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48 results for “Basement”
Enhanced 3D velocity structure, seismicity relocation and basement characterization of Changning shale gas and salt mining regions in Sichuan Basin
<p>This repository contains the datasets and results of the joint inversion-based Vp/Vs model consistency constrained double difference seismic tomography carried out for the manuscript titled “Enhanced 3D velocity structure, seismicity relocation and basement characterization of Changning shale gas and salt mining regions in Sichuan Basin.” Included are the following: column descriptions of data files, catalog earthquake information (CX_event.dat), relocated events after inversion (CX_tomoDDMC.reloc), inverted Vp model (CX_Vpmodel.dat), inverted Vs model (CX_Vsmodel.dat) and inverted Vp/Vs model (CX_VpVsmodel.dat). Please consult the manual for tomoDD by Zhang and Thurber (2003) for detailed formats of these files. In addition, an averaged velocity model (MOD_averaged) computed based on the inversion results is included, and the converged model (Vp_model_reinverted) resulting from the reinversion, as well as basement structure data for Figure 14.</p>
Regional scale surface of the top of the Variscan basement in some sector of Italy - Supplementary material
<p>The dataset represent the Supplementary material of thew manuscript entitled "Map of the top of the Variscan basement in some sectors of Italy" now under revision.</p> <p>The Supplementary material consist of 9 files:</p> <ul> <li>input data: <ul> <li>dataset_CROP.csv</li> <li>deep_wells.csv</li> <li>domains.geojson</li> <li>thrusts_2.geojson</li> <li>INA_data_point.csv</li> </ul> </li> <li>output data: <ul> <li>INA_depth_1km.csv</li> <li>ONA_OA_ISA_AF_depth_5km.csv</li> <li>INA_contour.geojson</li> <li>ONA_OA_ISA_AF_contour.geojson</li> </ul> </li> </ul>
Fracture Data Supporting: 'The 2024 Mw4.8 New Jersey Intraplate Earthquake: Preferential Rupture of an Immature Fault in Frictionally Unstable Basement Rocks'
<p>The spreadsheets contain fracture and paleoslip surface datasets measured across the epicentral region of the April 5, 2024 Mw4.8 New Jersey earthquake. Datasets contain coordinates of outcrops, strike, dip, and trend/plunge or rake (where slickenlines are observed).</p>
Text-fig. 11. Permian ichthyofaunas from the French Massif Central. Preliminary comparisons based on total accounts of individuals (see text for explanations). Sharks in green, Acanthodes sp. in yellow, Actinopterygians in blue, Dipnoi in white (not visible but present at Autun; see Tab. 1 for details). Each circle is proportional to the total number of specimens recovered. Permian outcrops in black. Hercynian basement indicated by vertical lines. Map modified from Gand and Durand (2006). in New Actinopterygians From The Permian Of The Brive Basin, And The Ichthyofaunas Of The French Massif Central
Text-fig. 11. Permian ichthyofaunas from the French Massif Central. Preliminary comparisons based on total accounts of individuals (see text for explanations). Sharks in green, Acanthodes sp. in yellow, Actinopterygians in blue, Dipnoi in white (not visible but present at Autun; see Tab. 1 for details). Each circle is proportional to the total number of specimens recovered. Permian outcrops in black. Hercynian basement indicated by vertical lines. Map modified from Gand and Durand (2006).
Composition-based estimates of the thermal properties of New Zealand basement rocks: data used for calculations and figures
<p>This archive contains four files with compositional data (mineralogical and geochemical) used to estimate thermal conductivity and heat production in New Zealand basement terranes (Kirkby et al., 2024).</p> <p><br>HPR_source_data.csv - contains K, Th, and U concentrations and calculated heat production rates.</p> <p>Longitude - longitude (New Zealand Geodetic Datum)<br>Latitude - latitude(New Zealand Geodetic Datum)<br>K_wtpct - K concentration in weight percent<br>Th_ppm - Th concentration in ppm<br>U_ppm - U concentration in ppm<br>Heat_production_uW/m3 - heat production calculated from K, Th and U concentrations, in microWatts per meter cubed<br>Terrane - name of basement terrane that sample has been assigned to<br>Source - source of data, either PetLAB (Strong et al. 2016), PMAP (Turnbull ref) or separate compilation for this study<br>Reference - Reference citation for data as listed in PetLAB/PMAP or added for this study</p> <p> </p> <p>TC_from_majors_PMAP.csv - contains thermal conductivity estimated from major element geochemistry (Kirkby et al., 2024) using method of, Jennings et al. (2019).<br>Columns are as follows:</p> <p>Collection - collection that sample is contained in within the PetLAB database (Strong et al., 2016)<br>Collection_Number - sample number within the collection above<br>Sample_ID - unique sample ID in PetLAB<br>Analysis_ID - unique analysis ID in PetLAB<br>Longitude - longitude (New Zealand Geodetic Datum)<br>Latitude - latitude(New Zealand Geodetic Datum)<br>**_wtpct - major oxide concentration in weight percent (normalised to non-volatile component)<br>Terrane - name of basement terrane that sample has been assigned to<br>Analysis_Method - analysis method for major oxide concentrations<br>Thermal_conductivity_pred - calculated estimate of thermal conductivity based on major oxide composition, W/mK<br>Bib_ref - analysis source reference, direct copy of Bib_ref field in PetLAB<br>Reference - analysis source reference, direct copy of Reference field in PetLAB</p> <p><br>TC_from_modal_mineralogy.csv - contains thermal conductivity estimated from modal mineralogy (Kirkby et al., 2024).<br>Columns are as follows:</p> <p>Longitude - longitude (New Zealand Geodetic Datum)<br>Latitude - latitude(New Zealand Geodetic Datum)<br>Analysis_ID - unique analysis ID in PetLAB<br>Collection - collection that sample is contained in within the PetLAB database (Strong et al., 2016)<br>Collection_ID - sample number within the collection above<br>Subsample - in the case of thermal conductivity, sometimes two samples were measured. This column distinguishes the two measurements<br>Mineralogy_method - method of determining mineralogy, either point count or QEMSCAN<br>Quartz - percentage of quartz in sample<br>Olivine - percentage of olivine in sample<br>Pyroxene - percentage of pyroxene in sample<br>Other - percentage of other minerals in sample<br>Thermal_conductivity_grain_pred - estimated thermal conductivity (W/mK) from mineralogy (Kirkby et al, 2024), W/mK<br>Thermal_conductivity_dry_measured - measured dry thermal conductivity (W/mK) for samples reported by Sanders et al (2024), W/mK<br>Porosity_measured_pct - measured porosity (percent) for samples reported by Sanders et al (2024)<br>Thermal_conductivity_grain_measured - grain thermal conductivity (W/mK) calculated from measured dry thermal conductivity and porosity<br>Terrane - name of basement terrane that sample has been assigned to<br>Bib_ref - analysis source reference, direct copy of Bib_ref field in PetLAB<br>Reference - analysis source reference, direct copy of Reference field in PetLAB</p> <p><br>TC_from_normative_mineralogy.csv</p> <p>Longitude - longitude (New Zealand Geodetic Datum)<br>Latitude - latitude(New Zealand Geodetic Datum)<br>Analysis_ID - unique analysis ID in PetLAB<br>Collection - collection that sample is contained in within the PetLAB database (Strong et al., 2016)<br>Collection_ID - sample number within the collection above<br>Mineralogy_method - method of determining mineralogy, either Mesonorm or CIPWnormhb (CIPW norm with hornblende)<br>Quartz - percentage of quartz in sample<br>Olivine - percentage of olivine in sample<br>Pyroxene - percentage of pyroxene in sample<br>Other - percentage of other minerals in sample<br>Thermal_conductivity_grain_pred - estimated thermal conductivity (W/mK) from mineralogy (Kirkby et al, 2024)<br>Thermal_conductivity_dry_measured - measured dry thermal conductivity (W/mK) for samples reported by Sagar et al (2022)<br>Porosity_measured_pct - measured porosity (percent) for samples reported by Sagar et al (2024)<br>Thermal_conductivity_grain_measured - grain thermal conductivity (W/mK) calculated from measured dry thermal conductivity and porosity<br>Terrane - name of basement terrane that sample has been assigned to<br>Bib_ref - analysis source reference, direct copy of Bib_ref field in PetLAB<br>Reference - analysis source reference, direct copy of Reference field in PetLAB</p> <p> </p> <p>tc_by_terrane.csv</p> <p>Contains thermal conductivity, standard deviation, and standard error of thermal conductivity estimates by terrane as shown in Figure 7 of Kirkby et al (2024)</p> <p> </p> <p>hpr_by_terrane.csv</p> <p>Contains thermal conductivity, standard deviation, and standard error of thermal conductivity estimates by terrane as shown in Figure 7 of Kirkby et al (2024).</p> <p> </p> <p><br>References</p> <p>Jennings, S., Hasterok, D., & Payne, J. (2019). A new compositionally based thermal conductivity model for plutonic rocks. Geophysical Journal International, 219(2), 1377-1394. https://doi.org/10.1093/gji/ggz376<br>Kirkby, A., N. Mortimer, R. Funnell, M. Sagar, A. Seward, K. Faure and F. Sanders (2024). Composition-based estimates of the thermal properties of New Zealand basement rocks, New Zealand Journal of Geology and Geophysics.<br>Sagar, M. W., Funnell, R., Randell, K., Faure, K., Seward, A., Sanders, F., & Stratford, W. R. (2022). Physical properties of Te Riu-a-Māui / Zealandia crustal rocks: Reconnaissance study and future research. (GNS Science Internal Report 2022/05. <br>Sanders, F., Seward, A., Sagar, M., & Faure, K. (2024). Thermal Properties of Zealandia Basement Rocks: results of Thermal Conductivity Scanner measurements 2023. Lower Hutt. (GNS Science Report. <br>Strong, D. T., Turnbull, R. E., Haubrock, S., & Mortimer, N. (2016). Petlab: New Zealand’s national rock catalogue and geoanalytical database. New Zealand Journal of Geology and Geophysics, 59(3), 475-481. https://doi.org/10.1080/00288306.2016.1157086 </p>
Örebro University basement SLAM dataset - Radar, Velodyne
<p>Dataset recorded using the Taurob Tracker in Örebro University. The data includes a novel radar sensor and velodyne data.</p>
Text-fig. 2. Main geological structures of the eastern slope of the Sikhote-Alin' ridge and main plant-bearing localities of the Cenozoic floras. I – Mesozoic folded basement; II – East Sikhote-Alin' Volcanic Belt (Late Cretaceous–Early Palaeocene); III – Near-Shore Basaltic Volcanic Belt (Eocene–Early Miocene); IV – Udyl Basin (Cenozoic); V – Late Neogene to Quaternary plateaubasalts; Va – Sovgavan plateau; Vb – Samarga plateau; Vc – Bikin plateau. 1 – Malo-Mikhaylovka; 2 – Siziman; 3 – Sjurkum; 4 – Botchi; 5 – Dembi; 6 – Bui; 7 – Sonje; 8 – Takhobe; 9 – Amgu; 10 – Velikaya Kema; 11 – Zerkal'naya (former Tadushi). 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. 2. Main geological structures of the eastern slope of the Sikhote-Alin' ridge and main plant-bearing localities of the Cenozoic floras. I – Mesozoic folded basement; II – East Sikhote-Alin' Volcanic Belt (Late Cretaceous–Early Palaeocene); III – Near-Shore Basaltic Volcanic Belt (Eocene–Early Miocene); IV – Udyl Basin (Cenozoic); V – Late Neogene to Quaternary plateaubasalts; Va – Sovgavan plateau; Vb – Samarga plateau; Vc – Bikin plateau. 1 – Malo-Mikhaylovka; 2 – Siziman; 3 – Sjurkum; 4 – Botchi; 5 – Dembi; 6 – Bui; 7 – Sonje; 8 – Takhobe; 9 – Amgu; 10 – Velikaya Kema; 11 – Zerkal'naya (former Tadushi).
Spatial and Temporal Clustering of Anti-Glomerular Basement Membrane Disease
<p><strong>Background and objectives</strong> An environmental trigger has been proposed as an inciting factor in the development of anti-GBM disease. This multicenter, observational study sought to define the national incidence of anti-GBM disease during an 11-year period (2003–2014) in Ireland, investigate clustering of cases in time and space, and assess the effect of spatial variability in incidence on outcome.</p> <p><strong>Design, setting, participants, & measurements</strong> We ascertained cases by screening immunology laboratories for instances of positivity for anti-GBM antibody and the national renal histopathology registry for biopsy-proven cases. The population at risk was defined from national census data. We used a variable-window scan statistic to detect temporal clustering. A Bayesian spatial model was used to calculate standardized incidence ratios (SIRs) for each of the 26 counties.</p> <p><strong>Results</strong> Seventy-nine cases were included. National incidence was 1.64 (95% confidence interval [95% CI], 0.82 to 3.35) per million population per year. A temporal cluster (<em>n</em>=10) was identified during a 3-month period; six cases were resident in four rural counties in the southeast. Spatial analysis revealed wide regional variation in SIRs and a cluster (<em>n</em>=7) in the northwest (SIR, 1.71; 95% CI, 1.02 to 3.06). There were 29 deaths and 57 cases of ESRD during a mean follow-up of 2.9 years. Greater distance from diagnosis site to treating center, stratified by median distance traveled, did not significantly affect patient (hazard ratio, 1.80; 95% CI, 0.87 to 3.77) or renal (hazard ratio, 0.76; 95% CI, 0.40 to 1.13) survival.</p> <p><strong>Conclusions</strong> To our knowledge, this is the first study to report national incidence rates of anti-GBM disease and formally investigate patterns of incidence. Clustering of cases in time and space supports the hypothesis of an environmental trigger for disease onset. The substantial variability in regional incidence highlights the need for comprehensive country-wide studies to improve our understanding of the etiology of anti-GBM disease.</p>
Basement of a Roman villa in locality Monticchio
The villa is located in Terracina (Italy) and is built on a terracing system in opus quasi quadratum. Nearby there are the remains of a thermal building Source: Objaverse 1.0 / Sketchfab
Basement photogrammetry
A photogrammetry of a small intersection in a post-soviet block of flats basement - it was built in early 60s'. The model is created based on 469 photos taken with Canon 100D. Source: Objaverse 1.0 / Sketchfab
Broadband seismic constraints on the nature of the basement of the Junggar Basin, the southwestern Central Asian Orogenic Belt
<p>The cross-correlation function (CCF) of ambient noise recordings between two receivers under the equipartition assumption.</p> <p>Sacdir is a directory that stores cross-correlation functions between all pairs of seismic stations, with the output format in SAC.</p> <p>Sacdir contains the cross-correlation results of seismic data from 96 permanent stations and 59 temporary stations in the Xinjiang region, spanning 13 months from June 2021 to June 2022, totaling 11,935 pairs.</p> <p>The "CCFs-pairs.txt" file shows the table listing the geographic coordinates of the station pairs of all the CCFs files (in SAC-format) in the Sacdir directory. </p> <p>The processing program is modified from: [CC-FJpy: A Software Package for Ambient Noise Cross-Correlation and Frequency-Bessel Transform Method](https://github.com/ColinLii/CC-FJpy)</p>
Magnetic Anomaly Characteristics and Magnetic Basement Structure in Changning Area of Southern Sichuan Basin
<p>The data are used in the article "Magnetic Anomaly Characteristics and Magnetic Basement Structure in Changning Area of Southern Sichuan Basin".</p>
Basement of the Gujari Mahal, Gwalior Fort
<p>Rectangular performance space in the basement of the Gujari Mahal, Gwalior Fort, Madhya Pradesh.</p>
Stress-State Differences between Sedimentary Cover and Basement of the Songliao Basin, NE China: In-situ Stress Measurements at 6–7 km depth of an ICDP Scientific Drilling Borehole (SK-II)
<p>The excel file is the original ASR test data (Nine samples, 6293 - 6846 m vertical depth).</p>
Evolution of the Greater Caucasus basement and formation of the Main Caucasus Thrust, Georgia
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Data from: Image based modelling of lateral magma flow: the Basement Sill, Antarctica
The McMurdo Dry Valleys magmatic system, Antarctica, provides a world-class example of pervasive lateral magma flow on a continental scale. The lowermost intrusion (Basement Sill) offers detailed sections through the now frozen particle microstructure of a congested magma slurry. We simulated the flow regime in two and three dimensions using numerical models built on a finite-element mesh derived from field data. The model captures the flow behaviour of the Basement Sill magma over a viscosity range of 1–104 Pa s where the higher end (greater than or equal to 102 Pa s) corresponds to a magmatic slurry with crystal fractions varying between 30 and 70%. A novel feature of the model is the discovery of transient, low viscosity (less than or equal to 50 Pa s) high Reynolds number eddies formed along undulating contacts at the floor and roof of the intrusion. Numerical tracing of particle orbits implies crystals trapped in eddies segregate according to their mass density. Recovered shear strain rates (10−3–10−5 s−1) at viscosities equating to high particle concentrations (around more than 40%) in the Sill interior point to shear-thinning as an explanation for some types of magmatic layering there. Model transport rates for the Sill magmas imply a maximum emplacement time of ca 105 years, consistent with geochemical evidence for long-range lateral flow. It is a theoretically possibility that fast-flowing magma on a continental scale will be susceptible to planetary-scale rotational forces.
Lion head - ceramic basement
Photoscanned ceramic lion head Source: Objaverse 1.0 / Sketchfab
Basement, Kalmar Castle, 1550
One end of the admiralitybasement at Kalmar Castle. Source: Objaverse 1.0 / Sketchfab
Datasets generated for the manuscript: The basement membrane regulates the cellular localization and the cytoplasmic interactome of Yes-Associated Protein (YAP) in mammary epithelial cells
<p><strong>File proteinGroups-CoIP-Yap1:</strong> Dataset of co-Immunoprecipitation followed of Yes-associated protein (YAP) followed by proteomics to identify YAP interactants.</p> <p><strong>File Gene_set_file_YAP: </strong>Gene sets used for gene set enrichment analysis.</p> <p><strong>Files enrichr_x: </strong>output of the EnrichR tool</p>
CONTAM Project Files and Exposure Data for An In Silico Investigation of Activity-Related Physical, Chemical, and Biological Pollutant Exposure in Basements Using CONTAM
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Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
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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.