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opencc-by-4.0Dec 2022View details →

Fig. 4. Mean outline shape constructed from 10 in Identification and Distribution of Wedge Clams (Donacidae: Bivalvia) in Thailand by Geometric Morphometric and Molecular Analysis.

Fig. 4. Mean outline shape constructed from 10 harmonics of elliptic Fourier analysis of eight Donax species from Thai waters: Donax (Latona) cuneatus (A), D. (Latona) solidus (B), D. (Latona) faba (C), D. (Deltachion) spinosus (D), D. (Dentilatona) incarnatus (E), D. (Deltachion) bruneirufi (F), D. (Deltachion) semisulcatus semisulcatus (G) and D. (Hecuba) scortum (H).

opencc-by-4.0May 2016View details →

Fig. 2 in Does size matter for horny beetles? A geometric morphometric analysis of interspecific and intersexual size and shape variation in Colophon haughtoni Barnard, 1929, and C. kawaii Mizukami, 1997 (Coleoptera: Lucanidae)

Fig. 2 Landmarks used for geometric morphometric analysis of Colophon specimens: a male C. haughtoni mandible; b male C. kawaii mandible; c male C. haughtoni head; d female head; e pronotum; f elytron. Scale bars represent 2 mm

opencc-by-4.0May 2016View details →

Fig. 1 Adult Colophon beetles. a Colophon haughtoni. b in Does size matter for horny beetles? A geometric morphometric analysis of interspecific and intersexual size and shape variation in Colophon haughtoni Barnard, 1929, and C. kawaii Mizukami, 1997 (Coleoptera: Lucanidae)

Fig. 1 Adult Colophon beetles. a Colophon haughtoni. b Ventral photograph of C. haughtoni head showing (1) gena, (2) mandible base, (3) ventral process, (4) dorsal process and (5) apex of the mandible. c Ventral view of C. kawaii head. Scale bars represent 4 mm (a) and 2 mm (b, c). Photographs by H.J. de Klerk

opencc-by-4.0Apr 2013View details →

Synthetic Data for Neutrophil Analysis: Sets with irregular shapes and Poisson noise

Synthetic Datasets with irregular shapes and Poisson noise. Part of the PhagoSight neutrophil tracking and analysis package (Henry, et al., PLOS ONE, 2013):   https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0072636 http://www.phagosight.org https://github.com/phagosight/phagosight   A series of synthetic data sets that reproduce different behaviour characteristics of migrating neutrophils were generated in MATLAB. The data sets consisted of six artificial neutrophils that travelled along paths that presented different conditions of tortuosity, times to activation and proximity to other neutrophils during 98 time frames. Numerous data sets of neutrophils in zebrafish were carefully observed before setting the characteristics. Six trajectories were manually determined by setting the row, column positions of the centroids at every time point for 98 time frames. Each trajectory was designed so that it would represent different neutrophil behaviours: some trajectories were very oriented and had movements with uniform distance between time frames, whilst others were less uniform and would move at different velocities, some were tortuous whilst others were straight. The trajectories of cells 1 and 2 collided several times in the second half of the time frames whilst cells 3 and 4 collided at the beginning of the movement. Cell 6 migrated without meandering and then stopped at the end (which represents the wound area of an inflammation-based experiment) whilst 5 presented a delayed activation.  Each time frame consisted of 11 slices of z-stack each with 275 x 275 pixels, where the neutrophils were formed by irregular shapes (sum of Gaussians) and Poisson Noise (check the corresponding sets with regular shapes, i.e. Gaussians with Gaussian noise plus another set with a single large neutrophil and Poisson noise) distributions of higher intensities than the background. The orientation of the Poisson varied according to the displacement of the artificial neutrophils, i.e.they were round when the cells were static, or elongated when in movement. The tracks with the Shapes were saved as the gold standard and five different data sets were generated by adding varying levels of white Poisson noise resulting in data sets with distributions with increasing similarity between the neutrophils and the background reflected by the decreasing values of the Bhattacharyya Distance (1.61, 1.25, 1, 0.66, 0.45) as defined by Coleman 1979.   Files corresponding to the sets with irregular shapes and Poisson noise (noise increases from 1 to 5): <ul> <li>    x,y,t trajectories    ThreeDTracks</li> <li>    Ground Truth       syntheticData_P_mat_La </li> <li>    First data set         syntheticData_P1_mat_Re</li> <li>    Second data set     syntheticData_P2_mat_Re</li> <li>    Third data set       syntheticData_P3_mat_Re</li> <li>    Fourth data set     syntheticData_P4_mat_Re</li> <li>    Fifth data set        syntheticData_P5_mat_Re</li> </ul> Corresponding GIF files are also included as illustrations of the cells in motion.   Main Reference: <a href="https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0072636">PhagoSight: An Open-Source MATLAB® Package for the Analysis of Fluorescent Neutrophil and Macrophage Migration in a Zebrafish Model </a> Henry KM, Pase L, Ramos-Lopez CF, Lieschke GJ, Renshaw SA, Reyes-Aldasoro CC. (2013) PhagoSight: An Open-Source MATLAB® Package for the Analysis of Fluorescent Neutrophil and Macrophage Migration in a Zebrafish Model. PLOS ONE 8(8): e72636. <a href="https://doi.org/10.1371/journal.pone.0072636">https://doi.org/10.1371/journal.pone.0072636</a>

opencc-by-4.0Apr 2013View details →

Synthetic Data for Neutrophil Analysis: Sets with regular shapes and Gaussian noise

Synthetic Datasets with regular shapes and Gaussian noise. Part of the PhagoSight neutrophil tracking and analysis package (Henry, et al., PLOS ONE, 2013):   https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0072636 http://www.phagosight.org https://github.com/phagosight/phagosight   A series of synthetic data sets that reproduce different behaviour characteristics of migrating neutrophils were generated in MATLAB. The data sets consisted of six artificial neutrophils that travelled along paths that presented different conditions of tortuosity, times to activation and proximity to other neutrophils during 98 time frames. Numerous data sets of neutrophils in zebrafish were carefully observed before setting the characteristics. Six trajectories were manually determined by setting the row, column positions of the centroids at every time point for 98 time frames. Each trajectory was designed so that it would represent different neutrophil behaviours: some trajectories were very oriented and had movements with uniform distance between time frames, whilst others were less uniform and would move at different velocities, some were tortuous whilst others were straight. The trajectories of cells 1 and 2 collided several times in the second half of the time frames whilst cells 3 and 4 collided at the beginning of the movement. Cell 6 migrated without meandering and then stopped at the end (which represents the wound area of an inflammation-based experiment) whilst 5 presented a delayed activation.  Each time frame consisted of 11 slices of z-stack each with 275 x 275 pixels, where the neutrophils were formed by Gaussian distributions of higher intensities than the background and Gaussian noise (check the corresponding irregular shapes with Poisson noise plus another set with a single large neutrophil and Poisson noise). The orientation of the Gaussians varied according to the displacement of the artificial neutrophils, i.e.they were round when the cells were static, or elongated when in movement. The tracks with the Gaussians were saved as the gold standard and five different data sets were generated by adding varying levels of white Gaussian noise resulting in data sets with distributions with increasing similarity between the neutrophils and the background reflected by the decreasing values of the Bhattacharyya Distance (1.61, 1.25, 1, 0.66, 0.45) as defined by Coleman 1979.   Files corresponding to the sets with irregular shapes and Poisson noise (noise increases from 1 to 6): <ul> <li>    x,y,t trajectories    ThreeDTracks</li> <li>    Ground Truth       syntheticData0_mat_Re </li> <li>    First data set         syntheticData1_mat_Re</li> <li>    Second data set     syntheticData2_mat_Re</li> <li>    Third data set       syntheticData3_mat_Re</li> <li>    Fourth data set     syntheticData4_mat_Re</li> <li>    Fifth data set         syntheticData5_mat_Re</li> <li>    Sixth data set         syntheticData6_mat_Re</li> </ul>   Corresponding GIF files are also included as illustrations of the cells in motion.   Main Reference: <a href="https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0072636">PhagoSight: An Open-Source MATLAB® Package for the Analysis of Fluorescent Neutrophil and Macrophage Migration in a Zebrafish Model </a> Henry KM, Pase L, Ramos-Lopez CF, Lieschke GJ, Renshaw SA, Reyes-Aldasoro CC. (2013) PhagoSight: An Open-Source MATLAB® Package for the Analysis of Fluorescent Neutrophil and Macrophage Migration in a Zebrafish Model. PLOS ONE 8(8): e72636. <a href="https://doi.org/10.1371/journal.pone.0072636">https://doi.org/10.1371/journal.pone.0072636</a>

opencc-by-4.0Mar 2023View details →

Figure 1 in The importance of shape analysis of the first upper molar in the separation of two subspecies of the Hazel dormouse (Muscardinus avellanarius (Linnaeus, 1758)) in Northern Anatolia

Figure 1. Worldwide distribution of Muscardinus avellanarius (a) and trapped localities in Northern Anatolia, Turkey (b) [Number of specimens: in the West; Bolu = 23, Bursa = 3, Düzce = 6, and in the East; Giresun = 4, Ordu = 6, Trabzon = 14].

Figure 8 in Discrete aggregate analysis of ovoid egg shapes in various bird species

Figure 8. Golden proportion manifested in the shape of bird eggs: 1, 13, 25, 37, ovoid profiles; 2, 14, 26, 38, ovoid profile profiles for comparison with bird eggs. Bird eggs: 3 – Alectoris chukar; 4 – Glareola pratincola; 5 – Sturnus vulgaris; 6 – Sylvia nisoria; 7 – Milvus milvus; 8 – Buteo buteo; 9 – Falco cherrug; 10 – Lanius collurio; 11 - Perdix perdix; 12 – Garrulus glandarius; 15 – Sylvia communis; 16 – Perdix perdix; 17 – Numida meleagris; 18 – Alectoris chukar; 19 – Garrulus glandarius; 20 – Coccothraustes coccothraustes; 21 – Larus melanocephalus; 22 – Dendrocopos major; 23 – Picus canus; 24 – Jynx torquilla; 27 – Luscinia svecica; 28 – Oenanthe oenanthe; 29 – Turdus merula; 30– Picus canus; 31– Aquila pomarina; 32 – Perdix perdix; 33 – Lanius collurio; 34 – Anthus trivialis; 35 – Jynx torquilla; 36– Hieraaetus pennatus; 39 – Turdus philomelos; 40 – Oriolus oriolus; 41 – Ficedula albicollis; 42 – Dendrocopos leucotos; 43 – Delichon urbica; 44 – Coccothraustes coccothraustes; 45 – Garrulus glandarius; 46 – Corvus frugilegus; 47 – Turdus merula; 48 – Gallinula chloropus.

Figure 5 in Discrete aggregate analysis of ovoid egg shapes in various bird species

Figure 5. Comparison of geometric standards (1, 7, 13, 19, 25, 31) with profiles of real eggs: 2 – Athene noctua; 3 – Neophron percnopterus; 4 – Merops apiaster; 5 – Phylloscopus sibilatrix; 6 – Alcedo atthis; 8 – Falco vespertinus; 9 – Aegithalos caudatus; 10 – Merops apiaster; 11 – Ficedula hypoleuca; 12 – Jynx torquilla; 14 – Sterna hirundo; 15 – Buteo buteo; 16 – Falco cherrug; 17 – Upupa epops; 18 – Dendrocopos major; 20 – Picus canus; 21 – Perdix perdix; 22 – Phasianus colchicus; 23 – Corvus monedula; 24 – Coccothraustes coccothraustes; 26 – Limosa limosa; 27 – Pica pica; 28 – Luscinia luscinia; 29 – Corvus frugilegus; 30 – Alca torda; 32 – Uria aalge; 33 – Numenius arquata; 34 – Recurvirostra avosetta; 35 – Alca torda; 36 – Corvus corax.

Figure 3 in Discrete aggregate analysis of ovoid egg shapes in various bird species

Figure 3. Discrete variants of combinations of the lateral arcs of the ovoid profiles (matrices): a - 0.75D; b -1.0 D; c - 1.25D; d - 1.5D; e - 1.75D.

Figure 7 in Discrete aggregate analysis of ovoid egg shapes in various bird species

Figure 7. Construction of ovoid profiles with golden ratio: a - construction of ovoids with doubling of radii of circles; b - construction of ovoids with increasing of radii of circles by F=1,618; c - getting golden section by a combination of four circles; d - construction of ovoids with golden section by pentagons.

Figure 11 in Discrete aggregate analysis of ovoid egg shapes in various bird species

Figure 11. Schematics for calculating the complementarity indices of avian eggs: 1, 2, 9, 10 - scheme and geometric profile of eggs with a complementarity index close to unity (rc=ri=(L–D)/2); 3 – Podiceps cristatus; 4 – Cygnus olor; 5 – Egretta alba; 6 – Pelecanus crispus; 7 – Egretta garzetta; 8 – Mergus serrator; 11 – Anser anser; 12 – Casuarius casuarius; 13 – Porzana parva; 14 – Phalacrocorax carbo; 15 – Podiceps nigricollis; 16 – Ardea cinerea; 17, 18 - scheme and geometric profile of eggs with a complementarity index close to 1,333 (rc=ri=lipz=L/3); 19 – Pygoscelis papua; 20 – Nyctea scandiaca; 21 – Strutio camelus; 22 – Dendrocopos minor; 23 – Alcedo atthis; 24 – Buteo chemilasius; 25 – Jynx torquilla; 26 – Asio otus; 27 – Streptopelia decaocto; 28 – Merops apiaster; 29 – Asio flammeus; 30 – Aquila pomarina; 31 – Bubo bubo; 32 – Columba oenas; 33, 34 – scheme and geometric profile of eggs with a complementarity index greater than 1,5 (rc=ri/lipz˃1,5); 35 – Athene noctua; 36 – Otus scops; 37 – Otus brucei; 38 – Merops apiaster; 39 – Strix aluco; 40 – Pygoscelis papua; 41 – Alcedo atthis; 42 – Merops superciliosus; 43 – Milvus migrans; 44 – Asio flammeus; 45 – Strutio camelus; 46 – Hieraaetus pennatus; 47 – Strix aluco; 48 – Accipiter nisus.

Figure 2 in Discrete aggregate analysis of ovoid egg shapes in various bird species

Figure 2. Relationship between the ovoid constructs with the diagonals of the square and the double square.

Figure 6 in Discrete aggregate analysis of ovoid egg shapes in various bird species

Figure 6. Ovoid profiles (a) Erkoca, 2021; (b) Rojas, 2002; (c) Dixon, 1987; (d) Petrović et al., 2010.

Figure 10 in Discrete aggregate analysis of ovoid egg shapes in various bird species

Figure 10. Schemes of taking measurements to calculate wurfs for eggs of different types: a - true ovoids; b, c - symmetric and asymmetric pseudoovoids.

Figure 1 in Discrete aggregate analysis of ovoid egg shapes in various bird species

Figure 1. Geometric constructor figures for constructing ovoids: (a) Vesica piscis with circles inside, (b) A fragment of the matrix to obtain ovoids.

FIGURE 5 in Otolith shape analysis supports three cryptic species in the Stellifer punctatissimus complex (Acanthuriformes: Sciaenidae)

FIGURE 5 | Otolith's contour reconstruction (Fourier). GM = Stellifer gomezi, MN = S. menezesi, PC = S. punctatissimus.

FIGURE 7 in Otolith shape analysis supports three cryptic species in the Stellifer punctatissimus complex (Acanthuriformes: Sciaenidae)

FIGURE 7 | A. Principal Component Analysis (PCA) of sulcus acusticus's shape variation using Procrustes residual of geometric morphometric method. Shape variation in each principal component (PC1 in the horizontal and PC2 in the vertical) in the upper left corner. B. Pairwise shape comparisons; GM = Stellifer gomezi, MN = S. menezesi, PC = S. punctatissimus.

FIGURE 4 in Otolith shape analysis supports three cryptic species in the Stellifer punctatissimus complex (Acanthuriformes: Sciaenidae)

FIGURE 4 | A. Scatterplot of otolith weight using a LOESS curve fitting. B. Scatterplot of rectangularity index. GM = Stellifer gomezi, MN = S. menezesi, PC = S. punctatissimus.

FIGURE 3 in Otolith shape analysis supports three cryptic species in the Stellifer punctatissimus complex (Acanthuriformes: Sciaenidae)

FIGURE 3 | Otoliths of Stellifer punctatissimus complex. A. S. gomezi. B. S. menezesi. C. S. punctatissimus. Left: inner face; Middle: inset of the ostium; Right: dorsal profile. Arrow indicates spout-like groove; asterisk indicates projection on the outer face. Scale bars = 1 mm.

FIGURE 2 in Otolith shape analysis supports three cryptic species in the Stellifer punctatissimus complex (Acanthuriformes: Sciaenidae)

FIGURE 2 | Illustration of representative sagitta otolith with key anatomical features, based on an average shape specimen. Filled dots = landmarks, empty circles = semilandmarks; A = anterior, M = medial, D = dorsal (asterisk: sulcus acusticus = ostium + cauda).