Search results for " Statistics and Probability"

showing 10 items of 117 documents

(H,ρ)-induced dynamics and large time behaviors

2018

In some recent papers, the so called (H,ρ)-induced dynamics of a system S whose time evolution is deduced adopting an operatorial approach, borrowed in part from quantum mechanics, has been introduced. Here, H is the Hamiltonian for S, while ρ is a certain rule applied periodically (or not) on S. The analysis carried on throughout this paper shows that, replacing the Heisenberg dynamics with the (H,ρ)-induced one, we obtain a simple, and somehow natural, way to prove that some relevant dynamical variables of S may converge, for large t, to certain asymptotic values. This cannot be so, for finite dimensional systems, if no rule is considered. In this case, in fact, any Heisenberg dynamics im…

(Hρ)-induced dynamicOperatorial modelSchrödinger and Heisenberg dynamicStressed bacterial population(Hρ)-induced dynamics; Operatorial models; Schrödinger and Heisenberg dynamics; Stressed bacterial populations; Statistics and Probability; Condensed Matter PhysicsSettore MAT/07 - Fisica Matematica
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The role of noise on the steady state distributions of phytoplankton populations

2016

The spatio-temporal behaviour of total chlorophyll concentration is investigated in the middle of the Tyrrhenian Sea by using a stochastic approach. The study is based on a reaction-diffusion-taxis model, which is used to analyse the dynamics of five phytoplankton groups, responsible for about 80% of the total chlorophyll a inside the euphotic zone of the water column. The analysis is performed by considering: (i) the intraspecific competition of the phytoplanktonic groups for limiting factors, i.e. light intensity and nutrient concentration, (ii) the seasonal changes of environmental variables, and (iii) the random fluctuations of the components of the velocity field and temperature. Speci…

0106 biological sciencesStatistics and ProbabilityPhysicsSteady state (electronics)010504 meteorology & atmospheric sciences010604 marine biology & hydrobiologyturbulenceHydrodynamic fluctuationstochastic processes (theory)Statistical and Nonlinear Physics01 natural sciencesSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)NoisePhytoplanktonHydrodynamic fluctuations; stochastic particle dynamics (theory); stochastic processes (theory); turbulence; Statistical and Nonlinear Physics; Statistics and Probability; Statistics Probability and Uncertaintystochastic particle dynamics (theory)Statistical physicsStatistics Probability and UncertaintyStatistical and Nonlinear Physic0105 earth and related environmental sciencesJournal of Statistical Mechanics: Theory and Experiment
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Intermittent targeted therapies and stochastic evolution in patients affected by chronic myeloid leukemia

2016

Front line therapy for the treatment of patients affected by chronic myeloid leukemia (CML) is based on the administration of tyrosine kinase inhibitors, namely imatinib or, more recently, axitinib. Although imatinib is highly effective and represents an example of a successful molecular targeted therapy, the appearance of resistance is observed in a proportion of patients, especially those in advanced stages. In this work, we investigate the appearance of resistance in patients affected by CML, by modeling the evolutionary dynamics of cancerous cell populations in a simulated patient treated by an intermittent targeted therapy. We simulate, with the Monte Carlo method, the stochastic evolu…

0301 basic medicineOncologyDrugStatistics and Probabilitymedicine.medical_specialtymedicine.medical_treatmentmedia_common.quotation_subjectTargeted therapy03 medical and health sciencesClassical Monte Carlo simulations; computational biology; models for evolution (theory); mutational and evolutionary processes (theory); Statistical and Nonlinear Physics; Statistics and Probability; Statistics Probability and Uncertainty0302 clinical medicinecomputational biologyInternal medicinemedicineClassical Monte Carlo simulationmutational and evolutionary processes (theory)media_commonbusiness.industryMyeloid leukemiaStatistical and Nonlinear PhysicsImatinibSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)Axitinib030104 developmental biology030220 oncology & carcinogenesisCancer cellToxicityStatistics Probability and Uncertaintybusinessmodels for evolution (theory)Tyrosine kinasemedicine.drugStatistical and Nonlinear Physic
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Newly Digitized Database Reveals the Lives and Families of Forced Migrants from Finnish Karelia

2017

Studies on displaced persons often suffer from a lack of data on the long-term effects of forced migration. A register created during 1960s and published as a book series ‘Siirtokarjalaisten tie’ in 1970 documented the lives of individuals who fled the southern Karelian district of Finland after its first and second occupation by the Soviet Union in 1940 and 1944. To realize the potential value of these data for scientific research, we have recently scanned the register using optical character recognition (OCR) software, and developed proprietary computer code to extract these data. Here we outline the steps involved in the digitization process, and present an overview of the Migration Kare…

0301 basic medicineRegister (sociolinguistics)Historyväestönsiirrotdatabases [http://www.yso.fi/onto/yso/p3056]forced migrationmarriage [http://www.yso.fi/onto/yso/p2790]computer.software_genrelcsh:Social Sciences03 medical and health sciencesbirthsoccupations (professions) [http://www.yso.fi/onto/yso/p1179]avioituvuustietokannatrekisterit112 Statistics and probabilityDigitizationta119syntyvyysdatabaseFinlandmobility [http://www.yso.fi/onto/yso/p252]perheet (ryhmät)Databaseregister informationoccupationsDisplaced persondisplaced personsOptical character recognition113 Computer and information sciencesmarriagesmobilitylcsh:HForced migration030104 developmental biologyliikkuvuuslcsh:HB848-3697digitizationlcsh:Demography. Population. Vital eventsta1181Research findingsSoviet unionKarjalacomputerdigiointiFinnish Yearbook of Population Research
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Assessing statistical significance in multivariable genome wide association analysis

2016

Motivation: Although Genome Wide Association Studies (GWAS) genotype a very large number of single nucleotide polymorphisms (SNPs), the data are often analyzed one SNP at a time. The low predictive power of single SNPs, coupled with the high significance threshold needed to correct for multiple testing, greatly decreases the power of GWAS. Results: We propose a procedure in which all the SNPs are analyzed in a multiple generalized linear model, and we show its use for extremely high-dimensional datasets. Our method yields P-values for assessing significance of single SNPs or groups of SNPs while controlling for all other SNPs and the family wise error rate (FWER). Thus, our method tests whe…

0301 basic medicineStatistics and Probability1303 BiochemistryGenotypeOperations researchLibrary sciencePolymorphism Single NucleotideBiochemistryGerman03 medical and health sciences10007 Department of EconomicsPolitical scienceGenome-Wide Association Analysis1312 Molecular Biology1706 Computer Science ApplicationsCluster AnalysisHumansComputer Simulation2613 Statistics and ProbabilityMolecular BiologyEuropean researchGenetics and Population AnalysisComputational BiologyReproducibility of ResultsOriginal Paperslanguage.human_languageComputer Science Applications330 EconomicsComputational MathematicsPhenotype030104 developmental biologyComputational Theory and MathematicsLinear Modelslanguage2605 Computational MathematicsGenome-Wide Association Study1703 Computational Theory and Mathematics
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Gene-based and semantic structure of the Gene Ontology as a complex network

2012

The last decade has seen the advent and consolidation of ontology based tools for the identification and biological interpretation of classes of genes, such as the Gene Ontology. The information accumulated time-by-time and included in the GO is encoded in the definition of terms and in the setting up of semantic relations amongst terms. This approach might be usefully complemented by a bottom-up approach based on the knowledge of relationships amongst genes. To this end, we investigate the Gene Ontology from a complex network perspective. We consider the semantic network of terms naturally associated with the semantic relationships provided by the Gene Ontology consortium and a gene-based …

0301 basic medicineStatistics and ProbabilityFOS: Computer and information sciencesPhysics - Physics and SocietyComplex systemComputer scienceMolecular Networks (q-bio.MN)Complex systemFOS: Physical sciencesNetworkCondensed Matter PhysicPhysics and Society (physics.soc-ph)computer.software_genreQuantitative Biology - Quantitative MethodsStatistics - ApplicationsGeneSemantic network03 medical and health sciencesSemantic similarityQuantitative Biology - Molecular NetworksApplications (stat.AP)GeneQuantitative Methods (q-bio.QM)Community detectionGene ontologybusiness.industryOntologyOntology-based data integrationComplex networkCondensed Matter PhysicsBipartite system030104 developmental biologyBipartite system; Community detection; Complex systems; Genes; Networks; Ontology; Condensed Matter Physics; Statistics and ProbabilityFOS: Biological sciencesOntologyWeighted networkData miningArtificial intelligenceComputingMethodologies_GENERALbusinesscomputerNatural language processing
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"Table 7" of "Measurement of the differential cross-section of highly boosted top quarks as a function of their transverse momentum in $\sqrt{s}$ = 8…

2016

Correlation matrix between the bins of the particle-level differential cross-section as a function of $p_{T,ptcl}$.

8000.0educationfood and beveragesTopAstrophysics::Cosmology and Extragalactic AstrophysicsPhysics::Data Analysis; Statistics and ProbabilityP P --> TOP TOPBAR Xbody regionsInclusiveSingle Differential Cross SectionProton-Proton Scatteringnatural sciencesDSIG/DPTTransverse Momentum Dependence
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Particle identification in ALICE: a Bayesian approach

2016

We present a Bayesian approach to particle identification (PID) within the ALICE experiment. The aim is to more effectively combine the particle identification capabilities of its various detectors. After a brief explanation of the adopted methodology and formalism, the performance of the Bayesian PID approach for charged pions, kaons and protons in the central barrel of ALICE is studied. PID is performed via measurements of specific energy loss ($\mathrm{d}E/\mathrm{d}x$) and time-of-flight. PID efficiencies and misidentification probabilities are extracted and compared with Monte Carlo simulations using high-purity samples of identified particles in the decay channels ${\rm K}^0_S \righta…

:Kjerne- og elementærpartikkelfysikk: 431 [VDP]Monte Carlo methodGeneral Physics and AstronomyPID controllerPP01 natural sciencesParticle identificationHigh Energy Physics - ExperimentParticle identificationHigh Energy Physics - Experiment (hep-ex)ALICEHadron-Hadron scattering (experiments)Heavy-ion collisionNuclear and High Energy Physics Hadron-Hadron scattering (experiments) Heavy Ion Experiments Heavy-ion collision Quark gluon plasma Particle identification Bayesianscattering [p p][PHYS.HEXP]Physics [physics]/High Energy Physics - Experiment [hep-ex]Nuclear Experiment (nucl-ex)Detectors and Experimental TechniquesNuclear ExperimentNuclear ExperimentPhysicsefficiency [particle identification]PB COLLISIONSVDP::Kjerne- og elementærpartikkelfysikk: 431Monte Carlo [numerical calculations]PB COLLISIONS PP PERFORMANCE.:Mathematics and natural scienses: 400::Physics: 430::Nuclear and elementary particle physics: 431 [VDP]PRIRODNE ZNANOSTI. Fizika.Time of flight:Nuclear and elementary particle physics: 431 [VDP]VDP::Nuclear and elementary particle physics: 431performancemomentum spectrum [charged particle]Nuclear and High Energy PhysicsParticle physicsMesoneducationBayesian probabilityFOS: Physical sciencesQuark gluon plasma[PHYS.NEXP]Physics [physics]/Nuclear Experiment [nucl-ex]114 Physical sciencesBayesianNuclear physicsPhysics and Astronomy (all)PionHeavy Ion Experiments0103 physical sciencesddc:530010306 general physics010308 nuclear & particles physicsBayesian approach:Matematikk og naturvitenskap: 400::Fysikk: 430::Kjerne- og elementærpartikkelfysikk: 431 [VDP]ALICE experimentPERFORMANCEparticle identification ; Bayesian approachNATURAL SCIENCES. Physics.PB COLLISIONS; TEV; PP; PERFORMANCEPhysics - Data Analysis Statistics and ProbabilityQuark–gluon plasmaBayesian [statistics]TEVHigh Energy Physics::Experimentparticle identificationData Analysis Statistics and Probability (physics.data-an)
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Ultra-fast detection of the center frequency of a spectral line from amplitude-weighted average

2023

Spectroscopy methods often require calculating the central frequency of a resonance line, that is usually implemented by finding a best fit to the spectrum by a line-shape function. Such an iterative procedure is slow and requires an initial guess. We report an analytical method for calculating the central frequency of a spectral line by using the mean value of its frequencies, which are weighted by corresponding normalized intensities. We use this method to calculate two-dimensional arrays of central frequencies from parallely measured magnetic resonance spectra, which are optically detected by a camera sensor in a thin layer of NV centers with superparamagnetic hemozoin crystals on top of…

Atomic Physics (physics.atom-ph)Physics - Data Analysis Statistics and ProbabilityFOS: Physical sciencesPhysics - Applied PhysicsApplied Physics (physics.app-ph)Data Analysis Statistics and Probability (physics.data-an)Physics - Atomic Physics
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Measurements of baryon pair decays of chi(cJ) mesons

2013

Using 106 $\times 10^{6}$ $\psi^{\prime}$ decays collected with the BESIII detector at the BEPCII, three decays of $\chi_{cJ}$ ($J=0,1,2$) with baryon pairs ($\llb$, $\ssb$, $\SSB$) in the final state have been studied. The branching fractions are measured to be $\cal{B}$$(\chi_{c0,1,2}\rightarrow\Lambda\bar\Lambda) =(33.3 \pm 2.0 \pm 2.6)\times 10^{-5}$, $(12.2 \pm 1.1 \pm 1.1)\times 10^{-5}$, $(20.8 \pm 1.6 \pm 2.3)\times 10^{-5}$; $\cal{B}$$(\chi_{c0,1,2}\rightarrow\Sigma^{0}\bar\Sigma^{0})$ = $(47.8 \pm 3.4 \pm 3.9)\times 10^{-5}$, $(3.8 \pm 1.0 \pm 0.5)\times 10^{-5}$, $(4.0 \pm 1.1 \pm 0.5) \times 10^{-5}$; and $\cal{B}$$(\chi_{c0,1,2}\rightarrow\Sigma^{+}\bar\Sigma^{-})$ = $(45.4 \pm…

BaryonPhysicsNuclear and High Energy PhysicsParticle physicsMesonBranching fractionPhysics - Data Analysis Statistics and ProbabilityAnalytical chemistrySigmaLambdaHigh Energy Physics - ExperimentPhysical Review D
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