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In addition to the predictions using Floquet Lyapunov theory, further instability regions based on first and higher approximations are identified.
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By varying a scaling parameter, approximations could be systematically obtained and several existing approximations were identified as particular cases of the proposed methodology.
In each iteration step, the approximation models are constructed by the response surface approximations with the samples which are obtained from the design of experiments, and a Pareto optimal set predicted by the approximations is identified through a multi-objective genetic algorithm.
Here, the parameters that govern the behavior of the transverse stiffeners are identified theoretically using the column buckling approximation.
We calculated population isolation by the two approximations that were identified in a previous study (Vogeli et al.
Four candidate approximation functions were identified and their approximation performance analyzed.
Some of these steps introduce approximations, which can be identified from changes in the set of conditional independence (CI) assertions of a network.
Layer 1a is subjacent to the pia and layer 1c is above layer 2. Layer 1b is identified by approximation as the middle sublayer.
A potential selectivity increase towards the linear aldehyde of 35% compared to a reference case from literature is identified and an approximation of the best reaction route is proposed.
The differentially expressed genes were identified using a Welch approximation based t-test (package stats, version 2.6.2) followed by a Benjamini-Hochberg correction procedure.
Importantly, while E-1 haplotype is a good approximation, the causative SNP for the renal disease has not been identified [1], [2].
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com