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One of the attractive features of this approach is explicit recognition of differences in processes affecting use versus the intensity of use of different types of services.
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This approach is an explicit method with high validity for resolving strong nonlinear oscillation system problems.
Central to this approach is the explicit inclusion of costs in determining where to allocate scarce conservation dollars to meet a specific conservation objective and the consideration of how investment should change through time to meet this objective [9] [11].
A key strength of the present approach is its explicit handling of feature dependencies (Fig. 5).
The advantage of this approach is that explicit models for contrasting evolutionary scenarios are compared with each other.
In particular, the approach is temporally explicit for all water bodies, instead of only those with measured river flow time series.
The main novelty in their approach is the explicit calculation of RNA secondary structures and minimal free energies for the evolving sequences and the use of the calculated parameters for the model simulations.
This new approach is based on explicit discrete-event simulation technology.
However, a limitation of this approach is it requires explicit knowledge of the software being migrated, compared to VM migration, which typically abstracts the software within a VM.
A completely different approach is to use explicit statistical models of grain noise and defects and to design an optimal filter based on those models.
The numerical approach is based on explicit FEM computations and presents some appealing advantages with respect to conventional models, since it does not use zero-thickness cohesive elements and does not require a non-physical penalty stiffness to be introduced between adjacent plies.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com