Sentence examples for datasets was found from inspiring English sources
From a linear regression analysis the correlation coefficient between the two datasets was found to be highly significant for areas with a distinct phenological cycle.
The selected clustering of both the NSI/SI and R5/X4 datasets was found according to the silhouette value described in the Materials and Methods and inspected in detail.
Moreover, the absolute correlation in the per-metabolic class median of the PC2 loading values between the two datasets was found equal to 0.68.
After the combined analysis, 167 SNP sites were obtained as risk loci in EAGLE (Table S2) and good association consistency between EAGLE and PLCO datasets was found in the hypothesis regarding amplification and 1(b)).
The mean unsigned difference (computed in normalized units) seen in the original and partially corrected (single spline fit) datasets was found to be 0.321 ± 0.134 and 0.142 ± 0.036, respectively.
Full-length protein sequences were included with our dataset of 125 008 non-redundant proteins into a single FASTA file, and the common intersection of source protein data among the three datasets was found using Warren Gish's nrdb (http://blast.wustl.edu/pub/nrdb/nrdb2).edu/pub/nrdb/nrdb2
Differences between the analysis datasets were found in the development of the trough and the horizontal distribution of moisture.
All of the datasets are found to produce very similar regression lines, except the Takeo (2009) dataset, which has a greater slope.
In the case of ANN model, the distribution patterns of observed and estimated datasets were found to be dissimilar for fifteen among sixteen events considered (Table 8).
Discrepancies between the GIMMS and MODIS datasets were found in equatorial areas (broadleaved, evergreen forest), Arctic areas (sparse herbaceous or sparse shrub cover) and arid areas (herbaceous cover, closed open).
Three new diffuse models proposed in this study, one trained for each of the three datasets, were found to greatly exceed the performance of existing modeling techniques, with slight improvements over the Perez model.
