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    Potential Scenario
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    2008-Lawson-Marion-An Introduction to Mathematical Modelling
    This is a broad based set of notes with sections: Building Models, Studying Models, and Using Models. No depth on any model, no solution strategies, but good references to models, and general approaches that apply in most situations are offered.
    Potential Scenario
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    2014-Blomhøj-EtAl-Compartment models
    An overview of compartment models with many rich illustrations and much attention to various numerical methods in solutions of the resulting differential equations using Matlab. Also included is a section on the limitations of compartment models.
    Potential Scenario
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    2014-Patel-Schlijper-Models of Consumer Behavior
    The problem posed to the Study Group was to construct models for consumer behaviour that might be useful in tools for brand management in markets for fast-moving consumer goods.
    Modeling Scenario
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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.
    Potential Scenario
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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.
    Potential Scenario
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    2015-Heiko_Enderling-Integrating experimental data to calibrate quantitative cancer models
    For quantitative cancer models to be meaningful and interpretable the number of unknown parameters must be kept minimal. We focus on a tumor hierarchy of cancer stem and progenitor non-stem cancer cells.
    Potential Scenario
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    2001-Knisley-Kerley-Using data to motivate the models used in introductory differential equations
    In this paper, the data itself is used to motivate mathematical models in introductory mathematics courses. In doing so, various regression and optimization techniques are illustrated.
    Potential Scenario
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    2011-Nakul-Chitnis-Introduction to Mathematical Epidemiology - Deterministic Compartmental Model
    Deterministic compartmental models form the simplest models in the mathematical study of infectious disease dynamics. They assume that a population is homogenous (all people are the same) and the only distinction is in their disease state.
    Potential Scenario
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    2002-Nelson-Perelson-Mathematical analysis of delay differential equations models of HIV-1 infection
    We develop and analyze a set of models that include intracellular delays, combination antiretroviral therapy, and the dynamics of both infected and uninfected T cells.
    Potential Scenario
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    1981-Nielsen-Rosenfeld-Substantive Interpretations of Differential Equation Models
    The use of differential equations models to study social processes has been increasing rapidly. There are, however, ambiguities in the interpretation of the parameters of these models.
    Potential Scenario
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    2014-Wang-EtAl-Estimating Mixed-Effects Differential Equation Models
    When multiple replicates of measurements are available for the dynamic process, it is of great interest to estimate mixed-effects in the ODE model for the process. We propose a semiparametric method to estimate mixed-effects ODE models.
    Potential Scenario
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    2014-Allen-EtAl-Perturbations in Epidemiological Models -When zombies attack we can survive
    In this paper, we investigate the existence of stability-changing bifurcations in epidemiological models used to study the spread of zombiism through a human population.
    Potential Scenario
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    2004-Denny-Yackel-Temperature Models for Ware Hall
    This paper offers some very nice extended models for cooling off a new office area for a mathematics department.
    Article or Presentation
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    2011-Brian_Winkel-Parameter_Estimates_in_Differential_Equation_Models_for_Population_Growth
    We estimate the parameters present in several differential equation models of population growth, specifically single species exponential and logistic growth, and multiple species competition and predation models.
    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...
    Potential Scenario
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    2000-Armson-Cockroft-Stone-Modelling a barnacle goose population
    This paper explores a number of models for the growth of a barnacle goose population. These geese spend their summers breeding in Spitsbergen and then winter in Caerlaverock on the Solway Firth. The population growth is modelled using exponential...
    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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    2018-Meredith_Greer-Ella_Livesay-Mathematical Epidemiology Goes to College
    In this article we present models that were inspired by two real-life outbreaks at a small residential college campus: H1N1 influenza in 2009 and, surprisingly, mumps in 2016.
    Potential Scenario
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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...
    Modeling Scenario
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    3-013-WhiffleBallFall-ModelingScenario
    We are given data on the time and position of a whiffle ball as it falls to the ground. We attempt to model the falling ball and we confront the different resistance terms and models.