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For raw distances, overall removing nodes that have the lowest clustering coefficient has the smallest impact, while removing nodes with the highest strength has the largest.
Middle Isomap embedding after removing nodes with the lowest 21.5 % clustering coefficient, right nodes removed according to the highest 21.5 % betweenness centrality.
By contrast, removing nodes with the highest degree of embeddedness has the largest impact on the cohesion of the connectome, thus supporting that highly embedded regions play important roles in the structural connectome.
Note that removing nodes with the lowest 21.5 % of nodal clustering coefficient (right panel of the top row, Fig. 9) minimally impacts structural connectome's intrinsic geometry, suggesting that clustering coefficient probes a network property that is to a great degree decoupled from properties such as nodal path length or strength.
By recursively removing nodes with degrees less than the k, network layers can be systematically investigated.
We performed in the same manner as edge swapping by removing nodes with criteria of 20%, 40 %, 60, and 80%.
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Therefore, Carrington et al. (2005) conclude that cluster analysis is to form the most connected nodes into one group, and remove nodes with little connection outside the subgroup.
Based on these thresholds, we removed nodes with EDI variation values higher than the thresholds in CitrusNet, and compared the average shortest path length after randomly removing the same number of nodes in CitrusNet.
In Figure 1A, as the sampling fraction decreases statistical weight tends to flow from high degrees to low degrees (we have removed nodes with k = 0 from the degree distribution).
Susceptible node can become removed node with an immune probability δ; infected node can be become removed node with an immune probability μ, too.
Infected nodes are cured with rate β and removed nodes again become susceptible with rate δ for immunization-lost.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com