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Many models involve more than one unknown.
Parameter identification is an important issue in computational biology since most of the models involve more parameters than the available data.
We propose that robust polymerase dimerization is necessary to ensure efficient and correct circularisation of progeny RNP, and this is consistent with some observations concerning replication by influenza polymerase (Jorba et al., 2008; York et al., 2013), but other influenza replication models involve more complicated higher order polymerization (Chang et al., 2015; Jorba et al., 2009).
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The results show that the curved beam element models, involving more degrees of freedom and coupling of translational and torsional motion, are more accurate at simulating the static and dynamic characters of an iced quad-conductor bundle.
We refer to [2, 8, 9] for details on physical models involving more general reaction-diffusion equations.
It may be noted that the other models involving more variables also give reasonable sensitivity (around 89%), specificity (around 95%), positive predictive value (around 95%) and negative predictive value (around 89%).
So, prediction using a single history matched model involves more risk because of the parameter uncertainty.
Over the years, according to Schultz, Cota has developed a deeper model, involving more fields, and has followed patients for a longer amount of time.
Of course, if a model involves more unknown functions, it is difficult to obtain the asymptotic behavior of traveling wave solutions by the inequalities similar to (3.6) and (3.7).
The flipped classroom model involves more than shifting content delivery outside of class time [ 6].
However, in our experience, fitting becomes difficult for any model involving more than two or three parameters.
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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