Further increase causes a decrease of efficiency of the process of interest.
The required layer thickness for the process of interest was 1 μm, with a standard deviation of 30 nm.
However, the information derived from single scans usually are biased by factors unrelated to the process of interest.
Several simulation methods can and should be combined to get a reliable picture of the process of interest.
When the biological process of interest is related to a specific disease, eliciting a better understanding of the underlying pathways can lead to designing a more effective treatment.
Therefore, selecting an appropriate resolution should be a compromise between the pore size and the representative element volume for the specific property or process of interest.
While many optimization and control methods for stochastic processes require gradient information from the process of interest, obtaining gradient information from experiments is prohibitively expensive and time-consuming.
Understanding genetic interactions during early development of a given organism, is the first step toward unveiling gene regulatory networks (GRNs) that govern a biological process of interest.
Using the resultant parameters, the optimal design of the fucose-separation process of interest was carried out on the basis of a simulated moving bed (SMB) technology.
Estimating an optimal set of parameters by optimization algorithms requires knowledge of the sensitivity of the process of interest to model parameters.
These validated parameters were then applied to the next stage of optimizing the SMB process of interest on the basis of standing wave design (SWD) principle.
