81,984 research outputs found

    First-principles thermodynamic modeling of atomic ordering in yttria-stabilized zirconia

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    Yttria-stabilized zirconia YSZ is modeled using a cluster expansion statistical thermodynamics method built upon a density-functional theory database. The reliability of cluster expansions in predicting atomic ordering is explored by comparing with the extensive experimental database. The cluster expansion of YSZ is utilized in lattice Monte Carlo simulations to compute the ordering of dopant and oxygen vacancies as a function of concentration. Cation dopants show a strong tendency to aggregate and vacate significantly sized domains below 9 mol % Y_2O_3, which is likely important for YSZ aging processes in ionic conductivity. Evolution of vibrational and underlying electronic properties as a function of Y doping is explored

    Protein docking refinement by convex underestimation in the low-dimensional subspace of encounter complexes

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    We propose a novel stochastic global optimization algorithm with applications to the refinement stage of protein docking prediction methods. Our approach can process conformations sampled from multiple clusters, each roughly corresponding to a different binding energy funnel. These clusters are obtained using a density-based clustering method. In each cluster, we identify a smooth “permissive” subspace which avoids high-energy barriers and then underestimate the binding energy function using general convex polynomials in this subspace. We use the underestimator to bias sampling towards its global minimum. Sampling and subspace underestimation are repeated several times and the conformations sampled at the last iteration form a refined ensemble. We report computational results on a comprehensive benchmark of 224 protein complexes, establishing that our refined ensemble significantly improves the quality of the conformations of the original set given to the algorithm. We also devise a method to enhance the ensemble from which near-native models are selected.Published versio

    Kinetic distance and kinetic maps from molecular dynamics simulation

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    Characterizing macromolecular kinetics from molecular dynamics (MD) simulations requires a distance metric that can distinguish slowly-interconverting states. Here we build upon diffusion map theory and define a kinetic distance for irreducible Markov processes that quantifies how slowly molecular conformations interconvert. The kinetic distance can be computed given a model that approximates the eigenvalues and eigenvectors (reaction coordinates) of the MD Markov operator. Here we employ the time-lagged independent component analysis (TICA). The TICA components can be scaled to provide a kinetic map in which the Euclidean distance corresponds to the kinetic distance. As a result, the question of how many TICA dimensions should be kept in a dimensionality reduction approach becomes obsolete, and one parameter less needs to be specified in the kinetic model construction. We demonstrate the approach using TICA and Markov state model (MSM) analyses for illustrative models, protein conformation dynamics in bovine pancreatic trypsin inhibitor and protein-inhibitor association in trypsin and benzamidine

    A comparative study of the AHP and TOPSIS methods for implementing load shedding scheme in a pulp mill system

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    The advancement of technology had encouraged mankind to design and create useful equipment and devices. These equipment enable users to fully utilize them in various applications. Pulp mill is one of the heavy industries that consumes large amount of electricity in its production. Due to this, any malfunction of the equipment might cause mass losses to the company. In particular, the breakdown of the generator would cause other generators to be overloaded. In the meantime, the subsequence loads will be shed until the generators are sufficient to provide the power to other loads. Once the fault had been fixed, the load shedding scheme can be deactivated. Thus, load shedding scheme is the best way in handling such condition. Selected load will be shed under this scheme in order to protect the generators from being damaged. Multi Criteria Decision Making (MCDM) can be applied in determination of the load shedding scheme in the electric power system. In this thesis two methods which are Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) were introduced and applied. From this thesis, a series of analyses are conducted and the results are determined. Among these two methods which are AHP and TOPSIS, the results shown that TOPSIS is the best Multi criteria Decision Making (MCDM) for load shedding scheme in the pulp mill system. TOPSIS is the most effective solution because of the highest percentage effectiveness of load shedding between these two methods. The results of the AHP and TOPSIS analysis to the pulp mill system are very promising

    Model Selection in Overlapping Stochastic Block Models

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    Networks are a commonly used mathematical model to describe the rich set of interactions between objects of interest. Many clustering methods have been developed in order to partition such structures, among which several rely on underlying probabilistic models, typically mixture models. The relevant hidden structure may however show overlapping groups in several applications. The Overlapping Stochastic Block Model (2011) has been developed to take this phenomenon into account. Nevertheless, the problem of the choice of the number of classes in the inference step is still open. To tackle this issue, we consider the proposed model in a Bayesian framework and develop a new criterion based on a non asymptotic approximation of the marginal log-likelihood. We describe how the criterion can be computed through a variational Bayes EM algorithm, and demonstrate its efficiency by running it on both simulated and real data.Comment: articl

    Open Clusters IC 4665 and Cr 359 and a Probable Birthplace of the Pulsar PSR B1929+10

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    Based on the epicyclic approximation, we have simulated the motion of the young open star clusters IC 4665 and Collinder 359. The separation between the cluster centers is shown to have been minimal 7 Myr ago, 36 pc. We have established a close evolutionary connection between IC 4665 and the Scorpius-Centaurus association -- the separation between the centers of these structures was ≈200\approx200 pc 15 Myr ago. In addition, the center of IC 4665 at this time was near two well-known regions of coronal gas: the Local Bubble and the North Polar Spur. The star HIP 86768 is shown to be one of the candidates for a binary (in the past) with the pulsar PSR B1929+10. At the model radial velocity of the pulsar Vr=2±50V_r= 2\pm50 km s−1^{-1}, a close encounter of this pair occurs in the vicinity of IC 4665 at a time of -1.1 Myr. At the same time, using currently available data for the pulsar B1929+10 at its model radial velocity Vr=200±50V_r=200\pm50 km s−1^{-1}, we show that the hypothesis of Hoogerwerf et al. (2001) about the breakup of the ζ\zetaOph--B1929+10 binary in the vicinity of Upper Scorpius (US) about 0.9 Myr ago is more plausible.Comment: 19 pages, 8 figure

    Effects of the complex mass distribution of dark matter halos on weak lensing cluster surveys

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    Gravitational lensing effects arise from the light ray deflection by all of the mass distribution along the line of sight. It is then expected that weak lensing cluster surveys can provide us true mass-selected cluster samples. With numerical simulations, we analyze the correspondence between peaks in the lensing convergence Îș\kappa-map and dark matter halos. Particularly we emphasize the difference between the peak Îș\kappa value expected from a dark matter halo modeled as an isolated and spherical one, which exhibits a one-to-one correspondence with the halo mass at a given redshift, and that of the associated Îș\kappa-peak from simulations. For halos with the same expected Îș\kappa, their corresponding peak signals in the Îș\kappa-map present a wide dispersion. At an angular smoothing scale of ΞG=1arcmin\theta_G=1\hbox{arcmin}, our study shows that for relatively large clusters, the complex mass distribution of individual clusters is the main reason for the dispersion. The projection effect of uncorrelated structures does not play significant roles. The triaxiality of dark matter halos accounts for a large part of the dispersion, especially for the tail at high Îș\kappa side. Thus lensing-selected clusters are not really mass-selected. (abridged)Comment: ApJ accepte
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