This is evident in the right panel of Fig. 1 which shows degree power (top) and degree correlation (bottom) for the first time derivative (secular variation) of the core field.
Parameters like average clustering coefficient, topological coefficient, average degree, power law distribution of degrees and betweenness centrality have been assessed to capture the topology of the networks.
Nonetheless, the first-degree power-law polynomial function describes only one of many hydrodynamics-based functional forms of activity metabolism.
The first-degree power-law polynomial function is frequently used to describe activity metabolism for steady swimming animals.
Consequently, the first-degree power-law polynomial function yields incorrect parameter values of energetic costs if activity metabolism is governed by the power-law polynomial function of any degree greater than one.
In particular, the first-degree power-law polynomial function is frequently used to describe activity metabolism for steady swimming animals to evaluate important parameters of energetic costs, such as the standard metabolic rate and the drag power indices [5], [8] [10].
For over 30 years, the first-degree power-law polynomial function (equation 1) has been used to describe f (U) for steady swimming animals, especially for fish [5], [8] [10], [15], [19], [24], [25], [31] [33].
The co-existence of scale-freeness, indicated by the degree power-law relationships, and modularity, indicated by high clustering coefficients deserves particular attention, since folk knowledge typically equates "scale-free" with "random", and "modular" with "structural".
They would also have recourse to different classes of shares with different degrees of power.
