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Can you explain this?
We can conclude that the ℳ O W and ℳ O E P distributions are excellent alternatives to explain this data set.
Can you explain it?
Can you explain that?
Can you explain why?
However, two non-exclusive theories can explain this data.
Thus, multiple-spacer events in this data set can be well explained by proximal deletions.
This result can be explained by the different quality of data measurements for this data set.
Second, cPBs can reach networks with lower BIC, meaning optimized network structures explain the data set better.
Anthony Kreis, the lead researcher who analyzed the data, explained that the data set included the 127 state high court cases involving LGBT claims from 2003 through 2015.
I then explain how these data sets have been merged in order to study particular linkages.
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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