Search results for "Computational Technique"

showing 10 items of 16 documents

Evolving Notch polyQ tracts reveal possible solenoid interference elements.

2016

ABSTRACTPolyglutamine (polyQ) tracts in regulatory proteins are extremely polymorphic. As functional elements under selection for length, triplet repeats are prone to DNA replication slippage and indel mutations. Many polyQ tracts are also embedded within intrinsically disordered domains, which are less constrained, fast evolving, and difficult to characterize. To identify structural principles underlying polyQ tracts in disordered regulatory domains, here I analyze deep evolution of metazoan Notch polyQ tracts, which can generate alleles causing developmental and neurogenic defects. I show that Notch features polyQ tract turnover that is restricted to a discrete number of conserved “polyQ …

0301 basic medicineModels MolecularProtein Structure ComparisonProtein FoldingHuntingtinlcsh:MedicineCarboxamideAnkyrin Repeat DomainBiochemistryProtein Structure SecondaryDatabase and Informatics Methods0302 clinical medicineProtein structureMacromolecular Structure AnalysisDrosophila Proteinslcsh:ScienceGeneticsHuntingtin ProteinMultidisciplinaryReceptors NotchChemistryDrosophila MelanogasterAnimal ModelsCell biologyInsectsExperimental Organism SystemsProtein foldingDrosophilaSequence AnalysisResearch ArticleMultiple Alignment CalculationProtein StructureArthropodamedicine.drug_classBioinformaticsProtein domainSequence alignmentBiologyIntrinsically disordered proteinsResearch and Analysis MethodsTerminal loopEvolution Molecular03 medical and health sciencesModel OrganismsProtein DomainsSequence Motif AnalysisComputational TechniquesmedicineHuntingtin ProteinAnimalsIndelMolecular BiologyRepetitive Sequences Nucleic AcidModels GeneticSequence Homology Amino Acidlcsh:RDNA replicationOrganismsBiology and Life SciencesProteinsHydrogen BondingInvertebratesSplit-Decomposition MethodIntrinsically Disordered Proteins030104 developmental biologyAnkyrin repeatlcsh:QPeptidesSequence Alignment030217 neurology & neurosurgeryPLoS ONE
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Bicausative matrices to measure structural change: Are they a good tool?

1999

The causative-matrix method to analyze temporal change assumes that a matrix transforms one Markovian transition matrix into another by a left multiplication of the first matrix; the method is demand-driven when applied to input-output economics. An extension is presented without assuming the demand-driven or supply-driven hypothesis. Starting from two flow matrices X and Y, two diagonal matrices are searched, one premultiplying and the second postmultiplying X, to obtain a result the closer as possible to Y by least squares. The paper proves that the method is deceptive because the diagonal matrices are unidentified and the interpretation of results is unclear. Keywords : Input-Output ; Ch…

BiproportionBicausativePure mathematicsJEL: C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C67 - Input–Output Modelsjel:C63jel:C67JEL: D - Microeconomics/D.D5 - General Equilibrium and Disequilibrium/D.D5.D57 - Input–Output Tables and AnalysisLeast squaresMeasure (mathematics)Interpretation (model theory)JEL: C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C63 - Computational Techniques • Simulation ModelingSylvester's law of inertiaMatrix (mathematics)Diagonal matrixStatisticsJEL : D - Microeconomics/D.D5 - General Equilibrium and Disequilibrium/D.D5.D57 - Input–Output Tables and Analysis[ SHS.ECO ] Humanities and Social Sciences/Economies and finances[SHS.ECO] Humanities and Social Sciences/Economics and FinanceGeneral Environmental ScienceMathematicsJEL : C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C67 - Input–Output Modelseconomic theoryhumanities social sciencessciences humaines et socialesStochastic matrixStructural ChangeGeneral Social Scienceseconomics[SHS.ECO]Humanities and Social Sciences/Economics and Financejel:D57CausativeJEL : C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C63 - Computational Techniques • Simulation ModelingChaosMultiplicationThe Annals of Regional Science
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Forecast Output Coincidence and Biproportion: Two Criteria to Determine the Orientation of an Economy. Comparison for France (1980-1997)

2002

International audience; The method of forecast output coincidence used to determine if sectors are demand-sided or supply-sided in an input-output framework mixes two effects, the structural effect (choosing between demand and supply side models) and the effect of an exogenous factor (final demand or added-value). The note recalls that another method is possible, the comparison of the stability of technical and allocation coefficients, generalized by the biproportional filter: if for a sector, after biproportional filtering, column coefficients are more stable than row coefficients, then this sector is declared as not supply-sided (but one cannot decide that it is demand-sided anyway), and …

BiproportionEconomics and EconometricsJEL: C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C67 - Input–Output ModelsSupplyChangeJEL: D - Microeconomics/D.D5 - General Equilibrium and Disequilibrium/D.D5.D57 - Input–Output Tables and AnalysisStability (probability)Column (database)CoincidenceSupply and demandMicroeconomicsJEL: C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C63 - Computational Techniques • Simulation ModelingEconometricsEconomicsDemandJEL : D - Microeconomics/D.D5 - General Equilibrium and Disequilibrium/D.D5.D57 - Input–Output Tables and Analysis[ SHS.ECO ] Humanities and Social Sciences/Economies and finances[SHS.ECO] Humanities and Social Sciences/Economics and FinanceInput/outputJEL : C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C67 - Input–Output ModelsOrientation (computer vision)Exogenous factorFilter (signal processing)[SHS.ECO]Humanities and Social Sciences/Economics and FinanceJEL : C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C63 - Computational Techniques • Simulation ModelingInput-OutputRAS
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A Computational Technique for Solving Singularly Perturbed Delay Partial Differential Equations

2021

Abstract In this work, a matrix method based on Laguerre series to solve singularly perturbed second order delay parabolic convection-diffusion and reaction-diffusion type problems involving boundary and initial conditions is introduced. The approximate solution of the problem is obtained by truncated Laguerre series. Moreover convergence analysis is introduced and stability is explained. Besides, a test case is given and the error analysis is considered by the different norms in order to show the applicability of the method.

Computational TechniquePartial differential equationlaguerre polynomials and seriesComputer scienceElectronic computers. Computer sciencedelay partial differential equationApplied mathematicslaguerre matrix-collocation methodQA75.5-76.95singularly perturbed parabolic problemconvergence analysisFoundations of Computing and Decision Sciences
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Pressure Dependence of Positron Annihilation in Si

1994

The pressure dependence of the electron-positron and the electron-electron momentum densities in silicon are studied. The observations that the electron-positron momentum density increases more rapidly with pressure than the electron-electron momentum density alone is explained in terms of increased positron penetration into the ion cores. The computational technique used here is based on the independent-particle model (IPM) coupled with the use of the electron pseudo-wave functions.

Computational TechniquePositronSiliconchemistrychemistry.chemical_elementPenetration (firestop)ElectronAtomic physicsPressure dependenceCondensed Matter PhysicsElectronic Optical and Magnetic MaterialsIonPositron annihilationphysica status solidi (b)
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Numerical simulation of fatigue-driven delamination using interface elements

2005

This paper presents a computational technique for the prediction of fatigue-driven delamination growth in composite materials. The interface element, which has been extensively applied to predict delamination growth due to static loading, has been modified to incorporate the effects of cyclic loading. Using a damage mechanics formulation, the constitutive law for the interface element has been extended by incorporating a modified version of a continuum fatigue damage model. The paper presents details of the fatigue degradation strategy and examples of the predicted fatigue delamination growth in mode I, mode II and mixed mode I/II are presented to demonstrate that the numerical model mimics…

DAMAGEinterface elementNumerical AnalysisEngineeringComputer simulationbusiness.industryApplied Mathematicscomposite materialsConstitutive equationGeneral EngineeringFracture mechanicsFatigue damageStructural engineeringdelaminationFinite element methodComputational TechniqueINTERLAMINAR FRACTURE SPECIMENS DAMAGE COMPOSITES FATIGUE GROWTHFATIGUE GROWTHDamage mechanicsMode couplingCOMPOSITESfatigueINTERLAMINAR FRACTURE SPECIMENSbusinessInternational Journal for Numerical Methods in Engineering
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The Asynchronous Leontief Model

1992

International audience; The traditional dynamic Leontief model is synchronous: every vertex acts simultaneously. A model with delays of action has been proposed, but it still remains synchronous. In this paper we propose an asynchronous version of the model that allows realistic computations. We fiurnish an algorithm and a program.

Discrete mathematicsLeontief modelVertex (graph theory)JEL : C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C67 - Input–Output ModelsEconomics and EconometricsJEL: C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C67 - Input–Output ModelsComputer scienceComputationJEL: D - Microeconomics/D.D5 - General Equilibrium and Disequilibrium/D.D5.D57 - Input–Output Tables and Analysis[SHS.ECO]Humanities and Social Sciences/Economics and FinanceAction (physics)JEL: C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C63 - Computational Techniques • Simulation ModelingJEL : C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C63 - Computational Techniques • Simulation ModelingAsynchronous communicationJEL : D - Microeconomics/D.D5 - General Equilibrium and Disequilibrium/D.D5.D57 - Input–Output Tables and Analysis[ SHS.ECO ] Humanities and Social Sciences/Economies and finances[SHS.ECO] Humanities and Social Sciences/Economics and Finance
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Chances and Challenges of Computational Data Gathering and Analysis

2015

Digital and social media and large available data-sets generate various new possibilities and challenges for conducting research focused on perpetually developing online news ecosystems. This paper presents a novel computational technique for gathering and processing large quantities of data from Facebook. We demonstrate how to use this technique for detecting and analysing issue-attention cycles and news flows in Facebook groups and pages. Although the paper concentrates on a Finnish Facebook group as a case study, the demonstrated method can be used for gathering and analysing large sets of data from various social network sites and national contexts. The paper also discusses Facebook pla…

Facebookcomputational data gathering020205 medical informaticsComputer scienceissue-attention cycledata warehouse050801 communication & media studies02 engineering and technologynews flowsWorld Wide WebComputational Technique0508 media and communications0202 electrical engineering electronic engineering information engineeringSocial mediata518semi-public datata113hybrid news ecosystemData collectionEthical issuesSocial networkbusiness.industryCommunication05 social sciencesOnline research methodsData warehousedigital and social media researchbusinessDigital Journalism
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Dynamique de la structure industrielle française

1990

JEL : C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C67 - Input–Output ModelsJEL: C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C63 - Computational Techniques • Simulation ModelingJEL: C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C67 - Input–Output ModelsJEL: C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C61 - Optimization Techniques • Programming Models • Dynamic AnalysisJEL : C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C63 - Computational Techniques • Simulation ModelingJEL: L - Industrial Organization/L.L1 - Market Structure Firm Strategy and Market Performance/L.L1.L16 - Industrial Organization and Macroeconomics: Industrial Structure and Structural Change • Industrial Price IndicesJEL : D - Microeconomics/D.D5 - General Equilibrium and Disequilibrium/D.D5.D57 - Input–Output Tables and AnalysisJEL : C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C61 - Optimization Techniques • Programming Models • Dynamic Analysis[ SHS.ECO ] Humanities and Social Sciences/Economies and financesJEL: D - Microeconomics/D.D5 - General Equilibrium and Disequilibrium/D.D5.D57 - Input–Output Tables and AnalysisJEL : L - Industrial Organization/L.L1 - Market Structure Firm Strategy and Market Performance/L.L1.L16 - Industrial Organization and Macroeconomics: Industrial Structure and Structural Change • Industrial Price Indices[SHS.ECO]Humanities and Social Sciences/Economics and Finance[SHS.ECO] Humanities and Social Sciences/Economics and Finance
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A Note on added information in the RAS Procedure: reexamination of some evidence

2006

International audience; An example in Miernyk (1977) presented a rather counterintuitive result, namely that introducing accurate exogenous information into an RAS matrix estimating procedure could lead to an estimate that was worse than one generated by RAS using no exogenous information at all. This became an oft-cited black mark against RAS. Miller and Blair (1985) included a different (and small) illustration of the same possibility. It was recently pointed out by one of us that the Miller/Blair numerical results are wrong. For that reason, we decided to reexamine all the empirical evidence we could find on the subject. While figures in both Miernyk and Miller/Blair appear to be wrong, …

JEL : C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C67 - Input–Output ModelsJEL: C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C67 - Input–Output ModelsCounterintuitiveClosenessJEL: D - Microeconomics/D.D5 - General Equilibrium and Disequilibrium/D.D5.D57 - Input–Output Tables and AnalysisEnvironmental Science (miscellaneous)Development[SHS.ECO]Humanities and Social Sciences/Economics and FinanceJEL: C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C63 - Computational Techniques • Simulation ModelingJEL : C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C63 - Computational Techniques • Simulation ModelingInput-outputbiproportionEconometricsJEL : D - Microeconomics/D.D5 - General Equilibrium and Disequilibrium/D.D5.D57 - Input–Output Tables and Analysis[ SHS.ECO ] Humanities and Social Sciences/Economies and finances[SHS.ECO] Humanities and Social Sciences/Economics and FinanceEmpirical evidenceMathematical economicsCounterexampleMathematicsRAS
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