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Assuming that l (characteristic size of the inhomogeneity of external stress field distribution) is smaller than the wavelength and geological structure sizes, we consider processes in geomaterial at two scales: macroscale characterized by L and λ and microscale characterized by sizes of inhomogeneous distribution of external stress field.
For the three initial population sizes we consider here, N0 = 10, 104 and 10, an effective population size given by N e ≈ DN0 [ 1], and mutation rate μ = 10-6, the mutation supply rates are S s = 0.001, S m = 0.1 and S l = 10 for the small, medium and large populations respectively.
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Because of small sample sizes, we considered only the first four groups and, where indicated, combined Mexican American and Other Hispanic into one Hispanic category.
Because different WGD pairs with the same sequence divergence have different shared neighborhood sizes, we considered both the average and maximum shared neighborhood sizes for given sequence divergence values.
However, on an empirical level, our simulations show that in the sample sizes we considered, this is not an apparent problem because the Wang-Allison tests have very high power and can control type I error quit well in the simulation studies and are practical for the lifespan studies).
Along with the transaction size, we consider each venture capitalist's level of involvement in nurturing the company to exit.
For each effect size, we consider the impact of study quality, observation period, regional effects, and publication bias as explanatory variables in a regression model.
Since we are analyzing the problem in a deterministic framework where extinctions only happen in declining populations, and we know that probabilities of extinction on specified time intervals are inversely related to population size, we consider what strategies maximize the population size.
Given the small sample size, we consider this difference meaningful.
In order to account for household size, we consider per capita expenditure.
However, by using a crossover study design, block randomisation and the large sample size, we consider the risk of bias reduced.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com