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After that, we select the most nodes of area (N imax ) to decrease in every cycle.
The small-world phenomenon states that most nodes of a network are reachable from any other node in a small number of steps and explains information efficiency in social networks.
A few interesting observations arise from Figure 3. First, even our smallest panels of AIMs (P1) achieve very high accuracy at most nodes of our decision tree.
As shown, most nodes of basal sauropodomorphs have Bremer support values of 1 or 2, and only a few nodes have frequency values above 50% in the bootstrap and jackknife analyses (see Appendix S1).
However, evolutionary reconstructions based on tRNA sequence similarity are unable to support this hypothesis, because of the low resolution of most nodes of the tree (data not shown).
In any case, however, we observed that most nodes of our TRNs exhibit a low connectivity, while very few nodes show a very high degree.
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As exemplified in Figure 4, GHR performs better than CYB for most nodes, irrespective of the age of the node.
Below the critical temperature the degree of connectivity of most nodes lies around 10% of the highest possible degree while at higher temperatures it is around 50% of the highest possible degree.
The high bootstrap values of most nodes indicate the robustness of the tree computed.
This missing data – infection states of most nodes and the infection times of the observed infected nodes – poses a challenge to the study of real-world epidemics/cascades.
It can be known from Fig. 5 that the distribution of most nodes is similar to those of C p and C r except several nodes.
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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