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We find that tuning parameter values 1.00, 0.70, 0.50, and 0.30 appear to work well for sample sizes 50, 100, 200, and 500, respectively.
As previously mentioned, we have found through trial and error that the following tuning parameter values 1.00, 0.70, 0.50, and 0.30 appear to work well for sample sizes N = 50, 100, 200, and 500, respectively.
In the upcoming discussion of the simulation study, we have found that the following tuning parameter values 1.00, 0.70, 0.50, and 0.30 appear to work well for sample sizes 50, 100, 200, and 500, respectively.
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These modifications also worked well for samples stored at 25 °C for 6 months, and particulate increase did not occur.
This generalized model is also excellent in incorporating the possible effect of heterogeneity in specimens and performs well for samples that show similar data distribution.
Vane geometry was used for the polymer shale samples; this geometry helps prevent wall slippage at higher shear rates, helps disrupt flow inhomogeneity while shearing, and also works well for samples containing suspended solids.
Vane geometry helps prevent wall slippage at higher shear rates, helps disrupt flow inhomogeneity while shearing, and also works well for samples with suspended solids (Goh et al. 2011).
This approach works well for samples that are otherwise identical, such that no additional sources of differences in proton relaxation rates are present.
We have shown that URSA performs well for samples from this platform, but there exist many other expression datasets that use other platforms, with new ones emerging continuously.
Once the resolving gel had set, a stacking gel (3.6% w/v acrylamide, 0.12 M TRIS pH 6.8, 0.1% SDS, 0.03% AMPS, 0.33% TEMED) was layered and a comb used to create wells for sample loading.
After the data had been collected the tape was removed and the identifiers matched with their respective plate wells (for sample identification please see Additional file 1).
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