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The quantitative simulation of the doping-dependent effect will be helpful for resolving this problem.
Innovations are thus required in the rapid, quantitative simulation of self-assembly on cellular scales.
This work provides a quantitative simulation model toward the rational design of high efficient membranes.
Shortcomings of qualitative simulation and of quantitative simulation motivate combining them to do simulations exhibiting strengths of both.
However, lack of biochemical data and complexity of biological environment complicate rational design of such circuits based on quantitative simulation.
In this paper, we describe a novel discrete-event queuing strategy for time- and memory-efficient quantitative simulation of self-assembly systems in continuous time.
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Our approach is evaluated through quantitative simulations in various environments.
A multi-phase field model for quantitative simulations of polycrystalline solidification of binary alloys is introduced.
For those initiating events, the quantitative simulations using transient mass and energy calculation and computational fluid dynamics were performed.
Although these models do not allow for quantitative simulations, they allow us to ask qualitative questions about the system and to learn valuable knowledge.
Many foresight researchers believe that quantitative simulations have a very restricted contribution in futures studies due to their simplicity and lack of creativity.
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