Sentence examples for strict similarity from inspiring English sources

The mathematical analysis of the experimental results showed a strict similarity between replicative senescence and age-related changes, enabling the definition of an in silico model mimicking PDPC behaviour in terms of nitric oxide (NO) production.

This paper presents and discusses scale effects of a specific scaling approach for multi-grain size mixtures that preserves similarity of initial motion for each grain size class and of the bank stability coefficient between the model and the prototype, but relaxes strict similarity of the Shields and particle Reynolds numbers.

Here we used genomic context and strict similarity criteria to choose which genes are orthologous, and are likely to have the same function.

The data in Table 2 shows that about 1/2 the bFLICs are represented well by single TCs in the TIGR BtGI using strict similarity criteria, but using less strict similarity criteria will result in a more ambiguous representation of the bFLIC using TCs because of the similarity between TCs.

The strict similarity value used to create the reference contigs may also explain the relatively short size of the contigs retained in the high coverage data set (average length = 595 bases).

Finally, from 245 fosmids that could be assigned to environmental A. macleodii (eA.macleodii) by a strict similarity threshold (see Materials and Methods), a total of 161 were successfully sequenced, assembled to a length larger than 10 kb, and analyzed.

Despite the strict similarities between TLR1 and TLR6 there are some areas of divergence within both the LRR-motifs and the TIR domains.

This stricter similarity metric was used for conducting a stricter test of our SVM model.

> -wrap-foot> Furthermore, Choi and Deane (2010) showed that the performance of FREAD can be enhanced by setting a much stricter similarity threshold.

In short, an invisible scheme may be considered a variant of visible watermarking with a 'negligible' (i.e., approaching zero) α, and having an additional (and even more strict) perceptual similarity requirement.

This results in a set of competitive parameters ranging from strict regional similarity (ω = 1) to entirely random matrices (ω = 0).