Search results for "Centrality"

showing 10 items of 164 documents

Transverse momentum spectra and nuclear modification factors of charged particles in pp, p-Pb and Pb-Pb collisions at the LHC

2018

We report the measured transverse momentum ($p_{\rm T}$) spectra of primary charged particles from pp, p-Pb and Pb-Pb collisions at a center-of-mass energy $\sqrt{s_{\rm NN}} = 5.02$ TeV in the kinematic range of $0.15<p_{\rm T}<50$ GeV/$c$ and $|\eta|< 0.8$. A significant improvement of systematic uncertainties motivated the reanalysis of data in pp and Pb-Pb collisions at $\sqrt{s_{\rm NN}} = 2.76$ TeV, as well as in p-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV, which is also presented. Spectra from Pb-Pb collisions are presented in nine centrality intervals and are compared to a reference spectrum from pp collisions scaled by the number of binary nucleon-nucleon collisions. For cent…

:Kjerne- og elementærpartikkelfysikk: 431 [VDP]heavy ion: scatteringHadronmomentum [up]binaryMULTIPLICITY DEPENDENCEPartonheavy ion: scattering ; transverse momentum: momentum spectrum ; quantum chromodynamics: matter ; parton: energy loss ; momentum: high ; up: momentum ; pp: scattering ; nucleus ; charged particle ; suppression ; energy dependence ; impact parameter ; transport theory ; nucleon nucleon ; CERN LHC Coll ; kinematics ; binarymomentum spectrum [transverse momentum]hiukkasfysiikkaKAONnucl-ex01 natural sciences7. Clean energy2760 GeV-cms/nucleonHigh Energy Physics - Experimenttransverse momentum: momentum spectrumHeavy Ion Experiments; Heavy-ion collision; Nuclear and high energy physicsHigh Energy Physics - Experiment (hep-ex)quark gluon plasma Heavy Ion Experiments Heavy-ion collisionnucleon nucleonHeavy-ion collisionhigh [momentum]PIONscattering [p p]transport theory[PHYS.HEXP]Physics [physics]/High Energy Physics - Experiment [hep-ex][ PHYS.NEXP ] Physics [physics]/Nuclear Experiment [nucl-ex]Nuclear Experiment (nucl-ex)impact parameterNuclear ExperimentNuclear ExperimentQCD matterparticle production and suppressionPhysicsPhysicsHADRONSheavy ion experiments heavy ion collision particle production and suppressionHeavy Ion Experiments; Heavy-ion collisionVDP::Kjerne- og elementærpartikkelfysikk: 431suppressionCENTRALITY DEPENDENCEcharged particleCharged particleMULTIPLICITY DEPENDENCE; CENTRALITY DEPENDENCE; HADRONS; SUPPRESSION; MODEL; KAON; PIONquark gluon plasma:Mathematics and natural scienses: 400::Physics: 430::Nuclear and elementary particle physics: 431 [VDP]:Nuclear and elementary particle physics: 431 [VDP]CERN LHC CollVDP::Nuclear and elementary particle physics: 431kinematicsHeavy Ion ExperimentImpact parameterParticle Physics - ExperimentHeavy Ion Experiments Heavy-ion collision Nuclear and High Energy Physics.Nuclear and High Energy Physicsp p: scatteringnucleon nucleon: scatteringenergy loss [parton]FOS: Physical sciences[PHYS.NEXP]Physics [physics]/Nuclear Experiment [nucl-ex]114 Physical sciencesenergy dependenceNuclear physicsPionHeavy Ion Experiments[ PHYS.HEXP ] Physics [physics]/High Energy Physics - Experiment [hep-ex]scattering [heavy ion]0103 physical sciencesmatter [quantum chromodynamics]lcsh:Nuclear and particle physics. Atomic energy. Radioactivityddc:530Nuclear Physics - Experiment5020 GeV-cms/nucleonup: momentum010306 general physicsp nucleus: scatteringquantum chromodynamics: matterta114010308 nuclear & particles physicshep-exnucleus:Matematikk og naturvitenskap: 400::Fysikk: 430::Kjerne- og elementærpartikkelfysikk: 431 [VDP]Nuclear and high energy physicsheavy ion collisionMODEL* Automatic Keywords *13. Climate actionmomentum: highQuark–gluon plasmalcsh:QC770-798High Energy Physics::Experimentparton: energy lossEnergy (signal processing)experimental results
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Transient seizure onset network for localization of epileptogenic zone: effective connectivity and graph theory-based analyses of ECoG data in tempor…

2018

Objective: Abnormal and dynamic epileptogenic networks cause difficulties for clinical epileptologists in the localization of the seizure onset zone (SOZ) and the epileptogenic zone (EZ) in preoperative assessments of patients with refractory epilepsy. The aim of this study is to investigate the characteristics of time-varying effective connectivity networks in various non-seizure and seizure periods, and to propose a quantitative approach for accurate localization of SOZ and EZ. Methods: We used electrocorticogram recordings in the temporal lobe and hippocampus from seven patients with temporal lobe epilepsy to characterize the effective connectivity dynamics at a high temporal resolution …

AdultMaleDrug Resistant EpilepsyHippocampusTemporal lobeYoung Adult03 medical and health sciencesEpilepsyadaptive directed transfer function0302 clinical medicineBetweenness centralitySeizuresNeural PathwaysPreoperative CaremedicineHumansaivotutkimus030212 general & internal medicineMathematicsClustering coefficientBrain Mappinggraph metricverkkoteoriabrain connectivitySignal Processing Computer-AssistedGraph theoryMiddle AgedEpileptogenic zonemedicine.diseaseTemporal LobeEpilepsy Temporal LobeNeurologyseizure onset zoneGraph (abstract data type)FemaleElectrocorticographyNeurology (clinical)Centralityepileptogenic zoneepilepsiaNeuroscience030217 neurology & neurosurgeryJournal of Neurology
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Further Neuroimaging Evidence for the Deficit Subtype of Schizophrenia

2015

The clinical heterogeneity of schizophrenia has hindered neurobiological investigations aimed at identifying neural correlates of the disorder.To identify network-based biomarkers across the spectrum of impairment present in schizophrenia by separately evaluating individuals with deficit and nondeficit subtypes of this disorder.A university hospital network-based neuroimaging study was conducted between February 1, 2007, and February 28, 2012. Participants included patients with schizophrenia (n = 128) and matched healthy controls (n = 130) from two academic centers and patients with bipolar I disorder (n = 39) and matched healthy controls (n = 43) from a third site. Patients with schizophr…

AdultMalemedicine.medical_specialtyBipolar DisorderBipolar I disorderNeuroimagingAudiologyBetweenness centralityNeuroimagingNeural PathwaysConnectomemedicineHumansPsychiatryCerebral CortexEvidence-Based MedicineMiddle Agedmedicine.diseaseTemporal LobeFrontal LobePsychiatry and Mental healthQuartileFrontal lobeSchizophreniaCase-Control StudiesSchizophreniaConnectomeFemaleCentralityPsychologyJAMA Psychiatry
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Analyzing the Correlation of Classical and Community-aware Centrality Measures in Complex Networks

2021

International audience; Identifying influential nodes in social networks is a fundamental issue. Indeed, it has many applications, such as inhibiting epidemic spreading, accelerating information diffusion, preventing terrorist attacks, and much more. Classically, centrality measures quantify the node's importance based on various topological properties of the network, such as Degree and Betweenness. Nonetheless, these measures are agnostic of the community structure, although it is a ubiquitous characteristic encountered in many real-world networks. To overcome this drawback, there is a growing trend to design so-called community-aware centrality measures. Although several works investigate…

AssortativityTransitivityEfficiency) and nine mesoscopic topological features (MixingAverage Distance[INFO.INFO-SI] Computer Science [cs]/Social and Information Networks [cs.SI]Density[INFO.INFO-LG] Computer Science [cs]/Machine Learning [cs.LG][INFO] Computer Science [cs][INFO.INFO-SI]Computer Science [cs]/Social and Information Networks [cs.SI]Diameter[INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG]Influential NodesCentrality Measures[INFO]Computer Science [cs]Community StructureComputingMilieux_MISCELLANEOUS
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Choosing Optimal Seed Nodes in Competitive Contagion.

2019

International audience; In recent years there has been a growing interest in simulating competitive markets to find out the efficient ways to advertise a product or spread an ideology. Along this line, we consider a binary competitive contagion process where two infections, A and B, interact with each other and diffuse simultaneously in a network. We investigate which is the best centrality measure to find out the seed nodes a company should adopt in the presence of rivals so that it can maximize its influence. These nodes can be used as the initial spreaders or advertisers by firms when two firms compete with each other. Each node is assigned a price tag to become an initial advertiser whi…

Big Datagame theoryComputer scienceProcess (engineering)01 natural sciencescompetitive contagionMicroeconomics010104 statistics & probabilityArtificial IntelligenceNode (computer science)Computer Science (miscellaneous)seed nodes0101 mathematicsOriginal ResearchSmall numbercentrality measures010102 general mathematicsStochastic game[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]complex networksComplex networkProduct (business)CentralityGame theorycompetitive marketingInformation SystemsFrontiers in big data
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Evolution of Cooperation Patterns in Psoriasis Research: Co-Authorship Network Analysis of Papers in Medline (1942–2013)

2015

BackgroundAlthough researchers have worked in collaboration since the origins of modern science and the publication of the first scientific journals in the eighteenth century, this phenomenon has acquired exceptional importance in the last several decades. Since the mid-twentieth century, new knowledge has been generated from within an ever-growing network of investigators, working cooperatively in research groups across countries and institutions. Cooperation is a crucial determinant of academic success.ObjectiveThe aim of the present paper is to analyze the evolution of scientific collaboration at the micro level, with regard to the scientific production generated on psoriasis research.Me…

Biomedical ResearchMEDLINEScienceClosenessInformation DisseminationMEDLINEBiologyBibliometricsBioinformaticsGiant componentSocial NetworkingBetweenness centralityRegional scienceHumansPsoriasisCooperative BehaviorClustering coefficientMultidisciplinarySocial networkInformation Disseminationbusiness.industryQRAuthorshipResearch PersonnelBibliometricsWorkforceMedicinePeriodicals as TopicbusinessResearch ArticlePLOS ONE
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Investigating Centrality Measures in Social Networks with Community Structure

2021

Centrality measures are crucial in quantifying the influence of the members of a social network. Although there has been a great deal of work dealing with this issue, the vast majority of classical centrality measures are agnostic of the community structure characterizing many social networks. Recent works have developed community-aware centrality measures that exploit features of the community structure information encountered in most real-world complex networks. In this paper, we investigate the interactions between 5 popular classical centrality measures and 5 community-aware centrality measures using 8 real-world online networks. Correlation as well as similarity measures between both t…

Bridging (networking)Social networkExploitbusiness.industryComputer scienceNode (networking)Community structure02 engineering and technologyComplex networkData science[INFO.INFO-SI]Computer Science [cs]/Social and Information Networks [cs.SI][INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG]020204 information systemsSimilarity (psychology)0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingbusinessCentralityComputingMilieux_MISCELLANEOUS
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"Table 20" of "K*(892)^0 and PHI(1020) production in Pb-Pb collisions at sqrt(sNN) = 2.76 TeV"

2015

Yield (dN/dy) of (K*(892)0 + anti-K*(892)0)/2 for different centrality intervals in Pb-Pb collisions at sqrt(sNN)=2.76 TeV. In the table, the first systematic uncertainty is uncorrelated between centrality intervals, the second is the normalization uncertainty.

CENTRALITYInclusiveDN/DYRAPStrange production2760.0PB PB --&gt; AK*(892)0 XRapidity DependencePB PB --&gt; K*(892)0 XDN/DCENTRALITYSingle Differential Distribution
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"Table 21" of "K*(892)^0 and PHI(1020) production in Pb-Pb collisions at sqrt(sNN) = 2.76 TeV"

2015

Yield (dN/dy) of phi(1020) mesons for different centrality intervals in Pb-Pb collisions at sqrt(sNN)=2.76 TeV. In the table, the first systematic uncertainty is uncorrelated between centrality intervals and the second is the normalization uncertainty.

CENTRALITYInclusiveDN/DYRAPStrange production2760.0Rapidity DependenceDN/DCENTRALITYSingle Differential DistributionPB PB --&gt; PHI XNuclear Experiment
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"Table 1" of "Measurement of the distributions of event-by-event flow harmonics in lead--lead collisions at sqrt(s_NN)=2.76 TeV with the ATLAS detect…

2014

The relationship between centrality intervals and MEAN(Npart) estimated from the Glauber model.

CENTRALITYPB PB --&gt; X2760.0Exclusive
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