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On the other hand, 2D numerical models always under predicted the shear modulus values at all simulation temperatures and loading frequencies because the reduced microstructure for the 2D models decreased the accuracy of numerical predictions.
The facet load in the implanted models decreased the most in type 3 (71%), followed by type 2 (31%) and type 1 (23%).
Interestingly, the inclusion of HRT in the models decreased the strength of these associations, which indicates an effect of menopause and a protective effect of estrogen therapy, as previously shown (Garrido Latorre et al. 2003; Korrick et al. 2002; Nash et al. 2004; Vahter et al. 2004; Webber et al. 1995).
Excluding city and area of residence from the models decreased the estimates in men [model 1, 21.7% (95% CI, 7.6 to 37.7%) increase in hs-CRP and 2.64% (95% CI, 0.1to 5.2%) increase in fibrinogen; model 2, 14.0% (95% CI, 1.7 to 27.8%) increase in hs-CRP and 1.6%9595% CI, −0.8 to 4.0%) increase in fibrinogen], whereas it had an inconsistent effect in women.
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As indicated before, more detailed models decrease the uncertainties in modeling.
These could falsely lower the apparent influence of parental history in the models, decreasing the magnitude of resulting risk estimates.
As already discussed, the incorporation of a mucus layer in gut epithelial models decreases the translocation (Walczak et al. 2014).
Finally, deletion of Pten, as in many other models, decreases the age of tumor onset and potentiates the development of high-grade lesions (84).
The mixed model decreased the maximum values of each single model.
Several rounds of smoothing and remeshing the model decreased the number of triangles to less than 32,000.
The overall gain in the training model decreased the most when slope was withdrawn from calculations, indicating that this variable provides a substantial amount of useful information that is not already contained in the other variables (Fig. 2).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com