The literature proposes several methods for pose variability problems.
Key steps in this process are described, including the selection of starting genes, methods for introducing variability, the choice of a heterologous expression system, ways to identify improved variants, and methods for combining improved variants to achieve the desired activity.
Strategies are described for microstructure-sensitive computational methods for estimating variability of high cycle fatigue (HCF) crack formation and early growth in metallic polycrystals to support design of fatigue resistant alloys.
The aim of this study was to develop a theoretic analysis of the cepstral peak (CP), to compare several CP software programs, and to propose methods for reducing variability in CP estimation.
Further research might consider improved methods for estimating variability; non-parametric methods for estimating protection curves might also be explored.
In lieu of undertaking probabilistic methods for exploring variability and/or uncertainty in the input values (due to limited data availability), we developed a simple database tool (eRISK); available from the authors or via the CAREX Canada website on request [ 62].
The PCA method looks for variability in the data and sorts the information of the data in order of importance, hence, PCA has been considered appropriate to measure the feature's relevance.
Combined analysis of the SNP effects across our sample collections was performed with the Mantel–Haenszel approach, which is a method correcting for variability in allele frequencies between collections provided that the effect sizes (that is, ORs) are not significantly divergent.
This method accounts for variability in stride length and quickness.
By way of a recently developed attribution metric, this study is aimed at developing a method for analysing variability in model inputs together with model structure variability to quantify their relative contributions in typical hydrological modelling applications.
