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654 results for “deformable”
GNSS and levelling data to detect ground deformation along the Upper Adriatic Sea coastal area (Italy)
<p>This geodetic dataset includes both Global Navigation Satellite System (GNSS) and levelling data. GNSS measurements were recorded by continuous stations managed by public institutions and private companies, while levelling measurements were obtained by the use of benchmarks managed by ENI S.p.A. </p> <p>This dataset is used in the manuscript entitled "Multi-technique geodetic detection of onshore and offshore subsidence along the Upper Adriatic Sea coasts" to estimate deformation around the littoral area of Ravenna (Italy) (Polcari et al., 2022). The GNSS data, from permanent stations RAVE, PCTA, FIUN and ANGA covers the period from around 1998 to 2018. The files in .csv format contain displacement time series with respect to the Adria-fixed reference frame and for PCTA, FIUN and ANGA also with respect to RAVE GNSS station.</p> <p>The levelling data refer to campaigns that took place in 2002, 2003, 2004, 2005, 2007, 2009, 2011, 2014, and 2017. The file named <em>Original.csv</em> contains the original height measurements for each benchmark, while the file named <em>Ref.RAVE.csv</em> contains the mean velocity and the displacement calculated for all 147 benchmarks. In this last file the data were scaled with respect to the mean velocity of the benchmark located near the RAVE station.</p>
Exploring Jupiter's Polar Deformation Lengths with High Resolution Shallow Water Modeling
<p>Movies for simulations of non-dimensional eddy potential vorticity generated using the Pencil Code for the article "Exploring Jupiter's Polar Deformation Lengths with High Resolution Shallow Water Modeling". These movies show the Jovian North polar region in the co-rotating frame using the shallow water approximation with the gamma-plane approximation. Simulations named with a preceding A correspond to Case A (Figure 2 in the article), while those with B correspond to Case B (Figure 5 in the article). Red indicates cyclonic behavior and blue indicates anticyclonic behavior.</p> <p>Long term trends are clear for most cases as early as day 10,000. However, the dynamical behavior of the system continues to evolve well past energy equilibration. For more details regarding these simulations, please read the parent article in the Planetary Science Journal.</p>
Failure and deformation characteristics of shale under true triaxial stress loading and unloading under water retention and seepage
<p class="MsoNormal"><span>A multifunctional true triaxial fluid-structure coupling system was used to conduct water retention and seepage tests of shale under true triaxial loading and unloading stress paths. The stress-strain evolution law of shale specimens under different experimental conditions was obtained, and the corresponding deformation and strength law was analyzed. The evolution law and failure characteristics of cracks in shale were obtained by CT scanning images before and after the experiment. The results show that under the condition of water retention, the volumetric strain of shale specimen increases first, then decreases and finally continues to increase with the increase of deviational stress, indicating that the volumetric change has experienced a process of compaction-expansion-compacting. The partial stress-maximum horizontal strain curve of the sample increases first and then decreases, while the deformation of the sample in the direction of intermediate principal stress shows the characteristics of repeated compression and expansion. In the seepage test, the permeability - maximum horizontal strain curve can be divided into two parts before and after fracture according to the deviant stress - maximum horizontal strain curve. Before fracture, the compression velocity of the specimen in the loading direction exceeds the expansion velocity <span>in the unloading direction, resulting in a decrease in volume and a decrease in permeability. With the increase of deviatoric stress, cracks occur inside the particles and continue to spread from the tip until the cracks break through the shale specimen. In this process, the pore fissure area increases and the permeability of the sample increases rapidly. In terms of fractur</span>e evolution, for the water-retaining test, dense tensile and shear cracks appear on the failure plane perpendicular to the direction of maximum and minimum principal stress, and complex shear fracture network appears on the failure plane perpendicular to the direction of intermediate principal stress. For the seepage test, heavy shear failure occurs throughout the original fracture of the sample. With the increase of the penetration depth, the crack shape on the failure surface perpendicular to the direction of intermediate principal stress gradually changes from single type to complex type.</span></p>
Dataset for: Locally resolved stress-state in samples during experimental deformation: insights into the effect of stress on mineral reactions
<p>Data used for the publication:<br> Cionoiu, S., Tajčmanová, L., Moulas, E. and Stünitz H. (under review, 2022) Locally resolved stress-state in samples during experimental deformation: insights into the effect of stress on mineral reactions, Journal of Geophysical Research: Solid Earth</p> <p>See details on the files in ReadMe.txt</p>
Dataset of "Effect of impact velocity and angle on deformational heating and post-impact temperature"
<p>This dataset contains input files for iSALE-3D and Data Set for the paper "Effect of impact velocity and angle on deformational heating and post-impact temperature" by S. Wakita et al.<br> <br> Please note that usage of the iSALE-3D code is restricted to those who have contributed to the development of iSALE-2D, and iSALE-2D is distributed on a case-by-case basis to academic users in the impact community. It requires a registration from the iSALE webpage (https://isale-code.github.io/) and usage of iSALE-2D and computational requirements are also shown in there. Please also note that pySALEPlot in the current stable release of iSALE-2D (Dellen) would not work for the data from iSALE-3D.</p>
Combined U-series and in situ U-Pb dating of fault-related carbonates for reconstructing a long-term history of fault activity in response to SE Tibetan Plateau brittle deformation
<p>Table S1. Analytical conditions for LA-ICP-MS U-Pb dating</p> <p>Table S2. Analytical conditions for LA-ICP-MS elemental mapping</p> <p>Table S3.<em> In situ </em>calcite LA-ICAPMS U-Pb dating data</p>
Supplemental Dataset: Seismological evidence for girdled olivine lattice-preferred orientation in oceanic lithosphere and implications for mantle deformation processes during seafloor spreading
<p>This repository contains supplementary datasets for the manuscript titled "Seismological evidence for girdled olivine lattice-preferred orientation in oceanic lithosphere and implications for mantle deformation processes during seafloor spreading", published in G-Cubed. All files are Microsoft Excel tables containing olivine fabric data.</p> <p>ds01_strain_data_ol60.xlsx: Anisotropy magnitude and fast directions for sample data shown in Figure 3 of the main text, assuming 60% olivine and 40% pyroxene (see methods for details).</p> <p>ds02_strain_data_ol100.xlsx: Anisotropy magnitude and fast directions for sample data shown in Figure 3 of the main text, assuming pure olivine.</p> <p>ds03_fabric_data_ol75.xlsx: Anisotropy fabric data shown in Figure 5 of the main text, assuming 75% olvine and 25% pyroxene (see methods for details).</p> <p>ds04_fabric_data_ol100.xlsx: Anisotropy fabric data shown in Figure 5 of the main text, assuming pure olivine.</p> <p> </p>
Viscoelastic properties of suspended cells measured with shear flow deformation cytometry
<p>Numerous cell functions are accompanied by phenotypic changes in viscoelastic properties, and measuring them can help elucidate higher-level cellular functions in health and disease. We present a high-throughput, simple and low-cost microfluidic method for quantitatively measuring the elastic (storage) and viscous (loss) modulus of individual cells. Cells are suspended in a high-viscosity fluid and are pumped with high pressure through a 5.8 cm long and 200 μm wide microfluidic channel. The fluid shear stress induces large, near ellipsoidal cell deformations. In addition, the flow profile in the channel causes the cells to rotate in a tank-treading manner. From the cell deformation and tank treading frequency, we extract the frequency-dependent viscoelastic cell properties based on a theoretical framework developed by R. Roscoe that describes the deformation of a viscoelastic sphere in a viscous fluid under steady laminar flow. We confirm the accuracy of the method using atomic force microscopy-calibrated polyacrylamide beads and cells. Our measurements demonstrate that suspended cells exhibit power-law, soft glassy rheological behavior that is cell cycle-dependent and mediated by the physical interplay between the actin filament and intermediate filament networks.</p>
Deep, shallow and surface fault-zone deformation during and after the 2021 Mw7.4 Maduo, Qinghai, earthquake illuminates fault structural immaturity
<p>These datasets include the postseismic InSAR time series on ascending and descending tracks and the relocated aftershocks (Wang et al., 2021) of the 2021 Maduo earthquake. The details can be found in our JGR paper.</p> <p>Reference</p> <p>Wang, W., Fang, L., Wu, J., Tu, H., Chen, L., Lai, G., & Zhang, L. (2021). Aftershock sequence relocation of the 2021 Ms7. 4 Maduo earthquake, Qinghai, China. Science China Earth Sciences, 64(8), 1371-1380.</p>
Earthquake Cycle Deformation Associated with the 2021 Mw 7.4 Maduo (Eastern Tibet) Earthquake: An Intrablock Rupture Event on a Slow-Slipping Fault from Sentinel-1 InSAR and Teleseismic Data
<p>Coseismic slip models of the 2021 Mw 7.4 Maduo (eastern Tibet) earthquake derived from Sentinel-1 InSAR and teleseismic data.</p> <p>Interseismic eastward and vertical velocity and maximum shear strain rate fields.</p> <p>Citations:</p> <p>Fang, J., Ou, Q., Wright, T. J., Okuwaki, R., Amey, R. M. J., Craig, T. J., et al. (2022). Earthquake cycle deformation associated with the 2021 M<span>W </span>7.4 Maduo (eastern Tibet) earthquake: An intrablock rupture event on a slow-slipping fault from Sentinel-1 InSAR and teleseismic data. Journal of Geophysical Research: Solid Earth, 127, e2022JB024268. <span>https://</span>doi.org/10.1029/2022JB024268</p> <p>Fang, J., Ou, Q., Wright, T. J., Okuwaki, R., Amey, R. M. J., Craig, T. J., et al. (2022). Earthquake cycle deformation associated with the 2021 M<span>W </span>7.4 Maduo (eastern Tibet) earthquake: An intrablock rupture event on a slow-slipping fault from Sentinel-1 InSAR and teleseismic data [Data set]. Zenodo. https://doi.org/10.5281/zenodo.7215161<span>.</span></p>
Present‑day crustal deformation across the Daliang Shan, southeastern Tibetan Plateau: constrained by a dense GPS network
<p><strong>1. Intensive observations</strong> </p> <p>In this study, we collected and processed GPS data from three sources to obtain a crustal horizontal velocity field. The dataset from the first source was raw GPS observations primarily from Phase I of the Crustal Movement Observation Network of China (CMONOC), which was resurveyed every 2 or 3 years from 1999 to 2007, and Phase II of the CMONOC, which involved campaign surveys every year from 2009 to 2020 and continuous surveys from 2010. The dataset from the second source was obtained from the National Key Research and Development Program of China. This dataset contained data from 31 continuous-measurement sites located close to the Anninghe–Zemuhe–Daliangshan fault zone, which were operated from August 2019 to August 2021, and 38 campaign sites from the National GPS Geodetic Control Network of China (NGGCNC), which were measured in 2014 and 2019. All of the campaign surveys used dual-frequency GPS receivers and choke ring antennas, with an operation of 3–4 consecutive days. The dataset from the third source consisted of published GPS velocities from existing studies of the Daliang Shan and its adjacent areas.In this study, we collected and processed GPS data from three sources to obtain a crustal horizontal velocity field. The dataset from the first source was raw GPS observations primarily from Phase I of the Crustal Movement Observation Network of China (CMONOC), which was resurveyed every 2 or 3 years from 1999 to 2007, and Phase II of the CMONOC, which involved campaign surveys every year from 2009 to 2020 and continuous surveys from 2010. The dataset from the second source was obtained from the National Key Research and Development Program of China. This dataset contained data from 31 continuous-measurement sites located close to the Anninghe–Zemuhe–Daliangshan fault zone, which were operated from August 2019 to August 2021, and 38 campaign sites from the National GPS Geodetic Control Network of China (NGGCNC), which were measured in 2014 and 2019. All of the campaign surveys used dual-frequency GPS receivers and choke ring antennas, with an operation of 3–4 consecutive days. The dataset from the third source consisted of published GPS velocities from existing studies of the Daliang Shan and its adjacent areas.</p> <p><strong>2. Data processing</strong></p> <p>We employed the GAMIT and GLOBK software (Herring et al., 2015a, 2015b) to process the raw GPS data and derived the GPS positioning time series with respect to the international terrestrial reference frame for 2014 (ITRF2014) (Altamimi et al., 2017). We utilized the GAMIT software to process the double-differenced carrier-phase observations and acquired regional daily loosely constrained solutions for the site coordinates and satellite orbits. The geophysical models used have been described by Hao et al. (2021). In addition, we employed the same strategy to process ~70 evenly distributed ITRF core GPS sites to acquire global daily loosely constrained solutions. Then, we employed the GLOBK software to combine the same regional and global daily solutions to obtain a GPS time series.</p> <p>Three large earthquakes occurred in the study area: the 2004 M 9.1 Sumatra earthquake, the 2008 M 8.0 Sichuan Wenchuan earthquake, and the 2013 M 7.0 Sichuan Lushan earthquake. For the GPS time series for the campaign sites, we utilized the coseismic slip model of the 2004 Sumatra earthquake (Chlieh et al., 2007). We interpolated the coseismic displacements of the 2008 Wenchuan earthquake (Shen et al., 2009) to correct the coseismic offsets. We only used the data observed before 2008 for those GPS sites contaminated by significant postseismic deformation related to the 2008 Wenchuan earthquake (Wang & Shen, 2020). For the GPS sites affected by the coseismic deformation caused by the 2013 Lushan earthquake (Jiang et al., 2014), we also used data observed before the mainshock to mitigate the coseismic and postseismic deformation. After removing the transient deformation caused by the earthquakes, we used the weighted least-squares adjustment method to estimate linear trends of the velocities. We used the linear trend, seasonal variations, coseismic offset, and color noise model for the continuous GPS sites to fit the time series. We utilized the maximum likelihood estimation (MLE) technique and the CATS software (Williams et al., 2004; Williams., 2008) to estimate the characteristics of the noise in the residuals of the GPS time series after removing the linear trend and seasonal variations (Hao et al., 2016). Then, we obtained the GPS velocities with respect to the ITRF2014 and applied Euler rotation to transfer it to the Eurasia-fixed frame (Altamimi et al., 2017).</p> <p>The reference frames of the GPS velocities reported in previous studies are different from ours. Therefore, to transfer the latter to our selected frame, we employed the Helmert transformation with four parameters through common sites for our velocities and the published velocities. We only chose spatially uniformly distributed common sites with post-fit residuals of less than 1.0 mm/yr in the north-ward and east-ward components. Finally, we derived the geodetically consistent GPS crustal movement in the Daliang Shan and its adjacent areas with respect to the stable Eurasian Plate. Additionally, in order to reduce the residual rigid motion caused by the far-field reference of the Eurasian Plate, we chose the stable South China block as the near-field reference frame. Subsequently, our derived GPS velocities were translated into the South China block reference frame using the published Euler rotation vectors (Hao et al., 2019).</p> <p> </p> <p><strong>References </strong></p> <p>Altamimi, Z., Métivier, L, Rebischung, P., Rouby, H., Collilieux, X., 2017. ITRF2014 plate motion model. Geophys. J. Int. 209:1906–1912</p> <p>Chlieh, M., Avouac, J. P. , Hjorleifsdottir, V. , Song, T. , Ji, C. , Sieh, K., Sladen, A., Hebert, H., Prawirodirdjo, L., Bock, Y., Galetzka, J., 2007. Coseismic slip and afterslip of the great <em>M</em>w 9.15 Sumatra-Andaman earthquake of 2004. Bulletin of the Seismological Society of America, 97(1A), 152–173.</p> <p>Hao, M., Freymueller, J. T., Wang, Q. L., Cui, D. X., Qin, S. L. 2016. Vertical crustal movement around the southeastern Tibetan Plateau constrained by GPS and GRACE data. Earth and Planetary Science Letters, 437, 1-8. http://dx.doi.org/10.1016/j.epsl.2015.12.038.</p> <p>Hao, M., Li, Y., Zhuang, W., 2019. Crustal movement and strain distribution in east Asia revealed by GPS observations. Scientific Reports, https://doi.org/10.1038/s41598-019-53306-y, 16797.</p> <p>Hao, M., Wang, Q., Zhang, P., Li, Z., Li, Y., Zhuang, W., 2021. “Frame wobbling” causing crustal deformation around the Ordos block. Geophysical Research Letters 48, e2020GL091008. https://doi.org/10.1029/2020GL091008.</p> <p>Herring, T.A., King, R.W., McClusky, S.C., 2015a. GAMIT reference manual, GPS analysis at MIT, Release 10.6. Massachusetts Institute of Technology, Cambridge.</p> <p>Herring, T.A., King, R.W., McClusky, S.C., 2015b. GAMIT reference manual, global Kalman filter VLBI and GPS analysis program, Release 10.6. Massachusetts Institute of Technology, Cambridge.</p> <p>Jiang, Z., Wang, M., Wang, Y., Wu, Y., Che, S., Shen, Z.K., Bürgmann, R., Sun, J., Yang, Y., Liao, H., Li, Q., 2014. GPS constrained coseismic source and slip distribution of the 2013 Mw6.6 Lushan, China, earthquake and its tectonic implications. Geophysical Research Letters 41, 407–413, doi:10.1002/2013GL058812.</p> <p>Shen, Z.K., Sun, J., Zhang, P., Wan, Y., Wang, M., Bürgmann, R., Zeng, Y.H., Gan, W.J., Wang, Q.L., 2009. Slip maxima at fault junctions and rupturing of barriers during the 2008 Wenchuan earthquake. Nat Geosci 2:718–724.</p> <p>Wang, M., Shen, Z.K., 2020. Present-day crustal deformation of continental China derived from GPS and its tectonic implications. J. Geophys. Res. 125 (2) https://doi. org/10.1029/2019JB018774.</p> <p>Williams, S.D.P., 2008. CATS: GPS coordinate time series analysis software. GPS Solutions, 12, 147–153. <a href="http://dx.doi.org/10.1007/s10291-007-0086-4">http://dx.doi.org/10.1007/s10291-007-0086-4</a>.</p> <p>Williams, S.D.P., Bock, Y., Fang, P., Jamason, P., Nikolaidis, R.M., Prawirodirdjo, L., Miller, M., Johnson, D.J. 2004. Error analysis of continuous GPS position time series. J. Geophys. Res. 109 (B03412). http://dx.doi.org/10.1029/2003JB002741.</p> <p> </p> <p> </p>
InSAR time-series and FEM Model of the Post-seismic Surface Deformation following the 2013 Baluchistan Earthquake
<p>Subduction zone accretionary prisms are commonly modeled as elastic structures where permanent deformation is accommodated by faulting and folding of otherwise elastic materials, yet accretionary prisms may exhibit other deformation styles over relatively short time scales. In this study, we use 6.5-year (2014-2021) Sentinel-1 InSAR time-series of post-seismic deformation in the Makran accretionary prism of southeast Pakistan to characterize non-linear viscoelastic deformation within an active accretionary prism on short timescales (months to years). We constructed a series of 3-D finite-element models of the Makran subduction zone, including an accretionary prism, and constrained the elastic thickness of the upper wedge and the flow-law parameters (power-law exponent, activation enthalpy, and pre-exponential constant) of the lower wedge through forward model fits to the InSAR time-series. Our results show that the prism is elastically thin (8-12 km) and the non-linear viscoelastic relaxation of the deep portions of the prism alone can sufficiently explain the post-seismic surface deformation. Our best fitting flow-law parameters (<em>n</em> = 3.76±0.39, <em>Q</em> = 82.2±37.73 kJ mol<sup>-1</sup>, and <em>A</em> = 10<sup>-3.36±4.69</sup>) are consistent with triggering of low temperature dislocation creep within fluid-saturated siliciclastic rocks. We believe that the fluids necessary for this weakening originate from sedimentary underplating and/or the presence the hydrocarbons. The presence of power-law rheology within the lower wedge impacts the estimated plate coupling and the stress state in the subduction system, with respect to the conventional elastic wedge model, and hence need to be considered in future earthquake cycle models.</p>
Dynamics of Surface Deformation Induced By Dikes and Cone Sheets in a Cohesive Brittle Coulomb Crust Data
<p>Two files containing raw surface monitoring data from two experimental series and one file containing the analysis of the processed surface monitoring data.<br> <br> </p>
High resolution dataset of plastic deformation at cryogenic temperatures in a nickel-based superalloy
<p>A nickel-based superalloy is examined during monotonic deformation at cryogenic temperatures, reaching as low as liquid helium temperature. A detailed multimodal analysis of the microstructure and plasticity is conducted to discern changes in deformation mechanisms and plastic deformation localization under cryogenic conditions. This study employs high-resolution digital image correlation to identify the deformation mechanisms and understand their influence on plastic deformation localization as the temperature varies. At cryogenic temperatures, unusual plastic deformation localization processes are observed, attributed to the competing activation of a range of deformation processes. Furthermore, a mechanism of slip delocalization, i.e., local plastic deformation homogenization through closely spaced slip, is noted at these extreme temperatures. Ultimately, the impact of the microstructure is identified across the temperature range, from room to cryogenic temperatures.</p>
Data+Analysis+Plotting scripts for "Constraint on the dissipative tidal deformability of neutron stars"
<p>The .zip file contains three directories. </p> <p>1. GW170817-Strain: the raw data (glitch free). Downloaded from https://gwosc.org/events/GW170817/.<br>2. Bilby-Output: the output from running our Bilby sampling scripts. These can be found at https://github.com/JLRipley314/NRTidal-D/tree/main<br>3. Plotting-Scripts: the plotting scripts we used in our paper https://arxiv.org/abs/2312.11659.</p> <p>NOTE: If you want to make sure the plotting scripts work properly, you should download bilby and related dependencies as described in https://github.com/JLRipley314/NRTidal-D/tree/main (or at https://doi.org/10.5281/zenodo.11589416)</p>
Research Data - Microstructural and material property changes in severely deformed Eurofer-97
<p>Research data and associated processing and plotting scripts for the article:</p> <p>Song <em>et al</em>., 'Microstructural and material property changes in severely deformed Eurofer-97', <em>Materials Characterization</em>, 114144, 2024</p> <p><a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.matchar.2024.114144" target="_blank" rel="noreferrer noopener"><span><span>https://doi.org/10.1016/j.matchar.2024.114144</span></span></a></p>
Data supporting "Influence of water on crystallographic preferred orientation patterns in a naturally-deformed quartzite"
<p>These files contain supporting data for the manuscript: "<span>Influence of water on crystallographic preferred orientation patterns in a naturally-deformed quartzite</span>", submitted to Solid Earth.</p> <p>1) an excel file containing FTIR data, aspect ratios, and crystallographic orientation data of quartz</p> <p>2) a powerpoint file containing a animated gif illustrating how quartz CPO in the studied sample changes with increasing water content</p>
Data bundle for "The role of beta-titanium ligaments in the deformation of dual phase titanium alloys"
<p>Data bundle for "The role of ¥â-titanium ligaments in the deformation of dual phase titanium alloys"</p> <p>Tea-Sung Jun1,2, Xavier Maeder3, Ayan Bhowmik1,a, Gaylord Guillonneau3,4, Johann Michler3, Finn Giuliani1, T. Ben Britton1*<br> 1 Department of Materials, Royal School of Mines, Imperial College London, London SW7 2AZ, UK<br> 2 Department of Mechanical Engineering, Incheon National University, Incheon 22012, Republic of Korea<br> 3 EMPA, Swiss Federal Laboratories for Materials Science and Technology, Laboratory for Mechanics of Materials and Nanostructures, Feuerwerkerstrasse 39, CH-3602 Thun, Switzerland<br> 4 Universite de Lyon, Ecole Centrale de Lyon, LTDS UMR CNRS 5513, 36 Avenue Guy de Collongue, 69134 Ecully Cedex, France<br> a now at Rolls-Royce@NTU Corporate Lab, Nanyang Technological University, Singapore</p> <p>For more information please contact: b.britton@imperial.ac.uk (Ben Britton)</p> <p>---</p> <p>This data bundle contains 1 file and 5 subfolders:</p> <p>Figures - all the images that were included in the paper<br> Subfolder for Figure 4 - raw data for load vs. displacement<br> Subfolder for Figure 7(A) - raw data for engineering stress vs. engineering strain <br> Subfolder for Figure 7(B) - cross court data and images of beta vertical micropillar <br> Subfolder for Figure 7(C) - cross court data and images of beta inclined micropillar<br> Subfolder for Figure 10 - raw data for stress relaxation vs. time</p>
Deformed iron data set
<p>This is a reduced (software binned) data set. The full resolution version of this data set is published here: 10.5281/zenodo.1214829</p> <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>
Figure 1 in Spinal deformities in Amazon sailfin catfish Pterygoplichthys pardalis (Siluriformes: Locariidae), an introduced fish in the Palizada River (Southeastern Mexico)
Figure 1. - Collection area of Amazon sailfin catfish in the Palizada River, Campeche, Mexico.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.