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Systematic conservation planning methods to design marine protected area (MPA) networks can provide more meaningful results by addressing the spatiotemporal variability of biota, and by using these data to inform target assignment.
An analysis of the background fractal dimension distributions obtained using TTE and DISCSC data (143 and 110 background regions, respectively), indicates that for both datasets background fractal dimensions 〈Dbgr〉 = 1.5 that the fractal dimension distributions obtained by using these data can be processed simultaneously.
The structural model is generated by using these data.
By using these data, it is possible to calculate linear sedimentation rates (LSRs) at all the six sites with high time resolution (Additional file 4: Table S2).
By using these data sets interactively, we can identify and map the areas of greater vulnerability and the structures with the highest risk.
By using these data, we realized that many genes associated with mucocyst formation were co-regulated, and that moreover co-regulation itself could be used as a screen to identify novel mucocyst-associated factors.
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However, by using these data-driven models and processes, leaders can create clarity for teams to move forward and execute quickly on their decisions.
Companies can start taking advantage of this by using these data-based insights to come up with more effective advertising, and get to know their target demographics on a more specific, qualitative level.
Triangulation of data was done by using these two data collection techniques to increase the validity of the study findings [ 12].
It has generously made its full data sets, as well as all results from studies conducted by researchers using these data, available from the outset.
By using these joint data we derive an estimate for the distribution of the absorbing column density in Sy2s.
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