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@article{fds346319,
Author = {Shan, S and Kovalsky, SZ and Winchester, JM and Boyer, DM and Daubechies, I},
Title = {ariaDNE: A robustly implemented algorithm for Dirichlet
energy of the normal},
Journal = {Methods in Ecology and Evolution},
Volume = {10},
Number = {4},
Pages = {541-552},
Year = {2019},
Month = {April},
url = {http://dx.doi.org/10.1111/2041-210X.13148},
Abstract = {© 2019 The Authors. Methods in Ecology and Evolution ©
2019 British Ecological Society Shape characterizers are
metrics that quantify aspects of the overall geometry of a
three-dimensional (3D) digital surface. When computed for
biological objects, the values of a shape characterizer are
largely independent of homology interpretations and often
contain a strong ecological and functional signal. Thus,
shape characterizers are useful for understanding
evolutionary processes. Dirichlet normal energy (DNE) is a
widely used shape characterizer in morphological studies.
Recent studies found that DNE is sensitive to various
procedures for preparing 3D mesh from raw scan data, raising
concerns regarding comparability and objectivity when
utilizing DNE in morphological research. We provide a
robustly implemented algorithm for computing the Dirichlet
energy of the normal (ariaDNE) on 3D meshes. We show through
simulation that the effects of preparation-related mesh
surface attributes, such as triangle count, mesh
representation, noise, smoothing and boundary triangles, are
much more limited on ariaDNE than DNE. Furthermore, ariaDNE
retains the potential of DNE for biological studies,
illustrated by its effectiveness in differentiating species
by dietary preferences. Use of ariaDNE can dramatically
enhance the assessment of the ecological aspects of
morphological variation by its stability under different 3D
model acquisition methods and preparation procedure. Towards
this goal, we provide scripts for computing ariaDNE and
ariaDNE values for specimens used in previously published
DNE analyses.},
Doi = {10.1111/2041-210X.13148},
Key = {fds346319}
}
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