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The mean degree of the entire network is equal to.
We choose mean degree as the independent parameter instead of the correlation threshold because, unlike the latter, the mean degree is a network property.
We generate networks with mean degree in the range 24 ≤ 〈k〉 ≤ 39.
We find that the lethal cluster has the largest mean degree.
We have shown in Figs 3, 5 and 6 network properties as a function of mean degree in increments of Δ〈k〉 = 1, for 16 different values of mean degree.
Properties related to bone strength include rate of bone turnover, bone mineral density, geometry, microarchitecture, and mean degree of mineralization.
Based on this sampling distribution, estimators for the mean degree, the degree correlation, and the clustering coefficient are proposed.
We first generate a coarse-grained network whose node is regarded as community, using the Barabási-Albert (BA) model56 having NC = 100 nodes and mean degree six.
Figure 3 shows the average Shannon entropy of the degree distributions as a function of mean degree, considering networks from all subjects, before and after Ayahuasca intake.
A fair comparison of the "before" and "after" networks is possible by considering the entropy of networks of identical mean degree.
Since the quantity 2lnN never exceeds 10, our maximum threshold condition (minimum mean degree) was determined by the requirement for obtaining fully connected graphs.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com