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The versatility is investigated by applying this procedure on two different iPP grades.
The blue symbols in Fig. 3b,c show that the collisional broadening and shift are successfully suppressed by applying this procedure.
Moreover, by applying this procedure, the element removal impact factor and the most critical locations of such removals were obtained.
The random dynamic response obtained by applying this procedure is compared with that evaluated through numerical integration based on the Harmonic Balance Method and the Monte Carlo simulations.
By applying this procedure to neurites labelled by three Gal4 lines, we show that neuritic territories are established in the embryo and maintained throughout larval life, although the complexity of neuritic arborisations increases during this period.
We finally obtained two networks by applying this procedure to the mRNA and the protein expression data, respectively.
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Rankings obtained by iteratively applying this procedure are similar to those based on the average item information function (IIF) at the pass-fail ability threshold, IIF (θ=0), and the average information gain (IG).
By applying this new procedure to the two original GWAS with internal controls and two reconstructed studies with external controls, we documented its advantage over other commonly used PC selection strategies.
We also show that by applying this filtering procedure to primary data from the HM450 bead array, it is possible to yield analyses of significant interest from a biological perspective that may be unobservable without principled probe filtering.
We refined our gene frequency ranking by combining the results generated from applying this procedure several times with different parameters.
The next step is to transform the contents of this matrix into gray-scale values by applying the procedure given by (1).
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