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Great article! we have always promoted the value of our product lines, and for us, when we focus on the perceived benefits of our branding strategy, whatever pricing model we choose just seems to "make sense" for our prospective clients.
For example, in linear plateau model, we choose two representative points (0,b) and (c,d), where (0,b) is the a point on the Y axis, and (c,d) is the point of highest yield, so that Xm=c, Ym=d, β0=b, β1= d-b /c.
However, for this model we choose the lags with the highest correlation values.
For the abstract mobility model, we choose the Poisson distribution [19] to describe the statistical distribution of the nodes.
Among all the versions of the model, we choose the version of the model in column (5) as the most appropriate.
Moreover, in Section 5 we stated that "in our proposed model we choose 16-bits word length to be the typical word length".
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For the simple model simulation we choose α i =1, β i =0 and ϕ0=1.
With all the problems nonequity clubs are facing, he said, "The model we chose is resonating more than ever".
As our model comprised quadratic terms instead of a simple linear model, we chose a D-optimal design in order to minimize the experiment number.
As a cell model, we chose epithelial ovarian cancer, an aggressive disease typically diagnosed at an advanced stage when chemoresistance occurs.
Based on our previous experience with this model, we chose a time point – 4 hours – at which mice with parenchymal TLR4 expression were starting to develop manifestations of SIRS but before animals showed signs of multiorgan failure.
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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