01
International audience Based on physical laws describing the multi-scale structure of turbulent flows, this article proposes a regularizer for fluid motion estimation from an image sequence. Regularization is achieved by imposing some scale invariance property between histograms of motion increments computed at different scales. By reformulating this problem from a Bayesian perspective, an algorithm is proposed to jointly estimate motion, regularization hyper-parameters, and to select the ...
Bayesian Kernel Mixtures for Counts
Canale, Antonio; David B Dunson
2011-01-01
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 deviatio...
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
Bayesian second law of thermodynamics.
Bartolotta, Anthony; Carroll, Sean M; Leichenauer, Stefan; Pollack, Jason
2016-08-01
We derive a generalization of the second law of thermodynamics that uses Bayesian updates to explicitly incorporate the effects of a measurement of a system at some point in its evolution. By allowing an experimenter's knowledge to be updated by the measurement process, this formulation resolves a tension between the fact that the entropy of a statistical system can sometimes fluctuate downward and the information-theoretic idea that knowledge of a stochastically evolving system degrades over time. The Bayesian second law can be written as ΔH(ρ_{m},ρ)+〈Q〉_{F|m}≥0, where ΔH(ρ_{m},ρ) is the change in the cross entropy between the original phase-space probability distribution ρ and the measurement-updated distribution ρ_{m} and 〈Q〉_{F|m} is the expectation value of a generalized heat flow out of the system. We also derive refined versions of the second law that bound the entropy increase from below by a non-negative number, as well as Bayesian versions of integral fluctuation theorems. We demonstrate the formalism using simple analytical and numerical examples. PMID:27627241
Bayesian second law of thermodynamics
Bartolotta, Anthony; Carroll, Sean M.; Leichenauer, Stefan; Pollack, Jason
2016-08-01
We derive a generalization of the second law of thermodynamics that uses Bayesian updates to explicitly incorporate the effects of a measurement of a system at some point in its evolution. By allowing an experimenter's knowledge to be updated by the measurement process, this formulation resolves a tension between the fact that the entropy of a statistical system can sometimes fluctuate downward and the information-theoretic idea that knowledge of a stochastically evolving system degrades over time. The Bayesian second law can be written as Δ H (ρm,ρ ) + F |m≥0 , where Δ H (ρm,ρ ) is the change in the cross entropy between the original phase-space probability distribution ρ and the measurement-updated distribution ρm and F |m is the expectation value of a generalized heat flow out of the system. We also derive refined versions of the second law that bound the entropy increase from below by a non-negative number, as well as Bayesian versions of integral fluctuation theorems. We demonstrate the formalism using simple analytical and numerical examples.
An Exact Relaxation of Clustering
DEFF Research Database (Denmark)
Mørup, Morten; Hansen, Lars Kai
2009-01-01
of clustering problems such as the K-means objective and pairwise clustering as well as graph partition problems, e.g., for community detection in complex networks. In particular we show that a relaxation to the simplex can be given for which the extreme solutions are stable hard assignment solutions and vice......Continuous relaxation of hard assignment clustering problems can lead to better solutions than greedy iterative refinement algorithms. However, the validity of existing relaxations is contingent on problem specific fuzzy parameters that quantify the level of similarity between the original...... versa. Based on the new relaxation we derive the SR-clustering algorithm that has the same complexity as traditional greedy iterative refinement algorithms but leading to significantly better partitions of the data. A Matlab implementation of the SR-clustering algorithm is available for download....
Polarization and relaxation of radon
Tardiff, E R; Chupp, T E; Gulyuz, K; Lefferts, R S; Lorenzon, W; Nuss-Warren, S R; Pearson, M R; Pietralla, N; Rainovski, G; Sell, J F; Sprouse, G D
2006-01-01
Investigations of the polarization and relaxation of $^{209}$Rn by spin exchange with laser optically pumped rubidium are reported. On the order of one million atoms per shot were collected in coated and uncoated glass cells. Gamma-ray anisotropies were measured as a signal of the alignment (second order moment of the polarization) resulting from the combination of polarization and quadrupole relaxation at the cell walls. The temperature dependence over the range 130$^\\circ$C to 220$^\\circ$C shows the anisotropies increasing with increasing temperature as the ratio of the spin exchange polarization rate to the wall relaxation rate increases faster than the rubidium polarization decreases. Polarization relaxation rates for coated and uncoated cells are presented. In addition, improved limits on the multipole mixing ratios of some of the main gamma-ray transitions have been extracted. These results are promising for electric dipole moment measurements of octupole-deformed $^{223}$Rn and other isotopes, provided...
Shape Dependence of Low-Temperature Magnetic Relaxation of Mn12Ac
Institute of Scientific and Technical Information of China (English)
LIU Hai-Qing; SU Shao-Kui; JING Xiu-nian; LIU Ying; LI Yan-rong; HE Lun-Hua; GE Pei-Wen; YAN Qi-Wei; WANG Yun-Ping
2008-01-01
We report the discovery that the low-temperature magnetic relaxation in Mn,12 Ac single crystals strongly depends on the shape of the samples. The relaxation time exhibits a minimum at the phase transition point between ferromagnetic and antiferromagnetic phases. The shape dependence is attributed to the dipolar interaction between molecular magnets.
Relaxation Time of the Particle Beam with an Anisotropic Velocity Distribution
Directory of Open Access Journals (Sweden)
V.P. Vechirka
2012-11-01
Full Text Available The computer experiment for study of the relaxation time of the beam particles with an anisotropic velocity distribution is performed by the molecular dynamics. Obtained results agree with the characteristic times of thermal relaxation in plasma for the electronic coolers in modern storage rings.
Relaxation of a Simulated Lipid Bilayer Vesicle Compressed by an AFM
Barlow, Ben M; Joos, Béla
2016-01-01
Using Coarse-Grained Molecular Dynamics simulations, we study the relaxation of bilayer vesicles, uniaxially compressed by an Atomic Force Microscope (AFM) cantilever. The relaxation time exhibits a strong force-dependence. Force-compression curves are very similar to recent experiments wherein giant unilamellar vesicles were compressed in a nearly identical manner.
Reduced complexity turbo equalization using a dynamic Bayesian network
Myburgh, Hermanus C.; Olivier, Jan C.; van Zyl, Augustinus J.
2012-12-01
It is proposed that a dynamic Bayesian network (DBN) is used to perform turbo equalization in a system transmitting information over a Rayleigh fading multipath channel. The DBN turbo equalizer (DBN-TE) is modeled on a single directed acyclic graph by relaxing the Markov assumption and allowing weak connections to past and future states. Its complexity is exponential in encoder constraint length and approximately linear in the channel memory length. Results show that the performance of the DBN-TE closely matches that of a traditional turbo equalizer that uses a maximum a posteriori equalizer and decoder pair. The DBN-TE achieves full convergence and near-optimal performance after small number of iterations.
Archiving the Relaxed Consistency Web
Xie, Zhiwu; Van de Sompel, Herbert; Liu, Jinyang; Van Reenen, Johann; Jordan, Ramiro
2013-01-01
The historical, cultural, and intellectual importance of archiving the web has been widely recognized. Today, all countries with high Internet penetration rate have established high-profile archiving initiatives to crawl and archive the fast-disappearing web content for long-term use. As web technologies evolve, established web archiving techniques face challenges. This paper focuses on the potential impact of the relaxed consistency web design on crawler driven web archiving. Relaxed consist...
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.
Entropy relaxation of ASDEX plasmas
International Nuclear Information System (INIS)
In tokamak discharges with improved ohmic confinement (IOC) in ASDEX a transition is observed from flat density profiles towards more peaked ones, while the normalized temperature profile is preserved. For this behaviour of the radial profiles it is shown that the entropy of the plasma increases during the IOC phase. Hence IOC and entropy relaxation are closely related. If the IOC phase is long enough, one finds stationary plasma states, which are compared with the relaxed state described in theory. (orig.)
Difference and similarity of dielectric relaxation processes among polyols
Minoguchi, Ayumi; Kitai, Kei; Nozaki, Ryusuke
2003-09-01
Complex permittivity measurements were performed on sorbitol, xylitol, and sorbitol-xylitol mixture in the supercooled liquid state in an extremely wide frequency range from 10 μHz to 500 MHz at temperatures near and above the glass transition temperature. We determined detailed behavior of the relaxation parameters such as relaxation frequency and broadening against temperature not only for the α process but also for the β process above the glass transition temperature, to the best of our knowledge, for the first time. Since supercooled liquids are in the quasi-equilibrium state, the behavior of all the relaxation parameters for the β process can be compared among the polyols as well as those for the α process. The relaxation frequencies of the α processes follow the Vogel-Fulcher-Tammann manner and the loci in the Arrhenius diagram are different corresponding to the difference of the glass transition temperatures. On the other hand, the relaxation frequencies of the β processes, which are often called as the Johari-Goldstein processes, follow the Arrhenius-type temperature dependence. The relaxation parameters for the β process are quite similar among the polyols at temperatures below the αβ merging temperature, TM. However, they show anomalous behavior near TM, which depends on the molecular size of materials. These results suggest that the origin of the β process is essentially the same among the polyols.
Nuclear magnetic relaxation of liquids in porous media
International Nuclear Information System (INIS)
Nuclear magnetic relaxation is useful for probing physical and chemical properties of liquids in porous media. Examples are given on high surface area porous materials including calibrated porous silica glasses, granular packings, plaster pastes, cement-based materials and natural porous materials, such as sandstone and carbonate rocks. Here, we outline our recent NMR relaxation work for these very different porous materials. For instance, low field NMR relaxation of water in calibrated granular packings leads to striking different pore-size dependencies of the relaxation times T1 and T2 when changing the amount of surface paramagnetic impurities. This allows separation of the diffusion and surface limited regimes of relaxation in these macroporous media. The magnetic field dependence of the nuclear spin-lattice relaxation rate 1/T1(ω0) is also a rich source of dynamical information for characterizing the molecular dynamics of liquids in porous media. This allows a continuous characterization of the evolving microstructure of various cementitious materials. Our recent applications of two-dimensional (2D) T1-T2 and T2-z-store-T2 correlation experiments have evidenced the water exchange in connected micropores of cement pastes. The direct probing of water adsorption time on a solid surface gives access to an original characterization of the surface nano-wettability of porous plaster pastes. We show that such a parameter depends directly on the physical chemistry of the pore surfaces. Lastly, we outline our recent measurements of wettability in oil/brine/reservoir carbonate rocks.
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...
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 SiO
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...
Wang, Xianlong; Mallory, Frank B.; Mallory, Clelia W.; Odhner, Hosanna R.; Beckmann, Peter A.
2014-05-01
We report ab initio density functional theory electronic structure calculations of rotational barriers for t-butyl groups and their constituent methyl groups both in the isolated molecules and in central molecules in clusters built from the X-ray structure in four t-butyl aromatic compounds. The X-ray structures have been reported previously. We also report and interpret the temperature dependence of the solid state 1H nuclear magnetic resonance spin-lattice relaxation rate at 8.50, 22.5, and 53.0 MHz in one of the four compounds. Such experiments for the other three have been reported previously. We compare the computed barriers for methyl group and t-butyl group rotation in a central target molecule in the cluster with the activation energies determined from fitting the 1H NMR spin-lattice relaxation data. We formulate a dynamical model for the superposition of t-butyl group rotation and the rotation of the t-butyl group's constituent methyl groups. The four compounds are 2,7-di-t-butylpyrene, 1,4-di-t-butylbenzene, 2,6-di-t-butylnaphthalene, and 3-t-butylchrysene. We comment on the unusual ground state orientation of the t-butyl groups in the crystal of the pyrene and we comment on the unusually high rotational barrier of these t-butyl groups.
Energy Technology Data Exchange (ETDEWEB)
Wang, Xianlong, E-mail: WangXianlong@uestc.edu.cn, E-mail: pbeckman@brynmawr.edu [Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, 4 North Jianshe Rd., 2nd Section, Chengdu 610054 (China); Mallory, Frank B. [Department of Chemistry, Bryn Mawr College, 101 North Merion Ave., Bryn Mawr, Pennsylvania 19010-2899 (United States); Mallory, Clelia W. [Department of Chemistry, Bryn Mawr College, 101 North Merion Ave., Bryn Mawr, Pennsylvania 19010-2899 (United States); Department of Chemistry, University of Pennsylvania, Philadelphia, Pennsylvania 19104-6323 (United States); Odhner, Hosanna R.; Beckmann, Peter A., E-mail: WangXianlong@uestc.edu.cn, E-mail: pbeckman@brynmawr.edu [Department of Physics, Bryn Mawr College, 101 North Merion Ave., Bryn Mawr, Pennsylvania 19010-2899 (United States)
2014-05-21
We report ab initio density functional theory electronic structure calculations of rotational barriers for t-butyl groups and their constituent methyl groups both in the isolated molecules and in central molecules in clusters built from the X-ray structure in four t-butyl aromatic compounds. The X-ray structures have been reported previously. We also report and interpret the temperature dependence of the solid state {sup 1}H nuclear magnetic resonance spin-lattice relaxation rate at 8.50, 22.5, and 53.0 MHz in one of the four compounds. Such experiments for the other three have been reported previously. We compare the computed barriers for methyl group and t-butyl group rotation in a central target molecule in the cluster with the activation energies determined from fitting the {sup 1}H NMR spin-lattice relaxation data. We formulate a dynamical model for the superposition of t-butyl group rotation and the rotation of the t-butyl group's constituent methyl groups. The four compounds are 2,7-di-t-butylpyrene, 1,4-di-t-butylbenzene, 2,6-di-t-butylnaphthalene, and 3-t-butylchrysene. We comment on the unusual ground state orientation of the t-butyl groups in the crystal of the pyrene and we comment on the unusually high rotational barrier of these t-butyl groups.
An Adaptively Accelerated Bayesian Deblurring Method with Entropy Prior
Directory of Open Access Journals (Sweden)
Yong-Hoon Kim
2008-05-01
Full Text Available The development of an efficient adaptively accelerated iterative deblurring algorithm based on Bayesian statistical concept has been reported. Entropy of an image has been used as a Ã¢Â€ÂœpriorÃ¢Â€Â distribution and instead of additive form, used in conventional acceleration methods an exponent form of relaxation constant has been used for acceleration. Thus the proposed method is called hereafter as adaptively accelerated maximum a posteriori with entropy prior (AAMAPE. Based on empirical observations in different experiments, the exponent is computed adaptively using first-order derivatives of the deblurred image from previous two iterations. This exponent improves speed of the AAMAPE method in early stages and ensures stability at later stages of iteration. In AAMAPE method, we also consider the constraint of the nonnegativity and flux conservation. The paper discusses the fundamental idea of the Bayesian image deblurring with the use of entropy as prior, and the analytical analysis of superresolution and the noise amplification characteristics of the proposed method. The experimental results show that the proposed AAMAPE method gives lower RMSE and higher SNR in 44% lesser iterations as compared to nonaccelerated maximum a posteriori with entropy prior (MAPE method. Moreover, AAMAPE followed by wavelet wiener filtering gives better result than the state-of-the-art methods.
DPpackage: Bayesian Semi- and Nonparametric Modeling in R
Directory of Open Access Journals (Sweden)
Alejandro Jara
2011-04-01
Full Text Available Data analysis sometimes requires the relaxation of parametric assumptions in order to gain modeling flexibility and robustness against mis-specification of the probability model. In the Bayesian context, this is accomplished by placing a prior distribution on a function space, such as the space of all probability distributions or the space of all regression functions. Unfortunately, posterior distributions ranging over function spaces are highly complex and hence sampling methods play a key role. This paper provides an introduction to a simple, yet comprehensive, set of programs for the implementation of some Bayesian nonparametric and semiparametric models in R, DPpackage. Currently, DPpackage includes models for marginal and conditional density estimation, receiver operating characteristic curve analysis, interval-censored data, binary regression data, item response data, longitudinal and clustered data using generalized linear mixed models, and regression data using generalized additive models. The package also contains functions to compute pseudo-Bayes factors for model comparison and for eliciting the precision parameter of the Dirichlet process prior, and a general purpose Metropolis sampling algorithm. To maximize computational efficiency, the actual sampling for each model is carried out using compiled C, C++ or Fortran code.
Variational bayesian method of estimating variance components.
Arakawa, Aisaku; Taniguchi, Masaaki; Hayashi, Takeshi; Mikawa, Satoshi
2016-07-01
We developed a Bayesian analysis approach by using a variational inference method, a so-called variational Bayesian method, to determine the posterior distributions of variance components. This variational Bayesian method and an alternative Bayesian method using Gibbs sampling were compared in estimating genetic and residual variance components from both simulated data and publically available real pig data. In the simulated data set, we observed strong bias toward overestimation of genetic variance for the variational Bayesian method in the case of low heritability and low population size, and less bias was detected with larger population sizes in both methods examined. The differences in the estimates of variance components between the variational Bayesian and the Gibbs sampling were not found in the real pig data. However, the posterior distributions of the variance components obtained with the variational Bayesian method had shorter tails than those obtained with the Gibbs sampling. Consequently, the posterior standard deviations of the genetic and residual variances of the variational Bayesian method were lower than those of the method using Gibbs sampling. The computing time required was much shorter with the variational Bayesian method than with the method using Gibbs sampling.
SYNTHESIZED EXPECTED BAYESIAN METHOD OF PARAMETRIC ESTIMATE
Institute of Scientific and Technical Information of China (English)
Ming HAN; Yuanyao DING
2004-01-01
This paper develops a new method of parametric estimate, which is named as "synthesized expected Bayesian method". When samples of products are tested and no failure events occur, thedefinition of expected Bayesian estimate is introduced and the estimates of failure probability and failure rate are provided. After some failure information is introduced by making an extra-test, a synthesized expected Bayesian method is defined and used to estimate failure probability, failure rateand some other parameters in exponential distribution and Weibull distribution of populations. Finally,calculations are performed according to practical problems, which show that the synthesized expected Bayesian method is feasible and easy to operate.
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....... 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 in...
Bayesian Methods and Universal Darwinism
Campbell, John
2009-12-01
Bayesian methods since the time of Laplace have been understood by their practitioners as closely aligned to the scientific method. Indeed a recent Champion of Bayesian methods, E. T. Jaynes, titled his textbook on the subject Probability Theory: the Logic of Science. Many philosophers of science including Karl Popper and Donald Campbell have interpreted the evolution of Science as a Darwinian process consisting of a `copy with selective retention' algorithm abstracted from Darwin's theory of Natural Selection. Arguments are presented for an isomorphism between Bayesian Methods and Darwinian processes. Universal Darwinism, as the term has been developed by Richard Dawkins, Daniel Dennett and Susan Blackmore, is the collection of scientific theories which explain the creation and evolution of their subject matter as due to the Operation of Darwinian processes. These subject matters span the fields of atomic physics, chemistry, biology and the social sciences. The principle of Maximum Entropy states that Systems will evolve to states of highest entropy subject to the constraints of scientific law. This principle may be inverted to provide illumination as to the nature of scientific law. Our best cosmological theories suggest the universe contained much less complexity during the period shortly after the Big Bang than it does at present. The scientific subject matter of atomic physics, chemistry, biology and the social sciences has been created since that time. An explanation is proposed for the existence of this subject matter as due to the evolution of constraints in the form of adaptations imposed on Maximum Entropy. It is argued these adaptations were discovered and instantiated through the Operations of a succession of Darwinian processes.
Phase transitions in semidefinite relaxations.
Javanmard, Adel; Montanari, Andrea; Ricci-Tersenghi, Federico
2016-04-19
Statistical inference problems arising within signal processing, data mining, and machine learning naturally give rise to hard combinatorial optimization problems. These problems become intractable when the dimensionality of the data is large, as is often the case for modern datasets. A popular idea is to construct convex relaxations of these combinatorial problems, which can be solved efficiently for large-scale datasets. Semidefinite programming (SDP) relaxations are among the most powerful methods in this family and are surprisingly well suited for a broad range of problems where data take the form of matrices or graphs. It has been observed several times that when the statistical noise is small enough, SDP relaxations correctly detect the underlying combinatorial structures. In this paper we develop asymptotic predictions for several detection thresholds, as well as for the estimation error above these thresholds. We study some classical SDP relaxations for statistical problems motivated by graph synchronization and community detection in networks. We map these optimization problems to statistical mechanics models with vector spins and use nonrigorous techniques from statistical mechanics to characterize the corresponding phase transitions. Our results clarify the effectiveness of SDP relaxations in solving high-dimensional statistical problems. PMID:27001856
Numeracy, frequency, and Bayesian reasoning
Directory of Open Access Journals (Sweden)
Gretchen B. Chapman
2009-02-01
Full Text Available Previous research has demonstrated that Bayesian reasoning performance is improved if uncertainty information is presented as natural frequencies rather than single-event probabilities. A questionnaire study of 342 college students replicated this effect but also found that the performance-boosting benefits of the natural frequency presentation occurred primarily for participants who scored high in numeracy. This finding suggests that even comprehension and manipulation of natural frequencies requires a certain threshold of numeracy abilities, and that the beneficial effects of natural frequency presentation may not be as general as previously believed.
Bayesian Query-Focused Summarization
Daumé, Hal
2009-01-01
We present BayeSum (for ``Bayesian summarization''), a model for sentence extraction in query-focused summarization. BayeSum leverages the common case in which multiple documents are relevant to a single query. Using these documents as reinforcement for query terms, BayeSum is not afflicted by the paucity of information in short queries. We show that approximate inference in BayeSum is possible on large data sets and results in a state-of-the-art summarization system. Furthermore, we show how BayeSum can be understood as a justified query expansion technique in the language modeling for IR framework.
Bayesian Sampling using Condition Indicators
DEFF Research Database (Denmark)
Faber, Michael H.; Sørensen, John Dalsgaard
2002-01-01
The problem of control quality of components is considered for the special case where the acceptable failure rate is low, the test costs are high and where it may be difficult or impossible to test the condition of interest directly. Based on the classical control theory and the concept...... of condition indicators introduced by Benjamin and Cornell (1970) a Bayesian approach to quality control is formulated. The formulation is then extended to the case where the quality control is based on sampling of indirect information about the condition of the components, i.e. condition indicators...
Dielectric relaxation of long-chain glass-forming monohydroxy alcohols
Gao, Yanqin; Tu, Wenkang; Chen, Zeming; Tian, Yongjun; Liu, Riping; Wang, Li-Min
2013-10-01
The dielectric relaxation of two long-chain glass forming monohydroxy alcohols, 2-butyl-1-octanol and 2-hexyl-1-decanol, is studied at low temperature. Remarkable broadening from the pure Debye relaxation is identified for the slowest dynamics, differing from the dielectric spectra of short-chain alcohols. The broadening of the Debye-like relaxation in the two liquids develops as temperature increases, and the approaching of the Debye-like and structural relaxation widths is shown. Similar results are observed in the dielectric spectra of dilute 2-ethyl-1-hexanol in either 2-hexyl-1-decanol or squalane. The results of the liquids and mixtures reveal a correlation between the broadening and the Debye-like relaxation strength. Molecular associations in monohydroxy alcohols are discussed with the modification of the Debye relaxation.
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 analysis of exoplanet and binary orbits
Schulze-Hartung, Tim; Launhardt, Ralf; Henning, Thomas
2012-01-01
We introduce BASE (Bayesian astrometric and spectroscopic exoplanet detection and characterisation tool), a novel program for the combined or separate Bayesian analysis of astrometric and radial-velocity measurements of potential exoplanet hosts and binary stars. The capabilities of BASE are demonstrated using all publicly available data of the binary Mizar A.
Bayesian credible interval construction for Poisson statistics
Institute of Scientific and Technical Information of China (English)
ZHU Yong-Sheng
2008-01-01
The construction of the Bayesian credible (confidence) interval for a Poisson observable including both the signal and background with and without systematic uncertainties is presented.Introducing the conditional probability satisfying the requirement of the background not larger than the observed events to construct the Bayesian credible interval is also discussed.A Fortran routine,BPOCI,has been developed to implement the calculation.
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…
Advances in Bayesian Modeling in Educational Research
Levy, Roy
2016-01-01
In this article, I provide a conceptually oriented overview of Bayesian approaches to statistical inference and contrast them with frequentist approaches that currently dominate conventional practice in educational research. The features and advantages of Bayesian approaches are illustrated with examples spanning several statistical modeling…
Learning dynamic Bayesian networks with mixed variables
DEFF Research Database (Denmark)
Bøttcher, Susanne Gammelgaard
This paper considers dynamic Bayesian networks for discrete and continuous variables. We only treat the case, where the distribution of the variables is conditional Gaussian. We show how to learn the parameters and structure of a dynamic Bayesian network and also how the Markov order can be learned...
The Bayesian Revolution Approaches Psychological Development
Shultz, Thomas R.
2007-01-01
This commentary reviews five articles that apply Bayesian ideas to psychological development, some with psychology experiments, some with computational modeling, and some with both experiments and modeling. The reviewed work extends the current Bayesian revolution into tasks often studied in children, such as causal learning and word learning, and…
Bayesian Network for multiple hypthesis tracking
W.P. Zajdel; B.J.A. Kröse
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 produ
Rheology and Relaxation Timescales of ABA Triblock Polymer Gels
Peters, Andrew; Lodge, Timothy
When dissolved in a midblock selective solvent, ABA polymers form gels composed of aggregated end block micelles bridged by the midblocks. While much effort has been devoted to the study of the structure of these systems, the dynamics of these systems has received less attention. We examine the underlying mechanism of shear relaxation of ABA triblock polymer gels, especially as a function of chain length, composition, and concentration. Recent work using time-resolved small-angle neutron scattering of polystyrene (PS)-block-poly(ethylene-alt-propylene) (PEP) in squalane has elucidated many aspects of the dynamics of diblock chain exchange. By using rheology to study bulk relaxation phenomena of the triblock equivalent, PS-PEP-PS, we apply the knowledge gained from the chain exchange studies to bridge the gap between the molecular and macroscopic relaxation phenomena in PS-PEP-PS triblock gels.
LAVENDER AROMATERAPHY AS A RELAXANT
Directory of Open Access Journals (Sweden)
IGA Prima Dewi AP
2013-02-01
Full Text Available Aromatherapy is a kind of treatment that used aroma with aromatherapy essential oil. Extraction process from essential oil generally doing in three methods, there are distilling with water (boiled, distilling with water and steam, and distilling with steam. One of the most favorite aroma is lavender. The main content from lavender is linalyl acetate and linalool (C10H18O. Linalool is main active contents in lavender which can use for anti-anxiety (relaxation. Based on some research, the conclusion indicates that essential oil from lavender can give relaxation (carminative, sedative, reduce anxiety level and increasing mood.
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 BICLUSTERING FOR PATIENT STRATIFICATION.
Khakabimamaghani, Sahand; Ester, Martin
2016-01-01
The move from Empirical Medicine towards Personalized Medicine has attracted attention to Stratified Medicine (SM). Some methods are provided in the literature for patient stratification, which is the central task of SM, however, there are still significant open issues. First, it is still unclear if integrating different datatypes will help in detecting disease subtypes more accurately, and, if not, which datatype(s) are most useful for this task. Second, it is not clear how we can compare different methods of patient stratification. Third, as most of the proposed stratification methods are deterministic, there is a need for investigating the potential benefits of applying probabilistic methods. To address these issues, we introduce a novel integrative Bayesian biclustering method, called B2PS, for patient stratification and propose methods for evaluating the results. Our experimental results demonstrate the superiority of B2PS over a popular state-of-the-art method and the benefits of Bayesian approaches. Our results agree with the intuition that transcriptomic data forms a better basis for patient stratification than genomic data.
BAYESIAN BICLUSTERING FOR PATIENT STRATIFICATION.
Khakabimamaghani, Sahand; Ester, Martin
2016-01-01
The move from Empirical Medicine towards Personalized Medicine has attracted attention to Stratified Medicine (SM). Some methods are provided in the literature for patient stratification, which is the central task of SM, however, there are still significant open issues. First, it is still unclear if integrating different datatypes will help in detecting disease subtypes more accurately, and, if not, which datatype(s) are most useful for this task. Second, it is not clear how we can compare different methods of patient stratification. Third, as most of the proposed stratification methods are deterministic, there is a need for investigating the potential benefits of applying probabilistic methods. To address these issues, we introduce a novel integrative Bayesian biclustering method, called B2PS, for patient stratification and propose methods for evaluating the results. Our experimental results demonstrate the superiority of B2PS over a popular state-of-the-art method and the benefits of Bayesian approaches. Our results agree with the intuition that transcriptomic data forms a better basis for patient stratification than genomic data. PMID:26776199
Bayesian predictive modeling for genomic based personalized treatment selection.
Ma, Junsheng; Stingo, Francesco C; Hobbs, Brian P
2016-06-01
Efforts to personalize medicine in oncology have been limited by reductive characterizations of the intrinsically complex underlying biological phenomena. Future advances in personalized medicine will rely on molecular signatures that derive from synthesis of multifarious interdependent molecular quantities requiring robust quantitative methods. However, highly parameterized statistical models when applied in these settings often require a prohibitively large database and are sensitive to proper characterizations of the treatment-by-covariate interactions, which in practice are difficult to specify and may be limited by generalized linear models. In this article, we present a Bayesian predictive framework that enables the integration of a high-dimensional set of genomic features with clinical responses and treatment histories of historical patients, providing a probabilistic basis for using the clinical and molecular information to personalize therapy for future patients. Our work represents one of the first attempts to define personalized treatment assignment rules based on large-scale genomic data. We use actual gene expression data acquired from The Cancer Genome Atlas in the settings of leukemia and glioma to explore the statistical properties of our proposed Bayesian approach for personalizing treatment selection. The method is shown to yield considerable improvements in predictive accuracy when compared to penalized regression approaches. PMID:26575856
DEFF Research Database (Denmark)
Guillot, Gilles; Carpentier-Skandalis, Alexandra
2011-01-01
We study the accuracy of a Bayesian supervised method used to cluster individuals into genetically homogeneous groups on the basis of dominant or codominant molecular markers. We provide a formula relating an error criterion to the number of loci used and the number of clusters. This formula...
Dielectric relaxation of CdO nanoparticles
Tripathi, Ramna; Dutta, Alo; Das, Sayantani; Kumar, Akhilesh; Sinha, T. P.
2016-02-01
Nanoparticles of cadmium oxide have been synthesized by soft chemical route using thioglycerol as the capping agent. The crystallite size is determined by X-ray diffraction technique and the particle size is obtained by transmission electron microscope. The band gap of the material is obtained using Tauc relation to UV-visible absorption spectrum. The photoluminescence emission spectra of the sample are measured at various excitation wavelengths. The molecular components in the material have been analyzed by FT-IR spectroscopy. The dielectric dispersion of the material is investigated in the temperature range from 313 to 393 K and in the frequency range from 100 Hz to 1 MHz by impedance spectroscopy. The Cole-Cole model is used to describe the dielectric relaxation of the system. The scaling behavior of imaginary part of impedance shows that the relaxation describes the same mechanism at various temperatures. The frequency-dependent electrical data are also analyzed in the framework of conductivity and electrical modulus formalisms. The frequency-dependent conductivity spectra are found to obey the power law.
Bayesian analysis of genetic differentiation between populations.
Corander, Jukka; Waldmann, Patrik; Sillanpää, Mikko J
2003-01-01
We introduce a Bayesian method for estimating hidden population substructure using multilocus molecular markers and geographical information provided by the sampling design. The joint posterior distribution of the substructure and allele frequencies of the respective populations is available in an analytical form when the number of populations is small, whereas an approximation based on a Markov chain Monte Carlo simulation approach can be obtained for a moderate or large number of populations. Using the joint posterior distribution, posteriors can also be derived for any evolutionary population parameters, such as the traditional fixation indices. A major advantage compared to most earlier methods is that the number of populations is treated here as an unknown parameter. What is traditionally considered as two genetically distinct populations, either recently founded or connected by considerable gene flow, is here considered as one panmictic population with a certain probability based on marker data and prior information. Analyses of previously published data on the Moroccan argan tree (Argania spinosa) and of simulated data sets suggest that our method is capable of estimating a population substructure, while not artificially enforcing a substructure when it does not exist. The software (BAPS) used for the computations is freely available from http://www.rni.helsinki.fi/~mjs. PMID:12586722
Approximate Bayesian Computation in Large Scale Structure: constraining the galaxy-halo connection
Hahn, ChangHoon; Walsh, Kilian; Hearin, Andrew P; Hogg, David W; Cambpell, Duncan
2016-01-01
The standard approaches to Bayesian parameter inference in large scale structure (LSS) assume a Gaussian functional form (chi-squared form) for the likelihood. They are also typically restricted to measurements such as the two point correlation function. Likelihood free inferences such as Approximate Bayesian Computation (ABC) make inference possible without assuming any functional form for the likelihood, thereby relaxing the assumptions and restrictions of the standard approach. Instead it relies on a forward generative model of the data and a metric for measuring the distance between the model and data. In this work, we demonstrate that ABC is feasible for LSS parameter inference by using it to constrain parameters of the halo occupation distribution (HOD) model for populating dark matter halos with galaxies. Using specific implementation of ABC supplemented with Population Monte Carlo importance sampling, a generative forward model using HOD, and a distance metric based on galaxy number density, two-point...
Meredith, Robert W; Pires, Marcelo N; Reznick, David N; Springer, Mark S
2010-05-01
Poeciliids are one of the most intensively studied groups within Cyprinodontiformes owing to their use as model organisms for experimental studies on natural and sexual selection, and comparative studies of life-history evolution. Life-history studies have demonstrated multiple origins of placentotrophy and superfetation in poeciliids, including the recent description of placentotrophy in three species of Poecilia (Micropoecilia): P. bifurca, P. branneri, and P. parae. Here, we use a concatenation of seven nuclear gene segments and two mitochondrial segments to examine relationships within Micropoecilia and between this subgenus and other subgenera in Poecilia (Mollienesia, Limia, Pamphorichthys, Acanthophacelus). The combined molecular data set (8668 bp) was analyzed with maximum parsimony, maximum likelihood, and Bayesian methods. We also employed a relaxed molecular clock method to estimate divergence times within Poecilia. All phylogenetic analyses with the combined DNA data set supported the monophyly of Poecilia and recovered a basal split between Poecilia (Acanthophacelus)+Poecilia (Micropoecilia) and the other three subgenera. Within Micropoecilia, P. bifurca grouped with P. branneri, and these joined P. parae to the exclusion of P. picta. Ancestral reconstructions based on parsimony and Bayesian methods suggest that placentotrophy evolved once in Micropoecilia in the common ancestor of P. bifurca, P. branneri, and P. parae. Divergence time estimates suggest that placentotrophy in Micropoecilia evolved in 4 million years.
Space dispersion of structural relaxation in simple liquids
International Nuclear Information System (INIS)
The concept of a reduced description is used to study the space dispersion of the structural relaxation in simple classical liquids. Microscopic expressions are derived. Dispersion curves are found for the half-width at half-maximum of a dynamic structure factor and also for four other parameters of the structural relaxation: the relaxation time τs, the structure lifetime τls, the memory lifetime τlm, and the parameter var-epsilon = τls/τlm. The latter parameter characterizes the relative 'speeding up' or 'slowing down' of the molecular memory. A comparison of the theoretical results with experimental data on liquid rubidium, krypton, and argon reveals both the dispersion of this set of five relaxation parameters (τs, Δω1/2, τls, τlm, and var-epsilon) and the dispersion of the non-Markovian behavior of the structural relaxation and its transition to a quasi-Markov regime at small wave vectors, near the de Gennes narrowing and the maximum of the static structure factor
Relaxation and resonances in fluctuating dielectric systems
Garcia-Colin, L. S.; del Castillo, L. F.
1989-09-01
In this paper we show how the ideas behind extended irreversible thermodynamics are used to generate a systematic treatment of the relaxation and resonance phenomena in the propagation and absorption of electromagnetic energy in dielectric materials in a nonequilibrium state. Two cases are discussed: the first, in which the forced oscillations arising from the correlation between the fluctuations of the polarization vector and the electric field are neglected, and the second, in which this term is taken into account. In both cases we show how the main equations serve to make a connection between the macroscopic approach followed here and a number of results obtained for both, gases and polar liquids using molecular models. The results obtained here are compared with previous work on this problem, and new effects arising from the second case are pointed out.
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.
Choosing a skeletal muscle relaxant.
See, Sharon; Ginzburg, Regina
2008-08-01
Skeletal muscle relaxants are widely used in treating musculoskeletal conditions. However, evidence of their effectiveness consists mainly of studies with poor methodologic design. In addition, these drugs have not been proven to be superior to acetaminophen or nonsteroidal anti-inflammatory drugs for low back pain. Systematic reviews and meta-analyses support using skeletal muscle relaxants for short-term relief of acute low back pain when nonsteroidal anti-inflammatory drugs or acetaminophen are not effective or tolerated. Comparison studies have not shown one skeletal muscle relaxant to be superior to another. Cyclobenzaprine is the most heavily studied and has been shown to be effective for various musculoskeletal conditions. The sedative properties of tizanidine and cyclobenzaprine may benefit patients with insomnia caused by severe muscle spasms. Methocarbamol and metaxalone are less sedating, although effectiveness evidence is limited. Adverse effects, particularly dizziness and drowsiness, are consistently reported with all skeletal muscle relaxants. The potential adverse effects should be communicated clearly to the patient. Because of limited comparable effectiveness data, choice of agent should be based on side-effect profile, patient preference, abuse potential, and possible drug interactions. PMID:18711953
Anisotropic spin relaxation in graphene
Tombros, N.; Tanabe, S.; Veligura, A.; Jozsa, C.; Popinciuc, M.; Jonkman, H. T.; van Wees, B. J.
2008-01-01
Spin relaxation in graphene is investigated in electrical graphene spin valve devices in the nonlocal geometry. Ferromagnetic electrodes with in-plane magnetizations inject spins parallel to the graphene layer. They are subject to Hanle spin precession under a magnetic field B applied perpendicular
Dielectric relaxation of samarium aluminate
Energy Technology Data Exchange (ETDEWEB)
Sakhya, Anup Pradhan; Dutta, Alo; Sinha, T.P. [Bose Institute, Department of Physics, Kolkata (India)
2014-03-15
A ceramic SmAlO{sub 3} (SAO) sample is synthesized by the solid-state reaction technique. The Rietveld refinement of the X-ray diffraction pattern has been done to find the crystal symmetry of the sample at room temperature. An impedance spectroscopy study of the sample has been performed in the frequency range from 50 Hz to 1 MHz and in the temperature range from 313 K to 573 K. Dielectric relaxation peaks are observed in the imaginary parts of the spectra. The Cole-Cole model is used to analyze the dielectric relaxation mechanism in SAO. The temperature-dependent relaxation times are found to obey the Arrhenius law having an activation energy of 0.29 eV, which indicates that polaron hopping is responsible for conduction or dielectric relaxation in this material. The complex impedance plane plot of the sample indicates the presence of both grain and grain-boundary effects and is analyzed by an electrical equivalent circuit consisting of a resistance and a constant-phase element. The frequency-dependent conductivity spectra follow a double-power law due to the presence of two plateaus. (orig.)
Schubert, Alexander; Falvo, Cyril; Meier, Christoph
2016-08-01
We present mixed quantum-classical simulations on relaxation and dephasing of vibrationally excited carbon monoxide within a protein environment. The methodology is based on a vibrational surface hopping approach treating the vibrational states of CO quantum mechanically, while all remaining degrees of freedom are described by means of classical molecular dynamics. The CO vibrational states form the "surfaces" for the classical trajectories of protein and solvent atoms. In return, environmentally induced non-adiabatic couplings between these states cause transitions describing the vibrational relaxation from first principles. The molecular dynamics simulation yields a detailed atomistic picture of the energy relaxation pathways, taking the molecular structure and dynamics of the protein and its solvent fully into account. Using the ultrafast photolysis of CO in the hemoprotein FixL as an example, we study the relaxation of vibrationally excited CO and evaluate the role of each of the FixL residues forming the heme pocket. PMID:27497540
Post-shock relaxation in crystalline nitromethane
Rivera-Rivera, Luis A.; Sewell, Thomas D.; Thompson, Donald L.
2013-02-01
Molecular dynamics simulations of shocked (100)-oriented crystalline nitromethane were carried out to determine the rates of relaxation behind the shock wave. The forces were described by the fully flexible non-reactive Sorescu-Rice-Thompson force field [D. C. Sorescu, B. M. Rice, and D. L. Thompson, J. Phys. Chem. B 104, 8406 (2000)], 10.1021/jp000942q. The time scales for local and overall thermal equilibration in the shocked crystal were determined. The molecular center-of-mass and atomic kinetic energy distributions rapidly reach substantially different local temperatures. Several picoseconds are required for the two distributions to converge, corresponding to establishment of thermal equilibrium in the shocked crystal. The decrease of the molecular center-of-mass temperature and the increase of the atomic temperature behind the shock front exhibit essentially exponential dependence on time. Analysis of covalent bond distance distributions ahead of, immediately behind, and well behind the shock front showed that the effective bond stretching potentials are essentially harmonic. Effective force constants for the C-N, C-H, and N-O bonds immediately behind the shock front are larger by factors of 1.6, 2.5, and 2.0, respectively, than in the unshocked crystal; and by factors of 1.2, 2.2, and 1.7, respectively, compared to material sufficiently far behind the shock front to be essentially at thermal equilibrium.
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.
Quantum Bayesianism at the Perimeter
Fuchs, Christopher A
2010-01-01
The author summarizes the Quantum Bayesian viewpoint of quantum mechanics, developed originally by C. M. Caves, R. Schack, and himself. It is a view crucially dependent upon the tools of quantum information theory. Work at the Perimeter Institute for Theoretical Physics continues the development and is focused on the hard technical problem of a finding a good representation of quantum mechanics purely in terms of probabilities, without amplitudes or Hilbert-space operators. The best candidate representation involves a mysterious entity called a symmetric informationally complete quantum measurement. Contemplation of it gives a way of thinking of the Born Rule as an addition to the rules of probability theory, applicable when one gambles on the consequences of interactions with physical systems. The article ends by outlining some directions for future work.
Hedging Strategies for Bayesian Optimization
Brochu, Eric; de Freitas, Nando
2010-01-01
Bayesian optimization with Gaussian processes has become an increasingly popular tool in the machine learning community. It is efficient and can be used when very little is known about the objective function, making it popular in expensive black-box optimization scenarios. It is able to do this by sampling the objective using an acquisition function which incorporates the model's estimate of the objective and the uncertainty at any given point. However, there are several different parameterized acquisition functions in the literature, and it is often unclear which one to use. Instead of using a single acquisition function, we adopt a portfolio of acquisition functions governed by an online multi-armed bandit strategy. We describe the method, which we call GP-Hedge, and show that this method almost always outperforms the best individual acquisition function.
Bayesian Networks and Influence Diagrams
DEFF Research Database (Denmark)
Kjærulff, Uffe Bro; Madsen, Anders Læsø
, and exercises are included for the reader to check his/her level of understanding. The techniques and methods presented for knowledge elicitation, model construction and verification, modeling techniques and tricks, learning models from data, and analyses of models have all been developed and refined......, 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 Networks and Influence Diagrams
DEFF Research Database (Denmark)
Kjærulff, Uffe Bro; Madsen, Anders Læsø
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......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...
State Information in Bayesian Games
Cuff, Paul
2009-01-01
Two-player zero-sum repeated games are well understood. Computing the value of such a game is straightforward. Additionally, if the payoffs are dependent on a random state of the game known to one, both, or neither of the players, the resulting value of the game has been analyzed under the framework of Bayesian games. This investigation considers the optimal performance in a game when a helper is transmitting state information to one of the players. Encoding information for an adversarial setting (game) requires a different result than rate-distortion theory provides. Game theory has accentuated the importance of randomization (mixed strategy), which does not find a significant role in most communication modems and source coding codecs. Higher rates of communication, used in the right way, allow the message to include the necessary random component useful in games.
Multiview Bayesian Correlated Component Analysis
DEFF Research Database (Denmark)
Kamronn, Simon Due; Poulsen, Andreas Trier; Hansen, Lars Kai
2015-01-01
Correlated component analysis as proposed by Dmochowski, Sajda, Dias, and Parra (2012) is a tool for investigating brain process similarity in the responses to multiple views of a given stimulus. Correlated components are identified under the assumption that the involved spatial networks...... 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....
Elvira, Clément; Dobigeon, Nicolas
2015-01-01
Sparse representations have proven their efficiency in solving a wide class of inverse problems encountered in signal and image processing. Conversely, enforcing the information to be spread uniformly over representation coefficients exhibits relevant properties in various applications such as digital communications. Anti-sparse regularization can be naturally expressed through an $\\ell_{\\infty}$-norm penalty. This paper derives a probabilistic formulation of such representations. A new probability distribution, referred to as the democratic prior, is first introduced. Its main properties as well as three random variate generators for this distribution are derived. Then this probability distribution is used as a prior to promote anti-sparsity in a Gaussian linear inverse problem, yielding a fully Bayesian formulation of anti-sparse coding. Two Markov chain Monte Carlo (MCMC) algorithms are proposed to generate samples according to the posterior distribution. The first one is a standard Gibbs sampler. The seco...
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. PMID:22523437
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 ...
The relaxational behaviour of poly-(vinylidene fluoride) before and after gamma-irradiation
International Nuclear Information System (INIS)
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
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...
Identification of Structural Relaxation in the Dielectric Response of Water
Hansen, Jesper S.; Kisliuk, Alexander; Sokolov, Alexei P.; Gainaru, Catalin
2016-06-01
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.
Anomalous orientational relaxation of solute probes in binary mixtures
Bhattacharyya, Sarika; Bagchi, Biman
2001-01-01
The orientation of a solute probe in a binary mixture often exhibits multiple relaxation times at the same solvent viscosity but different compositions [Beddard et al., Nature (London) 294, 145 (1981)]. In order to understand this interesting observation, we have carried out (NPT) molecular dynamics simulation study of rotation of prolate ellipsoids in binary mixtures. The simulations show that for a broad range of model parameters the experimental behavior can be reproduced. The plot of orie...
INVESTIGATION ON NONEQULIBRIUM RADIATION AND RELAXATION PHENOMENA IN SHOCK TUBES
Institute of Scientific and Technical Information of China (English)
竺乃宜; 杨乾锁; 张恒利; 余西龙; 黄立舜
2003-01-01
The experimental results for the excited time of the nonequlibrium radiation andthe ionization behind strong shock waves are presented. Using an optical multichannel analyzer, InSb infrared detectors and near-free-molecular Langmuir probes, the infrared radiation, the electron density of air and the nonequlibrium radiation spectra at different moments of the relaxation process in nitrogen test gas behind normal shock waves were obtained, respectively, in hydrogen oxygen combustion driven shock tubes.
Plasmon-mediated energy relaxation in graphene
Energy Technology Data Exchange (ETDEWEB)
Ferry, D. K. [School of Electrical, Computer, and Energy Engineering, Arizona State University, Tempe, Arizona 85287-5706 (United States); Somphonsane, R. [Department of Physics, King Mongkut' s Institute of Technology, Ladkrabang, Bangkok 10520 (Thailand); Ramamoorthy, H.; Bird, J. P. [Department of Electrical Engineering, University at Buffalo, the State University of New York, Buffalo, New York 14260-1500 (United States)
2015-12-28
Energy relaxation of hot carriers in graphene is studied at low temperatures, where the loss rate may differ significantly from that predicted for electron-phonon interactions. We show here that plasmons, important in the relaxation of energetic carriers in bulk semiconductors, can also provide a pathway for energy relaxation in transport experiments in graphene. We obtain a total loss rate to plasmons that results in energy relaxation times whose dependence on temperature and density closely matches that found experimentally.
Plasmon-mediated energy relaxation in graphene
Ferry, D. K.; Somphonsane, R.; Ramamoorthy, H.; Bird, J. P.
2015-12-01
Energy relaxation of hot carriers in graphene is studied at low temperatures, where the loss rate may differ significantly from that predicted for electron-phonon interactions. We show here that plasmons, important in the relaxation of energetic carriers in bulk semiconductors, can also provide a pathway for energy relaxation in transport experiments in graphene. We obtain a total loss rate to plasmons that results in energy relaxation times whose dependence on temperature and density closely matches that found experimentally.
Shetty, Rahul; Bigiel, Frank
2012-01-01
We develop a Bayesian linear regression method which rigorously treats measurement uncertainties, and accounts for hierarchical data structure for investigating the relationship between the star formation rate and gas surface density. The method simultaneously estimates the intercept, slope, and scatter about the regression line of each individual subject (e.g. a galaxy) and the population (e.g. an ensemble of galaxies). Using synthetic datasets, we demonstrate that the Bayesian method accurately recovers the parameters of both the individuals and the population, especially when compared to commonly employed least squares methods, such as the bisector. We apply the Bayesian method to estimate the Kennicutt-Schmidt (KS) parameters of a sample of spiral galaxies compiled by Bigiel et al. (2008). We find significant variation in the KS parameters, indicating that no single KS relationship holds for all galaxies. This suggests that the relationship between molecular gas and star formation differs between galaxies...
The Diagnosis of Reciprocating Machinery by Bayesian Networks
Institute of Scientific and Technical Information of China (English)
无
2003-01-01
A Bayesian Network is a reasoning tool based on probability theory and has many advantages that other reasoning tools do not have. This paper discusses the basic theory of Bayesian networks and studies the problems in constructing Bayesian networks. The paper also constructs a Bayesian diagnosis network of a reciprocating compressor. The example helps us to draw a conclusion that Bayesian diagnosis networks can diagnose reciprocating machinery effectively.
Nonequilibrium interfacial tension during relaxation.
Bier, Markus
2015-10-01
The concept of a nonequilibrium interfacial tension, defined via the work required to deform a system such that the interfacial area is changed while the volume is conserved, is investigated theoretically in the context of the relaxation of an initial perturbation of a colloidal fluid towards the equilibrium state. The corresponding general formalism is derived for systems with planar symmetry and applied to fluid models of colloidal suspensions and polymer solutions. It is shown that the nonequilibrium interfacial tension is not necessarily positive, that negative nonequilibrium interfacial tensions are consistent with strictly positive equilibrium interfacial tensions, and that the sign of the interfacial tension can influence the morphology of density perturbations during relaxation. PMID:26565189
Kinetic activation-relaxation technique.
Béland, Laurent Karim; Brommer, Peter; El-Mellouhi, Fedwa; Joly, Jean-François; Mousseau, Normand
2011-10-01
We present a detailed description of the kinetic activation-relaxation technique (k-ART), an off-lattice, self-learning kinetic Monte Carlo (KMC) algorithm with on-the-fly event search. Combining a topological classification for local environments and event generation with ART nouveau, an efficient unbiased sampling method for finding transition states, k-ART can be applied to complex materials with atoms in off-lattice positions or with elastic deformations that cannot be handled with standard KMC approaches. In addition to presenting the various elements of the algorithm, we demonstrate the general character of k-ART by applying the algorithm to three challenging systems: self-defect annihilation in c-Si (crystalline silicon), self-interstitial diffusion in Fe, and structural relaxation in a-Si (amorphous silicon).
Institute of Scientific and Technical Information of China (English)
王卫东; 郝跃; 纪翔; 易成龙; 牛翔宇
2012-01-01
分别采用Tersoff-Brenner势和AIREBO势，对三种长宽比的单层石墨烯纳米带在不同热力学温度（0．01—4000K）下的弛豫性能进行了分子动力学模拟．对基于两种势函数模拟的石墨烯纳米带弛豫的能量曲线和表面形貌进行了分析对比，研究了石墨烯纳米带在弛豫过程中的动态平衡过程．模拟结果表明：单层石墨烯纳米带并非完美的平面结构，边缘处和内部都会呈现一定程度的起伏和皱褶，这与已有的实验结果相符合；石墨烯纳米带的表面起伏程度随长宽比的减小而减小，并且在不同温度条件下，系统动能对石墨烯纳米带的弛豫变形的影响很大，即系统温度越高，石墨烯纳米带的弛豫变形幅度愈大；高长宽比纳米带在一定温度条件下甚至会出现卷曲现象．最后，对采用Tersoff-Brenner势和AIREBO势进行石墨烯的分子动力学模拟进行了深入分析．%At different thermodynamic temperatures (between 0.01 and 4000 K), the relaxation properties of three kinds of graphene nanorib- bons with different aspect ratios are simulated by molecular dynamics method based on Tersoff-Brenner and AIREBO potential func- tions separately. Then we compare the energy curves and surface morphologies of nanoribbon relaxation with two kinds of potential functions, and study the dynamic equilibrium process of the graphene nanoribbons during their relaxation simulation. The simulation results show that the single layer graphene nanoribbon is not of a perfect planar structure and that a certain degree of fluctuations and folds occur at the edges and inside of nanoribbons, which are consistent with the existing experimental results; the surface fluctuation level of graphene nanoribbons decreases with the reduction of the aspect ratio, and the system kinetic energy has a dramatic influence on the relaxation deformation of the graphene nanoribbons at different temperatures, which
LAVENDER AROMATERAPHY AS A RELAXANT
IGA Prima Dewi AP
2013-01-01
Aromatherapy is a kind of treatment that used aroma with aromatherapy essential oil. Extraction process from essential oil generally doing in three methods, there are distilling with water (boiled), distilling with water and steam, and distilling with steam. One of the most favorite aroma is lavender. The main content from lavender is linalyl acetate and linalool (C10H18O). Linalool is main active contents in lavender which can use for anti-anxiety (relaxation). Based on some research, the co...
Chang, Zhiwei; Halle, Bertil
2013-10-01
In complex biological or colloidal samples, magnetic relaxation dispersion (MRD) experiments using the field-cycling technique can characterize molecular motions on time scales ranging from nanoseconds to microseconds, provided that a rigorous theory of nuclear spin relaxation is available. In gels, cross-linked proteins, and biological tissues, where an immobilized macromolecular component coexists with a mobile solvent phase, nuclear spins residing in solvent (or cosolvent) species relax predominantly via exchange-mediated orientational randomization (EMOR) of anisotropic nuclear (electric quadrupole or magnetic dipole) couplings. The physical or chemical exchange processes that dominate the MRD typically occur on a time scale of microseconds or longer, where the conventional perturbation theory of spin relaxation breaks down. There is thus a need for a more general relaxation theory. Such a theory, based on the stochastic Liouville equation (SLE) for the EMOR mechanism, is available for a single quadrupolar spin I = 1. Here, we present the corresponding theory for a dipole-coupled spin-1/2 pair. To our knowledge, this is the first treatment of dipolar MRD outside the motional-narrowing regime. Based on an analytical solution of the spatial part of the SLE, we show how the integral longitudinal relaxation rate can be computed efficiently. Both like and unlike spins, with selective or non-selective excitation, are treated. For the experimentally important dilute regime, where only a small fraction of the spin pairs are immobilized, we obtain simple analytical expressions for the auto-relaxation and cross-relaxation rates which generalize the well-known Solomon equations. These generalized results will be useful in biophysical studies, e.g., of intermittent protein dynamics. In addition, they represent a first step towards a rigorous theory of water 1H relaxation in biological tissues, which is a prerequisite for unravelling the molecular basis of soft
Bayesian Uncertainty Analyses Via Deterministic Model
Krzysztofowicz, R.
2001-05-01
Rational decision-making requires that the total uncertainty about a variate of interest (a predictand) be quantified in terms of a probability distribution, conditional on all available information and knowledge. Suppose the state-of-knowledge is embodied in a deterministic model, which is imperfect and outputs only an estimate of the predictand. Fundamentals are presented of three Bayesian approaches to producing a probability distribution of the predictand via any deterministic model. The Bayesian Processor of Output (BPO) quantifies the total uncertainty in terms of a posterior distribution, conditional on model output. The Bayesian Processor of Ensemble (BPE) quantifies the total uncertainty in terms of a posterior distribution, conditional on an ensemble of model output. The Bayesian Forecasting System (BFS) decomposes the total uncertainty into input uncertainty and model uncertainty, which are characterized independently and then integrated into a predictive distribution.
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.
A Bayesian approach to model uncertainty
International Nuclear Information System (INIS)
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 Control for Concentrating Mixed Nuclear Waste
Welch, Robert L.; Smith, Clayton
2013-01-01
A control algorithm for batch processing of mixed waste is proposed based on conditional Gaussian Bayesian networks. The network is compiled during batch staging for real-time response to sensor input.
An Intuitive Dashboard for Bayesian Network Inference
International Nuclear Information System (INIS)
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++
An Intuitive Dashboard for Bayesian Network Inference
Reddy, Vikas; Charisse Farr, Anna; Wu, Paul; Mengersen, Kerrie; Yarlagadda, Prasad K. D. V.
2014-03-01
Current Bayesian network software packages provide good graphical interface for users who design and develop Bayesian networks for various applications. However, the intended end-users of these networks may not necessarily find such an interface appealing and at times it could be overwhelming, particularly when the number of nodes in the network is large. To circumvent this problem, this paper presents an intuitive dashboard, which provides an additional layer of abstraction, enabling the end-users to easily perform inferences over the Bayesian networks. Unlike most software packages, which display the nodes and arcs of the network, the developed tool organises the nodes based on the cause-and-effect relationship, making the user-interaction more intuitive and friendly. In addition to performing various types of inferences, the users can conveniently use the tool to verify the behaviour of the developed Bayesian network. The tool has been developed using QT and SMILE libraries in C++.
Nomograms for Visualization of Naive Bayesian Classifier
Možina, Martin; Demšar, Janez; Michael W Kattan; Zupan, Blaz
2004-01-01
Besides good predictive performance, the naive Bayesian classifier can also offer a valuable insight into the structure of the training data and effects of the attributes on the class probabilities. This structure may be effectively revealed through visualization of the classifier. We propose a new way to visualize the naive Bayesian model in the form of a nomogram. The advantages of the proposed method are simplicity of presentation, clear display of the effects of individual attribute value...
Subjective Bayesian Analysis: Principles and Practice
Goldstein, Michael
2006-01-01
We address the position of subjectivism within Bayesian statistics. We argue, first, that the subjectivist Bayes approach is the only feasible method for tackling many important practical problems. Second, we describe the essential role of the subjectivist approach in scientific analysis. Third, we consider possible modifications to the Bayesian approach from a subjectivist viewpoint. Finally, we address the issue of pragmatism in implementing the subjectivist approach.
Bayesian Analysis of Multivariate Probit Models
Siddhartha Chib; Edward Greenberg
1996-01-01
This paper provides a unified simulation-based Bayesian and non-Bayesian analysis of correlated binary data using the multivariate probit model. The posterior distribution is simulated by Markov chain Monte Carlo methods, and maximum likelihood estimates are obtained by a Markov chain Monte Carlo version of the E-M algorithm. Computation of Bayes factors from the simulation output is also considered. The methods are applied to a bivariate data set, to a 534-subject, four-year longitudinal dat...
Fitness inheritance in the Bayesian optimization algorithm
Pelikan, Martin; Sastry, Kumara
2004-01-01
This paper describes how fitness inheritance can be used to estimate fitness for a proportion of newly sampled candidate solutions in the Bayesian optimization algorithm (BOA). The goal of estimating fitness for some candidate solutions is to reduce the number of fitness evaluations for problems where fitness evaluation is expensive. Bayesian networks used in BOA to model promising solutions and generate the new ones are extended to allow not only for modeling and sampling candidate solutions...
Kernel Bayesian Inference with Posterior Regularization
Song, Yang; Jun ZHU; Ren, Yong
2016-01-01
We propose a vector-valued regression problem whose solution is equivalent to the reproducing kernel Hilbert space (RKHS) embedding of the Bayesian posterior distribution. This equivalence provides a new understanding of kernel Bayesian inference. Moreover, the optimization problem induces a new regularization for the posterior embedding estimator, which is faster and has comparable performance to the squared regularization in kernel Bayes' rule. This regularization coincides with a former th...
Bayesian Classification in Medicine: The Transferability Question *
Zagoria, Ronald J.; Reggia, James A.; Price, Thomas R.; Banko, Maryann
1981-01-01
Using probabilities derived from a geographically distant patient population, we applied Bayesian classification to categorize stroke patients by etiology. Performance was assessed both by error rate and with a new linear accuracy coefficient. This approach to patient classification was found to be surprisingly accurate when compared to classification by two neurologists and to classification by the Bayesian method using “low cost” local and subjective probabilities. We conclude that for some...
Bayesian target tracking based on particle filter
Institute of Scientific and Technical Information of China (English)
无
2005-01-01
For being able to deal with the nonlinear or non-Gaussian problems, particle filters have been studied by many researchers. Based on particle filter, the extended Kalman filter (EKF) proposal function is applied to Bayesian target tracking. Markov chain Monte Carlo (MCMC) method, the resampling step, etc novel techniques are also introduced into Bayesian target tracking. And the simulation results confirm the improved particle filter with these techniques outperforms the basic one.
Bayesian Variable Selection in Spatial Autoregressive Models
Jesus Crespo Cuaresma; Philipp Piribauer
2015-01-01
This paper compares the performance of Bayesian variable selection approaches for spatial autoregressive models. We present two alternative approaches which can be implemented using Gibbs sampling methods in a straightforward way and allow us to deal with the problem of model uncertainty in spatial autoregressive models in a flexible and computationally efficient way. In a simulation study we show that the variable selection approaches tend to outperform existing Bayesian model averaging tech...
Fuzzy Functional Dependencies and Bayesian Networks
Institute of Scientific and Technical Information of China (English)
LIU WeiYi(刘惟一); SONG Ning(宋宁)
2003-01-01
Bayesian networks have become a popular technique for representing and reasoning with probabilistic information. The fuzzy functional dependency is an important kind of data dependencies in relational databases with fuzzy values. The purpose of this paper is to set up a connection between these data dependencies and Bayesian networks. The connection is done through a set of methods that enable people to obtain the most information of independent conditions from fuzzy functional dependencies.
Bayesian Models of Brain and Behaviour
Penny, William
2012-01-01
This paper presents a review of Bayesian models of brain and behaviour. We first review the basic principles of Bayesian inference. This is followed by descriptions of sampling and variational methods for approximate inference, and forward and backward recursions in time for inference in dynamical models. The review of behavioural models covers work in visual processing, sensory integration, sensorimotor integration, and collective decision making. The review of brain models covers a range of...
Bayesian Modeling of a Human MMORPG Player
Synnaeve, Gabriel
2010-01-01
This paper describes an application of Bayesian programming to the control of an autonomous avatar in a multiplayer role-playing game (the example is based on World of Warcraft). We model a particular task, which consists of choosing what to do and to select which target in a situation where allies and foes are present. We explain the model in Bayesian programming and show how we could learn the conditional probabilities from data gathered during human-played sessions.
Bayesian Modeling of a Human MMORPG Player
Synnaeve, Gabriel; Bessière, Pierre
2011-03-01
This paper describes an application of Bayesian programming to the control of an autonomous avatar in a multiplayer role-playing game (the example is based on World of Warcraft). We model a particular task, which consists of choosing what to do and to select which target in a situation where allies and foes are present. We explain the model in Bayesian programming and show how we could learn the conditional probabilities from data gathered during human-played sessions.
Short-Time Beta Relaxation in Glass-Forming Liquids Is Cooperative in Nature
Karmakar, Smarajit; Dasgupta, Chandan; Sastry, Srikanth
2016-02-01
Temporal relaxation of density fluctuations in supercooled liquids near the glass transition occurs in multiple steps. Using molecular dynamics simulations for three model glass-forming liquids, we show that the short-time β relaxation is cooperative in nature. Using finite-size scaling analysis, we extract a growing length scale associated with beta relaxation from the observed dependence of the beta relaxation time on the system size. We find, in qualitative agreement with the prediction of the inhomogeneous mode coupling theory, that the temperature dependence of this length scale is the same as that of the length scale that describes the spatial heterogeneity of local dynamics in the long-time α -relaxation regime.
Ngai, K L; Habasaki, J; Prevosto, D; Capaccioli, S; Paluch, Marian
2012-07-21
By now it is well established that the structural α-relaxation time, τ(α), of non-associated small molecular and polymeric glass-formers obey thermodynamic scaling. In other words, τ(α) is a function Φ of the product variable, ρ(γ)/T, where ρ is the density and T the temperature. The constant γ as well as the function, τ(α) = Φ(ρ(γ)/T), is material dependent. Actually this dependence of τ(α) on ρ(γ)/T originates from the dependence on the same product variable of the Johari-Goldstein β-relaxation time, τ(β), or the primitive relaxation time, τ(0), of the coupling model. To support this assertion, we give evidences from various sources itemized as follows. (1) The invariance of the relation between τ(α) and τ(β) or τ(0) to widely different combinations of pressure and temperature. (2) Experimental dielectric and viscosity data of glass-forming van der Waals liquids and polymer. (3) Molecular dynamics simulations of binary Lennard-Jones (LJ) models, the Lewis-Wahnström model of ortho-terphenyl, 1,4 polybutadiene, a room temperature ionic liquid, 1-ethyl-3-methylimidazolium nitrate, and a molten salt 2Ca(NO(3))(2)·3KNO(3) (CKN). (4) Both diffusivity and structural relaxation time, as well as the breakdown of Stokes-Einstein relation in CKN obey thermodynamic scaling by ρ(γ)/T with the same γ. (5) In polymers, the chain normal mode relaxation time, τ(N), is another function of ρ(γ)/T with the same γ as segmental relaxation time τ(α). (6) While the data of τ(α) from simulations for the full LJ binary mixture obey very well the thermodynamic scaling, it is strongly violated when the LJ interaction potential is truncated beyond typical inter-particle distance, although in both cases the repulsive pair potentials coincide for some distances. PMID:22830715
Ngai, K. L.; Habasaki, J.; Prevosto, D.; Capaccioli, S.; Paluch, Marian
2012-07-01
By now it is well established that the structural α-relaxation time, τα, of non-associated small molecular and polymeric glass-formers obey thermodynamic scaling. In other words, τα is a function Φ of the product variable, ργ/T, where ρ is the density and T the temperature. The constant γ as well as the function, τα = Φ(ργ/T), is material dependent. Actually this dependence of τα on ργ/T originates from the dependence on the same product variable of the Johari-Goldstein β-relaxation time, τβ, or the primitive relaxation time, τ0, of the coupling model. To support this assertion, we give evidences from various sources itemized as follows. (1) The invariance of the relation between τα and τβ or τ0 to widely different combinations of pressure and temperature. (2) Experimental dielectric and viscosity data of glass-forming van der Waals liquids and polymer. (3) Molecular dynamics simulations of binary Lennard-Jones (LJ) models, the Lewis-Wahnström model of ortho-terphenyl, 1,4 polybutadiene, a room temperature ionic liquid, 1-ethyl-3-methylimidazolium nitrate, and a molten salt 2Ca(NO3)2.3KNO3 (CKN). (4) Both diffusivity and structural relaxation time, as well as the breakdown of Stokes-Einstein relation in CKN obey thermodynamic scaling by ργ/T with the same γ. (5) In polymers, the chain normal mode relaxation time, τN, is another function of ργ/T with the same γ as segmental relaxation time τα. (6) While the data of τα from simulations for the full LJ binary mixture obey very well the thermodynamic scaling, it is strongly violated when the LJ interaction potential is truncated beyond typical inter-particle distance, although in both cases the repulsive pair potentials coincide for some distances.
Bayesian Predictive Distribution for the Magnitude of the Largest Aftershock
Shcherbakov, R.
2014-12-01
Aftershock sequences, which follow large earthquakes, last hundreds of days and are characterized by well defined frequency-magnitude and spatio-temporal distributions. The largest aftershocks in a sequence constitute significant hazard and can inflict additional damage to infrastructure. Therefore, the estimation of the magnitude of possible largest aftershocks in a sequence is of high importance. In this work, we propose a statistical model based on Bayesian analysis and extreme value statistics to describe the distribution of magnitudes of the largest aftershocks in a sequence. We derive an analytical expression for a Bayesian predictive distribution function for the magnitude of the largest expected aftershock and compute the corresponding confidence intervals. We assume that the occurrence of aftershocks can be modeled, to a good approximation, by a non-homogeneous Poisson process with a temporal event rate given by the modified Omori law. We also assume that the frequency-magnitude statistics of aftershocks can be approximated by Gutenberg-Richter scaling. We apply our analysis to 19 prominent aftershock sequences, which occurred in the last 30 years, in order to compute the Bayesian predictive distributions and the corresponding confidence intervals. In the analysis, we use the information of the early aftershocks in the sequences (in the first 1, 10, and 30 days after the main shock) to estimate retrospectively the confidence intervals for the magnitude of the expected largest aftershocks. We demonstrate by analysing 19 past sequences that in many cases we are able to constrain the magnitudes of the largest aftershocks. For example, this includes the analysis of the Darfield (Christchurch) aftershock sequence. The proposed analysis can be used for the earthquake hazard assessment and forecasting associated with the occurrence of large aftershocks. The improvement in instrumental data associated with early aftershocks can greatly enhance the analysis and
Bayesian inference for OPC modeling
Burbine, Andrew; Sturtevant, John; Fryer, David; Smith, Bruce W.
2016-03-01
The use of optical proximity correction (OPC) demands increasingly accurate models of the photolithographic process. Model building and inference techniques in the data science community have seen great strides in the past two decades which make better use of available information. This paper aims to demonstrate the predictive power of Bayesian inference as a method for parameter selection in lithographic models by quantifying the uncertainty associated with model inputs and wafer data. Specifically, the method combines the model builder's prior information about each modelling assumption with the maximization of each observation's likelihood as a Student's t-distributed random variable. Through the use of a Markov chain Monte Carlo (MCMC) algorithm, a model's parameter space is explored to find the most credible parameter values. During parameter exploration, the parameters' posterior distributions are generated by applying Bayes' rule, using a likelihood function and the a priori knowledge supplied. The MCMC algorithm used, an affine invariant ensemble sampler (AIES), is implemented by initializing many walkers which semiindependently explore the space. The convergence of these walkers to global maxima of the likelihood volume determine the parameter values' highest density intervals (HDI) to reveal champion models. We show that this method of parameter selection provides insights into the data that traditional methods do not and outline continued experiments to vet the method.
Bayesian analysis of cosmic structures
Kitaura, Francisco-Shu
2011-01-01
We revise the Bayesian inference steps required to analyse the cosmological large-scale structure. Here we make special emphasis in the complications which arise due to the non-Gaussian character of the galaxy and matter distribution. In particular we investigate the advantages and limitations of the Poisson-lognormal model and discuss how to extend this work. With the lognormal prior using the Hamiltonian sampling technique and on scales of about 4 h^{-1} Mpc we find that the over-dense regions are excellent reconstructed, however, under-dense regions (void statistics) are quantitatively poorly recovered. Contrary to the maximum a posteriori (MAP) solution which was shown to over-estimate the density in the under-dense regions we obtain lower densities than in N-body simulations. This is due to the fact that the MAP solution is conservative whereas the full posterior yields samples which are consistent with the prior statistics. The lognormal prior is not able to capture the full non-linear regime at scales ...
Bayesian analysis of volcanic eruptions
Ho, Chih-Hsiang
1990-10-01
The simple Poisson model generally gives a good fit to many volcanoes for volcanic eruption forecasting. Nonetheless, empirical evidence suggests that volcanic activity in successive equal time-periods tends to be more variable than a simple Poisson with constant eruptive rate. An alternative model is therefore examined in which eruptive rate(λ) for a given volcano or cluster(s) of volcanoes is described by a gamma distribution (prior) rather than treated as a constant value as in the assumptions of a simple Poisson model. Bayesian analysis is performed to link two distributions together to give the aggregate behavior of the volcanic activity. When the Poisson process is expanded to accomodate a gamma mixing distribution on λ, a consequence of this mixed (or compound) Poisson model is that the frequency distribution of eruptions in any given time-period of equal length follows the negative binomial distribution (NBD). Applications of the proposed model and comparisons between the generalized model and simple Poisson model are discussed based on the historical eruptive count data of volcanoes Mauna Loa (Hawaii) and Etna (Italy). Several relevant facts lead to the conclusion that the generalized model is preferable for practical use both in space and time.
BAYESIAN APPROACH OF DECISION PROBLEMS
Directory of Open Access Journals (Sweden)
DRAGOŞ STUPARU
2010-01-01
Full Text Available Management is nowadays a basic vector of economic development, a concept frequently used in our country as well as all over the world. Indifferently of the hierarchical level at which the managerial process is manifested, decision represents its essential moment, the supreme act of managerial activity. Its can be met in all fields of activity, practically having an unlimited degree of coverage, and in all the functions of management. It is common knowledge that the activity of any type of manger, no matter the hierarchical level he occupies, represents a chain of interdependent decisions, their aim being the elimination or limitation of the influence of disturbing factors that may endanger the achievement of predetermined objectives, and the quality of managerial decisions condition the progress and viability of any enterprise. Therefore, one of the principal characteristics of a successful manager is his ability to adopt the most optimal decisions of high quality. The quality of managerial decisions are conditioned by the manager’s general level of education and specialization, the manner in which they are preoccupied to assimilate the latest information and innovations in the domain of management’s theory and practice and the applying of modern managerial methods and techniques in the activity of management. We are presenting below the analysis of decision problems in hazardous conditions in terms of Bayesian theory – a theory that uses the probabilistic calculus.
Bayesian demography 250 years after Bayes.
Bijak, Jakub; Bryant, John
2016-01-01
Bayesian statistics offers an alternative to classical (frequentist) statistics. It is distinguished by its use of probability distributions to describe uncertain quantities, which leads to elegant solutions to many difficult statistical problems. Although Bayesian demography, like Bayesian statistics more generally, is around 250 years old, only recently has it begun to flourish. The aim of this paper is to review the achievements of Bayesian demography, address some misconceptions, and make the case for wider use of Bayesian methods in population studies. We focus on three applications: demographic forecasts, limited data, and highly structured or complex models. The key advantages of Bayesian methods are the ability to integrate information from multiple sources and to describe uncertainty coherently. Bayesian methods also allow for including additional (prior) information next to the data sample. As such, Bayesian approaches are complementary to many traditional methods, which can be productively re-expressed in Bayesian terms. PMID:26902889
Bayesian demography 250 years after Bayes.
Bijak, Jakub; Bryant, John
2016-01-01
Bayesian statistics offers an alternative to classical (frequentist) statistics. It is distinguished by its use of probability distributions to describe uncertain quantities, which leads to elegant solutions to many difficult statistical problems. Although Bayesian demography, like Bayesian statistics more generally, is around 250 years old, only recently has it begun to flourish. The aim of this paper is to review the achievements of Bayesian demography, address some misconceptions, and make the case for wider use of Bayesian methods in population studies. We focus on three applications: demographic forecasts, limited data, and highly structured or complex models. The key advantages of Bayesian methods are the ability to integrate information from multiple sources and to describe uncertainty coherently. Bayesian methods also allow for including additional (prior) information next to the data sample. As such, Bayesian approaches are complementary to many traditional methods, which can be productively re-expressed in Bayesian terms.
International Nuclear Information System (INIS)
Nuclear Magnetic Relaxation Dispersion (NMRD) of protons was studied in the pentapeptide Met-enkephalin and the amino acids, which constitute it. Experiments were run by using high-resolution Nuclear Magnetic Resonance (NMR) in combination with fast field-cycling, thus enabling measuring NMRD curves for all individual protons. As in earlier works, Papers I–III, pronounced effects of intramolecular scalar spin-spin interactions, J-couplings, on spin relaxation were found. Notably, at low fields J-couplings tend to equalize the apparent relaxation rates within networks of coupled protons. In Met-enkephalin, in contrast to the free amino acids, there is a sharp increase in the proton T1-relaxation times at high fields due to the changes in the regime of molecular motion. The experimental data are in good agreement with theory. From modelling the relaxation experiments we were able to determine motional correlation times of different residues in Met-enkephalin with atomic resolution. This allows us to draw conclusions about preferential conformation of the pentapeptide in solution, which is also in agreement with data from two-dimensional NMR experiments (rotating frame Overhauser effect spectroscopy). Altogether, our study demonstrates that high-resolution NMR studies of magnetic field-dependent relaxation allow one to probe molecular mobility in biomolecules with atomic resolution
Dielectric and mechanical relaxation in isooctylcyanobiphenyl (8*OCB)
Pawlus, S.; Mierzwa, M.; Paluch, M.; Rzoska, S. J.; Roland, C. M.
2010-06-01
The dynamics of isooctylcyanobiphenyl (8*OCB) was characterized using dielectric and mechanical spectroscopies. This isomer of the liquid crystalline octylcyanobiphenyl (8OCB) vitrifies during cooling or on application of pressure, exhibiting the typical features of glass-forming liquids: non-Debye relaxation function, non-Arrhenius temperature dependence of the relaxation times, τα, a dynamic crossover at T ~ 1.6Tg. This crossover is evidenced by changes in the behavior of both the peak shape and the temperature dependence of τα. The primary relaxation time at the crossover, 2 ns at ambient pressure, is the smallest value reported to date for any molecular liquid or polymer. Interestingly, at all temperatures below this crossover, τα and the dc conductivity remain coupled (i.e., conform to the Debye-Stokes-Einstein relation). Two secondary relaxations are observed in the glassy state, one of which is identified as the Johari-Goldstein process. Unlike the case for 8OCB, no liquid crystalline phase could be attained for 8*OCB, demonstrating that relatively small differences in chemical structure can effect substantial changes in the intermolecular potential.
Dielectric and mechanical relaxation in isooctylcyanobiphenyl (8*OCB)
Energy Technology Data Exchange (ETDEWEB)
Pawlus, S; Mierzwa, M; Paluch, M; Rzoska, S J [Institute of Physics, University of Silesia, Uniwersytecka 4, 40-007 Katowice (Poland); Roland, C M, E-mail: michal.mierzwa@us.edu.p [Chemistry Division, Naval Research Laboratory, Code 6120, Washington, DC 20375-5342 (United States)
2010-06-16
The dynamics of isooctylcyanobiphenyl (8*OCB) was characterized using dielectric and mechanical spectroscopies. This isomer of the liquid crystalline octylcyanobiphenyl (8OCB) vitrifies during cooling or on application of pressure, exhibiting the typical features of glass-forming liquids: non-Debye relaxation function, non-Arrhenius temperature dependence of the relaxation times, {tau}{sub {alpha}}, a dynamic crossover at T {approx} 1.6T{sub g}. This crossover is evidenced by changes in the behavior of both the peak shape and the temperature dependence of {tau}{sub {alpha}}. The primary relaxation time at the crossover, 2 ns at ambient pressure, is the smallest value reported to date for any molecular liquid or polymer. Interestingly, at all temperatures below this crossover, {tau}{sub {alpha}}and the dc conductivity remain coupled (i.e., conform to the Debye-Stokes-Einstein relation). Two secondary relaxations are observed in the glassy state, one of which is identified as the Johari-Goldstein process. Unlike the case for 8OCB, no liquid crystalline phase could be attained for 8*OCB, demonstrating that relatively small differences in chemical structure can effect substantial changes in the intermolecular potential.
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
An introduction to Gaussian Bayesian networks.
Grzegorczyk, Marco
2010-01-01
The extraction of regulatory networks and pathways from postgenomic data is important for drug -discovery and development, as the extracted pathways reveal how genes or proteins regulate each other. Following up on the seminal paper of Friedman et al. (J Comput Biol 7:601-620, 2000), Bayesian networks have been widely applied as a popular tool to this end in systems biology research. Their popularity stems from the tractability of the marginal likelihood of the network structure, which is a consistent scoring scheme in the Bayesian context. This score is based on an integration over the entire parameter space, for which highly expensive computational procedures have to be applied when using more complex -models based on differential equations; for example, see (Bioinformatics 24:833-839, 2008). This chapter gives an introduction to reverse engineering regulatory networks and pathways with Gaussian Bayesian networks, that is Bayesian networks with the probabilistic BGe scoring metric [see (Geiger and Heckerman 235-243, 1995)]. In the BGe model, the data are assumed to stem from a Gaussian distribution and a normal-Wishart prior is assigned to the unknown parameters. Gaussian Bayesian network methodology for analysing static observational, static interventional as well as dynamic (observational) time series data will be described in detail in this chapter. Finally, we apply these Bayesian network inference methods (1) to observational and interventional flow cytometry (protein) data from the well-known RAF pathway to evaluate the global network reconstruction accuracy of Bayesian network inference and (2) to dynamic gene expression time series data of nine circadian genes in Arabidopsis thaliana to reverse engineer the unknown regulatory network topology for this domain. PMID:20824469
Relaxation in finite fermion systems
International Nuclear Information System (INIS)
The derivation of a collision term extending time-dependent mean-field theories to describe the equilibration in finite fermion systems due to the residual interaction is discussed. Numerical results based on a relaxation ansatz for the collision term exhibit its qualitative effect. The equation for the time-dependent occupation numbers of the s.p. orbits is reduced to a non-linear partial differential equation which is solved analytically. In the equilibrium limit, a Fermi-type distribution for the occupation numbers is attained
Institute of Scientific and Technical Information of China (English)
DENG Jia-Jun; ZHAO Jian-Hua; BI Jing-Feng; ZHENG Yu-Hong; JIA Quan-Jie; NIU Zhi-Chuan; WU Xiao-Guang; ZHENG Hou-Zhi
2006-01-01
@@ Zincblende CrSb (zb-CrSb) layers with room-temperature ferromagnetism have been grown on relaxed and strained (In, Ga)As buffer layers epitaxially prepared on (001) GaAs substrates by molecular-beam epitaxy.
Structural relaxation of acridine orange dimer in bulk water and inside a single live lung cell
Chowdhury, Rajdeep; Nandi, Somen; Halder, Ritaban; Jana, Biman; Bhattacharyya, Kankan
2016-02-01
Structural relaxation of the acridine orange (AO) dimer in bulk water and inside a single live lung cell is studied using time resolved confocal microscopy and molecular dynamics (MD) simulations. The emission maxima ( λem max ˜ 630 nm) of AO in a lung cancer cell (A549) and a non-cancer lung fibroblast cell (WI38) suggest that AO exists as a dimer inside the cell. Time-dependent red shift in emission maximum indicates dynamic relaxation of the AO dimer (in the excited state) with a time constant of 500-600 ps, both in bulk water and inside the cell. We have calculated the equilibrium relaxation dynamics of the AO dimer in the ground state using MD simulations and found a slow component of time scale ˜350 ps. The intra- and inter-molecular components of the total relaxation dynamics of the AO dimer reveal the presence of a slow component of the order of a few hundred picoseconds. Upon restricting intra-molecular dye dynamics by harmonic constraint between AO monomers, the slow component vanishes. Combining the experimental observations and MD simulation results, we ascribe the slow component of the dynamic relaxation of the AO dimer to the structural relaxation, namely, fluctuations in the distance between the two monomers and associated fluctuation in the number of water molecules.
Institute of Scientific and Technical Information of China (English)
Stefanie M. ICKERT-BOND; Catarina RYDIN; Susanne S. RENNER
2009-01-01
Ephedra comprises approximately 50 species, which are roughly equally distributed between the Old and New World deserts, but not in the intervening regions (amphitropical range). Great heterogeneity in the substitution rates of Gnetales (Ephedra, Gnetum, and Welwitschia) has made it difficult to infer the ages of the major divergence events in Ephedra, such as the timing of the Beringian disjunction in the genus and the entry into South America. Here, we use data from as many Gnetales species and genes as available from GenBank and from a recent study to investigate the timing of the major divergence events. Because of the tradeoff between the amount of missing data and taxon/gene sampling, we reduced the initial matrix of 265 accessions and 12 loci to 95 accessions and 10 loci, and further to 42 species (and 7736 aligned nucleotides) to achieve stationary distributions in the Bayesian molecular clock runs. Results from a relaxed clock with an uncorrelated rates model and fossil-based calibration reveal that New World species are monophyletic and diverged from their mostly Asian sister clade some 30 mya, fitting with many other Beringian disjunctions. The split between the single North American and the single South American clade occurred approximately 25 mya, well before the closure of the Panamanian Isthmus. Overall, the biogeographic history of Ephedra appears dominated by long-distance dispersal, but finer-scale studies are needed to test this hypothesis.
Divergence date estimation and a comprehensive molecular tree of extant cetaceans.
McGowen, Michael R; Spaulding, Michelle; Gatesy, John
2009-12-01
Cetaceans are remarkable among mammals for their numerous adaptations to an entirely aquatic existence, yet many aspects of their phylogeny remain unresolved. Here we merged 37 new sequences from the nuclear genes RAG1 and PRM1 with most published molecular data for the group (45 nuclear loci, transposons, mitochondrial genomes), and generated a supermatrix consisting of 42,335 characters. The great majority of these data have never been combined. Model-based analyses of the supermatrix produced a solid, consistent phylogenetic hypothesis for 87 cetacean species. Bayesian analyses corroborated odontocete (toothed whale) monophyly, stabilized basal odontocete relationships, and completely resolved branching events within Mysticeti (baleen whales) as well as the problematic speciose clade Delphinidae (oceanic dolphins). Only limited conflicts relative to maximum likelihood results were recorded, and discrepancies found in parsimony trees were very weakly supported. We utilized the Bayesian supermatrix tree to estimate divergence dates among lineages using relaxed-clock methods. Divergence estimates revealed rapid branching of basal odontocete lineages near the Eocene-Oligocene boundary, the antiquity of river dolphin lineages, a Late Miocene radiation of balaenopteroid mysticetes, and a recent rapid radiation of Delphinidae beginning approximately 10 million years ago. Our comprehensive, time-calibrated tree provides a powerful evolutionary tool for broad-scale comparative studies of Cetacea. PMID:19699809
Bayesian tomographic reconstruction of microsystems
Salem, Sofia Fekih; Vabre, Alexandre; Mohammad-Djafari, Ali
2007-11-01
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.
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.
Tactile length contraction as Bayesian inference.
Tong, Jonathan; Ngo, Vy; Goldreich, Daniel
2016-08-01
To perceive, the brain must interpret stimulus-evoked neural activity. This is challenging: The stochastic nature of the neural response renders its interpretation inherently uncertain. Perception would be optimized if the brain used Bayesian inference to interpret inputs in light of expectations derived from experience. Bayesian inference would improve perception on average but cause illusions when stimuli violate expectation. Intriguingly, tactile, auditory, and visual perception are all prone to length contraction illusions, characterized by the dramatic underestimation of the distance between punctate stimuli delivered in rapid succession; the origin of these illusions has been mysterious. We previously proposed that length contraction illusions occur because the brain interprets punctate stimulus sequences using Bayesian inference with a low-velocity expectation. A novel prediction of our Bayesian observer model is that length contraction should intensify if stimuli are made more difficult to localize. Here we report a tactile psychophysical study that tested this prediction. Twenty humans compared two distances on the forearm: a fixed reference distance defined by two taps with 1-s temporal separation and an adjustable comparison distance defined by two taps with temporal separation t ≤ 1 s. We observed significant length contraction: As t was decreased, participants perceived the two distances as equal only when the comparison distance was made progressively greater than the reference distance. Furthermore, the use of weaker taps significantly enhanced participants' length contraction. These findings confirm the model's predictions, supporting the view that the spatiotemporal percept is a best estimate resulting from a Bayesian inference process. PMID:27121574
Dimensionality reduction in Bayesian estimation algorithms
Directory of Open Access Journals (Sweden)
G. W. Petty
2013-03-01
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.
Tactile length contraction as Bayesian inference.
Tong, Jonathan; Ngo, Vy; Goldreich, Daniel
2016-08-01
To perceive, the brain must interpret stimulus-evoked neural activity. This is challenging: The stochastic nature of the neural response renders its interpretation inherently uncertain. Perception would be optimized if the brain used Bayesian inference to interpret inputs in light of expectations derived from experience. Bayesian inference would improve perception on average but cause illusions when stimuli violate expectation. Intriguingly, tactile, auditory, and visual perception are all prone to length contraction illusions, characterized by the dramatic underestimation of the distance between punctate stimuli delivered in rapid succession; the origin of these illusions has been mysterious. We previously proposed that length contraction illusions occur because the brain interprets punctate stimulus sequences using Bayesian inference with a low-velocity expectation. A novel prediction of our Bayesian observer model is that length contraction should intensify if stimuli are made more difficult to localize. Here we report a tactile psychophysical study that tested this prediction. Twenty humans compared two distances on the forearm: a fixed reference distance defined by two taps with 1-s temporal separation and an adjustable comparison distance defined by two taps with temporal separation t ≤ 1 s. We observed significant length contraction: As t was decreased, participants perceived the two distances as equal only when the comparison distance was made progressively greater than the reference distance. Furthermore, the use of weaker taps significantly enhanced participants' length contraction. These findings confirm the model's predictions, supporting the view that the spatiotemporal percept is a best estimate resulting from a Bayesian inference process.
MAP estimators and their consistency in Bayesian nonparametric inverse problems
Dashti, M.
2013-09-01
We consider the inverse problem of estimating an unknown function u from noisy measurements y of a known, possibly nonlinear, map applied to u. We adopt a Bayesian approach to the problem and work in a setting where the prior measure is specified as a Gaussian random field μ0. We work under a natural set of conditions on the likelihood which implies the existence of a well-posed posterior measure, μy. Under these conditions, we show that the maximum a posteriori (MAP) estimator is well defined as the minimizer of an Onsager-Machlup functional defined on the Cameron-Martin space of the prior; thus, we link a problem in probability with a problem in the calculus of variations. We then consider the case where the observational noise vanishes and establish a form of Bayesian posterior consistency for the MAP estimator. We also prove a similar result for the case where the observation of can be repeated as many times as desired with independent identically distributed noise. The theory is illustrated with examples from an inverse problem for the Navier-Stokes equation, motivated by problems arising in weather forecasting, and from the theory of conditioned diffusions, motivated by problems arising in molecular dynamics. © 2013 IOP Publishing Ltd.
MAP estimators and their consistency in Bayesian nonparametric inverse problems
Dashti, M.; Law, K. J. H.; Stuart, A. M.; Voss, J.
2013-09-01
We consider the inverse problem of estimating an unknown function u from noisy measurements y of a known, possibly nonlinear, map {G} applied to u. We adopt a Bayesian approach to the problem and work in a setting where the prior measure is specified as a Gaussian random field 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 {G}(u) can be repeated as many times as desired with independent identically distributed noise. The theory is illustrated with examples from an inverse problem for the Navier-Stokes equation, motivated by problems arising in weather forecasting, and from the theory of conditioned diffusions, motivated by problems arising in molecular dynamics.
Dielectric and specific heat relaxations in vapor deposited glycerol.
Kasina, A; Putzeys, T; Wübbenhorst, M
2015-12-28
Recently [S. Capponi, S. Napolitano, and M. Wübbenhorst, Nat. Commun. 3, 1233 (2012)], vapor deposited glasses of glycerol have been found to recover their super-cooled liquid state via a metastable, ordered liquid (MROL) state characterized by a tremendously enhanced dielectric strength along with a slow-down of the relaxation rate of the structural relaxation. To study the calorimetric signature of this phenomenon, we have implemented a chip-based, differential AC calorimeter in an organic molecular beam deposition setup, which allows the simultaneous measurement of dielectric relaxations via interdigitated comb electrodes and specific heat relaxation spectra during deposition and as function of the temperature. Heating of the as-deposited glass just above the bulk Tg and subsequent cooling/reheating revealed a step-wise increase in cp by in total 9%, indicating unambiguously that glycerol, through slow vapour deposition, forms a thermodynamically stable glass, which has a specific heat as low as that of crystalline glycerol. Moreover, these glasses were found to show excellent kinetic stability as well as evidenced by both a high onset-temperature and quasi-isothermal recovery measurements at -75 °C. The second goal of the study was to elucidate the impact of the MROL state on the specific heat and its relaxation to the super-cooled state. Conversion of "MROL glycerol" to its "normal" (ordinary liquid, OL) state revealed a second, small (∼2%) increase of the glassy cp, a little gain (crystallisation and reorganisation effects, which give rise to pronounced out-of phase components of the specific heat at higher temperatures. PMID:26723689
Improving standard practices for prediction in ungauged basins: Bayesian approach
Prieto, Cristina; Le-Vine, Nataliya; García, Eduardo; Medina, Raúl
2015-04-01
In hydrological modelling, the prediction of flows in ungauged basins is still a defiance. Among the different alternatives to quantify and reduce the uncertainty in the predictions, a Bayesian framework has proven to be advantageous. This framework allows flow prediction in ungauged basins based on regionalised hydrological indices. Being grounded on probability theory, the procedure requires a number of assumptions and decisions to be made. Among the most important ones are 1) selection of representative hydrological signatures, 2) selection of regionalization model functional form, and 3) a 'perfect' model/ input assumption. The contribution of this research is to address these three assumptions. First, to reduce an extensive set of available hydrological signatures we select a compact orthogonal set of information pieces using Principal Component Analysis. This advances the standard practice of semi-empirical selection of individual hydrological signatures. Second, we use functional-form-assumption-free Random Forests to regionalize the selected information. This allows the traditional assumption of linear regression between catchment properties and characteristics of hydrological response to be relaxes. And third, we propose utilizing non-traditional metrics to flag-up possible model/ input errors: Bayes' Factor and a newly-proposed 'Suitability' test. This addresses the typical non-realistic assumption that model is 'perfect' and the input is noise-free. The proposed methodological developments are illustrated for the empirical challenge of flow prediction in rivers in Northern Spain.
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.
Internal magnetic relaxation in levitation superconductors
Smolyak, B M; Ermakov, G V
2001-01-01
Effect of arresting levitation relaxation, appearing during reverse magnetization of YBaCuO superconducting ceramics, was detected. At bipolar magnetization magnetic moment of a sample remains invariable. Internal magnetic relaxation occurs, in the course of which magnetic flux is redistributed inside the sample. As a result the state of filed at the sample boundary does not change and full force acting on the system of closed currents remains constant. A formula for calculating the time of internal relaxation is provided
Exploiting Semidefinite Relaxations in Constraint Programming
van Hoeve, Willem Jan
2004-01-01
Constraint programming uses enumeration and search tree pruning to solve combinatorial optimization problems. In order to speed up this solution process, we investigate the use of semidefinite relaxations within constraint programming. In principle, we use the solution of a semidefinite relaxation to guide the traversal of the search tree, using a limited discrepancy search strategy. Furthermore, a semidefinite relaxation produces a bound for the solution value, which is used to prune parts o...
Motional Spin Relaxation in Large Electric Fields
Schmid, Riccardo; Plaster, B; Filippone, B.W.
2008-01-01
We discuss the precession of spin-polarized Ultra Cold Neutrons (UCN) and $^{3}$He atoms in uniform and static magnetic and electric fields and calculate the spin relaxation effects from motional $v\\times E$ magnetic fields. Particle motion in an electric field creates a motional $v\\times E$ magnetic field, which when combined with collisions, produces variations of the total magnetic field and results in spin relaxation of neutron and $^{3}$He samples. The spin relaxation times $T_{1}$ (long...
Debye relaxation in high magnetic fields
Brooks, J. S.; Vasic, R.; Kismarahardja, A.; Steven, E.; Tokumoto, T.; Schlottmann, P.; Kelly, S.
2008-01-01
Dielectric relaxation is universal in characterizing polar liquids and solids, insulators, and semiconductors, and the theoretical models are well developed. However, in high magnetic fields, previously unknown aspects of dielectric relaxation can be revealed and exploited. Here, we report low temperature dielectric relaxation measurements in lightly doped silicon in high dc magnetic fields B both parallel and perpendicular to the applied ac electric field E. For B//E, we observe a temperatur...
Bayesian Methods for Radiation Detection and Dosimetry
Groer, Peter G
2002-01-01
We performed work in three areas: radiation detection, external and internal radiation dosimetry. In radiation detection we developed Bayesian techniques to estimate the net activity of high and low activity radioactive samples. These techniques have the advantage that the remaining uncertainty about the net activity is described by probability densities. Graphs of the densities show the uncertainty in pictorial form. Figure 1 below demonstrates this point. We applied stochastic processes for a method to obtain Bayesian estimates of 222Rn-daughter products from observed counting rates. In external radiation dosimetry we studied and developed Bayesian methods to estimate radiation doses to an individual with radiation induced chromosome aberrations. We analyzed chromosome aberrations after exposure to gammas and neutrons and developed a method for dose-estimation after criticality accidents. The research in internal radiation dosimetry focused on parameter estimation for compartmental models from observed comp...
Adaptive approximate Bayesian computation for complex models
Lenormand, Maxime; Deffuant, Guillaume
2011-01-01
Approximate Bayesian computation (ABC) is a family of computational techniques in Bayesian statistics. These techniques allow to fit a model to data without relying on the computation of the model likelihood. They instead require to simulate a large number of times the model to be fitted. A number of refinements to the original rejection-based ABC scheme have been proposed, including the sequential improvement of posterior distributions. This technique allows to decrease the number of model simulations required, but it still presents several shortcomings which are particularly problematic for costly to simulate complex models. We here provide a new algorithm to perform adaptive approximate Bayesian computation, which is shown to perform better on both a toy example and a complex social model.
Learning Bayesian Networks from Correlated Data
Bae, Harold; Monti, Stefano; Montano, Monty; Steinberg, Martin H.; Perls, Thomas T.; Sebastiani, Paola
2016-05-01
Bayesian networks are probabilistic models that represent complex distributions in a modular way and have become very popular in many fields. There are many methods to build Bayesian networks from a random sample of independent and identically distributed observations. However, many observational studies are designed using some form of clustered sampling that introduces correlations between observations within the same cluster and ignoring this correlation typically inflates the rate of false positive associations. We describe a novel parameterization of Bayesian networks that uses random effects to model the correlation within sample units and can be used for structure and parameter learning from correlated data without inflating the Type I error rate. We compare different learning metrics using simulations and illustrate the method in two real examples: an analysis of genetic and non-genetic factors associated with human longevity from a family-based study, and an example of risk factors for complications of sickle cell anemia from a longitudinal study with repeated measures.
Bayesian Fusion of Multi-Band Images
Wei, Qi; Tourneret, Jean-Yves
2013-01-01
In this paper, a Bayesian fusion technique for remotely sensed multi-band images is presented. The observed images are related to the high spectral and high spatial resolution image to be recovered through physical degradations, e.g., spatial and spectral blurring and/or subsampling defined by the sensor characteristics. The fusion problem is formulated within a Bayesian estimation framework. An appropriate prior distribution exploiting geometrical consideration is introduced. To compute the Bayesian estimator of the scene of interest from its posterior distribution, a Markov chain Monte Carlo algorithm is designed to generate samples asymptotically distributed according to the target distribution. To efficiently sample from this high-dimension distribution, a Hamiltonian Monte Carlo step is introduced in the Gibbs sampling strategy. The efficiency of the proposed fusion method is evaluated with respect to several state-of-the-art fusion techniques. In particular, low spatial resolution hyperspectral and mult...
Bayesian Image Reconstruction Based on Voronoi Diagrams
Cabrera, G F; Hitschfeld, N
2007-01-01
We present a Bayesian Voronoi image reconstruction technique (VIR) for interferometric data. Bayesian analysis applied to the inverse problem allows us to derive the a-posteriori probability of a novel parameterization of interferometric images. We use a variable Voronoi diagram as our model in place of the usual fixed pixel grid. A quantization of the intensity field allows us to calculate the likelihood function and a-priori probabilities. The Voronoi image is optimized including the number of polygons as free parameters. We apply our algorithm to deconvolve simulated interferometric data. Residuals, restored images and chi^2 values are used to compare our reconstructions with fixed grid models. VIR has the advantage of modeling the image with few parameters, obtaining a better image from a Bayesian point of view.
Dynamic Bayesian Combination of Multiple Imperfect Classifiers
Simpson, Edwin; Psorakis, Ioannis; Smith, Arfon
2012-01-01
Classifier combination methods need to make best use of the outputs of multiple, imperfect classifiers to enable higher accuracy classifications. In many situations, such as when human decisions need to be combined, the base decisions can vary enormously in reliability. A Bayesian approach to such uncertain combination allows us to infer the differences in performance between individuals and to incorporate any available prior knowledge about their abilities when training data is sparse. In this paper we explore Bayesian classifier combination, using the computationally efficient framework of variational Bayesian inference. We apply the approach to real data from a large citizen science project, Galaxy Zoo Supernovae, and show that our method far outperforms other established approaches to imperfect decision combination. We go on to analyse the putative community structure of the decision makers, based on their inferred decision making strategies, and show that natural groupings are formed. Finally we present ...
Variational Bayesian Inference of Line Spectra
DEFF Research Database (Denmark)
Badiu, Mihai Alin; Hansen, Thomas Lundgaard; Fleury, Bernard Henri
2016-01-01
In this paper, we address the fundamental problem of line spectral estimation in a Bayesian framework. We target model order and parameter estimation via variational inference in a probabilistic model in which the frequencies are continuous-valued, i.e., not restricted to a grid; and the coeffici......In this paper, we address the fundamental problem of line spectral estimation in a Bayesian framework. We target model order and parameter estimation via variational inference in a probabilistic model in which the frequencies are continuous-valued, i.e., not restricted to a grid......; and the coefficients are governed by a Bernoulli-Gaussian prior model turning model order selection into binary sequence detection. Unlike earlier works which retain only point estimates of the frequencies, we undertake a more complete Bayesian treatment by estimating the posterior probability density functions (pdfs...
Event generator tuning using Bayesian optimization
Ilten, Philip; Yang, Yunjie
2016-01-01
Monte Carlo event generators contain a large number of parameters that must be determined by comparing the output of the generator with experimental data. Generating enough events with a fixed set of parameter values to enable making such a comparison is extremely CPU intensive, which prohibits performing a simple brute-force grid-based tuning of the parameters. Bayesian optimization is a powerful method designed for such black-box tuning applications. In this article, we show that Monte Carlo event generator parameters can be accurately obtained using Bayesian optimization and minimal expert-level physics knowledge. A tune of the PYTHIA 8 event generator using $e^+e^-$ events, where 20 parameters are optimized, can be run on a modern laptop in just two days. Combining the Bayesian optimization approach with expert knowledge should enable producing better tunes in the future, by making it faster and easier to study discrepancies between Monte Carlo and experimental data.
Hessian PDF reweighting meets the Bayesian methods
Paukkunen, Hannu
2014-01-01
We discuss the Hessian PDF reweighting - a technique intended to estimate the effects that new measurements have on a set of PDFs. The method stems straightforwardly from considering new data in a usual $\\chi^2$-fit and it naturally incorporates also non-zero values for the tolerance, $\\Delta\\chi^2>1$. In comparison to the contemporary Bayesian reweighting techniques, there is no need to generate large ensembles of PDF Monte-Carlo replicas, and the observables need to be evaluated only with the central and the error sets of the original PDFs. In spite of the apparently rather different methodologies, we find that the Hessian and the Bayesian techniques are actually equivalent if the $\\Delta\\chi^2$ criterion is properly included to the Bayesian likelihood function that is a simple exponential.
A Large Sample Study of the Bayesian Bootstrap
Lo, Albert Y.
1987-01-01
An asymptotic justification of the Bayesian bootstrap is given. Large-sample Bayesian bootstrap probability intervals for the mean, the variance and bands for the distribution, the smoothed density and smoothed rate function are also provided.
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.
Dielectric Relaxation of Water: Theory and Experiment
International Nuclear Information System (INIS)
We have studied the hydrogen bond dynamics and methods for evaluation of probability and relaxation time for hydrogen bond network. Further, dielectric relaxation time has been calculated by using a diagonalization procedure by obtaining eigen values (inverse of relaxation time) of a master equation framed on the basis of Fokker-Planck equations. Microwave cavity spectrometer has been described to make measurements of relaxation time. Slater's perturbation equations are given for the analysis of the data. A comparison of theoretical and experimental data shows that there is a need for improvements in the theoretical model and experimental techniques to provide exact information about structural properties of water. (author)
Relaxation and Visualization Strategies for Story Telling
Institute of Scientific and Technical Information of China (English)
冯灵林
2012-01-01
The importance of training students to tell or retell story is self - evident for mastering English language. The following activity introduces relaxation and visualization strategies for story telling.
Temperature relaxation in dense plasma mixtures
Faussurier, Gérald; Blancard, Christophe
2016-09-01
We present a model to calculate temperature-relaxation rates in dense plasma mixtures. The electron-ion relaxation rates are calculated using an average-atom model and the ion-ion relaxation rates by the Landau-Spitzer approach. This method allows the study of the temperature relaxation in many-temperature electron-ion and ion-ion systems such as those encountered in inertial confinement fusion simulations. It is of interest for general nonequilibrium thermodynamics dealing with energy flows between various systems and should find broad use in present high energy density experiments.
Length Scales in Bayesian Automatic Adaptive Quadrature
Directory of Open Access Journals (Sweden)
Adam Gh.
2016-01-01
Full Text Available Two conceptual developments in the Bayesian automatic adaptive quadrature approach to the numerical solution of one-dimensional Riemann integrals [Gh. Adam, S. Adam, Springer LNCS 7125, 1–16 (2012] are reported. First, it is shown that the numerical quadrature which avoids the overcomputing and minimizes the hidden floating point loss of precision asks for the consideration of three classes of integration domain lengths endowed with specific quadrature sums: microscopic (trapezoidal rule, mesoscopic (Simpson rule, and macroscopic (quadrature sums of high algebraic degrees of precision. Second, sensitive diagnostic tools for the Bayesian inference on macroscopic ranges, coming from the use of Clenshaw-Curtis quadrature, are derived.
Bayesian 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
Bayesian Optimisation Algorithm for Nurse Scheduling
Li, Jingpeng
2008-01-01
Our research has shown that schedules can be built mimicking a human scheduler by using a set of rules that involve domain knowledge. This chapter presents a Bayesian Optimization Algorithm (BOA) for the nurse scheduling problem that chooses such suitable scheduling rules from a set for each nurses assignment. Based on the idea of using probabilistic models, the BOA builds a Bayesian network for the set of promising solutions and samples these networks to generate new candidate solutions. Computational results from 52 real data instances demonstrate the success of this approach. It is also suggested that the learning mechanism in the proposed algorithm may be suitable for other scheduling problems.
A Bayesian Analysis of Spectral ARMA Model
Directory of Open Access Journals (Sweden)
Manoel I. Silvestre Bezerra
2012-01-01
Full Text Available Bezerra et al. (2008 proposed a new method, based on Yule-Walker equations, to estimate the ARMA spectral model. In this paper, a Bayesian approach is developed for this model by using the noninformative prior proposed by Jeffreys (1967. The Bayesian computations, simulation via Markov Monte Carlo (MCMC is carried out and characteristics of marginal posterior distributions such as Bayes estimator and confidence interval for the parameters of the ARMA model are derived. Both methods are also compared with the traditional least squares and maximum likelihood approaches and a numerical illustration with two examples of the ARMA model is presented to evaluate the performance of the procedures.
A Bayesian Concept Learning Approach to Crowdsourcing
DEFF Research Database (Denmark)
Viappiani, Paolo Renato; Zilles, Sandra; Hamilton, Howard 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...... techniques, inference methods, and query selection strategies to assist a user charged with choosing a configuration that satisfies some (partially known) concept. Our model is able to simultaneously learn the concept definition and the types of the experts. We evaluate our model with simulations, showing...... that our Bayesian strategies are effective even in large concept spaces with many uninformative experts....
Comparison of the Bayesian and Frequentist Approach to the Statistics
Hakala, Michal
2015-01-01
The Thesis deals with introduction to Bayesian statistics and comparing Bayesian approach with frequentist approach to statistics. Bayesian statistics is modern branch of statistics which provides an alternative comprehensive theory to the frequentist approach. Bayesian concepts provides solution for problems not being solvable by frequentist theory. In the thesis are compared definitions, concepts and quality of statistical inference. The main interest is focused on a point estimation, an in...
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...
Bayesian reduced-order models for multiscale dynamical systems
Koutsourelakis, P S
2010-01-01
While existing mathematical descriptions can accurately account for phenomena at microscopic scales (e.g. molecular dynamics), these are often high-dimensional, stochastic and their applicability over macroscopic time scales of physical interest is computationally infeasible or impractical. In complex systems, with limited physical insight on the coherent behavior of their constituents, the only available information is data obtained from simulations of the trajectories of huge numbers of degrees of freedom over microscopic time scales. This paper discusses a Bayesian approach to deriving probabilistic coarse-grained models that simultaneously address the problems of identifying appropriate reduced coordinates and the effective dynamics in this lower-dimensional representation. At the core of the models proposed lie simple, low-dimensional dynamical systems which serve as the building blocks of the global model. These approximate the latent, generating sources and parameterize the reduced-order dynamics. We d...
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 default Bayesian hypothesis test for ANOVA designs
R. Wetzels; R.P.P.P. Grasman; E.J. Wagenmakers
2012-01-01
This article presents a Bayesian hypothesis test for analysis of variance (ANOVA) designs. The test is an application of standard Bayesian methods for variable selection in regression models. We illustrate the effect of various g-priors on the ANOVA hypothesis test. The Bayesian test for ANOVA desig
A Gentle Introduction to Bayesian Analysis : Applications to Developmental Research
Van de Schoot, Rens; Kaplan, David; Denissen, Jaap; Asendorpf, Jens B.; Neyer, Franz J.; van Aken, Marcel A G
2014-01-01
Bayesian statistical methods are becoming ever more popular in applied and fundamental research. In this study a gentle introduction to Bayesian analysis is provided. It is shown under what circumstances it is attractive to use Bayesian estimation, and how to interpret properly the results. First, t
Bayesian Just-So Stories in Psychology and Neuroscience
Bowers, Jeffrey S.; Davis, Colin J.
2012-01-01
According to Bayesian theories in psychology and neuroscience, minds and brains are (near) optimal in solving a wide range of tasks. We challenge this view and argue that more traditional, non-Bayesian approaches are more promising. We make 3 main arguments. First, we show that the empirical evidence for Bayesian theories in psychology is weak.…
Two structural relaxations in protein hydration water and their dynamic crossovers.
Camisasca, G; De Marzio, M; Corradini, D; Gallo, P
2016-07-28
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. PMID:27475377
Vibrational relaxation in liquids: Comparisons between gas phase and liquid phase theories
International Nuclear Information System (INIS)
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
Individual organisms as units of analysis: Bayesian-clustering alternatives in population genetics.
Mank, Judith E; Avise, John C
2004-12-01
Population genetic analyses traditionally focus on the frequencies of alleles or genotypes in 'populations' that are delimited a priori. However, there are potential drawbacks of amalgamating genetic data into such composite attributes of assemblages of specimens: genetic information on individual specimens is lost or submerged as an inherent part of the analysis. A potential also exists for circular reasoning when a population's initial identification and subsequent genetic characterization are coupled. In principle, these problems are circumvented by some newer methods of population identification and individual assignment based on statistical clustering of specimen genotypes. Here we evaluate a recent method in this genre--Bayesian clustering--using four genotypic data sets involving different types of molecular markers in non-model organisms from nature. As expected, measures of population genetic structure (F(ST) and phiST) tended to be significantly greater in Bayesian a posteriori data treatments than in analyses where populations were delimited a priori. In the four biological contexts examined, which involved both geographic population structures and hybrid zones, Bayesian clustering was able to recover differentiated populations, and Bayesian assignments were able to identify likely population sources of specific individuals.
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...
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...
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 CONCLUS...
Relaxation-limited evaporation of globular clusters
van Putten, Maurice H P M
2011-01-01
Evaporative evolution of stellar clusters is shown to be relaxation limited when the number of stars satisfies $N>>N_c$, where $N_c\\simeq 1600$. For a Maxwell velocity distribution that extends beyond the escape velocity, this process is {\\em bright} in that the Kelvin-Helmholtz time scale, $f_H^{-1}t_{relax}$, is shorter than the Ambartsumian-Spitzer time scale, $f_N^{-1}t_{relax}$, where $f_H>f_N$ denote the fractional changes in total energy and number of stars per relaxation time, $t_{relax}$. The resulting evaporative lifetime $t_{ev}\\simeq 20.5 t_{relax}$ for isolated clusters is consistent with Fokker-Planck and N-body simulations, where $t_{relax}$ is expressed in terms of the half-mass radius. We calculate the grey body factor by averaging over the anisotropic perturbation of the potential barrier across the tidal sphere, and derive the tidal sensitivity ${d\\ln t_{ev}}/{dy}\\simeq -1.9$ to -0.7 as a function of the ratio $y$ of the virial-to-tidal radius. Relaxation limited evaporation applies to the ...
Analysis of sawtooth relaxation oscillations in tokamaks
International Nuclear Information System (INIS)
Sawtooth relaxation oscillations are analyzed using the Kadomtsev's disruption model and a thermal relaxation model. The sawtooth period is found to be very sensitive to the thermal conduction loss. Qualitative agreement between these calculations and the sawtooth period observed in several tokamaks is demonstrated
Windowing Waveform Relaxation of Initial Value Problems
Institute of Scientific and Technical Information of China (English)
Yao-lin Jiang
2006-01-01
We present a windowing technique of waveform relaxation for dynamic systems. An effective estimation on window length is derived by an iterative error expression provided here. Relaxation processes can be speeded up if one takes the windowing technique in advance. Numerical experiments are given to further illustrate the theoretical analysis.
Superparamagnetic relaxation of weakly interacting particles
DEFF Research Database (Denmark)
Mørup, Steen; Tronc, Elisabeth
1994-01-01
The influence of particle interactions on the superparamagnetic relaxation time has been studied by Mossbauer spectroscopy in samples of maghemite (gamma-Fe2O3) particles with different particle sizes and particle separations. It is found that the relaxation time decreases with decreasing particl...
Jones, Matt; Love, Bradley C
2011-08-01
The prominence of Bayesian modeling of cognition has increased recently largely because of mathematical advances in specifying and deriving predictions from complex probabilistic models. Much of this research aims to demonstrate that cognitive behavior can be explained from rational principles alone, without recourse to psychological or neurological processes and representations. We note commonalities between this rational approach and other movements in psychology - namely, Behaviorism and evolutionary psychology - that set aside mechanistic explanations or make use of optimality assumptions. Through these comparisons, we identify a number of challenges that limit the rational program's potential contribution to psychological theory. Specifically, rational Bayesian models are significantly unconstrained, both because they are uninformed by a wide range of process-level data and because their assumptions about the environment are generally not grounded in empirical measurement. The psychological implications of most Bayesian models are also unclear. Bayesian inference itself is conceptually trivial, but strong assumptions are often embedded in the hypothesis sets and the approximation algorithms used to derive model predictions, without a clear delineation between psychological commitments and implementational details. Comparing multiple Bayesian models of the same task is rare, as is the realization that many Bayesian models recapitulate existing (mechanistic level) theories. Despite the expressive power of current Bayesian models, we argue they must be developed in conjunction with mechanistic considerations to offer substantive explanations of cognition. We lay out several means for such an integration, which take into account the representations on which Bayesian inference operates, as well as the algorithms and heuristics that carry it out. We argue this unification will better facilitate lasting contributions to psychological theory, avoiding the pitfalls
Most frugal explanations in Bayesian networks
Kwisthout, J.H.P.
2015-01-01
Inferring the most probable explanation to a set of variables, given a partial observation of the remaining variables, is one of the canonical computational problems in Bayesian networks, with widespread applications in AI and beyond. This problem, known as MAP, is computationally intractable (NP-ha
Bayesian semiparametric dynamic Nelson-Siegel model
C. Cakmakli
2011-01-01
This paper proposes the Bayesian semiparametric dynamic Nelson-Siegel model where the density of the yield curve factors and thereby the density of the yields are estimated along with other model parameters. This is accomplished by modeling the error distributions of the factors according to a Diric
Von Neumann was not a Quantum Bayesian.
Stacey, Blake C
2016-05-28
Wikipedia has claimed for over 3 years now that John von Neumann was the 'first quantum Bayesian'. In context, this reads as stating that von Neumann inaugurated QBism, the approach to quantum theory promoted by Fuchs, Mermin and Schack. This essay explores how such a claim is, historically speaking, unsupported. PMID:27091166
Von Neumann Was Not a Quantum Bayesian
Blake C. Stacey
2014-01-01
Wikipedia has claimed for over three years now that John von Neumann was the "first quantum Bayesian." In context, this reads as stating that von Neumann inaugurated QBism, the approach to quantum theory promoted by Fuchs, Mermin and Schack. This essay explores how such a claim is, historically speaking, unsupported.
A Bayesian Approach to Interactive Retrieval
Tague, Jean M.
1973-01-01
A probabilistic model for interactive retrieval is presented. Bayesian statistical decision theory principles are applied: use of prior and sample information about the relationship of document descriptions to query relevance; maximization of expected value of a utility function, to the problem of optimally restructuring search strategies in an…
Bayesian regularization of diffusion tensor images
DEFF Research Database (Denmark)
Frandsen, Jesper; Hobolth, Asger; Østergaard, Leif;
2007-01-01
several directions. The measured diffusion coefficients and thereby the diffusion tensors are subject to noise, leading to possibly flawed representations of the three dimensional fibre bundles. In this paper we develop a Bayesian procedure for regularizing the diffusion tensor field, fully utilizing...
Inverse Problems in a Bayesian Setting
Matthies, Hermann G.
2016-02-13
In a Bayesian setting, inverse problems and uncertainty quantification (UQ)—the propagation of uncertainty through a computational (forward) model—are strongly connected. In the form of conditional expectation the Bayesian update becomes computationally attractive. We give a detailed account of this approach via conditional approximation, various approximations, and the construction of filters. Together with a functional or spectral approach for the forward UQ there is no need for time-consuming and slowly convergent Monte Carlo sampling. The developed sampling-free non-linear Bayesian update in form of a filter is derived from the variational problem associated with conditional expectation. This formulation in general calls for further discretisation to make the computation possible, and we choose a polynomial approximation. After giving details on the actual computation in the framework of functional or spectral approximations, we demonstrate the workings of the algorithm on a number of examples of increasing complexity. At last, we compare the linear and nonlinear Bayesian update in form of a filter on some examples.
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.
Bayesian Vector Autoregressions with Stochastic Volatility
Uhlig, H.F.H.V.S.
1996-01-01
This paper proposes a Bayesian approach to a vector autoregression with stochastic volatility, where the multiplicative evolution of the precision matrix is driven by a multivariate beta variate.Exact updating formulas are given to the nonlinear filtering of the precision matrix.Estimation of the au
Scaling Bayesian network discovery through incremental recovery
Castelo, J.R.; Siebes, A.P.J.M.
1999-01-01
Bayesian networks are a type of graphical models that, e.g., allow one to analyze the interaction among the variables in a database. A well-known problem with the discovery of such models from a database is the ``problem of high-dimensionality''. That is, the discovery of a network from a database w
A Bayesian Bootstrap for a Finite Population
Lo, Albert Y.
1988-01-01
A Bayesian bootstrap for a finite population is introduced; its small-sample distributional properties are discussed and compared with those of the frequentist bootstrap for a finite population. It is also shown that the two are first-order asymptotically equivalent.
Bayesian calibration for forensic age estimation.
Ferrante, Luigi; Skrami, Edlira; Gesuita, Rosaria; Cameriere, Roberto
2015-05-10
Forensic medicine is increasingly called upon to assess the age of individuals. Forensic age estimation is mostly required in relation to illegal immigration and identification of bodies or skeletal remains. A variety of age estimation methods are based on dental samples and use of regression models, where the age of an individual is predicted by morphological tooth changes that take place over time. From the medico-legal point of view, regression models, with age as the dependent random variable entail that age tends to be overestimated in the young and underestimated in the old. To overcome this bias, we describe a new full Bayesian calibration method (asymmetric Laplace Bayesian calibration) for forensic age estimation that uses asymmetric Laplace distribution as the probability model. The method was compared with three existing approaches (two Bayesian and a classical method) using simulated data. Although its accuracy was comparable with that of the other methods, the asymmetric Laplace Bayesian calibration appears to be significantly more reliable and robust in case of misspecification of the probability model. The proposed method was also applied to a real dataset of values of the pulp chamber of the right lower premolar measured on x-ray scans of individuals of known age. PMID:25645903
Exploiting structure in cooperative Bayesian games
F.A. Oliehoek; S. Whiteson; M.T.J. Spaan
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,
Perfect Bayesian equilibrium. Part II: epistemic foundations
Bonanno, Giacomo
2011-01-01
In a companion paper we introduced a general notion of perfect Bayesian equilibrium which can be applied to arbitrary extensive-form games. The essential ingredient of the proposed definition is the qualitative notion of AGM-consistency. In this paper we provide an epistemic foundation for AGM-consistency based on the AGM theory of belief revision.
Decision generation tools and Bayesian inference
Jannson, Tomasz; Wang, Wenjian; Forrester, Thomas; Kostrzewski, Andrew; Veeris, Christian; Nielsen, Thomas
2014-05-01
Digital Decision Generation (DDG) tools are important software sub-systems of Command and Control (C2) systems and technologies. In this paper, we present a special type of DDGs based on Bayesian Inference, related to adverse (hostile) networks, including such important applications as terrorism-related networks and organized crime ones.
Von Neumann Was Not a Quantum Bayesian
Stacey, Blake C
2014-01-01
Wikipedia has claimed for over two years now that John von Neumann was the "first quantum Bayesian." In context, this reads as stating that von Neumann inaugurated QBism, the approach to quantum theory promoted by Fuchs, Mermin and Schack. This essay explores how such a claim is, historically speaking, unsupported.
Bayesian calibration of car-following models
Van Hinsbergen, C.P.IJ.; Van Lint, H.W.C.; Hoogendoorn, S.P.; Van Zuylen, H.J.
2010-01-01
Recent research has revealed that there exist large inter-driver differences in car-following behavior such that different car-following models may apply to different drivers. This study applies Bayesian techniques to the calibration of car-following models, where prior distributions on each model p
Basics of Bayesian Learning - Basically Bayes
DEFF Research Database (Denmark)
Larsen, Jan
Tutorial presented at the IEEE Machine Learning for Signal Processing Workshop 2006, Maynooth, Ireland, September 8, 2006. The tutorial focuses on the basic elements of Bayesian learning and its relation to classical learning paradigms. This includes a critical discussion of the pros and cons...
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...
Bayesian Estimation Supersedes the "t" Test
Kruschke, John K.
2013-01-01
Bayesian estimation for 2 groups provides complete distributions of credible values for the effect size, group means and their difference, standard deviations and their difference, and the normality of the data. The method handles outliers. The decision rule can accept the null value (unlike traditional "t" tests) when certainty in the estimate is…
Bayesian Estimation of Thermonuclear Reaction Rates
Iliadis, Christian; Coc, Alain; Timmes, Frank; Starrfield, Sumner
2016-01-01
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 in the past to this problem, 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 extra-solar planets, gravitational waves, and type Ia supernovae. However, nuclear physics, in particular, has been slow to adopt Bayesian methods. We present the first 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 d(p,$\\gamma$)$^3$He, $^3$He($^3$He,2p)$^4$He, and $^3$He($\\alpha$,$\\gamma$)$^7$Be reactions,...
Bayesian analysis of Markov point processes
DEFF Research Database (Denmark)
Berthelsen, Kasper Klitgaard; Møller, Jesper
2006-01-01
Recently Møller, Pettitt, Berthelsen and Reeves introduced a new MCMC methodology for drawing samples from a posterior distribution when the likelihood function is only specified up to a normalising constant. We illustrate the method in the setting of Bayesian inference for Markov point processes...
Bayesian Averaging is Well-Temperated
DEFF Research Database (Denmark)
Hansen, Lars Kai
2000-01-01
Bayesian predictions are stochastic just like predictions of any other inference scheme that generalize from a finite sample. While a simple variational argument shows that Bayes averaging is generalization optimal given that the prior matches the teacher parameter distribution the situation...
Modelling crime linkage with Bayesian networks
J. de Zoete; M. Sjerps; D. Lagnado; N. Fenton
2015-01-01
When two or more crimes show specific similarities, such as a very distinct modus operandi, the probability that they were committed by the same offender becomes of interest. This probability depends on the degree of similarity and distinctiveness. We show how Bayesian networks can be used to model
Dynamics of Star Polymers in Fast Extensional Flow and Stress Relaxation
DEFF Research Database (Denmark)
Huang, Qian; Agostini, Serena; Hengeller, Ludovica;
2016-01-01
We confirm the observation from Ianniruberto and Marrucci [ Macromolecules 2013, 46, 267-275 ] that entangled melts of branched polystyrenes behave like linear polystyrenes in the steady state of fast extensional flow, by measuring a linear, an asymmetric star, and a symmetric star polystyrene...... with the same span molecular weight (180 kg/mol). We show that all three melts reach the same extensional steady-state viscosity in fast extensional flow (faster than the inverse Rouse time). We further measure stress relaxation following steady extensional flow for the three melts. We show that initially...... they relax in a similar way, most likely via arm retraction, at short time, but behave differently at long time due to both the length of the arm and the branch point. The terminal relaxation is described by a Doi and Edwards based model, i.e., considering pure orientational relaxation....
Effect of cure cycle on enthalpy relaxation and post shrinkage in neat epoxy and epoxy composites
DEFF Research Database (Denmark)
Jensen, Martin; Jakobsen, Johnny
2016-01-01
The effect of cure cycle on enthalpy relaxation and warpage is studied for both neat epoxy and glass/epoxy composites. An approach for determining the enthalpy relaxation in the matrix of composite materials combining modulated differential scanning calorimetry and thermogravimetry is presented....... The enthalpy relaxation is coupled to structural dimension changes upon reheating by performing modulated thermo mechanical analysis. The enthalpy relaxation is affected by the cooling rate and the presence of the fibrous reinforcement, but is unaffected by variation between a 1-stage and 2-stage cure cycle....... Enthalpy recovery is found to exert a minor impact on the sample dimension during reheating since a non-reversing shrinkage is observed during reheating. This shrinkage is ascribed to structural changes on molecular level in the specimen and it is inferred that samples with a high initial disorder only...
Effects of Periodic Temperature Changes on Stress Relaxation of Chemically Treated Wood
Institute of Scientific and Technical Information of China (English)
Xie Manhua; Zhao Guangjie
2004-01-01
In order to clarify the relationship between the microstructural changes and the rheological behaviors of four chemically treated woods (delignified wood, hemicellulose-removed wood, DMSO swollen and decrystallization treated wood), the stress relaxation of wood with three different moisture contents was determined during periodic temperature changes. The experimental results show that after wood relaxation for 4 h at 25 °C, the stress decays sharply when the temperature increases and 2 h later the stress recovers again when the temperature drops back to the original point. The additional stress relaxation, produced after temperature begins to increase, is mainly caused by the thermal swelling, molecular thermal movement and the break of a part of residual hydrogen bonds. The number of hydrogen bonds and the size and amount of cavities in various treated woods greatly affect the magnitude of the additional relaxed stress and the recovery stress.
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.
Anomalous enthalpy relaxation in vitreous silica
DEFF Research Database (Denmark)
Yue, Yuanzheng
2015-01-01
scans. It is known that the liquid fragility (i.e., the speed of the viscous slow-down of a supercooled liquid at its Tg during cooling) has impact on enthalpy relaxation in glass. Here, we find that vitreous silica (as a strong system) exhibits striking anomalies in both glass transition and enthalpy...... relaxation compared to fragile oxide systems. The anomalous enthalpy relaxation of vitreous silica is discovered by performing the hyperquenching-annealing-calorimetry experiments. We argue that the strong systems like vitreous silica and vitreous Germania relax in a structurally cooperative manner, whereas...... the fragile ones do in a structurally independent fashion. We discuss the origin of the anomalous enthalpy relaxation in the HQ vitreous silica....
Theoretical evaluation of bulk viscosity: Expression for relaxation time
Hossein Mohammad Zaheri, Ali; Srivastava, Sunita; Tankeshwar, K.
2007-10-01
A theoretical calculation of bulk viscosity has been carried out by deriving an expression for the relaxation time which appears in the formula for bulk viscosity derived by Okumura and Yonezawa. The expression involved a pair distribution function and interaction potential. Numerical results have been obtained over a wide range of densities and temperatures for Lennard-Jones fluids. It is found that our results provide a good description of bulk viscosity as has been judged by comparing the results with nonequilibrium molecular dynamics results. In addition, our results demonstrate the importance of the multiparticle correlation function.
Enhancement of Paramagnetic Relaxation by Photoexcited Gold Nanorods
Wen, Tao; Wamer, Wayne G.; Subczynski, Witold K.; Hou, Shuai; Wu, Xiaochun; Yin, Jun-Jie
2016-01-01
Electron spin resonance (ESR) spectroscopy was used to investigate the switchable, light-dependent effects of gold nanorods (GNRs) on paramagnetic properties of nitroxide spin probes. The photoexcited GNRs enhanced the spin-spin and spin-lattice relaxations of nitroxide spin probes. It was shown that molecular oxygen plays the key role in this process. Our results demonstrate that ESR is a powerful tool for investigating the events following photoexcitation of GNRs. The novel light-controlled effects observed for GNRs on paramagnetic properties and activities of surrounding molecules have a number of significant applications where oxygen sensing and oxygen activity is important. PMID:27071507
Computational statistics using the Bayesian Inference Engine
Weinberg, Martin D.
2013-09-01
This paper introduces the Bayesian Inference Engine (BIE), a general parallel, optimized software package for parameter inference and model selection. This package is motivated by the analysis needs of modern astronomical surveys and the need to organize and reuse expensive derived data. The BIE is the first platform for computational statistics designed explicitly to enable Bayesian update and model comparison for astronomical problems. Bayesian update is based on the representation of high-dimensional posterior distributions using metric-ball-tree based kernel density estimation. Among its algorithmic offerings, the BIE emphasizes hybrid tempered Markov chain Monte Carlo schemes that robustly sample multimodal posterior distributions in high-dimensional parameter spaces. Moreover, the BIE implements a full persistence or serialization system that stores the full byte-level image of the running inference and previously characterized posterior distributions for later use. Two new algorithms to compute the marginal likelihood from the posterior distribution, developed for and implemented in the BIE, enable model comparison for complex models and data sets. Finally, the BIE was designed to be a collaborative platform for applying Bayesian methodology to astronomy. It includes an extensible object-oriented and easily extended framework that implements every aspect of the Bayesian inference. By providing a variety of statistical algorithms for all phases of the inference problem, a scientist may explore a variety of approaches with a single model and data implementation. Additional technical details and download details are available from http://www.astro.umass.edu/bie. The BIE is distributed under the GNU General Public License.
Vibrational relaxation and energy transfer of matrix isolated HCl and DCl
Energy Technology Data Exchange (ETDEWEB)
Wiesenfeld, J.M.
1977-12-01
Vibrational kinetic and spectroscopic studies have been performed on matrix-isolated HCl and DCl between 9 and 20 K. Vibrational relaxation rates for v = 2 and v = 1 were measured by a tunable infrared laser-induced, time-resolved fluorescence technique. In an Ar matrix, vibrational decay times are faster than radiative and it is found that HCl relaxes about 35 times more rapidly than CCl, in spite of the fact that HCl must transfer more energy to the lattice than DCl. This result is explained by postulating that the rate-determining step for vibrational relaxation produces a highly rotationally excited guest in a V yield R step; rotational relaxation into lattice phonons follows rapidly. HCl v = 1, but not v = 2, excitation rapidly diffuses through the sample by a resonant dipole-dipole vibrational energy transfer process. Molecular complexes, and in particular the HCl dimer, relax too rapidly for direct observation, less than or approximately 1 ..mu..s, and act as energy sinks in the energy diffusion process. The temperature dependence for all these processes is weak--less than a factor of two between 9 and 20 K. Vibrational relaxation of HCl in N/sub 2/ and O/sub 2/ matrices is unobservable, presumably due to rapid V yield V transfer to the host. A V yield R binary collision model for relaxation in solids is successful in explaining the HCl(DCl)/Ar results as well as results of other experimenters. The model considers relaxation to be the result of ''collisions'' due to molecular motion in quantized lattice normal modes--gas phase potential parameters can fit the matrix kinetic data.
Vibrational relaxation and energy transfer of matrix isolated HCl and DCl
International Nuclear Information System (INIS)
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 N2 and O2 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
Relaxation and physical aging in network glasses: a review
Micoulaut, Matthieu
2016-06-01
Recent progress in the description of glassy relaxation and aging are reviewed for the wide class of network-forming materials such as GeO2, Ge x Se1‑x , silicates (SiO2–Na2O) or borates (B2O3–Li2O), all of which have an important usefulness in domestic, geological or optoelectronic applications. A brief introduction of the glass transition phenomenology is given, together with the salient features that are revealed both from theory and experiments. Standard experimental methods used for the characterization of the slowing down of the dynamics are reviewed. We then discuss the important role played by aspects of network topology and rigidity for the understanding of the relaxation of the glass transition, while also permitting analytical predictions of glass properties from simple and insightful models based on the network structure. We also emphasize the great utility of computer simulations which probe the dynamics at the molecular level, and permit the calculation of various structure-related functions in connection with glassy relaxation and the physics of aging which reveal the non-equilibrium nature of glasses. We discuss the notion of spatial variations of structure which leads to the concept of ‘dynamic heterogeneities’, and recent results in relation to this important topic for network glasses are also reviewed.
Brownian relaxation of an inelastic sphere in air
Bird, G. A.
2016-06-01
The procedures that are used to calculate the forces and moments on an aerodynamic body in the rarefied gas of the upper atmosphere are applied to a small sphere of the size of an aerosol particle at sea level. While the gas-surface interaction model that provides accurate results for macroscopic bodies may not be appropriate for bodies that are comprised of only about a thousand atoms, it provides a limiting case that is more realistic than the elastic model. The paper concentrates on the transfer of energy from the air to an initially stationary sphere as it acquires Brownian motion. Individual particle trajectories vary wildly, but a clear relaxation process emerges from an ensemble average over tens of thousands of trajectories. The translational and rotational energies in equilibrium Brownian motion are determined. Empirical relationships are obtained for the mean translational and rotational relaxation times, the mean initial power input to the particle, the mean rates of energy transfer between the particle and air, and the diffusivity. These relationships are functions of the ratio of the particle mass to an average air molecule mass and the Knudsen number, which is the ratio of the mean free path in the air to the particle diameter. The ratio of the molecular radius to the particle radius also enters as a correction factor. The implications of Brownian relaxation for the second law of thermodynamics are discussed.
Relaxation and physical aging in network glasses: a review
Micoulaut, Matthieu
2016-06-01
Recent progress in the description of glassy relaxation and aging are reviewed for the wide class of network-forming materials such as GeO2, Ge x Se1-x , silicates (SiO2-Na2O) or borates (B2O3-Li2O), all of which have an important usefulness in domestic, geological or optoelectronic applications. A brief introduction of the glass transition phenomenology is given, together with the salient features that are revealed both from theory and experiments. Standard experimental methods used for the characterization of the slowing down of the dynamics are reviewed. We then discuss the important role played by aspects of network topology and rigidity for the understanding of the relaxation of the glass transition, while also permitting analytical predictions of glass properties from simple and insightful models based on the network structure. We also emphasize the great utility of computer simulations which probe the dynamics at the molecular level, and permit the calculation of various structure-related functions in connection with glassy relaxation and the physics of aging which reveal the non-equilibrium nature of glasses. We discuss the notion of spatial variations of structure which leads to the concept of ‘dynamic heterogeneities’, and recent results in relation to this important topic for network glasses are also reviewed.
Universal Darwinism as a process of Bayesian inference
Campbell, John O
2016-01-01
Many of the mathematical frameworks describing natural selection are equivalent to Bayes Theorem, also known as Bayesian updating. By definition, a process of Bayesian Inference is one which involves a Bayesian update, so we may conclude that these frameworks describe natural selection as a process of Bayesian inference. Thus natural selection serves as a counter example to a widely-held interpretation that restricts Bayesian Inference to human mental processes (including the endeavors of statisticians). As Bayesian inference can always be cast in terms of (variational) free energy minimization, natural selection can be viewed as comprising two components: a generative model of an "experiment" in the external world environment, and the results of that "experiment" or the "surprise" entailed by predicted and actual outcomes of the "experiment". Minimization of free energy implies that the implicit measure of "surprise" experienced serves to update the generative model in a Bayesian manner. This description clo...
Structural relaxation and rheological response of a driven amorphous system.
Varnik, F
2006-10-28
The interplay between the structural relaxation and the rheological response of a simple amorphous system {a 80:20 binary Lennard-Jones mixture [W. Kob and H. C. Andersen, Phys. Rev. Lett. 73, 1376 (1994)]} is studied via molecular dynamics simulations. In the quiescent state, the model is well known for its sluggish dynamics and a two step relaxation of correlation functions at low temperatures. An ideal glass transition temperature of Tc=0.435 has been identified in the previous studies via the analysis of the system's dynamics in the framework of the mode coupling theory of the glass transition [W. Kob and H. C. Andersen, Phys. Rev. E 51, 4626 (1995)]. In the present work, we focus on the question whether a signature of this ideal glass transition can also be found in the case where the system's dynamics is driven by a shear motion. Indeed, the following distinction in the structural relaxation is found: In the supercooled state, the structural relaxation is dominated by the shear at relatively high shear rates gamma, whereas at sufficiently low gamma the (shear-independent) equilibrium relaxation is recovered. In contrast to this, the structural relaxation of a glass is always driven by shear. This distinct behavior of the correlation functions is also reflected in the rheological response. In the supercooled state, the shear viscosity eta decreases with increasing shear rate (shear thinning) at high shear rates, but then converges toward a constant as the gamma is decreased below a (temperature-dependent) threshold value. Below Tc, on the other hand, the shear viscosity grows as eta proportional, etax 1/gamma, suggesting a divergence at gamma=0. Thus, within the accessible observation time window, a transition toward a nonergodic state seems to occur in the driven glass as the driving force approaches zero. As to the flow curves (stress versus shear rate), a plateau forms at low shear rates in the glassy phase. A consequence of this stress plateau for
Graf, Daniel L; Jones, Hugh; Geneva, Anthony J; Pfeiffer, John M; Klunzinger, Michael W
2015-04-01
The freshwater mussel family Hyriidae (Mollusca: Bivalvia: Unionida) has a disjunct trans-Pacific distribution in Australasia and South America. Previous phylogenetic analyses have estimated the evolutionary relationships of the family and the major infra-familial taxa (Velesunioninae and Hyriinae: Hyridellini in Australia; Hyriinae: Hyriini, Castaliini, and Rhipidodontini in South America), but taxon and character sampling have been too incomplete to support a predictive classification or allow testing of biogeographical hypotheses. We sampled 30 freshwater mussel individuals representing the aforementioned hyriid taxa, as well as outgroup species representing the five other freshwater mussel families and their marine sister group (order Trigoniida). Our ingroup included representatives of all Australian genera. Phylogenetic relationships were estimated from three gene fragments (nuclear 28S, COI and 16S mtDNA) using maximum parsimony, maximum likelihood, and Bayesian inference, and we applied a Bayesian relaxed clock model calibrated with fossil dates to estimate node ages. Our analyses found good support for monophyly of the Hyriidae and the subfamilies and tribes, as well as the paraphyly of the Australasian taxa (Velesunioninae, (Hyridellini, (Rhipidodontini, (Castaliini, Hyriini)))). The Hyriidae was recovered as sister to a clade comprised of all other Recent freshwater mussel families. Our molecular date estimation supported Cretaceous origins of the major hyriid clades, pre-dating the Tertiary isolation of South America from Antarctica/Australia. We hypothesize that early diversification of the Hyriidae was driven by terrestrial barriers on Gondwana rather than marine barriers following disintegration of the super-continent.
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.
Directory of Open Access Journals (Sweden)
Harlow Timothy J
2005-01-01
Full Text Available Abstract Background Bayesian phylogenetic inference holds promise as an alternative to maximum likelihood, particularly for large molecular-sequence data sets. We have investigated the performance of Bayesian inference with empirical and simulated protein-sequence data under conditions of relative branch-length differences and model violation. Results With empirical protein-sequence data, Bayesian posterior probabilities provide more-generous estimates of subtree reliability than does the nonparametric bootstrap combined with maximum likelihood inference, reaching 100% posterior probability at bootstrap proportions around 80%. With simulated 7-taxon protein-sequence datasets, Bayesian posterior probabilities are somewhat more generous than bootstrap proportions, but do not saturate. Compared with likelihood, Bayesian phylogenetic inference can be as or more robust to relative branch-length differences for datasets of this size, particularly when among-sites rate variation is modeled using a gamma distribution. When the (known correct model was used to infer trees, Bayesian inference recovered the (known correct tree in 100% of instances in which one or two branches were up to 20-fold longer than the others. At ratios more extreme than 20-fold, topological accuracy of reconstruction degraded only slowly when only one branch was of relatively greater length, but more rapidly when there were two such branches. Under an incorrect model of sequence change, inaccurate trees were sometimes observed at less extreme branch-length ratios, and (particularly for trees with single long branches such trees tended to be more inaccurate. The effect of model violation on accuracy of reconstruction for trees with two long branches was more variable, but gamma-corrected Bayesian inference nonetheless yielded more-accurate trees than did either maximum likelihood or uncorrected Bayesian inference across the range of conditions we examined. Assuming an exponential
Electron spin relaxation can enhance the performance of a cryptochrome-based magnetic compass sensor
Kattnig, Daniel R.; Sowa, Jakub K.; Solov'yov, Ilia A.; Hore, P. J.
2016-06-01
The radical pair model of the avian magnetoreceptor relies on long-lived electron spin coherence. Dephasing, resulting from interactions of the spins with their fluctuating environment, is generally assumed to degrade the sensitivity of this compass to the direction of the Earth's magnetic field. Here we argue that certain spin relaxation mechanisms can enhance its performance. We focus on the flavin–tryptophan radical pair in cryptochrome, currently the only candidate magnetoreceptor molecule. Correlation functions for fluctuations in the distance between the two radicals in Arabidopsis thaliana cryptochrome 1 were obtained from molecular dynamics (MD) simulations and used to calculate the spin relaxation caused by modulation of the exchange and dipolar interactions. We find that intermediate spin relaxation rates afford substantial enhancements in the sensitivity of the reaction yields to an Earth-strength magnetic field. Supported by calculations using toy radical pair models, we argue that these enhancements could be consistent with the molecular dynamics and magnetic interactions in avian cryptochromes.
Evidence of slow Debye-like relaxation in the anti-inflammatory agent etoricoxib
Rams-Baron, M.; Wojnarowska, Z.; Dulski, M.; Ratuszna, A.; Paluch, M.
2015-08-01
The origin of Debye-like relaxation in some hydrogen-bonded liquids is a matter of hot debate over the past decade. While a relatively clear picture of the issue has been established for monohydroxy alcohols, the Debye-type dynamics in other glass-forming systems still remains a not fully understood phenomenon. In this paper we present the results of dielectric measurements performed in the frequency interval 10-1 to 109Hz , both in the supercooled and normal liquid state of etoricoxib anti-inflammatory agent. Our investigations reveal the presence of slow Debye-like relaxation with features similar to that found for another active pharmaceutical ingredient, ibuprofen. Our results provide a fresh insight into the molecular nature of Debye-type relaxation in H-bonded pharmaceutically relevant materials and thus may stimulate the academic community for further discussion concerning the molecular dynamics of hydrogen-bonded fluids in general.
Bayesian network learning for natural hazard assessments
Vogel, Kristin
2016-04-01
Even though quite different in occurrence and consequences, from a modelling perspective many natural hazards share similar properties and challenges. Their complex nature as well as lacking knowledge about their driving forces and potential effects make their analysis demanding. On top of the uncertainty about the modelling framework, inaccurate or incomplete event observations and the intrinsic randomness of the natural phenomenon add up to different interacting layers of uncertainty, which require a careful handling. Thus, for reliable natural hazard assessments it is crucial not only to capture and quantify involved uncertainties, but also to express and communicate uncertainties in an intuitive way. Decision-makers, who often find it difficult to deal with uncertainties, might otherwise return to familiar (mostly deterministic) proceedings. In the scope of the DFG research training group „NatRiskChange" we apply the probabilistic framework of Bayesian networks for diverse natural hazard and vulnerability studies. The great potential of Bayesian networks was already shown in previous natural hazard assessments. Treating each model component as random variable, Bayesian networks aim at capturing the joint distribution of all considered variables. Hence, each conditional distribution of interest (e.g. the effect of precautionary measures on damage reduction) can be inferred. The (in-)dependencies between the considered variables can be learned purely data driven or be given by experts. Even a combination of both is possible. By translating the (in-)dependences into a graph structure, Bayesian networks provide direct insights into the workings of the system and allow to learn about the underlying processes. Besides numerous studies on the topic, learning Bayesian networks from real-world data remains challenging. In previous studies, e.g. on earthquake induced ground motion and flood damage assessments, we tackled the problems arising with continuous variables
Vibrational and Rotational Energy Relaxation in Liquids
DEFF Research Database (Denmark)
Petersen, Jakob
Vibrational and rotational energy relaxation in liquids are studied by means of computer simulations. As a precursor for studying vibrational energy relaxation of a solute molecule subsequent to the formation of a chemical bond, the validity of the classical Bersohn-Zewail model for describing the...... qualitative agreement is found in both cases. Furthermore, the rotational energy relaxation of H2O in liquid water is studied via simulations and a power-and-work analysis. The mechanism of the energy transfer from the rotationally excited H2O molecule to its water neighbors is elucidated, i.e. the energy...
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.
Molecular mobility in glassy dispersions
Mehta, Mehak; McKenna, Gregory B.; Suryanarayanan, Raj
2016-05-01
Dielectric spectroscopy was used to characterize the structural relaxation in pharmaceutical dispersions containing nifedipine (NIF) and either poly(vinyl) pyrrolidone (PVP) or hydroxypropyl methylcellulose acetate succinate (HPMCAS). The shape of the dielectric response (permittivity versus log time) curve was observed to be independent of temperature. Thus, for the pure NIF as well as the dispersions, the validity of the time-temperature superposition principle was established. Furthermore, though the shape of the full dielectric response varied with polymer concentration, the regime related to the α- or structural relaxation was found to superimpose for the dispersions, though not with the response of the NIF itself. Hence, there is a limited time-temperature-concentration superposition for these systems as well. Therefore, in this polymer concentration range, calculation of long relaxation times in these glass-forming systems becomes possible. We found that strong drug-polymer hydrogen bonding interactions improved the physical stability (i.e., delayed crystallization) by reducing the molecular mobility. The strength of hydrogen bonding, structural relaxation time, and crystallization followed the order: NIF-PV P>NIF-HPMCAS>NIF. With an increase in polymer concentration, the relaxation times were longer indicating a decrease in molecular mobility. The temperature dependence of relaxation time, in other words fragility, was independent of polymer concentration. This is the first application of the superposition principle to characterize structural relaxation in glassy pharmaceutical dispersions.
Hydrogen sulfide and vascular relaxation
Institute of Scientific and Technical Information of China (English)
SUN Yan; TANG Chao-shu; DU Jun-bao; JIN Hong-fang
2011-01-01
Objective To review the vasorelaxant effects of hydrogen sulfide (H2S) in arterial rings in the cardiovascular system under both physiological and pathophysiological conditions and the possible mechanisms involved.Data sources The data in this review were obtained from Medline and Pubmed sources from 1997 to 2011 using the search terms "hydrogen sulfide" and ""vascular relaxation".Study selection Articles describing the role of hydrogen sulfide in the regulation of vascular activity and its vasorelaxant effects were selected.Results H2S plays an important role in the regulation of cardiovascular tone.The vasomodulatory effects of H2S depend on factors including concentration,species and tissue type.The H2S donor,sodium hydrosulfide (NarS),causes vasorelaxation of rat isolated aortic rings in a dose-dependent manner.This effect was more pronounced than that observed in pulmonary arterial rings.The expression of KATP channel proteins and mRNA in the aortic rings was increased compared with pulmonary artery rings.H2S is involved in the pathogenesis of a variety of cardiovascular diseases.Downregulation of the endogenous H2S pathway is an important factor in the pathogenesis of cardiovascular diseases.The vasorelaxant effects of H2S have been shown to be mediated by activation of KATP channels in vascular smooth muscle cells and via the induction of acidification due to activation of the CI/HCO3 exchanger.It is speculated that the mechanisms underlying the vasoconstrictive function of H2S in the aortic rings involves decreased NO production and inhibition of cAMP accumulation.Conclusion H2S is an important endogenous gasotransmitter in the cardiovascular system and acts as a modulator of vascular tone in the homeostatic regulation of blood pressure.
Time resolved scattering relaxation mechanisms of microcavity polaritons
Chaves, F.; Rodriguez, F. J.
2005-01-01
We study the polariton relaxation dynamics for different scattering mechanisms as: Phonon and electron scattering procesess. The relaxation polariton is obtained at very short times by solving the Boltzman equation. Instead of the well-known relaxation process by phonons, we show that the bottleneck effect relaxes to the ground state more efficiently at low pump power intensity when the electron relaxation process is included. In this way, we clearly demonstrate that different relaxation time...
“I think relax, relax and it flows a lot easier”: Exploring client-generated relax strategies
Directory of Open Access Journals (Sweden)
Dianne Cirone
2014-10-01
Full Text Available Background. Some adult stroke survivors participating in Cognitive Orientation to daily Occupational Performance (CO-OP treatment programs self-generated relax strategies that have not been explored in previous CO-OP publications. The objective of this study was to describe the process by which adults with stroke used relax strategies and to explore the outcomes associated with their use. Methods. Secondary analysis of transcripts of intervention sessions from five participants was conducted. Results. All five participants applied relax strategies after initially observing a breakdown in performance that was attributed to increased fatigue or tension. The relax strategies used by the participants during their occupations included general relaxation, physical modifications to reduce tension, mental preparation, and pacing. The application of these strategies seemed to result in improved skill performance, reduced fatigue, and transfer to other activities. Conclusion. The relax strategy warrants further investigation as a potentially important therapeutic tool to improve occupational performance in individuals who have had a stroke.
Guo, Yun-Nan; Ungur, Liviu; Granroth, Garrett E.; Powell, Annie K.; Wu, Chunji; Nagler, Stephen E.; Tang, Jinkui; Chibotaru, Liviu F.; Cui, Dongmei
2014-06-01
Single-molecule magnets are compounds that exhibit magnetic bistability purely of molecular origin. The control of anisotropy and suppression of quantum tunneling to obtain a comprehensive picture of the relaxation pathway manifold, is of utmost importance with the ultimate goal of slowing the relaxation dynamics within single-molecule magnets to facilitate their potential applications. Combined ab initio calculations and detailed magnetization dynamics studies reveal the unprecedented relaxation mediated via the second excited state within a new DyNCN system comprising a valence-localized carbon coordinated to a single dysprosium(III) ion. The essentially C2v symmetry of the DyIII ion results in a new relaxation mechanism, hitherto unknown for mononuclear DyIII complexes, opening new perspectives for means of enhancing the anisotropy contribution to the spin-relaxation barrier.
Ultrafast Librational Relaxation of H2O in Liquid Water
DEFF Research Database (Denmark)
Petersen, Jakob; Møller, Klaus Braagaard; Rey, Rossend;
2013-01-01
the excited H2O to its water neighbors, which occurs on a sub-100 fs time scale, to be followed in molecular detail, i.e., to determine which water molecules receive the energy and in which degrees of freedom. It is found that the dominant energy flow is to the four hydrogen-bonded water partners in the first......The ultrafast librational (hindered rotational) relaxation of a rotationally excited H2O molecule in pure liquid water is investigated by means of classical nonequilibrium molecular dynamics simulations and a power and work analysis. This analysis allows the mechanism of the energy transfer from...... hydration shell, dominated by those partners’ rotational motion, in a fairly symmetric fashion over the hydration shell. The minority component of the energy transfer, to these neighboring waters’ translational motion, exhibits an asymmetry in energy reception between hydrogen-bond-donating and -accepting...
Bayesian parameter estimation for effective field theories
Wesolowski, S; Furnstahl, R J; Phillips, D R; Thapaliya, A
2015-01-01
We present procedures based on Bayesian statistics for effective field theory (EFT) parameter estimation from data. The extraction of low-energy constants (LECs) is guided by theoretical expectations that supplement such information in a quantifiable way through the specification of Bayesian priors. A prior for natural-sized LECs reduces the possibility of overfitting, and leads to a consistent accounting of different sources of uncertainty. A set of diagnostic tools are developed that analyze the fit and ensure that the priors do not bias the EFT parameter estimation. The procedures are illustrated using representative model problems and the extraction of LECs for the nucleon mass expansion in SU(2) chiral perturbation theory from synthetic lattice data.
Applications of Bayesian spectrum representation in acoustics
Botts, Jonathan M.
This dissertation utilizes a Bayesian inference framework to enhance the solution of inverse problems where the forward model maps to acoustic spectra. A Bayesian solution to filter design inverts a acoustic spectra to pole-zero locations of a discrete-time filter model. Spatial sound field analysis with a spherical microphone array is a data analysis problem that requires inversion of spatio-temporal spectra to directions of arrival. As with many inverse problems, a probabilistic analysis results in richer solutions than can be achieved with ad-hoc methods. In the filter design problem, the Bayesian inversion results in globally optimal coefficient estimates as well as an estimate the most concise filter capable of representing the given spectrum, within a single framework. This approach is demonstrated on synthetic spectra, head-related transfer function spectra, and measured acoustic reflection spectra. The Bayesian model-based analysis of spatial room impulse responses is presented as an analogous problem with equally rich solution. The model selection mechanism provides an estimate of the number of arrivals, which is necessary to properly infer the directions of simultaneous arrivals. Although, spectrum inversion problems are fairly ubiquitous, the scope of this dissertation has been limited to these two and derivative problems. The Bayesian approach to filter design is demonstrated on an artificial spectrum to illustrate the model comparison mechanism and then on measured head-related transfer functions to show the potential range of application. Coupled with sampling methods, the Bayesian approach is shown to outperform least-squares filter design methods commonly used in commercial software, confirming the need for a global search of the parameter space. The resulting designs are shown to be comparable to those that result from global optimization methods, but the Bayesian approach has the added advantage of a filter length estimate within the same unified
Narrowband interference parameterization for sparse Bayesian recovery
Ali, Anum
2015-09-11
This paper addresses the problem of narrowband interference (NBI) in SC-FDMA systems by using tools from compressed sensing and stochastic geometry. The proposed NBI cancellation scheme exploits the frequency domain sparsity of the unknown signal and adopts a Bayesian sparse recovery procedure. This is done by keeping a few randomly chosen sub-carriers data free to sense the NBI signal at the receiver. As Bayesian recovery requires knowledge of some NBI parameters (i.e., mean, variance and sparsity rate), we use tools from stochastic geometry to obtain analytical expressions for the required parameters. Our simulation results validate the analysis and depict suitability of the proposed recovery method for NBI mitigation. © 2015 IEEE.
Bayesian networks for enterprise risk assessment
Bonafede, C E
2006-01-01
According to different typologies of activity and priority, risks can assume diverse meanings and it can be assessed in different ways. In general risk is measured in terms of a probability combination of an event (frequency) and its consequence (impact). To estimate the frequency and the impact (severity) historical data or expert opinions (either qualitative or quantitative data) are used. Moreover qualitative data must be converted in numerical values to be used in the model. In the case of enterprise risk assessment the considered risks are, for instance, strategic, operational, legal and of image, which many times are difficult to be quantified. So in most cases only expert data, gathered by scorecard approaches, are available for risk analysis. The Bayesian Network is a useful tool to integrate different information and in particular to study the risk's joint distribution by using data collected from experts. In this paper we want to show a possible approach for building a Bayesian networks in the parti...
Bayesianism and inference to the best explanation
Directory of Open Access Journals (Sweden)
Valeriano IRANZO
2008-01-01
Full Text Available Bayesianism and Inference to the best explanation (IBE are two different models of inference. Recently there has been some debate about the possibility of “bayesianizing” IBE. Firstly I explore several alternatives to include explanatory considerations in Bayes’s Theorem. Then I distinguish two different interpretations of prior probabilities: “IBE-Bayesianism” (IBE-Bay and “frequentist-Bayesianism” (Freq-Bay. After detailing the content of the latter, I propose a rule for assessing the priors. I also argue that Freq-Bay: (i endorses a role for explanatory value in the assessment of scientific hypotheses; (ii avoids a purely subjectivist reading of prior probabilities; and (iii fits better than IBE-Bayesianism with two basic facts about science, i.e., the prominent role played by empirical testing and the existence of many scientific theories in the past that failed to fulfil their promises and were subsequently abandoned.
QBism, the Perimeter of Quantum Bayesianism
Fuchs, Christopher A
2010-01-01
This article summarizes the Quantum Bayesian point of view of quantum mechanics, with special emphasis on the view's outer edges---dubbed QBism. QBism has its roots in personalist Bayesian probability theory, is crucially dependent upon the tools of quantum information theory, and most recently, has set out to investigate whether the physical world might be of a type sketched by some false-started philosophies of 100 years ago (pragmatism, pluralism, nonreductionism, and meliorism). Beyond conceptual issues, work at Perimeter Institute is focused on the hard technical problem of finding a good representation of quantum mechanics purely in terms of probabilities, without amplitudes or Hilbert-space operators. The best candidate representation involves a mysterious entity called a symmetric informationally complete quantum measurement. Contemplation of it gives a way of thinking of the Born Rule as an addition to the rules of probability theory, applicable when an agent considers gambling on the consequences of...
Distributed Bayesian Networks for User Modeling
DEFF Research Database (Denmark)
Tedesco, Roberto; Dolog, Peter; Nejdl, Wolfgang;
2006-01-01
The World Wide Web is a popular platform for providing eLearning applications to a wide spectrum of users. However – as users differ in their preferences, background, requirements, and goals – applications should provide personalization mechanisms. In the Web context, user models used...... by such adaptive applications are often partial fragments of an overall user model. The fragments have then to be collected and merged into a global user profile. In this paper we investigate and present algorithms able to cope with distributed, fragmented user models – based on Bayesian Networks – in the context...... of Web-based eLearning platforms. The scenario we are tackling assumes learners who use several systems over time, which are able to create partial Bayesian Networks for user models based on the local system context. In particular, we focus on how to merge these partial user models. Our merge mechanism...
Machine learning a Bayesian and optimization perspective
Theodoridis, Sergios
2015-01-01
This tutorial text gives a unifying perspective on machine learning by covering both probabilistic and deterministic approaches, which rely on optimization techniques, as well as Bayesian inference, which is based on a hierarchy of probabilistic models. The book presents the major machine learning methods as they have been developed in different disciplines, such as statistics, statistical and adaptive signal processing and computer science. Focusing on the physical reasoning behind the mathematics, all the various methods and techniques are explained in depth, supported by examples and problems, giving an invaluable resource to the student and researcher for understanding and applying machine learning concepts. The book builds carefully from the basic classical methods to the most recent trends, with chapters written to be as self-contained as possible, making the text suitable for different courses: pattern recognition, statistical/adaptive signal processing, statistical/Bayesian learning, as well as shor...
Bayesian image reconstruction: Application to emission tomography
Energy Technology Data Exchange (ETDEWEB)
Nunez, J.; Llacer, J.
1989-02-01
In this paper we propose a Maximum a Posteriori (MAP) method of image reconstruction in the Bayesian framework for the Poisson noise case. We use entropy to define the prior probability and likelihood to define the conditional probability. The method uses sharpness parameters which can be theoretically computed or adjusted, allowing us to obtain MAP reconstructions without the problem of the grey'' reconstructions associated with the pre Bayesian reconstructions. We have developed several ways to solve the reconstruction problem and propose a new iterative algorithm which is stable, maintains positivity and converges to feasible images faster than the Maximum Likelihood Estimate method. We have successfully applied the new method to the case of Emission Tomography, both with simulated and real data. 41 refs., 4 figs., 1 tab.
The Bayesian Who Knew Too Much
Benétreau-Dupin, Yann
2014-01-01
In several papers, John Norton has argued that Bayesianism cannot handle ignorance adequately due to its inability to distinguish between neutral and disconfirming evidence. He argued that this inability sows confusion in, e.g., anthropic reasoning in cosmology or the Doomsday argument, by allowing one to draw unwarranted conclusions from a lack of knowledge. Norton has suggested criteria for a candidate for representation of neutral support. Imprecise credences (families of credal probability functions) constitute a Bayesian-friendly framework that allows us to avoid inadequate neutral priors and better handle ignorance. The imprecise model generally agrees with Norton's representation of ignorance but requires that his criterion of self-duality be reformulated or abandoned
Software Health Management with Bayesian Networks
Mengshoel, Ole; Schumann, JOhann
2011-01-01
Most modern aircraft as well as other complex machinery is equipped with diagnostics systems for its major subsystems. During operation, sensors provide important information about the subsystem (e.g., the engine) and that information is used to detect and diagnose faults. Most of these systems focus on the monitoring of a mechanical, hydraulic, or electromechanical subsystem of the vehicle or machinery. Only recently, health management systems that monitor software have been developed. In this paper, we will discuss our approach of using Bayesian networks for Software Health Management (SWHM). We will discuss SWHM requirements, which make advanced reasoning capabilities for the detection and diagnosis important. Then we will present our approach to using Bayesian networks for the construction of health models that dynamically monitor a software system and is capable of detecting and diagnosing faults.
Learning Bayesian networks using genetic algorithm
Institute of Scientific and Technical Information of China (English)
Chen Fei; Wang Xiufeng; Rao Yimei
2007-01-01
A new method to evaluate the fitness of the Bayesian networks according to the observed data is provided. The main advantage of this criterion is that it is suitable for both the complete and incomplete cases while the others not.Moreover it facilitates the computation greatly. In order to reduce the search space, the notation of equivalent class proposed by David Chickering is adopted. Instead of using the method directly, the novel criterion, variable ordering, and equivalent class are combined,moreover the proposed mthod avoids some problems caused by the previous one. Later, the genetic algorithm which allows global convergence, lack in the most of the methods searching for Bayesian network is applied to search for a good model in thisspace. To speed up the convergence, the genetic algorithm is combined with the greedy algorithm. Finally, the simulation shows the validity of the proposed approach.
Bayesian Population Projections for the United Nations.
Raftery, Adrian E; Alkema, Leontine; Gerland, Patrick
2014-02-01
The United Nations regularly publishes projections of the populations of all the world's countries broken down by age and sex. These projections are the de facto standard and are widely used by international organizations, governments and researchers. Like almost all other population projections, they are produced using the standard deterministic cohort-component projection method and do not yield statements of uncertainty. We describe a Bayesian method for producing probabilistic population projections for most countries that the United Nations could use. It has at its core Bayesian hierarchical models for the total fertility rate and life expectancy at birth. We illustrate the method and show how it can be extended to address concerns about the UN's current assumptions about the long-term distribution of fertility. The method is implemented in the R packages bayesTFR, bayesLife, bayesPop and bayesDem.