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Sun et al. (1995) optimized the concentration, temperature, and duration of pretreatment using sodium hydroxide.
In order to maximize SNP discrimination, we first optimized the concentration of Ca2+ in the system.
Because C-labeling GL is expensive, we optimized the concentration of GL to save substrate without affecting the growth rate of P. tricornutum.
Initial experiments optimized the concentration of SBV N protein used as coating antigen, selection of the microtest plate, the dilution of the test milk and saliva, and the dilution of the HRP conjugated secondary antibody to provide the best discrimination between known positive and negative specimens as determined by commercial test with adequate serum sample.
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The desired properties were treated as objectives and were extremized simultaneously by utilizing a multi-objective optimization algorithm that optimized the concentrations of each of the alloying elements.
Furthermore, we optimized the concentrations of the metal ions using a Box-Behnken design [23],[24] to minimize the IB solubility.
We have optimized the concentrations of ZnCl2, chitosan and NaOH, pH of the reaction medium, reaction temperature and stirring time for complexation of Zn chitosan complex and precipitation of Zn(OH 2 out of the complex.
We then optimized the concentrations of NF-D1 and NF-D2.
Using factorial design we optimized the concentrations of TNFα, TGFβ1 and IL-13 to generate the most eotaxin-1 possible from NHLFs so enabling functional analysis.
Firstly, to maximize the masking effect of reduction-sensitive PEG on R8, we optimized the concentrations of CHO-S-S-PEG5000 CHO-S-S-PEG5000 CHO-S-S-PEG5000 CHO-S-S-PEG5000 thandthe higheR8concentrandon of CHO-S-S-PEG5000, the betteresultsasking eFigct on R8.
The simulation results are used to optimize the concentration of nanoparticles for the best tribological properties.
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