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Generally, in the sequential execution scheme, the most efficient variant, e.g. in terms of response time or financial cost, is located first in the series, and is termed primary variant.
Since many variables were investigated, the studies were conducted in a mode, in which only the most efficient variant of a given parameter tested in the current round of experiments was used for the next round.
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The stochastic acceptance procedure of a solution proposed by Metropolis et al. (1953), combined with the temperature decreasing geometric scheme of Kirkpatrick et al. (1982) are the most efficient variants.
While the most efficient variants utilize atmospheric oxygen as the terminal oxidant, many such transformations require the use of expensive or toxic oxidants, often coupled with the need for transition metal catalysts.
Through this manner, the most efficient DE variant is expected to obtain the most computational resources during the optimization process.
After every predefined generations, the most efficient constituent DE variant is determined and the reward subpopulation is assigned to that best performed DE variant as an extra reward.
The computational efficiency of the FAM allows a numerical optimization of the operating points of flowsheet alternatives in order to determine the most energy-efficient variant.
Instead, we propose two approaches to empirically determine the most efficient grouping of rare variants.
However, we believe that the most efficient strategy to localize disease/trait variants will involve approaches that can identify both common and rare variants in the same model.
Genome- and population-wide re-sequencing would allow for most efficient detection of causal trait variants.
Thus, the W361A variant was the most efficient for ginsenoside Rd hydrolysis.
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