Anomalous diffusion means that the outcome of diffusion measurements essentially depends on the time scale probed.
Several earlier studies simulate the impact of geometry on the outcome of diffusion measurements.
Cowen (2011) has in turn approached stagnation as an outcome of the exhaustion of a significant set of "low-hanging fruits" reaped in recent history, namely one-off supply-side opportunities associated with post-war reconstruction; trade opening; diffusion of new technologies in power, transport, and communications; and educational attainments, among others.
As a consequence, vast resources are devoted to the task of predicting the outcomes of diffusion processes, but the quality of such predictions is often poor.
The results suggest that increasingly complex contact situations will continue to expand the possible outcomes of diffusion.
While this cline suggested that agriculture spread across Europe in a SE-NW fashion, the archaeological data alone cannot detect whether this is the outcome of a demic diffusion, cultural diffusion, or a palimpsest of complex demographic and historical processes.
Specifically, Colbaugh and Glass describe an ongoing effort to predict the outcomes of social diffusion processes using a dynamic network approach.
Outcomes of a meta-analysis of diffusion tensor imaging studies regarding the association between white matter integrity and auditory verbal hallucinations are highlighted.
We begin by introducing a biologically-inspired S-HDS model for social dynamics on multi-scale networks, and then perform stochastic reachability analysis with this model to show that the outcomes of social diffusion processes may depend crucially upon the way the early dynamics of the process interacts with the underlying network's meso-scale topological structures.
We then perform formal stochastic reachability analysis with this S-HDS model and conclude that the outcomes of social diffusion processes may depend crucially upon the way the early dynamics of the process interacts with the underlying network's community structure and core-periphery structure.
With the S-HDS model in hand, we then perform formal stochastic reachability analysis and conclude that the outcomes of social diffusion processes may depend crucially upon the way the early dynamics of the process propagates with respect to the underlying network's 1).
