Exact(1)
Figure 11 explicitly demonstrates stochastic pattern fluctuation, which emerges based on a common background with the main states of (N i, j)) ranging about in ([0.3, 0.8]) (Fig. 11(b)).
Similar(59)
Prior to the analytical and numerical study, an experiment to demonstrate stochastic resonance in a mechanical system is described.
We find that a key experiment by Wilson and von Hippel [Wilson, K. S. & von Hippel, P. H. (1994) J. Mol. Biol. 244, 36-51] toought to demonstrate stochastic termination was an incorrectly analyzed regulatory effect of Mg(2+) binding.
In this study, we experimentally demonstrated stochastic resistive switching in TiO2-based ReRAM devices that possess identical initial resistive states.
This study demonstrates that stochastic fatigue analysis can be used as a practical tool for assessing the fatigue performance observed in some miter gates and for inspection and maintenance planning.
As Figure 1 demonstrates, the stochastic sampling of a single haplotype per species could render a myriad of different results, some more resolved than others, but none alone particularly accurate at estimating the true course of the species' evolutionary history.
This simulation demonstrates that stochastic elements could potentially have a major influence on the burden of metastasis, to the point that it would seem unreliable, in any individual, to base assessments as to the biological potential of the cancer on the metastatic burden.
The third example Web application demonstrates how stochastic simulation in Shiny can be used to explore a series of ibuprofen dosing regimens for patent ductus arteriosus (PDA) closure in preterm neonates less than 32 weeks gestation (Example 3; supplementary code available online).
► Demonstrate stochastic analysis can be performed on large and complex models.
The effectiveness of this algorithm is demonstrated for stochastic wind loads in the frequency domain.
We demonstrate that stochastic global optimization algorithms of the first order, i.e., with local minimization after each iteration (e.g., Monte Carlo-Minimization), have a greater chance of finding the global minimum after a fixed number of function evaluations.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com