Evidence of shape variation in wild Tor Mahseer ( Tor tor ) from Indian Rivers

2021 ◽  
Author(s):  
Arvind Kumar Dwivedi
Keyword(s):  
Shape Variation ◽  
Indian Rivers ◽  
Tor Tor

Learning body shape variation in physics-based characters

2019 ◽  
Vol 38 (6) ◽  
pp. 1-12 ◽  
Author(s):  
Jungdam Won ◽  
Jehee Lee
Keyword(s):  
Body Shape ◽  
Shape Variation

The assessment of the impact of mask pattern shape variation on the OPC-modeling by using SEM-Contours from wafer and mask

2011 ◽  
Author(s):  
Daisuke Hibino ◽  
Yutaka Hojyo ◽  
Hiroyuki Shindo ◽  
Thuy Do ◽  
Aasutosh Dave ◽  
...  
Keyword(s):  
Mask Pattern ◽  
Shape Variation ◽  
Pattern Shape ◽  
The Impact

scholarly journals Exploring palatal and dental shape variation with 3D shape analysis and geometric deep learning

2021 ◽  
Author(s):  
Nele Nauwelaers ◽  
Harold Matthews ◽  
Yi Fan ◽  
Balder Croquet ◽  
Hanne Hoskens ◽  
...  
Keyword(s):  
Deep Learning ◽  
Shape Analysis ◽  
Shape Variation ◽  
3D Shape ◽  
3D Shape Analysis

scholarly journals A developmentally descriptive method for quantifying shape in gastropod shells

2020 ◽  
Vol 17 (163) ◽  
pp. 20190721
Author(s):  
J. Larsson ◽  
A. M. Westram ◽  
S. Bengmark ◽  
T. Lundh ◽  
R. K. Butlin
Keyword(s):  
Empirical Studies ◽  
Three Dimensional ◽  
Shell Shape ◽  
Large Set ◽  
Littorina Saxatilis ◽  
Shape Variation ◽  
Gastropod Shell ◽  
Geometric Morphometric ◽  
Wide Range ◽  
Descriptive Method

The growth of snail shells can be described by simple mathematical rules. Variation in a few parameters can explain much of the diversity of shell shapes seen in nature. However, empirical studies of gastropod shell shape variation typically use geometric morphometric approaches, which do not capture this growth pattern. We have developed a way to infer a set of developmentally descriptive shape parameters based on three-dimensional logarithmic helicospiral growth and using landmarks from two-dimensional shell images as input. We demonstrate the utility of this approach, and compare it to the geometric morphometric approach, using a large set of Littorina saxatilis shells in which locally adapted populations differ in shape. Our method can be modified easily to make it applicable to a wide range of shell forms, which would allow for investigations of the similarities and differences between and within many different species of gastropods.

scholarly journals Variation of the Three-Dimensional Femoral J-Curve in the Native Knee

2021 ◽  
Vol 11 (7) ◽  
pp. 592
Author(s):  
Sonja A. G. A. Grothues ◽  
Klaus Radermacher
Keyword(s):  
Geometric Parameter ◽  
Knee Kinematics ◽  
Size Variation ◽  
Principal Component ◽  
Parameter Analysis ◽  
Patient Specific ◽  
3D Analysis ◽  
Relative Location ◽  
Shape Variation ◽  
J Curve

The native femoral J-Curve is known to be a relevant determinant of knee biomechanics. Similarly, after total knee arthroplasty, the J-Curve of the femoral implant component is reported to have a high impact on knee kinematics. The shape of the native femoral J-Curve has previously been analyzed in 2D, however, the knee motion is not planar. In this study, we investigated the J-Curve in 3D by principal component analysis (PCA) and the resulting mean shapes and modes by geometric parameter analysis. Surface models of 90 cadaveric femora were available, 56 male, 32 female and two without respective information. After the translation to a bone-specific coordinate system, relevant contours of the femoral condyles were derived using virtual rotating cutting planes. For each derived contour, an extremum search was performed. The extremum points were used to define the 3D J-Curve of each condyle. Afterwards a PCA and a geometric parameter analysis were performed on the medial and lateral 3D J-Curves. The normalized measures of the mean shapes and the aspects of shape variation of the male and female 3D J-Curves were found to be similar. When considering both female and male J-Curves in a combined analysis, the first mode of the PCA primarily consisted of changes in size, highlighting size differences between female and male femora. Apart from changes in size, variation regarding aspect ratio, arc lengths, orientation, circularity, as well as regarding relative location of the 3D J-Curves was found. The results of this study are in agreement with those of previous 2D analyses on shape and shape variation of the femoral J-Curves. The presented 3D analysis highlights new aspects of shape variability, e.g., regarding curvature and relative location in the transversal plane. Finally, the analysis presented may support the design of (patient-specific) femoral implant components for TKA.

Human skin model capable of natural shape variation

1988 ◽  
Vol 3 (5) ◽  
pp. 265-271 ◽  
Author(s):  
Koji Komatsu
Keyword(s):  
Human Skin ◽  
Shape Variation ◽  
Skin Model

Morphometric discrimination of pelagic fish stocks challenged by variation in body condition

2017 ◽  
Vol 75 (2) ◽  
pp. 711-718
Author(s):  
George Geladakis ◽  
Nikolaos Nikolioudakis ◽  
George Koumoundouros ◽  
Stylianos Somarakis
Keyword(s):  
Body Condition ◽  
Prey Availability ◽  
Eastern Mediterranean ◽  
Morphological Differentiation ◽  
Shape Variation ◽  
Geometric Morphometric ◽  
Morphometric Characters ◽  
Mesozooplankton Biomass ◽  
Stock Discrimination ◽  
Principal Coordinates

Abstract Morphometric characters have traditionally been used to describe the population structure of fishes. Body shape variation, which is often environmentally induced, may provide a good record of short-term population structuring. However, factors unrelated to environmental or genetic influences on body morphology may complicate sampling and the use of morphometric features for stock discrimination. In the present study, we used geometric morphometric variables to compare the European sardine Sardina pilchardus putative stocks of the Aegean and Ionian Seas (eastern Mediterranean). Landmark data of fish collected at seven different sites were subjected to canonical analysis of principal coordinates (CAP). The average body condition of sardines from these sites was strongly and linearly related to corresponding scores along CAP1, the axis exhibiting the highest correlation with the morphometric data cloud. The average scores along CAP2 and CAP3 appeared to be linked to morphological differentiation related to temperature effects and prey availability (mesozooplankton biomass). Despite the primary and confounding effect of body condition, discrimination of different morphotypes corresponding to the Aegean and the Ionian Sea stocks was highly significant with 81% correct reallocations for the respective CAP model.

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