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Several sequence-based approaches can generate thermostable variants of mesophilic proteins.
These approaches can generate novel compounds and reactions with proposed enzyme candidates.
Depending on the reasons for missingness, both these approaches can generate biased results, but they are used here as sensitivity analyses to assess the robustness of the findings.
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Whether this approach can generate big profits over the long term is not clear, but plenty of people are giving it a try.
By deploying such rules, our approach can generate four different types of traceability relations.
The analysis also indicates that the proposed cooperative coevolution approach can generate more diverse sets of non-dominated scheduling heuristics.
The second is whether either approach can generate reliable results given the limitations of the experimental design.
Only this integrated approach can generate the co-benefits needed to create coalitions among national and local stakeholders, which is necessary to overcome the barriers described before.
This approach can generate sliding spotlight raw signal not only from raw data evaluated by the simulators, but also from real data in the stripmap/spotlight mode.
Results show that the proposed approach can generate more accurate MF metamodels by providing the optimal high-to-low sample size ratio and sample locations.
The look-ahead approach can generate the feedrate profile to satisfy the geometrical constraints and kinematical characteristics determined by machine tools.
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