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    Potential Scenario
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    2014-Niemann-Miklos-Simple Method for Estimation of Parameters in First Order Systems
    A simple method for estimation of parameters in first order systems with time delays is presented in this paper.
    Potential Scenario
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    2012-Jambhekar-Breen-Extravascular Routes Of Drug Administration in Basic Pharamacokinetics
    This provides an excellent step-by-step of the physiology, construction of model, and notions like peak concentration as well as issues like lag time.
    Potential Scenario
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    1967-Israelsson- Johnsson-Circumnutations In Helianthus Annuus
    A theory is given for circumnutations in plants, especially hypocotyls of Helianthus annuus, which were used as experimental material.
    Potential Scenario
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    1986-Istvan_Gyori-Connections between compartment systems pipes and integro-differential equations
    In this paper we give the mathematical description of models in which the mass transport between compartments requires a given definite time or transit times are distributed according to given probability distribution functions.
    Potential Scenario
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    2017-Zhang-Wang-Study on public opinion propagation in self media age based on time delay differential model
    We establish the Logistic equation, introduce the operator time delay differential equation, and finally establish the improved delay differential equation, which can describe the propagation trend of network news from the self media.
    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...
    Modeling Scenario
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    6-010-SocialCampaign-ModelingScenario
    The epidemic modeling problem is formulated as a system of three nonlinear, first order differential equations in which three compartments (S, I, and R) of the population are linked.
    Potential Scenario
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    2011-Radouane_Yafia-A Study of Differential Equations Modeling Malignant Tumor Cells in Competition with Immune System
    In this paper, we present a competition model of malignant tumor growth that includes the immune system response. The model considers two populations: immune system (effector cells) and population of tumor (tumor cells).
    Potential Scenario
    130

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    2006-Shigui_Ruan-Delay differential equations in single species dynamics
    In this survey, we shall review various delay differential equations models arising from studying single species dynamics.
    Potential Scenario
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    2003-Yildirim-Mackey-Feedback Regulation in the Lactose Operon
    A mathematical model for the regulation of induction in the lac operon in Escherichia coli is presented.
    Potential Scenario
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    2016-Banks-EtAl-Modeling Bumble Bee Population Dynamics with Delay Differential Equations
    To provide a tool for projecting and testing sensitivity of growth of populations under contrasting and combined pressures, we propose a delay differential equation model that describes multi-colony bumble bee population dynamics.
    Potential Scenario
    165

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    1984-W_Brunner-D__Focht-Deterministic Three-Half-Order Kinetic Model for Microbial Degradation
    The kinetics of mineralization of carbonaceous substrates has been explained by a deterministic model which is applicable to either growth or nongrowth conditions in soil.
    Potential Scenario
    158

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    2006-Cooke-Elderkin-Huang-Predator-Prey interactions with delays due to juvenile maturation
    This paper focuses on predator-prey models with juvenile/mature class structure for each of the predator and prey populations in turn, further classified by whether juvenile or mature individuals are active with respect to the predation process.
    Potential Scenario
    252

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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.