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212 results for “sandstone”
Supplementary material to: Long-term (bio)deterioration of Fe-containing and Fe-depleted sandstones: An experimental insight into biotic and abiotic interactions.
<p>This dataset includes: micorphotographs, scanning electron microscope images and related EDS spectra, thermal analysis (DSC-TG), grain size distribution. Abbreviations used in the supplementary file names refer to: GMB (growth medium inoculated with the bacteria, Pseudomonas fluorescens), GM (sterile growth medium), ARE (artificial root exudates), H2O (water), NR (Sample Nowa Ruda), Z (Sample Żerkowice ŻR).</p>
Supplementary material to: Bioweathering of Egyptian Nubian sandstone and Theban limestone: three months insight by experimental incubation
<p>This dataset includes: microscope images, scanning electron microscope images and related EDS spectra, thermal analysis (DSC-TG), grain size parameters, XRD data. Abbreviations used in the supplementary file names refer to: S3: Nubian sandstone sample S3, S6: Nubian sandstone sample S6, TL: Theban limestone sample, SEM afterEXP: scanning electron microscope observations made after termination of the experiment, SEM: scanning electron microscope, XRD: X-ray powder diffraction.</p>
Multi-resolution X-Ray micro-CT images of Bentheimer Sandstones
<p>This dataset consists of multi-resolution X-Ray micro-tomography images of two Bentheimer sandstone rock cores. The rock cores were first used experimentally in [1] with further modelling in [2]. This new dataset is used directly in the publication [3] - preprint available at https://arxiv.org/abs/2111.01270. </p> <p>The original dataset from [1] (of the same rock cores) is hosted on the BGS National Geoscience Data Centre, ID #130625 at dx.doi.org/10.5285/5f899de8-4085-4370-a45e-e613f27e8f1d and there is also a subvolume image dataset, for easier download available on the Digital Rocks Portal, project 229, DOI:10.17612/KT0B-SZ28 at digitalrocksportal.org/projects/229. </p> <p>The images provided herein are from two distinct Bentheimer rock cores -- core 1 and core 2. The cores have diameter, 12.35mm, lengths 73.2mm and 64.7mm, core-averaged porosities of 0.203 and 0.223 and permeabilities of 1.636D and 0.681D for core 1 and 2, respectively. Core 2 has a clear low permeability lamination occurring at 2/3 of the total core length, whereas core 1 has a general fining towards the outlet of the core creating a reduction in porosity [1].</p> <p>The images were acquired with a Zeiss Versa 510 X-Ray CT scanner. We acquired images of two sub volumes from each core, at locations 1/3rd (subvolume 1) and 2/3rds (subvolume 2) of the way along the core length, at resolutions of 2, 6 and 18 microns. We refer to the 2 micron images as high-resolution (HR), the 6 micron images as low-resolution (LR) and the 18 micron images as very-low-resolution (VLR). There are also super-resolution (SR) images created at 2 micron resolution from the LR images, using a deep-learning algorithm. There are also cubic interpolation images created from the LR image - these are labels bicubic. These have a resolution of 2 microns, and size equal to the HR and SR images. Details of the SR and LR Bicubic generation are found in [3]. The following scanning protocols were used for the direct imaging:</p> <p>2 micron images:<br> --We use a 4x microscope objective, an exposure time of 8s, 2x averaged binning, 9001 projections, a scan voltage of 80kV and a power of 7W. Each scan takes approximately 24 hours.</p> <p>6 micron images:<br> --We use a flat panel detector, an exposure time of 0.7s, 10x repeat frames, 1x averaged binning, 2401 projections, a scan voltage of 80kV and a power of 7W. The cone angle is 14.46 degrees and the fan angle is 22.2 degrees. Each scan takes approximately 1 hour.</p> <p>18 micron images:<br> --We use a 0.4x microscope objective, an exposure time of 1s, 10x repeat frames, 1x averaged binning, 2401 projections, a scan voltage of 80kV and a power of 7W. The cone angle is 12.65 degrees and the fan angle is 12.65 degrees. Each scan takes approximately 2 hours.</p> <p>We present 4 sets of the images with different levels of processing. All images are mutual registered to each other. Each image filename has a Core#_Subvol#_resolution identifier, either with the actual resolution (e.g. 6) or the short form (e.g. LR). The following name endings are used</p> <p>(1) - '_16bit_LE.raw'. These are the .raw images of little-endian format. Preceding this filename is also the cubic image side length in voxels, e.g. _75cube. 12 images in total.</p> <p>(2) - '_16bit_LE_normalised.raw'. These are the .raw images of little-endian format with normalised greyscale values following the procedure in [1]. Preceding this filename is also the cubic image side length in voxels, e.g. _75cube. 12 images in total.</p> <p>(3) - 'Core1_Subvol1_HR' etc. These are the .tiff images of (2) above, which have been converted to 8 bit. Includes bicubic interpolation images and SR images, but no 16 micron images, since these were not used in the analysis of [3]. 16 images in total. </p> <p>(4) - 'Core1_Subvol1_HR_filtered' etc. These are the .tiff images from (3) above, which have filtered using non-local means filtering. More details are found in [3]. Note there are no SR images here since they are already essentially filtered, and included in (3) above. 12 images in total.</p> <p><br> <strong>References</strong><br> <br> [1] Jackson, S.J., Lin, Q. and Krevor, S. 2020. Representative Elementary Volumes, Hysteresis, and Heterogeneity in Multiphase Flow from the Pore to Continuum Scale. Water Resources Research, 56(6), e2019WR026396</p> <p>[2] Zahasky, C., Jackson, S.J., Lin, Q., and Krevor, S. 2020. Pore network model predictions of Darcy‐scale multiphase flow heterogeneity validated by experiments. Water Resources Research, 56(6), e e2019WR026708.</p> <p>[3] Jackson, S.J, Niu, Y., Manoorkar, S., Mostaghimi, P. and Armstrong, R.T. 2021. Deep learning of multi-resolution X-Ray micro-CT images for multi-scale modelling. Under review, preprint available at https://arxiv.org/abs/2111.01270 </p>
CT-Scan Image Dataset of Residual Fluid-Driven Fracture in a Molasse de Villarlod Sandstone Core - Post-Radial Hydraulic Fracture Experiment - M03 Sample
<h3><strong>Dataset Description</strong></h3> <p>This dataset contains high-resolution CT-scan images that capture the residual fracture surface within a core sample of Molasse de Villarlod Sandstone. The core sample was extracted after conducting a radial hydraulic fracture experiment on a 25 × 25 × 25 cm cubic block of sandstone (M03 sample). The experiment was designed to simulate fluid-driven fracture propagation and closure, and the resulting fracture path was preserved in the core sample.</p> <p><strong>Core Location in the M03 Cube Sample:</strong></p> <ul> <li><strong>Z:</strong> 12.5 cm</li> <li><strong>South-North:</strong> 12.5 cm</li> <li><strong>West-East:</strong> 11.5 cm to 1.36 cm (Coring direction)</li> </ul> <p>This spatial information specifies the exact location and orientation of the core extraction within the M03 cube sample.</p> <h4><strong>CT-scan instrument details:</strong></h4> <p>The M03 sample was analyzed using an X-ray micro-CT scanner (RX-Solutions Ultratom) under consistent scanning protocols and parameters. A reflective 230 kV microfocus X-ray source (Hamamatsu L10801) equipped with a 0.2 mm thick copper filter, a tungsten cathode, and a tungsten target was employed for the imaging process. The scans were conducted with a voltage of 120 kV and a current intensity of 80 mA.</p> <p>The volume data acquisition was performed in continuous helical mode, ensuring complete coverage of the sample’s height. For sample M03, 6 full rotations were executed, with 1312 projections captured for each 360° rotation, allowing for highly precise volume reconstruction. The X-ray beam attenuation was recorded by an XL Varex Paxscan 2530HE plane detector with a resolution of 2176 x 1792 pixels, and an exposure time of 0.50 seconds per projection.</p> <p>The acquired projections were processed using RX-Solutions X-act software with Filtered Backprojection to reconstruct a corrected volume. This reconstruction yielded approximately 9000 slices in 16-bit TIFF format, with voxel dimensions of 10 x 10 x 10 microns, providing detailed insights into the internal structure of the sample.</p> <h4><strong>Key Features:</strong></h4> <ul> <li> <p><strong>Fracture Characteristics</strong>: The fracture observed in the CT-scans represents a residual opening that remains post-fracturation. It is entirely contained within the core, showcasing the internal fracture geometry resulting from the hydraulic fracturing process.</p> </li> <li> <p><strong>CT-Scan Details</strong>: The CT-scans were taken perpendicular to the fracture surface, offering a detailed cross-sectional view of the fracture at different depths. This orientation is critical for accurately capturing the fracture morphology and allows for the reconstruction of the fracture surface in 3D.</p> </li> <li> <p><strong>Material Information</strong>: The core sample is composed of Molasse de Villarlod Sandstone, a sedimentary rock which is porous (18% porosity) and permeable. This material choice is relevant for studying fracture closure subjected to the leak-off of the fluid inside the porous medium.</p> </li> <li> <p><strong>Experimental Context</strong>: The radial hydraulic fracture experiment aimed to simulate the propagation of hydraulic fracture and its closure due to the leakage of fluid inside fracture into the porous medium. The dataset provides valuable insights into fracture propagation patterns, surface roughness, and the effects of fluid-driven fractures in porous media.</p> </li> </ul> <h4><strong>Applications:</strong></h4> <p>This dataset is particularly valuable for researchers and engineers involved in:</p> <ul> <li>Fracture mechanics and surface characterization</li> <li>3D reconstruction and visualization of fracture surfaces</li> <li>Surface roughness analysis</li> <li>Hydraulic fracturing studies</li> <li>Geomechanical modeling</li> </ul> <h4><strong>File Structure:</strong></h4> <p>The dataset is organized into zip-folder contains .tif images corresponding to different depths within the core. Each tif-image is a CT-scan for that specific depth, labeled according to their position along the fracture path.</p> <h4><strong>Processing code:</strong></h4> <p>Follow the <strong>URL repository</strong> in the software section to access to the code for processing these images and reconstructing the fracture surfaces.</p> <p><strong>Acknowledgment:</strong></p> <p>We would like to extend our deepest thanks to Gary Perrenoud, Albert Taureg, and Lionel Pittet, the technical specialists of the PIXE platform at École Polytechnique Fédérale de Lausanne (EPFL). Their expertise and support in operating the CT-scan machine were important to the success of this research. We greatly appreciate their dedication and the high-quality work they provided.</p> <p><strong>Contact and Support:</strong></p> <p>Email:</p> <p>Brice Lecampion: brice.lecampion@epfl.ch</p> <p>Mohsen Talebkeikhah: m.talebkeikhah@gmail.com</p>
Experimental data for fracture toughness analysis of sandstone and granite samples under fluid saturation conditions
<p>This database includes experimental results from mode I fracture toughness (KIC) tests conducted on saturated rock specimens. Three lithologies were studied: a porous siliceous sandstone (Corvio, C) and two high-strength, low-porosity granites (Blanco Mera, BM and Blanco Alba, BA). Tests were conducted at room pressure and temperature using the pseudo-compact tension (pCT) methodology. Seven different fluids were used: deionized water, methanol, NaCl-saturated water, mineral oil, diesel fuel, an acidic HCl solution, and a caustic NaOH solution.</p>
Pore network data for Heletz sandstones
<p>CT-scan image of Heletz sandstone and extracted network data from CT-scan images for Heletz sandstone.</p>
Sandstone rock tomographic data, i12 beamline, DLS synchrotron
<p>This data compliments a paper <i>Conditional generative adversarial networks for stripe artefact removal in high-resolution X-ray tomography </i>by D. Kazantsev, L. Beveridge, V. Shanmugasundar and O. Magdysyuk to be published in the <strong>Tomography of Materials and Structures</strong> journal in 2023 (to be updated). This data alongside the data from <a href="https://zenodo.org/records/1443568#.ZBREbUjP1qN">here</a> was used to train the network to remove stripe artefacts. </p><p>The code is written in Python and located at: https://github.com/dkazanc/NoStripesNet</p>
Automatic detection of clefts and corridors within the sandstone plateau - Szczeliniec Wielki & Szczeliniec Mały mesas, Poland
<p>This dataset presents the method of automatic clefts and corridors detection within areas of highly dissected relief. This methodical approach was developed for a geomorphological study on Szczeliniec Wielki and Szczeliniec Mały sandstone mesas (Stołowe Mts., SW Poland) (Migoń et al. 2023)</p> <p>Contents:</p> <ol> <li>CleftHunter_manual_v1_0.pdf - short method description</li> <li>kernel_examples.zip - set of exemplary kernel files </li> <li>Szczeliniec_Wielki_clefts_threshold_depth_2m.zip - raster dataset of automatically detected clefts within the plateau of Szczeliniec Wielki (.tif)</li> <li>Szczeliniec_Maly_clefts_threshold_depth_2m.zip - raster dataset of automatically detected clefts within the plateau of Szczeliniec Mały (.tif)</li> <li>Szczeliniec_Wielki_mesa_caprock_base.zip - Szczeliniec Wielki caprock zone (.shp, polygon)</li> <li>Szczeliniec_Maly_mesa_caprock_base.zip - Szczeliniec Mały caprock zone (.shp, polygon)</li> <li>Szczeliniec_Wielki_mesa_caprock_hillshade.zip - shaded relief of the Szczeliniec Wielki plateau (.tif)</li> <li>Szczeliniec_Maly_mesa_caprock_hillshade.zip - shaded relief of the Szczeliniec Mały plateau (.tif)</li> </ol> <p>Preferred citation:</p> <p>Migoń P., Duszyński F., Jancewicz K., Kotowska M., Porębna W. (2023), Surface-subsurface connectivity in the morphological evolution of sandstone-capped tabular hills – how much analogy to karst?. Geomorphology vol. 440, Id 108884, 1–22<br>DOI: 10.1016/j.geomorph.2023.108884</p> <p> </p> <p>This research was funded by National Science Centre, Poland, research project no. 2020/39/D/ST10/00861.</p>
Investigations on single and multi-grain optically stimulated luminescence (OSL) sensitivity and electron spin resonance (ESR) signals in quartz derived from sandstones: Insights on provenance of quartz in ancient depositional systems
<p><span>Trapped charge techniques of luminescence and electron spin resonance (ESR) are classic tools for dating Quaternary deposits. Over the past decade, these techniques have been routinely applied to investigate provenance and /or the sedimentary history of grains based on the different luminescence and ESR characteristics of quartz. Of these, optically stimulated luminescence (OSL) sensitivity is one of the most widely investigated parameter for luminescence-based provenance approach. A majority of studies on this parameter are based on evaluation of multi-grain OSL sensitivity of the samples. This is particularly concerning because single-grain quartz luminescence studies have shown that the luminescence signal of a multi-grain aliquot is contributed by less than ~1-10% of the total grains. Since the sole criteria for discrimination of sources based on luminescence sensitivity relies on its intensity, therefore the results based on multi-grain analysis will most likely be skewed depending on the proportion and ‘brightness’ of a few grains. This demands a need to evaluate the potential of single-grain quartz OSL sensitivity in provenance studies. In this study, we investigate single and multi-grain quartz OSL sensitivities from compositionally different sandstones with well-characterised sources based on U-Pb zircon ages. We further complement this analysis with characterisation of ESR centres commonly used in quartz provenance, namely E’<sub>1</sub> and [AlO<sub>4</sub>]<sup>0</sup> centres. Our study shows that single-grain quartz OSL sensitivity can help distinguish between sediments that have a predominant input from a single source as compared to those with contribution from multiple sources, which otherwise cannot be inferred from multi-grain studies. Moreover, our results on characterisation of quartz-based ESR intensity of E’<sub>1</sub> and saturated [AlO<sub>4</sub>]<sup>0</sup> centres successfully differentiates between sandstones and further complements the luminescence-based characterisation. </span></p>
Three-dimensional Digital Outcrop Models of the Tullig Sandstone, Western Irish Namurian Basin, Co. Clare, Ireland
<p>Tullig Sandstone is part of the Tullig Cyclothem, Western Irish Namurian Basin, Co. Clare, Ireland. The Tullig Sandstone is a prominent sandstone interval that represents an ancient fluvial-deltaic system. </p> <p>Outcrops of the Tullig Sandstone were surveyed by an unmanned aerial vehicle (UAV, DJI Mavic Pro Platinum™). Three-dimensional digital outcrop models were generated from images collected from UAV using Agisoft Metashape™.</p>
Dataset for the journal article: " In-situ Capillary Pressure and its Interrelationships with Flow Characteristics during Steady-state Three-phase Flow in Water-wet Berea Sandstone"
<p>Dataset 1 contains the summary results of the image analysis performed on a set of three-phase micro-CT images. <br> The analysis are:(1) Fluid saturations, (2) Characteristics of Gas clusters, (3) Characteristics of Oil clusters, (4) Pore-fluid occupancy, and (5) In-situ capillary pressure measurements. </p> <p>Dataset 2 contains the three-phase relative permeability data with the correction analysis. </p>
Text-fig. 4. Porechye open pit coal mine. a: photography of the Lipovtsy Formation section; b: stratigraphic column, 1 – sandstone, 2 – conglomerate, 3 – coal, 4 – tuff dated by U-Th-Pb geochronology, 5 – siltstone, 6 – mudstone, 7 – palynological samples with angiosperm pollen, 8 – dispersed angiosperm cuticles. in Angiosperm Diversification In The Early Cretaceous Of Primorye, Far East Of Russia
Text-fig. 4. Porechye open pit coal mine. a: photography of the Lipovtsy Formation section; b: stratigraphic column, 1 – sandstone, 2 – conglomerate, 3 – coal, 4 – tuff dated by U-Th-Pb geochronology, 5 – siltstone, 6 – mudstone, 7 – palynological samples with angiosperm pollen, 8 – dispersed angiosperm cuticles.
Text-fig. 3. Outcrop cross section of the turbidite facies distribution in the Majalengka, correlated northwest to southeast. The progradation pattern indicated by thickening of sandstone into the basin area are shown. F1 – heterolithic sandstone-mudstone 1; F2 – heterolithic sandstone-mudstone 2; F3 – mudstone facies; F4 – heterolithic fine sand and mudstone; F5 – conglomeratic to massive sandstone facies (Muljana 2012). in Lithofacies And Ichnofacies Of Turbidite Deposits, West Java, Indonesia
Text-fig. 3. Outcrop cross section of the turbidite facies distribution in the Majalengka, correlated northwest to southeast. The progradation pattern indicated by thickening of sandstone into the basin area are shown. F1 – heterolithic sandstone-mudstone 1; F2 – heterolithic sandstone-mudstone 2; F3 – mudstone facies; F4 – heterolithic fine sand and mudstone; F5 – conglomeratic to massive sandstone facies (Muljana 2012).
Text-fig. 4. a: Conglomeratic to massive sandstone facies 1, facies A are composed of Andesit (AF), Clay (CF) and Sandstone (SF) fragments lain on medium-sandstone. b: Conglomeratic to massive sandstone facies, outcropping of massive sandstone facies comprises of fine to medium grain size of grey to yellowish sandstone. c: Heterolithic sandstone-mudstone facies, intercalation of fine sand with silt and shale as type form of heterolithic sandstone mudstone as indicated by a high sand/shale ratio. d: Example outcrops of heterolithic sandstone-mudstone 2 indicated by low sand/shale ratio. e: Heterolithic fine sand and mudstone and mudstone facies, intercalation of thin sandstone and shale. f: Representative of slump deposits outcrops belong to conglomeratic to massive sandstone facies, which is indicated by the intercalation of sandstone and shale and some disturbed beds or layers as seen in slump deposits. The facies type is normally deposited within the basin floor, channel margin or as a product of the overbank deposits. In this figure the slump deposit is shown as internal bedding, some occurred on the bedding-plane. Trend slope measurement of the fold-axis revealed values N 135°E and N 108°E. in Lithofacies And Ichnofacies Of Turbidite Deposits, West Java, Indonesia
Text-fig. 4. a: Conglomeratic to massive sandstone facies 1, facies A are composed of Andesit (AF), Clay (CF) and Sandstone (SF) fragments lain on medium-sandstone. b: Conglomeratic to massive sandstone facies, outcropping of massive sandstone facies comprises of fine to medium grain size of grey to yellowish sandstone. c: Heterolithic sandstone-mudstone facies, intercalation of fine sand with silt and shale as type form of heterolithic sandstone mudstone as indicated by a high sand/shale ratio. d: Example outcrops of heterolithic sandstone-mudstone 2 indicated by low sand/shale ratio. e: Heterolithic fine sand and mudstone and mudstone facies, intercalation of thin sandstone and shale. f: Representative of slump deposits outcrops belong to conglomeratic to massive sandstone facies, which is indicated by the intercalation of sandstone and shale and some disturbed beds or layers as seen in slump deposits. The facies type is normally deposited within the basin floor, channel margin or as a product of the overbank deposits. In this figure the slump deposit is shown as internal bedding, some occurred on the bedding-plane. Trend slope measurement of the fold-axis revealed values N 135°E and N 108°E.
Text-fig. 2. E-W cross section of the Urema Graben from Gorongosa to Inhaminga adapted from Flores (1973: fig. 5). Note that in this schema the Mazamba Sandstone directly overlies the Cheringoma Limestone. I.P.CO No. 5 is a bore hole. Vertical exaggeration ×10. in Stratigraphy, Chronology And Palaeontology Of The Tertiary Rocks Of The Cheringoma Plateau, Mozambique
Text-fig. 2. E-W cross section of the Urema Graben from Gorongosa to Inhaminga adapted from Flores (1973: fig. 5). Note that in this schema the Mazamba Sandstone directly overlies the Cheringoma Limestone. I.P.CO No. 5 is a bore hole. Vertical exaggeration ×10.
Text-fig. 5. East-west cross section of the Urema Graben and Cheringoma Plateau adapted from Pfaffhuber et al. (2009). The Urema Graben is ca. 45–50 km broad. Note that in this scheme, the Eocene Limestone (i.e., the Cheringoma Fm) is overlain by Oligocene sandstone in the position mapped as Mazamba Formation by Real (1966) and by Tinley (1977). in Stratigraphy, Chronology And Palaeontology Of The Tertiary Rocks Of The Cheringoma Plateau, Mozambique
Text-fig. 5. East-west cross section of the Urema Graben and Cheringoma Plateau adapted from Pfaffhuber et al. (2009). The Urema Graben is ca. 45–50 km broad. Note that in this scheme, the Eocene Limestone (i.e., the Cheringoma Fm) is overlain by Oligocene sandstone in the position mapped as Mazamba Formation by Real (1966) and by Tinley (1977).
Text-fig. 2. Moderately dipping Oligocene layers of the Mány Member in the eastern part of the Strázsa Hill quarry, SW of Zsámbék. The claymarl and siltstone layers cover sandstone and conglomerate. The arrow indicates the position of fossiliferous layers. Photo: László Fodor. in The Late Oligocene Macroflora Of Zsámbék, Central Hungary
Text-fig. 2. Moderately dipping Oligocene layers of the Mány Member in the eastern part of the Strázsa Hill quarry, SW of Zsámbék. The claymarl and siltstone layers cover sandstone and conglomerate. The arrow indicates the position of fossiliferous layers. Photo: László Fodor.
Pore network modeling data for Fontainebleau and Berea Sandstones
<p>This data set contains results from pore network modeling of one sample of dry Fontainebleau sandstone (Case 1), and two samples of Berea sandstones (dry, Case 2, oil and water saturated, case 3). For each sample, there are two .csv file. One file containing information about pockets (pores) and the other containing information about throats. The content of each column is described in the heading of the files.</p> <p> </p>
Text-fig. 6. Geological plan of Malo-Mikhaylovka. 1 – andesito-dacite; 2 – coarse-grained tuff; 3 – argillitic tuffite; 4 – tuffitic sandstone; 5 – lignite, coal clay; 6 – lenses of tuffitic conglomerate; 7 – acidic tuff; 8 – dacite; 9 – andesito-basalt; 10 – basalt; 11 – sandstone; 12 – andesite; 13 – break; 14 – inclination/direction of beds; 15 – plant-bearing levels; 16 – talus. in Mid-Latitude Palaeogene Floras Of Eurasia Bound To Volcanic Settings And Palaeoclimatic Events - Experience Obtained From The Far East Of Russia (Sikhote-Alin') And Central Europe (Bohemian Massif)
Text-fig. 6. Geological plan of Malo-Mikhaylovka. 1 – andesito-dacite; 2 – coarse-grained tuff; 3 – argillitic tuffite; 4 – tuffitic sandstone; 5 – lignite, coal clay; 6 – lenses of tuffitic conglomerate; 7 – acidic tuff; 8 – dacite; 9 – andesito-basalt; 10 – basalt; 11 – sandstone; 12 – andesite; 13 – break; 14 – inclination/direction of beds; 15 – plant-bearing levels; 16 – talus.
Text-fig. 8. Basalts, agglomerates and coarse tuffs (dark) and plant-bearing coarse tuffaceous sandstones with fossil plants (light) on the Nitusi Cape, Siziman locality. in Mid-Latitude Palaeogene Floras Of Eurasia Bound To Volcanic Settings And Palaeoclimatic Events - Experience Obtained From The Far East Of Russia (Sikhote-Alin') And Central Europe (Bohemian Massif)
Text-fig. 8. Basalts, agglomerates and coarse tuffs (dark) and plant-bearing coarse tuffaceous sandstones with fossil plants (light) on the Nitusi Cape, Siziman locality.
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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.