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More specifically, we address both the construction of a stochastic model and the definition of a methodology allowing the numerical simulation (and consequently, the inverse experimental identification) of random elasticity tensors whose mean distance (in a sense to be defined) to a given class of material symmetry is specified.
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New datasets are applied as simulation samples to the model and consequently simulation results are obtained.
Figures 1 and 2 include the major results and lead to the conclusion that, in principle, there is a viable niche for predators in our simulations and consequently in any biological system that adheres to the same basic physical and ecological principles.
This explains why there are so many FPs from t-test in our simulations; and consequently t-test selects so many different DE genes than SAM and MBIS do in real data.
Note that the absolute number of mutations in the true driver genes is the same for both simulation sets, and consequently the relative mutation rate for driver genes in the simulated ovarian data is higher than that in the simulated lung data.
The simulation principle is completely deterministic and consequently the computed images present no photon noise.
The results are important for the dynamic simulation of gear transmission behavior, and consequently helpful for the monitoring of gearbox working condition and detection of early crack damage that may exist in gear sets.
This model can serve as a testbed to evaluate other cost criteria that can be more complex than the simple additive relationship in modeling effects of computation load imbalance and communication delays on the number of roll backs and consequently the simulation execution time.
The objective is an accurate evaluation of the local elastic stiffness of spot joints in FE analysis, which is fundamental to perform a reliable simulation of multi-joint structures and, consequently, a good estimate of loads acting on spots; this makes it possible to introduce structural stress or new general criteria allowing, for example, to predict fatigue behaviour.
Each simulation is characterised by its own temperature: low temperature simulations tend to explore local minima, while high temperature simulations may overcome energy barriers and consequently move in between local minima.
By CFD simulations a mean shear rate and consequently the corresponding effective liquid viscosity is estimated as a function of the gas flow rate.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com