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To examine whether such an ascertainment bias has an effect on the estimation of the effective SNP size, we used HapMap phase I SNPs, which had strong ascertainment bias, and phase II SNPs, which had less sampling ascertainment bias [ 2].
This model, in conjunction with experimental results, allows estimation of the effective surface self-diffusion coefficient.
This study focuses on a theoretical estimation of the effective permeability of unsaturated cracked porous media.
The results indicate that the estimation of the effective characteristics influences considerably the computed response.
A new method for the estimation of the effective anisotropic relaxation behavior based on higher order normalization schemes is introduced.
Estimation of the effective carbon diffusivity in the compound layer, which reached 12.9 · 10− 8 cm2/s was carried out.
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An exception is the estimation of the the effective population size from SNP density data based on the differences between the alleles at many loci of the heterozygous tree (e.g. Halley et al. 2014).
If these two phenomena are present, the estimation of the effect of effective density on local productivity will be biased and thus not conducive to correct projections.
Both of these factors cause a reduction in the estimations of the effective dose.
For a limited number of radiopharmaceuticals, and for adults, it has been shown that there is a difference between earlier estimations of the effective dose and the results of the calculations using the new ICRP/ICRU reference phantoms and the new ICRP tissue weighting factors [10 12].
Estimations of the effective properties and both the first and second statistical moments of fields in the constituents of CMs are presented in a general form of perturbations introduced by the heterogeneities and taking into account a possible imperfection of interface conditions.
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