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    Potential Scenario
    186

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    74

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    1996-D_Erdman-MM_Morelock-A Study of Kinetics
    This paper introduces new and old features of the SAS System for the estimation and simulation of systems of first-order differential equations with emphasis on examples in kinetics.
    simulationkineticsparameter estimationEnzymesubstratesavingscompartmentstomachbloodginseng
    Modeling Scenario
    255

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    270

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    1-002-Tossing-ModelingScenario
    We offer students simulation experience or data from a simulation and ask them to model the simulation using several approaches, to include exponential decay fit, difference equation, and differential equation.
    Modeling and simulationexponentialdecaydice
    Potential Scenario
    1249

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    47

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    2000-Erdman-Morelock-A Study of Kinetics The Estimation and Simulation of Systems of First-Order Differential Equations
    This paper introduces new and old features of the SAS System for the estimation and simulation of systems of first-order differential equations with emphasis on examples in kinetics.
    kineticsSAScompartmentpharmacokinetics
    Modeling Scenario
    404

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    506

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    1-047a-CondensationOptimization-ModelingScenario
    We seek to optimize a condensation process which is modeled by a simulation using 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.
    simulationdataoptimizationenergycondensationbest fitcostsum of scquare errors
    Modeling Scenario
    265

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    126

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    0

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    1-084-GoingViral-ModelingScenario
    Students employ randomization in order to create a simulation of the spread of a viral disease in a population (the classroom). Students then use qualitative analysis of the expected behavior of the virus to devise a logistic differential equation.
    simulationlogisticrandomfittingpartial fractions
    Article or Presentation
    235

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    70

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    2009-Brian_Winkel-Population_modelling_with_MandMs
    Several activities in which population dynamics can be modeled by tossing M&M’s® candy are presented.
    simulationparameter estimationimmigrationdeathdifference equation
    Modeling Scenario
    406

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    485

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    1-001-MM-DeathAndImmigration-ModelingScenario
    We conduct a simulation of death and immigration, using a small set of "individuals", m&m candies or any two sided object (coin, chips), in which upon tossing a set of individuals we cause some to die and others then to immigrate. Modeling ensues!
    simulationimmigrationdeathSpanishdatsWinkelBrian Winkel
    Potential Scenario
    256

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    67

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    2018-Van_Kinh Nguyen-Esteban_Hernandez-Vargas-Parameter estimation in mathematical models of viral infections using R
    Mathematical modeling has played a central role to understand mechanisms in different viral infectious diseases. In this approach, biological-based hypotheses are expressed via mathematical relations and then tested based on empirical data.
    simulationdiseasevirusviral infection
    Modeling Scenario
    366

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    162

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    1-001d-HotelPopulationDecay-ModelingScenario
    You will be modeling the following situation: 100 people are in a hotel. Each day, each person has a random chance of 50% of leaving the hotel. No new people enter the hotel. Before you run the simulation in MATLAB, answer some questions.
    simulationlogisticexponential decayfitting
    Potential Scenario
    166

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    57

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    2019-Hu-Treinen-One-step_method_for_modelling_longitudinal_data_with_differential_equations
    This study proposes a new approach to estimate the parameters in differential equation models used to describe non-linear trajectories of longitudinal data.
    simulationparameter estimationshoppingfittingbehaviour
    Article or Presentation
    190

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    57

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    2011-Brian_Winkel-Sourcing_for_parameter_estimation_and_study_of_logistic_differential_equation
    We present two simulation activities for students to generate real data and several data sources for the purpose of estimating parameters in the logistic differential equation model.
    dataparameter estimationparameterlogistic equationsource
    Potential Scenario
    280

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    98

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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
    Potential Scenario
    202

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    73

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    2017-D_Goulet-Modeling, Simulating, and Parameter Fitting of Biochemical Kinetic Experiments
    In many chemical and biological applications, systems of differential equations containing unknown parameters are used to explain empirical observations and experimental data. The differential equations are typically nonlinear.
    optimizationBiochemistrysensitivity analysischromatographymass actioncluster analysisconservation lawsdimerizationestrogen receptor protein
    Modeling Scenario
    373

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    910

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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
    Potential Scenario
    308

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    55

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    0

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    1976-JG-Wagner-Computers in pharmacokinetics
    This is a seminal paper in pharmacokinetics in which the author introduces historic notions and approaches. As can be seen from the abstract there is a variety of material here.
    kineticscomputerparametersPharmacologydrugspharmacokinetics
    Potential Scenario
    135

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    62

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    2016-Barbarossa-Kuttler-Mathematical Modeling of Bacteria Communication in Continuous Cultures
    This paper presents a simple system of delay differential equations (DDEs) for quorum sensing of Pseudomonas putida with one positive feedback plus one (delayed) negative feedback mechanism.
    gene regulatory networkschemostatbifurcationNumerical Simulationquorum sensing
    Modeling Scenario
    459

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    183

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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
    Modeling Scenario
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    501

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    1

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    1-017-DiseaseSpread-ModelingScenario
    Using a grid and m&m candies, we simulate the spread of disease. Students conduct the simulation and collect data to estimate parameters (in several ways) in a differential equation model for the spread of the disease.
    Potential Scenario
    112

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    62

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    2015-Peter_Cumber-Waggling pendulums and visualization in mechanics
    This article describes an equation of motion for a waggling pendulum.
    resonanceinverted pendulummechanicsdamped pendulum
    Modeling Scenario
    568

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    424

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    1-034-T-FishMixing-ModelingScenario
    This activity gives students a chance to build the underlying differential equation and/or difference equation for a mixing problem using tangible objects (fish) and a student-designed restocking and fishing plan in a lake.
    simulationfishFishingmixingrestocking