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Thus, D is a measure of how much samples FORG and CONCEN differ.
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The question that is being assessed here is how much sample is really required?
In this case, the free energy calculations would be anywhere from 100 to 1000 times faster depending on how much sampling error can be tolerated.
why the sample was required; how much sample was required; how to collect the sample; where they should return it; and when they should expect to get the results.
Participants wanted information on: why the sample was required; how much sample was required; how to collect the sample; where they should return it; and when they should expect to get the results.
The precision of several sampling scenarios was simulated to quantitatively demonstrate how much composite samples improved the representativeness of the data.
Moreover, it is difficult to assess how much these samples have evolved during emplacment, and thus how representative the recorded grain sizes are of normal mantle conditions.
The principle is to take away from the observed biomarker concentration a value depending on how much the sampling conditions for subject i differ from the standard sampling conditions, i.e. those that should have been observed for all subjects in ideal conditions.
So, one may examine sample size for smaller effect size: say, effect size of 1.2 and 1.1 and see how much the sample size would change in these two additional settings.
By normalizing the sampler flux decrease in the 3D situation for that in 1D, kDBL provides a measure of how much the sampler flux is changed in the 3D geometry compared to the common 1D solutions of the DGT equation.
Here, the two function values are the integral of geodesic distance over the polygonal shape [9] and surface curvature, where the integral of geodesic distance represents how much the sample point is far away from the object center.
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