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Whenever simulations are performed, choices must be made when modeling true events.
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Typically, various unrealistic assumptions are made when modelling trains within networks in order to facilitate their analyses.
It seems that the basic understanding on modelling polymer properties is quite substantial, but there is still significant contributions to be made when modelling the morphology evolution of these complex polymer particles.
We discuss and motivate the specific modelling choices made when building the model and investigate how the model details influence the predicted dynamics.
A fundamental hypothesis that is made, when these models are used for the above application, is that the first IMF contains a specific part of the noise as derived from the above models.
Exclusions of covariates were only made when the models that included those variables failed to converge.
Different assumptions are made when exposure is modeled categorically vs. continuously, making direct comparisons of results difficult.
In the next paper in this series, we will discuss the statistical assumptions made when using statistical models, and provide advice on choosing the appropriate model and covariates therein.
This chapter provides examples of typical dynamic biogeochemical models and discusses the considerations that have to be made when selecting the model complexity and equations.
Therefore, in case of concentrated systems, as often encountered in extraction and distillation processes, errors are made when the film model is used instead of the more appropriate penetration model.
A major decision has to be made when deriving a model of color.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com