Sentence examples for centrality was found from inspiring English sources

No relationship with any node centrality was found (Table  3).

Of the measurements of network importance we calculated, closeness centrality was found to have a significant negative correlation with rates of non-synonymous substitution and with ω values as a result of a significant correlation with d N (ρ=−0.4766, p=0.004) and no relation with d S.

Nodes from the orange subgroup, having slightly elevated eigenvector centrality and slightly reduced leverage centrality were found largely in the region of the precuneus and posterior cingulate.

However, two other aspects of pathway centrality are found to be less important in multicellular eukarya: the degree centrality (fraction of the network a pathway is connected to), and the closeness centrality (inverse of the distance between a pathway and all other pathways).

The highest values of all centralities is found in correspondence to public research institutions, like universities and specific research centres.

Comparing the rankings by betweenness centrality and closeness centrality, it was found that Quarry Bay Station and Yau Tong Station (two interchanges between two rail lines) have much lower rankings using closeness centrality.

Eigenvector centrality (binary) was found to be the most influential metric in the model with the lowest mean squared error in predicting information processing speed (P = 0.01, R = 0.64), with its regression coefficient lying >2 SD above that of the next highest metric in the optimized selection (Fig. 5).

Notably, the network betweenness centrality of these high-degree nodes was found to be significantly higher than that of nonhigh-degree nodes (P < 0.001, 10 000 permutations), suggesting a central position of these nodes in the overall network topology.

Finally, prior performance was found to influence not only students' performance, but also students' centrality within the social networks (r = 0.14, S.E. = 0.04, p < 0.001).

Comparing five disruption strategies (e.g., random, human capital, degree centrality, betweenness centrality, and human capital and degree centrality) and three recovery mechanisms (e.g., random, preference by social distance or degree centrality), networks were found to exhibit greater density, and thus more resiliency, after attacks targeting those with the most human capital.

Furthermore, calculation on degree and betweenness centrality of all actors in both networks was performed, and the result of the top-15 actors with the highest centrality can be found in Fig. 4.