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However, these developed models for residual stress prediction are operational complexity, time-consuming and low prediction efficiency.
In addition, traditional models for residual biomass prediction were developed from dendrometric parameters (tree height, crown diameter, and diameter at breast height).
A maximum of 6.65 g/L residual biomass and 6.75 g/L PHB was obtained using optimized concentrations, representing 94 and 83% validity of the predicted models for residual biomass and PHB production, respectively.
Various models for residual unexplained variability (RUV) were also tested.
The method was based on log-linear models for residual and individual variances expressed as functions of explanatory variables.
A proportional and combined additive and proportional models for residual variability for pharmacokinetic observations were evaluated (Equations 8 and 9).
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A predictive model for residual stresses induced in a laser hardened workpiece of AISI 4140 steel with no melting has been developed and experimentally verified.
A stochastic model for residual strength is developed and time-dependent methods are employed to quantify the probability of failure so that the time for the pipeline to be failed and hence requiring repairs can be determined.
A proportional model for residual variability was used.
Hence, the impact of using a different constitutive model for residual stress could be significant.
A reaction norm model to estimate genetic variance for macro-environmental sensitivity was combined with a structural model for residual variance to estimate genetic variance for micro-environmental sensitivity using a double hierarchical generalized linear model in ASReml.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com