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We will review the theory of $A_\infty $-algebras, their minimal models and differential graded realizations.
Dynamic neural networks (DNNs) have important properties that make them convenient to be used together with nonlinear control approaches based on state space models and differential geometry, such as feedback linearisation.
Stochastic process algebras, stochastic Petri nets, continuous Petri nets, rule-based models and differential equations, would all be ideal candidates for this purpose.
Although some formalisms like Petri nets, constraint-based models and differential equations have been applied for all these networks, no single formalism covers the whole spectrum of functionalities reviewed in this work.
Given that initial brain influx would be expected to be the same in both mouse models, and differential retention of 18F-7B in transgenic mice could result from its binding to Aβ plaques and clearance of the unbound tracer as a function of time, we therefore used dynamic PET imaging over 1 to 75 min to interrogate regional localization of 18F-7B withen the brains of transgenic and WT mice.
Neutral models and differential responses of species to environmental heterogeneity offer complementary explanations of species abundance distribution and dynamics.
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A comprehensive theoretical model of the membrane reactor was constructed using Maxwell Stefan equations, the dusty gas model and differential energy balances.
This is a "unified" model in two important ways: (i) It combines inter-host and in-host dynamics into a single model, and (ii) it links two very different modeling approaches - agent-based modeling and differential equations - into a single model.
Reducing the number of features prior to statistical analyses will result in more accurate multivariate modeling and differential feature selection, as well as decreased reporting of unknowns that often constitute the largest proportion of human metabolomics data.
Rasch Model and differential item functioning assessed scale properties.
The linear model and differential expression functions were applied to all microarray data sets.
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