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We choose the sample size (n=1000), and we treat each input variable ((lambda, d_{T}, r, k, eta, d_{L}, a, delta, N, c), (n_{rt}), and (n_{p})) as a uniform distribution and treat each set of value of (H_{2}, H_{3}), and (mathcal {R}_{0}-1) as the output variables.
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Here she offers a new theory, "liberal nationalism," which allows each set of values to accommodate the other.
Moreover, each set of values of these dimensionless rheological properties defines a class of rheologically equivalent materials.
For each set of values, data were expressed as mean ± standard error (SE) or median (interquartile range) where appropriate.
As before, data for each set of values was simulated 10,000 times.
HDL and non-HDL values were log2 transformed resulting in a normalized distribution for each set of values.
The student t-test was used to test for significance in each set of values, assuming equal variance.
Several values were measured from each run and the mean value of each set of values was used in subsequent analysis.
For each set of values of the core parameters, the experiments were simulated and the result (success or failure) was recorded for each experiment.
For each simulation, and each set of values { T, ng, dts}, five separate annealing runs were carried out, each beginning with a different set of estimates for the locus selection coefficients { σ ˜ i }.
For each set of values of (β T, a, b), the value of β 0 was determined by a minimization algorithm from a sample of 1,000,000 in order to guarantee the outcome to occur in 50percentnt of subjects, approximately.
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CEO of Professional Science Editing for Scientists @ prosciediting.com