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The randomly-extracted samples are further adjusted with scaled-chaotic sequences to provide more flexibility and control over the granularity of the sampling of the solution space.
The combination of parallellism and generalized perturbation theory offers the opportunity to perform very exhaustive, fast and accurate sampling of the solution space for the equilibrium cycle reload pattern optimization problem.
Uniform random sampling of the solution space in any environmental condition is a rapid and scalable way to characterize the structure of the allowed space of metabolic fluxes.
Uniform random sampling of the solution space for E. coli metabolic models in any environmental condition is a rapid and scalable way to characterize the structure of the allowed space of metabolic fluxes [ 25].
The sampling of the solution space and, especially, the robustness analysis are extremely useful as they both provide the idea for the each reaction's "importance" in terms of the overall system performance and uncover the existing relationships between the reactions.
We have employed a constraint-based setting where an extensive and controlled sampling of the solution space is possible [ 21, 22] on a large-scale model of compartmentalized brain energy metabolism.
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The prepared samples of the solution and hydrogels were designated as #1, #2, #3, and #4.
The concentrated residue was dissolved in 100 μL of methanol and a 1.0 μL sample of the solution was injected into the GC-MS system.
Progress of the dissolution reaction was monitored by taking samples of the solution (5.0 ± 0.01 mL) at different times established according to the total reaction time (tr) of each experiment (≈20 samples per experiment).
Samples of the solution were intermittently analyzed for PO2, PCO2 and pH.
A 3.5 μl sample of the solution was applied to glow discharged, lacey carbon film on copper grids (300 mesh).
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