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    Modeling Scenario
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    5-015-RunnersSynchronize-ModelingScenario
    In this modeling scenario we practice finding and classifying equilibria of a one-variable differential equation. We do this in the context of a phase model which is often a simpler way of studying oscillatory phenomena.
    predatorAutonomous equationsoscillationcoupled oscillatorsynchronyrunnerpreyKuramato model
    Potential Scenario
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    49

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    2012-Yuan_Yuan-A coupled plankton system with instantaneous and delayed predation
    We present two simple plankton population models: one has instantaneous predation, another has delayed predation.
    phytoplanktonbifurcationorbitsherbivorous zooplanktoneffect of fishmaturation time delay
    Potential Scenario
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    1999-Kowalczyk-Hausknecht-Using DEs To Model Real World Data
    With the increasing availability of easy to use interactive differential equation software, we convinced ourselves to completely redesign the way we teach differential equations.
    circuitTorricelli's LawHooke's LawRC circuitharmonic oscillatorglucoseglucose tolerance test
    Potential Scenario
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    2014-Vance-Eads-Sensitivity Analysis of a Three-Species Nonlinear Response Omnivory Model with Predator Stage Structure
    We investigate a three-species nonlinear response omnivory model incorporating stage structure in the top predator. The model consists of four coupled ordinary differential equations involving fourteen parameters.
    stage structuresensitivity analysismortalityomnivoreomnivory modelsearch rates
    Potential Scenario
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    2010-Shianga-EtAl-Computational model of the human glucose-insulin regulatory system
    A computational model of insulin secretion and glucose metabolism for assisting the diagnosis of diabetes mellitus in clinical research is introduced. The
    glucose tolerance testsum of squared residualsmultiple shooting methodcost function
    Potential Scenario
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    1975-David_Burghes-Population dynamics An introduction to differential equations
    In this paper a number of population models, which lead to differential equations, are derived. First-order variables separable equations are formulated from the Malthusian population model and its extension to include crowding effects.
    fishpredator-preylogisticpopulationdelaylag