Sentence examples for model significantly increases from inspiring English sources

The inclusion of dynamic load model significantly increases the nonlinearity of the system.

We demonstrate that including volumetric deformations in the material model significantly increases the accuracy of the predictions.

It is shown that the proposed material model significantly increases the accuracy of the finite element predictions compared to the standard orthotropic linear material model with almost identical computation times.

However, including breadth of gene expression into the regression model significantly increases its fit (table 3)—possibly because expression breadth is only moderately correlated with transcript levels (supplementary table S4, Supplementary Material online).

Evidence to support a protective role for estrogen in SS can be found in a recent study in mice where ovariectomy of adult females (modeling menopause) in a SS model significantly increased inflammation in the lacrimal (tear) gland [ 69].

Finally, the measured initial imperfections are included in the model significantly increasing the numerical experimental correlation.

The extended version of the model significantly increased the proportion of variance explained to 54.3% and 38.8% of variance in intention and behaviour respectively.

Its addition as an explanatory variable in a built-up prediction model significantly increased the prediction power, which makes it a useful variable in urban land use change scenarios.

In this study, in-vivo examinations of the use of newly designed PCL-NGF/TF conduits to promote the generation of nerves in a defective rat model significantly increased the gastrocnemius muscle mass, and led to the successful regeneration of nerves that bridged a 12 mm long defected gap of nerves in rats.

The contact force history curves, intra- and inter-laminar damage evolution process are found to be strain rate dependent, and thus the numerical errors predicted by the strain-rate-independent damage model significantly increase with the increment of the applied impact energy, which is unacceptable in practice for LVI with relatively high impact energies.

The age-period-cohort model significantly increased the fit for the model for both sexes (P > 0.001).