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In this stage the optimization potential is still very large, at very low cost.
For the MSSA stage, the optimization problem is decoupled into subproblems which can be solved distributively in linear time.
In the second stage the "optimization machinery" is applied on the set of live bids and computes the set of bids accepted in the round, which becomes the new set of standing bids.
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At the second stage of the optimization procedure, the microtubule cytoskeleton conformation that was obtained at the first stage is kept fixed.
A critical stage in the optimization of in vitro maturation (IVM) is the selection of good quality oocytes.
The approach is based on first calculating an optimal current density map, which is then used to allocate coils for the second stage of the optimization process.
A computationally efficient approach is developed to provide smooth transition between cells by considering three cells at each stage of the optimization.
The last stage of the optimization involves the exploitation of thread-level parallelism to leverage the multiple cores in the DSP.
The final stage of the optimization incorporated major influencing parameters, namely concentration of feathers, MgSO4 and KH2PO4, to define their effect on the release of soluble proteins from the keratinous substrate.
At the first stage of the optimization procedure, each microtubule is approximated numerically as a chain of straight, freely jointed segments of equal length and number.
During this stage of the optimization, we do not conduct any additional FBA, but rather perform a complex search among the previously computed designs.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com