Search results for "Data analysis"

showing 10 items of 383 documents

Reinterpretation of Classic Proton Charge Form Factor Measurements

2020

In 1963, a proton radius of $0.805(11)~\mathrm{fm}$ was extracted from electron scattering data and this classic value has been used in the standard dipole parameterization of the form factor. In trying to reproduce this classic result, we discovered that there was a sign error in the original analysis and that the authors should have found a value of $0.851(19)~\mathrm{fm}$. We additionally made use of modern computing power to find a robust function for extracting the radius using this 1963 data's spacing and uncertainty. This optimal function, the Pad\'{e} $(0,1)$ approximant, also gives a result which is consistent with the modern high precision proton radius extractions.

ProtonMaterials Science (miscellaneous)BiophysicsFOS: Physical sciencesGeneral Physics and Astronomy01 natural sciences0103 physical sciencesPadé approximantNuclear Experiment (nucl-ex)Physical and Theoretical Chemistry010306 general physicsform factorsNuclear ExperimentMathematical PhysicsPhysicsForm factor (quantum field theory)Function (mathematics)Radiuslcsh:QC1-999Computational physicsDipolecharge radiuselectron scatteringPhysics - Data Analysis Statistics and Probabilitystatistical methodsElectron scatteringlcsh:PhysicsData Analysis Statistics and Probability (physics.data-an)protonSign (mathematics)Frontiers in Physics
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Measurement of proton electromagnetic form factors in the time-like region using initial state radiation at BESIII

2021

Physics letters / B 817, 136328 (2021). doi:10.1016/j.physletb.2021.136328

Protonannihilation [electron positron]01 natural sciencesform factor [electron]High Energy Physics - ExperimentSubatomär fysikHigh Energy Physics - Experiment (hep-ex)BESIII; Electromagnetic form factors; Initial state radiation; ProtonSubatomic Physicsangular distributionNuclear ExperimentPhysicsPhysicsForm factor (quantum field theory)initial-state interaction [radiation]Beijing Stormagnetic [form factor]ratio [form factor]electron positron --> p anti-pcolliding beams [electron positron]ProtonInitial State Radiationpair production [p]electromagnetic [form factor]Born approximationNuclear and High Energy Physicsdata analysis methodQC1-999FOS: Physical sciencesRadiation5303.773-4.600 GeV-cmsNONuclear physicsCross section (physics)Angular distributionElectromagnetic form factors0103 physical sciencesform factor [p]tree approximationddc:530010306 general physicsinitial stateBES010308 nuclear & particles physicshelicity [p]BESIIIState (functional analysis)(p anti-p) [mass spectrum]Electromagnetic form FactorsHigh Energy Physics::Experimentproduction [threshold]Initial state radiationexperimental results
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Quantitative and qualitative analysis of the mental models deployed by undergraduate students in explaining thermally activated phenomena

2017

In this contribution we describe a research aimed at pointing out the quality of mental models undergraduate engineering students deploy when asked to create explanations for phenomena/processes and/or use a given model in the same context. Student responses to a specially designed written questionnaire are initially analyzed using researcher-generated categories of reasoning, based on the Physics Education Research literature on student understanding of the relevant physics content. The inferred students’ mental models about the analyzed phenomena are categorized as practical, descriptive, or explanatory, based on an analysis of student responses to the questionnaire. A qualitative analysi…

Pulmonary and Respiratory MedicineResearch literatureQuantitative analysimedia_common.quotation_subjectSettore FIS/08 - Didattica E Storia Della Fisica05 social sciencesPhysics education050301 educationContext (language use)qualitative analysimental modelsQualitative analysisQuantitative analysis (finance)Pediatrics Perinatology and Child HealthMathematics educationComputingMilieux_COMPUTERSANDEDUCATIONQuality (business)Undergraduate engineeringmental models quantitative data analysisPsychologylcsh:L0503 educationmedia_commonlcsh:Education
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Retrospective screening for SARS-CoV-2 among influenza-like illness hospitalizations: 2018-2019 and 2019-2020 seasons, Valencia region, Spain

2021

Este artículo se encuentra disponible en la siguiente URL: https://onlinelibrary.wiley.com/doi/epdf/10.1111/irv.12899 En este artículo de investigación también participan: Juan Mollar-Maseres, Germán Schwarz-Chavarri, Sandra García-Esteban, Joan Puig-Barberà, Javier Díez-Domingo y F. Xavier López-Labrador. On 9 March 2020, the World Health Organization (WHO) Global Influenza Programme (GIP) asked participant sites on the Global Influenza Hospital Surveillance Network (GIHSN) to contribute to data collection concerning severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We re-analysed 5833 viral RNA archived samples collected prospectively from hospital admissions for influenza-lik…

Pulmonary and Respiratory Medicinemedicine.medical_specialty2019-20 coronavirus outbreakRT‐PCRSARS-CoV-2 (Virus) - Diagnóstico - 2018-2019 - España - Valencia (Comunidad Valenciana)EpidemiologyShort CommunicationSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)PopulationShort CommunicationscoronavirusData analysis.COVID-19 - Diagnóstico - 2019-2020 - España - Valencia (Comunidad Autónoma)medicine.disease_causeWorld healthCOVID‐19Influenza HumanPandemicmedicineHumansCOVID-19 - Diagnóstico - 2018-2019 - España - Valencia (Comunidad Autónoma)Influenza - Diagnosis - 2019-2020 - Spain - Valencia (Autonomous Community)Viral rnaGripe - Diagnóstico - 2018-2019 - España - Valencia (Comunidad Autónoma)influenza‐like‐illnesseducationRetrospective StudiesCoronaviruseducation.field_of_studyInfluenza-like illnessSARS-CoV-2business.industrySARS-CoV-2 (Virus) - Diagnosis - 2018-2019 - Spain - Valencia (Autonomous Community)COVID-19 (Disease) - Diagnosis - 2019-2020 - Spain - Valencia (Autonomous Community)Public Health Environmental and Occupational HealthCOVID-19virus diseasesCOVID-19 (Disease) - Diagnosis - 2018-2019 - Spain - Valencia (Autonomous Community)Análisis de datos.HospitalizationSARS-CoV-2 (Virus) - Diagnóstico - 2019-2020 - España - Valencia (Comunidad Valenciana)Infectious DiseasesInfluenza - Diagnosis - 2018-2019 - Spain - Valencia (Autonomous Community)SpainGripe - Diagnóstico - 2019-2020 - España - Valencia (Comunidad Autónoma)Emergency medicineSARS-CoV-2 (Virus) - Diagnosis - 2019-2020 - Spain - Valencia (Autonomous Community)Seasonsbusiness
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GeneTonic: an R/Bioconductor package for streamlining the interpretation of RNA-seq data

2021

AbstractBackgroundThe interpretation of results from transcriptome profiling experiments via RNA sequencing (RNA-seq) can be a complex task, where the essential information is distributed among different tabular and list formats - normalized expression values, results from differential expression analysis, and results from functional enrichment analyses. A number of tools and databases are widely used for the purpose of identification of relevant functional patterns, yet often their contextualization within the data and results at hand is not straightforward, especially if these analytic components are not combined together efficiently.ResultsWe developed the GeneTonic software package, whi…

QH301-705.5Process (engineering)Computer scienceShinyComputer applications to medicine. Medical informaticsBioconductor610 MedizinR858-859.7Context (language use)Interactive data analysisReproducible researchBioconductorInteractivity610 Medical sciencesUse caseRNA-SeqBiology (General)MIT LicenseTranscriptomicsInformation retrievalBase SequenceSequence Analysis RNAData interpretationData visualizationRReproducibility of ResultsIdentification (information)WorkflowRNASoftwareFunctional enrichment analysis
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"Table 2" of "Measurement of the correlations between the polar angles of leptons from top quark decays in the helicity basis at $\sqrt{s}=7$TeV usin…

2017

The correlation factors for the statistical uncertainties between any two bins of the unfolded distribution.

Quantitative Biology::BiomoleculesP P --> LEPTON+ NU LEPTON- NUBAR BOTTOM BOTTOMBAR XDifferential Cross SectionP P --> W+ W- BOTTOM BOTTOMBAR XTopTop Production7000.0Astrophysics::Cosmology and Extragalactic AstrophysicsPhysics::Data Analysis; Statistics and ProbabilityP P --> TOP TOPBAR XInclusiveProton-Proton ScatteringW Pair ProductionAngular DependenceW ProductionDSIG/DTHETA
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Feature selection on a dataset of protein families: from exploratory data analysis to statistical variable importance

2016

Proteins are characterized by several typologies of features (structural, geometrical, energy). Most of these features are expected to be similar within a protein family. We are interested to detect which features can identify proteins that belong to a family, as well as to define the boundaries among families. Some features are redundant: they could generate noise in identifying which variables are essential as a fingerprint and, consequently, if they are related or not to a function of a protein family. We defined an original approach to analyze protein features for defining their relationships and peculiarities within protein families. A multistep approach has been mainly performed in R …

Quantitative Biology::Biomoleculesbusiness.industrySparse PCAPattern recognitionFeature selectionLinear discriminant analysisCross-validationRandom forestExploratory data analysisStatistical classificationArtificial intelligencebusinessCluster analysisMathematics
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Appendix D. Pairwise Pearson correlation coefficients between the commercial and ecological traits considered in the meta-analysis.

2016

Pairwise Pearson correlation coefficients between the commercial and ecological traits considered in the meta-analysis.

Quantitative Biology::Populations and EvolutionPhysics::Data Analysis; Statistics and ProbabilityQuantitative Biology::Genomics
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Investigating the quality of mental models deployed by undergraduate engineering students in creating explanations: The case of thermally activated p…

2013

This paper describes a method aimed at pointing out the quality of the mental models undergraduate engineering students deploy when asked to create explanations for phenomena or processes and/or use a given model in the same context. Student responses to a specially designed written questionnaire are quantitatively analyzed using researcher-generated categories of reasoning, based on the physics education research literature on student understanding of the relevant physics content. The use of statistical implicative analysis tools allows us to successfully identify clusters of students with respect to the similarity to the reasoning categories, defined as ``practical or everyday,'' ``descri…

Quantitative data analysiQualitative data analysisPhysics educationLC8-6691Learning environmentmedia_common.quotation_subjectMultimethodologySettore FIS/08 - Didattica E Storia Della FisicaPhysicsQC1-999Physics educationGeneral Physics and AstronomyContext (language use)Special aspects of educationEducationConsistency (negotiation)Engineering educationSimilarity (psychology)Mathematics educationQuality (business)Psychologymedia_commonPhysical Review Special Topics. Physics Education Research
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Observation of time-invariant coherence in a room temperature quantum simulator

2015

The ability to live in coherent superpositions is a signature trait of quantum systems and constitutes an irreplaceable resource for quantum-enhanced technologies. However, decoherence effects usually destroy quantum superpositions. It has been recently predicted that, in a composite quantum system exposed to dephasing noise, quantum coherence in a transversal reference basis can stay protected for indefinite time. This can occur for a class of quantum states independently of the measure used to quantify coherence, and requires no control on the system during the dynamics. Here, such an invariant coherence phenomenon is observed experimentally in two different setups based on nuclear magnet…

Quantum PhysicsCondensed Matter - Mesoscale and Nanoscale PhysicsPhysics - Data Analysis Statistics and ProbabilityMesoscale and Nanoscale Physics (cond-mat.mes-hall)FOS: Physical sciencesNuclear Experiment (nucl-ex)Quantum Physics (quant-ph)Nuclear ExperimentData Analysis Statistics and Probability (physics.data-an)
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