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We first present the models and their fits to various data sets (simulated data points are reported at 100 ms intervals to match the FSCV recordings) and subsequently discuss the parameter values.
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We will begin by discussing the parameter values that were selected before presenting some general results that show that the coupled channels model has an oscillatory regime that is very robust and exists for a wide range of parameters.
Note that, as discussed below, the parameter values found for ATPases in C4 should be considered phenomenological only and suggest a tight functional coupling between some ATPases and endogenous PK in permeabilized rat cardiomyocytes.
We analyze default and user-defined parameters, provide guidance on setting parameter values, and discuss the parameter effect on the extraction results.
4, we will discuss the parameter assignment.
In this article, we discuss the significance of the parameter values, compare our correlation to others found in the literature for different classes of fuels, and contrast the above expression's performance with correlations obtained using leading FAME kinetic models in 4%O2/Ar mixtures.
In the following we discuss the literature on the parameter values in detail.
Ades and Jordan met briefly last week to discuss the parameters of a negotiation.
Numerical results were obtained using the parameter values as discussed above.
We first describe the two kinds of models and how we learn the parameter values from data, then discuss our way to combine the two lists of predicted edges into a final list of predictions.
Relations of the parameter values to the filler type and concentration are discussed.
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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