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Minutes and reports of the joint meetings of the ARTs during the annual REACT project meetings and the general reports of the annual REACT project meetings Minutes of the monthly REACT Steering Committee telephone meetings and of its meetings during the annual project meetings The second major data set consists of the in-depth interviews carried out at the end of the study.
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There are several major data sets.
On the two major data sets for action recognition, our approaches outperformed those found in the literature, both in the unsupervised and supervised case.
Supporting Information, Table S1 summarizes the major data sets used in this study, with details shown below.
Furthermore, our own comparison of these data sets (summarized in Table 1) shows that there is no correlation between any of the three major data sets.
We investigated rates of protein evolution by using a great tit (P. major) transcriptome data set based on RNA extracted from eight different tissues (brain, heart, kidney, liver, muscle, pancreas, skin, and testis/ovary; Santure et al. 2011).
A major difficulty with the data set lies in the difference of data collection with respect to contacts at work.
Rather, the major partition in the data set occurred locally within the large sample from a single beach in North Wale.
We examined the validity of FST analysis by testing ten candidate major genes in our data set.
Takezaki's two-cluster test (Takezaki et al. 1995) statistically rejected the clock hypothesis by demonstrating a significant rate of heterogeneity (CP > 95%) between two of the major clusters in our data set.
Likewise, Takezaki's two cluster test was employed by utilizing the LINTREE (Takezaki et al. 1995), which established a significant rate of heterogeneity between the two major clusters in our data set, that is, tetrapods and teleosts.
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