Search results for "Ensembl"

showing 10 items of 165 documents

Isotropic–isotropic phase separation in mixtures of rods and spheres: Some aspects of Monte Carlo simulation in the grand canonical ensemble

2008

Abstract In this article we consider mixtures of non-adsorbing polymers and rod-like colloids in the isotropic phase, which upon the addition of polymers show an effective attraction via depletion forces. Above a certain concentration, the depletant causes phase separation of the mixture. We performed Monte Carlo simulations to estimate the phase boundaries of isotropic–isotropic coexistence. To determine the phase boundaries we simulated in the grand canonical ensemble using successive umbrella sampling [J. Chem. Phys. 120 (2004) 10925]. The location of the critical point was estimated by a finite size scaling analysis. In order to equilibrate the system efficiently, we used a cluster move…

Condensed Matter::Soft Condensed MatterPhysicsCanonical ensembleHybrid Monte CarloGrand canonical ensembleHardware and ArchitectureQuantum Monte CarloMonte Carlo methodDynamic Monte Carlo methodGeneral Physics and AstronomyKinetic Monte CarloStatistical physicsMonte Carlo molecular modelingComputer Physics Communications
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How Do Droplets Depend on the System Size? Droplet Condensation and Nucleation in Small Simulation Cells

2003

Using large scale grandcanonical Monte Carlo simulations in junction with a multicanonical reweighting scheme we investigate the liquid-vapor transition of a Lennard—Jones fluid. Particular attention is focused on the free energy of droplets and the transition between different system configurations as the system tunnels between the vapor and the liquid state as a function of system size. The results highlight the finite size dependence of droplet properties in the canonical ensemble and free energy barriers along the path from the vapor to the liquid in the grandcanonical ensemble.

Condensed Matter::Soft Condensed MatterPhysics::Fluid DynamicsCanonical ensembleLiquid stateMaterials scienceScale (ratio)Monte Carlo methodCondensationNucleationMechanicsSize dependence
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How do droplets on a surface depend on the system size?

2002

Abstract We investigate the thermodynamics of inhomogeneous polymer melts in the framework of a coarse grained off-lattice model. Properties of the liquid–vapour interface and the packing of the melt in contact with an attractive wall are considered. We employ Monte Carlo simulations in the grand canonical ensemble to determine excess free energies, the wetting temperature and the pre-wetting line, as well as the pre-wetting critical point. Having determined the wetting properties and the phase diagram of the model polymer, we perform canonical Monte Carlo simulations of small droplets on a surface. This allows us to study the dependence of droplet size on the wetting properties. It is foun…

Condensed Matter::Soft Condensed MatterPhysics::Fluid DynamicsContact angleSurface tensionGrand canonical ensembleColloid and Surface ChemistryWetting transitionChemistryCritical point (thermodynamics)Monte Carlo methodThermodynamicsWettingPhase diagram
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Contribution to variational analysis : stability of tangent and normal cones and convexity of Chebyshev sets

2014

The aim of this thesis is to study the following three problems: 1) We are concerned with the behavior of normal cones and subdifferentials with respect to two types of convergence of sets and functions: Mosco and Attouch-Wets convergences. Our analysis is devoted to proximal, Fréchet, and Mordukhovich limiting normal cones and subdifferentials. The results obtained can be seen as extensions of Attouch theorem to the context of non-convex functions on locally uniformly convex Banach space. 2) For a given bornology β on a Banach space X we are interested in the validity of the following "lim inf" formula (…).Here Tβ(C; x) and Tc(C; x) denote the β-tangent cone and the Clarke tangent cone to …

Contingent coneCône tangent de BouligandSuite minimisanteFonctions sous-régulières cône normal (tangent) de ClarkeClarke tangent (normal) coneMetric projection[MATH.MATH-GM] Mathematics [math]/General Mathematics [math.GM]Chebyshev setMosco (Attouch-Wets) convergenceAsplund spaceCône normal proximalProjection metriqueEnsemble de ChebyshevConvergence au sens de Mosco (d'Attouch-Wets)Subsmooth sets (functions)BornologyBornologieMinimizing sequenceProximal normal coneFréchet (Mordukhovich limiting) subdifferentialEspace d'AsplundTrustworthinessSous-différentiel de Fréchet (de Mordukhovich)Ensembles sous-réguliers
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State and parameter update in a coupled energy/hydrologic balance model using ensemble Kalman filtering

2012

Summary The capability to accurately monitor and describe daily evapotranspiration (ET) in a cost effective manner is generally attributed to hydrological models. However, continuous solution of energy and water balance provides precise estimations only when a detailed knowledge of sub-surface characteristics is available. On the other hand, residual surface energy balance models, based on remote observation of land surface temperature, are characterised by sufficient accuracy, but their applicability is limited by the lack of high frequency and high resolution thermal data. A compromise between these two methodologies is represented by the use of data assimilation scheme to include sparse …

Continuous modellingSettore ICAR/02 - Costruzioni Idrauliche E Marittime E IdrologiaKalman filterResidualHydrologic balanceOlive treesWater balanceData assimilationEvapotranspirationEnsemble Kalman filterSettore AGR/08 - Idraulica Agraria E Sistemazioni Idraulico-ForestaliEnvironmental scienceEnsemble Kalman filterSVAT modellingSurface energy fluxesSVAT modelling Surface energy fluxes Hydrologic balance Ensemble Kalman filterWater Science and TechnologyRemote sensingJournal of Hydrology
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Inverse Conformational Selection in Lipid–Protein Binding

2021

International audience; Interest in lipid interactions with proteins and other biomolecules is emerging not only in fundamental biochemistry but also in the field of nanobiotechnology where lipids are commonly used, for example, in carriers of mRNA vaccines. The outward-facing components of cellular membranes and lipid nanoparticles, the lipid headgroups, regulate membrane interactions with approaching substances, such as proteins, drugs, RNA, or viruses. Because lipid headgroup conformational ensembles have not been experimentally determined in physiologically relevant conditions, an essential question about their interactions with other biomolecules remains unanswered: Do headgroups excha…

DYNAMICSELECTRIC CHARGEBILAYERSPHOSPHATIDYLCHOLINE HEADGROUPMembrane lipidsDEUTERIUMPlasma protein bindingMolecular Dynamics Simulationlipidit010402 general chemistry01 natural sciencesBiochemistrybiomolekyylitCatalysis03 medical and health sciencesMolecular dynamicskemialliset sidoksetColloid and Surface ChemistryProtein structurePHOSPHOLIPID-BINDINGMAGNETIC-RESONANCE[SDV.BBM] Life Sciences [q-bio]/Biochemistry Molecular BiologySEGMENTAL ORDER[SDV.BBM]Life Sciences [q-bio]/Biochemistry Molecular BiologyConformational ensemblesNuclear Magnetic Resonance Biomolecular030304 developmental biologychemistry.chemical_classification0303 health sciencesChemistryBiomoleculeMEMBRANE-LIPIDSProteinsPhosphatidylglycerolsGeneral Chemistrycomputer.file_formatProtein Data BankLipids0104 chemical sciencesBiophysicsPhospholipid BindingPhosphatidylcholinesMAS NMR1182 Biochemistry cell and molecular biologylipids (amino acids peptides and proteins)proteiinitcomputerProtein Binding
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Prototype-based learning on concept-drifting data streams

2014

Data stream mining has gained growing attentions due to its wide emerging applications such as target marketing, email filtering and network intrusion detection. In this paper, we propose a prototype-based classification model for evolving data streams, called SyncStream, which dynamically models time-changing concepts and makes predictions in a local fashion. Instead of learning a single model on a sliding window or ensemble learning, SyncStream captures evolving concepts by dynamically maintaining a set of prototypes in a new data structure called the P-tree. The prototypes are obtained by error-driven representativeness learning and synchronization-inspired constrained clustering. To ide…

Data streamConcept driftbusiness.industryComputer scienceData stream miningConstrained clusteringcomputer.software_genreData structureMachine learningEnsemble learningSynchronization (computer science)Data miningArtificial intelligencebusinesscomputerProceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining
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Researching ensemble teachers’ assessment criteria and values from a dialogical theoretical perspective

2009

Since the beginning of the 1980s, playing in pop ensembles and rock ensembles has been an integrated part of both Swedish music teacher education and the Swedish national curricula for music. However, there is little research on ensemble playing and teaching in Swedish schools, and even less so on the assessment and the criteria for assessment of this practice. The aim of my PhD project is to investigate what values music teachers in focus groups express and what criteria they base their judgements on when they comment on and discuss video excerpts from ensemble classes. This paper, however, focuses on the method of analysis: a discourse analytical method that is informed by a dialogical th…

Dialogical sociocultural theoryensemble musicassessmentdiscourse
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Diversity in Ensemble Feature Selection

2003

Ensembles of learnt models constitute one of the main current directions in machine learning and data mining. Ensembles allow us to achieve higher accuracy, which is often not achievable with single models. It was shown theoretically and experimentally that in order for an ensemble to be effective, it should consist of high-accuracy base classifiers that should have high diversity in their predictions. One technique, which proved to be effective for constructing an ensemble of accurate and diverse base classifiers, is to use different feature subsets, or so-called ensemble feature selection. Many ensemble feature selection strategies incorporate diversity as a component of the fitness funct…

Dynamic integration of classifiersComputingMethodologies_PATTERNRECOGNITIONEnsemble diversityFeature selectionEnsemble of classifiersSearch strategy
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Free Energy, Enthalpy and Entropy from Implicit Solvent End-Point Simulations

2018

Free energy is the key quantity to describe the thermodynamics of biological systems. In this perspective we consider the calculation of free energy, enthalpy and entropy from end-point molecular dynamics simulations. Since the enthalpy may be calculated as the ensemble average over equilibrated simulation snapshots the difficulties related to free energy calculation are ultimately related to the calculation of the entropy of the system and in particular of the solvent entropy. In the last two decades implicit solvent models have been used to circumvent the problem and to take into account solvent entropy implicitly in the solvation terms. More recently outstanding advancement in both impli…

Energy estimationEnthalpyContinuum solvent Enthalpy Entropy Free energy Implicit solvent MM/GBSA Molecular dynamics simulationscontinuum solvent010402 general chemistry01 natural sciencesBiochemistry Genetics and Molecular Biology (miscellaneous)BiochemistryMolecular dynamicsenthalpy0103 physical sciencesMolecular BiosciencesStatistical physicsPhysics::Chemical PhysicsMolecular Biologylcsh:QH301-705.5PhysicsMM/GBSAQuantitative Biology::BiomoleculesEnd point010304 chemical physicsEnsemble averageSolvationimplicit solventmolecular dynamics simulationsfree energy0104 chemical sciencesSolventlcsh:Biology (General)Solvent modelsPerspectiveentropyFrontiers in Molecular Biosciences
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