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opencc-by-4.0Feb 2023View details →

Figure 4 in The dentition of the extinct megamouth shark, (Lamniformes: Megachasmidae), from southern California, USA, based on geometric morphometrics

Figure 4. Three reconstructed dentitions of Megachasma applegatei under three different assumptions (see text for detail). A. Artificial dentition based on Odontaspis ferox as a model. B. Artificial dentition depicted as intermediate between O. ferox and M. pelagios. C. Artificial dentition based on M. pelagios as a model. Scale bar = 5 mm (note: each scale bar applies to each respective dentition consisting of teeth with digitally adjusted sizes [see text]).

FIGURE 2 in Geometric morphometric assessment of Guanshan trilobites (Yunnan Province, China) reveals a limited diversity of palaeolenid taxa

FIGURE 2. Reconstruction of the Palaeolenus douvilei cephalon showing chosen landmarks and semilandmarks. Blue outlines show semilandmarks placement. White arrows indicate semilandmarks trajectory. The black lines show the orientations which are following Whittington et al. (1997). Abbreviations: sag. – sagittal; tr. – transverse; exs. – exsagittal.

FIGURE 3 in Geometric morphometric assessment of Guanshan trilobites (Yunnan Province, China) reveals a limited diversity of palaeolenid taxa

FIGURE 3. Plots of principal component analyses. A. Plot of PC1-PC2 space where two main clusters are identified. Cluster in more positive PC1 space contains Palaeolenus douvillei specimens and the cluster in more negative PC1 space contains Megapalaeolenus deprati specimens. Thin-plate spline indicates the extreme shape for each axis. B. Plot of PC2-PC3 space showing no distinct clusters. C. Plot of PC1-PC3 space showing two distinct clusters of the P. douvillei and M. deprati. Clusters are all bound by convex hulls of proposed taxa.

FIGURE 1. Geological and biostratigraphical maps. A in Geometric morphometric assessment of Guanshan trilobites (Yunnan Province, China) reveals a limited diversity of palaeolenid taxa

FIGURE 1. Geological and biostratigraphical maps. A. The Shitangshan Section showing approximate stratigraphic distribution of Redlichia mansuyi and Redlichia mai (modified from Hu et al. 2010). B–D. Studied sections showing their approximate stratigraphic levels respectively in Wulongqing Formation. B. Huanglongqing Section. C. Longbaoshan Section. D. Xinglongcun Section. E. Map of Kunming showing the localities of studied sections. The red lines with arrows showing approximate sampling interbeds in each section.

FIGURE 6 in Geometric morphometric assessment of Guanshan trilobites (Yunnan Province, China) reveals a limited diversity of palaeolenid taxa

FIGURE 6. Articulated and disarticulated specimens of Megapalaeolenus deprati from the Huanglongqing Section. A. HLQ-39A. B. HLQ-19. C. HLQ-37. D. HLQ-50. E. HLQ-13. F. HLQ-33. Scale bars equal 5 mm.

FIGURE 5 in Geometric morphometric assessment of Guanshan trilobites (Yunnan Province, China) reveals a limited diversity of palaeolenid taxa

FIGURE 5. Articulated specimens of Palaeolenus douvillei from the Longbaoshan and Xinglongcun sections. A. LBS- 548. B. XLC-1960. C. LBS-566. D. XLC-2000A. E. LBS-661A. F. LBS-151. G. XLC-0904. H. LBS-629. I. LBS-177. Scale bars equal 3 mm. White arrows indicate the thorax-pygidium boundary.

FIGURE 4 in Geometric morphometric assessment of Guanshan trilobites (Yunnan Province, China) reveals a limited diversity of palaeolenid taxa

FIGURE 4. The log-centroid size against regressed Procrustes ANOVA scores plot indicates the distinct clusters of the Palaeolenus douvillei and Megapalaeolenus deprati. Clusters bound by convex hulls of taxa. Hollow circles around points indicate specimens with 13 tergites and hollow pentagons around points indicate specimens with at least 14 tergites.

Fig. 7 in Morphological disparity of early ammonoids: A geometric morphometric approach to investigate conch geometry

Fig. 7. Evolution of the relative contribution of ammonoid superfamilies to diversity and disparity (mean squared Euclidean distance to the centroid) through the Early and Middle Devonian; based on the analysis of the whorl profiles. A. Relative contribution of ammonoid superfamilies to diversity (sampled-in-bin). B. Fluctuations of the mean squared Euclidean distance to the centroid (black line with grey area showing the confidence intervals computed after 1000 bootstraps) and sampled-in-bin diversity (blue bars). C. Relative contribution of ammonoid superfamilies to disparity (mean squared Euclidean distance to the centroid). See Fig. 2 for interval labels.

Fig. 9 in Morphological disparity of early ammonoids: A geometric morphometric approach to investigate conch geometry

Fig. 9. Evolution of the relative contribution of ammonoid superfamilies to diversity and disparity (mean squared Euclidean distance to the centroid) through the Early and Middle Devonian ammonoid zones (biozones numbered from 1 to 30, see Fig. 2); based on the analysis of the whorl profiles. A. Relative contribution of ammonoid superfamilies to diversity (sampled-in-bin). B. Fluctuations of the mean squared Euclidean distance to the centroid (black line with grey area showing the confidence intervals computed after 1000 bootstraps) and sampled-in-bin diversity (blue bars). C. Relative contribution of ammonoid superfamilies to disparity (mean squared Euclidean distance to the centroid).

Fig. 6 in Morphological disparity of early ammonoids: A geometric morphometric approach to investigate conch geometry

Fig. 6. Evolution of the morphospace occupation through the seven intervals constituting the Early and Middle Devonian, showing the distribution of ammonoid superfamilies; based on the analysis of the whorl profiles (on each diagram, the horizontal axis corresponds to PC1 and the vertical axis to PC2). See Fig. 2 for interval labels.

Fig. 11 in Morphological disparity of early ammonoids: A geometric morphometric approach to investigate conch geometry

Fig. 11. Variations of the convex hull area computed for PC1 and PC2, based on the analysis of the whorl profiles through the Early and Middle Devonian. Comparison of the measured values with the expected values given diversity, computed by applying the null model of Whalen et al. (2020). A. Fluctuations computed at the interval resolution. B. Fluctuations computed at the biozone resolution. See Fig. 2 for interval labels and biozones.

Fig. 5 in Morphological disparity of early ammonoids: A geometric morphometric approach to investigate conch geometry

Fig. 5. Diagrams showing the morphospace occupation observed for the three stages constituting the Early and Middle Devonian (A–C), with level contours and density curves; based on the analysis of the whorl profiles. The grey dots correspond to the data recorded for the entire studied time interval (Early and Middle Devonian); the black dots refer to the data recorded for each of the studied stage (respectively, Emsian, Eifelian, and Givetian). The colours refer to the density of the data in the morphospace; the red-yellowwhite gradient indicates the decreasing density of occupied areas. Compare also with density curves (in grey) above and to the right of the diagrams.

Fig. 4 in Morphological disparity of early ammonoids: A geometric morphometric approach to investigate conch geometry

Fig. 4. Morphospace occupation observed for the Early and Middle Devonian, based on the analysis of the whorl profiles, with representative examples of shapes. The first two axes explain 95.7% of the variance.

Fig. 3. Ammonoid morphology and dataset. A in Morphological disparity of early ammonoids: A geometric morphometric approach to investigate conch geometry

Fig. 3. Ammonoid morphology and dataset. A. Morphology of an ammonoid; as an example, the outline of the whorl profile taken at the maximum conch diameter is highlighted by a thick black line (modified from De Baets et al. 2010). B. Dataset analysed here; compilation of drawings of whorl profile outlines corresponding to Early and Middle Devonian ammonoids from Morocco.

Fig. 8 in Morphological disparity of early ammonoids: A geometric morphometric approach to investigate conch geometry

Fig. 8. Disparity and diversity fluctuations through the Early and Middle Devonian; based on the analysis of the whorl profiles. A. Sum of ranges (black line with grey area showing the confidence intervals) and sampled-in-bin diversity (blue bars). B. Sum of variances (black line with grey area showing the confidence intervals) and sampled-in-bin diversity (blue bars). C. Average displacement (black line with grey area showing the confidence intervals) and sampled-in-bin diversity (blue bars). Confidence intervals (error bars) are computed after 1000 bootstraps. See Fig. 2 for interval labels.

Fig. 1 in Morphological disparity of early ammonoids: A geometric morphometric approach to investigate conch geometry

Fig. 1. Simplified geological map of Morocco (modified from Klug 2002b). The square shows the area where Early and Middle Devonian ammonoids are reported (Tafilalt and Ma'der basins).

Fig. 2 in Morphological disparity of early ammonoids: A geometric morphometric approach to investigate conch geometry

Fig. 2. Stratigraphic scheme for the Early and Middle Devonian of the Anti-Atlas of Morocco, showing the distribution of superfamilies through time. Ammonoid biozonation from (Klug 2002a; Aboussalam and Becker 2011; Bockwinkel et al. 2015; Becker et al. 2019). Absolute ages from the Geological Time Scale v. 5.0 (Walker et al. 2018). "Sobolewia sp. nov." and "Afromaenioceras sp. nov" have been introduced by Becker et al. (2004), and Lunupharciceras sp. nov." by Aboussalam and Becker (2011); these new taxa have not yet been formally described but they are mentioned in several studies where they are used to establish the biozonation (e.g., Becker et al. 2004; Aboussalam and Becker 2011).

Fig. 10 in Morphological disparity of early ammonoids: A geometric morphometric approach to investigate conch geometry

Fig. 10. Disparity and diversity fluctuations through the Early and Middle Devonian ammonoid zones (biozones numbered from 1 to 30, see Fig. 2); based on the analysis of the whorl profiles. A. Sum of ranges (black line with grey area showing the confidence intervals) and sampled-in-bin diversity (blue bars). B. Sum of variances (black line with grey area showing the confidence intervals) and sampled-in-bin diversity (blue bars). C. Average displacement black line with grey area showing the confidence intervals) and sampled-in-bin diversity (blue bars). Confidence intervals (error bars) are computed after 1000 bootstraps.

opencc-by-sa-4.0Nov 2023View details →

Rotor37: a 3D CFD RANS dataset, under geometrical variations of a compressor blade

This dataset contains 3D CFD RANS solutions, under geometrical variations of a compressor blade. A Description is provided in <a href="https://arxiv.org/pdf/2305.12871.pdf">2305.12871.pdf (arxiv.org)</a> Sections 4.1 and Appendix A.1. The file format is PLAID, see the <a href="https://plaid-lib.readthedocs.io/">plaid documentation</a>. The variablity in the samples are 2 input scalars and the geometry (mesh). Outputs of interest are 3 scalars and 3 fields. Eight nested training sets of sizes 8 to 1000 are provided, with complete input-output data. A testing set of size 200 is provided, for which outputs are not provided.     Tips to access the data: After decompressing the downloaded file: from plaid.containers.dataset import Dataset from plaid.problem_definition import ProblemDefinition dataset = Dataset() problem = ProblemDefinition() problem._load_from_dir_(os.path.join(/path/to/data,'problem_definition')) dataset._load_from_dir_(os.path.join(/path/to/data,'dataset'), verbose = True) print("problem =", problem) print("dataset =", dataset) sample = dataset[0] print("sample =", sample) for fn in sample.get_field_names():     print(f"{fn} =", sample.get_field(fn)) for sn in sample.get_scalar_names():     print(f"{sn} =", sample.get_scalar(sn)) print("nodes =", sample.get_nodes()) print("elements =", sample.get_elements())