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55 results for “Lithology”
Fig. 4 in New Stratigraphic Data from the Erlian Basin: Implications for the Division, Correlation, and Definition of Paleogene Lithological Units in Nei Mongol (Inner Mongolia)
Fig. 4. Above, The Arshanto Formaiton (middle beds) and Irdin Manha Formation (upper beds) at the Nuhetingboerhe locality; the arrow points to the upper hiatus between the two formatitons. Below, Close-up view of the upper hiatus showing the lithology and erosional surface.
Fig. 3 in New Stratigraphic Data from the Erlian Basin: Implications for the Division, Correlation, and Definition of Paleogene Lithological Units in Nei Mongol (Inner Mongolia)
Fig. 3. Above, Beds at the transition of the Nomogen (lower) and Arshanto (upper) at the Huheboerhe locality. Below, Close-up view of the lower hiatus showing the lithology and erosional surface between the Nomogen and Arshanto fomarions.
Fig. 2 in New Stratigraphic Data from the Erlian Basin: Implications for the Division, Correlation, and Definition of Paleogene Lithological Units in Nei Mongol (Inner Mongolia)
Fig. 2. Above, Paleogene outcrops at the Nuhetingboerhe locality. The arrow points to the lower hiatus between the Nomogen (lower) and Arshanto (upper) formations; Below, Close-up view of the lower hiatus showing the lithology and erosional surface.
Fig. 1. A in New Stratigraphic Data from the Erlian Basin: Implications for the Division, Correlation, and Definition of Paleogene Lithological Units in Nei Mongol (Inner Mongolia)
Fig. 1. A. Localities (black dots) of the Erlian Basin, Nei Mongol (Inner Mongolia). The shaded area indicates the location of the Nuhetingboerhe-Huheboerhe area (NHA). B. Topographic map of NHA. The black bars indicate positions of measured sections at the Daoteyin Obo, Nuhetingboerhe, Wulanboerhe (Huheboerhe of Meng et al., 2004), and Huheboerhe.
Text-fig. 2. Studied section in Jirásek's Quarry with essential data on lithology and samples studied on rhynchonelliform brachiopods and trilobites (black dots – productive, white dots – barren). in Rhynchonelliform Brachiopods And Trilobites Of The 'Upper Dark Interval' In The Koněprusy Area Devonian, Eifelian, Kačák Event; The Czech Republic
Text-fig. 2. Studied section in Jirásek's Quarry with essential data on lithology and samples studied on rhynchonelliform brachiopods and trilobites (black dots – productive, white dots – barren).
Text-fig. 2. Geological setting of the studied sites. a: Stratigraphic position of the Mospyne Formation in the Carboniferous succession of the Donets Basin. b: Stratigraphic position of the studied locality of ammonoids (numbers in circles to the right of the lithological column). c–f: Some studied localities, c – stratigraphic level with ammonoids No. 8, d – stratigraphic level No. 4, e – stratigraphic level No. 3, f – part of the section of the Mospyne Formation in Sukha Ravine and the position of stratigraphic levels with ammonoids. Abbreviations: Tour. – Tournaisian, Serpukhov. – Serpukhovian, Kasimov. – Kasimovian. in Late Bashkirian Ammonoids From The Mospyne Formation Of The Donets Basin, Ukraine
Text-fig. 2. Geological setting of the studied sites. a: Stratigraphic position of the Mospyne Formation in the Carboniferous succession of the Donets Basin. b: Stratigraphic position of the studied locality of ammonoids (numbers in circles to the right of the lithological column). c–f: Some studied localities, c – stratigraphic level with ammonoids No. 8, d – stratigraphic level No. 4, e – stratigraphic level No. 3, f – part of the section of the Mospyne Formation in Sukha Ravine and the position of stratigraphic levels with ammonoids. Abbreviations: Tour. – Tournaisian, Serpukhov. – Serpukhovian, Kasimov. – Kasimovian.
Text-fig. 6. Stratigraphic distribution of ammonoids in the Mospyne Formation. The lithological symbols are the same as in Text-fig. 2. in Late Bashkirian Ammonoids From The Mospyne Formation Of The Donets Basin, Ukraine
Text-fig. 6. Stratigraphic distribution of ammonoids in the Mospyne Formation. The lithological symbols are the same as in Text-fig. 2.
Varanasi Lithologs
<p>Lithological logs retrieved from Varanasi through Project SANDHI GQV at IIT Kharagpur</p>
Borehole Lithological Facies Dataset for Interval Kriging
<p>Four sets of well log data and predefined grids for performing the interval kriging estimation. </p>
Figure 2 in High-resolution stratigraphy of the Changhsingian (Late Permian) successions of NW Iran and the Transcaucasus based on lithological features, conodonts and ammonoids
Figure 2. The Permian–Triassic boundary sections in the Ali Bashi Mountains, NW Iran.
River bed sediment and debris flow deposit lithology and Schmidt Hammer Rock Strength dataset, Suiattle River, Washington State, USA
<p>This dataset includes measurements of river bed sediment lithology and Schmidt Hammer Rock Strength (SHRS), as well as debris flow deposit lithology, grain size, and SHRS, at sites along the Suiattle River, North Cascades, Washington State, USA. See Pfeiffer et al. (2022, JGR-ES) for further description of the collection methodology and site description.</p>
BRUSTEL Tables of central peak lithologies and CRISM signatures
<p>Tables and Supplementary material from Brustel et al. <em>Global scale remnants of early Martian Noachian crust (JGR)</em></p> <p>Tables including the morphology and CRISM signatures of massive rocks in central peaks of impact craters. Table 1: CRISM detections and other information displayed in figure 4, 5, 8 and 9. More details on the labels at the end of the table. Table 2: Morphology of central peaks rocks, Figure 4.</p> <p>''Supplementary Material'' includes figure S1 to S4.</p>
Text-fig. 2. Lithologic profiles from "Kazimierz" openpit and BK-110 borehole. in Micropalaeontological Taphocoenoses Of The Miocene Poznań Formation (Konin Area, Central Poland)
Text-fig. 2. Lithologic profiles from "Kazimierz" openpit and BK-110 borehole.
Data for "To heal or not to heal? Part I: The effect of pore fluid pressure on the frictional healing behavior of Oklahoma lithologies"
<p>This dataset includes the original data files for each experiment in csv format, the mat version with an additional friction column, the hold picks, the velocity step picks, and the RSFitting results. They have the following names:</p> <ul> <li>UC####.csv</li> <li>UC####.mat</li> <li>UC##_hold_picks.mat</li> <li>UC##_healing_picks.mat</li> <li>UC##_VS_RSFit.mat</li> </ul> <p>The CSV and mat files include the on-sample shear displacement data labeled LVDT1 and LVDT2 and the on-sample radial displacement data labeled LVDT3. All data files except for the RSFit include an OG_Index column which is consistent across files for each experiment, such that it provides a unique indicator for each datapoint. Note that all experiment numbers are available in the main text, except for UC0094, which is shown in the supplement text S6.</p>
Fig. 7. Sketch profile from the locality 10 in New Stratigraphic Data from the Erlian Basin: Implications for the Division, Correlation, and Definition of Paleogene Lithological Units in Nei Mongol (Inner Mongolia)
Fig. 7. Sketch profile from the locality 10 miles southwest of the Camp Margetts (Granger, 1930).
Generating a Labeled Dataset to Train Machine Learning Algorithms for Lithological Classification of Drill Cuttings
<p>This dataset contains 16,700 fully labeled SEM images of rock chips isolated from 14 thin sections of drill cutting samples. These samples come from a low-permeability reservoir in western Canada.</p>
Bedrock rivers are steep but not narrow: Hydrological and lithological controls on river geometry across the USA
<p>Dataset used in the article:</p> <p>Buckley, J, Hodge RA and Slater L. 2024. Bedrock rivers are steep but not narrow: Discharge and lithological controls on river geometry across the USA. <a href="https://doi.org/10.1130/G51627.1" target="_blank" rel="noopener">https://doi.org/10.1130/G51627.1</a></p> <p>All data apart from rock type and precipitation are from National Rivers and Streams Assessment 2008-2009 data (U.S. Environmental Protection Agency, 2016). Lithology data were extracted from the Geology of the Conterminous United States dataset (Schruben et al., 1994). Precipitation data are from https://prism.oregonstate.edu/normals/.</p> <p>This dataset has been updated to reflect the changes made to the second revised version of the paper.</p> <p><strong>Acknowledgements</strong></p> <p>The National Rivers and Streams Assessment 2008-2009 data were a result of the collective efforts of dedicated field crews, laboratory staff, data management and quality control staff, analysts and many others from EPA, states, tribes, federal agencies, universities, and other organizations. Please contact <a href="mailto:nars-hq@epa.gov">nars-hq@epa.gov</a> with any questions.</p> <p><strong>References</strong></p> <p>Schruben, P.G., Arndt, R.E., Bawiec, W.J., and Ambroziak, R.A., 1994, Geology of the Conterminous United States at 1: 2,500,000 Scale–A Digital Representation of the 1974 PB King and HM Beikman Map: US Geological Survey: Digital Data Series, DDS-11, scale, v. 1, p. 2500000.</p> <p>U.S. Environmental Protection Agency, 2016, National Rivers and Streams Assessment 2008-2009:, https://www.epa.gov/national-aquatic-resource-surveys/data-national-aquatic-resource-surveys (accessed September 2021).</p> <p> </p>
Lithological controls on soil geochemistry regulate microbial carbon use efficiency and carbon storage
<p><span>The data supporting the findings of the study titled "Lithological controls on soil geochemistry regulate microbial carbon use efficiency and carbon storage". lithology mediates the effects of soil aggregates and minerals on microbial carbon use efficiency and microbial necromass stability. Furthermore, despite high mineral abundance reduced microbial carbon use efficiency, it enhanced microbial necromass stabilization through organo-mineral associations.</span></p>
Source data of the lithologic indicators of climate for NC
<p>Source data are the ~290 Ma (Figure 4a) and ~280 Ma (Figure 4b) lithologic indicators of climate from Boucot et al. (2013).</p>
Supplementary Data for Crelier et al. (2025) entitled "Mobility of South America's Transcontinental Drainage Divide and Shrinkage of the Paraná River Basin Linked to Lithologic and Geodynamic Controls"
<p>Supplementary Data for Crelier et al. (2025) entitled “Mobility of South America’s Transcontinental Drainage Divide and Shrinkage of the Paraná River Basin Linked to Lithologic and Geodynamic Controls” and published in Springer Nature's Scientific Reports.</p>
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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.