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To maintain viable elephant populations composed of individuals whose ranging behaviour is driven by ecological constraints rather than by fear, at least two management policies must be included and implemented in such a strategy.
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Schemas support this strategy and are implemented in such a way that perfection is disregarded at the profit of an intuitive trade-off between performance and cognitive resources savings.
While the first strategy is not applicable to hash table-based algorithms such as SSAHA2 and BLAT, the second strategy could be implemented in such programs and may substantially accelerate them by saving much time on the construction of repetitive alignments.
We know that creativity can be measured, managed and fostered; there is no excuse to not implement such a strategy in our school system.
According to the process evaluation we were able to implement such a strategy in participating hospitals.
However, little is known about how to implement such a strategy, especially in the African context.
The challenge is developing methods to implement such a strategy successfully in fragile health systems and resource limited settings.
The next round of climate negotiations in Mexico this December could pursue several actions to implement such a strategy.
We discuss key elements of this multi-purpose sampling strategy and the planning process used to implement such a strategy.
When implemented behaviourally, such a strategy minimizes the mean distance travelled before detecting a target.
We predict one difficulty in implementing such a strategy: it is possible that different subgroups of the data will show different, sometimes conflicting patterns of metabolite phenotype relationship, and including the metabolome data from a large number of widely divergent strains may yield a poor-performing model that fail to indicate any significant metabolite.
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