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The method eliminates a step used in earlier attempts to derive iPS cells that scientists fear might cause cancer-inducing mutations.
Extensive experimental results on the dataset created by the authors, involves 673 images collected from 11 different scenes, demonstrate that the proposed method eliminates a large percentage of the false alarms produced by the HOG pedestrian detector.
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It can be used as a preprocessing step to any multiple alignment or repeats inference method, eliminating a possibly large fraction of the input that is guaranteed not to contain any approximate repeat.
One standard solution is to enrich for the polyadenylated (poly(A)) RNA transcripts (so called mRNA-Seq) with oligo (dT) primers, similar to how DNA microarrays are primed; however, this method eliminates all non-poly(A) RNAs in addition to rRNAs.
Furthermore, the method eliminates any potential multi-estimation problem.
This method eliminates any contamination of the studied sample.
PMOnly methods display a large number of highly correlated gene pairs in the Hasse dataset and in two of the three dual-channel datasets (PramilaS and PramilaL), while LoessOnly methods eliminate a large part of these correlations, especially in the Hasse dataset.
This method eliminated any risk of default, a very real problem in the American Stafford Loan system.
This method eliminates the need for a cumbersome analytical approach.
The method eliminates smoothing by constructing a singular quadrature rule for the Biot Savart law at each time step, using quadtrees and orthogonal polynomials.
The method eliminates the need for a coordinate generation and/or premapping required for regularization of the computational domain in standard implementations of spectral discretizations.
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