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    Potential Scenario
    91

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    1977-HI_Freedman-P_Whitman-Mathematical models of population interactions with dispersal
    A system of differential equations is proposed as a model of dispersion between two populations in habitats separated by a barrier.
    predatorbarriertwo populationstwo habitats
    Potential Scenario
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    25

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    2008-Jai-Li-Differential equations models for interacting wild and transgenic mosquito populations
    We formulate and study continuous-time models, based on systems of ordinary differential equations, for interacting wild and transgenic mosquito populations.
    Mosquito borne diseasespopulationsHolling-II-type mating ratestransgenic mosquitoesnonhyperbolic equilibriummosquitoes
    Potential Scenario
    172

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    38

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    2010-Shaza_Hussein-Predator-Prey Modeling
    The objective of this project was to create five projections of animal populations based on a simple predator-prey model and explore the trends visible.
    population dynamicspredator-preylogistic equationEndangered Catsdecreasing populationrabbitsfoxes
    Potential Scenario
    149

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    35

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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.
    population modelReproductionspline approximationsBombus terrestrisneonicotinoidsbumble bee
    Potential Scenario
    188

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    34

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    2009-Schaffer-Bronnikova-Controlling malaria
    The present paper reviews potential control strategies from the viewpoint of mathematical epidemiology.
    epidemiologymalariabifurcationmosquitotransgenic mosquitoes
    Potential Scenario
    104

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    73

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    2018-Banerjee-EtAl-Prey-Predator Model with a Nonlocal Bistable Dynamics of Prey
    The primary goal of our present work is to consider nonlocal consumption of resources in a spatiotemporal prey-predator model with bistable reaction kinetics for prey growth in the absence of predators.
    predator-preynonlocal consumptionTuring bifurcationspatial Hopf bifurcationspatio-temporal patternprey growth
    Potential Scenario
    116

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    38

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    2013-Michael-Evans-Growth and Decay
    Sometimes, we can describe processes of growth and decay—whether physical, chemical, biological or sociological—by mathematical models.
    exponential growthexponential decayisotopespopulationsresource depletion
    Potential Scenario
    158

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    39

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    2013-Gonzalez_Parra-Arenas-Mathematical Model for Social Security Systems with Dynamical Systems
    In this paper it is proposed a mathematical approach based on dynamic systems to study the effect of the increase in the Social Security normal retirement age on the worker and on the dynamics of retiree populations.
    dynamical systemsretirement modelSocial Security
    Potential Scenario
    194

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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).
    Immunologytumorhopf bifrucation
    Free Online Textbook
    108

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    37

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    2014-Andre_De Ross-Modeling Population Dynamics
    This course is intended as an introduction to the formulation, analysis and application of mathematical models that describe the dynamics of biological populations.
    predator-preycompetitionpopulationgrowthbifrucationtext
    Potential Scenario
    120

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    37

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    2014-Chivers-EtAl-Predator-prey systems depend on a prey refuge
    We present an agent-based model which does not require the factors or constraints of previous models to reproduce all six patterns in persistent populations.
    Individual & Agent Based Modelingpredator-preythink-pair-shareslynxrefugeprey switchingMustela-Clethrionomys systempatter oriented
    Potential Scenario
    102

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    27

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    1998-K_H_Louie_Clark-P_C_D_Newton-Analysis of differential equation models in biology-clover meristem populations
    A simple differential equation model (dynamical system) for clover, based on meristem numbers, is outlined and analysed mathematically.
    sensitivity analysisstability analysissteady statesgrowing pointsbudsmeristems
    Modeling Scenario
    218

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    102

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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
    306

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    205

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    6-040-StruggleForExistence-ModelingScenario
    We use historical data from the 1930's in the Soviet Union and model competition between two species of yeast after modeling each species separately and estimate parameters
    competitionlogisticcarrying capacityparamecium
    Potential Scenario
    203

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    39

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    2006-Juska-Gedminiene-Ivanec-Growth of Microbial Populations-Mathematical Modeling-Laboratory Exercises-Model-Based Data Analysis
    The aim is to teach the students to use a fresh approach to the problems they are familiar with, to come up with an articulate verbal model after a mental effort, to express it in rigorous mathematical terms, to solve (with the aid of computers).
    population growth ratelogistic equationVerhulst equationgeneration timelag time
    Potential Scenario
    128

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    35

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    2007-Hui_Luo-Population Modeling by Differential Equations
    A general model for the population of Tibetan antelope is constructed. The present model shows that the given data is reasonably logistic.
    population dynamicsextinctionlogisticTibetan antelope
    Modeling Scenario
    322

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    124

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    1-039-StochasticPopModels-ModelingScenario
    We develop strategies for creating a population model using some simple probabilistic assumptions. These assumptions lead to a system of differential equations for the probability that a system is in state (or population size) n at time t.
    Probabilitypopulation dynamicsVarianceMeanstochasticdeterministic
    Modeling Scenario
    167

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    106

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    1-109-EmployeeAttrition-ModelingScenario
    This scenario models the loss of employees and the employer's attempt to retain them through stock options. It most naturally is solved with a first-order linear decay model with two populations.
    populationlinear growthdecayemployeeattrition
    Potential Scenario
    113

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    34

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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.
    predator-preyhost-parasitebifurcationage structrematuration delay
    Potential Scenario
    176

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    65

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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.
    fishpredator-preylogisticpopulationdelaylag