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By comparing proteomes and conducting simulations, we demonstrated that the difference in assortativity can well be explained by assuming that the duplicability of proteins is dependent on its degree and the dependency is different among species.
Such distributions are always relevant when outcomes depend on continuously distributed random variables and the dependency is defined by a piecewise continuous function.
The neighboring cliques overlap by 50%, so the dependency is well propagated.
The dependency is shown to be well approximated by a simple analytical formula derived from a reduced-order model.
Absence of the dependency is explained by the different factors governing double layer formation, main of which is presence of the oxygen-content groups and specific porous structure.
In particular, saturation of the dependency is observed already at a field 0.2 T while corresponding changes in magnetization curve require much wider field range.
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Morocco is highly dependent on imports of energy sources; in 2015, the dependency was about 94.5%.
This complexity measure counts the (maximum) number of attributes to be handled in the stub if the dependency were broken.
This complexity measure counts the number of operations to be emulated in the stub if the dependency were broken.
This was different in Test 5, where the relative position of the dependency was tested.
One popular method of modeling the dependencies is the copula approach.
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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