Sentence examples for patterns to discriminate from inspiring English sources

Exact(7)

In a series of experiments in which, among other things, they placed fish inside a glass chamber equipped with UV filters, they showed that P. amboinensis used the patterns to discriminate between the two species.

The box-plot and the abundance-area were the most meaningful patterns to discriminate models in terms of their ability to represent the observed patterns.

Few studies have been reported concerning the utilization of prolamins patterns to discriminate Vicia taxa in comparison with albumins and globulins.

The presented methodology for landscape character assessment is proposed as support for spatial planning processes and policy development for landscape conservation by providing a quantitative tool to analyze landscape patterns, to discriminate between the various landscapes in a study area and by elucidating features that are important for the identity of a region.

Furthermore, the contaminating DNA appears to degrade in a fashion similar to ancient DNA, making it hard to use damage patterns to discriminate between the two [6].

Four peaks at 1950, 3960, 4304, and 5211 Da were chosen for patterns to discriminate the relapse group from the non-relapse group.

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Similar(52)

By receiver operating curve analysis, the ability of UIS pattern to discriminate radiographic ARDS was fair (AUC 0.73, 95%% CI 0.63 0.83) (Additional file 2: Figure S2).

Following the general patterns of psoriatic tissue differentiation, the use of decision tree ensembles was explored to classify samples into PN and PP classes and derive the major gene patterns able to discriminate the psoriatic phenotypes (see Figure  1, step1).

The different range and hit pattern allow to discriminate different particles crossing the IFR.

One site showing this integration pattern seems to discriminate between attractive and less attractive foods when it matters, i.e. when one is hungry, but is indifferent to them when the individual is sated.

(2013), which applied multivariate neural pattern classifiers to discriminate between expected (predicted) and unexpected (unpredicted) visual stimuli (faces or houses) when they were attended (task-relevant) or unattended.

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