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Nanocrystallization in many driven amorphous alloys can be understood using the kinetic model developed here.
The basic idea behind dispersion management is quite simple and can be understood using the pulse propagation equation.
Although subtle changes in processes are not the goal to be recognized by this method, general changing trends in processes will be understood using the proposed fuzzy recognition model, which is good to realize suboptimal process control.
It has recently been shown that the form of unloading curves obtained during indentation of elastic-plastic materials with geometrically self-similar indenters such as pyramids and cones can be understood using the concept of an "effective indenter shape".
In a previous paper [13], we showed that the scrambled experiment could be understood using the network in Fig. 5b.
A slow change of the magnetic energy during the loading phase can be understood using the fact that the rate of magnetic flux transfer from the dayside to the tail is limited by the flow velocity V in the magnetosheath.
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Thus, the concept of numerical magnitude is understood using the mechanisms of the visual/haptic system that evolved to process magnitude in a physical sense (e.g., estimating distance to an object one intends to grasp).
The consistency of the two views is understood using the double-adiabatic approximation in a fully quantum description of the system.
The effects of growth can be understood using intuition about the coalescent model.
In this regard, the Delphi process could be understood using fuzzy logic to clarify the reasons for using this method with business ethics in mind.
Once the mechanism is understood, using DNA to code and predict the growth of NPs would be possible.
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