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FIGURE 1 in Non-destructive analysis of in situ ammonoid jaws by synchrotron radiation X-ray micro-computed tomography

FIGURE 1. Left lateral (1), dorsal (2) and ventral (3) views of Phyllopachyceras ezoensis with preserved upper and lower jaws in situ within the body chamber. UMUT MM 27831 (modified from Tanabe et al., 2013).

FIGURE 7 in Non-destructive analysis of in situ ammonoid jaws by synchrotron radiation X-ray micro-computed tomography

FIGURE 7. Result of segmentation of the upper jaw of the specimen, from frontal (1), rear (2), left-lateral (3) views and the transverse section of the area (4) indicated as a square in (3). The three-dimensional reconstruction (5) shows areal distributions of the "chitinous" lamellae and the calcareous covering. The reconstruction of the transverse section (6), which corresponds to (4), shows the architecture of the outer lamella. The abbreviations are indicated in (5).

FIGURE 6 in Non-destructive analysis of in situ ammonoid jaws by synchrotron radiation X-ray micro-computed tomography

FIGURE 6. Result of segmentation of the lower jaw of the specimen, from lateral view which is restricted to its anterior and posterior portion (1). Three-dimensional reconstruction (2) suggests a wide distribution of calcareous material. The outer calcareous layer on the outer "chitinous" layer is partly taken off in (2). The transverse section of the area indicated as a square in (1) shows that the calcareous covering of the lower jaw also covers the internal surface of the "chitinous" lamella (3). The abbreviation is indicated in (2).

FIGURE 4 in Non-destructive analysis of in situ ammonoid jaws by synchrotron radiation X-ray micro-computed tomography

FIGURE 4. Linear absorption coefficient (LAC) of the internal portions of the specimen estimated by their mean luminance values in the tomographic images. The numbers (1)-(10) correspond to the materials in Table 1. The dashed lines indicate the known values for the materials (Chantler et al., 2005) that could be expected to be observed in the specimen. Note that glycine is the most dominant amino acid in jaws of Octopus vulgaris (Hunt and Nixon, 1981). The relationship between LAC values and luminance values is based on the assumption that the LAC values for the surrounding air are zero and that the crystals precipitated in the phragmocone are calcite.

FIGURE 3 in Non-destructive analysis of in situ ammonoid jaws by synchrotron radiation X-ray micro-computed tomography

FIGURE 3. Serial cross-sections of the body chamber portion of the specimen cut from the venter (1) to the dorsum (4), in which sectioned images of the upper jaw are shown. Note that the vertical stripes are due to the separated scanning.

FIGURE 3 in Heterochrony in helicoid spiral cones: a computer model for demonstrating heterochronic evolution

FIGURE 3. Modes of heterochronic change. The central simulation has parameters W0=2.5, ΔW=-0.12, D=0, S=0.8, T'0=0.4, ΔT'=0.06, and has six whorls. The other four simulations show the result of one increment of each mode of heterochronic change. The two forms on the left are paedomorphic; the forms on the right are peramorphic. Note that in this case neoteny results in larger size as the ontogenetic decline in whorl expansion is reduced, and acceleration results in a smaller size for the converse reason.

FIGURE 6. Heterochronic modelling experiment 3 in Heterochrony in helicoid spiral cones: a computer model for demonstrating heterochronic evolution

FIGURE 6. Heterochronic modelling experiment 3. The "ancestor" on the left has parameters W0=2, ΔW=-0.05, D=0, S=0.9, T'0=0.2, ΔT'=0.07, and has eight whorls. As in Figure 4, this is a common general type of gastropod shell shape. The central simulation is a "descendant" derived from this by two increments of neoteny (relative scale x 0.5); the simulation on the right has resulted from two further increments of neoteny (relative scale x 0.39). All three simulations have analogues in the Family Helicidae of the Pulmonata, and this result constitutes a hypothesis for the possible heterochronic evolution of forms with flattened spires (depressed and sub-planispiral).

FIGURE 2 in Heterochrony in helicoid spiral cones: a computer model for demonstrating heterochronic evolution

FIGURE 2. Isometric and allometric gastropods and simulations. 1, An example of a "Raupian" gastropod (Epitonium), showing isometric growth. 2, An example of a "Raupian" simulation with similar shape. 3, An example of an allometric gastropod (Megacochlea); note that there is no straight line that is tangential to the outside of all whorls. 4, A simulation using the program described here with similar shape. (Figures 2.1 and 2.3 © The Trustees of the Natural History Museum, London, reproduced from Anon, 1975, with kind permission.)

FIGURE 1 in Heterochrony in helicoid spiral cones: a computer model for demonstrating heterochronic evolution

FIGURE 1. Raup's definition of the shell dimensions on which the equations for parameters W, D and T are derived. Based on Raup (1966).

FIGURE 5. Heterochronic modelling experiment 2 in Heterochrony in helicoid spiral cones: a computer model for demonstrating heterochronic evolution

FIGURE 5. Heterochronic modelling experiment 2. The "ancestor" on the left has parameters W0=1.1, ΔW=0.05, D=0, S=2.3, T'0=2, ΔT'=-0.03, and has 10 whorls. It has a form, including the slightly concave profile of the spire, which is similar to some members of the Family Volutidae. The next simulations are "descendants" derived from this by successive increments of acceleration (relative scales x 0.5, x 0.225, x 0.0875, respectively). All of these have parallels in the Volutidae, with the final form resembling the giant volutids in the genus Melo. The observation that the simulation predicts the large size of the final form supports the heterochronic hypothesis in the evolution of these gastropods.

FIGURE 4. Heterochronic modelling experiment 1 in Heterochrony in helicoid spiral cones: a computer model for demonstrating heterochronic evolution

FIGURE 4. Heterochronic modelling experiment 1. The "ancestor" on the left has parameters W0=2.5, ΔW=-0.1, D=0, S=1, T'0=0, ΔT'=0.15, and has seven whorls. It has a general shape that is common in gastropods, and especially amongst the subclass Pulmonata. The central simulation is derived from this by one increment of acceleration (relative scale x 1.5) and the simulation on the right by two increments of acceleration (relative scale x 2). The incipient reduction in whorl diameter and incipient loss of whorl-to-whorl contact is typical of some Pulmonata, such as Family Chondrinidae. Note that if Raup's T were used, incipient reduction in whorl diameter (W<1) would lead to reversal of the translation direction, which is nonsensical; using T', this is not the case.

FIGURE 3 in Using X-ray computed tomography analysis tools to compare the skeletal element morphology of fossil and modern frog (Anura) species

FIGURE 3. Morphological bone-to-bone comparison between the 'nominal' male (CP001) and 'actual' female (CP002) Xenopus laevis. The differences are colour-coded and show female (CP002) variance relative to the nominal bone of the male (CP001) which is depicted in the figure.

FIGURE 4 in Using X-ray computed tomography analysis tools to compare the skeletal element morphology of fossil and modern frog (Anura) species

FIGURE 4. Morphological bone-to-bone comparison between the 'nominal' Xenopus laevis (CP001) with the 'actual' fossil Xenopus sp. (ZM 71336)

FIGURE 2 in Using X-ray computed tomography analysis tools to compare the skeletal element morphology of fossil and modern frog (Anura) species

FIGURE 2. Bone cortex thickness analysis on a male Xenopus laevis (CP001) (A) and a fossil Xenopus sp. (ZM 71336) (B) depicted side by side in slice view from top view (1) and side view (3) and in a 3D colour-coded analysis (2 and 3).

FIGURE 1. A in Using X-ray computed tomography analysis tools to compare the skeletal element morphology of fossil and modern frog (Anura) species

FIGURE 1. A complete Breviceps montanus (Catalogue number ZR-050053) CT scan with segmentation of humerus and femur demonstrated.

opencc-by-4.0Aug 2024View details →

Surrogate waveform model data for black hole binary systems computed in point-particle black hole perturbation theory

This repository contains all publicly available surrogate data for gravitational waveforms produced within the point-particle black hole perturbation theory framework and calibrated to numerical relativity simulations performed with the Spectral Einstein Code (SpEC).  Several surrogate models are currently available in this catalog: <ol> <li>BHPTNRSur2dq1e3, for aligned spin black hole binary systems with mass-ratios varying from 3 to 1000 and spins from −0.8≤χ1≤0.8 on the larger black hole. This surrogate model is trained on waveform data generated by point-particle black hole perturbation theory (ppBHPT) with calibration to numerical relativity (NR) data. The waveforms include all spin-weighted spherical harmonic modes up to ℓ=4 except the (4,1) and m=0 modes. Model details can be found in <a href="https://arxiv.org/abs/2407.18319">Rink et al. 2024</a>. This data file is used to evaluate the surrogate model with either stand-alone Python code hosted by the <a href="https://bhptoolkit.org/BHPTNRSurrogate/">Black Hole Perturbation Toolkit</a> (Jupyter notebook <a href="https://github.com/BlackHolePerturbationToolkit/BHPTNRSurrogate/blob/main/tutorials/BHPTNRSur2dq1e3.ipynb">tutorial</a>) or the GWSurrogate Python package, which can be found on <a href="https://pypi.python.org/pypi/gwsurrogate/">PyPI</a> or <a href="https://anaconda.org/conda-forge/gwsurrogate">conda-forge</a>.</li> <li>BHPTNRSur1dq1e4, an updated version of the EMRISur1dq1e4 model described below. The updated version includes better calibration to NR, a smoother transition to plunge model, and more harmonic modes. Model details can be found in <a href="https://arxiv.org/abs/2204.01972">Islam et al. 2022</a>. This data file is used to evaluate the surrogate model with either stand-alone Python code hosted by the <a href="https://bhptoolkit.org/BHPTNRSurrogate/">Black Hole Perturbation Toolkit</a> (Jupyter notebook <a href="https://github.com/BlackHolePerturbationToolkit/BHPTNRSurrogate/tree/main/tutorials/BHPTNRSur1dq1e4">tutorial</a>) or the GWSurrogate Python package, which can be found on <a href="https://pypi.python.org/pypi/gwsurrogate/">PyPI</a> or <a href="https://anaconda.org/conda-forge/gwsurrogate">conda-forge</a>.</li> <li>EMRISur1dq1e4, for non-spinning black hole binary systems with mass-ratios varying from 3 to 10000. This surrogate model is trained on waveform data generated by point-particle black hole perturbation theory (ppBHPT), with the total mass rescaling parameter tuned to NR simulations. Available modes are [(2,2), (2,1), (3,3), (3,2), (3,1), (4,4), (4,3), (4,2), (5,5), (5,4), (5,3)]. The m<0 modes are deduced from the m>0 modes. Model details can be found in <a href="https://arxiv.org/abs/1910.10473">Rifat et al. 2019</a>. This data file is used to evaluate the surrogate model with either stand-alone Python code hosted by the <a href="http://github.com/BlackHolePerturbationToolkit/EMRISurrogate">Black Hole Perturbation Toolkit</a> (Jupyter notebook <a href="https://github.com/BlackHolePerturbationToolkit/EMRISurrogate/blob/master/EMRISur1dq1e4.ipynb">tutorial</a>) or the GWSurrogate Python package (Jupyter notebook <a href="https://github.com/sxs-collaboration/gwsurrogate/blob/master/tutorial/notebooks/nonspinning_nr_emri.ipynb">tutorial</a>), which can be found on <a href="https://pypi.python.org/pypi/gwsurrogate/">PyPI</a>.</li> </ol>

opencc-by-nc-nd-4.0Sep 2024View details →

High spatiotemporal resolution free surface detection using cost-effective video equipment and computer vision techniques in nearly stationary flow along a transparent wall in the laboratory

The identification of the air-water interface in free surface flows traditionally involves intrusive techniques or costly equipment. Non-intrusive alternatives, such as computer vision, are emerging as highly effective substitutes or supplements for more invasive techniques in laboratory measurements, thanks to their straightforward implementation and cost efficiency. This research specifically delves in the conjunction of various naive techniques, exploring their collective precision in detecting the air-water interface along transparent walls in laboratory. A detection technique based on the double gradient of the image is applied and thoroughly examined. The study progresses through multiple refinement stages, culminating in a method that is both cost effective and easy to implement. This methodology allows for large-scale, high resolution measurements (200 mm × 1800 frames per video at a 0.25 mm, 50 Hz resolution), offering both spatial and temporal measurements by adeptly detecting the free surface along transparent walls.

opencc-by-4.0Jul 2024View details →

Computational data (frequencies calculations) of the nitroxides

Data associated with <a href="https://doi.org/10.1016/j.molliq.2024.126207">https://doi.org/10.1016/j.molliq.2024.126207</a>. This dataset contains the Gaussian checkpoint files (this is a formatted text format, described at <a href="https://gaussian.com/interfacing/">https://gaussian.com/interfacing/</a>) corresponding to the frequency calculations performed on each structure (in both solvents and for each complexation state). Check out README.md for detailed data organisation.

opencc-by-4.0Aug 2024View details →

GFRP Glass fibre plain weave laminate - Micro-computed tomography scans

A sample of computed tomography image of a glass fibre plain weave laminate. Detailed description can be found in the attached metadata files as well as in the associated paper: <a href="https://doi.org/10.1016/j.compositesa.2015.03.027">https://doi.org/10.1016/j.compositesa.2015.03.027 </a> The sample was used for geometrical analysis and for creating a TexGen model with the subsequent image-based permeability modelling.