Search results for "vector [form factor]"

showing 10 items of 770 documents

Functional renormalization group approach to the Kraichnan model.

2015

We study the anomalous scaling of the structure functions of a scalar field advected by a random Gaussian velocity field, the Kraichnan model, by means of Functional Renormalization Group techniques. We analyze the symmetries of the model and derive the leading correction to the structure functions considering the renormalization of composite operators and applying the operator product expansion.

Pure mathematicsStatistical Mechanics (cond-mat.stat-mech)GaussianFOS: Physical sciencesRenormalization groupRenormalizationsymbols.namesakeHomogeneous spacesymbolsFunctional renormalization groupVector fieldOperator product expansionScalar fieldCondensed Matter - Statistical MechanicsMathematicsMathematical physicsPhysical review. E, Statistical, nonlinear, and soft matter physics
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A poincar�-bendixson theorem for analytic families of vector fields

1995

We provide a characterization of the limit periodic sets for analytic families of vector fields under the hypothesis that the first jet is non-vanishing at any singular point. Also, applying the family desingularization method, we reduce the complexity of some of these sets.

Pure mathematicsVector measureSolenoidal vector fieldJet (mathematics)General MathematicsMathematical analysisVector fieldSingular point of a curveDirection vectorPoincaré–Bendixson theoremMathematicsVector potentialBoletim da Sociedade Brasileira de Matem�tica
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Instruction-based clinical eye-tracking study on the visual interpretation of divergence : how do students look at vector field plots?

2018

Relating mathematical concepts to graphical representations is a challenging task for students. In this paper, we introduce two visual strategies to qualitatively interpret the divergence of graphical vector field representations. One strategy is based on the graphical interpretation of partial derivatives, while the other is based on the flux concept. We test the effectiveness of both strategies in an instruction-based eye-tracking study with N = 41 physics majors. We found that students’ performance improved when both strategies were introduced (74% correct) instead of only one strategy (64% correct), and students performed best when they were free to choose between the two strategies (88…

QC1-999graafinen esitysUndergraduate StudentsPhysics Education ResearchGeneral Physics and AstronomyResearch MethodologyContext (language use)LernenAssessmentMachine learningcomputer.software_genre01 natural sciencesEducationVisual processingsilmänliikkeetddc:370Concept learning0103 physical sciencesvektorit (matematiikka)ddc:530ta516Wissensrepräsentation010306 general physicsDivergence (statistics)graphical representationsvisual processingeye-trackingLC8-6691studentsopiskelijatbusiness.industryPhysicsMultimethodology05 social sciencesConcepts & Principles050301 educationKognitives LernenSpecial aspects of educationSaccadic maskingPhysikdidaktikEye trackingPartial derivativeArtificial intelligencebusinessvector fields0503 educationcomputer
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Automated quality control protocol for MR spectra of brain tumors.

2008

Item does not contain fulltext eTUMOUR (http://www.etumour.net/) is acquiring a large database of brain tumor (1)H MR spectra to develop automated pattern recognition methods and decision support system (DSS) for tumor diagnosis. Development of accurate pattern-recognition algorithms requires spectra undistorted by artifacts, low signal-to-noise, or broad lines. eTUMOUR currently uses panels of expert spectroscopists to subjectively grade spectra as being acceptable or unacceptable. Automated quality control (QC) would be more satisfactory for several reasons: 1) to provide a reproducible objective classification of spectrum quality; 2) for use within the future DSS to prevent misdiagnosis …

Quality ControlProtocol (science)Decision support systemMagnetic Resonance SpectroscopyBrain NeoplasmsComputer sciencemedia_common.quotation_subjectFeature extractioncomputer.software_genreIndependent component analysisDecision Support TechniquesPattern Recognition AutomatedTest setPattern recognition (psychology)Support vector machine classifierHumansRadiology Nuclear Medicine and imagingQuality (business)Functional Imaging [UMCN 1.1]Data miningcomputermedia_commonMagnetic Resonance in Medicine
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Machine learning-based models to predict modes of toxic action of phenols to Tetrahymena pyriformis.

2017

The phenols are structurally heterogeneous pollutants and they present a variety of modes of toxic action (MOA), including polar narcotics, weak acid respiratory uncouplers, pro-electrophiles, and soft electrophiles. Because it is often difficult to determine correctly the mechanism of action of a compound, quantitative structure-activity relationship (QSAR) methods, which have proved their interest in toxicity prediction, can be used. In this work, several QSAR models for the prediction of MOA of 221 phenols to the ciliated protozoan Tetrahymena pyriformis, using Chemistry Development Kit descriptors, are reported. Four machine learning techniques (ML), k-nearest neighbours, support vector…

Quantitative structure–activity relationshipAntiprotozoal AgentsQuantitative Structure-Activity RelationshipBioengineeringModes of toxic action010501 environmental sciencesMachine learningcomputer.software_genre01 natural sciencesMachine Learningchemistry.chemical_compoundPhenolsMolecular descriptorDrug DiscoveryPhenols0105 earth and related environmental sciencesCiliated protozoanArtificial neural networkbusiness.industryTetrahymena pyriformisGeneral Medicine0104 chemical sciencesSupport vector machine010404 medicinal & biomolecular chemistrychemistryTetrahymena pyriformisMolecular MedicineArtificial intelligenceNeural Networks ComputerbusinesscomputerSAR and QSAR in environmental research
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<strong>Machine Learning and Atom-Based Quadratic Indices for Proteasome Inhibition Prediction </strong>

2015

The atom-based quadratic indices are used in this work together with some machine learning techniques that includes: support vector machine, artificial neural network, random forest and k-nearest neighbor. This methodology is used for the development of two quantitative structure-activity relationship (QSAR) studies for the prediction of proteasome inhibition. A first set consisting of active and non-active classes was predicted with model performances above 85% and 80% in training and validation series, respectively. These results provided new approaches on proteasome inhibitor identification encouraged by virtual screenings procedures. .

Quantitative structure–activity relationshipArtificial neural networkSeries (mathematics)Computer sciencebusiness.industryMachine learningcomputer.software_genreRandom forestSupport vector machineSet (abstract data type)Quadratic equationProteasome inhibitormedicineArtificial intelligencebusinesscomputermedicine.drugProceedings of MOL2NET, International Conference on Multidisciplinary Sciences
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Predictive modeling of aryl hydrocarbon receptor (AhR) agonism

2020

Abstract The aryl hydrocarbon receptor (AhR) plays a key role in the regulation of gene expression in metabolic machinery and detoxification systems. In the recent years, this receptor has attracted interest as a therapeutic target for immunological, oncogenic and inflammatory conditions. In the present report, in silico and in vitro approaches were combined to study the activation of the AhR. To this end, a large database of chemical compounds with known AhR agonistic activity was employed to build 5 classifiers based on the Adaboost (AdB), Gradient Boosting (GB), Random Forest (RF), Multilayer Perceptron (MLP) and Support Vector Machine (SVM) algorithms, respectively. The built classifier…

Quantitative structure–activity relationshipEnvironmental EngineeringSupport Vector MachineHealth Toxicology and MutagenesisIn silico0208 environmental biotechnologyContext (language use)02 engineering and technologyComputational biology010501 environmental sciences01 natural scienceschemistry.chemical_compoundPhenolsBasic Helix-Loop-Helix Transcription FactorsEnvironmental ChemistryAnimalsHumans[CHIM]Chemical SciencesComputer SimulationBenzothiazolesProspective StudiesReceptorComputingMilieux_MISCELLANEOUS0105 earth and related environmental sciencesRegulation of gene expressionbiologyChemistryPublic Health Environmental and Occupational HealthRobustness (evolution)General MedicineGeneral ChemistryAryl hydrocarbon receptorPollution020801 environmental engineering3. Good healthBenzothiazoleReceptors Aryl Hydrocarbonbiology.proteinNeural Networks Computer[INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM]Algorithms[CHIM.CHEM]Chemical Sciences/Cheminformatics
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Exclusive radiative decays of W and Z bosons in QCD factorization

2015

We present a detailed theoretical analysis of very rare, exclusive hadronic decays of the electroweak gauge bosons V=W, Z from first principles of QCD. Our main focus is on the radiative decays V->M+gamma, in which M is a pseudoscalar or vector meson. At leading order in an expansion in powers of Lambda_{QCD}/m_V the decay amplitudes can be factorized into convolutions of calculable hard-scattering coefficients with the leading-twist light-cone distribution amplitude of the meson M. Power corrections to the decay rates arise first at order (Lambda_{QCD}/m_V)^2. They can be estimated in terms of higher-twist distribution amplitudes and are predicted to be tiny. We include one-loop O(alpha…

Quantum chromodynamicsPhysicsGauge bosonParticle physicsNuclear and High Energy PhysicsMeson010308 nuclear & particles physicsHigh Energy Physics::LatticeElectroweak interactionHigh Energy Physics::PhenomenologyFOS: Physical sciences01 natural sciencesHigh Energy Physics - PhenomenologyHigh Energy Physics - Phenomenology (hep-ph)W and Z bosons0103 physical sciencesHigh Energy Physics::ExperimentVector mesonResummation010306 general physicsLeptonJournal of High Energy Physics
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An experimental study of γγ → hadrons at LEP

1993

An analysis of γγ interactions has been performed using untagged hadronic data obtained by the ALEPH detector at LEP. The data show at low transverse momentum (pt) are well reproduced by a model based on the vector meson dominance mechinism (VDM). At high pt thrust the presence of hard scattering processes is demonstrated. This component is well described in shape and normalization by a QCD calculation.

Quantum chromodynamicsPhysicsNormalization (statistics)Nuclear and High Energy PhysicsParticle physicsROSS-SECTIONE+E-PHYSICSScatteringHigh Energy Physics::PhenomenologyHadronElementary particleVector meson dominancePhoton structure functionJET FRAGMENTATIONNuclear physicsALEPH ExperimentPHOTONLUND MONTE-CARLOCSCATTERINGHigh Energy Physics::ExperimentALEPH experiment
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Linear Wave Equations and Effective Lagrangians for Wigner Supermultiplets

1995

The relevance of the contracted SU(4) group as a symmetry group of the pion nucleon scattering amplitudes in the large $N_c$ limit of QCD raises the problem on the construction of effective Lagrangians for SU(4) supermultiplets. In the present study we suggest effective Lagrangians for selfconjugate representations of SU(4) in exploiting isomorphism between so(6) and ist universal covering su(4). The model can be viewed as an extension of the linear $\sigma$ model with SO(6) symmetry in place of SO(4) and generalizes the concept of the linear wave equations for particles with arbitrary spin. We show that the vector representation of SU(4) reduces on the SO(4) level to a complexified quatern…

Quantum chromodynamicsPhysicsNuclear and High Energy PhysicsDegrees of freedom (statistics)FOS: Physical sciencesAstronomy and AstrophysicsSymmetry groupAtomic and Molecular Physics and OpticsSymmetry (physics)Minimal modelScattering amplitudeHigh Energy Physics - PhenomenologyHigh Energy Physics - Phenomenology (hep-ph)Vector mesonQuaternionMathematical physics
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