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To verify the accuracy and validity of the finite-element modeling under lateral cyclic loading, the experimental test results of a previously published test specimen by Chang et al. (2012) were used and compared with the numerical results obtained from material and geometric nonlinear static analysis for calibration of analyses.
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The results of the analytical model exhibit an excellent agreement with the previously published test data both for thin and thick plate geometries and even in highly twisted configurations.
Finally, in an attempt to increase the specificity of the previously published test tool for identification of herds with poor welfare [ 7], this was combined with the currently identified test set to identify herds with good welfare, increasing the possibility to more correctly distinguish between herds with truly, according to the field assessment, good or poor welfare.
Numerical results for previously published test cases are presented to demonstrate attitude estimation accuracy.
In general, soft pivot model predictions are closely predicted when compared to the previously published test data.
An analytical model is developed to predict the mechanical behavior of confined concrete columns, and validated using previously published test results.
Using previously published test cases on NH3 oxidation, we demonstrate that despite of the reduced storage requirements and faster interpolation times, reduced Hermite interpolation achieves the same interpolation accuracy as conventional full tensor product splines.
Although we were able to recreate higher performance runs for MetaPhlAn on their previously published test sets, MetaPhlAn's lower performance on the PhymmBL test suggests that it may be more difficult to do both taxonomic identification and relative abundance estimation when microbial content consists exclusively of exceptionally low per genome coverage.
Analyses have been carried out on a total of 302 previously published tests using a nonparametric regression procedure known as multivariate adaptive regression splines (MARS), to assess the capacity energy required to trigger liquefaction in sand and silty sands.
Analyses have been carried out on a total of 405 previously published tests using back-propagation neural networks, to assess the capacity energy required to trigger liquefaction in sand and silty sands.
Importantly, while these pathway signatures have previously been validated [ 2], the model by model pathway predictions shown in Table 2 are highly consistent with previously published tests.
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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