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    Potential Scenario
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    2019-Stender_EtAl-Recovery_Of_Differential_Equations_From_Impulse_Response
    In this work, a recent method, which allows reconstructing differential equations from time series data, is extended for higher degrees of automation.
    Free Online Textbook
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    2012-Brian_Ingalls-Mathematical_Modelling_in_Systems_Biology
    This text provides an introduction to dynamic mathematical modeling of cellular processes. The emphasis is on using computational tools to investigate models of cellular phenomena.
    Modeling Scenario
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    1-096-OP-AMP-Differentiator-ModelingScenario
    The output waveform (function) of a operational amplifier type of differentiator circuit is determined analytically from the first order governing ordinary differential equation and compared with the data acquired from numerical model (using...
    Free Online Textbook
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    Potential Scenario
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    2009-Shamim-EtAl-Investigating viscous damping using a webcam
    We describe an experiment involving a mass oscillating in a viscous fluid and analyze overdamped, critically damped and underdamped regimes of harmonic motion.
    Potential Scenario
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    1992-Jude_Sommerfeld-More Applied Math Problems on Vessel Draining
    From a chemical engineering point of view emptying processing and storage tanks is important and this article considers many issues and shapes of containers. The main interest is in the total time it takes to empty the tank for a collection of...
    Potential Scenario
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    1977-Michael_Mackey-Leon_Glass-Oscillation and Chaos in Physiological Control Systems
    First-order nonlinear differential-delay equations describing physiological control systems are studied. The equations display a broad diversity of dynamical behavior including limit cycle oscillation.
    Modeling Scenario
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    3-067-RLCSeriesCircuit-ModelingScenario
    In this validation-oriented setup, the second order linear ordinary differential governing equation of a small signal RLC series AC circuit is solved analytically, and the results are compared with the data acquired from analyzing the numerical...
    Potential Scenario
    146

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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.
    Technique Narrative
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    9-001-SkinBurnModelNumericalMethods-TechniqueNarrative
    The heat equation is an important partial differential equation (PDE) which describes the distribution of heat in a given region over time. Numerical methods play an important role in solving these.