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    Technique Narrative
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    2-001-NumericalMethodsComparisons-TechniqueNarrative
    This material teaches the basics of numerical methods for first order differential equations by following graphical and numerical approaches. We discuss the order of accuracy of the methods and compare their CPU times.
    Free Online Textbook
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    2015-Eric_Sullivan-Numerical Methods_An_Inquiry-Based_Approach_with_Python
    This is an OER effort on the part of Eric Sullivan to explore the joy of numerical methods. He has provided several versions.
    Free Online Textbook
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    2015-Dan_Sloughte-Notes on Diffy Qs Differential Equations for Engineers
    This is a calculus book with the last chapter devoted to ordinary differential equations topics. The effort begins with a study of numerical methods and goes through traditional technique strategies.
    Potential Scenario
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    2018-Robert_Phair-Differential_equation_methods_for_simulation_of_GFP_kinetics_in_non–steady_state_experiments
    Here, we derive new tracer kinetic analytical methods for non–steady state biological systems by constructing mechanistic nonlinear differential equation models of the underlying cell biological processes.
    Potential Scenario
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    2011-Carl_Leinbach-Beyond Newton's law of cooling - estimation of time since death
    The paper offers an excellent history of temperature-based methods and then proceeds to demonstrate these with some data. Here the history is rich and will support student investigation as well as faculty development.
    Potential Scenario
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    2005-Albert_Tarantola-Inverse Problem Theory and Methods for Model Parameter Estimation
    This is a bible of approaches to support parameter estimation approaches in inverse problems. Theory and algorithms are offers with examples.
    Potential Scenario
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    2017-GR_Gustafson-Differential Equations Course Materials
    There are many applications from compartment and cascade analysis, recycling brine tank, home heating with multiple rooms, chemostat, microbes, heartbeats, lidocaine, nutrient flow in an aquarium, biomass transfer, pesticides, forecasting prices,...
    Potential Scenario
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    2013-Fathalla_Rihan-Delay Differential Equations in Biosciences - Parameter estimation and sensitivity analysis
    This is a review article to show that delay differential models have a richer mathematical framework (compared with models without memory or after-effects) and a better consistency with biological phenomena such dynamical diseases and cell growth...
    Free Online Textbook
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    2009-Eriksson- Estep-Hansho-Johnson-Computational Differential Equations
    Differential Equations and Advanced Computational Differential Equations, presents a unified approach to computational mathematical modeling using differential equations based on a principle of a fusion of mathematics and computation.
    Potential Scenario
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    2007-Bellomo-De_Angelis-Delitala-Lecture Notes on Mathematical Modelling in Applied Sciences
    The Lectures Notes correspond to the first part of the course devoted to modelling issues to show how the application of models to describe real world phenomena generates mathematical problems to be solved by appropriate mathematical methods.
    Potential Scenario
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    2017-Justin_Krueger-Parameter Estimation Methods for Ordinary Differential Equation Models with Applications to Microbiology
    We demonstrate the feasibility of principal differential analysis using simulation studies and then apply the method to intestinal and vaginal microbiota data.
    Potential Scenario
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    1999-Khorasheh-Ahmadi-Gerayeli-Application of Direct Search Optimization for Pharmacokinetic Parameter Estimation
    For simple pharmacokinetic compartmental models, analytical solution to the governing differential equations provide a mean to evaluate the associated rate constants. Such methods, however, can not be used used for more complex multi-compartment...
    Potential Scenario
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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.
    Potential Scenario
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    2015-Dios-EtAl-How Engineers deal with Mathematics solving Differential Equations
    The students of fourth course, of the bachelor’s degree in Computer Sciences or Industrial Engineering at the University of Salamanca (Spain), they learn mathematics solving real problems with the help of the acquired interdisciplinary knowledge.
    Potential Scenario
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    2015-Cano-EtAl-Bringing partial differential equations to life for students
    This work describes how to use an authoring tool, Easy Java Simulations, to build interactive simulations using FreeFem++ (Hecht F 2012 J. Numer. Math. 20 251) as a PDE solver engine.
    Potential Scenario
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    2005-P_Howard-Modeling with ODE
    In these notes we consider three critical aspects in the theory of ordinary differential equations: developing models of physical phenomena, mathematically well-posed, solving ODE numerically .
    Modeling Scenario
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    6-024-DronePackageDelivery-ModelingScenario
    Students will derive a system of first order differential equations which describe the flight path of a drone delivering a package.
    Article or Presentation
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    SIMIODE Spring 2024 Webinars - WikiModel
    WikiModel is cloud-based application and requires no installation and is run via a web-browser to facilitate rapid implementation. Equations are typed in as they appear in a textbook. ODEs are automatically integrated via Runge-Kutta methods.
    Potential Scenario
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    2018-Akman-EtAl-Parameter Estimation in Ordinary Differential Equations Modeling via Particle Swarm Optimization
    We demonstrate Particle Swarm Optimization efficacy by showing that it outstrips evolutionary computing methods previously used to analyze an epidemic model.
    Potential Scenario
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    1999-T_Chen-HL_He-GM_Church-S_Shafer-Modeling Gene Expression with Differential Equations
    The paper proposes and give great detail for a differential equation model for gene expression with two methods for constructing the model from a set of temporal data.