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System-level design should embrace robust approaches for two separate reasons.
In this review, we highlight robust approaches for probing metabolism and addressing metabolically related questions though parallel labeling experiments.
Following the line of the previous discussion, in this paper, we investigate and compare the matched, mismatched, and robust approaches for inference methods in complex t-distributed data.
The remote sensing science and application communities have developed increasingly reliable, consistent, and robust approaches for capturing land dynamics to meet a range of information needs.
We then present a derivation of the physics-based consensus scheme for distributed and simultaneous recovery of multiple instantaneous and localized diffusion sources in Section 5, along with robust approaches for handling sensor noise, under unquantized and quantized sensor interactions.
Since collection of direct dynamic information about cell migration is incompatible with high throughput, we therefore chose to explore indirect, yet reproducible and robust, approaches for obtaining such information.
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Section 5 is dedicated to outlining a robust approach for 3D localization of the moving objects.
In the following, the application of the mentioned robust approach for our problem is represented.
Therefore, in the next chapter, an alternative M robust approach for generating VFF adaptively is proposed.
Chemoenzymatic glycoengineering is a robust approach for remodeling of IgG-Fc glycoforms.
This method might be considered as a robust approach for clinical applications.
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