Sentence examples for using a reduced sampling from inspiring English sources

Insulin sensitivity was assessed by the frequently sampled intravenous glucose tolerance test (FSIGT), using a reduced sampling protocol [ 17].

The image series were acquired from 49×4949 nm2 areas using a reduced sampling of 0.048 nm/pixel, resulting in a recording rate of approximately 1 frame per second.

We also repeated our analysis on A. thaliana using a reduced data set constructed by sampling one allele from each of the five "populations" identified by the STRUCTURE model (Pritchard et al. 2000; Falush et al. 2003; Nordborg et al. 2005).

Then, I test the use of methods which employ the bulk of information in big data and other methods using a very reduced sample.

Using a slightly reduced sample (N = 499) with CSF biomarker data available, all 8 identified interactions remained statistically significant when performing hierarchical linear regression using the CSF phenotypes (one baseline measure: A β, two ratios: t-Tau/A β and p-Tau/A β) instead of the AV-45 measure as outlined earlier (Table 3).

To assess the relationship between sample size and matrix stability in the wing patterns, the modular architectures were also examined using reduced sample numbers and the results were compared to those obtained using all samples.

HTC screening of 40 novel Kynar® poly vinylidene fluoride) (PVDF /acrylic polyelectrolyte (PE) membranes focused on varying the Kynar® type (5×) and PE composition (8×) using reduced sample sizes.

The necessity to use reduced sample sizes, in order to achieve better spatial resolution in studies on the pore microstructure of Portland cement matrix composites, leads researchers to perform the fractionation of specimens.

This study investigates whether load estimates and resultant power to detect trends can be enhanced by (i) modelling the error structure so that temporal correlation can be better quantified, (ii) making use of predictive variables, and (iii) by identifying an efficient and feasible sampling strategy that may be used to reduce sampling error.

The premise is to apply subset simulation to tackle the short-term variability, while importance sampling is used to reduce sampling variability arising from long-term uncertainty (whose characteristics are more amenable to an approximate treatment for constructing an importance sampling density).

To account for this variability, methods based on estimating parameters over "windows" have been successfully used to reduce sampling error while retaining true signal in studies aimed at identifying evidence of selection in populations [ 2- 5].