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Then there are at most (c(G -1) vertices of G -1t covertices its maximum matching.
Then, there are at most (c G-G_{1})-1+1=c G-G_{ vertices of G not covered by its maximum matching.
Since (B l,x,k)) ((xgeq2)) has a path as its spanning subgraph, there is at most (1=c(G -1) vertex not covered by its maximum matchinG -1
Similar(55)
Scale maxratio by its maximum value.
The acceleration waveforms are normalized by its maximum amplitude.
Each of the records is normalized by its maximum value.
Each trace is normalized by its maximum amplitude.
In the plot, is normalized by its maximum.
Each recording is normalized by its maximum value (gain normalization).
From the output alignments, the best alignments among multi-mapped reads were chosen by following criteria in order: maximum matched bases, minimum mismatch, minimum number of gaps in query of alignment, minimum number of gaps in target of alignment, minimum number of gapped bases in query of alignment and minimum number of gapped bases in target of alignment (preferred first).
By the induction assumption there are at most (c(G_{2} -1) vertices not covered by a maximum matching of (G_{2}).
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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