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This paper empirically examines properties of the major methods currently used to estimate average default probabilities by grade.
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The complexity of neuroimaging data sets allows researchers to examine properties of collective neural activity at the level of networks.
A number of different graph-theoretic measures can be applied to such a graph to examine properties of centrality.
Looking beyond the genetics and proteomics of individual cells to examine properties that might seem less important can actually lead to some interesting results.
Additionally, the replacement of fine natural aggregates has a more pronounced effect on the examined properties.
Equations expressing the effect of the replacement level on the examined properties were formulated, whenever appropriate.
Here we examine properties of critical DSRs — that is, DSRs whose products lie entirely on the attainable region's boundary.
The number of passes generally had a more pronounced effect on the examined properties compared with pressure.
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CEO of Professional Science Editing for Scientists @ prosciediting.com