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Fig. 3 in Shelly fossils from the lower Cambrian White Point Conglomerate, Kangaroo Island, South Australia
Fig. 3. The solenopleurid trilobite Trachoparia? sp. from the lower Cambrian White Point Conglomerate, Kangaroo Island, South Australia. Latex cast of partial cranidium (SAM P57221) showing pustulose ornament and strongly tapered glabella in dorsal (A1), anterior (A3), and oblique anterolateral (A4) views; testate cranidium in dorsal view (A2).
Fig. 2 in Shelly fossils from the lower Cambrian White Point Conglomerate, Kangaroo Island, South Australia
Fig. 2. Correlation chart showing shelly fossil biozones against the stratigraphic succession in the Flinders Ranges, Fleurieu Peninsula, and Kangaroo Island (adapted from Betts et al. 2018: fig. 27). Note: The succession in the NE Kangaroo Island is based on the Investigator-1 drill core in which the Mt. McDonnell Formation is not apparent (Gehling et al. 2011). Lower boundary of White Point Conglomerate (WPC) is likely faulted. Abundant and diverse shelly fauna (SSF) from the bioclastic limestone clasts in the WPC have an upper Dailyatia odyssei Zone age. Dashed lines indicate uncertain stratigraphic relationship. Abbreviations: K., Kulparina; P., Parabadiella; S., Sunnaginia.
Weak lensing maps for a pair of point masses in MOND
<p>Figures for the paper: "<span>Peculiar dark matter halos inferred from gravitational lensing as a</span><br><span>manifestation of modified gravity</span>", accepted by Astronomy and Astrophysics on 31/7/2024.</p>
Surrogate waveform model data for black hole binary systems computed in point-particle black hole perturbation theory
<p>This repository contains all publicly available surrogate data for gravitational waveforms produced within the point-particle black hole perturbation theory framework and calibrated to numerical relativity simulations performed with the Spectral Einstein Code (SpEC). </p> <p>Several surrogate models are currently available in this catalog:</p> <ol> <li><strong>BHPTNRSur2dq1e3</strong>, for aligned spin black hole binary systems with mass-ratios varying from 3 to 1000 and spins from −0.8≤χ1≤0.8 on the larger black hole. This surrogate model is trained on waveform data generated by point-particle black hole perturbation theory (ppBHPT) with calibration to numerical relativity (NR) data. The waveforms include all spin-weighted spherical harmonic modes up to ℓ=4 except the (4,1) and m=0 modes. Model details can be found in <a href="https://arxiv.org/abs/2407.18319">Rink et al. 2024</a>. This data file is used to evaluate the surrogate model with either stand-alone Python code hosted by the <a href="https://bhptoolkit.org/BHPTNRSurrogate/">Black Hole Perturbation Toolkit</a> (Jupyter notebook <a href="https://github.com/BlackHolePerturbationToolkit/BHPTNRSurrogate/blob/main/tutorials/BHPTNRSur2dq1e3.ipynb">tutorial</a>) or the GWSurrogate Python package, which can be found on <a href="https://pypi.python.org/pypi/gwsurrogate/">PyPI</a> or <a href="https://anaconda.org/conda-forge/gwsurrogate">conda-forge</a>.</li> <li><strong>BHPTNRSur1dq1e4</strong>, an updated version of the <strong>EMRISur1dq1e4 </strong>model described below. The updated version includes better calibration to NR, a smoother transition to plunge model, and more harmonic modes. Model details can be found in <a href="https://arxiv.org/abs/2204.01972">Islam et al. 2022</a>. This data file is used to evaluate the surrogate model with either stand-alone Python code hosted by the <a href="https://bhptoolkit.org/BHPTNRSurrogate/">Black Hole Perturbation Toolkit</a> (Jupyter notebook <a href="https://github.com/BlackHolePerturbationToolkit/BHPTNRSurrogate/tree/main/tutorials/BHPTNRSur1dq1e4">tutorial</a>) or the GWSurrogate Python package, which can be found on <a href="https://pypi.python.org/pypi/gwsurrogate/">PyPI</a> or <a href="https://anaconda.org/conda-forge/gwsurrogate">conda-forge</a>.</li> <li><strong>EMRISur1dq1e4</strong>, for non-spinning black hole binary systems with mass-ratios varying from 3 to 10000. This surrogate model is trained on waveform data generated by point-particle black hole perturbation theory (ppBHPT), with the total mass rescaling parameter tuned to NR simulations. Available modes are [(2,2), (2,1), (3,3), (3,2), (3,1), (4,4), (4,3), (4,2), (5,5), (5,4), (5,3)]. The m<0 modes are deduced from the m>0 modes. Model details can be found in <a href="https://arxiv.org/abs/1910.10473">Rifat et al. 2019</a>. This data file is used to evaluate the surrogate model with either stand-alone Python code hosted by the <a href="http://github.com/BlackHolePerturbationToolkit/EMRISurrogate">Black Hole Perturbation Toolkit</a> (Jupyter notebook <a href="https://github.com/BlackHolePerturbationToolkit/EMRISurrogate/blob/master/EMRISur1dq1e4.ipynb">tutorial</a>) or the GWSurrogate Python package (Jupyter notebook <a href="https://github.com/sxs-collaboration/gwsurrogate/blob/master/tutorial/notebooks/nonspinning_nr_emri.ipynb">tutorial</a>), which can be found on <a href="https://pypi.python.org/pypi/gwsurrogate/">PyPI</a>.</li> </ol>
Terrestrial Lidar Point Cloud Data for: Evaporation and condensation dynamics within saturated epiphyte communities in a Quercus virginiana forest
<p><span>Terrestrial lidar scans were captured using a BLK360 scanner (Leica Geosystems, Norcross, GA, USA) which has a range of 0.5 – 45 m and measurement rate up to 680,000 points s<sup>−1</sup> at the high-resolution setting. A georeferenced, 3-D point cloud of the study site was generated from 12 scans, approximately 50 m apart in both horizontal directions. Scans were performed in orientations intended to maximize branch exposure to the scanner and to scan during optimal weather conditions to minimize occlusion of features due to noise or movement generated by wind. Scan co-registration was done in Leica Geosystem’s Cyclone Register 360 software using its Visual Simultaneous Localization and Mapping algorithm (Visual SLAM) and resulted in relatively low overall co-registration error ranging from 0.005-0.009 m. From this study site point cloud, manual straight-line measurements from the ground to the sensors were made using Leica’s Cyclone Register 360 software.</span></p>
Flash point of butanol + Fatty Acid Ethyl Esters mixtures
<p>Experimental flash point data for 1-butanol and Fatty Acid Ethyl Esters were measured using a Miniflash FLPH analyzer (Grabner Instruments, Austria) in accordance with ASTM D6450.</p>
LiDAR 2023, RAW point cloud
<h2>Abstract</h2> <p>RAW LiDAR data from new flights on 30/09/23+ 01/10/23, high point density >10pts/sqm. </p> <p>This depositry contains data generated within the European S34 project. </p> <p> </p> <h2>Metadata Information</h2> <table> <tbody> <tr> <td> <p><strong>Identification</strong></p> </td> </tr> <tr> <td> <p>Full Title</p> </td> <td> <p>LiDAR 2023, RAW data</p> </td> </tr> <tr> <td> <p>Abstract</p> </td> <td> <p>RAW LiDAR data from new flights on 30/09/23+ 01/10/23, high point density >10pts/sqm</p> </td> </tr> <tr> <td> <p>Keywords</p> </td> <td> <p>LiDAR, RAW, 3D point cloud</p> </td> </tr> <tr> <td> <p>Pilot area</p> </td> <td> <p>Áramo</p> </td> </tr> <tr> <td> <p>Associated resources</p> </td> <td> <p>LiDAR-Trajectory (SHP)</p> <p>LiDAR footprints (SHP)</p> <p>Point density map (TIF)</p> <p>AOI, Tile definition (SHP)</p> </td> </tr> <tr> <td> <p>Language</p> </td> <td> <p>English</p> </td> </tr> <tr> <td> <p>URL</p> </td> <td> <p>/</p> </td> </tr> <tr> <td> <p>Categories</p> </td> <td> <p>Lidar</p> </td> </tr> <tr> <td> <p><strong>Temporal reference</strong></p> </td> </tr> <tr> <td> <p>Creation date (dd.mm.yyyy)</p> </td> <td> <p>15.12.2023</p> </td> </tr> <tr> <td> <p>Revision date (dd.mm.yyyy)</p> </td> <td> <p>15.12.2023</p> </td> </tr> <tr> <td> <p><strong>Quality and validity</strong></p> </td> </tr> <tr> <td> <p>Representation type</p> </td> <td> <p>Other</p> </td> </tr> <tr> <td> <p>Fromat</p> </td> <td> <p>LAS/LAZ</p> </td> </tr> <tr> <td> <p>Lineage</p> </td> <td> <p>New LiDAR flight to derive high quality terrain data and detect small topographical elements. </p> </td> </tr> <tr> <td> <p>Spatial resolution</p> </td> <td> <p>>10 pts/sqm</p> <p>>20 pts/sqm on the mountain plateau</p> </td> </tr> <tr> <td> <p>Positional accuracy</p> </td> <td> <p><0,15m</p> </td> </tr> <tr> <td> <p>Maintenance information</p> </td> <td> <p>no updates planned</p> </td> </tr> <tr> <td> <p>Coordinate system</p> </td> <td> <p> EPSG 4326</p> </td> </tr> <tr> <td> <p><strong>Constranits related to access and use</strong></p> </td> </tr> <tr> <td> <p>Use limitation</p> </td> <td> <p>/</p> </td> </tr> <tr> <td> <p>Access constraint</p> </td> <td> <p>/</p> </td> </tr> <tr> <td> <p>Public/Private</p> </td> <td> <p>Public</p> </td> </tr> <tr> <td> <p><strong>Responsible organisation</strong></p> </td> </tr> <tr> <td> <p>Responsible Contact</p> </td> <td> <p> Victoria Jadot</p> </td> </tr> <tr> <td> <p>Responsible Party</p> </td> <td> <p>Eurosense</p> </td> </tr> <tr> <td> <p><strong>Metadata on metadata</strong></p> </td> </tr> <tr> <td> <p>Contact</p> </td> <td> <p>Victoria Jadot </p> </td> </tr> <tr> <td> <p>Metadata language</p> </td> <td> <p>English</p> </td> </tr> </tbody> </table>
Comprehensive Single Point Mutational Landscape Analysis of the Monkeypox Virus Proteome
Open the record for dataset details and reuse information.
Cappadocia Mobile LiDAR 3D Point Cloud Dataset
<p>The dataset includes 6 3D point cloud files collected with Velodyne VLP-16 mobile LiDAR (*.las) belonging to 4 cultural and natural heritage structures located in Cappadocia, Türkiye. The structures are:</p> <p>1- St. Theodore Church (Interior & Exterior): The Church of St. Theodore is located in Yeşilöz Village in Ürgüp district of Nevşehir. Formerly known as Tagar, now known as Yesiloz Village is approximately 16 km from the center of Urgup district and is a settlement area built on the slope of the valley. The church was carved into a large rock mass on the hill northwest of the village. As a result of excavations near the village, a monastery with a courtyard on three sides was discovered. It is thought that the church belonged to this monastery. The church is called both St. Theodore and Tagar Church. Although it is not known where the name Theodore comes from, it is estimated that this name may have been given because the church was built in the name of St. Theodore. </p> <p>2- Mustafa Efendi Mosque (Interior & Exterior): The masonry Mustafa Efendi Mosque in Bahçeli Village of Ürgüp District of Nevşehir Province is the oldest of the 3 mosques built in the village. It is estimated that it was built about 50 years before the Osman Efendi Mosque, which was presented as a proposed building within the scope of the project, with a construction date of 1746. Although it is known to have a small inscription with the date of construction, this inscription was not found during the survey. According to this information, Mustafa Efendi Mosque is estimated to be a 17th-18th century work.</p> <p>3- Fairy Chimney: The distance between Bahçeli Village where the fairy chimney is located and Urgup district is 15 kilometers and the formations between these two areas are generally natural formations without caps and in the late fairy chimney period. It shows that the fairy chimney is a natural formation without a cap and in the late fairy chimney period. The fairy chimney is in the 1st degree natural protected area.</p> <p>4- Masonry House: Bahçeli Village, where the building examined within the scope of the project is located, is 15 km away from Ürgüp district and is a mixed settlement type. There are approximately 200 cove-carved and masonry historical buildings in the village. A large part of the village, including the structures examined in the village, is a 3rd degree natural protected area. The masonry-rock-carved civil architecture dwelling in Bahçeli Village, Ürgüp District, Nevşehir has not been in use since the 1980s and some of the spaces have been completely lost.</p> <p>The creation of this dataset was funded by the Scientific and Technological Research Council of Türkiye (TUBITAK) 1001 program under Project no. 122Y017.</p> <div> <div> <div> </div> <div> </div> <div> </div> </div> </div>
Linked collectors and determiners for: On the taxonomy of the desert lizard Liolaemus stolzmanni (Steindachner, 1891) A third point of view (Squamata: Liolaemidae).
Natural history specimen data linked to collectors and determiners held within, "On the taxonomy of the desert lizard Liolaemus stolzmanni (Steindachner, 1891) A third point of view (Squamata: Liolaemidae)". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/5c4392c3-3b82-435e-aa25-b3458f39af89">https://bionomia.net/dataset/5c4392c3-3b82-435e-aa25-b3458f39af89</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/5c4392c3-3b82-435e-aa25-b3458f39af89">https://gbif.org/dataset/5c4392c3-3b82-435e-aa25-b3458f39af89</a>. Formatted as a Frictionless Data package.
Linked collectors and determiners for: Fossil butterflies, calibration points and the molecular clock (Lepidoptera: Papilionoidea).
Natural history specimen data linked to collectors and determiners held within, "Fossil butterflies, calibration points and the molecular clock (Lepidoptera: Papilionoidea)". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/6c479acc-8b18-4f0b-a6e5-85bcd6d7b6b7">https://bionomia.net/dataset/6c479acc-8b18-4f0b-a6e5-85bcd6d7b6b7</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/6c479acc-8b18-4f0b-a6e5-85bcd6d7b6b7">https://gbif.org/dataset/6c479acc-8b18-4f0b-a6e5-85bcd6d7b6b7</a>. Formatted as a Frictionless Data package.
Linked collectors and determiners for: University of Wisconsin Stevens Point Mammals.
Natural history specimen data linked to collectors and determiners held within, "University of Wisconsin Stevens Point Mammals". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/8a87a58e-5aad-41da-ad0c-07f6888f8796">https://bionomia.net/dataset/8a87a58e-5aad-41da-ad0c-07f6888f8796</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/8a87a58e-5aad-41da-ad0c-07f6888f8796">https://gbif.org/dataset/8a87a58e-5aad-41da-ad0c-07f6888f8796</a>. Formatted as a Frictionless Data package.
Linked collectors and determiners for: NEON Biorepository Aquatic Plant, Bryophyte, Lichen, and Macroalgae Collection (Herbarium Vouchers [Point Counts]).
Natural history specimen data linked to collectors and determiners held within, "NEON Biorepository Aquatic Plant, Bryophyte, Lichen, and Macroalgae Collection (Herbarium Vouchers [Point Counts])". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/3f5df259-243c-4c32-9520-921c89fe689f">https://bionomia.net/dataset/3f5df259-243c-4c32-9520-921c89fe689f</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/3f5df259-243c-4c32-9520-921c89fe689f">https://gbif.org/dataset/3f5df259-243c-4c32-9520-921c89fe689f</a>. Formatted as a Frictionless Data package.
Vertically pointing doppler radar profiles (24 GHz Metek MRR-2) at Concordia Station (Dome C, Antarctica), aggregated to 5min, monthly netCDF archive
<p>Vertical profiles along the first three kilometres of atmosphere above the ground (from 300 to 3000 m AGL) of equivalent radar reflectivity factor (Ze), Doppler velocity (W) and Doppler spectral width (Sw) from a 24-GHz vertically pointing Micro Rain Radar MRR-2 by METEK GmbH positioned at Concordia Station (Dome C, Antarctica).</p> <p>Metadata available at <a href="https://antarcticdatacenter.cnr.it/geonetwork/srv/eng/catalog.search#/metadata/6dc25ff0-4c03-4ca8-af0d-cba06a411dc2" target="_blank" rel="noopener">https://antarcticdatacenter.cnr.it/geonetwork/srv/eng/catalog.search#/metadata/6dc25ff0-4c03-4ca8-af0d-cba06a411dc2</a> </p> <p>--------------------------------------------------------------------</p> <p>Example of netCDF file structure:</p> <h2><strong>File "DMC_MRR_MeK_201901_5min.nc"</strong></h2> <pre><strong> dimensions</strong>: <em>range </em>= 31; <em>time </em>= UNLIMITED; // (7736 currently) <strong>variables</strong>: float <em>Ze</em>(range=31, time=7736); :description = "Equivalent reflectivity factor relative to the most significant peak, dealiased, 5min non-logarithmic average. NaN means clear sky at the specified height."; :units = "dBZ"; :_ChunkSizes = 31U, 1U; // uint long <em>time_UTC(time=7736);</em> :description = "Measurement time. Timestamp indicates the end of the aggregation interval, e.g. 01-Mar-2020 00:05:00 represents the average of the variables between 01-Mar-2020 00:00:01 and 01-Mar-2020 00:05:00."; :time_zone = "UTC"; :units = "Seconds since 1970-01-01 00:00:00 (Unix time)."; :_ChunkSizes = 512U; // uint float <em>W</em>(range=31, time=7736); :description = "Mean Doppler Velocity of the most significant peak, dealiased, 5min average. Value not available in clear-sky conditions."; :units = "m s^-1"; :_ChunkSizes = 31U, 1U; // uint float <em>height</em>(range=31, time=7736); :description = "Height above instrument."; :units = "m"; :_ChunkSizes = 31U, 1U; // uint float <em>spectralWidth</em>(range=31, time=7736); :description = "Doppler Spectral Width of the most significant peak, dealiased, 5min average. Value not available in clear-sky conditions."; :units = "m s^-1"; :_ChunkSizes = 31U, 1U; // uint // <strong>global attributes</strong>: :<em>title </em>= "Micro rain radar data processed with IMProToo (Maahn, M. and Kollias, P., 2012), aggregated to 5min, monthly netCDF archive."; :<em>comment </em>= "IMProToo has been developed for improved snow measurements. Note that this data has been processed regardless of precipitation type."; :<em>time_label </em>= "Jan 2019"; :<em>source </em>= "Micro Rain Radar 2 (MRR-2), METEK GmbH, at DMC (Antarctica), frequency: 24 GHz, power: 50 mW, antenna diameter: 60 cm [https://metek.de/product/mrr-2/]"; :<em>institution </em>= "CNR-INO, Florence (IT)"; :<em>contact_person </em>= "Gianluca Di Natale, CNR-INO, Florence (IT), gianluca.dinatale@ino.cnr.it"; :<em>location </em>= "Concordia Station (Dome C, Antarctica, 75°06\'S, 123°21\'E, 3233 m a.s.l.)"; :<em>author </em>= "Giacomo Roversi, Ca\' Foscari University, Venice (IT) and CNR-ISAC, Rome (IT), g.roversi@isac.cnr.it"; :<em>creation_date </em>= "22-Oct-2024 17:32:24 UTC"; :<em>coverage </em>= "Monthly coverage (Jan 2019): 90.3226 %"; :<em>time_resolution </em>= "5 minutes"; :<em>history </em>= "Created with IMProToo v0.107 [https://github.com/maahn/IMProToo], aggregated to 5 minutes temporal resolution with an average of the 1-minute values if least 3 out of 5 are not NaN."; </pre>
Oriental Honey-Buzzards Dataset | Climate change leads to range contraction for the Oriental Honey-Buzzards: How to point out the future conservation strategies?
<p>This dataset contains raster data (.TIF) in probability and binary outputs of oriental honey-buzzards distribution within the wintering and breeding areas under changing climate.</p> <p><strong>File Size</strong>: ~184 MB (13.8 MB in compressed ZIP file)</p> <p><strong>Format File</strong>:</p> <p><em>ohb_A_B_C</em>.tif (.tfw; .XML; .dbf)</p> <p><strong>A</strong>: breeding or wintering</p> <p><strong>B</strong>: timepoint and scenario. e.g., 2050ssp5 or 2010ssp2</p> <p><strong>C</strong>: binary or probability outputs. e.g., bin or prob. <em>Note: for binary maps, value 0: non-suitable areas for OHB and value 1: suitable areas for OHB</em></p> <p>For further inquiries. Please contact: aryo_acondro@apps.ipb.ac.id</p>
Point clouds from terrestrial laser scanning of 97 trees in St Pancras Old Church, London
<p>Point clouds of 97 trees scanned in the grounds of St Pancras Old Church, Camden, London</p> <p>Tree species is predominantly London Plane (<em>Platanus × hispanica</em>) but also includes the <a href="https://www.atlasobscura.com/places/the-hardy-tree-london-england">Hardy ash tree</a>.</p> <p>Data was captured on 18/7/2017 (leaf-on) with a RIEGL VZ-400 terrestrial laser scanner. 38 scans were conducted from 19 positions. The weather was good, with little to no noticeable wind.</p> <p>Data is a binary PLY format with <em>xyz</em> fields in an arbitrary coordinate system. Trees have been extracted from the global point cloud and have been "cleaned" to remove the ground and neighbouring trees (however there may be some errors). Data has been downsampled to a voxel size of 0.04 m.</p> <p>Raw data can be accessed from here.</p> <p>Please acknowledge the data set authors if using this data.</p>
Point clouds from terrestrial laser scanning of 30 trees along Malet Street, London
<p>Point clouds of 30 street trees scanned along <a href="https://goo.gl/maps/7x3dutn6vHcxVPdC6">Malet Street, London, UK</a>. </p> <p>Tree species is predominantly London Plane (<em>Platanus × hispanica</em>).</p> <p>Data was captured on 8/2/2017 (leaf-off) with a RIEGL VZ-400 terrestrial laser scanner. 24 scans were conducted from 12 positions along the street. The weather was good, with little to no noticeable wind.</p> <p>Data is a binary PLY format with <em>xyz</em> fields in an arbitrary coordinate system. Trees have been extracted from the global point cloud and have been "cleaned" to remove the ground and neighbouring trees (however there may be some errors). Data has been downsampled to a voxel size of 0.04 m.</p> <p>Raw data can be accessed from here.</p> <p>Please acknowledge the data set authors if using this data.</p>
Preliminary displacement analyses over Surfside Florida KMZ file pointing to REST URL
<p><em><strong>Preliminary displacement analyses over Surfside Florida. KMZ file pointing to REST URL. The file can be opened in Google Earth Pro and will allow overlaying displacement results with Google's temporal optical imagery catalog. Contains modified Copernicus Sentinel-1 data. Persistent Scatterers Interferometry (PSI) was performed using SARscape v5.6.</strong></em></p>
Point clouds from terrestrial laser scanning of 74 trees in Russell Square, London
<p>Point clouds of 74 trees scanned in <a href="https://www.google.co.uk/maps/place/Russell+Square/@51.5217533,-0.1280787,17z/data=!3m1!4b1!4m5!3m4!1s0x48761b310bb300bf:0xd1190a08b331324a!8m2!3d51.52175!4d-0.12589">Russell Square, London</a></p> <p>Tree species is predominantly London Plane (<em>Platanus × hispanica</em>).</p> <p>Data was captured on 8/2/2017 (leaf-off) with a RIEGL VZ-400 terrestrial laser scanner. 22 scans were conducted from 11 positions. The weather was good, with little to no noticeable wind.</p> <p>Data is a binary PLY format with <em>xyz</em> fields in an arbitrary coordinate system. Trees have been extracted from the global point cloud and have been "cleaned" to remove the ground and neighbouring trees (however there may be some errors). Data has been downsampled to a voxel size of 0.04 m.</p> <p>Raw data can be downloaded from <a href="https://doi.org/10.5281/zenodo.5070681">10.5281/zenodo.5070681</a></p> <p>Please acknowledge the data set authors if using this data.</p>
Weight-loss & metabolite data of cachetic cancer patients over multiple time points
<p>This dataset contains weight-loss data and metabolite measurements from cachetic cancer patients. This data set is part of the publication "Biomarkers related to fatty acid oxidative capacity are predictive for continued weight loss in cachectic cancer patients" by Catanese et al., 2021 (<a href="https://doi.org/10.1002/jcsm.12817">LINK</a>). Data were collected over a extended time period starting from the day of hospital admission. Up to seven time points are available for individual patients. A metabolite profile consisting of amino acids and acylcarnitines measured via tandem MS/MS from both blood plasma and dried blood spots is available for each patient at each time point. Additional available phenotypes are the age, sex and historic weight of each patient. </p> <p>Abbreviations:</p> <ul> <li>HW - Historical weight</li> <li>TP - Time point</li> <li>WL - Weight loss</li> <li>DBS - Dried blood spot</li> <li>Metabolite abbreviations are explained in Supplementary Table S5 of the corresponding publication</li> </ul>
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.