Exact(6)
To measure how dynamical are the strategies of users in a tie we consider (a_{i}), the number of ties created by user i in period Ω.
We demonstrate how dynamical models can be used to examine how distinct withdrawal-related processes are related over time and how treatment influences these relations.
In this paper it is shown, how dynamical properties of the rubber phase localized on the filler particles will contribute in a special way to the reinforcement and the viscoelastic properties of the elastomers.
In a second part, we bridge the gap between the description of bursts in the framework of percolation and the temporal description of neural networks activity by showing how dynamical simulations of bursts with an adaptive exponential integrate-and-fire model lead to a mean description of bursts activation which is captured by Quorum Percolation.
To characterize how dynamical are the strategies of both i and j we consider the geometrical mean a_{ij}=sqrt{frac{a_{i}}{k_{i}}cdot frac{a_{j}}{k_{j}}}. (3) If both i and j are explorers, (a_{ij} simeq 1) and the tie is more likely to decay since it connects users with highly dynamical social strategies, while if they are both keepers, (a_{ij} simeq 0) and the tie most likely will persist.
Investigating how dynamical activities arise from complex network topology is of fundamental importance to understanding the functions of real-world systems [ 1, 16, 17].
Similar(53)
As this paper supports, statistical analysis accomplished in both libraries can potentially guide us to identify: 1) robust dynamical properties inherent to the biological systems, 2) scrutinize how dynamic properties depend on specific kinetic parameters, and 3) potentially associate dynamical with functional behavior in cell.
It is very difficult to account for how the dynamical nature of the ground state of the Michaelis complex modulates function by transition state concepts since dynamical disorder is not a starting feature of the theory.
We have presented how various dynamical models predict different behavior of modelled communities characterized by the same structure and complexity.
The results show how N dynamical systems oscillating in a limit cycle and receiving impulsive inputs can be represented with N phase variables.
As an interesting example to illustrate the theory, we show how the dynamical quantum SU 2) group, as studied by Etingof Varchenko and Koelink Rosengren, fits into this framework.
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