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
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
Relaxation oscillations in optically pumped molecular lasers
Lawandy, N. M.; Koepf, G. A.
1980-01-01
The observation of relaxation oscillations in both the (C-13)H3F and (C-12)H3F optically pumped lasers is reported. Expressions are derived for the oscillation frequency and its temperature and pressure dependences using a four-level rate equation model. Excellent agreement between measured frequencies and the theory presented is observed. Models are considered for using this phenomenon to determine the rotational and vibrational relaxation mechanisms of the laser gases.
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.
Accelerating convergence of molecular dynamics-based structural relaxation
DEFF Research Database (Denmark)
Christensen, Asbjørn
2005-01-01
We describe strategies to accelerate the terminal stage of molecular dynamics (MD)based relaxation algorithms, where a large fraction of the computational resources are used. First, we analyze the qualitative and quantitative behavior of the QuickMin family of MD relaxation algorithms and explore...... the influence of spectral properties and dimensionality of the molecular system on the algorithm efficiency. We test two algorithms, the MinMax and Lanczos, for spectral estimation from an MD trajectory, and use this to derive a practical scheme of time step adaptation in MD relaxation algorithms to...
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
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
The molecular basis of anesthesia studied by solvent relaxation technique
Czech Academy of Sciences Publication Activity Database
Barucha-Kraszewska, Justyna; Przybylo, M.; Langner, M.; Hof, Martin
Regensburg : Digital Print Group O. Schimek GmbH, 2007. s. 262-262. [Conference on Methods and Applications of Fluorescence /10./. 09.09.2007-12.09.2007, Salzburg] Institutional research plan: CEZ:AV0Z40400503 Keywords : solvent relaxation * molecular basis Subject RIV: CF - Physical ; Theoretical Chemistry
Rotational relaxation of molecular hydrogen at moderate temperatures
Sharma, S. P.
1994-01-01
Using a coupled rotation-vibration-dissociation model the rotational relaxation times for molecular hydrogen as a function of final temperature (500-5000 K), in a hypothetical scenario of sudden compression, are computed. The theoretical model is based on a master equation solver. The bound-bound and bound-free transition rates have been computed using a quasiclassical trajectory method. A review of the available experimental data on the rotational relaxation of hydrogen is presented, with a critical overview of the method of measurements and data reduction, including the sources of errors. These experimental data are then compared with the computed results.
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.
Polymer degradation and molecular relaxation during accelerated weathering of coatings
Fernando, B. Malcolm Dilhan
2011-12-01
A model polyester-urethane coating similar to those on USAF aircraft was the focus in this research. It was studied for physical property changes during accelerated weathering. Isothermal aging and natural weathering were utilized as control studies. Coatings subjected to accelerated weathering had an increase in tensile modulus, glass transition temperature and surface stiffness. DSC analysis of these coatings clearly showed evidence for 'physical aging'. This phenomenon was pursued further to find out the impact of macromolecular relaxation on the polymer physical properties. The unique feature of this research is the investigation of kinetics of macromolecular relaxation whilst a polymer undergoes simultaneous degradation. Assessment was done for some material parameters as found in theoretical models. Fictive temperature (Tf), apparent activation energy (Deltah*/R) and non linearity parameter ( x) found in Tool-Narayanswamy-Moyniham (TNM) model were explored. Tf was found to be decreasing with weathering and explained the increasingly aged 'state' of the structure. Deltah*/R was found to be increasing and explains an increased energy barrier to overcome to attain relaxation. DSC peak-shift method was used to characterize x. At early stages there is a stronger non linearity of relaxation (lower x) with a stronger structure dependence and later the relaxation kinetics seems more temperature dependent (higher x). MDSC was done to characterize the non exponentiality parameter (beta) as found in the Kohlrauch-Williams-Watts (KWW) equation. Decreasing beta value with exposure implies an increasingly broad distribution of relaxation times. The Cooperatively Rearranging Regions (CRR) concept of Adams and Gibbs was also examined. Molecular weight (Ma) of the volume (Va) represented by a CRR was compared with Mc, the molecular weight between crosslinks. Nanoindentation was done to explore the coatings' surface mechanical properties. During accelerated weathering the
Molecular alignment relaxation in polymer optical fibers for sensing applications
Stajanca, Pavol; Cetinkaya, Onur; Schukar, Marcus; Mergo, Pawel; Webb, David J.; Krebber, Katerina
2016-03-01
A systematic study of annealing behavior of drawn PMMA fibers was performed. Annealing dynamics were investigated under different environmental conditions by fiber longitudinal shrinkage monitoring. The shrinkage process was found to follow a stretched exponential decay function revealing the heterogeneous nature of the underlying molecular dynamics. The complex dependence of the fiber shrinkage on initial degree of molecular alignment in the fiber, annealing time and temperature was investigated and interpreted. Moreover, humidity was shown to have a profound effect on the annealing process, which was not recognized previously. Annealing was also shown to have considerable effect on the fiber mechanical properties associated with the relaxation of molecular alignment in the fiber. The consequences of fiber annealing for the climatic stability of certain polymer optical fiber-based sensors are discussed, emphasizing the importance of fiber controlled pre-annealing with respect to the foreseeable operating conditions.
Excitation Dynamics and Relaxation in a Molecular Heterodimer
Balevicius, V; Abramavicius, D; Mancal, T; Valkunas, L
2011-01-01
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 energy gap of the molecular excitation, 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.
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...
Fitz, Benjamin David
Segmental dynamics are investigated in model compounds, polymers, and network-forming polymers. Two aspects of these materials are investigated: (1) the role of molecular structure and connectivity on determining the characteristics of the segmental relaxation, and (2) monitoring the variations in the segmental dynamics during network-forming chemical reactions. We quantify the most important aspects of the dynamics: the relaxation shape, the relaxation strength, the relaxation time, and the temperature dependencies of these properties. Additionally, two general segmental dynamics issues of interest are the length-scale and the homogeneous/heterogeneous aspects. A judicious choice of network-forming polymer provides for the determination of an upper bound on the length-scale. A comparison of relaxation characteristics between dynamic light scattering (measuring density fluctuations) and dielectric relaxation spectroscopy (measuring segmental dipolar reorientation) provides one evaluation of the heterogeneity issue. Dipole dynamics in small molecule model compounds show the influence of molecular connectivity on the cooperative molecular response associated with the glass transition. A rigid, nonpolar, cyanate ester network is shown to develop an anomalous relaxation process during crosslinking. A specific local mode of motion is assigned. Additionally, the main relaxation becomes extraordinarily broad during the course of the network formation, due to markedly increased segmental rigidity and loss of configurational entropy.
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
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.
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.
Holmes, R. J.; Forrest, S. R.
2005-06-01
We examine the influence of singlet-triplet intersystem crossing (ISC) and excited-state molecular relaxation on strong exciton-photon coupling in optical microcavities filled with small-molecular-weight organic materials. The effect of ISC is considered by comparing coupling effects in the phosphorescent organic platinum(II) octaethylporphyrin to those in the fluorescent free-base porphyrin tetraphenylporphyrin (TPP). The influence of excited-state molecular relaxation is studied by examining coupling to the Soret band of TPP. Both ISC and excited-state molecular relaxation prevent the population of polariton states under nonresonant optical excitation. The interplay between strong coupling and relaxation processes offers a unique opportunity to directly probe fundamental ultrafast excitonic phenomena. The competition between coupling in microcavities and these processes allows for estimation of their relative transition rates.
International Nuclear Information System (INIS)
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 K3H(SO4)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.
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.
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
2016-03-01
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
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).
Simple molecular mechanism of heat transfer: Debye relaxation versus power-law
International Nuclear Information System (INIS)
We study a simple molecular model (at coarse-grain level) as a basis of irreversible heat transfer through a diathermic partition. The partition separates into two adjacent parts a box containing ideal point particles that communicate only though this partition. We provide the basic mechanism of energy transfer between the left- and right-hand side gas samples by assuming equipartition of kinetic energy of all outgoing particles colliding with the partition at a given time. We analyse and compare two essentially different cases (A) the reference one, where we assume that the border walls of the box and the diathermic partitions can randomize the direction of motion of rebounding particles, and (B) the case where we assume the mirror collisions of particles with the border walls and the partition. In both cases the rebounding of the particles from border walls is elastic. The above introduced assumptions allow us to numerically simulate and analytically consider, for example, the relaxation of temperatures of both gas samples and the entropy of the system. However, in both cases the long-time relaxation is essentially different since in case (A) it is an exponential one, while in case (B) it seems to be a power-law relaxation. The obtained results well agree in case (A) with the predictions of the phenomenological, linear theory of irreversible theory had to be developed which assumes time-dependence of heat conductivity; it describes the relaxation of the system far from equilibrium. The explanation of the results obtained in this case is, nevertheless, an intriguing problem. (author)
Water interactions with varying molecular states of bovine casein: 2H NMR relaxation studies
International Nuclear Information System (INIS)
The caseins occur in milk as spherical colloidal complexes of protein and salts with an average diameter of 1200 A, the casein micelles. Removal of Ca2+ is thought to result in their dissociation into smaller protein complexes stabilized by hydrophobic interactions and called submicelles. Whether these submicelles actually occur within the micelles as discrete particles interconnected by calcium phosphate salt bridges has been the subject of much controversy. A variety of physical measurements have shown that casein micelles contain an inordinately high amount of trapped water (2 to 7 g H2O/g protein). With this in mind it was of interest to determine if NMR relaxation measurements could detect the presence of this trapped water within the micelles, and to evaluate whether it is a continuum with picosecond correlation times or is associated in part with discrete submicellar structures with nanosecond motions. For this purpose the variations in 2H NMR longitudinal and transverse relaxation rates of water with protein concentration were determined for bovine casein at various temperatures, under both submicellar and micellar conditions. D2O was used instead of H2O to eliminate cross-relaxation effects. From the protein concentration dependence of the relaxation rates, the second virial coefficient of the protein was obtained by nonlinear regression analysis. Using either an isotropic tumbling or an intermediate asymmetry model, degrees of hydration, v, and correlation times, tau c, were calculated for the caseins; from the latter parameter the Stokes radius, r, was obtained. Next, estimates of molecular weights were obtained from r and the partial specific volume. Values were in the range of those published from other methodologies for the submicelles
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.
Molecular-dynamics study of amorphous SiO{sub 2} relaxation
Energy Technology Data Exchange (ETDEWEB)
Fadhilah, Irfan Muhammad, E-mail: irfanmuhammadf@ymail.com [Department of Physics, Universitas Padjadjaran, Jatinangor, Sumedang 45363 (Indonesia); Rosandi, Yudi, E-mail: rosandi@geophys.unpad.ac.id [Theoretical and Computational Geophysics Laboratory, Department of Physics, Universitas Padjadjaran, Jatinangor, Sumedang 45363 (Indonesia)
2015-09-30
Using Molecular-Dynamics simulation we observed the generation of amorphous SiO{sub 2} target from a randomly distributed Si and O atoms. We applied a sequence of annealing of the target with various temperature and quenching to room temperature. The relaxation time required by the system to form SiO{sub 4} tetrahedral mesh after a relatively long simulation time, is studied. The final amorphous target was analyzed using the radial distribution function method, which can be compared with the available theoretical and experimental data. We found that up to 70% of the target atoms form the tetrahedral SiO{sub 4} molecules. The number of formed tetrahedral increases following the growth function and the rate of SiO{sub 4} formation follows Arrhenius law, depends on the annealing temperature. The local structure of amorphous SiO{sub 2} after this treatment agrees well with those reported in some literatures.
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.
Nuclear magnetic relaxation, correlation time spectrum, and molecular dynamics in a linear polymer
International Nuclear Information System (INIS)
The pulsed nuclear magnetic resonance (NMR) method at a proton frequency of 25 MHz at temperatures of 22-160oC is used to detect the transverse magnetization decay in polyisoprene rubbers with various molecular masses, to determine the NMR damping time T2, and to measure spin-lattice relaxation time T1 and time T2eff of damping of solid-echo signals under the action of a sequence of MW-4 pulses modified by introducing 180o pulses. The dispersion dependences of T2eff obtained for each temperature are combined into one using the temperature-frequency equivalence principle. On the basis of the combined dispersion dependence of T2eff and the data on T2 and T1, the correlation time spectrum of molecular movements is constructed. Analysis of the shape of this spectrum shows that the dynamics of polymer molecules can be described in the first approximation by the Doi-Edwards tube-reptation model
DEFF Research Database (Denmark)
Almond, A; Bunkenborg, Jakob; Franch, T; Gotfredsen, Charlotte Held; Duus, J O
2001-01-01
An investigation has been performed to assess how aqueous dynamical simulations of flexible molecules can be compared against NMR data. The methodology compares state-of-the-art NMR data (residual dipolar coupling, NOESY, and (13)C relaxation) to molecular dynamics simulations in water over sever...
Energy Technology Data Exchange (ETDEWEB)
Xie, Wen Jun; Yang, Yi Isaac; Gao, Yi Qin, E-mail: gaoyq@pku.edu.cn [Institute of Theoretical and Computational Chemistry, College of Chemistry and Molecular Engineering and Biodynamic Optical Imaging Center, Peking University, Beijing 100871 (China)
2015-12-14
In this study, we examine how complex ions such as oxyanions influence the dynamic properties of water and whether differences exist between simple halide anions and oxyanions. Nitrate anion is taken as an example to investigate the hydration properties of oxyanions. Reorientation relaxation of its hydration water can occur through two different routes: water can either break its hydrogen bond with the nitrate to form one with another water or switch between two oxygen atoms of the same nitrate. The latter molecular mechanism increases the residence time of oxyanion’s hydration water and thus nitrate anion slows down the translational motion of neighbouring water. But it is also a “structure breaker” in that it accelerates the reorientation relaxation of hydration water. Such a result illustrates that differences do exist between the hydration of oxyanions and simple halide anions as a result of different molecular geometries. Furthermore, the rotation of the nitrate solute is coupled with the hydrogen bond rearrangement of its hydration water. The nitrate anion can either tilt along the axis perpendicularly to the plane or rotate in the plane. We find that the two reorientation relaxation routes of the hydration water lead to different relaxation dynamics in each of the two above movements of the nitrate solute. The current study suggests that molecular geometry could play an important role in solute hydration and dynamics.
International Nuclear Information System (INIS)
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)
Knapp Michael
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.
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.
International Nuclear Information System (INIS)
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 15N-labeled SH3 (Src homology 3) domain proteins in aqueous buffer were used to generate general order parameters (S2) 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 (S2) were derived from the MD trajectory. Correlation analysis using the Gromos force field indicated that S2 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. S2 parameters from MD simulations with charges for all three histidines and with the SPC/E water model correlated well with S2 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 (S2) 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
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.
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
Generalized extended Navier-Stokes theory: Multiscale spin relaxation in molecular fluids
DEFF Research Database (Denmark)
Hansen, Jesper Schmidt
2013-01-01
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...... 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...
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.
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
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...
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 ...
Huestis, D. L.
2008-12-01
Laboratory sound absorption measurements provide much of what we know about the vibrational kinetics of air mixtures, forming the core basis for retrieving the altitude profile of water in the mesosphere from infrared emissions between 6.3 and 6.9 μm. Here we show that sound-absorption and laser-excitation experiments follow exactly the same kinetics, reflect the same underlying reaction rates, and can be vulnerable to similar ambiguities. This has not been obvious because the literature lacks a consistent prescription for calculating the sound absorption frequency spectrum from the reaction rate coefficients. We have developed the first general theoretical formalism for calculating the absolute magnitude of sound absorption per-unit-length, versus sound frequency, for any number of collisional excitation, relaxation, and energy transfer processes, for any mixture of atomic and molecular gases. This new formalism, and the computer code that implements it, provide the first systematic means for inferring collisional rate coefficients from sound absorption measurements in which more than one rotational or vibrational mode is active, such as N2/O2/H2O/CO2 gas mixtures in the laboratory and the atmosphere. When a sound wave travels through a gas, the alternating compression and expansion cycles heat and cool the gas. If the acoustic frequency roughly matches the rate of vibrational relaxation, then the effective vibrational temperature lags behind the translational temperature and the energy in the sound wave is attenuated. The measured frequency of maximum absorption is proportional to the vibrational relaxation rate. In the simplest laser-based experiment, we excite a single molecular level and record its exponential time decay, with the vibrational relaxation rate being proportional to the decay frequency. In both experiments we derive the relaxation rate coefficient from the linear graph versus gas pressure. The technical problem is that any mixture of molecular
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).
Poirier-Brulez, Fabienne; Roudaut, Gaëlle; Champion, Dominique; Tanguy, Marie; Simatos, Denise
2006-02-01
Molecular mobility is known to be a key parameter in controlling the physical properties of materials and thus their quality and performance. Beyond glass transition related changes, attention should be called to the impact of local motions remaining in the glassy state. Gelatinized waxy maize starch at different sucrose contents (0-20% solids) was equilibrated between 0 and 14% water and sorption isotherms determined at 25 degrees C. The effect of water and sucrose content on the molecular mobility of glassy starch was investigated by differential scanning calorimetry through enthalpy relaxation studies and dynamical mechanical thermal analysis. The existence of sucrose-starch interactions was suggested by the sorption isotherms not following the expected additivity of the single component sorption curves. Contrary to the glass transition or associated alpha relaxation, water and sucrose affected differently the secondary relaxations. Indeed, the beta relaxation observed around -15 degrees C was shifted to lower temperature upon increasing hydration, and to higher temperature when sucrose content increased, suggesting a hindering of these local motions. Enthalpy relaxation of the ternary mixtures was studied following aging up to 668 h at Tg -15 degrees C. Ternary mixtures exhibited an enthalpy relaxation upon aging lower than starch alone as a sign of lower polymer mobility in the presence of small molecules, contrary to the free volume theory. Relaxation kinetics were characterized with the Cowie-Ferguson model and compared to literature data. The extent of the enthalpy relaxation appeared to be controlled by the distance between the aging temperature and the beta relaxation temperature. PMID:16127661
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
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%.
Energy Technology Data Exchange (ETDEWEB)
Rheingold, Arnold L.; DiPasquale, Antonio G. [Department of Chemistry and Biochemistry, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0358 (United States); Beckmann, Peter A. [Department of Physics, Bryn Mawr College, 101 North Merion Avenue, Bryn Mawr, PA 19010-2899 (United States)], E-mail: pbeckman@brynmawr.edu
2008-04-03
We correlate an X-ray determination of the molecular and crystal structures of 2-tert-butylanthracene and 2-tert-butylanthraquinone reported here with the previously reported dynamical nuclear magnetic resonance determination of the motions of the tert-butyl groups and their resident methyl groups in the solid state [P.A. Beckmann, K.S. Burbank, M.M.W. Lau, J.N. Ree, T.L. Weber, Chem. Phys. 290 (2003) 241].
International Nuclear Information System (INIS)
We correlate an X-ray determination of the molecular and crystal structures of 2-tert-butylanthracene and 2-tert-butylanthraquinone reported here with the previously reported dynamical nuclear magnetic resonance determination of the motions of the tert-butyl groups and their resident methyl groups in the solid state [P.A. Beckmann, K.S. Burbank, M.M.W. Lau, J.N. Ree, T.L. Weber, Chem. Phys. 290 (2003) 241
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.
Proton spin-lattice relaxation and molecular motion in solid dimethylsulphoxide
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An NMR-25MHz pulse spectrometer, characterised by 4,0 μsec recovery time and 1,5 μsec π/2 pulse length, was constructed in our Laboratory. Measurements of proton spin-lattice relaxation times in solid DMSO were performed as a function of temperature down to 900K using 90-t-90 and 180-t-90 pulse sequences. LogT1 plotted versus reciprocal temperature exhibits two minima at 2200K and 1650K. Arrhenius behaviour of T1 enables to determine activation energies: 3,84 kcal/mol above 2200K; 2,95 kcal/mol below 1650K; and 4,36 kcal/ mol below 1100K. The results can be interpreted as evidence of non-equivalent motion of methyl groups, as revealed by the observed double minimum yielding the pre-exponential factors for correlation times 5.10-13sec and 6.10-13sec and confirmed by x-ray measurements suggesting a difference of 0,05 Angstroem in carbon-sulphur distances /Thomas, Shoemaker, Eriks/. Below 1100K, both methyl groups characterised by the same values of correlation times appear to be dynamically equivalent. Theoretical values of Tsub(1min), calculated for methyl groups reorienting about the C3 axis and coupled via dipole-dipole interaction, are in good agreement with experiment. The intermolecular contribution is negligible from measurements performed for deuterated solutions. The present measurement of T1 do not suggest an overall tumbling of molecues in the experimental conditions. (author)
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
International Nuclear Information System (INIS)
Practical theoretical methods are developed and implemented for handling molecular collision problems and subsequently a study was made of the important processes which influence collision rates and a computation made of rate information suitable for gas laser and combustion kinetics modeling studies. The study focuses on CO and HF molecules, which are of practical interest as molecular lasers and of theoretical interest for discerning the role of rotation processes in vibrational relaxation. 26 references
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.
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.
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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 107 cm–2 and a root mean square roughness of less than 1 nm are obtained
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
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.
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
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
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.
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
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.
Prévot, G.; Cohen, C.; Schmaus, D.; Hecquet, P.; Salanon, B.
2002-05-01
We have studied the relaxations and vibrations of atoms near the surface of a (1,1,19) copper crystal. For this purpose, we have performed molecular dynamics simulations using a semi-empirical many-body potential derived from tight binding models. The total displacement field can be described as the sum of a mean surface relaxation and a specific contribution of the steps, which is maximal for step edge atoms (0.08 Å) and corner atoms (0.06 Å). Whereas step edge atoms relax towards the inner terrace and towards the bulk, corner atoms relax in the opposite direction, leading to vortex-like structures in the displacement field. We demonstrate that, as predicted by continuous elasticity, the displacement field induced by steps is equivalent to the one created by a line of dipoles on a flat surface. In the particular case studied here, the equivalent dipole density is 3.3×10 -10 N. The specific relaxations of kink atoms have been calculated. We have also studied the variation of the relaxations as a function of temperature ( T). A strong effect is predicted for inner terrace atoms: when increasing T, the contraction of the first interplanar distance, with respect to the bulk value, progressively cancels and turns to an expansion at high T. This is not the case for the specific contraction of step edge atoms that is nearly temperature independent. This latter behaviour is related to very strong longitudinal correlation between vibrations of the step edge atom and of its nearest neighbour inside the terrace. In the same time, whereas the vibrations of inner terrace atoms are found to be isotropic, the ones of step edge atoms are anisotropic, with a larger component along the direction parallel to the terrace plane and perpendicular to the step edge, the other components being the same as for inner terrace atoms.
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.
International Nuclear Information System (INIS)
Graphical abstract: Picosecond IR-UV pump–probe study revealed a detailed energy dissipation route and its time scale from the energy put into the OH(OD) stretching vibration for the phenol–water hydrogen-bonded complex. - Abstract: A comparative study of vibrational energy relaxation (VER) between the monohydrated complexes of phenol-d0 and phenol-d1 is investigated in a supersonic molecular beam. The direct time-resolved measurement of energy redistribution from the phenolic OH/OD stretching mode of the phenol-d0-H2O/phenol-d1-D2O is performed by picosecond IR-UV pump–probe spectroscopy. Two complexes follow the same relaxation process that begins with the intramolecular vibrational energy redistribution (IVR) and the intermolecular vibrational energy redistribution (IVR), which is followed by the vibrational predissociation (VP). The difference in the relaxation lifetimes between them is discussed by anharmonic force field and RRKM calculations. Anharmonic analysis implies that intra- (IVR) and intermolecular (IVR) relaxations occur in parallel in the complexes. The RRKM-predicted dissociation (VP) lifetimes show qualitative agreement with the observed results, suggesting that VP takes place after the statistical energy distribution in the complexes
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.
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.
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
RELAX: detecting relaxed selection in a phylogenetic framework.
Wertheim, Joel O; Murrell, Ben; Smith, Martin D; Kosakovsky Pond, Sergei L; Scheffler, Konrad
2015-03-01
Relaxation of selective strength, manifested as a reduction in the efficiency or intensity of natural selection, can drive evolutionary innovation and presage lineage extinction or loss of function. Mechanisms through which selection can be relaxed range from the removal of an existing selective constraint to a reduction in effective population size. Standard methods for estimating the strength and extent of purifying or positive selection from molecular sequence data are not suitable for detecting relaxed selection, because they lack power and can mistake an increase in the intensity of positive selection for relaxation of both purifying and positive selection. Here, we present a general hypothesis testing framework (RELAX) for detecting relaxed selection in a codon-based phylogenetic framework. Given two subsets of branches in a phylogeny, RELAX can determine whether selective strength was relaxed or intensified in one of these subsets relative to the other. We establish the validity of our test via simulations and show that it can distinguish between increased positive selection and a relaxation of selective strength. We also demonstrate the power of RELAX in a variety of biological scenarios where relaxation of selection has been hypothesized or demonstrated previously. We find that obligate and facultative γ-proteobacteria endosymbionts of insects are under relaxed selection compared with their free-living relatives and obligate endosymbionts are under relaxed selection compared with facultative endosymbionts. Selective strength is also relaxed in asexual Daphnia pulex lineages, compared with sexual lineages. Endogenous, nonfunctional, bornavirus-like elements are found to be under relaxed selection compared with exogenous Borna viruses. Finally, selection on the short-wavelength sensitive, SWS1, opsin genes in echolocating and nonecholocating bats is relaxed only in lineages in which this gene underwent pseudogenization; however, selection on the functional
Kirstein, Roland
2005-01-01
This paper presents a modification of the inspection game: The ?Bayesian Monitoring? model rests on the assumption that judges are interested in enforcing compliant behavior and making correct decisions. They may base their judgements on an informative but imperfect signal which can be generated costlessly. In the original inspection game, monitoring is costly and generates a perfectly informative signal. While the inspection game has only one mixed strategy equilibrium, three Perfect Bayesia...
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.
The conundrum of relaxation times
International Nuclear Information System (INIS)
The current theories of proton relaxation times fall short of explaining satisfactorily the physical and biological mechanisms responsible for the dissimilarities of relaxation behavior in normal and pathological tissues. An alternative approach to understand these mechanisms is needed. This paper advances the possibility that the dissimilarities of relaxation behavior in normal and pathological tissues is due to the consumption of paramagnetic molecular O2 dissolved in cell-associated water. (orig.)
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.
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
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.
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.
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
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.
International Nuclear Information System (INIS)
Dielectric relaxation measurements carried out in nematic BOAOB reveal fast reorientational motions of the whole molecule around the long axis (τ1 ∼ 60 ps) as well as slow reorientational motions of the whole molecule around the short axis (τ1 ∼ 10-8 s). Incoherent quasielastic neutron scattering spectra obtained for nematic BOAOB, with normal and deuterated alkoxy terminals, are inpterpreted as dominated by reorientations (around the C-N bonds) of moieties consisting of benzene rings coupled with alkoxy terminals (τ1 ∼ 4 ps). In addition fast conformational changes occur in the terminals. Dielectric relaxation measurements reveal librations of the whole molecule in phases Cr 1 and Cr 2 accompanied by reorientation of the terminal groups in these phases. The reorientations occur in the time scale amounting to 10-8 s. Incoherent quasielastic neutron scattering spectra obtained for Cr 1 and Cr 2 phases of BOAOB were interpreted as dominated by overdamped librational motions of the moieties accompanied by fast conformational changes in the terminals. Cr 3 phase corresponds to a normal molecular crystal. 22 refs., 8 figs., 4 tabs. (author)
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
Gonzalez, Luis E.; Gonzalez, David J
2006-01-01
We have performed orbital free ab initio molecular dynamics simulations in order to study the thermal behaviour of two open surfaces of solid metallic systems, namely the (110) face of fcc Al and the (10-10) face of hcp Mg. Our results reproduce qualitatively both the experimental measurements and previous ab initio calculations performed with the more costly Kohn-Sham approach of Density Functional Theory. These calculations can be viewed as a validation test of the orbital free method for s...
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
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...... 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...
Directory of Open Access Journals (Sweden)
Daniela Becker
2008-09-01
Full Text Available Blendas de poliamida amorfa (aPA com copolímero de estireno-acrilonitrila (SAN utilizando uma série de copolímeros de metil metacrilato-anidrido maleico (MMA-MA como agente compatibilizante foram preparadas. Estes copolímeros acrílicos são miscíveis com a fase SAN, e o anidrido maleico (MA é capaz de reagir com os grupos terminais da poliamida, levando a formação de um copolímero na interfase da blenda durante o processamento. Este estudo foca o efeito da massa molar e a concentração de anidrido maleico do compatibilizante nas propriedades de relaxação dielétrica. Os resultados mostram que tanto a concentração de anidrido maleico e a massa molar do compatibilizante influenciam a mobilidade molecular. Blendas com compatibilizantes com 5 e 10% de anidrido maleico apresentaram menor energia de ativação devido à alta mobilidade da fase SAN.Blends of amorphous polyamide (aPA with acrylonitrile/styrene copolymer (SAN using a series of methyl methacrylate-maleic anhydride (MMA-MA copolymers as compatibilizing agents were prepared. These acrylic copolymers were miscible with SAN, whereas the maleic anhydride units in the copolymers are capable to react with the polyamide end groups; this could lead to the formation of grafted copolymers at the blend interface during melt processing. This study focuses on the effects of molecular weight and concentration of the reactive maleic anhydride units of the compatibilizer on the dielectric relaxation properties. The results show that both maleic anhydride quantity and molecular weight of MMA MA influenced the dielectric relaxation properties. Blends with 5 and 10% of MA in the compatibilizer present lower activation energy due to the high mobility of SAN phase.
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)
Energy Technology Data Exchange (ETDEWEB)
Andreozzi, L; Faetti, M; Giordano, M; Palazzuoli, D [Dipartimento di Fisica, Universita di Pisa, via F Buonarroti 2 Pisa I-56127, Italy and INFM, UdR Pisa, Italy (Italy)
2003-03-26
The enthalpy recovery mechanism of a low molecular weight synthesis of polymethylmethacrylate is investigated by means of differential scanning calorimetry (DSC) experiments. The experimental results can be described satisfactorily in terms of the Tool-Narayanaswamy-Moynihan theory. This work is mainly focused on developing a strategy for evaluation of the best set of parameters for the model. The approach starts with a simultaneous fitting procedure of several experimental DSC traces. Sets of parameters are obtained which exhibit agreement with experiments. The enthalpy lost on ageing of the sample in the glassy state as a function of the annealing time is then compared with the predictions provided by using the different sets of parameters. We show that this procedure is able to single out the best set of parameters and to provide a good estimation of the Adam-Gibbs temperature.
On polyhedral approximations of polytopes for learning Bayesian networks
Czech Academy of Sciences Publication Activity Database
Studený, Milan; Haws, D.C.
2013-01-01
Roč. 4, č. 1 (2013), s. 59-92. ISSN 1309-3452 R&D Projects: GA ČR GA201/08/0539 Institutional support: RVO:67985556 Keywords : Bayesian network structure * integer programming * standard imset * characteristic imset * LP relaxation Subject RIV: BA - General Mathematics http://library.utia.cas.cz/separaty/2013/MTR/studeny-on polyhedral approximations of polytopes for learning bayesian networks.pdf
RELAX: Detecting Relaxed Selection in a Phylogenetic Framework
Wertheim, Joel O; Murrell, Ben; Smith, Martin D.; Kosakovsky Pond, Sergei L; Scheffler, Konrad
2014-01-01
Relaxation of selective strength, manifested as a reduction in the efficiency or intensity of natural selection, can drive evolutionary innovation and presage lineage extinction or loss of function. Mechanisms through which selection can be relaxed range from the removal of an existing selective constraint to a reduction in effective population size. Standard methods for estimating the strength and extent of purifying or positive selection from molecular sequence data are not suitable for det...
International Nuclear Information System (INIS)
The formation of H2 in the interstellar medium, from two hydrogen atoms, is a fundamental question in astrophysics. This very exothermic reaction is indeed the first step of a series of essential reactions for the interstellar physical-chemistry that takes place on the surface of interstellar dust grains. In the warm regions of the ISM, diffuse clouds and Photodissociation regions, the invoked formation mechanism is the Eley-Rideal heterogeneous catalysis reaction, in which one H atom is initially chemisorbed. The grains have mainly carbonaceous graphitic-like composition. Previous theoretical works carried out using constrained geometries were unable to explain the formation of H2 in the observed rovibrationnal states (v≤5). In order to take into account the degrees of freedom of all relevant atoms, we have built, from the Brenner potential, a new potential that models the graphene H-H system.With this potential, we have completed a classical molecular dynamics study of the formation of H2. This work has been performed for collision energies of the impinging H atoms from 0.015 eV to 0.2 eV and for surface temperature of 0, 10 and 30 K. One of the salient results is that the reaction cross section is directly related with the shape of the potential seen by the impinging H atom. Furthermore, the rovibrationnal distribution obtained by allowing the surface atoms to move is in better agreement with the one observed by astrophysicists (v≤6), the surface absorbs a large part (∼25%) of the available energy. Some works about the influence of: an additional H atom upon the surface or a possible porous structure of the grains, on the formation of H2 are presented in appendices. (author)
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.
Sour, Angélique; Jenni, Sébastien; Ortí-Suárez, Ana; Schmitt, Julie; Heitz, Valérie; Bolze, Frédéric; Loureiro de Sousa, Paulo; Po, Chrystelle; Bonnet, Célia S; Pallier, Agnès; Tóth, Éva; Ventura, Barbara
2016-05-01
A molecular theranostic agent for magnetic resonance imaging (MRI) and photodynamic therapy (PDT) consisting of four [GdDTTA](-) complexes (DTTA(4-) = diethylenetriamine-N,N,N″,N″-tetraacetate) linked to a meso-tetraphenylporphyrin core, as well as its yttrium(III) analogue, was synthesized. A variety of physicochemical methods were used to characterize the gadolinium(III) conjugate 1 both as an MRI contrast agent and as a photosensitizer. The proton relaxivity measured in H2O at 20 MHz and 25 °C, r1 = 43.7 mmol(-1) s(-1) per gadolinium center, is the highest reported for a bishydrated gadolinium(III)-based contrast agent of medium size and can be related to the rigidity of the molecule. The complex displays also a remarkable singlet oxygen quantum yield of ϕΔ = 0.45 in H2O, similar to that of a meso-tetrasulfonated porphyrin. We also evidenced the ability of the gadolinium(III) conjugate to penetrate in cancer cells with low cytotoxicity. Its phototoxicity on Hela cells was evaluated following incubation at low micromolar concentration and moderate light irradiation (21 J cm(-2)) induced 50% of cell death. Altogether, these results demonstrate the high potential of this conjugate as a theranostic agent for MRI and PDT. PMID:27074089
Characteristic imsets for learning Bayesian network structure
Czech Academy of Sciences Publication Activity Database
Hemmecke, R.; Lindner, S.; Studený, Milan
2012-01-01
Roč. 53, č. 9 (2012), s. 1336-1349. ISSN 0888-613X R&D Projects: GA MŠk(CZ) 1M0572; GA ČR GA201/08/0539 Institutional support: RVO:67985556 Keywords : learning Bayesian network structure * essential graph * standard imset * characteristic imset * LP relaxation of a polytope Subject RIV: BA - General Mathematics Impact factor: 1.729, year: 2012 http://library.utia.cas.cz/separaty/2012/MTR/studeny-0382596.pdf
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...
BEAST: Bayesian evolutionary analysis by sampling trees
Drummond Alexei J; Rambaut Andrew
2007-01-01
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 m...
BEAST: Bayesian evolutionary analysis by sampling trees
Drummond, Alexei J.; Rambaut, Andrew
2007-01-01
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 su...
Rubin, Donald B.
1981-01-01
The Bayesian bootstrap is the Bayesian analogue of the bootstrap. Instead of simulating the sampling distribution of a statistic estimating a parameter, the Bayesian bootstrap simulates the posterior distribution of the parameter; operationally and inferentially the methods are quite similar. Because both methods of drawing inferences are based on somewhat peculiar model assumptions and the resulting inferences are generally sensitive to these assumptions, neither method should be applied wit...
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
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
Latanowicz, L.; Medycki, W.; Jakubas, R.
2011-08-01
Molecular dynamics of a polycrystalline sample of (CH 3NH 3) 5Bi 2Br 11 (MAPBB) is studied on the basis of the proton T1 (55.2 MHz) relaxation time and the proton second moment of NMR line. The T1 (55.2 MHz) was measured for temperatures from 20 K to 330 K, while the second moment M2 for those from 40 K to 330 K. The proton spin pairs of the methyl and ammonium groups perform a complex stochastic motion being a resultant of four components characterised by the correlation times τ3T, τ3H, τ2, and τ iso, referring to the tunnelling and over the barrier jumps in a triple potential, jumps between two equilibrium sites and isotropic rotation. The theoretical expressions for the spectral densities in the cases of the complex motion considered were derived. For τ3H, τ2, and τ iso the Arrhenius temperature dependence was assumed, while for τ3T - the Schrödinger one. The correlation times τ3H for CH 3 and NH 3 groups differ, which indicates the uncorrelated motion of these groups. The stochastic tunnelling jumps are not present above the temperature T tun at which the thermal energy is higher than the activation energy of jumps over the barrier attributed to the hindered rotation of the CH 3 and NH 3 groups. The T tun temperature is 54.6 K for NH 3 group and 46.5 K for CH 3 group in MAPBB crystal. The tunnelling jumps of the methyl and ammonium protons are responsible for the flattening of T1 temperature dependence at low temperatures. The isotropic tumbling is detectable only from the M2 temperature dependence. The isotropic tumbling reduces the second moment to 4 G2 which is the value of the intermolecular part of the second moment. The motion characterised by the correlation time τ2 is well detectable from both T1 and M2 temperature dependences. This motion causes the appearance of T1 minimum at 130 K and reduction of the second moment to the 7.7 G2 value. The small tunnelling splitting ω T of the same value for the methyl and ammonium groups was estimated as
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…
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
Non-monotonic behaviour in relaxation dynamics of image restoration
International Nuclear Information System (INIS)
We have investigated the relaxation dynamics of image restoration through a Bayesian approach. The relaxation dynamics is much faster at zero temperature than at the Nishimori temperature where the pixel-wise error rate is minimized in equilibrium. At low temperature, we observed non-monotonic development of the overlap. We suggest that the optimal performance is realized through premature termination in the relaxation processes in the case of the infinite-range model. We also performed Markov chain Monte Carlo simulations to clarify the underlying mechanism of non-trivial behaviour at low temperature by checking the local field distributions of each pixel
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.
Bayesian exploratory factor analysis
Gabriella Conti; Sylvia Frühwirth-Schnatter; James Heckman; Rémi Piatek
2014-01-01
This paper develops and applies a Bayesian approach to Exploratory Factor Analysis that improves on ad hoc classical approaches. Our framework relies on dedicated factor models and simultaneously determines the number of factors, the allocation of each measurement to a unique factor, and the corresponding factor loadings. Classical identifi cation criteria are applied and integrated into our Bayesian procedure to generate models that are stable and clearly interpretable. A Monte Carlo study c...
Bayesian Exploratory Factor Analysis
Conti, Gabriella; Frühwirth-Schnatter, Sylvia; Heckman, James J.; Piatek, Rémi
2014-01-01
This paper develops and applies a Bayesian approach to Exploratory Factor Analysis that improves on ad hoc classical approaches. Our framework relies on dedicated factor models and simultaneously determines the number of factors, the allocation of each measurement to a unique factor, and the corresponding factor loadings. Classical identification criteria are applied and integrated into our Bayesian procedure to generate models that are stable and clearly interpretable. A Monte Carlo study co...
Bayesian Exploratory Factor Analysis
Gabriella Conti; Sylvia Fruehwirth-Schnatter; Heckman, James J.; Remi Piatek
2014-01-01
This paper develops and applies a Bayesian approach to Exploratory Factor Analysis that improves on \\emph{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 s...
Bayesian exploratory factor analysis
Conti, Gabriella; Frühwirth-Schnatter, Sylvia; Heckman, James J.; Piatek, Rémi
2014-01-01
This paper develops and applies a Bayesian approach to Exploratory Factor Analysis that improves on ad hoc classical approaches. Our framework relies on dedicated factor models and simultaneously determines the number of factors, the allocation of each measurement to a unique factor, and the corresponding factor loadings. Classical identification criteria are applied and integrated into our Bayesian procedure to generate models that are stable and clearly interpretable. A Monte Carlo st...
Bayesian exploratory factor analysis
Conti, Gabriella; Frühwirth-Schnatter, Sylvia; Heckman, James; Piatek, Rémi
2014-01-01
This paper develops and applies a Bayesian approach to Exploratory Factor Analysis that improves on ad hoc classical approaches. Our framework relies on dedicated factor models and simultaneously determines the number of factors, the allocation of each measurement to a unique factor, and the corresponding factor loadings. Classical identification criteria are applied and integrated into our Bayesian procedure to generate models that are stable and clearly interpretable. A Monte Carlo study co...
Carbonetto, Peter; Kisynski, Jacek; De Freitas, Nando; Poole, David L
2012-01-01
The Bayesian Logic (BLOG) language was recently developed for defining first-order probability models over worlds with unknown numbers of objects. It handles important problems in AI, including data association and population estimation. This paper extends BLOG by adopting generative processes over function spaces - known as nonparametrics in the Bayesian literature. We introduce syntax for reasoning about arbitrary collections of objects, and their properties, in an intuitive manner. By expl...
Bayesian default probability models
Andrlíková, Petra
2014-01-01
This paper proposes a methodology for default probability estimation for low default portfolios, where the statistical inference may become troublesome. The author suggests using logistic regression models with the Bayesian estimation of parameters. The piecewise logistic regression model and Box-Cox transformation of credit risk score is used to derive the estimates of probability of default, which extends the work by Neagu et al. (2009). The paper shows that the Bayesian models are more acc...
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.
... 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 ...
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 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...
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 ...
Stress relaxation of bi-disperse polystyrene melts
DEFF Research Database (Denmark)
Hengeller, Ludovica; Huang, Qian; Dorokhin, Andriy;
2016-01-01
We present start-up of uniaxial extension followed by stress relaxation experiments of a bi-disperse 50 % by weight blend of 95k and 545k molecular weight polystyrene. We also show, for comparison, stress relaxation measurements of the polystyrene melts with molecular weight 95k and 545k, which are...
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.
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.
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 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...
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. PMID:26932314
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.
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.
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 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...... 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 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...
Czech Academy of Sciences Publication Activity Database
Krejsa, Jiří; Věchet, S.
Bratislava: Slovak University of Technology in Bratislava, 2010, s. 217-222. ISBN 978-80-227-3353-3. [Robotics in Education . Bratislava (SK), 16.09.2010-17.09.2010] Institutional research plan: CEZ:AV0Z20760514 Keywords : mobile robot localization * bearing only beacons * Bayesian filters Subject RIV: JD - Computer Applications, Robotics
DEFF Research Database (Denmark)
Antoniou, Constantinos; Harrison, Glenn W.; Lau, Morten I.;
2015-01-01
A large literature suggests that many individuals do not apply Bayes’ Rule when making decisions that depend on them correctly pooling prior information and sample data. We replicate and extend a classic experimental study of Bayesian updating from psychology, employing the methods of experimenta...
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...
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 as a...
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.
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
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
International Nuclear Information System (INIS)
Graphical abstract: Display Omitted - Abstract: Gel electrolyte based on low molecular weight organic gelator methyl-4,6-O-(p-nitrobenzylidene)-α-D-glucopyranoside was formed by the self-assembly phenomena in aqueous solution of high temperature ionic liquid tetramethylammonium bromide. The solidification process was based on sol-gel technique with controlled gelation temperature. When the temperature was below the characteristic gel-sol phase transition temperature, Tgs, the gel electrolyte was solid-like. The gel electrolytes showed enhanced ionic conductivity to those of the pure electrolyte in liquid state in whole temperature range below Tgs. The thermal stability, ionic conductivity and molecular dynamics investigated as a function of temperature and concentration of the gelator, together with the gel microstructure were performed to get some insight in to the origin of the enhanced conductivity properties. Intermolecular interaction between ion complexes and gelator aggregates was implicated by the data obtained and suggested as the origin of the conductivity enhancement effect
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...
Bayesian Magic in Asteroseismology
Kallinger, T.
2015-09-01
Only a few years ago asteroseismic observations were so rare that scientists had plenty of time to work on individual data sets. They could tune their algorithms in any possible way to squeeze out the last bit of information. Nowadays this is impossible. With missions like MOST, CoRoT, and Kepler we basically drown in new data every day. To handle this in a sufficient way statistical methods become more and more important. This is why Bayesian techniques started their triumph march across asteroseismology. I will go with you on a journey through Bayesian Magic Land, that brings us to the sea of granulation background, the forest of peakbagging, and the stony alley of model comparison.
Bayesian Nonparametric Graph Clustering
Banerjee, Sayantan; Akbani, Rehan; Baladandayuthapani, Veerabhadran
2015-01-01
We present clustering methods for multivariate data exploiting the underlying geometry of the graphical structure between variables. As opposed to standard approaches that assume known graph structures, we first estimate the edge structure of the unknown graph using Bayesian neighborhood selection approaches, wherein we account for the uncertainty of graphical structure learning through model-averaged estimates of the suitable parameters. Subsequently, we develop a nonparametric graph cluster...
Approximate Bayesian recursive estimation
Czech Academy of Sciences Publication Activity Database
Kárný, Miroslav
2014-01-01
Roč. 285, č. 1 (2014), s. 100-111. ISSN 0020-0255 R&D Projects: GA ČR GA13-13502S Institutional support: RVO:67985556 Keywords : Approximate parameter estimation * Bayesian recursive estimation * Kullback–Leibler divergence * Forgetting Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 4.038, year: 2014 http://library.utia.cas.cz/separaty/2014/AS/karny-0425539.pdf
Bayesian Benchmark Dose Analysis
Fang, Qijun; Piegorsch, Walter W.; Barnes, Katherine Y.
2014-01-01
An important objective in environmental risk assessment is estimation of minimum exposure levels, called Benchmark Doses (BMDs) that induce a pre-specified Benchmark Response (BMR) in a target population. Established inferential approaches for BMD analysis typically involve one-sided, frequentist confidence limits, leading in practice to what are called Benchmark Dose Lower Limits (BMDLs). Appeal to Bayesian modeling and credible limits for building BMDLs is far less developed, however. Indee...
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...
Heteroscedastic Treed Bayesian Optimisation
Assael, John-Alexander M.; Wang, Ziyu; Shahriari, Bobak; De Freitas, Nando
2014-01-01
Optimising black-box functions is important in many disciplines, such as tuning machine learning models, robotics, finance and mining exploration. Bayesian optimisation is a state-of-the-art technique for the global optimisation of black-box functions which are expensive to evaluate. At the core of this approach is a Gaussian process prior that captures our belief about the distribution over functions. However, in many cases a single Gaussian process is not flexible enough to capture non-stat...
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.
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 Neural Word Embedding
Barkan, Oren
2016-01-01
Recently, several works in the domain of natural language processing presented successful methods for word embedding. Among them, the Skip-gram (SG) with negative sampling, known also as Word2Vec, advanced the state-of-the-art of various linguistics tasks. In this paper, we propose a scalable Bayesian neural word embedding algorithm that can be beneficial to general item similarity tasks as well. The algorithm relies on a Variational Bayes solution for the SG objective and a detailed step by ...
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.
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...
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...
Unbounded Bayesian Optimization via Regularization
Shahriari, Bobak; Bouchard-Côté, Alexandre; De Freitas, Nando
2015-01-01
Bayesian optimization has recently emerged as a popular and efficient tool for global optimization and hyperparameter tuning. Currently, the established Bayesian optimization practice requires a user-defined bounding box which is assumed to contain the optimizer. However, when little is known about the probed objective function, it can be difficult to prescribe such bounds. In this work we modify the standard Bayesian optimization framework in a principled way to allow automatic resizing of t...
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...
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...
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
Relaxation Techniques for Health
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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.
Sarwate, Anand D.; Gastpar, Michael
2012-01-01
The arbitrarily varying channel (AVC) is a conservative way of modeling an unknown interference, and the corresponding capacity results are pessimistic. We reconsider the Gaussian AVC by relaxing the classical model and thereby weakening the adversarial nature of the interference. We examine three different relaxations. First, we show how a very small amount of common randomness between transmitter and receiver is sufficient to achieve the rates of fully randomized codes. Second, akin to the ...
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.
Decentralized Distributed Bayesian Estimation
Czech Academy of Sciences Publication Activity Database
Dedecius, Kamil; Sečkárová, Vladimíra
Praha: ÚTIA AVČR, v.v.i, 2011 - (Janžura, M.; Ivánek, J.). s. 16-16 [7th International Workshop on Data–Algorithms–Decision Making. 27.11.2011-29.11.2011, Mariánská] R&D Projects: GA ČR 102/08/0567; GA ČR GA102/08/0567 Institutional research plan: CEZ:AV0Z10750506 Keywords : estimation * distributed estimation * model Subject RIV: BB - Applied Statistics, Operational Research http://library.utia.cas.cz/separaty/2011/AS/dedecius-decentralized distributed bayesian estimation.pdf
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.
Improved iterative Bayesian unfolding
D'Agostini, G
2010-01-01
This paper reviews the basic ideas behind a Bayesian unfolding published some years ago and improves their implementation. In particular, uncertainties are now treated at all levels by probability density functions and their propagation is performed by Monte Carlo integration. Thus, small numbers are better handled and the final uncertainty does not rely on the assumption of normality. Theoretical and practical issues concerning the iterative use of the algorithm are also discussed. The new program, implemented in the R language, is freely available, together with sample scripts to play with toy models.
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.
Adaptive Dynamic Bayesian Networks
Energy Technology Data Exchange (ETDEWEB)
Ng, B M
2007-10-26
A discrete-time Markov process can be compactly modeled as a dynamic Bayesian network (DBN)--a graphical model with nodes representing random variables and directed edges indicating causality between variables. Each node has a probability distribution, conditional on the variables represented by the parent nodes. A DBN's graphical structure encodes fixed conditional dependencies between variables. But in real-world systems, conditional dependencies between variables may be unknown a priori or may vary over time. Model errors can result if the DBN fails to capture all possible interactions between variables. Thus, we explore the representational framework of adaptive DBNs, whose structure and parameters can change from one time step to the next: a distribution's parameters and its set of conditional variables are dynamic. This work builds on recent work in nonparametric Bayesian modeling, such as hierarchical Dirichlet processes, infinite-state hidden Markov networks and structured priors for Bayes net learning. In this paper, we will explain the motivation for our interest in adaptive DBNs, show how popular nonparametric methods are combined to formulate the foundations for adaptive DBNs, and present preliminary results.
Bayesian analysis toolkit - BAT
International Nuclear Information System (INIS)
Statistical treatment of data is an essential part of any data analysis and interpretation. Different statistical methods and approaches can be used, however the implementation of these approaches is complicated and at times inefficient. The Bayesian analysis toolkit (BAT) is a software package developed in C++ framework that facilitates the statistical analysis of the data using Bayesian theorem. The tool evaluates the posterior probability distributions for models and their parameters using Markov Chain Monte Carlo which in turn provide straightforward parameter estimation, limit setting and uncertainty propagation. Additional algorithms, such as simulated annealing, allow extraction of the global mode of the posterior. BAT sets a well-tested environment for flexible model definition and also includes a set of predefined models for standard statistical problems. The package is interfaced to other software packages commonly used in high energy physics, such as ROOT, Minuit, RooStats and CUBA. We present a general overview of BAT and its algorithms. A few physics examples are shown to introduce the spectrum of its applications. In addition, new developments and features are summarized.
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...
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)
DEFF Research Database (Denmark)
Hartelius, Karsten; Carstensen, Jens Michael
2003-01-01
A method for locating distorted grid structures in images is presented. The method is based on the theories of template matching and Bayesian image restoration. The grid is modeled as a deformable template. Prior knowledge of the grid is described through a Markov random field (MRF) model which...... represents the spatial coordinates of the grid nodes. Knowledge of how grid nodes are depicted in the observed image is described through the observation model. The prior consists of a node prior and an arc (edge) prior, both modeled as Gaussian MRFs. The node prior models variations in the positions of grid...... nodes and the arc prior models variations in row and column spacing across the grid. Grid matching is done by placing an initial rough grid over the image and applying an ensemble annealing scheme to maximize the posterior distribution of the grid. The method can be applied to noisy images with missing...
Kobayashi, T
1993-01-01
Conjugated polymers are attractive from the viewpoint of possible applications as novel nonlinear optical materials and conductive materials. They are also very important as a group of materials of one dimensionality. The progress of research in this field is very rapid. At the present stage it is extremely useful to have review articles giving information on the most recent progress.Relaxation in Polymers contains state-of-the-art reviews on: ultrafast responses in various conjugated polymers with large optical nonlinearity; ultrafast relaxation in polysilanes; electronic properties of polysi
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...
A Bayesian variable selection procedure for ranking overlapping gene sets
DEFF Research Database (Denmark)
Skarman, Axel; Mahdi Shariati, Mohammad; Janss, Luc;
2012-01-01
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...... 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...
Current trends in Bayesian methodology with applications
Upadhyay, Satyanshu K; Dey, Dipak K; Loganathan, Appaia
2015-01-01
Collecting Bayesian material scattered throughout the literature, Current Trends in Bayesian Methodology with Applications examines the latest methodological and applied aspects of Bayesian statistics. The book covers biostatistics, econometrics, reliability and risk analysis, spatial statistics, image analysis, shape analysis, Bayesian computation, clustering, uncertainty assessment, high-energy astrophysics, neural networking, fuzzy information, objective Bayesian methodologies, empirical Bayes methods, small area estimation, and many more topics.Each chapter is self-contained and focuses on
Bayesian 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...
Portfolio Allocation for Bayesian Optimization
Brochu, Eric; Hoffman, Matthew W.; 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 uses Bayesian methods to sample the objective efficiently using an acquisition function which incorporates the model's estimate of the objective and the uncertainty at any given point. However, there are several differen...
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...
Bayesian Networks and Influence Diagrams
DEFF Research Database (Denmark)
Kjærulff, Uffe Bro; Madsen, Anders Læsø
Probabilistic networks, also known as Bayesian networks and influence diagrams, have become one of the most promising technologies in the area of applied artificial intelligence, offering intuitive, efficient, and reliable methods for diagnosis, prediction, decision making, classification......, troubleshooting, and data mining under uncertainty. Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis provides a comprehensive guide for practitioners who wish to understand, construct, and analyze intelligent systems for decision support based on probabilistic networks. Intended...
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.
... 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. ...
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 ...
BAT - Bayesian Analysis Toolkit
International Nuclear Information System (INIS)
One of the most vital steps in any data analysis is the statistical analysis and comparison with the prediction of a theoretical model. The many uncertainties associated with the theoretical model and the observed data require a robust statistical analysis tool. The Bayesian Analysis Toolkit (BAT) is a powerful statistical analysis software package based on Bayes' Theorem, developed to evaluate the posterior probability distribution for models and their parameters. It implements Markov Chain Monte Carlo to get the full posterior probability distribution that in turn provides a straightforward parameter estimation, limit setting and uncertainty propagation. Additional algorithms, such as Simulated Annealing, allow to evaluate the global mode of the posterior. BAT is developed in C++ and allows for a flexible definition of models. A set of predefined models covering standard statistical cases are also included in BAT. It has been interfaced to other commonly used software packages such as ROOT, Minuit, RooStats and CUBA. An overview of the software and its algorithms is provided along with several physics examples to cover a range of applications of this statistical tool. Future plans, new features and recent developments are briefly discussed.
Dielectric Relaxation of Hexadeutero Dimethylsulfoxide
Betting, H.; Stockhausen, M.
1999-11-01
The dielectric relaxation parameters of the title substance (DMSO-d6) in its pure liquid state are determined from meas-urements up to 72 GHz at 20°C in comparison to protonated DMSO. While the relaxation strengths do not differ, the relax-ation time of DMSO-d 6 is significantly longer (21.3 ps) than that of DMSO (19.5 ps).
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
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.
Bayesian seismic AVO inversion
Energy Technology Data Exchange (ETDEWEB)
Buland, Arild
2002-07-01
A new linearized AVO inversion technique is developed in a Bayesian framework. The objective is to obtain posterior distributions for P-wave velocity, S-wave velocity and density. Distributions for other elastic parameters can also be assessed, for example acoustic impedance, shear impedance and P-wave to S-wave velocity ratio. The inversion algorithm is based on the convolutional model and a linearized weak contrast approximation of the Zoeppritz equation. The solution is represented by a Gaussian posterior distribution with explicit expressions for the posterior expectation and covariance, hence exact prediction intervals for the inverted parameters can be computed under the specified model. The explicit analytical form of the posterior distribution provides a computationally fast inversion method. Tests on synthetic data show that all inverted parameters were almost perfectly retrieved when the noise approached zero. With realistic noise levels, acoustic impedance was the best determined parameter, while the inversion provided practically no information about the density. The inversion algorithm has also been tested on a real 3-D dataset from the Sleipner Field. The results show good agreement with well logs but the uncertainty is high. The stochastic model includes uncertainties of both the elastic parameters, the wavelet and the seismic and well log data. The posterior distribution is explored by Markov chain Monte Carlo simulation using the Gibbs sampler algorithm. The inversion algorithm has been tested on a seismic line from the Heidrun Field with two wells located on the line. The uncertainty of the estimated wavelet is low. In the Heidrun examples the effect of including uncertainty of the wavelet and the noise level was marginal with respect to the AVO inversion results. We have developed a 3-D linearized AVO inversion method with spatially coupled model parameters where the objective is to obtain posterior distributions for P-wave velocity, S
Bayesian 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 ...
Dielectric relaxation and hydrogen diffusion in amorphous silicon
Energy Technology Data Exchange (ETDEWEB)
Phillips, J.C. (AT and T Bell Labs., Murray Hill, NJ (United States))
1994-04-01
Hydrogen diffusion is technologically critical to the processing of amorphous Si for solar cell applications. It is shown that this diffusion belongs to a broad class of dielectric relaxation mechanisms which were first studied by Kohlrausch in 1847. A microscopic theory of the Kohlrausch relaxation constant [beta][sub K] is also constructed. This theory explains the values of [beta] observed in many electronic, molecular and polymeric relaxation processes. It is based on two novel concepts: Wiener sausages, from statistical mechanics, and the magic wand, from axiomatic set theory
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
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 methods for proteomic biomarker development
Directory of Open Access Journals (Sweden)
Belinda Hernández
2015-12-01
In this review we provide an introduction to Bayesian inference and demonstrate some of the advantages of using a Bayesian framework. We summarize how Bayesian methods have been used previously in proteomics and other areas of bioinformatics. Finally, we describe some popular and emerging Bayesian models from the statistical literature and provide a worked tutorial including code snippets to show how these methods may be applied for the evaluation of proteomic biomarkers.
Bayesian variable 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 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.
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 Model Averaging for Propensity Score Analysis
Kaplan, David; Chen, Jianshen
2013-01-01
The purpose of this study is to explore Bayesian model averaging in the propensity score context. Previous research on Bayesian propensity score analysis does not take into account model uncertainty. In this regard, an internally consistent Bayesian framework for model building and estimation must also account for model uncertainty. The…
Bayesian 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 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
Vinther, Jakob; Sperling, Erik A; Briggs, Derek E G; Peterson, Kevin J
2012-04-01
Aplacophorans have long been argued to be basal molluscs. We present a molecular phylogeny, including the aplacophorans Neomeniomorpha (Solenogastres) and Chaetodermomorpha (Caudofoveata), which recovered instead the clade Aculifera (Aplacophora + Polyplacophora). Our relaxed Bayesian molecular clock estimates an Early Ordovician appearance of the aculiferan crown group consistent with the presence of chiton-like molluscs with seven or eight dorsal shell plates by the Late Cambrian (approx. 501-490 Ma). Molecular, embryological and palaeontological data indicate that aplacophorans, as well as chitons, evolved from a paraphyletic assemblage of chiton-like ancestors. The recovery of cephalopods as a sister group to aculiferans suggests that the plesiomorphic condition in molluscs might be a morphology similar to that found in monoplacophorans. PMID:21976685
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.
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 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 in...
ANALYSIS OF BAYESIAN CLASSIFIER ACCURACY
Directory of Open Access Journals (Sweden)
Felipe Schneider Costa
2013-01-01
Full Text Available The naÃ¯ve Bayes classifier is considered one of the most effective classification algorithms today, competing with more modern and sophisticated classifiers. Despite being based on unrealistic (naÃ¯ve assumption that all variables are independent, given the output class, the classifier provides proper results. However, depending on the scenario utilized (network structure, number of samples or training cases, number of variables, the network may not provide appropriate results. This study uses a process variable selection, using the chi-squared test to verify the existence of dependence between variables in the data model in order to identify the reasons which prevent a Bayesian network to provide good performance. A detailed analysis of the data is also proposed, unlike other existing work, as well as adjustments in case of limit values between two adjacent classes. Furthermore, variable weights are used in the calculation of a posteriori probabilities, calculated with mutual information function. Tests were applied in both a naÃ¯ve Bayesian network and a hierarchical Bayesian network. After testing, a significant reduction in error rate has been observed. The naÃ¯ve Bayesian network presented a drop in error rates from twenty five percent to five percent, considering the initial results of the classification process. In the hierarchical network, there was not only a drop in fifteen percent error rate, but also the final result came to zero.
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 Networks and Influence Diagrams
DEFF Research Database (Denmark)
Kjærulff, Uffe Bro; Madsen, Anders Læsø
Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis, Second Edition, provides a comprehensive guide for practitioners who wish to understand, construct, and analyze intelligent systems for decision support based on probabilistic networks. This new edition contains six new...
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...
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.)
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...
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...
Temperature Relaxation in Hot Dense Hydrogen
Murillo, Michael S.; Dharma-wardana, M. W. C.
2007-01-01
Temperature equilibration of hydrogen is studied for conditions relevant to inertial confinement fusion. New molecular-dynamics simulations and results from quantum many-body theory are compared with Landau-Spitzer (LS) predictions for temperatures T from 50 eV to 5000 eV, and densities with Wigner-Seitz radii r_s = 1.0 and 0.5. The relaxation is slower than the LS result, even for temperatures in the keV range, but converges to agreement in the high-T limit.
Structural relaxation of amorphous silicon carbide
International Nuclear Information System (INIS)
We have examined amorphous structures of silicon carbide (SiC) using both transmission electron microscopy and a molecular-dynamics approach. Radial distribution functions revealed that amorphous SiC contains not only heteronuclear (Si-C) bonds but also homonuclear (Si-Si and C-C) bonds. The ratio of heteronuclear to homonuclear bonds was found to change upon annealing, suggesting that structural relaxation of the amorphous SiC occurred. Good agreement was obtained between the simulated and experimentally measured radial distribution functions
Structural relaxation of amorphous silicon carbide.
Ishimaru, Manabu; Bae, In-Tae; Hirotsu, Yoshihiko; Matsumura, Syo; Sickafus, Kurt E
2002-07-29
We have examined amorphous structures of silicon carbide (SiC) using both transmission electron microscopy and a molecular-dynamics approach. Radial distribution functions revealed that amorphous SiC contains not only heteronuclear (Si-C) bonds but also homonuclear (Si-Si and C-C) bonds. The ratio of heteronuclear to homonuclear bonds was found to change upon annealing, suggesting that structural relaxation of the amorphous SiC occurred. Good agreement was obtained between the simulated and experimentally measured radial distribution functions. PMID:12144449
Excited-state relaxation of some aminoquinolines
Directory of Open Access Journals (Sweden)
B. M. Uzhinov
2006-04-01
Full Text Available The absorption and fluorescence spectra, fluorescence quantum yields and lifetimes, and fluorescence rate constants (kf of 2-amino-3-(2Ã¢Â€Â²-benzoxazolylquinoline (I, 2-amino-3-(2Ã¢Â€Â²-benzothiazolylquinoline (II, 2-amino-3-(2Ã¢Â€Â²-methoxybenzothiazolyl-quinoline (III, 2-amino-3-(2Ã¢Â€Â²-benzothiazolylbenzoquinoline (IV at different temperatures have been measured. The shortwavelength shift of fluorescence spectra of compounds studied (23Ã¢Â€Â“49 nm in ethanol as the temperature decreases (the solvent viscosity increases points out that the excited-state relaxation process takes place. The rate of this process depends essentially on the solvent viscosity, but not the solvent polarity. The essential increasing of fluorescence rate constant kf (up to about 7 times as the solvent viscosity increases proves the existence of excited-state structural relaxation consisting in the mutual internal rotation of molecular fragments of aminoquinolines studied, followed by the solvent orientational relaxation.
Tsvetkov, N. V.; Mikhailova, M. E.; Lebedeva, E. V.; Lezov, A. A.; Rogozhin, V. B.; Rotinyan, T. A.
2016-03-01
Free relaxation of electric birefringence in tetrachloromethane solution of high molecular weight poly(butyl-isocyanate) was studied. The effect of electric field strength on the average relaxation time was observed. The relaxation spectrum was analyzed using the Rouse and Zimm theories. With increase in the electric field strength, the contribution of fast (deformation) relaxation modes also increased significantly. It is assumed that certain changes in intramolecular mobility occur under the influence of electric field.
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.
Attention in a bayesian framework
DEFF Research Database (Denmark)
Whiteley, Louise Emma; Sahani, Maneesh
2012-01-01
include both selective phenomena, where attention is invoked by cues that point to particular stimuli, and integrative phenomena, where attention is invoked dynamically by endogenous processing. However, most previous Bayesian accounts of attention have focused on describing relatively simple experimental...... settings, where cues shape expectations about a small number of upcoming stimuli and thus convey "prior" information about clearly defined objects. While operationally consistent with the experiments it seeks to describe, this view of attention as prior seems to miss many essential elements of both its......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...
Bayesian Sampling using Condition Indicators
DEFF Research Database (Denmark)
Faber, Michael H.; Sørensen, John Dalsgaard
2002-01-01
allows for a Bayesian formulation of the indicators whereby the experience and expertise of the inspection personnel may be fully utilized and consistently updated as frequentistic information is collected. The approach is illustrated on an example considering a concrete structure subject to corrosion......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. This...
BAYESIAN IMAGE RESTORATION, USING CONFIGURATIONS
Directory of Open Access Journals (Sweden)
Thordis Linda Thorarinsdottir
2011-05-01
Full Text Available In this paper, we develop a Bayesian procedure for removing noise from images that can be viewed as noisy realisations of random sets in the plane. The procedure utilises recent advances in configuration theory for noise free random sets, where the probabilities of observing the different boundary configurations are expressed in terms of the mean normal measure of the random set. These probabilities are used as prior probabilities in a Bayesian image restoration approach. Estimation of the remaining parameters in the model is outlined for salt and pepper noise. The inference in the model is discussed in detail for 3 X 3 and 5 X 5 configurations and examples of the performance of the procedure are given.
Bayesian Seismology of the Sun
Gruberbauer, Michael
2013-01-01
We perform a Bayesian grid-based analysis of the solar l=0,1,2 and 3 p modes obtained via BiSON in order to deliver the first Bayesian asteroseismic analysis of the solar composition problem. We do not find decisive evidence to prefer either of the contending chemical compositions, although the revised solar abundances (AGSS09) are more probable in general. We do find indications for systematic problems in standard stellar evolution models, unrelated to the consequences of inadequate modelling of the outer layers on the higher-order modes. The seismic observables are best fit by solar models that are several hundred million years older than the meteoritic age of the Sun. Similarly, meteoritic age calibrated models do not adequately reproduce the observed seismic observables. Our results suggest that these problems will affect any asteroseismic inference that relies on a calibration to the Sun.
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 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...
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
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...
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 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 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 ...
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.
Skill Rating by Bayesian Inference
Di Fatta, Giuseppe; Haworth, Guy McCrossan; Regan, Kenneth W.
2009-01-01
Systems Engineering often involves computer modelling the behaviour of proposed systems and their components. Where a component is human, fallibility must be modelled by a stochastic agent. The identification of a model of decision-making over quantifiable options is investigated using the game-domain of Chess. Bayesian methods are used to infer the distribution of players’ skill levels from the moves they play rather than from their competitive results. The approach is used on large sets of ...
Topics in Nonparametric Bayesian Statistics
2003-01-01
The intersection set of Bayesian and nonparametric statistics was almost empty until about 1973, but now seems to be growing at a healthy rate. This chapter gives an overview of various theoretical and applied research themes inside this field, partly complementing and extending recent reviews of Dey, Müller and Sinha (1998) and Walker, Damien, Laud and Smith (1999). The intention is not to be complete or exhaustive, but rather to touch on research areas of interest, partly by example.
Cover Tree Bayesian Reinforcement Learning
Tziortziotis, Nikolaos; Dimitrakakis, Christos; Blekas, Konstantinos
2013-01-01
This paper proposes an online tree-based Bayesian approach for reinforcement learning. For inference, we employ a generalised context tree model. This defines a distribution on multivariate Gaussian piecewise-linear models, which can be updated in closed form. The tree structure itself is constructed using the cover tree method, which remains efficient in high dimensional spaces. We combine the model with Thompson sampling and approximate dynamic programming to obtain effective exploration po...
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 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...
Bayesian Optimization for Adaptive MCMC
Mahendran, Nimalan; Wang, Ziyu; Hamze, Firas; De Freitas, Nando
2011-01-01
This paper proposes a new randomized strategy for adaptive MCMC using Bayesian optimization. This approach applies to non-differentiable objective functions and trades off exploration and exploitation to reduce the number of potentially costly objective function evaluations. We demonstrate the strategy in the complex setting of sampling from constrained, discrete and densely connected probabilistic graphical models where, for each variation of the problem, one needs to adjust the parameters o...
Inference in hybrid Bayesian networks
DEFF Research Database (Denmark)
Lanseth, Helge; Nielsen, Thomas Dyhre; Rumí, Rafael;
2009-01-01
and reliability block diagrams). However, limitations in the BNs' calculation engine have prevented BNs from becoming equally popular for domains containing mixtures of both discrete and continuous variables (so-called hybrid domains). In this paper we focus on these difficulties, and summarize some of the last...... decade's research on inference in hybrid Bayesian networks. The discussions are linked to an example model for estimating human reliability....
Quantile pyramids for Bayesian nonparametrics
2009-01-01
P\\'{o}lya trees fix partitions and use random probabilities in order to construct random probability measures. With quantile pyramids we instead fix probabilities and use random partitions. For nonparametric Bayesian inference we use a prior which supports piecewise linear quantile functions, based on the need to work with a finite set of partitions, yet we show that the limiting version of the prior exists. We also discuss and investigate an alternative model based on the so-called substitut...
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 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 Credit Ratings (new version)
Paola Cerchiello; Paolo Giudici
2013-01-01
In this contribution we aim at improving ordinal variable selection in the context of causal models. In this regard, we propose an approach that provides a formal inferential tool to compare the explanatory power of each covariate, and, therefore, to select an effective model for classification purposes. Our proposed model is Bayesian nonparametric, and, thus, keeps the amount of model specification to a minimum. We consider the case in which information from the covariates is at the ordinal ...
Sobotka, Martin
2014-01-01
Objekt SPORT & RELAX CENTRUM je novostavba tvořena nosným ŽB monolitickým skeletem. Výplňové zdivo je tvořeno z pórobetonových tvárnic YTONG. Zateplení je provedeno z desek z minerální vlny. Fasáda je provětrávaná a vytvořena z fasádních vláknocementových desek. Objekt je dvoupodlažní, podsklepený. Základové konstrukce jsou železobetonové monolitické pasy a patky. Schodiště je tříramenné monolitické železobetonové. Objekt je zastřešený plochou jednoplášťovou střechou, nad částí restauračního ...
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.
Quantum Inference on Bayesian Networks
Yoder, Theodore; Low, Guang Hao; Chuang, Isaac
2014-03-01
Because quantum physics is naturally probabilistic, it seems reasonable to expect physical systems to describe probabilities and their evolution in a natural fashion. Here, we use quantum computation to speedup sampling from a graphical probability model, the Bayesian network. A specialization of this sampling problem is approximate Bayesian inference, where the distribution on query variables is sampled given the values e of evidence variables. Inference is a key part of modern machine learning and artificial intelligence tasks, but is known to be NP-hard. Classically, a single unbiased sample is obtained from a Bayesian network on n variables with at most m parents per node in time (nmP(e) - 1 / 2) , depending critically on P(e) , the probability the evidence might occur in the first place. However, by implementing a quantum version of rejection sampling, we obtain a square-root speedup, taking (n2m P(e) -1/2) time per sample. The speedup is the result of amplitude amplification, which is proving to be broadly applicable in sampling and machine learning tasks. In particular, we provide an explicit and efficient circuit construction that implements the algorithm without the need for oracle access.
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...
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...
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.
Spin relaxation experiments on surfaces
International Nuclear Information System (INIS)
The following topics are considered: generic treatment of nuclear spin relaxation on surfaces; spin relaxation experiments with polarized alkali nuclei on hot transition-metal surfaces; and prospects for studying spin relaxation of hydrogen and other polarized nuclei on arbitrary surfaces. The experimental results achieved thus far have been mostly for polycrystalline materials. But while this might be considered a weakness for basic surface-science studies, it in fact shows the power of the technique for polarized target applications. Polarized target walls, after all, are unlikely to be single-crystal surfaces
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 ...
Ultrafast Librational Relaxation of H2O in Liquid Water
DEFF Research Database (Denmark)
Petersen, Jakob; Møller, Klaus Braagaard; Rey, Rossend;
2013-01-01
The ultrafast librational (hindered rotational) relaxation of a rotationally excited H2O molecule in pure liquid water is investigated by means of classical nonequilibrium molecular dynamics simulations and a power and work analysis. This analysis allows the mechanism of the energy transfer from...
Bayesian networks with applications in reliability analysis
Langseth, Helge
2002-01-01
A common goal of the papers in this thesis is to propose, formalize and exemplify the use of Bayesian networks as a modelling tool in reliability analysis. The papers span work in which Bayesian networks are merely used as a modelling tool (Paper I), work where models are specially designed to utilize the inference algorithms of Bayesian networks (Paper II and Paper III), and work where the focus has been on extending the applicability of Bayesian networks to very large domains (Paper IV and ...
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.
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.
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.
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...
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......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...... and vice 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...
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.
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...
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.)
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
Bayesian Methods and Universal Darwinism
Campbell, John
2009-12-01
Bayesian methods since the time of Laplace have been understood by their practitioners as closely aligned to the scientific method. Indeed a recent Champion of Bayesian methods, E. T. Jaynes, titled his textbook on the subject Probability Theory: the Logic of Science. Many philosophers of science including Karl Popper and Donald Campbell have interpreted the evolution of Science as a Darwinian process consisting of a `copy with selective retention' algorithm abstracted from Darwin's theory of Natural Selection. Arguments are presented for an isomorphism between Bayesian Methods and Darwinian processes. Universal Darwinism, as the term has been developed by Richard Dawkins, Daniel Dennett and Susan Blackmore, is the collection of scientific theories which explain the creation and evolution of their subject matter as due to the Operation of Darwinian processes. These subject matters span the fields of atomic physics, chemistry, biology and the social sciences. The principle of Maximum Entropy states that Systems will evolve to states of highest entropy subject to the constraints of scientific law. This principle may be inverted to provide illumination as to the nature of scientific law. Our best cosmological theories suggest the universe contained much less complexity during the period shortly after the Big Bang than it does at present. The scientific subject matter of atomic physics, chemistry, biology and the social sciences has been created since that time. An explanation is proposed for the existence of this subject matter as due to the evolution of constraints in the form of adaptations imposed on Maximum Entropy. It is argued these adaptations were discovered and instantiated through the Operations of a succession of Darwinian processes.
Bayesian 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.
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 inference for Hawkes processes
DEFF Research Database (Denmark)
Rasmussen, Jakob Gulddahl
The Hawkes process is a practically and theoretically important class of point processes, but parameter-estimation for such a process can pose various problems. In this paper we explore and compare two approaches to Bayesian inference. The first approach is based on the so-called conditional...... intensity function, while the second approach is based on an underlying clustering and branching structure in the Hawkes process. For practical use, MCMC (Markov chain Monte Carlo) methods are employed. The two approaches are compared numerically using three examples of the Hawkes process....
Bayesian inference for Hawkes processes
DEFF Research Database (Denmark)
Rasmussen, Jakob Gulddahl
2013-01-01
The Hawkes process is a practically and theoretically important class of point processes, but parameter-estimation for such a process can pose various problems. In this paper we explore and compare two approaches to Bayesian inference. The first approach is based on the so-called conditional...... intensity function, while the second approach is based on an underlying clustering and branching structure in the Hawkes process. For practical use, MCMC (Markov chain Monte Carlo) methods are employed. The two approaches are compared numerically using three examples of the Hawkes process....
Collaborative Kalman Filtration: Bayesian Perspective
Czech Academy of Sciences Publication Activity Database
Dedecius, Kamil
Lisabon, Portugalsko: Institute for Systems and Technologies of Information, Control and Communication (INSTICC), 2014, s. 468-474. ISBN 978-989-758-039-0. [11th International Conference on Informatics in Control, Automation and Robotics - ICINCO 2014. Vien (AT), 01.09.2014-03.09.2014] R&D Projects: GA ČR(CZ) GP14-06678P Institutional support: RVO:67985556 Keywords : Bayesian analysis * Kalman filter * distributed estimation Subject RIV: BB - Applied Statistics, Operational Research http://library.utia.cas.cz/separaty/2014/AS/dedecius-0431324.pdf
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.
Bayesian Decision Theoretical Framework for Clustering
Chen, Mo
2011-01-01
In this thesis, we establish a novel probabilistic framework for the data clustering problem from the perspective of Bayesian decision theory. The Bayesian decision theory view justifies the important questions: what is a cluster and what a clustering algorithm should optimize. We prove that the spectral clustering (to be specific, the…
Bayesian Statistics for Biological Data: Pedigree Analysis
Stanfield, William D.; Carlton, Matthew A.
2004-01-01
The use of Bayes' formula is applied to the biological problem of pedigree analysis to show that the Bayes' formula and non-Bayesian or "classical" methods of probability calculation give different answers. First year college students of biology can be introduced to the Bayesian statistics.
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…
Nonparametric Bayesian Modeling of Complex Networks
DEFF Research Database (Denmark)
Schmidt, Mikkel Nørgaard; Mørup, Morten
2013-01-01
Modeling structure in complex networks using Bayesian nonparametrics makes it possible to specify flexible model structures and infer the adequate model complexity from the observed data. This article provides a gentle introduction to nonparametric Bayesian modeling of complex networks: Using...... for complex networks can be derived and point out relevant literature....
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 ...
Compiling Relational Bayesian Networks for Exact Inference
DEFF Research Database (Denmark)
Jaeger, Manfred; Darwiche, Adnan; Chavira, Mark
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 eva...
Bayesian analysis of exoplanet and binary orbits
Schulze-Hartung, Tim; 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.
Computational methods for Bayesian model choice
Robert, Christian P.; Wraith, Darren
2009-01-01
In this note, we shortly survey some recent approaches on the approximation of the Bayes factor used in Bayesian hypothesis testing and in Bayesian model choice. In particular, we reassess importance sampling, harmonic mean sampling, and nested sampling from a unified perspective.
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
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...
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. PMID:26776199
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
Nuclear spin dipolar relaxation in paramagnetic systems undergoing multiple internal motions
International Nuclear Information System (INIS)
A theoretical treatment is proposed for the relaxation induced by the dipolar interaction between two spins separated by several bonds. The influence of the internal and overall molecular motions upon the carbon 13 longitudinal relaxation is discussed on the model of n-butylamine coordinated to a paramagnetic ion having a comparatively long electron spin relaxation time like Mn2+. A computer program has been made to analyze in terms of internal motions and transient conformations the 13C longitudinal dipolar relaxation in flexible and partially rigid molecules. The calculations of 13C relaxation rates have been also applied to the conformational study of less simple molecules undergoind several internal motions as leucine and norleucine coordinated to Gd3+ in aqueous solution. Numerical values are given on electron spin relaxation time and reorientation correlation time for these molecules: Mn, Ni, La, Gd, Dy amino-complexes and leucine and norleucine complexes
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...
Gekoppelte molekulare Umlagerungen als Ursache von Relaxation und Fließen
Holzmüller, W.
Relaxation und Fließen beruhen auf molekularen Umlagerungen, wobei strukturbedingte Haftstellen gekoppelte Platzwechsel verursachen. Das Verhalten wird durch ein System simultaner Differentialgleichungen beschrieben. Je nach den Anfangs- und Randbedingungen treten unterschiedliche in einer Tabelle zusammengefaßte Lösungen auf.Translated AbstractCoupled Molecular Dislocation Processes Causing Relaxation and FlowRelaxation and flowing processes are caused by molecular displacements. Coupled dislocation processes occur if there are adhering places depending on structure. The behavior will be described by a system of simultaneous differential equations. The results for many cases are recorded in a schedule.
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.
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.
Electron spin relaxation in cryptochrome-based magnetoreception.
Kattnig, Daniel R; Solov'yov, Ilia A; Hore, P J
2016-05-14
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 a significant effect on the coherent spin dynamics of the radicals. It is generally assumed that evolutionary pressure has led to protection of the electron spins from irreversible loss of coherence in order that the underlying quantum dynamics can survive in a noisy biological environment. Here, we address this question for a structurally characterized model cryptochrome expected to share many properties with the putative avian receptor protein. To this end we combine all-atom molecular dynamics simulations, Bloch-Redfield relaxation theory and spin dynamics calculations to assess the effects of spin relaxation on the performance of the protein as a compass sensor. Both flavin-tryptophan and flavin-Z˙ radical pairs are studied (Z˙ is a radical with no hyperfine interactions). Relaxation is considered to arise from modulation of hyperfine interactions by librational motions of the radicals and fluctuations in certain dihedral angles. For Arabidopsis thaliana cryptochrome 1 (AtCry1) we find that spin relaxation implies optimal radical pair lifetimes of the order of microseconds, and that flavin-Z˙ pairs are less affected by relaxation than flavin-tryptophan pairs. Our results also demonstrate that spin relaxation in isolated AtCry1 is incompatible with the long coherence times that have been postulated to explain the disruption of the avian magnetic compass sense by weak radiofrequency magnetic fields. We conclude that a cryptochrome sensor in vivo would have to differ dynamically, if not structurally, from isolated AtCry1. Our results clearly mark the limits of the current hypothesis and lead to a better understanding of the operation of radical pair magnetic sensors
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 ...
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.
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
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.
Nonparametric Bayesian inference in biostatistics
Müller, Peter
2015-01-01
As chapters in this book demonstrate, BNP has important uses in clinical sciences and inference for issues like unknown partitions in genomics. Nonparametric Bayesian approaches (BNP) play an ever expanding role in biostatistical inference from use in proteomics to clinical trials. Many research problems involve an abundance of data and require flexible and complex probability models beyond the traditional parametric approaches. As this book's expert contributors show, BNP approaches can be the answer. Survival Analysis, in particular survival regression, has traditionally used BNP, but BNP's potential is now very broad. This applies to important tasks like arrangement of patients into clinically meaningful subpopulations and segmenting the genome into functionally distinct regions. This book is designed to both review and introduce application areas for BNP. While existing books provide theoretical foundations, this book connects theory to practice through engaging examples and research questions. Chapters c...
On Bayesian System Reliability Analysis
International Nuclear Information System (INIS)
The view taken in this thesis is that reliability, the probability that a system will perform a required function for a stated period of time, depends on a person's state of knowledge. Reliability changes as this state of knowledge changes, i.e. when new relevant information becomes available. Most existing models for system reliability prediction are developed in a classical framework of probability theory and they overlook some information that is always present. Probability is just an analytical tool to handle uncertainty, based on judgement and subjective opinions. It is argued that the Bayesian approach gives a much more comprehensive understanding of the foundations of probability than the so called frequentistic school. A new model for system reliability prediction is given in two papers. The model encloses the fact that component failures are dependent because of a shared operational environment. The suggested model also naturally permits learning from failure data of similar components in non identical environments. 85 refs
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...
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.
Cooperative extensions of the Bayesian game
Ichiishi, Tatsuro
2006-01-01
This is the very first comprehensive monograph in a burgeoning, new research area - the theory of cooperative game with incomplete information with emphasis on the solution concept of Bayesian incentive compatible strong equilibrium that encompasses the concept of the Bayesian incentive compatible core. Built upon the concepts and techniques in the classical static cooperative game theory and in the non-cooperative Bayesian game theory, the theory constructs and analyzes in part the powerful n -person game-theoretical model characterized by coordinated strategy-choice with individualistic ince
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
Supra-Bayesian Combination of Probability Distributions
Czech Academy of Sciences Publication Activity Database
Sečkárová, Vladimíra
Veszprém : University of Pannonia, 2010, s. 112-117. ISBN 978-615-5044-00-7. [11th International PhD Workshop on Systems and Control. Veszprém (HU), 01.09.2010-03.09.2010] R&D Projects: GA ČR GA102/08/0567 Institutional research plan: CEZ:AV0Z10750506 Keywords : Supra-Bayesian approach * sharing of probabilistic information * Bayesian decision making Subject RIV: BC - Control Systems Theory http://library.utia.cas.cz/separaty/2010/AS/seckarova-supra-bayesian combination of probability distributions.pdf
Bayesian Soft Sensing in Cold Sheet Rolling
Czech Academy of Sciences Publication Activity Database
Dedecius, Kamil; Jirsa, Ladislav
Praha: ÚTIA AV ČR, v.v.i, 2010. s. 45-45. [6th International Workshop on Data–Algorithms–Decision Making. 2.12.2010-4.12.2010, Jindřichův Hradec] R&D Projects: GA MŠk(CZ) 7D09008 Institutional research plan: CEZ:AV0Z10750506 Keywords : soft sensor * bayesian statistics * bayesian model averaging Subject RIV: BB - Applied Statistics, Operational Research http://library.utia.cas.cz/separaty/2010/AS/dedecius-bayesian soft sensing in cold sheet rolling.pdf
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
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...
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.
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.
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
Relaxation times estimation in MRI
Baselice, Fabio; Caivano, Rocchina; Cammarota, Aldo; Ferraioli, Giampaolo; Pascazio, Vito
2014-03-01
Magnetic Resonance Imaging is a very powerful techniques for soft tissue diagnosis. At the present, the clinical evaluation is mainly conducted exploiting the amplitude of the recorded MR image which, in some specific cases, is modified by using contrast enhancements. Nevertheless, spin-lattice (T1) and spin-spin (T2) relaxation times can play an important role in many pathology diagnosis, such as cancer, Alzheimer or Parkinson diseases. Different algorithms for relaxation time estimation have been proposed in literature. In particular, the two most adopted approaches are based on Least Squares (LS) and on Maximum Likelihood (ML) techniques. As the amplitude noise is not zero mean, the first one produces a biased estimator, while the ML is unbiased but at the cost of high computational effort. Recently the attention has been focused on the estimation in the complex, instead of the amplitude, domain. The advantage of working with real and imaginary decomposition of the available data is mainly the possibility of achieving higher quality estimations. Moreover, the zero mean complex noise makes the Least Square estimation unbiased, achieving low computational times. First results of complex domain relaxation times estimation on real datasets are presented. In particular, a patient with an occipital lesion has been imaged on a 3.0T scanner. Globally, the evaluation of relaxation times allow us to establish a more precise topography of biologically active foci, also with respect to contrast enhanced images.
Onsager relaxation of toroidal plasmas
International Nuclear Information System (INIS)
The slow relaxation of isolated toroidal plasmas towards their thermodynamical equilibrium is studied in an Onsager framework based on the entropy metric. The basic tool is a variational principle, equivalent to the kinetic equation, involving the profiles of density, temperature, electric potential, electric current. New minimization procedures are proposed to obtain entropy and entropy production rate functionals. (author)
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++.
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
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++
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.
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.
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 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...
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...
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...
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...
Bayesian Network Models for Adaptive Testing
Czech Academy of Sciences Publication Activity Database
Plajner, Martin; Vomlel, Jiří
Achen: Sun SITE Central Europe, 2016 - (Agosta, J.; Carvalho, R.), s. 24-33. (CEUR Workshop Proceedings. Vol 1565). ISSN 1613-0073. [The Twelfth UAI Bayesian Modeling Applications Workshop (BMAW 2015). Amsterdam (NL), 16.07.2015] R&D Projects: GA ČR GA13-20012S Institutional support: RVO:67985556 Keywords : Bayesian networks * Computerized adaptive testing Subject RIV: JD - Computer Applications, Robotics http://library.utia.cas.cz/separaty/2016/MTR/plajner-0458062.pdf
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.
An Entropy Search Portfolio for Bayesian Optimization
Shahriari, Bobak; Wang, Ziyu; Hoffman, Matthew W.; Bouchard-Côté, Alexandre; De Freitas, Nando
2014-01-01
Bayesian optimization is a sample-efficient method for black-box global optimization. How- ever, the performance of a Bayesian optimization method very much depends on its exploration strategy, i.e. the choice of acquisition function, and it is not clear a priori which choice will result in superior performance. While portfolio methods provide an effective, principled way of combining a collection of acquisition functions, they are often based on measures of past performance which can be misl...
A Bayesian Framework for Active Artificial Perception
Ferreira, Joao; Lobo, Jorge; Bessiere, Pierre; Castelo-Branco, M; Dias, Jorge
2012-01-01
In this text, we present a Bayesian framework for active multimodal perception of 3D structure and motion. The design of this framework finds its inspiration in the role of the dorsal perceptual pathway of the human brain. Its composing models build upon a common egocentric spatial configuration that is naturally fitting for the integration of readings from multiple sensors using a Bayesian approach. In the process, we will contribute with efficient and robust probabilistic solutions for cycl...
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...
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.
Evaluation System for a Bayesian Optimization Service
Dewancker, Ian; McCourt, Michael; Clark, Scott; Hayes, Patrick; Johnson, Alexandra; Ke, George
2016-01-01
Bayesian optimization is an elegant solution to the hyperparameter optimization problem in machine learning. Building a reliable and robust Bayesian optimization service requires careful testing methodology and sound statistical analysis. In this talk we will outline our development of an evaluation framework to rigorously test and measure the impact of changes to the SigOpt optimization service. We present an overview of our evaluation system and discuss how this framework empowers our resea...
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 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 Approach to Handling Informative Sampling
Sikov, Anna
2015-01-01
In the case of informative sampling the sampling scheme explicitly or implicitly depends on the response variable. As a result, the sample distribution of response variable can- not be used for making inference about the population. In this research I investigate the problem of informative sampling from the Bayesian perspective. Application of the Bayesian approach permits solving the problems, which arise due to complexity of the models, being used for handling informative sampling. The main...
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.
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.
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...
NMR relaxation in the magnetic balls system
International Nuclear Information System (INIS)
The mathematical model of nucleon spin relaxation time in the presence of dipole-dipole magnetic interaction is presented. The relaxation times as a temperature function are calculated using an expansion into spherical harmonics series. Results of calculations are presented
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
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.
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
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
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
Inverse problems in the Bayesian framework
International Nuclear Information System (INIS)
The history of Bayesian methods dates back to the original works of Reverend Thomas Bayes and Pierre-Simon Laplace: the former laid down some of the basic principles on inverse probability in his classic article ‘An essay towards solving a problem in the doctrine of chances’ that was read posthumously in the Royal Society in 1763. Laplace, on the other hand, in his ‘Memoirs on inverse probability’ of 1774 developed the idea of updating beliefs and wrote down the celebrated Bayes’ formula in the form we know today. Although not identified yet as a framework for investigating inverse problems, Laplace used the formalism very much in the spirit it is used today in the context of inverse problems, e.g., in his study of the distribution of comets. With the evolution of computational tools, Bayesian methods have become increasingly popular in all fields of human knowledge in which conclusions need to be drawn based on incomplete and noisy data. Needless to say, inverse problems, almost by definition, fall into this category. Systematic work for developing a Bayesian inverse problem framework can arguably be traced back to the 1980s, (the original first edition being published by Elsevier in 1987), although articles on Bayesian methodology applied to inverse problems, in particular in geophysics, had appeared much earlier. Today, as testified by the articles in this special issue, the Bayesian methodology as a framework for considering inverse problems has gained a lot of popularity, and it has integrated very successfully with many traditional inverse problems ideas and techniques, providing novel ways to interpret and implement traditional procedures in numerical analysis, computational statistics, signal analysis and data assimilation. The range of applications where the Bayesian framework has been fundamental goes from geophysics, engineering and imaging to astronomy, life sciences and economy, and continues to grow. There is no question that Bayesian
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...
Bayesian Vision for Shape Recovery
Jalobeanu, Andre
2004-01-01
We present a new Bayesian vision technique that aims at recovering a shape from two or more noisy observations taken under similar lighting conditions. The shape is parametrized by a piecewise linear height field, textured by a piecewise linear irradiance field, and we assume Gaussian Markovian priors for both shape vertices and irradiance variables. The observation process. also known as rendering, is modeled by a non-affine projection (e.g. perspective projection) followed by a convolution with a piecewise linear point spread function. and contamination by additive Gaussian noise. We assume that the observation parameters are calibrated beforehand. The major novelty of the proposed method consists of marginalizing out the irradiances considered as nuisance parameters, which is achieved by Laplace approximations. This reduces the inference to minimizing an energy that only depends on the shape vertices, and therefore allows an efficient Iterated Conditional Mode (ICM) optimization scheme to be implemented. A Gaussian approximation of the posterior shape density is computed, thus providing estimates both the geometry and its uncertainty. We illustrate the effectiveness of the new method by shape reconstruction results in a 2D case. A 3D version is currently under development and aims at recovering a surface from multiple images, reconstructing the topography by marginalizing out both albedo and shading.
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 APPROACH OF DECISION PROBLEMS
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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 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.
Spin-lattice relaxation in phosphorescent triplet state molecules
International Nuclear Information System (INIS)
The present thesis contains the results of a study of spin-lattice relaxation (SLR) in the photo-excited triplet state of aromatic molecules, dissolved in a molecular host crystal. It appears that SLR in phosphorescent triplet state molecules often is related to the presence of so-called (pseudo) localized phonons in the molecular mixed crystals. These local phonons can be thought to correspond with vibrations (librations) of the guest molecule in the force field of the surrounding host molecules. Since the intermolecular forces are relatively weak, the frequencies corresponding with these vibrations are relatively low and usually are of the order of 10-30 cm-1. (Auth.)
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
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
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.
Time of relaxation in dusty plasma model
Timofeev, A. V.
2015-11-01
Dust particles in plasma may have different values of average kinetic energy for vertical and horizontal motion. The partial equilibrium of the subsystems and the relaxation processes leading to this asymmetry are under consideration. A method for the relaxation time estimation in nonideal dusty plasma is suggested. The characteristic relaxation times of vertical and horizontal motion of dust particles in gas discharge are estimated by analytical approach and by analysis of simulation results. These relaxation times for vertical and horizontal subsystems appear to be different. A single hierarchy of relaxation times is proposed.
International Nuclear Information System (INIS)
In the first section, the measurement of total deexcitation cross sections of the 3P2,1,0 and 1P1 argon states by N2, H2, CO and SF6 using a pulsed gas radiolysis technique and 600 keV electrons is discussed. The energy transfer from the resonant states 3P1 and 1P1 of argon (as excited selectively by synchrotron radiation) to the C3πu state of nitrogen has been studied in more detail. On the basis of these results, the different theoretical models for these reactions have been discussed. In the second section, the fluorescence of the second continuum of molecular xenon at around 1700 A, as excited by synchrotron radiation in the region of the 3P1 1S0 resonance line at 1470 A, is considered. A short lived component of the fluorescence decay has been observed; this is attributed to emission at short interatomic distances from the high vibrational levels of Xe2+ (Ou+). The emissions at the left turning point of the potential curve of the Ou+ state has been observed at λ > 2000 A. From these results, the potential curves for the states Xe2 (Og+) and Xe2* (Ou+) have been estimated and the Franck-Condon factors have also been calculated as a function of the wavelength of the fluorescence. (author)
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.
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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
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.
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.
Dimensionality reduction in Bayesian estimation algorithms
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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. PMID:27121574
Bayesian Methods for Medical Test Accuracy
Directory of Open Access Journals (Sweden)
Lyle D. Broemeling
2011-05-01
Full Text Available Bayesian methods for medical test accuracy are presented, beginning with the basic measures for tests with binary scores: true positive fraction, false positive fraction, positive predictive values, and negative predictive value. The Bayesian approach is taken because of its efficient use of prior information, and the analysis is executed with a Bayesian software package WinBUGS®. The ROC (receiver operating characteristic curve gives the intrinsic accuracy of medical tests that have ordinal or continuous scores, and the Bayesian approach is illustrated with many examples from cancer and other diseases. Medical tests include X-ray, mammography, ultrasound, computed tomography, magnetic resonance imaging, nuclear medicine and tests based on biomarkers, such as blood glucose values for diabetes. The presentation continues with more specialized methods suitable for measuring the accuracies of clinical studies that have verification bias, and medical tests without a gold standard. Lastly, the review is concluded with Bayesian methods for measuring the accuracy of the combination of two or more tests.
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.
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
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.
Image compression using constrained relaxation
He, Zhihai
2007-01-01
In this work, we develop a new data representation framework, called constrained relaxation for image compression. Our basic observation is that an image is not a random 2-D array of pixels. They have to satisfy a set of imaging constraints so as to form a natural image. Therefore, one of the major tasks in image representation and coding is to efficiently encode these imaging constraints. The proposed data representation and image compression method not only achieves more efficient data compression than the state-of-the-art H.264 Intra frame coding, but also provides much more resilience to wireless transmission errors with an internal error-correction capability.
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
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...
BAMBI: blind accelerated multimodal Bayesian inference
Graff, Philip; Hobson, Michael P; Lasenby, Anthony
2011-01-01
In this paper we present an algorithm for rapid Bayesian analysis that combines the benefits of nested sampling and artificial neural networks. The blind accelerated multimodal Bayesian inference (BAMBI) algorithm implements the MultiNest package for nested sampling as well as the training of an artificial neural network (NN) to learn the likelihood function. In the case of computationally expensive likelihoods, this allows the substitution of a much more rapid approximation in order to increase significantly the speed of the analysis. We begin by demonstrating, with a few toy examples, the ability of a NN to learn complicated likelihood surfaces. BAMBI's ability to decrease running time for Bayesian inference is then demonstrated in the context of estimating cosmological parameters from WMAP and other observations. We show that valuable speed increases are achieved in addition to obtaining NNs trained on the likelihood functions for the different model and data combinations. These NNs can then be used for an...
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.
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 ...
Bayesian Inference Methods for Sparse Channel Estimation
DEFF Research Database (Denmark)
Pedersen, Niels Lovmand
2013-01-01
inference algorithms based on the proposed prior representation for sparse channel estimation in orthogonal frequency-division multiplexing receivers. The inference algorithms, which are mainly obtained from variational Bayesian methods, exploit the underlying sparse structure of wireless channel responses......This thesis deals with sparse Bayesian learning (SBL) with application to radio channel estimation. As opposed to the classical approach for sparse signal representation, we focus on the problem of inferring complex signals. Our investigations within SBL constitute the basis for the development of...... Bayesian inference algorithms for sparse channel estimation. Sparse inference methods aim at finding the sparse representation of a signal given in some overcomplete dictionary of basis vectors. Within this context, one of our main contributions to the field of SBL is a hierarchical representation of...
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.
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...
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...
Revisiting k-means: New Algorithms via Bayesian Nonparametrics
Kulis, Brian; Jordan, Michael I.
2011-01-01
Bayesian models offer great flexibility for clustering applications---Bayesian nonparametrics can be used for modeling infinite mixtures, and hierarchical Bayesian models can be utilized for sharing clusters across multiple data sets. For the most part, such flexibility is lacking in classical clustering methods such as k-means. In this paper, we revisit the k-means clustering algorithm from a Bayesian nonparametric viewpoint. Inspired by the asymptotic connection between k-means and mixtures...
Cybis, Gabriela Bettella
2014-01-01
Combining models for phenotypic and molecular evolution can lead to powerful inference tools.Under the flexible framework of Bayesian phylogenetics, I develop statistical methods to address phylodynamic problems in this intersection.First, I present a hierarchical phylogeographic method that combines information across multiple datasets to draw inference on a common geographical spread process. Each dataset represents a parallel realization of this geographic process on a different group of ...
An Improved Algorithm of Bayesian Text Categorization
Directory of Open Access Journals (Sweden)
Tao Dong
2011-08-01
Full Text Available Text categorization is a fundamental methodology of text mining and a hot topic of the research of data mining and web mining in recent years. It plays an important role in building traditional information retrieval, web indexing architecture, Web information retrieval, and so on. This paper presents an improved algorithm of text categorization that combines the feature weighting technique with Naïve Bayesian classifier. Experimental results show that using the improved Gini index algorithm to feature weight can improve the performance of Naïve Bayesian classifier effectively. This algorithm obtains good application in the sensitive information recognition system.
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.
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 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...
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.…
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
A SAS Interface for Bayesian Analysis with WinBUGS
Zhang, Zhiyong; McArdle, John J.; Wang, Lijuan; Hamagami, Fumiaki
2008-01-01
Bayesian methods are becoming very popular despite some practical difficulties in implementation. To assist in the practical application of Bayesian methods, we show how to implement Bayesian analysis with WinBUGS as part of a standard set of SAS routines. This implementation procedure is first illustrated by fitting a multiple regression model…
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...
Structural relaxation in a glassy liquid crystal: MBBA
International Nuclear Information System (INIS)
Combined neutron and Raman scattering measurements were performed to analyze the solid polymorphic modifications of a typical nematic liquid crystal substance, MBBA. A glassy solid phase, classified as oriented molecular glass (OMG) may be produced by fast cooling from the nematic phase. A sequence of irreversible phase transitions was observed on reheating OMG. Four different solid modifications were found: two structurally relaxed amorphous 'mesophases' and two crystalline ones. A distinct modification can be found by slow crystallization from the nematic phase and it can be transformed reversibly into an other crystal structure by further cooling. The role of medium range order in the non-crystalline phases and the structural relaxation of the OMG state were analyzed. (author)
Influence of E-beam irradiation on dielectric relaxation of recycled polypropylene
International Nuclear Information System (INIS)
Full text: The dielectric relaxation connected with molecular groups and polymer chain mobility for un-irradiated and e-beam irradiated recycled polypropylene was investigated. It was studied films of samples produced from virgin (initial) and e- beam irradiated of the polymer granules (E-beam source with 5 MeV energy). The dielectric losses were measured with temperature increasing and decreasing regime. The losses were measured with E8-4 bridge help (the frequency is 1kH). Heating velocity was 2 grad/min. The dielectric losses did not appeared in minus temperature region for the initial polypropylene samples. The measurement in temperature increasing and decreasing shows that the relaxation peak at ∼ 35o C for un-irradiated and ∼70o C for irradiated polymer samples connected with macromolecular segments mobility with water molecular groups participation. The main relaxation peak (higher 100o C) shifts after e-beam irradiation is result of the cross-links formation. ) The peak connected with macromolecular segments mobility in polymer amorphous regions (β-relaxation process). In irradiated polypropylene on IR spectroscopy data oxygen molecular groups is increased. The molecular groupings form inter-molecular hydrogen bonds. The intermolecular bonds also hindered molecular groups and macromolecular mobility. The e-beam stimulated cross-links formation was confirmed by method of sol-gel analyses. The work was supported by STCU Fund (Project No 3009)
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.
Structural relaxation in annealed hyperquenched basaltic glasses
DEFF Research Database (Denmark)
Guo, Xiaoju; Mauro, John C.; Potuzak, M.;
2012-01-01
The enthalpy relaxation behavior of hyperquenched (HQ) and annealed hyperquenched (AHQ) basaltic glass is investigated through calorimetric measurements. The results reveal a common onset temperature of the glass transition for all the HQ and AHQ glasses under study, indicating that the primary...... relaxation is activated at the same temperature regardless of the initial departure from equilibrium. The analysis of secondary relaxation at different annealing temperatures provides insights into the enthalpy recovery of HQ glasses....
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...
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
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)
Integer variables estimation problems: the Bayesian approach
Directory of Open Access Journals (Sweden)
G. Venuti
1997-06-01
Full Text Available In geodesy as well as in geophysics there are a number of examples where the unknown parameters are partly constrained to be integer numbers, while other parameters have a continuous range of possible values. In all such situations the ordinary least square principle, with integer variates fixed to the most probable integer value, can lead to paradoxical results, due to the strong non-linearity of the manifold of admissible values. On the contrary an overall estimation procedure assigning the posterior distribution to all variables, discrete and continuous, conditional to the observed quantities, like the so-called Bayesian approach, has the advantage of weighting correctly the possible errors in choosing different sets of integer values, thus providing a more realistic and stable estimate even of the continuous parameters. In this paper, after a short recall of the basics of Bayesian theory in section 2, we present the natural Bayesian solution to the problem of assessing the estimable signal from noisy observations in section 3 and the Bayesian solution to cycle slips detection and repair for a stream of GPS measurements in section 4. An elementary synthetic example is discussed in section 3 to illustrate the theory presented and more elaborate, though synthetic, examples are discussed in section 4 where realistic streams of GPS observations, with cycle slips, are simulated and then back processed.
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 Averaging is Well-Temperated
DEFF Research Database (Denmark)
Hansen, Lars Kai
2000-01-01
Bayesian predictions are stochastic just like predictions of any other inference scheme that generalize from a finite sample. While a simple variational argument shows that Bayes averaging is generalization optimal given that the prior matches the teacher parameter distribution the situation is l...
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.
Explanation mode for Bayesian automatic object recognition
Hazlett, Thomas L.; Cofer, Rufus H.; Brown, Harold K.
1992-09-01
One of the more useful techniques to emerge from AI is the provision of an explanation modality used by the researcher to understand and subsequently tune the reasoning of an expert system. Such a capability, missing in the arena of statistical object recognition, is not that difficult to provide. Long standing results show that the paradigm of Bayesian object recognition is truly optimal in a minimum probability of error sense. To a large degree, the Bayesian paradigm achieves optimality through adroit fusion of a wide range of lower informational data sources to give a higher quality decision--a very 'expert system' like capability. When various sources of incoming data are represented by C++ classes, it becomes possible to automatically backtrack the Bayesian data fusion process, assigning relative weights to the more significant datums and their combinations. A C++ object oriented engine is then able to synthesize 'English' like textural description of the Bayesian reasoning suitable for generalized presentation. Key concepts and examples are provided based on an actual object recognition problem.
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.
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
On Bayesian Nonparametric Continuous Time Series Models
Karabatsos, George; Walker, Stephen G.
2013-01-01
This paper is a note on the use of Bayesian nonparametric mixture models for continuous time series. We identify a key requirement for such models, and then establish that there is a single type of model which meets this requirement. As it turns out, the model is well known in multiple change-point problems.
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
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 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 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
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.
Optimized Bayesian dynamic advising theory and algorithms
Karny, Miroslav
2006-01-01
Written by one of the world''s leading groups in the area of Bayesian identification, control, and decision making, this book provides the theoretical and algorithmic basis of optimized probabilistic advising. It is accompanied by a CD that contains a specialized Matlab-based Mixtools toolbox, and examples illustrating the important areas.
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,...
An Approximate Bayesian Fundamental Frequency Estimator
DEFF Research Database (Denmark)
Nielsen, Jesper Kjær; Christensen, Mads Græsbøll; Jensen, Søren Holdt
Joint fundamental frequency and model order estimation is an important problem in several applications such as speech and music processing. In this paper, we develop an approximate estimation algorithm of these quantities using Bayesian inference. The inference about the fundamental frequency and...
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. The...
Sensitivity to Sampling in Bayesian Word Learning
Xu, Fei; Tenenbaum, Joshua B.
2007-01-01
We report a new study testing our proposal that word learning may be best explained as an approximate form of Bayesian inference (Xu & Tenenbaum, in press). Children are capable of learning word meanings across a wide range of communicative contexts. In different contexts, learners may encounter different sampling processes generating the examples…
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...
Postseismic relaxation and transient creep
Savage, J.C.; Svarc, J.L.; Yu, S.-B.
2005-01-01
Postseismic deformation has been observed in the epicentral area following the 1992 Landers (M = 7.3), 1999 Chi-Chi (M = 7.6), 1999 Hector Mine (M = 7.1), 2002 Denali (M = 7.9), 2003 San Simeon (M = 6.5), and 2004 Parkfield (M = 6.0) earthquakes. The observations consist of repeated GPS measurements of the position of one monument relative to another (separation ???100 km). The early observations (t creep, the early postseismic response may be governed by transient creep as Benioff proposed in 1951. That inference is provisional as the stress conditions prevailing in postseismic relaxation are not identical to the constant stress condition in creep experiments. The observed logarithmic time dependence includes no characteristic time that might aid in identifying the micromechanical cause.
Congestion management utilizing concentric relaxation
Directory of Open Access Journals (Sweden)
Škokljev Ivan
2007-01-01
Full Text Available In the market-oriented power system environment, congestion management is a novel term connoting the power system steady state security functions. A large number of transmission transactions are dispatched in the regional day-ahead market and traverse the network adding to the power flow loading of the grid elements. Congestion is defined as a network security limit violation prospective due to transactions. Congestion management is a set of measures aimed at solving the congestion problem. This paper devises the concentric relaxation assisted approach to open access transmission network congestion management. The DC load flow symbolic simulator generates line power transfer functions. Congestion management is a systematic procedure based on linear programming. The DC load flow symbolic simulator generates all constraints and the black-box optimization library function is used to solve the problem of congestion on a sample IEEE RTS power system.
A tutorial on Bayesian Normal linear regression
Klauenberg, Katy; Wübbeler, Gerd; Mickan, Bodo; Harris, Peter; Elster, Clemens
2015-12-01
Regression is a common task in metrology and often applied to calibrate instruments, evaluate inter-laboratory comparisons or determine fundamental constants, for example. Yet, a regression model cannot be uniquely formulated as a measurement function, and consequently the Guide to the Expression of Uncertainty in Measurement (GUM) and its supplements are not applicable directly. Bayesian inference, however, is well suited to regression tasks, and has the advantage of accounting for additional a priori information, which typically robustifies analyses. Furthermore, it is anticipated that future revisions of the GUM shall also embrace the Bayesian view. Guidance on Bayesian inference for regression tasks is largely lacking in metrology. For linear regression models with Gaussian measurement errors this tutorial gives explicit guidance. Divided into three steps, the tutorial first illustrates how a priori knowledge, which is available from previous experiments, can be translated into prior distributions from a specific class. These prior distributions have the advantage of yielding analytical, closed form results, thus avoiding the need to apply numerical methods such as Markov Chain Monte Carlo. Secondly, formulas for the posterior results are given, explained and illustrated, and software implementations are provided. In the third step, Bayesian tools are used to assess the assumptions behind the suggested approach. These three steps (prior elicitation, posterior calculation, and robustness to prior uncertainty and model adequacy) are critical to Bayesian inference. The general guidance given here for Normal linear regression tasks is accompanied by a simple, but real-world, metrological example. The calibration of a flow device serves as a running example and illustrates the three steps. It is shown that prior knowledge from previous calibrations of the same sonic nozzle enables robust predictions even for extrapolations.
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...
Hydration shell effects in the relaxation dynamics of photoexcited Fe-II complexes in water
Nalbach, P; Frey, M; Grosser, M; Gawelda, W; Galler, A; Assefa, T; Bressler, C; Thorwart, M
2014-01-01
We study the relaxation dynamics of photoexcited Fe-II complexes dissolved in water and identify the relaxation pathway which the molecular complex follows in presence of a hydration shell of bound water at the interface between the complex and the solvent. Starting from a low-spin state, the photoexcited complex can reach the high-spin state via a cascade of different possible transitions involving electronic as well as vibrational relaxation processes. By numerically exact path integral calculations for the relaxational dynamics of a continuous solvent model, we find that the vibrational life times of the intermittent states are of the order of a few ps. Since the electronic rearrangement in the complex occurs on the time scale of about 100 fs, we find that the complex first rearranges itself in a high-spin and highly excited vibrational state, before it relaxes its energy to the solvent via vibrational relaxation transitions. By this, the relaxation pathway can be clearly identified. We find that the life ...
International Nuclear Information System (INIS)
A poly(vinylpyrrolidone-co-butyl acrylate) (60VP-40BA) membrane is synthesized as a tractable and hydrophilic material, obtaining a water-swelling percentage around 60%. An investigation of molecular mobility by means of differential scanning calorimetry, dynamic mechanical analysis and broadband dielectric relaxation spectroscopy (DRS) is fulfilled in the dry membrane. Dielectric and viscoelastic relaxation measurements are carried out on the 60VP-40BA sample at several frequencies between −150 and 150 °C. The dielectric spectrum shows several relaxation processes labelled γ, β and α in increasing order of temperature, whereas in the mechanical spectrum only the β and α relaxation processes are completely defined. In the dielectric measurements, conductive contributions overlap the α-relaxation. The apparent activation energies have similar values for the β-relaxation in both, the mechanical and the dielectric measurements. The β process is a Johari–Golstein secondary relaxation and it is related to the local motions of the pyrrolidone group accompanied by the motion of the segments of the polymer backbone. The γ process is connected with the butyl unit's motions, both located in the side chains of the polymer. (paper)
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
Theory of Activated Relaxation in Nanoscale Confined Liquids
Mirigian, Stephen; Schweizer, Kenneth
2014-03-01
We extend the recently developed Elastically Cooperative Nonlinear Langevin Equation(ECNLE) theory of activated relaxation in supercooled liquids to treat the case of geometrically confined liquids. Generically, confinement of supercooled liquids leads to a speeding up of the dynamics(with a consequent depression of the glass transition temperature) extending on the order of tens of molecular diameters away from a free surface. At present, this behavior is not theoretically well understood. Our theory interprets the speed up in dynamics in terms of two coupled effects. First, a direct surface effect, extending two to three molecular diameters from a free surface, and related to a local rearrangement of molecules with a single cage. The second is a longer ranged ``confinement'' effect, extending tens of molecular diameters from a free surface and related to the long range elastic penalty necessary for a local rearrangement. The theory allows for the calculation of relaxation time and Tg profiles within a given geometry and first principles calculations of relevant length scales. Comparison to both dynamic and pseudo-thermodynamic measurements shows reasonable agreement to experiment with no adjustable parameters.
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.
Superparamagnetic relaxation in alpha-Fe particles
DEFF Research Database (Denmark)
Bødker, Franz; Mørup, Steen; Pedersen, Michael Stanley; Svedlindh, P.; Jonsson, G.T.; Garcia-Palacios, J.L.; Lazaro, F.J.
1998-01-01
The superparamagnetic relaxation time of carbon-supported alpha-Fe particles with an average size of 3.0 Mm has been studied over a large temperature range by the use of Mossbauer spectroscopy combined with AC and DC magnetization measurements. It is found that the relaxation time varies with...
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 ...
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...
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...
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
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.
Simulation for mechanical relaxation and interaction of point defects
International Nuclear Information System (INIS)
A molecular dynamics computer simulation for self-interstitials in copper crystals has been performed by using the embedded atom method potential functions. Configuration and stress distribution around an interstitial are calculated. Interaction energy between two interstitials for parallel and perpendicular configuration is calculated as a function of distance. Thermal vibration and migration of dipole are also investigated by a simulation at a constant temperature, 300 K. The time evolution of the atomic displacement and the power spectra are calculated. A large unstable motion of interstitial atoms in split direction is observed when the interstitial migrate. The method can be applied to the simulation of complex relaxation
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
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....
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
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.
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
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.
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
Thermodynamically consistent Bayesian analysis of closed biochemical reaction systems
Directory of Open Access Journals (Sweden)
Goutsias John
2010-11-01
Full Text Available Abstract Background Estimating the rate constants of a biochemical reaction system with known stoichiometry from noisy time series measurements of molecular concentrations is an important step for building predictive models of cellular function. Inference techniques currently available in the literature may produce rate constant values that defy necessary constraints imposed by the fundamental laws of thermodynamics. As a result, these techniques may lead to biochemical reaction systems whose concentration dynamics could not possibly occur in nature. Therefore, development of a thermodynamically consistent approach for estimating the rate constants of a biochemical reaction system is highly desirable. Results We introduce a Bayesian analysis approach for computing thermodynamically consistent estimates of the rate constants of a closed biochemical reaction system with known stoichiometry given experimental data. Our method employs an appropriately designed prior probability density function that effectively integrates fundamental biophysical and thermodynamic knowledge into the inference problem. Moreover, it takes into account experimental strategies for collecting informative observations of molecular concentrations through perturbations. The proposed method employs a maximization-expectation-maximization algorithm that provides thermodynamically feasible estimates of the rate constant values and computes appropriate measures of estimation accuracy. We demonstrate various aspects of the proposed method on synthetic data obtained by simulating a subset of a well-known model of the EGF/ERK signaling pathway, and examine its robustness under conditions that violate key assumptions. Software, coded in MATLAB®, which implements all Bayesian analysis techniques discussed in this paper, is available free of charge at http://www.cis.jhu.edu/~goutsias/CSS%20lab/software.html. Conclusions Our approach provides an attractive statistical methodology for
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.
The NIFTY way of Bayesian signal inference
International Nuclear Information System (INIS)
We introduce NIFTY, 'Numerical Information Field Theory', a software package for the development of Bayesian signal inference algorithms that operate independently from any underlying spatial grid and its resolution. A large number of Bayesian and Maximum Entropy methods for 1D signal reconstruction, 2D imaging, as well as 3D tomography, appear formally similar, but one often finds individualized implementations that are neither flexible nor easily transferable. Signal inference in the framework of NIFTY can be done in an abstract way, such that algorithms, prototyped in 1D, can be applied to real world problems in higher-dimensional settings. NIFTY as a versatile library is applicable and already has been applied in 1D, 2D, 3D and spherical settings. A recent application is the D3PO algorithm targeting the non-trivial task of denoising, deconvolving, and decomposing photon observations in high energy astronomy
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.
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...
A Bayesian Probabilistic Framework for Rain Detection
Directory of Open Access Journals (Sweden)
Chen Yao
2014-06-01
Full Text Available Heavy rain deteriorates the video quality of outdoor imaging equipments. In order to improve video clearness, image-based and sensor-based methods are adopted for rain detection. In earlier literature, image-based detection methods fall into spatio-based and temporal-based categories. In this paper, we propose a new image-based method by exploring spatio-temporal united constraints in a Bayesian framework. In our framework, rain temporal motion is assumed to be Pathological Motion (PM, which is more suitable to time-varying character of rain steaks. Temporal displaced frame discontinuity and spatial Gaussian mixture model are utilized in the whole framework. Iterated expectation maximization solving method is taken for Gaussian parameters estimation. Pixels state estimation is finished by an iterated optimization method in Bayesian probability formulation. The experimental results highlight the advantage of our method in rain detection.
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...
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 Peak Picking for NMR Spectra
Cheng, Yichen
2014-02-01
Protein structure determination is a very important topic in structural genomics, which helps people to understand varieties of biological functions such as protein-protein interactions, protein–DNA interactions and so on. Nowadays, nuclear magnetic resonance (NMR) has often been used to determine the three-dimensional structures of protein in vivo. This study aims to automate the peak picking step, the most important and tricky step in NMR structure determination. We propose to model the NMR spectrum by a mixture of bivariate Gaussian densities and use the stochastic approximation Monte Carlo algorithm as the computational tool to solve the problem. Under the Bayesian framework, the peak picking problem is casted as a variable selection problem. The proposed method can automatically distinguish true peaks from false ones without preprocessing the data. To the best of our knowledge, this is the first effort in the literature that tackles the peak picking problem for NMR spectrum data using Bayesian method.
Approximate Bayesian Computation: a nonparametric perspective
Blum, Michael
2010-01-01
Approximate Bayesian Computation is a family of likelihood-free inference techniques that are well-suited to models defined in terms of a stochastic generating mechanism. In a nutshell, Approximate Bayesian Computation proceeds by computing summary statistics s_obs from the data and simulating summary statistics for different values of the parameter theta. The posterior distribution is then approximated by an estimator of the conditional density g(theta|s_obs). In this paper, we derive the asymptotic bias and variance of the standard estimators of the posterior distribution which are based on rejection sampling and linear adjustment. Additionally, we introduce an original estimator of the posterior distribution based on quadratic adjustment and we show that its bias contains a fewer number of terms than the estimator with linear adjustment. Although we find that the estimators with adjustment are not universally superior to the estimator based on rejection sampling, we find that they can achieve better perfor...
Probabilistic forecasting and Bayesian data assimilation
Reich, Sebastian
2015-01-01
In this book the authors describe the principles and methods behind probabilistic forecasting and Bayesian data assimilation. Instead of focusing on particular application areas, the authors adopt a general dynamical systems approach, with a profusion of low-dimensional, discrete-time numerical examples designed to build intuition about the subject. Part I explains the mathematical framework of ensemble-based probabilistic forecasting and uncertainty quantification. Part II is devoted to Bayesian filtering algorithms, from classical data assimilation algorithms such as the Kalman filter, variational techniques, and sequential Monte Carlo methods, through to more recent developments such as the ensemble Kalman filter and ensemble transform filters. The McKean approach to sequential filtering in combination with coupling of measures serves as a unifying mathematical framework throughout Part II. Assuming only some basic familiarity with probability, this book is an ideal introduction for graduate students in ap...
Bayesian Magnetohydrodynamic Seismology of Coronal Loops
Arregui, Inigo
2011-01-01
We perform a Bayesian parameter inference in the context of resonantly damped transverse coronal loop oscillations. The forward problem is solved in terms of parametric results for kink waves in one-dimensional flux tubes in the thin tube and thin boundary approximations. For the inverse problem, we adopt a Bayesian approach to infer the most probable values of the relevant parameters, for given observed periods and damping times, and to extract their confidence levels. The posterior probability distribution functions are obtained by means of Markov Chain Monte Carlo simulations, incorporating observed uncertainties in a consistent manner. We find well localized solutions in the posterior probability distribution functions for two of the three parameters of interest, namely the Alfven travel time and the transverse inhomogeneity length-scale. The obtained estimates for the Alfven travel time are consistent with previous inversion results, but the method enables us to additionally constrain the transverse inho...
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.
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.
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.
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
Social optimality in quantum Bayesian games
Iqbal, Azhar; Chappell, James M.; Abbott, Derek
2015-10-01
A significant aspect of the study of quantum strategies is the exploration of the game-theoretic solution concept of the Nash equilibrium in relation to the quantization of a game. Pareto optimality is a refinement on the set of Nash equilibria. A refinement on the set of Pareto optimal outcomes is known as social optimality in which the sum of players' payoffs is maximized. This paper analyzes social optimality in a Bayesian game that uses the setting of generalized Einstein-Podolsky-Rosen experiments for its physical implementation. We show that for the quantum Bayesian game a direct connection appears between the violation of Bell's inequality and the social optimal outcome of the game and that it attains a superior socially optimal outcome.
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...... mechanism efficiently combines distributed learner models without the need to exchange internal structure of local Bayesian networks, nor local evidence between the involved platforms....
Bayesian parameter estimation for effective field theories
Wesolowski, S.; Klco, N.; Furnstahl, R. J.; Phillips, D. R.; Thapaliya, A.
2016-07-01
We present procedures based on Bayesian statistics for estimating, from data, the parameters of effective field theories (EFTs). The extraction of low-energy constants (LECs) is guided by theoretical expectations 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 is developed that analyzes the fit and ensures that the priors do not bias the EFT parameter estimation. The procedures are illustrated using representative model problems, including 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
Quantum-like Representation of Bayesian Updating
Asano, Masanari; Ohya, Masanori; Tanaka, Yoshiharu; Khrennikov, Andrei; Basieva, Irina
2011-03-01
Recently, applications of quantum mechanics to coginitive psychology have been discussed, see [1]-[11]. It was known that statistical data obtained in some experiments of cognitive psychology cannot be described by classical probability model (Kolmogorov's model) [12]-[15]. Quantum probability is one of the most advanced mathematical models for non-classical probability. In the paper of [11], we proposed a quantum-like model describing decision-making process in a two-player game, where we used the generalized quantum formalism based on lifting of density operators [16]. In this paper, we discuss the quantum-like representation of Bayesian inference, which has been used to calculate probabilities for decision making under uncertainty. The uncertainty is described in the form of quantum superposition, and Bayesian updating is explained as a reduction of state by quantum measurement.
Distributed Detection via Bayesian Updates and Consensus
Liu, Qipeng; Wang, Xiaofan
2014-01-01
In this paper, we discuss a class of distributed detection algorithms which can be viewed as implementations of Bayes' law in distributed settings. Some of the algorithms are proposed in the literature most recently, and others are first developed in this paper. The common feature of these algorithms is that they all combine (i) certain kinds of consensus protocols with (ii) Bayesian updates. They are different mainly in the aspect of the type of consensus protocol and the order of the two operations. After discussing their similarities and differences, we compare these distributed algorithms by numerical examples. We focus on the rate at which these algorithms detect the underlying true state of an object. We find that (a) The algorithms with consensus via geometric average is more efficient than that via arithmetic average; (b) The order of consensus aggregation and Bayesian update does not apparently influence the performance of the algorithms; (c) The existence of communication delay dramatically slows do...
Advanced Bayesian Method for Planetary Surface Navigation
Center, Julian
2015-01-01
Autonomous Exploration, Inc., has developed an advanced Bayesian statistical inference method that leverages current computing technology to produce a highly accurate surface navigation system. The method combines dense stereo vision and high-speed optical flow to implement visual odometry (VO) to track faster rover movements. The Bayesian VO technique improves performance by using all image information rather than corner features only. The method determines what can be learned from each image pixel and weighs the information accordingly. This capability improves performance in shadowed areas that yield only low-contrast images. The error characteristics of the visual processing are complementary to those of a low-cost inertial measurement unit (IMU), so the combination of the two capabilities provides highly accurate navigation. The method increases NASA mission productivity by enabling faster rover speed and accuracy. On Earth, the technology will permit operation of robots and autonomous vehicles in areas where the Global Positioning System (GPS) is degraded or unavailable.
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.
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.
Bayesian nonparametric regression with varying residual density
Pati, Debdeep; Dunson, David B.
2013-01-01
We consider the problem of robust Bayesian inference on the mean regression function allowing the residual density to change flexibly with predictors. The proposed class of models is based on a Gaussian process prior for the mean regression function and mixtures of Gaussians for the collection of residual densities indexed by predictors. Initially considering the homoscedastic case, we propose priors for the residual density based on probit stick-breaking (PSB) scale mixtures and symmetrized ...
Informed Source Separation: A Bayesian Tutorial
Knuth, Kevin
2013-01-01
Source separation problems are ubiquitous in the physical sciences; any situation where signals are superimposed calls for source separation to estimate the original signals. In this tutorial I will discuss the Bayesian approach to the source separation problem. This approach has a specific advantage in that it requires the designer to explicitly describe the signal model in addition to any other information or assumptions that go into the problem description. This leads naturally to the idea...
A Bayesian Modelling of Wildfires in Portugal
Silva, Giovani L.; Soares, Paulo; Marques, Susete; Dias, Inês M.; Oliveira, Manuela M.; Borges, Guilherme J.
2015-01-01
In the last decade wildfires became a serious problem in Portugal due to different issues such as climatic characteristics and nature of Portuguese forest. In order to analyse wildfire data, we employ beta regression for modelling the proportion of burned forest area, under a Bayesian perspective. Our main goal is to find out fire risk factors that influence the proportion of area burned and what may make a forest type susceptible or resistant to fire. Then, we analyse wildfire...
Market Segmentation Using Bayesian Model Based Clustering
Van Hattum, P.
2009-01-01
This dissertation deals with two basic problems in marketing, that are market segmentation, which is the grouping of persons who share common aspects, and market targeting, which is focusing your marketing efforts on one or more attractive market segments. For the grouping of persons who share common aspects a Bayesian model based clustering approach is proposed such that it can be applied to data sets that are specifically used for market segmentation. The cluster algorithm can handle very l...
Centralized Bayesian reliability modelling with sensor networks
Czech Academy of Sciences Publication Activity Database
Dedecius, Kamil; Sečkárová, Vladimíra
2013-01-01
Roč. 19, č. 5 (2013), s. 471-482. ISSN 1387-3954 R&D Projects: GA MŠk 7D12004 Grant ostatní: GA MŠk(CZ) SVV-265315 Keywords : Bayesian modelling * Sensor network * Reliability Subject RIV: BD - Theory of Information Impact factor: 0.984, year: 2013 http://library.utia.cas.cz/separaty/2013/AS/dedecius-0392551.pdf
Approximate Bayesian computation in population genetics.
Beaumont, Mark A; Zhang, Wenyang; Balding, David J.
2002-01-01
We propose a new method for approximate Bayesian statistical inference on the basis of summary statistics. The method is suited to complex problems that arise in population genetics, extending ideas developed in this setting by earlier authors. Properties of the posterior distribution of a parameter, such as its mean or density curve, are approximated without explicit likelihood calculations. This is achieved by fitting a local-linear regression of simulated parameter values on simulated summ...
Nonparametric Bayesian Storyline Detection from Microtexts
Krishnan, Vinodh; Eisenstein, Jacob
2016-01-01
News events and social media are composed of evolving storylines, which capture public attention for a limited period of time. Identifying these storylines would enable many high-impact applications, such as tracking public interest and opinion in ongoing crisis events. However, this requires integrating temporal and linguistic information, and prior work takes a largely heuristic approach. We present a novel online non-parametric Bayesian framework for storyline detection, using the distance...
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...
Constrained bayesian inference of project performance models
Sunmola, Funlade
2013-01-01
Project performance models play an important role in the management of project success. When used for monitoring projects, they can offer predictive ability such as indications of possible delivery problems. Approaches for monitoring project performance relies on available project information including restrictions imposed on the project, particularly the constraints of cost, quality, scope and time. We study in this paper a Bayesian inference methodology for project performance modelling in ...
Dual Control for Approximate Bayesian Reinforcement Learning
Klenske, Edgar D.; Hennig, Philipp
2015-01-01
Control of non-episodic, finite-horizon dynamical systems with uncertain dynamics poses a tough and elementary case of the exploration-exploitation trade-off. Bayesian reinforcement learning, reasoning about the effect of actions and future observations, offers a principled solution, but is intractable. We review, then extend an old approximate approach from control theory---where the problem is known as dual control---in the context of modern regression methods, specifically generalized line...