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    Potential Scenario
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    2010-Kijek-Kijek-Modelling of Innovation Diffusion
    This paper offers a first order differential equation model for innovation diffusion, solves it, and offers qualitative analysis as well as approaches to estimating parameters with some data on final parameters for various countries.
    Bass modelinnovation diffusionLogistic modeldynamic model
    Potential Scenario
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    2015-Erzo-Luttmer-Four Models of Knowledge Diffusion and Growth
    This paper describes how long-run growth emerges in four closely related models that combine individual discovery with some form of social learning.
    knowledge diffusionstationary distributionsproductivity distributionreaction-diffusion equationsquasi-stationary distributions
    Potential Scenario
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    2011-Nancy_Rodrıguez-Applied Partial Differential Equations in Crime Modeling and Biological Aggregation
    In the first part we study a fully-parabolic system of PDEs for residential burglary ‘hotspots’ (spatio-temporal areas of high density of crime). In this work we are concerned with the existence and uniqueness of solutions of this model. In
    biologyDiffusionKeller-Segel modelchemotaxiscrime
    Potential Scenario
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    2004-Mitchell-von Meien-Krieger-Dalsenter-A review of recent developments in modeling of microbial growth kinetics
    Mathematical models are important tools for optimizing the design and operation of solid-state fermentation (SSF) bioreactors. Such models must describe the kinetics of microbial growth.
    Filamentous Fungisolid-state fermentationgrowth kineticsdiffusion-reactionoxygen transfer
    Potential Scenario
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    2014-Rogert_Smith-Mathematical Modeling of Zombies
    Here, we use diffusion to model the zombie population shuffling randomly over a one-dimensional domain.
    kineticsZombiezombificationinteraction times
    Potential Scenario
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    2017-Alex_Honchar-Neural Networks For Solving Differential Equations
    In this post I want to show how I applied simple feed-forward NNs to different differential equations with increasing complexity: ODEs, second order ODEs, and, finally, PDEs.
    neural networksCybenko theoremdiffusion equationfluid dynamics
    Potential Scenario
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    2012-Michael_Kerckhove-From Population Dynamics to Partial Differential Equations
    This article illustrates PDE models for location-dependent carrying capacities, migrations, and the dispersion of a population.
    population dynamicslogistic equationlocation-dependent carrying capacities
    Potential Scenario
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    2010-Singh-Mishra-athematical modeling approach to study growth rate of grassroots technological innovations
    In this paper we have proposed a simple mathematical model by using ordinary differential equation to know the spread rate of technological innovations in rural India.
    logisticexponentialsigmoidtechnological innovationsasymptoticspread of innovation
    Free Online Textbook
    157

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    2016-Langtangen-Pedersen - Scaling of Differential Equations
    Nowadays, the greatest practical benefit of scaling is related to running numerical simulations, since scaling greatly simplifies the choice of values for the input data and makes the simulations results more widely applicable.
    scalingdimensionlesscontinuum mechanics
    Potential Scenario
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    2017-Helen-Byrne-Further Mathematics Biology
    These studies will be in the context of ecological, biological and biochemical applications.
    epidemicschemotaxisenzyme-substrateion channelsnerve pulsesgene proagationtumour
    Potential Scenario
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    2016-Spayd-Puckett- A Three-Fold Approach to the Heat Equation - Data Modeling Numerics
    This article describes our modeling approach to teaching the one-dimensional heat (diffusion) equation in a one-semester undergraduate partial differential equations course.
    separation of variablesexperimentheat equationLab Equipmentcollect data
    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.
    protein quality controlkineticsCellssteady statechemical kineticsfluouresencephotoactivationinytracellular
    General Resource
    201

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    2003-Knorrenschild-Gross-Text Books on Mathematical Modeling in Biology
    Text Books on Mathematical Modeling in Biology Compiled from the Internet by Michael Knorrenschild,
    biologyMathematical Biologytextbooktext
    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.
    spring massLegendre polynomialsintegro-differential equationskinetic theory