Search results for "Complex system"

showing 10 items of 226 documents

Evolutionary dynamics of imatinib-treated leukemic cells by stochastic approach

2008

The evolutionary dynamics of a system of cancerous cells in a model of chronic myeloid leukemia (CML) is investigated by a statistical approach. Cancer progression is explored by applying a Monte Carlo method to simulate the stochastic behavior of cell reproduction and death in a population of blood cells which can experience genetic mutations. In CML front line therapy is represented by the tyrosine kinase inhibitor imatinib which strongly affects the reproduction of leukemic cells only. In this work, we analyze the effects of a targeted therapy on the evolutionary dynamics of normal, first-mutant and cancerous cell populations. Several scenarios of the evolutionary dynamics of imatinib-tr…

Monte Carlo simulation stochastic approach Evolutionary dynamicsMutation rate87.23.kgmedicine.drug_classQC1-999medicine.medical_treatmentPopulationGeneral Physics and AstronomyBiologyTyrosine-kinase inhibitorTargeted therapyhemic and lymphatic diseasesmedicine87.10.mncomplex systemsQuantitative Biology - Populations and EvolutioneducationEvolutionary dynamicseducation.field_of_studycancer evolutionPhysicsstochastic dynamics87.19.xjPopulations and Evolution (q-bio.PE)Myeloid leukemiaImatinibSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)FOS: Biological sciencesCancer cellCancer research87.10.rtmedicine.drugOpen Physics
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Measuring frequency domain granger causality for multiple blocks of interacting time series

2011

In the past years, several frequency-domain causality measures based on vector autoregressive time series modeling have been suggested to assess directional connectivity in neural systems. The most followed approaches are based on representing the considered set of multiple time series as a realization of two or three vector-valued processes, yielding the so-called Geweke linear feedback measures, or as a realization of multiple scalar-valued processes, yielding popular measures like the directed coherence (DC) and the partial DC (PDC). In the present study, these two approaches are unified and generalized by proposing novel frequency-domain causality measures which extend the existing meas…

Multivariate statisticsTime FactorsGeneral Computer ScienceLogarithmScalar (mathematics)Complex systemTopologyModels BiologicalNeurophysiological time serieBlock-based connectivity analysiGranger causalityStatisticsHumansComputer SimulationDirected coherenceMathematicsNumerical analysisPartial directed coherenceBrainElectroencephalographyVector autoregressive (VAR) modelBrain WavesCausalityAutoregressive modelFrequency domainComputer ScienceSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaGranger causalityAlgorithmsBiotechnologyBiological Cybernetics
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Managing expert knowledge in water network expansion project implementation

2021

[EN] The implementation of expansion projects of water networks supplying growing cities is deemed to be a complex decision-making problem involving both technical aspects and expert knowledge. Management and control processes must rely on experts in the field whose know-how must be coupled with techniques able to deal with the natural subjectivity that affects input evaluations. Given the presence of many decision-making elements, the choice of proper hydraulic technical parameters may be linked to the main aspects of analysis requiring formal expert evaluation. In this contribution, the simulation of hydraulic indicators is integrated with a multi-criteria approach able to eventually dete…

Network expansionEngineering managementComplex systemsExpansion projectControl and Systems EngineeringProject implementationComputer scienceEPAnet software 2.0Water distribution networksTOPSISMATEMATICA APLICADAManagement and control
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Air Transport Network: a short review

2013

Networks complex systems transport air traffic management
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Study on the transient characteristic in the human visual system using masking experiments

1979

In this paper the visual masking effect is interpreted on the basic of the transient characteristic in two dimensional neuronal networks. The study investigates the suitability of the effect for use as a measurement method. It is shown that the stimulus distribution in space can be scanned at different points in time and that various dynamic characteristic values of the system can be measured.

NeuronsMeasurement methodTime FactorsGeneral Computer ScienceComputer sciencebusiness.industryModels NeurologicalNeural ConductionComplex systemNeural InhibitionStimulus (physiology)Pattern Recognition VisualVisual maskingHuman visual system modelVisual PerceptionHumansVisual PathwaysComputer visionArtificial intelligenceNerve NetBiological systembusinessPhotic StimulationBiotechnologyBiological Cybernetics
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Multitasking associative networks.

2012

We introduce a bipartite, diluted and frustrated, network as a sparse restricted Boltzman machine and we show its thermodynamical equivalence to an associative working memory able to retrieve multiple patterns in parallel without falling into spurious states typical of classical neural networks. We focus on systems processing in parallel a finite (up to logarithmic growth in the volume) amount of patterns, mirroring the low-level storage of standard Amit-Gutfreund-Sompolinsky theory. Results obtained trough statistical mechanics, signal-to-noise technique and Monte Carlo simulations are overall in perfect agreement and carry interesting biological insights. Indeed, these associative network…

NeuronsRestricted Boltzmann machineTheoretical computer scienceArtificial neural networkComputer scienceMonte Carlo methodComplex systemGeneral Physics and AstronomyFOS: Physical sciencesStatistical mechanicsDisordered Systems and Neural Networks (cond-mat.dis-nn)Condensed Matter - Disordered Systems and Neural NetworksPhysics and Astronomy (all)Human multitaskingNeural Networks ComputerNerve NetEquivalence (measure theory)Associative propertyPhysical review letters
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Role of noise in a market model with stochastic volatility

2006

We study a generalization of the Heston model, which consists of two coupled stochastic differential equations, one for the stock price and the other one for the volatility. We consider a cubic nonlinearity in the first equation and a correlation between the two Wiener processes, which model the two white noise sources. This model can be useful to describe the market dynamics characterized by different regimes corresponding to normal and extreme days. We analyze the effect of the noise on the statistical properties of the escape time with reference to the noise enhanced stability (NES) phenomenon, that is the noise induced enhancement of the lifetime of a metastable state. We observe NES ef…

Noise inducedProbability theory stochastic processes and statisticFOS: Physical sciencesEconomicFOS: Economics and businessStochastic differential equationStatistical physicsMarket modelCondensed Matter - Statistical MechanicsEconomics; econophysics financial markets business and management; Probability theory stochastic processes and statistics; Fluctuation phenomena random processes noise and Brownian motion; Complex SystemsMathematicsFluctuation phenomena random processes noise and Brownian motionStatistical Finance (q-fin.ST)Stochastic volatilityStatistical Mechanics (cond-mat.stat-mech)Cubic nonlinearityQuantitative Finance - Statistical FinanceComplex SystemsWhite noiseDisordered Systems and Neural Networks (cond-mat.dis-nn)Condensed Matter - Disordered Systems and Neural NetworksCondensed Matter PhysicsSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)Electronic Optical and Magnetic MaterialsHeston modelVolatility (finance)econophysics financial markets business and management
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GUEST EDITORS' EDITORIAL: NOISE IN CONDENSED MATTER AND COMPLEX SYSTEMS

2005

NoiseGeneral MathematicsAcousticsComplex systemGeneral Physics and AstronomyEnvironmental scienceFluctuation and Noise Letters
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On the modeling of nonlinear interactions in large complex systems

2010

Abstract This work deals with the modeling of large systems of interacting entities in the framework of the mathematical kinetic theory for active particles. The contents are specifically focused on the modeling of nonlinear interactions which is one of the most important issues in the mathematical approach to modeling and simulating complex systems, and which includes a learning–hiding dynamics. Applications are focused on the modeling of complex biological systems and on immune competition.

Non lineariteLiving systems Nonlinearity Functional subsystems Kinetic theory Active particlesApplied MathematicsActive particlesComplex system010103 numerical & computational mathematics01 natural sciencesActive particlesLiving systems010101 applied mathematicsNonlinear systemLiving systemsFunctional subsystems0101 mathematicsKinetic theoryBiological systemComplex systems biologyNonlinearitySettore MAT/07 - Fisica MatematicaAlgorithmMathematicsApplied Mathematics Letters
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Regularity of solutions of nonlinear variational inequalities

1973

Nonlinear systemMathematics (miscellaneous)Mechanical EngineeringVariational inequalityMathematical analysisComplex systemAnalysisMathematicsArchive for Rational Mechanics and Analysis
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