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Results obtained with this dataset support our theory.
This fact limits the scope of analysis possible with this dataset.
With this dataset, a program was developed to automatically map whether detected acetyls were within known protein domains.
Regarding the identification of no-variation genes, MedianCD and SVCD normalization also worked correctly with this dataset.
The finally proposed extended model compares reasonably well with this dataset.
With this dataset we can estimate the UVB photoionisation rate independently for several redshift bins.
Given the similarity, I draw some comparisons with this dataset below.
The success with these strategies would have been quite considerable with this dataset.
As we will show later, our implementation has achieved even better results with this dataset.
Ask yourself the question: are my conclusions easy to understand for someone who didn't go through the same analysis and research process with this dataset?
The initial fact observed with this dataset is that 271 students (33.42%) dropout right after the first year or later.
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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