Search results for " Probability"

showing 10 items of 2176 documents

Computer Simulations of I-Center Annealing in KCl and KBr Crystals. Theoretical Interpretation of Thermostimulated Experiments

1995

Results of computer simulations of the kinetics of correlated annealing of pairs of close α–I and F–I centers in KCI and KBr crystals, enhanced by I-center diffusion and Coulomb or elastic attractions, respectively, are presented. Special attention is paid to the conditions under which multi-stage annealing stages arise as it has been observed experimentally more than once. Our general conclusions are: (i) a weak elastic interaction affects the recombination kinetics and the survival probability even for relatively well-separated F–I pairs, the more so is true for the case of Coulomb attraction between charged α–I pairs; (ii) the multi-step (kink) structure arises only for close (typically,…

CrystallographySurvival probabilityChemistryAnnealing (metallurgy)Vacancy defectKineticsCoulombElectron trappingCondensed Matter PhysicsMolecular physicsRecombinationElectronic Optical and Magnetic MaterialsIonphysica status solidi (b)
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Heat Kernel Measure on Central Extension of Current Groups in any Dimension

2006

We define measures on central extension of current groups in any dimension by using infinite dimensional Brownian motion.

Current (mathematics)lcsh:MathematicsMathematical analysisProbability (math.PR)central extensionExtension (predicate logic)Group Theory (math.GR)lcsh:QA1-939Measure (mathematics)Dimension (vector space)Mathematics::ProbabilityFOS: MathematicsGeometry and TopologyBrownian motionMathematics - Group TheoryMathematical PhysicsAnalysisHeat kernelBrownian motionMathematics - ProbabilityMathematicscurrent groups
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Anomalous transport effects on switching currents of graphene-based Josephson junctions

2017

We explore the effect of noise on the ballistic graphene-based small Josephson junctions in the framework of the resistively and capacitively shunted model. We use the non-sinusoidal current-phase relation specific for graphene layers partially covered by superconducting electrodes. The noise induced escapes from the metastable states, when the external bias current is ramped, give the switching current distribution, i.e. the probability distribution of the passages to finite voltage from the superconducting state as a function of the bias current, that is the information more promptly available in the experiments. We consider a noise source that is a mixture of two different types of proce…

DYNAMICSJosephson effectJosephson junctionsGaussianFOS: Physical sciencesgraphemeBioengineering01 natural sciencesNoise (electronics)Settore FIS/03 - Fisica Della Materia010305 fluids & plasmaslaw.inventionsymbols.namesakelawJosephson junction0103 physical sciencesMesoscale and Nanoscale Physics (cond-mat.mes-hall)Graphene; Josephson junctions; Levy processes; Non-thermal noise; Bioengineering; Chemistry (all); Materials Science (all); Mechanics of Materials; Mechanical Engineering; Electrical and Electronic EngineeringMechanics of MaterialGeneral Materials ScienceElectrical and Electronic Engineering010306 general physicsPhysicsSuperconductivityLevy processesCondensed matter physicsCondensed Matter - Mesoscale and Nanoscale PhysicsGrapheneMechanical EngineeringSTABLE RANDOM-VARIABLESChemistry (all)Non-thermal noiseBiasingGeneral ChemistryGraphene; Josephson junctions; Levy processes; Non-thermal noise; STABLE RANDOM-VARIABLES; DYNAMICSLevy processeMechanics of MaterialsPhysics - Data Analysis Statistics and ProbabilitysymbolsProbability distributionMaterials Science (all)GrapheneTransport phenomenaData Analysis Statistics and Probability (physics.data-an)
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Global data on earthworm abundance, biomass, diversity and corresponding environmental properties

2021

Earthworms are an important soil taxon as ecosystem engineers, providing a variety of crucial ecosystem functions and services. Little is known about their diversity and distribution at large spatial scales, despite the availability of considerable amounts of local-scale data. Earthworm diversity data, obtained from the primary literature or provided directly by authors, were collated with information on site locations, including coordinates, habitat cover, and soil properties. Datasets were required, at a minimum, to include abundance or biomass of earthworms at a site. Where possible, site-level species lists were included, as well as the abundance and biomass of individual species and ec…

Data DescriptorDistribuição GeográficaPlan_S-Compliant-OASoilBiomassbiodiversityDiversityEcologyBiodiversidadeQBiodiversityeliöyhteisötmaaperäeliöstöPE&RCComputer Science ApplicationsMultidisciplinary SciencesBiogeographyinternational1181 Ecology evolutionary biologyEcosystem engineersScience & Technology - Other TopicsStatistics Probability and UncertaintyInformation SystemsStatistics and ProbabilitylierotScienceInvertebradosLibrary and Information Sciences[SDV.SA.SDS]Life Sciences [q-bio]/Agricultural sciences/Soil studyEcology and EnvironmentEducationeliömaantiede[SDV.EE.ECO]Life Sciences [q-bio]/Ecology environment/EcosystemsMinhocaServiço ambientalBIODIVERSITY CHANGELife ScienceEcosystem servicesEarthwormsDatasetsAnimalsSpatial distributionCommunity ecologyOligochaetaLaboratorium voor NematologieEcosystem1172 Environmental sciencesbiogeographyScience & TechnologyLAND-USEBiology and Life SciencesPLATFORMBodemfysica en LandbeheerEcologíaEcossistemabiodiversiteettiSoil Physics and Land ManagementSoloBiologia do Solomaaperäeläimistö570 Life sciences; biologyeartworm ; abundance ; biomass ; diversityLaboratory of Nematology[SDE.BE]Environmental Sciences/Biodiversity and EcologyCOMMUNITIEScommunity ecology
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Network reconstruction for trans acting genetic loci using multi-omics data and prior information.

2022

Background: Molecular measurements of the genome, the transcriptome, and the epigenome, often termed multi-omics data, provide an in-depth view on biological systems and their integration is crucial for gaining insights in complex regulatory processes. These data can be used to explain disease related genetic variants by linking them to intermediate molecular traits (quantitative trait loci, QTL). Molecular networks regulating cellular processes leave footprints in QTL results as so-called trans-QTL hotspots. Reconstructing these networks is a complex endeavor and use of biological prior information can improve network inference. However, previous efforts were limited in the types of priors…

Data Integrationeducation.field_of_studyComputer scienceScale (chemistry)Bayesian probabilityPopulationQuantitative Trait LociBiological databaseInferenceData Integration ; Machine Learning ; Multi-omics ; Network Inference ; Personalized Medicine ; Prior Information ; Simulation ; Systems BiologyComputational biologyQuantitative trait locusReplication (computing)Machine LearningPrior probabilityCohortGeneticsMolecular MedicineHumans:Medicine [Science]Gene Regulatory NetworkseducationTranscriptomeMolecular BiologyGenetics (clinical)Genome medicine
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Data Augmentation Approach in Bayesian Modelling of Presence-only Data

2011

Abstract Ecologists are interested in prediction of potential distribution of species in suitable areas, essential for planning conservation and management strategies. Unfortunately, often the only available information in such studies is the true presence of the species at few locations of the study area and the associated environmental covariates over the entire area, referred as presence-only data. We propose a Bayesian approach to estimate logistic linear regressions adapted to presence-only data through the introduction of a random approximation of the correction factor in the adjusted logistic model that allows us to overcome the need to know a priori the prevalence of the species.

Data augmentationPresence-only dataComputer scienceBayesian probabilityLogistic regressionBayesian inferencePseudo-absence approachBayesian statisticsBayesian model; Data augmentation; MCMC algorithm; Potential distribution; Presence-only data; Pseudo-absence approachBayesian model Data augmentation MCMC algorithm Presence-only data Pseudo-absence approach Potential distributionpotentialdistributionBayesian modelBayesian multivariate linear regressionPotential distributionStatisticsCovariateEconometricsGeneral Earth and Planetary Sciencespseudo-absence approach; potentialdistribution.; data augmentation; presence-only data; potential distribution; mcmc algorithm; bayesian modelBayesian linear regressionBayesian averageMCMC algorithmGeneral Environmental ScienceProcedia Environmental Sciences
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Differences in Life Expectancy Between Self-Employed Workers and Paid Employees when Retirement Pensioners: Evidence from Spanish Social Security Rec…

2021

The aim of this paper is to examine differences in life expectancy (LE) between self-employed (SE) and paid employee (PE) workers when they become retirement pensioners, looking at levels of pension income using administrative data from Spanish social security records. We draw on the Continuous Sample of Working Lives (CSWL) to quantify changes in total life expectancy at age 65 (LE(65)) among retired men over the longest possible period covered by this data source: 2005–2018. These changes are broken down by pension regime and initial pension income level for three periods. The literature presents mixed evidence, even for the same country–for Japan and Italy, for example–with some studies …

Data sourcePensionSample (statistics)01 natural sciencesArticleSocial security010104 statistics & probability03 medical and health sciences0302 clinical medicineEconomía públicaEconomicsSelf employedLife expectancyIncome levelDemographic economics030212 general & internal medicineEconometría0101 mathematicsSocioeconomic statusDemographyPublic financeEuropean Journal of Population
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Forest of Normalized Trees: Fast and Accurate Density Estimation of Streaming Data

2018

Density estimation of streaming data is a relevant task in numerous domains. In this paper, a novel non-parametric density estimator called FRONT (forest of normalized trees) is introduced. It uses a structure of multiple normalized trees, segments the feature space of the data stream through a periodically updated linear transformation and is able to adapt to ever evolving data streams. FRONT provides accurate density estimation and performs favorably compared to existing online density estimators in terms of the average log score on multiple standard data sets. Its low complexity, linear runtime as well as constant memory usage, makes FRONT by design suitable for large data streams. Final…

Data streamComputer scienceData stream miningFeature vectorEstimator02 engineering and technologyDensity estimation01 natural sciencesData modeling010104 statistics & probabilityKernel (statistics)0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processing0101 mathematicsRandom variableAlgorithm2018 IEEE 5th International Conference on Data Science and Advanced Analytics (DSAA)
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Comparing normal means: new methods for an old problem

2007

Comparing the means of two normal populations is an old problem in mathematical statistics, but there is still no consensus about its most appropriate solution. In this paper we treat the problem of comparing two normal means as a Bayesian decision problem with only two alternatives: either to accept the hypothesis that the two means are equal, or to conclude that the observed data are, under the assumed model, incompatible with that hypothesis. The combined use of an information-theory based loss function, the intrinsic discrepancy (Bernardo and Rueda 2002}, and an objective prior function, the reference prior \citep{Bernardo 1979; Berger and Bernardo 1992), produces a new solution to this…

Database Expansion ItemStatistics and Probabilityreference priorApplied MathematicsCombined useBayesian probabilityMathematical statisticsBayes factorFunction (mathematics)Decision problemBRCBayes factorcomparison of normal meanstwo sided testsApplied mathematicsprecise hypothesis testingAlgorithmintrinsic discrepancyMathematicsBayesian Analysis
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Early stages of the acute physical stress response increase loss aversion and learning on decision making: A Bayesian approach

2021

Abstract When the cortisol peak is reached after a stressor people learn slower and make worse decisions in the Iowa Gambling Task (IGT). However, the effects of the early stress response have not received as much attention. Since physical exercise is an important neuroendocrine stressor, this study aimed to fill this gap using an acute physical stressor. We hypothesized that this stress stage would promote an alertness that may increase feedback-sensitivity and, therefore, reward-learning during IGT, leading to a greater overall decision-making. 90 participants were divided into two groups: 47 were exposed to an acute intense physical stressor (cycloergometer) and 43 to a distractor 5 min …

Decision MakingStressorBayesian probabilityBayes TheoremExperimental and Cognitive PsychologyPhysical exerciseIowa gambling taskDevelopmental psychologyBehavioral NeuroscienceAlertnessRewardLoss aversionGamblingStress (linguistics)HumansLearningCognitive skillPsychologyPhysiology & Behavior
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