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Text-fig. 8. a: Paramblypterus zeidleri (FRITSCH, 1895), Lectotype NM-M 901 from the locality Ruprechtice, scale bar 10 mm; b: Paramblypterus cf. rohani, significantly deformed specimen from the locality Otovice "Stěnava", DP 4529, scale bar 10 mm; c: Paramblypterus cf. rohani, significantly deformed specimen from the locality Otovice "Stěnava", DP 4257, scale bar 10 mm. in Actinopterygians Of The Broumov Formation (Permian) In The Czech Part Of The Intra-Sudetic Basin (The Czech Republic)
Text-fig. 8. a: Paramblypterus zeidleri (FRITSCH, 1895), Lectotype NM-M 901 from the locality Ruprechtice, scale bar 10 mm; b: Paramblypterus cf. rohani, significantly deformed specimen from the locality Otovice "Stěnava", DP 4529, scale bar 10 mm; c: Paramblypterus cf. rohani, significantly deformed specimen from the locality Otovice "Stěnava", DP 4257, scale bar 10 mm.
Text-fig. 10. Paramblypterus cf. rohani. a: the skull roof in dorsal view, locality Otovice "Chmelnice", P 64665, scale bar 5 mm; b: bones of the skull roof in dorsal view, locality Otovice "Chmelnice", NM-M 4920, scale bar 5 mm; c: right frontal in dorsal view, locality Otovice "Chmelnice", NM-M 4923, scale bar 5 mm; d: right dermopterotic in dorsal view, locality Otovice "Chmelnice", P 30943, scale bar 2 mm; e: right supracleithrum in lateral view, locality Otovice "Chmelnice", P 30944, scale bar 5 mm; f: fragment of not deformed body in lateral view, locality Otovice "Chmelnice", NM-M 4916, scale bar 10 mm; g: right maxilla in lateral view, locality Otovice "Chmelnice", P 64661, scale bar 5 mm; h: right maxilla in lateral view, locality Otovice "Chmelnice", NM-M 4922, scale bar 5 mm. Abbreviations: Dpt – dermopterotic, Dsph – dermosphenotic, Fr – frontal, Pa – parietal. in Actinopterygians Of The Broumov Formation (Permian) In The Czech Part Of The Intra-Sudetic Basin (The Czech Republic)
Text-fig. 10. Paramblypterus cf. rohani. a: the skull roof in dorsal view, locality Otovice "Chmelnice", P 64665, scale bar 5 mm; b: bones of the skull roof in dorsal view, locality Otovice "Chmelnice", NM-M 4920, scale bar 5 mm; c: right frontal in dorsal view, locality Otovice "Chmelnice", NM-M 4923, scale bar 5 mm; d: right dermopterotic in dorsal view, locality Otovice "Chmelnice", P 30943, scale bar 2 mm; e: right supracleithrum in lateral view, locality Otovice "Chmelnice", P 30944, scale bar 5 mm; f: fragment of not deformed body in lateral view, locality Otovice "Chmelnice", NM-M 4916, scale bar 10 mm; g: right maxilla in lateral view, locality Otovice "Chmelnice", P 64661, scale bar 5 mm; h: right maxilla in lateral view, locality Otovice "Chmelnice", NM-M 4922, scale bar 5 mm. Abbreviations: Dpt – dermopterotic, Dsph – dermosphenotic, Fr – frontal, Pa – parietal.
Data for the analysis of aquifer-system deformation in the Doñana Natural Space (Spain) using unsupervised cloud-computed InSAR data and wavelet analysis
<p>This are the data necessary to correlate InSAR and hydrogeological information through wavelet analysis, by WaSAR Python script (Jiménez-González & Guardiola-Albert, 2022, http://doi.org/10.5281/zenodo.6334996). The structure and information about the data is the following:</p> <p>PSBAS: Processed Interferometric Synthetic Aperture Radar (InSAR) data from the European Space Agency (ESA) Sentinel-1 satellites to estimate line-of-sight (LOS) ground motion in the period 2014-2020 in the Doñana area (SW Spain). These images have been processed using the P-SBAS approach (Parallel Small BAseline Subset), which is the parallel computing solution for the SBAS processing chain at the ESA Geohazards Exploitation Platform (GEP) by CNR-IREA.</p> <p>Aggregates deformation: Former InSAR information aggregated in polygons</p> <p>Climate: rainfall and ET information in the Doñana area for the 2014-2020 period. Daily records of evapotranspiration and precipitation have been obtained from the agroclimatic stations belonging to the Junta de Andalucía (https://www.juntadeandalucia.es/agriculturaypesca/ifapa/riaweb/web/).</p> <p>Piezometry: piezometry information in Doñana area for the 2014-2020 period. Groundwater level information was provided by the piezometric networks of the Guadalquivir Hydrographic Confederation and the Geological and Mining Institute of Spain.</p> <p>Pump rates: estimated pumping rate time series in the Matalascañas touristic resort</p>
Deep potential model and datasets used in the publication "Plastic Deformation of Superionic Water Ices"
<p>The file training_data_for_deepmd.zip contains the training set and deep potential model for superionic ices used in the publication "Plastic Deformation of Superionic Water Ices". The deep potential (DP) neural-network model was generated using the DeepMD-kit package. The training set was generated using AIMD/CP2K calculations for both undeformed and deformed states of the fcc superionic phase at temperatures of 2500, 3000, 3500 and 4000 K. </p> <p> </p> <p>The file cp2k_shear.zip contains instructions to modify the CP2K code to calculate the shear vs strain deformation in continuous mode. </p> <p> </p> <p>The file lammps_dislocation.zip contains the files needed to run the dislocation mobility calculation. </p> <p> </p>
Data associated with Versatile Multiple Object Tracking in Sparse 2D/3D Videos via Deformable Image Registration (2024)
<p>This includes a volumetric whole-brain calcium recording of a freely behaving worm (<em>C. elegans</em>) captured at 4 Hz with tracked fluorescent neuronal nuclei, used to demonstrate the performance of a multi-object tracking algorithm (ZephIR) described in the associated publication.</p>
→ Fig. 9. Antiarchan fish Bothriolepis leptocheira jeremejevi (Rohon, 1900), Sosnogorsk locality, Sosnogorsk Formation, lowermost Famennian, anterior median dorsal (A–G) and posterior median dorsal (H–M) plates of the trunk armour. A. IG KSC 155/5 in dorsal (A1) and visceral (A2) views. B. IG KSC 155/108 in dorsal (B1) and visceral (B2) views. C. IG KSC 155/97 in dorsal view. D. IG KSC 155/113 in dorsal (D1) and visceral (D2) views. E. IG KSC 155/140 in dorsal (E1) and visceral (E2) views. F. Impression of the dorsal surface of IG KSC 155/42. G. IG KSC 155/44 in dorsal view. H. Fragment of IG KSC 155/7 in dorsal view. I. IG KSC 155/1 in dorsal (I1) and visceral (I2) views. J. IG KSC 155/71 in dorsal view. K. Slightly deformed IG KSC 155/70 in dorsal (K1) and visceral (K2) views. L. IG KSC 155/158 in dorsal view. M. IG KSC 155/157 in dorsal (M1) and visceral (M2) views. Abbreviations: ADL, anterior dorso-lateral plate; alr, postlevator thickening; AMD, anterior median dorsal plate; cf.ADL, cf.AMD, and cf.MxL, area overlapping ADL, AMD or MxL respectively; cr.tp, posterior transversal internal crest; dlg1 and dlg2, anterior and posterior oblique dorsal sensory line groove; dma, tergal angle; dmr, dorsal median ridge; f.retr, levator fossa; grm, ventral median groove; l, lateral corner; mvr, median ventral ridge; MxL, mixilateral plate; npn, postnuchal notch; oa.ADL, oa.MxL and oa.PMD, area overlapped by ADL, MxL or PMD respectively; pa, posterior corner; pma, posterior marginal area; PMD, posterior median dorsal plate; pr.p, posterior process of AMD; pr.pl, external postlevator process; prv2, posterior ventral process of dorsal wall of trunk armour; pt1 and pt2, anterior and posterior ventral pit; pua, posterior unornamented area of PMD; rf, "round fossula"; sna, supranuchal area; tb, ventral tuberosity. in A new assessment of the Late Devonian antiarchan fish Bothriolepis leptocheira from South Timan (Russia) and the biotic crisis near the Frasnian-Famennian boundary
→ Fig. 9. Antiarchan fish Bothriolepis leptocheira jeremejevi (Rohon, 1900), Sosnogorsk locality, Sosnogorsk Formation, lowermost Famennian, anterior median dorsal (A–G) and posterior median dorsal (H–M) plates of the trunk armour. A. IG KSC 155/5 in dorsal (A1) and visceral (A2) views. B. IG KSC 155/108 in dorsal (B1) and visceral (B2) views. C. IG KSC 155/97 in dorsal view. D. IG KSC 155/113 in dorsal (D1) and visceral (D2) views. E. IG KSC 155/140 in dorsal (E1) and visceral (E2) views. F. Impression of the dorsal surface of IG KSC 155/42. G. IG KSC 155/44 in dorsal view. H. Fragment of IG KSC 155/7 in dorsal view. I. IG KSC 155/1 in dorsal (I1) and visceral (I2) views. J. IG KSC 155/71 in dorsal view. K. Slightly deformed IG KSC 155/70 in dorsal (K1) and visceral (K2) views. L. IG KSC 155/158 in dorsal view. M. IG KSC 155/157 in dorsal (M1) and visceral (M2) views. Abbreviations: ADL, anterior dorso-lateral plate; alr, postlevator thickening; AMD, anterior median dorsal plate; cf.ADL, cf.AMD, and cf.MxL, area overlapping ADL, AMD or MxL respectively; cr.tp, posterior transversal internal crest; dlg1 and dlg2, anterior and posterior oblique dorsal sensory line groove; dma, tergal angle; dmr, dorsal median ridge; f.retr, levator fossa; grm, ventral median groove; l, lateral corner; mvr, median ventral ridge; MxL, mixilateral plate; npn, postnuchal notch; oa.ADL, oa.MxL and oa.PMD, area overlapped by ADL, MxL or PMD respectively; pa, posterior corner; pma, posterior marginal area; PMD, posterior median dorsal plate; pr.p, posterior process of AMD; pr.pl, external postlevator process; prv2, posterior ventral process of dorsal wall of trunk armour; pt1 and pt2, anterior and posterior ventral pit; pua, posterior unornamented area of PMD; rf, "round fossula"; sna, supranuchal area; tb, ventral tuberosity.
Research Data - Deformation Localisation in Ion-Irradiated Fe and Fe10Cr
<p>Research data and associated processing and plotting scripts for the article:</p> <p>Song <em>et al.,</em> 'Deformation localisation in ion-irradiated Fe and Fe10Cr', <em>Journal of Nuclear Materials</em>, 155104, 2024</p> <p><a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.jnucmat.2024.155104" target="_blank" rel="noreferrer noopener"><span>https://doi.org/10.1016/j.jnucmat.2024.155104</span></a></p>
Influence of statistical size effects on the plastic deformation of coronary stents: Supporting data
<p>Data including UMATs and Abaqus input files related to the paper 'Influence of statistical size effects on the plastic deformation of coronary stents' <a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.jmbbm.2012.12.008" target="_blank" rel="noreferrer noopener"><span>https://doi.org/10.1016/j.jmbbm.2012.12.008</span></a></p>
Data for "High-temperature low-cycle fatigue and fatigue-creep behaviour of Inconel 718 superalloy: Damage and deformation mechanisms"
<p>Title of dataset: Data for "High-temperature low-cycle fatigue and fatigue-creep behaviour of Inconel 718 superalloy: Damage and deformation mechanisms"<br>Name/institution/contact information: Dr. Michal Bartošák, Czech Technical University in Prague - Faculty of Mechanical Engineering, email: michal.bartosak@fs.cvut.cz<br>Date of data collection: The data were collected from the start of 2021 to the end of 2023.<br>File name structure: The data within the folder "SEM" are images of microstructural observations of selected specimens. The data within the folder "FATIGUE_LIFE" include the fatigue lifetimes, as well as the stress and strain amplitudes at mid-life, of all investigated specimens.</p> <p>See https://doi.org/10.1016/j.ijfatigue.2024.108369 for the associated article and a detailed description of the methods.</p>
Self Consistent Recurrent Neural Network for Path Dependent Deformation
<p>Data and Machine Learning codes for the paper:</p> <ul> <li>Title<strong> : Self Consistent Recurrent Neural Network for Path Dependent Deformation</strong></li> </ul> <p><strong>Abstract</strong> : Current neural network (NN) structures can learn patterns from data points with historical dependence. Specifically, in natural language processing (NLP), sequential learning has transitioned from recurrence-based architectures to transformer-based architectures. However, it is not known in advance which NN architectures will perform best on datasets containing deformation history due to mechanical loading. Thus, this study ascertains the appropriateness of 1D-convolutional, recurrent, and transformer-based architectures for predicting material failure based on the earlier states in the form of deformation history. Following this investigation, the crucial issues arising from the mathematical computation process of the best-performing NN architectures and the physical properties of the deformation paths are examined in detail. Additionally, we propose a novel and adaptable RNN approach to address the fundamental challenges of truncation and consistency related to obtaining estimations that are compatible with the natural physical properties of deformation paths. This study will serve as a foundation for localization estimation and pave the way for future endeavors to propose further solutions to encountered challenges.</p>
Figures 3A–G. A, Eudendrium deforme. A in Deep-water hydroids (Hydrozoa: Leptolida) from Macquarie Island
Figures 3A–G. A, Eudendrium deforme. A, part of colony on dead branch of primnoid gorgonian, stn 46. B, single stem. C, cluster of male gonophores with paired immature gonophores and partially resorbed tentaclesof hydranth. D, undischarged nematocyst, probably eurytele from coenosarc of stem. E–G, Eudendrium macquariensis sp. nov., stn 44. E, stems from holotype colony on Eudendrium deforme. F, undischarged nematocyst from tentacles. G, undischarged nematocyst, site unknown. Scale bar: A, 25 mm; B, 10 mm; C, 0.5 mm; E, 1 mm; F, G, 10 µm.
Рис. 2. Ментум Λичинок роΑа Chironomus из озера Кенон Fig. 2. Mentum of the Chironomus genus larvae from Lake Kenon in Toxic pollution assessment of Chita TPP-1 cooling reservoir by applying the method of head capsule morphological deformations in chironomid larvae
Рис. 2. Ментум Λичинок роΑа Chironomus из озера Кенон Fig. 2. Mentum of the Chironomus genus larvae from Lake Kenon
Рис. 1. Схема мониторинговых станций на озере Кенон: 1–1.6 — ТЭЦ; 2–2.1 — КСК; 3 — Нефтебаза; 4 — Центр озера; 5 — КаΑаΛинка Fig. 1. Diagram of monitoring stations on Kenon lake: 1–1.6 — TPP; 2–2.1 — KSK; 3 — Tank farm; 4 — Lake Center; 5 — Kadalinka in Toxic pollution assessment of Chita TPP-1 cooling reservoir by applying the method of head capsule morphological deformations in chironomid larvae
Рис. 1. Схема мониторинговых станций на озере Кенон: 1–1.6 — ТЭЦ; 2–2.1 — КСК; 3 — Нефтебаза; 4 — Центр озера; 5 — КаΑаΛинка Fig. 1. Diagram of monitoring stations on Kenon lake: 1–1.6 — TPP; 2–2.1 — KSK; 3 — Tank farm; 4 — Lake Center; 5 — Kadalinka
Figure 2 in Root deformation affects mineral nutrition but not leaf gas exchange and growth of Genipa americana seedlings during the recovery phase after soil flooding
Figure 2. Concentrations of P in leaves for G. americana seedlings without or with root deformation (RD) after 28 days of soil drainage (recovery). N = 3. Means followed by the same letter are not significantly different according to Tukey's test (p <0.05). Capital letters represent comparisons water effects within root conditions and lower case letters represent comparisons of roots effects within water conditions.
Figure 1 in Root deformation affects mineral nutrition but not leaf gas exchange and growth of Genipa americana seedlings during the recovery phase after soil flooding
Figure 1. Four months old seedlings of G. americana without (A) and with (B) root deformation (RD) caused by errors in the pricking out process, and a detail of the RD (C).
Experimental data related to the publication: "In-situ analysis of the effect of residual fcc phase and special grain boundaries on the deformation dynamics in pure cobalt"
<p>The article figures were produced solely from these data sets employing data processing methods described therein. For experimental conditions and naming conventions please refer to the paper.</p> <p><br>1. Deformation data files contained within "deformation_data.zip":</p> <p>The .zip archive contains five files related to five samples of thermally treated cobalt:<br>def_co600.csv<br>def_co800.csv<br>def_co1100.csv<br>def_co1100-10c.csv<br>def_co1100-20c.csv</p> <p>The data were recorded during compression of the above-listed samples at room temperature. </p> <p><br>2. Acoustic emission (AE) data files contained within "AE_data.zip":</p> <p>The .zip archive contains four files related to four samples of thermally treated cobalt:<br>AE_co600.wav<br>AE_co800.wav<br>AE_co1100.wav<br>AE_co1100-20c.wav</p> <p>The AE data were recorded in continuous mode ("data streaming" at 2 MHz) during compression of the above-listed samples at room temperature. </p> <p> </p> <p>3. Electron back-scatter diffraction (EBSD) data files contained within "EBSD_data.zip":</p> <p>The .zip archive contains fifty-three .osc files related to samples of as-drawn and thermally treated cobalt within four folders:<br>0c - as-drawn and annealed samples (i.e. without thermal cycling)<br>10c - annealed samples after thermal cycling of 10 cycles<br>20c - annealed samples after thermal cycling of 20 cycles<br>ex-situ_def - ex-situ EBSD during deformation of selected samples</p> <p>The .osc data files represent EBSD data after clean-up procedures described in detail in the manuscript.</p> <p> </p> <p> </p> <p> </p>
Deformed Iron EBSD data set
<p>Data from Electron Backscatter Diffraction analysis for a small (83 x 110) point map captured using a Bruker eFlash HR (1st generation) with full pattern resolution on a FEI Quanta instrument. The orientation data can be loaded using MTEX 5.0.3 (<a href="http://mtex-toolbox.github.io/">http://mtex-toolbox.github.io/</a>). The data is released to facilitate the development of new EBSD analysis methodologies, including AstroEBSD (<a href="https://github.com/benjaminbritton/AstroEBSD/">https://github.com/benjaminbritton/AstroEBSD/</a>) which has been developed by the Experimental Micromechanics Research Group (<a href="http://www.expmicromech.com">http://www.expmicromech.com</a>) & the Oxford Micromechanics group (<a href="http://users.ox.ac.uk/~ajw/">http://users.ox.ac.uk/~ajw/</a>). The data is from a lightly deformed sample of interstitial free steel (Ferrite). Orientation analysis was performed using eSprit 2.1 and this is contained within the h5 file. Figures from this data set are provided to illustrate the correct representation of the data. The x axis points right to left, the y axis points top to bottom, and the z axis is out of the page (as per conventions described in <a href="http://dx.doi.org/10.1016/j.matchar.2016.04.008">http://dx.doi.org/10.1016/j.matchar.2016.04.008</a>). Data has been captured with a 0.15 um step size.</p> <p>This data was collected within the Harvey Flower EM Suite within the Department of Materials, Imperial College London. The equipment was funded under the Shell-Imperial Advanced Interfaces in Materials Science University Technology Center.</p> <p>Please contact Dr Ben Britton if you have any queries or require further information (b.britton@imperial.ac.uk).</p>
High Temperature Compression Studies of a Zr-2.5Nb Alloy using Deformation Dilatometer
<p>Data recorded in uniaxial compression for a Zr-2.5Nb alloy deformed at temperatures of 650C, 675C, 700C, 725C, 750C, 775C, 800C, 825C and 850C, at strain rates of 10-2.5, 10-2, 10-1.5, 10-1, 10-0.5 and 1 s-1, to 50% height reduction, using TA Instruments DIL 805 A/D/T Quenching and Deformation Dilatometer. The cylindrical samples measured 5 mm diameter and 10 mm height. The Zr-2.5Nb specimens were machined from the centre of an as-received forged plate manufactured at Wah Chang, with a beta-transformed starting microstructure. Si3N43 platens were used for all tests, with graphite lubricant applied at the ends of the sample to minimise friction. Tests were conducted in an inert He gas atmosphere. Temperature was controlled using an S-Type thermocouple spot-welded to the centre of the samples.</p> <p>Data recorded at high acquisition frequency during deformation is stored in the 'deformation_files' folder and saved with the format: ' test number (001 to 191)_temperature_log(strain rate)_repeat number (01 or 02)'. Data in the 'basic_files' folder is recorded at a lower acquisition frequency, but includes recording of the entire themomechanical cycle, including both heating and cooling stages, as well as deformation. The 'software_files' folder includes metadata stored in the form of a parameter file (.par and .pad), along with a Windows data file (.D5D) that can be loaded and analysed within the dilatometer user interface.</p> <p>An <a href="https://doi.org/10.5281/zenodo.3673105">accompanying python script</a> will allow the user to plot the stress-strain data using the Jupyter Notebook application, along with generating 'processing maps' of the material. A critical assessment of the application of 'processing maps' is included in the accompanying paper;</p> <p>C. S. Daniel, P. Jedrasiak, C. J. Peyton, J. Quinta da Fonseca, H. R. Shercliff, L. Bradley, and P. D.Honniball, “Quantifying Processing Map Uncertainties by Modeling the Hot-Compression Behavior of a Zr-2.5Nb Alloy,” in Zirconium in the Nuclear Industry: 19th International Symposium, ed. A. T. Motta and S. K. Yagnik (West Conshohocken, PA: ASTM International, 2021), 93–122. <a href="https://doi.org/10.1520/STP162220190031">10.1520/STP162220190031</a></p>
Pre-eruption ground deformation maps at Kilauea (Hawai`i, USA): 2014-2017 and 2018.
<p>Vertical displacement (velocity) maps of Kilauea (Hawai`i, USA) derived from InSAR, for the time periods 2014-2017 and 2018. Vertical velocity data were obtained by processing Sentinel-1 ascending and descending SAR data (tracks 124 and 87, respectively). Data were processed using the JPL-developed InSAR Scientific Computing Environment (ISCE) open-source software package, and further time-series analysis was performed using the MintPy software toolbox (Miami INsar Time-series software in PYthon), developed at the University of Miami. An SRTM-derived Digital Elevation Model is also provided. </p> <p>These data were generated for figures in: Farquharson, J. I. and Amelung, F. [2020], "<em>Extreme rainfall triggered the 2018 rift eruption at Kīlauea Volcano.</em>" <a href="https://doi.org/10.1038/s41586-020-2172-5">https://doi.org/10.1038/s41586-020-2172-5</a></p> <p> </p>
Research data supporting for "Characterization of recovery onset by subgrain and grain boundary migration in experimentally deformed polycrystalline olivine"
<p>Abstract: To apprehend plate tectonics and the dynamics of the lithosphere–asthenosphere boundary, composed principally of olivine, we need to understand the mechanisms that control plastic deformation of olivine in the relevant temperature domain. After more than 50 years of laboratory studies and investigations on natural rocks, the interplay of several key parameters (e.g. temperature, pressure, vacancy concentration, dislocation densities, grain size, strain rate) controlling polycrystalline olivine plasticity remains difficult to assess. Here, we study four olivine polycrystals, which have been deformed in axial compression under a confining pressure of 300MPa, at 1273 or 1473 K. Despite significant differences in mechanical properties (stress–strain curves), previous characterization by scanning (SEM) and transmission electron microscopy (TEM) did not reveal significant differences in dislocation microstructures which could explain these contrasted behaviours. We have undertaken automatic crystallographic orientation mapping (ACOM) analyses in TEM to increase the spatial resolution of characterization compared to previously obtained electron backscatter diffraction maps to further decipher the microstructures at nanoscale. With this novel technique applied to olivine, a noticeable difference in the onset of microstructural recovery has been identified between specimens deformed at 1273 and 1473 K. The microstructures of the olivine polycrystals deformed at 1473K exhibit numerous curved grain and subgrain boundaries, advocating for recovery by boundary migration. In contrast, the microstructures of the olivine polycrystals deformed at 1273K have significantly fewer subgrain boundaries and show more straight boundaries (i.e. closer to an equilibrium microstructure) than in the specimen deformed at 1473 K. Characterization by ACOM-TEM has permitted the identification of the onset of recovery, which is led by boundary migration even for very low macroscopic finite strains.</p> <p> </p>
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Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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