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First, we generated such a Map for a single atom: type Formula = Map[Isotope,Int].
First, we generated for each case i the effective earliest date ( B^{prime }_{i} ).
First, we generated highly porous 3D silk scaffolds that were biocompatible and amenable to bone morphogenetic protein 2 functionalization.
First, we generated an initial list of codes with two researchers collaborating to code all interview data.
First, we generated an 87Sr/86Sr map by classifying 87Sr/86Sr values into five geologically-representative isotope groups using cluster analysis.
First, we generated a HEK293S stable cell line expressing the receptor constitutively at a level of 60 pmol/mg of crude membrane protein.
First we generated random subsamples by eliminating 1000 random vectors at a time to create a series of subsets with N = 1000 100,000.
First, we generated all stereoisomers of a complex molecule which has so many stereogenic elements that expectation of second block collisions is high.
First, we generated three prediction models using the training set, one using the linear regression method, one using the RPART method, and one using the NNR method.
First, we generated a novel strain of Anp32a−/− mice (Figure 4).
First we generated 20,000 replicates of the original data set, sampling subjects with replacement.
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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