F is strictly increasing on (mathbb{R}^), for every sequence ({s_{n}}) in (mathbb{R}^), we have (lim_{nrightarrowinfty}s_{n} = 0) if and only if (lim_{nrightarrowinfty} F(s_{n}) = -infty), there exists a number (k in 0, 1)) such that (lim_{srightarrow0^s^{k}F s) = 0).
As (f(t)) is a.p. on (mathbb {R}), for every sequence ({s_{n}'} subsetmathbb {Z}subsetmathbb {R}) there exists a subsequence ({s_{n}} subset{s_{n}'}) such that ({f(t+s_{n})}) converging uniformly for (tinmathbb {R}).
If S ⊂ X γ,U is pointwise bounded on D1, then every sequence {f k } ⊂ S has a subsequence { f k i } such that lim i f k i ( x ) = f ( x ) uniformly on each D m, where f ∈ X γ,U).
If S ⊂ X γ,U is pointwise bounded on X, then every sequence {f n } in S has a subsequence { f n k } such that lim k f n k ( x ) = f ( x ) exists at each x∈ X, and f ∈ X γ,U).
In the jackknife test, prediction is done on every training sequence.
For lesions with Gleason score 8 and above, multi-parametric MRI yielded a tumor detection rate of 100% (13/13) and 12/13 demonstrated positive findings on every MRI sequence.
To account for novel genomic regions present in other O157 H7 strains, but not found in EDL933 or Sakai, an in silico subtractive hybridization was performed on every O157 H7 sequence in Table 1 against EDL933 and Sakai (Laing et al., in preparation).
A family of probability measures on is relatively compact if every sequence of elements of contains a subsequence which converges weakly to a probability measure, that is, for any bounded and continuous function on, (2.18).
It's not hard to see why people are jumping on this sequence.
Therefore, on average in every sequencing run 80 million reads were of high quality (⩾ AQ20 or one error in 100 base pairs (bp)) and provided useful sequence information.
