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To estimate the stability of the RPGs, we traced all RPGs in every year and checked for membership variation.
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Social group membership explained significant variation in gut microbial composition (PERMANOVA: r = 0.186, p < 10−4) as well as gut microbial enzyme ortholog composition (r = 0.108, p = 0.003).
Results suggested that CPs exhibit considerable variation in membership criteria, unclear decision-making procedures, and have uncertain representative structures.
One can assess the stability of clusters by tracking the variation of membership values as m and cluster number are increased.
Clustering coefficient was also calculated for individuals for each winter; this metric requires extensive observations of group membership to show interindividual variation and could not be reliably calculated for within-season sampling periods.
Our results are the first report of a neural signature for group membership based on phonetic variations of the same language.
We also observed that the distance between populations (based on their cluster memberships) is strongly positively correlated with F st between populations, which suggests that the inferred cluster memberships capture the genetic variation present in the data well.
A method to design a fuzzy controller is proposed by taking the variation ranges of membership functions within sampling intervals into consideration.
Year alone predicts 88% of the variation in union membership from election to election – meaning that there's a powerful relationship between years gone by and the decline of labor as a percentage of the electorate.
Besides directly comparing membership overlap, we study the variation of the metrics defined in Section 3.3.2 with the group size.
While the relationships are highly significant, we find that epigenetic variables and binding data explain only 8.3% of the variation in module membership and 4.3% of the variation of (Table 2).
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