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    Modeling Scenario
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    1-047-Condensation-ModelingScenario
    We simulate the random motion of 200 particles in a 50 by 50 square in which a particle bounces off the two vertical and top walls and condenses on the bottom wall. Animations are produced and data is offered for modeling with a differential...
    simulationsum of square errorscondensationbest fit
    Modeling Scenario
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    5-010-DNADegradation-ModelingScenario
    We ask students to use the system of first order linear differential equations given in a source paper and estimates of the data from laboratory procedures from a plot to estimate the parameters and complete the modeling process.
    DNA\kinetisplasmaratpharmacokinetis
    Modeling Scenario
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    1-093-SucroseReaction-ModelingScenario
    We offer data on the hydrolysis of sucrose in the presence of catalyst sucrase. We present students with several models and ask which model is best. We ask students to estimate parameters for the best model.
    kineticsMichaelis-Mentenhydrolysisreactionsucrose
    Potential Scenario
    148

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    76

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    2016-Manheim-EtAl-Improving Decision Support for Infectious Disease Prevention and Control
    This report describes decision-support tools, including models and nonmodeling approaches, that are relevant to infectious disease prevention, detection, and response and aligns these tools with real-world policy questions that the tools can help...
    infectious diseaseecosystemepidemicmodel policy
    Modeling Scenario
    272

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    217

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    1-078-MonodGrowthModel-ModelingScenario
    Students model growth of bacteria E. coli in a limiting nutrient environment using data from a historical study.
    bacterianutrient cyclesgrowthMonodconsumption
    Modeling Scenario
    248

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    216

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    1-054-GrowthInFarmland-ModelingScenario
    An enriching project developing a model from data with missing temporal information is described. Students fit functions to the data that leads to the creation of a differential equations model, which they then are required to analyze in multiple...
    fittingfarmfarmland
    Modeling Scenario
    250

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    209

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    1-066-USCensusModeling-ModelingScenario
    The United States Census, conducted every 10 years, gives data on the United States population, that can be modeled with the exponential, logistic, or Gompertz functions.
    datalogisticpopulationGompertzcensusgoodness of fit
    Modeling Scenario
    765

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    2017

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    9-014-TurkeyCook-ModelingScenario
    The goal of this project is to investigate several models for the cooking time for a turkey based on weight, test these models with data obtained from heating curves for turkeys of various weights, and develop a new model to fit this data.
    sphereheat equationturkeyPanofskyradial symmetry
    Modeling Scenario
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    313

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    6-008-PursuitModels-Modeling Scenario
    Students are prompted to build systems of nonlinear differential equations to model pursuit-evader activities in which a pursuer attempts to follow, perhaps track down and come close to, an evader without knowledge of the evader's intentions, just...
    Potential Scenario
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    69

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    2015-Zhang-EtAl-On the Selection of ODE Models with Application to Predator-Prey Dynamical Models
    We propose a computationally inexpensive approach that employs statistical estimation of the full model, followed by a combination of a least squares approximation (LSA) and the adaptive Lasso.
    least-squares approximationSpline modelingMonte Carlo simulationsvariable selectionadaptive LASSO
    Potential Scenario
    125

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    1999-F_Brauer-What Goes Up Must Come Down
    This paper is a wonderfully general analysis of the following, “It is natural to ask whether a particle propelled upwards takes longer to fall to earth from its maximum height than it takes to rise to this maximum height for frictional forces.
    projectilefrictionfalling timerising timemaximum height
    Article or Presentation
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    45

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    1999-F_Brauer-What_Goes_Up_Must_Come_Down
    It is natural to ask whether a particle propelled upwards takes longer to fall to earth from its maximum height than it takes to rise to this maximum height for frictional forces that are nonlinear functions of velocity.
    resistancefallingprojectilevertical projectile
    Modeling Scenario
    275

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    172

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    5-023-FakingGause-ModelingScenario
    We use a fake or toy data set to permit discovery of the parameters in a two population protozoan model used to study paramecium and yeast competition in the 1930's studies of G. F. Gause in the Soviet Union.
    competitionlogisticyeastGauseparameciumpoplulation
    Modeling Scenario
    367

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    6-007-FunctionsAndDerivativesInSIRModels-ModelingScenario
    Given a system of differential equations, how do the solution graphs compare with the graphs of the differential equations? Students tackle this question using SIR models for well-known infectious diseases.
    epidemiologyspecies interactionsderivativesvisualizationinfectionSIR modelsLaw of Mass Action
    Potential Scenario
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    41

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    2011-Teleken-EtAl-Mathematical modeling of microbial growth in milk
    A mathematical model to predict microbial growth in milk was developed and analyzed. The model consists of a system of two differential equations of first order. The equations are based on physical hypotheses of population growth.
    bacteriadairymilkfood safetymicrobilogy
    Potential Scenario
    274

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    94

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    2006-Wilensky-Reisman-Thinking Like a Wolf a Sheep or a Firefly
    We describe a computation-based approach that enables students to investigate the connections between different biological levels using agent-based, embodied modeling tools.
    simulationNetLogopredator-preyagent-basedwolffox
    Modeling Scenario
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    1-057-FiguringFluidFlow-ModelingScenario
    We propose three differential equations models for the height of a column of falling water as the water exits a small bore hole at the bottom of the cylinder and ask students to determine which model is the best of the three.
    dischargetankTorricelli's LawConservation of Energyfluid flowheightliquid
    Free Online Textbook
    201

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    78

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    2018-Eduardo-Sontag-Lecture_Notes_on_Mathematical_Systems_Biology
    I am often asked if it is OK to use these notes in courses at other universities. The answer is “of course!” though I strongly suggest that a link to my website be provided, so that students can always access the current version.
    biologytextbooksystemsdyanmical system
    Modeling Scenario
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    1-046-GoingViral-ModelingScenario
    Students participate in a simulation of the spread of a viral disease in the classroom and model the process with a logistic differential equation. The simulation uses random numbers and the entire class participates.
    simulationmathematical modeldatalogisticrandom number generatorfittingrandom process