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1,255 results for “High-resolution”
Figure 7 in High-resolution survey indicates high heterogeneity in copepod distribution in the hydrologically active Drake Passage
Figure 7. Biomass (mg/m3) of dominant copepods in the layer 0–200 m. Dotted line: boundary of the Polar Front.
Figure 1 in High-resolution survey indicates high heterogeneity in copepod distribution in the hydrologically active Drake Passage
Figure 1. Distribution of dominant copepod species in the Subantarctic Zone (SAZ), Polar Frontal Zone (PFZ) and Antarctic Zone (AZ). PF, Polar Front. Wide solid line indicates maximal abundance (75–100% of maximal recorded values), thin solid line indicates intermediate abundance (50–75% of maximal recorded values), and thin dotted line indicates minimal abundance (<50% of maximal recorded values).
Figure 3 in High-resolution survey indicates high heterogeneity in copepod distribution in the hydrologically active Drake Passage
Figure 3. (A) Examples of the T-S diagrams for Polar Frontal Zone (St. 2060), Polar Front (St. 2088) and Antarctic Zone (St. 2105). (B) Current vectors at a depth of 100 m (Koshlyakov et al., 2010). Circles mark hydrological stations, depths <2500 m are shaded.
Figure 6 in High-resolution survey indicates high heterogeneity in copepod distribution in the hydrologically active Drake Passage
Figure 6. Contribution of dominant copepods to the total biomass of each zone. 1. Calanus simillimus; 2. Calanoides acutus; 3. Rhincalanus gigas; 4. remaining species. PFZ, Polar Frontal Zone; PF, Polar Front; AZ, Antarctic Zone.
Figure 5 in High-resolution survey indicates high heterogeneity in copepod distribution in the hydrologically active Drake Passage
Figure 5. Distribution of chlorophyll a values integrated over the euphotic zone (Chlph) in the study area in the Drake Passage, October–November 2008 (Demidov et al. 2011). Open circles indicate stations. PFZ, Polar Front Zone; PF, Polar Front; AZ, Antarctic Zone; SPC, South Polar Current.
Figure 8 in High-resolution survey indicates high heterogeneity in copepod distribution in the hydrologically active Drake Passage
Figure 8. Contribution of the dominant species and groups of zooplankton to the total biomass along the transects.
Redefining floristic zones in the Korean Peninsula using high-resolution georeferenced specimen data and self-organizing maps
<p>The use of biota to analyze the distribution pattern of biogeographic regions is essential to gain a better understanding of the ecological processes that cause biotic differentiation and biodiversity at multiple spatiotemporal scales. Recently, the collection of high-resolution biological distribution data (e.g., specimens) and advances in analytical theory have led to the quantitative analysis and more refined spatial delineation of biogeographic regions. This study was conducted to redefine floristic zones in the southern part of the Korean Peninsula and to better understand the eco-evolutionary significance of the spatial distribution patterns. Based on 309,333 distribution data of 2,954 vascular plant species in the Korean Peninsula, we derived floristic zones using self-organizing maps. We compared the characteristics of the derived regions with those of historical floristic zones and ecologically important environmental factors (climate, geology, and geography). In the clustering analysis of the floristic assemblages, four distinct regions were identified, namely, the cold floristic zone (Zone I) in high-altitude regions at the center of the Korean Peninsula, cool floristic zone (Zone II) in high-altitude regions in the south of the Korean Peninsula, warm floristic zone (Zone III) in low-altitude regions in the central and southern parts of the Korean Peninsula, and maritime warm floristic zone (Zone IV) including the volcanic islands Jejudo and Ulleungdo. Totally, 1,099 taxa were common to the four floristic zones. Zone IV showed the highest abundance of specific plants (those found in only one zone), with 404 taxa. Our study improves floristic zone definitions using high-resolution regional biological distribution data. It will help better understand and re-establish regional species diversity. In addition, our study provides key data for hotspot analysis required for the conservation of plant diversity.</p>
Datasets for :Atmospheric chemistry of oxalate: Insight into the role of relative humidity and acidity from high-resolution observation.
<p>The datasets in this file were used to generate figures for the paper titled"Atmospheric chemistry of oxalate: Insight into the role of relative humidity and acidity from high-resolution observation."</p> <p>The datasets include the hourly concentration of atmospheric composition and meteorological parameters in Nanjing Area.</p>
High-resolution X-ray computed tomography images of Bentheim sandstone under elevated stress
<p>A dry sample of Bentheim (or Bentheimer) sandstone was characterized using 3D X-Ray microscopy (Versa XRM-500, XRadia-Zeiss) at three different confining pressures of 1 MPa, 20 MPa, and 30 MPa and two voxel sizes of (1.5854 µm)<sup>3</sup> and (3.3452 µm)<sup>3</sup>. The 5-mm-diameter, 20-mm-long dry sample was placed inside a custom-made pressure sell (Lebedev et al, 2017). The sample was subjected to confining pressure of 20 MPa and 3200 radiographs were acquired, then confining pressure was reduced to 1MPa and the sample was imaged again, finally, the sample was pressurized up to 30MPa and the final image set was taken. Image reconstruction was done using internal software (XRadia-Zeiss).</p>
Datasets related to paper "Crustal structure and fault geometries of the Garhwal Himalaya, India: Insight from new high-resolution gravity data modeling and PSO inversion"
<p>The files include Satellite gravity data, topography and earthquake data used in the paper "Crustal structure and fault geometries of the Garhwal Himalaya, India: Insight from new high-resolution gravity data modeling and PSO inversion" by Chamoli A., Rana S., Dwivedi D., Pandey A.K.. This has been submitted to Journal of Geophysical Research: Solid Earth. Restrictions applied to the availability of the land gravity data set.</p>
High-resolution African HLA resource uncovers HLA-DRB1 expression effects underlying vaccine response: summary statistics
<p>How human genetic variation contributes to vaccine immunogenicity and effectiveness is unclear, particularly in infants from Africa. We undertook genome-wide association analyses of eight vaccine antibody responses in 2,499 infants from three African countries and identified significant associations across the human leukocyte antigen (HLA) locus for five antigens spanning pertussis, diphtheria and hepatitis B vaccines. Using high-resolution HLA typing in 1,706 individuals from 11 African populations we constructed a continental imputation resource to fine-map signals of association across the class II HLA observing genetic variation explaining up to 10% of the observed variance in antibody responses. Using follicular helper T-cell assays, <em>in silico</em> binding, and immune cell eQTL datasets we find evidence of <em>HLA-DRB1</em> expression correlating with serological response and inferred protection from pertussis following vaccination. This work improves our understanding of molecular mechanisms underlying HLA associations that should support vaccine design and development across Africa with wider global relevance.</p>
High-Resolution Sporadic E Layer Observation Based on Ionosonde using a Cross-Spectrum Analysis Imaging Technique
<p>The package includes the data used in Figures 1 to 6 in the paper “High-Resolution Sporadic E Layer Observation Based on Ionosonde using a Cross-Spectrum Analysis Imaging Technique".</p> <p>Since the raw data of the ionosonde is quite large and difficult to upload, the echo data of the Es layer after high-resolution imaging processing is packed together and uploaded here.</p> <p>All data can be imported and viewed directly by MATLAB with the function of "imagesc".</p> <p>Due to internal delay, the actual range should be obtained by subtracting 5 range bins.</p>
3D-EPI Blip-Up/Down Acquisition (BUDA) with CAIPI and Joint Hankel Structured Low-Rank Reconstruction for Rapid Distortion-Free High-Resolution T2* Mapping
<p>3D-BUDA data acquired from a 3T Siemens scanner and a 7T Siemens scanner</p>
High-resolution (10 km × 10 km) anthropogenic methane emissions in China in 2020
<p>This dataset is a comprehensive and bottom-up estimate of China's anthropogenic CH4 emissions in 2020 from 45 sub-sectors and ~130,000 point sources. Generally, we classify all sources into two major categories: fossil-fuel system and food system. Fossil-fuel system releases CH4 emissions throughout the fossil-fuel related activities, which contains coal/gas/oil supply chain and fossil-fuel related waste management in this study. Food system contains rice cultivation, livestock, biomass burning and food-related waste management in this study. We allocate the annual CH4 emissions in 2020 at a spatial resolution of 0.1° × 0.1° (nearly 10km ×10km), wherein emissions from point sources are precisely allocated at their location information. The remaining anthropogenic sources in provincial level are allocated by the corresponding surrogate indexes, such as gridded gross domestic product (GDP), population, cultivated area and the source-specific surrogate indexes.</p>
High-resolution structural and functional retinal imaging in the awake behaving mouse
<p>Data presented in Communication Biology paper Feng et al. 2023 - 'High-resolution structural and functional retinal imaging in the awake behaving mouse'. Codes for processing and analysis are available on Github: https://github.com/GP-Feng/Awake_Mouse_Imaging_CommBio.git</p>
Data set of ""Reconciling high-resolution strain rate of continental China from GNSS data with the spherical spline interpolation""
<p>Date data of ”Reconciling high-resolution strain rate of continental China from GNSS data with the spherical spline interpolation“</p> <p>"readme.txt" is the description of those zips. And Each zip also contains a "readme.txt", which is a description of the respective zip.</p>
Global high-resolution sea surface hemispherical broadband emissivity dataset (1980-2020)
<p>This is the global sea surface hemispherical broadband emissivity (BBE, 8-13.5 micrometer) dataset (0.1°) derived by a lookup table-based method developed by Cheng et al., (2017). The accuracy of the estimated hemispherical BBE was 0.003 given a wind speed of zero. The foam effect was also incorporated into the BBE dataset.</p> <p>This dataset spans from 1980 to 2020.</p> <p><strong>Dataset Characteristics:</strong></p> <ul> <li>Spatial Coverage: Global</li> <li>Temporal Coverage: 1980.01-2020.12</li> <li>Spectral Range: 8~13.5μm</li> <li>Spatial Resolution: 0.1°</li> <li>Temporal Resolution: Daily (instantaneous at 12:30)</li> <li>Projection: GCS_WGS_1984</li> <li>Data Format: HDF</li> </ul> <p><strong>Citation </strong>(Please cite these papers when using the data)<strong>:</strong></p> <ol> <li> <p>Cheng, J., et al. (2017). A Lookup Table-Based Method for Estimating Sea Surface Hemispherical Broadband Emissivity Values (8–13.5 μm). <em>Remote Sensing, 9</em></p> </li> <li> <p>Cheng, J., et al. (2013). Estimating the Optimal Broadband Emissivity Spectral Range for Calculating Surface Longwave Net Radiation. IEEE Geoscience and Remote Sensing Letters, 10, 401-405</p> <p>If you have any questions, please contact Prof. Jie Cheng (Jie_Cheng@bnu.edu.cn).</p> </li> </ol>
High-resolution quasi-idealized experiments for future and present-day based upon composites from a decades-long set of recurving landfalling (RCL) North Atlantic ET cases
<p>We present a high-resolution quasi-idealized experiment based upon composites from a decades-long set of recurving landfalling (RCL) North Atlantic extratropical transition (ET) cases. Following Jung and Lackmann (2021), we apply the track-based classification method of Colbert and Soden (2012) to the historical database (1979 to 2018) of North Atlantic RCL ET events; recurving landfalling tropical cyclones (TCs) are defined as those which cross 70°W north of 25°N or cross 65W north of 40N and threaten the U.S. East Coast. We use the Atlantic Hurricane Database (HURDAT2) best-track data (Landsea and Franklin 2013); the track-based classification procedure yields 37 RCL ET cases over the 40-year period. To minimize the spread of the selected ET cases in terms of time to complete transition, we apply a threshold of 36 h as in Jung and Lackmann (2021). As HURDAT2 only specifies when transition is complete but does not provide the timeline of the transition, we supplement it with the cyclone phase space (CPS) method of Hart (2003) to diagnose onset and completion times of ET; ET events are first identified by HURDAT2 and then we compute the CPS parameters to confirm the ET timeline for each event using the ERA5 reanalysis dataset (Hersbach et al. 2020). This filtering process yields 21 RCL ET cases. This dataset is initialized by randomized 15-case composites selected from the 21 RCL ET cases as in Jung and Lackmann (2021). This dataset was used to produce figures and tables in the manuscript of Jung and Lackmann (2023, in review). </p> <p>Due to storage limitations, the full dataset is much too large to be published (~ 500GB). Instead, a subset consisting of 3-hourly atmospheric temperature at 17 vertical levels, zonal and meridional wind at 17 vertical levels, 3 hourly accumulated precipitation, mean sea level pressure, 10-m zonal and meridional wind, sea surface temperature, and relative humidity at 17 vertical levels is presented. If you wish to access the full dataset, please contact one of the authors. </p>
High-resolution structural and functional retinal imaging in the awake behaving mouse
<p>Source data presented in Communications Biology paper Feng et al. 2023 – ‘High-resolution structural and functional retinal imaging in the awake behaving mouse’. Complete processed data presented in Figures 2 and 3 are uploaded along with the raw simultaneously recorded rotary encoder data. Raw SLO video data of only one animal is provided due to the large size. All raw OCT and AOSLO images presented in Figures 4,6-10 are included. Codes for data analysis are available at GitHub: https://github.com/GP-Feng/Awake_Mouse_Imaging_CommBio. For additional data or questions, please contact authors Guanping Feng (gfeng4@ur.rochester.edu) or Jesse Schallek (jschall3@ur.rochester.edu).</p>
Datasets supporting the publication: Evaluating night-time light sources and correlation with socio-economic development using high-resolution multi-spectral Jilin-1 satellite imagery of Quito, Ecuador
<p>##################################</p> <p><strong>Datasets supporting the publication:</strong></p> <p><em>Evaluating night-time light sources and correlation with socio-economic development using high-resolution multi-spectral Jilin-1 satellite imagery of Quito, Ecuador.</em></p> <p>International Journal of Remote Sensing. <a href="https://doi.org/10.1080/01431161.2023.2205983">https://doi.org/10.1080/01431161.2023.2205983</a></p> <p>C. Scott Watson<sup>a</sup>*, John R. Elliott<sup>a</sup>, Marco Córdova<sup>b</sup>, Jonathan Menoscal<sup>b</sup>, Santiago Bonilla-Bedoya<sup>c</sup></p> <p><em><sup>a</sup>COMET, School of Earth and Environment, University of Leeds, LS2 9JT, UK</em></p> <p><em><sup>b</sup>Facultad Latinoamericana de Ciencias Sociales, FLACSO, Quito, Ecuador</em></p> <p><em><sup>c</sup>Research Center for the Territory and Sustainable Habitat, Universidad Tecnológica Indoamérica,Machala y Sabanilla, 170301, Quito, Ecuador</em></p> <p><strong>-Please refer to the publication for details on the production of each dataset.<br> -Please cite the publication and this dataset repository when using the data.</strong></p> <p>##################################</p> <p><strong>Data:</strong></p> <table> <tbody> <tr> <td><strong>File</strong></td> <td><strong>Description</strong></td> </tr> <tr> <td>J1_mosaic_max.tif</td> <td>Mosaicked Jilin-1 multi-spectral night-time image of Quito, Ecuador. Acquisition: 8th July 2021 at ~10:30 UTC (05:30 local time)</td> </tr> <tr> <td>corine_landcover_S2_20210705T153621_20210705T154215_T17MQV.tif</td> <td>Land cover classification applied to a Sentinel-2 image (5th July 2021)</td> <td> </td> </tr> <tr> <td>corine_landcover_symbology_qgis.txt</td> <td>Land cover classification symbology for QGIS</td> </tr> <tr> <td>light_type_classification.tif</td> <td>Light type classification: class 1 = LED, class 10 = HPS.</td> </tr> <tr> <td>classified_light_locations.shp</td> <td>Classified light source (point) locations</td> </tr> </tbody> </table>
ScienceDex guides
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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.