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Because of infrequent nature of such giant earthquakes, global collection of data is needed to increase our sample and knowledge on such large earthquakes.
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Either way, analysis of biogeographic patterns of the Caribbean marine biota taken as a whole, or even at the phylum to order level, is still difficult and limited, owing to insufficient and geographically biased sampling and knowledge.
Nevertheless, IR spectroscopy is very sensitive to qualitative and quantitative differences within and between samples, and knowledge on the absolute amounts is not always important.
To this end, the biobanking community and funders must work together with policy makers on regional, national, and international levels to provide legal and ethical frameworks or, at minimum, reciprocal 'safe harbor' recognition to encourage the use and sharing of data, samples, and knowledge.
Appropriate sample collection and knowledge of interpreting results on the basis of specimen type are essential for accurate triage of patients thought to have EVD.
Within the study sample, awareness and knowledge of constipation-related factors varied greatly from very well informed individuals to those who were finding new facts about constipation within the PILs.
Our assessment did not include such important elements of EDAT or E-EDAT as understanding that experiments have to be repeated, evaluation of the sample size, and knowledge that one can never unambiguously prove a hypothesis (Sirum and Humburg, 2011; Brownell et al., 2014).
The downside of a medical facility-based study is that it is not necessarily representative of the determinants of participation in population-based surveys (e.g., levels of -undisclosed- prior knowledge of one's HIV status may be higher in a health facility sample, and prior knowledge of HIV positive status has been identified as a source of bias in HIV prevalence estimates [ 29]).
As the eServices platform is still in development, synthetic data, based on real data sample and empiric knowledge, is being used to populate the initial dataset.
The use of new mathematical models to predict species richness based on sampling intensity and knowledge of habitat characteristics offers promise for both research and management of European biodiversity.
Measuring these rates is easy when the sample is known and knowledge of these rates is important to ensure that the validation tool does not introduce a bias.
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