The geometrical and electromagnetic characteristics are specified in the input files for each wall/object, i.e., vertex coordinates, thickness, complex permittivity, and the parameters of the diffuse scattering model.
However, the strong correlation between convexity and R1 survives the addition of vertex-wise thickness as a covariate.
We chose vertex-based thickness analyses over conventional VBM and DBM, as the approach shows relative sensitivity to subtle cortical effects (see Hutton et al. 2009; Scanlon et al. 2011).
Whole-brain cortical thickness (vertex by vertex) did not differ between groups.
The effects of subtended angle, semi-vertex angle, length, thickness and radius of the panel on the buckling load and mode are investigated.
Furthermore, correlations between the vertex-wise cortical thickness and the sleep quality (measured as PSQI score, higher PSQI indicates lower sleep quality) are shown in Figure 1(b).
For the comparison of whole brain cortical thickness, the vertex-by-vertex analysis was used, and means of cortical thickness were compared between groups using a two-tailed t test; cortical thickness was modeled as a function of group controlling for age and sex.
The guide vanes are positioned between two conical surfaces with a common vertex and have constant thickness distribution, except close to the leading and the trailing edges.
A CT scan of the brain was performed from the base of the skull to the vertex at a slice thickness of 2.5 mm for the posterior cranial fossa and 5 mm for the supra-tentorial compartment.
To provide a complementary perspective of our finding, a surface-based whole brain analysis using FreeSurfer's Qdec (version 1.4) was performed by fitting a between-subject GLM at each surface vertex to compare cortical thickness between the groups (uncorrected, p<0.001).
