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The differences in formal educational between the clusters could not be explained by a change in entry bar.
Getting the system to effectively extract and present the subtle differences between the clusters could be the key to improving visual pattern depiction.
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For 13 (28%) of the 47 DNA fingerprint clusters, epidemiologic links between some members of the clusters could be identified.
The maintenance of the differentiation between those clusters could be explained by the fact that sexual reproduction seems to play no role in the adaptive patterns recorded here.
Third, the number of youths within each of the ethnic groups was too restricted to determine whether the differences and similarities between the three clusters could have been replicated in each of these groups.
Thus, the variables that explained the largest differences between clusters could be identified.
A distribution and age of V. erioloba within a wider proximity for a potential relation between age clusters could further support conclusions on presumed episodic precipitation events that facilitate the propagation of V. erioloba within the dunes.
Between them, two clusters could be identified, strongly correlating with the geographical origin.
Regular translocations between areas within clusters could also be supported in order to maintain the genetic diversity [ 15, 20], particularly for entirely or partially fenced protected areas (e.g. Malilangwe, Hluhluwe-iMfolozi, etc).
All the SDS-identified top SNPs showed strong correlations with PC1, suggesting that heterogeneous geographic adaptations between these two clusters could partially explain DAF heterogeneity induced by very recent selection pressures on the Japanese population.
Migration between clusters could not be totally controlled, however our analysis was by intention to treat.
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CEO of Professional Science Editing for Scientists @ prosciediting.com