Subsequent modes of the statistical shape models of the individual bones characterized shape variation within the processes.
Additionally, they generated a population of random two-locus models within which they characterized "shape-based" classes of epistatic models.
Using landmark-based geometric morphometrics, we characterized shape variation in parental species, F1 hybrids, and backcross progeny and show that the main axis of shape variation within the backcross population matches the interspecific variation between parental species.
To characterize shape and smoothness of such surfaces, we track a sequence of quadratic functions anchored in a fixed coordinate system.
Applying general principles derived in [Computer Aided Geometric Design, doi 10.1016/j.cagd.2004.04.006, in press], this paper characterizes shape near such points for the subdivision schemes devised by Catmull and Clark and by Loop.
In contrast to size, shape is an inherently multidimensional space and we used Procrustes superimposition to characterize shape variation.
Homologous landmarks (i.e. the points that are aligned to match corresponding features in the shape) can be used to characterize shape and shape variations with the aid of a principal component analysis, or similar technique.
We are not aware of other work that uses a similar approach to characterize shape and intensity differences of functional data.
It has been successfully employed in characterizing shape and volume abnormalities of the hippocampus in neuropsychiatric disorders such as schizophrenia, dementia of the Alzheimer type, depression and epilepsy.
Particle shape was characterized by shape indices defined by Fourier analysis of particle outlines measured over the corresponding cross-sections of the green tape.
In this way, FMD can be characterized as being shaped by 'high-level' beliefs about symptoms.
