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The strain life methods successfully predicted fatigue life (factors 1/7.0 9.2 of the test) at high and low stress amplitudes of 352 and 315 MPa, respectively.
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Both methods successfully predict ∼80% of nucleosome positions in vitro with 2-bp precision (see Supplementary materials at http://numap.rit.edu/app/dna/suppMaterial.xhtml).xhtml
The latter method successfully predicted the transition to fully mixed, uniform fluidization conditions.
According to the results obtained, the statistical method successfully predicted the effects of variables on the final properties.
A comparison of seismicity before and after the giant event shows that our method successfully predicted the activation of seismicity.
In 11 out of 18 examples, our method successfully predicted the type of translational regulation by the sRNA.
Our method successfully predicted SMB gene clusters without using motif information from known genes in the SMB gene clusters.
Our method successfully predicted the cooperativity between Swi4 and Swi6, and the cooperativity between Mbp1 and Swi6 (see Figure 7).
For the diseases that only have one associated gene in OMIM, our method successfully predicted the tested genes in top 1 for 52.12% of diseases, while the baseline method succeeded in 11.47% prioritizations (P < e−4).
With these, the proposed analytical method successfully predicts the obtained experimental data with excellent accuracy.
It is shown that this method successfully predicts power draft in a variety of semi-autogenous plant operations.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com