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In a finite-size system, is it reasonable/possible to perform a robust statistical assessment of power law statistics?
We then provide evidence that a two dimensional model is already adequate for describing power law statistics of avalanches and fractal character of dislocation patterning.
Power law statistics have been observed in early development at a time when networks are thought to be purely excitatory [32, 59].
Steady plastic flows have been compared to developed turbulence because the two phenomena share the inherent complexity of particle trajectories, the scale free spatial patterns and the power law statistics of fluctuations.
A number of in vitro and in vivo studies [1 4] have shown neuronal avalanches cascades of neuronal firing that may exhibit power law statistics in the relationship between avalanche size and occurrence.
Assuming that the whole brain, or indeed a region of interest defined by where data can be obtained, is operating at criticality, can we reasonably expect power law statistics in neural data coming from a very small (possibly sub-sampled) subset of the system?
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Learning about the distribution of earthquakes may not prevent the Big One, but for war and terrorism, power-law statistics may teach governments something about how to defeat the enemy, and make war less deadly.
Systematic experimental investigations have demonstrated that the plastic deformation of micropillar proceeds through a sequence of intermittent bursts, the sizes of which follow power-law statistics.
It is found that these distributions follow power-law statistics for which the evolutions of exponents through cyclic driving are estimated.
Assuming that the brain, or population of neurons under study, operates in the region of a critical regime can it be expected to display power-law statistics given that it is a finite-size system?
Whereas the stress serrations display various types of statistical distributions depending on the driving strain rate, including power-law, peaked and bimodal histograms, it is found that acoustic emission is characterized by power-law statistics of event size in all experimental conditions.
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