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932 results for “CAP”
Cap de Silè, Museu de Lleida
CAT. Cap de vell sàtir identificat amb Silè i relacionat amb el seguici de Dionís. Es presenta barbat, amb cabells rinxolats i duu una garlanda vegetal al cap. És un objecte de marbre blanc, datat al s. ii i procedent de Tarragona. Es custòdia al Museu de Lleida. ESP. Cabeza de viejo sátiro identificado con Sileno y relacionado con el cortejo de Dioniso. Se presenta barbado, con pelo rizado y lleva una guirnalda vegetal en la cabeza. Es un objeto de mármol blanco, fechado en el s. ii y procedente de Tarragona. Se custodia en el Museo de Lleida. EN. Head of an elderly satyr believed to be Silenus, a member of Dionysus' retinue. He is shown as bearded, with curly hair and wearing a garland on his head. Made of white marble, the piece is dated to the 2nd century and originated in Tarragona. It is kept at the Lleida Museum. http://museudelleida.cat/collection/roma/ Model: Aleix Barberà. Textos: MDL Source: Objaverse 1.0 / Sketchfab
MH 1993.10.6 South Indian Carved Axle Cap
Culture: South Indian Title: carved wood axle cap (one of a pair) Materials: Carved wood Accession Number: MH 1993.10.6 Credit Line: Gift of Susan and Bernard N. Schilling (Susan Eisenhart, Class of 1932) View this object on the Collections Database: http://museums.fivecolleges.edu/detail.php?museum=all&t=objects&type=all&f=&s=mh+1993+10+3&record=18 Photographs and photogrammetry by Laura Shea (Digital Collections Coordinator and Museum Photographer), Mount Holyoke College Art Museum; Copyright info: Contact the Mount Holyoke College Art Museum South Hadley, Massachusetts, USA 01075 413-538-2245 http://www.mtholyoke.edu/artmuseum/ The Mount Holyoke College Art Museum is dedicated to teaching and learning; therefore, we value your feedback and welcome any scholarly observations. Please feel free to contact us if you would like to learn more about the objects you see here or to request 3D models of other objects in our collections. Source: Objaverse 1.0 / Sketchfab
Cap de la Gegantessa, Museu de la Garrotxa
**CAT** Escultura realitzada entre el 1888 i 1889 a partir d'un model de l'escultor Celestí Devesa. L'escultura es va fer al taller de l'empresa l'Art Cristià sota la direcció de l'artista Josep Berga i Boix. La peça es pot veure al Museu dels Sants d'Olot. **ES** Escultura realizada entre 1888 y 1889 a partir de un modelo del escultor Celestí Devesa. La escultura se hizo en el taller de la empresa el Arte Cristiano bajo la dirección del artista Josep Berga y Boix. La pieza se puede ver en el Museu dels Sants d'Olot. **EN** Sculpture completed between 1888 and 1889, based on a maquette by sculptor Celestí Devesa. The sculpture was completed in the workshop of the Arte Cristiano company under the direction of artist Josep Berga i Boix. The piece can be seen at the Museu dels Sants in Olot. Número de registre: MCGO 1132. [Adreça web >](https://museus.olot.cat/coleccio/cap-de-la-gegantessa-d-olot) Fotografies: Aleix Barberà. Processat: Néstor Marqués. Text: Àlex Rebollo. Source: Objaverse 1.0 / Sketchfab
Surface Height Displacements and Time-Variable Gravity From Changes in the Seasonal Polar Cap on Mars
<p>This repository is the location at which the data created for Wagner et al. 2024 is located. Info about specific files is included in the README.</p>
Evolution of plasma properties in 2D particle-in-cell simulations of pulsar polar caps as function of dipole inclination angle
<p>The video shows the evolution of plasma properties in polar cap region of neutron stars from initial simulation conditions to the quasi-periodic pair creation. Three inclination angles of magnetic dipole axis to the star rotation axis are investigate \iota = 0°, 45°, and 90°.</p> <p>The presented quantities are (in rows): Parallel current density, parallel electric field, parallel and perpendicular Poynting flux, electron and positron plasma density, and electron and positron plasma bulk momenta.</p> <p> </p>
Underwater images collected by an Autonomous Surface Vehicle in Cap-Homard, Réunion - 2023-11-28
<i>This dataset was collected by an Autonomous Surface Vehicle in Cap-Homard, Réunion - 2023-11-28.</i> <br> <br><br>Underwater or aerial images collected by scientists or citizens can have a wide variety of use for science, management, or conservation. These images can be annotated and shared to train IA models which can in turn predict the objects on the images. We provide a set of tools (hardware and software) to collect marine data, predict species or habitat, and provide maps.<br><br> This dataset is part of larger collection referencing numerous underwater and aerial images <a href="https://doi.org/10.5281/zenodo.11125847" target="_blank">Seatizen Altas</a>. Methods, tools and scientific objectives are also described in a dedicated data paper.<br> <h2>Image acquisition</h2> This session has 32.76 GB of MP4 files, which were trimmed into 12042 frames (at 2997/1000 fps). <br> The frames are georeferenced. <br> 2.63% of these extracted images are useful and 97.37% are useless, according to predictions made by <a href="jacques-v0.1.0_model-20240513_v20.0" target="_blank">Jacques model</a>. <br> Multilabel predictions have been made on useful frames using <a href="https://huggingface.co/lombardata/DinoVdeau-large-2024_04_03-with_data_aug_batch-size32_epochs150_freeze" target="_blank">DinoVd'eau</a> model. <br> <h2> GPS information: </h2> The data was processed with a PPK workflow to achieve centimeter-level GPS accuracy. <br> Base : Files coming from rtk a GPS-fixed station or any static positioning instrument which can provide with correction frames. <br> Device GPS : Emlid Reach M2 <br> Quality of our data - Q1: 93.32 %, Q2: 4.33 %, Q5: 2.35 % <br> <h2> Bathymetry </h2> The data are collected using a single-beam echosounder <a href="https://ceruleansonar.com/products/sounder-s500" target="_blank">S500</a>. <br> We only keep the values which have a GPS correction in Q1.<br> We keep the points that are the waypoints.<br> We keep the raw data where depth was estimated between 0.2 m and 50.0 m deep. <br> The data are first referenced against the WGS84 ellipsoid. Then we apply the local geoid if available.<br> At the end of processing, the data are projected into a homogeneous grid to create a raster and a shapefiles. <br> The size of the grid cells is 0.699 m. <br> The raster and shapefiles are generated by linear interpolation. The 3D reconstruction algorithm is ballpivot. <br> <h2> Generic folder structure </h2> YYYYMMDD_COUNTRYCODE-optionalplace_device_session-number <br> ├── DCIM : folder to store videos and photos depending on the media collected. <br> ├── GPS : folder to store any positioning related file. If any kind of correction is possible on files (e.g. Post-Processed Kinematic thanks to rinex data) then the distinction between device data and base data is made. If, on the other hand, only device position data are present and the files cannot be corrected by post-processing techniques (e.g. gpx files), then the distinction between base and device is not made and the files are placed directly at the root of the GPS folder. <br> │ ├── BASE : files coming from rtk station or any static positioning instrument. <br> │ └── DEVICE : files coming from the device. <br> ├── METADATA : folder with general information files about the session. <br> ├── PROCESSED_DATA : contain all the folders needed to store the results of the data processing of the current session. <br> │ ├── BATHY : output folder for bathymetry raw data extracted from mission logs. <br> │ ├── FRAMES : output folder for georeferenced frames extracted from DCIM videos. <br> │ ├── IA : destination folder for image recognition predictions. <br> │ └── PHOTOGRAMMETRY : destination folder for reconstructed models in photogrammetry. <br> └── SENSORS : folder to store files coming from other sources (bathymetry data from the echosounder, log file from the autopilot, mission plan etc.). <br> <h2> Software </h2> All the raw data was processed using our <a href="https://github.com/SeatizenDOI/plancha-workflow/releases/tag/v1.0.3" target="_blank">worflow</a>. <br>All predictions were generated by our <a href="https://github.com/SeatizenDOI/plancha-inference/releases/tag/v1.0.0" target="_blank">inference pipeline</a>. <br>You can find all the necessary scripts to download this data in this <a href="https://github.com/SeatizenDOI/zenodo-tools" target="_blank">repository</a>. <br>Enjoy your data with <a href="https://github.com/SeatizenDOI" target="_blank">SeatizenDOI</a>! <br>
Supplementary Figures Chapter 5 - Peat capping: Natural capping of wet landfills by peat formation
<p>Supplementary Figures to Chapter 5 "Peat capping: Natural capping of wet landfills by peat formation" of PhD thesis from Ciska Overbeek, "Peat formation on a former landfill - Production and decomposition of aquatic pioneer vegetation". </p> <p>Published by Harpenslager et al in 2018 in Ecological Engineering 114: 146-153. <a href="https://doi.org/10.1016/j.ecoleng.2017.04.040">https://doi.org/10.1016/j.ecoleng.2017.04.040</a>. </p>
The north polar cap of Mars
<p>Thickness of the north polar cap as seen by MARSIS and SHARAD at 213 locations. Thickness of the polar cap as predicted by MOLA assuming that the basement follows the long-wavelength regional slope.</p>
Dataset for "The 21st-century fate of the Mocho-Choshuenco ice cap in southern Chile"
<p>Dataset for the paper "The 21st-century fate of the Mocho-Choshuenco ice cap in southern Chile", <a href="https://doi.org/10.5194/tc-15-3637-2021">published in The Cryosphere</a>. For more information, please refer to the readme file, the metadata of the nc-files, and the paper.</p>
Supplemental High Resolution IPWM Run for "Ion heating in the polar cap under northwards IMF Bz": SDOP_April2016
<p>Full high resolution output from the Ionosphere/Polar Wind Model (IPWM) for results published in "Ion heating in the polar cap under northwards IMF Bz", by L. J. Lamarche, R. H. Varney, and A. S. Reimer. This is a simulation of the April 2016 event, with IPWM driven by SuperDARN convection maps and Ovation Prime precipitation (SDOP_April2016). Scripts to visualize these model output and produce the figures in the article are available in a separate repository <a href="http://doi.org/10.5281/zenodo.4453390">10.5281/zenodo.4453390</a>.</p> <p>If you are configuring the Resen bucket available in <a href="http://doi.org/10.5281/zenodo.4453390">10.5281/zenodo.4453390</a>, mount this repository to /home/jovyan/mount/SDOP_April2016_output.</p>
Supplemental High Resolution IPWM Run for "Ion heating in the polar cap under northwards IMF Bz": SDOP_May2014
<p>Full high resolution output from the Ionosphere/Polar Wind Model (IPWM) for results published in "Ion heating in the polar cap under northwards IMF Bz", by L. J. Lamarche, R. H. Varney, and A. S. Reimer. This is a simulation of the May 2014 event, with IPWM driven by SuperDARN convection maps and Ovation Prime precipitation (SDOP_May2014). Scripts to visualize these model output and produce the figures in the article are available in a separate repository <a href="http://doi.org/10.5281/zenodo.4453390">10.5281/zenodo.4453390</a>.</p> <p>If you are configuring the Resen bucket available in <a href="http://doi.org/10.5281/zenodo.4453390">10.5281/zenodo.4453390</a>, mount this repository to /home/jovyan/mount/SDOP_May2014_output.</p>
FIG. 3 in L'expédition scientifique de João da Silva Feijó aux îles du Cap Vert (1783-1796) et les tribulations de son herbier The scientific expedition of João da Silva Feijó to the Cabo Verde Islands (1783-1796) and the tribulations of his herbarium
FIG. 3. — Map of the Cabo Verde archipelago/Carte de l'archipel du Cap Vert.
Underwater images collected by an Autonomous Surface Vehicle in Cap-Homard, Réunion - 2023-11-28
<i>This dataset was collected by an Autonomous Surface Vehicle in Cap-Homard, Réunion - 2023-11-28.</i> <br> <br><br>Underwater or aerial images collected by scientists or citizens can have a wide variety of use for science, management, or conservation. These images can be annotated and shared to train IA models which can in turn predict the objects on the images. We provide a set of tools (hardware and software) to collect marine data, predict species or habitat, and provide maps.<br><br> This dataset is part of larger collection referencing numerous underwater and aerial images <a href="https://doi.org/10.5281/zenodo.11125847" target="_blank">Seatizen Altas</a>. Methods, tools and scientific objectives are also described in a dedicated data paper.<br> <h2>Image acquisition</h2> This session has 36.25 GB of MP4 files, which were trimmed into 8316 frames (at 2997/1000 fps). <br> The frames are georeferenced. <br> 99.77% of these extracted images are useful and 0.23% are useless, according to predictions made by <a href="jacques-v0.1.0_model-20240513_v20.0" target="_blank">Jacques model</a>. <br> Multilabel predictions have been made on useful frames using <a href="https://huggingface.co/lombardata/DinoVdeau-large-2024_04_03-with_data_aug_batch-size32_epochs150_freeze" target="_blank">DinoVd'eau</a> model. <br> <h2> GPS information: </h2> The data was processed with a PPK workflow to achieve centimeter-level GPS accuracy. <br> Base : Files coming from rtk a GPS-fixed station or any static positioning instrument which can provide with correction frames. <br> Device GPS : Emlid Reach M2 <br> Quality of our data - Q1: 18.63 %, Q2: 80.96 %, Q5: 0.41 % <br> <h2> Bathymetry </h2> The data are collected using a single-beam echosounder <a href="https://www.echologger.com/products/single-frequency-echosounder-deep" target="_blank">ETC 400</a>. <br> We only keep the values which have a GPS correction in Q1.<br> We keep the points that are the waypoints.<br> We keep the raw data where depth was estimated between 0.2 m and 50.0 m deep. <br> The data are first referenced against the WGS84 ellipsoid. Then we apply the local geoid if available.<br> At the end of processing, the data are projected into a homogeneous grid to create a raster and a shapefiles. <br> The size of the grid cells is 0.408 m. <br> The raster and shapefiles are generated by linear interpolation. The 3D reconstruction algorithm is ballpivot. <br> <h2>Photogrammetry</h2> OpenDroneMap software was used to create an orthophoto from the raw images. <br> Here is the list of parameters different from the default values for the orthophoto generation. <br> For more details, you can read the log.json file or the 000_photogrammatry_report.pdf report. <br><br> <code> {'auto_boundary': True, 'cog': True, 'fast_orthophoto': True, 'feature_quality': 'ultra', 'gps_accuracy': 0.1, 'max_concurrency': 44, 'optimize_disk_space': True, 'orthophoto_resolution': 0.1, 'rolling_shutter': True, 'skip_3dmodel': True} </code> <h2> Generic folder structure </h2> YYYYMMDD_COUNTRYCODE-optionalplace_device_session-number <br> ├── DCIM : folder to store videos and photos depending on the media collected. <br> ├── GPS : folder to store any positioning related file. If any kind of correction is possible on files (e.g. Post-Processed Kinematic thanks to rinex data) then the distinction between device data and base data is made. If, on the other hand, only device position data are present and the files cannot be corrected by post-processing techniques (e.g. gpx files), then the distinction between base and device is not made and the files are placed directly at the root of the GPS folder. <br> │ ├── BASE : files coming from rtk station or any static positioning instrument. <br> │ └── DEVICE : files coming from the device. <br> ├── METADATA : folder with general information files about the session. <br> ├── PROCESSED_DATA : contain all the folders needed to store the results of the data processing of the current session. <br> │ ├── BATHY : output folder for bathymetry raw data extracted from mission logs. <br> │ ├── FRAMES : output folder for georeferenced frames extracted from DCIM videos. <br> │ ├── IA : destination folder for image recognition predictions. <br> │ └── PHOTOGRAMMETRY : destination folder for reconstructed models in photogrammetry. <br> └── SENSORS : folder to store files coming from other sources (bathymetry data from the echosounder, log file from the autopilot, mission plan etc.). <br> <h2> Software </h2> All the raw data was processed using our <a href="https://github.com/SeatizenDOI/plancha-workflow/releases/tag/v1.0.3" target="_blank">worflow</a>. <br>All predictions were generated by our <a href="https://github.com/SeatizenDOI/plancha-inference/releases/tag/v1.0.0" target="_blank">inference pipeline</a>. <br>You can find all the necessary scripts to download this data in this <a href="https://github.com/SeatizenDOI/zenodo-tools" target="_blank">repository</a>. <br>Enjoy your data with <a href="https://github.com/SeatizenDOI" target="_blank">SeatizenDOI</a>! <br>
Disturbance-mediated hybridization in black-capped and mountain chickadees
<p>Human habitat disturbances can promote hybridization between closely related, but typically reproductively isolated, species. We explored whether human habitat disturbances are related to hybridization between two closely related songbirds, black-capped, and mountain chickadees, using both genomic and citizen science datasets. First, we genotyped 409 individuals from across both species' ranges using reduced-representation genome sequencing and compared measures of genetic admixture to a composite measure of human landscape disturbance. Then, using eBird observations, we compared human landscape disturbance values for sites where phenotypically diagnosed hybrids were observed to locations where either parental species was observed to determine whether hybrid chickadees are reported in more disturbed areas. We found that hybridization between black-capped and mountain chickadees positively correlates with human habitat disturbances. From genomic data, we found that 1) hybrid index significantly increased with habitat disturbance, 2) more hybrids were sampled in disturbed habitats, 3) mean hybrid indexes were higher in disturbed habitats versus wild habitats, and 4) hybrids were detected in habitats with significantly higher disturbance values than parentals. Using eBird data, we found that both hybrid and black-capped chickadees were significantly more disturbance-associated than mountain chickadees. Surprisingly, we found that nearly every black-capped chickadee we sampled contained some proportion of hybrid ancestry, while we detected very few mountain chickadee backcrosses. Our results highlight that hybridization between black-capped and mountain chickadees is widespread, but initial hybridization is rare (few F1s were detected). We conclude that human habitat disturbances can erode pre-zygotic reproductive barriers between chickadees and that post-zygotic isolation is incomplete. Understanding what becomes of recently hybridizing species following large-scale habitat disturbances is a new, but pressing, consideration for successfully preserving genetic biodiversity in a rapidly changing world.</p>
Inhibition of cellular RNA methyltransferase abrogates influenza virus capping and replication
<p>Raw data of the paper titled "Inhibition of cellular RNA methyltransferase abrogates influenza virus capping and replication".</p>
Multi-technique surface geophysical surveys over Devon Ice Cap, Canadian Arctic
<p>This dataset was acquired during a multi-technique surface geophysical campaign in May 2022 over Devon Ice Cap, Canadian Arctic.</p> <p><strong>Description of data:</strong></p> <p><strong>Seismic</strong><br> 9 km of active source seismic reflection data<br> raw segy files for line A and line B<br> seismic observation log<br> matlab script for plotting a raw stack of line A and line B<br> coordinates of each seismic spread, with the ice surface elevation and estimated bed elevation</p> <p><strong>Transient electromagnetic (TEM) </strong><br> 7 large loop TEM soundings <br> with 500 x 500 m loop with receiver 250 m outside the loop (away from the transmitter)<br> USF files for each sounding<br> coordinates for each TEM sounding<br> TEM observation log </p> <p><strong>Magnetotelluric (MT)</strong><br> 17 MT stations<br> raw, unprocessed EDI files <br> coordinates for each MT station <br> MT observation log</p> <p>Time series data (~80GB) can be found at:<br> https://drive.google.com/drive/folders/1OyCIP_B3VUJ4-ULSp8YOAPuNEMHuNcN-?usp=share_link</p> <p><strong>Acknowledgments</strong></p> <p>We thanks the Polar Continental Shelf Program for logistical support throughout the field season; Rob Harris at Geonics for his support and help with the TEM method; Zoe Vestrum at the University of Alberta for her MT support during deployment to the field; </p> <p><strong>Funding</strong></p> <p>This work was funded by the Weston Family Foundation. The aircraft hours were funded by the Polar Continental Survey Program (PCSP) and ArcticNet. MT survey was supported by a NSERC Discovery Grant to Martyn Unsworth and the Future Energy Systems program at the University of Alberta. </p> <p><strong>Corresponding Author</strong></p> <p>Siobhan Killingbeck skillin1@ualberta.ca</p>
Dataset for the article "Polarizable Embedding Potentials through Molecular Fractionation with Conjugate Caps including Hydrogen Bonds"
<p>This dataset contains additional material related to the article: "Polarizable Embedding Potentials through Molecular Fractionation with Conjugate Caps including Hydrogen Bonds". The published article can be found at <a href="https://doi.org/10.1021/acs.jctc.3c00613">https://doi.org/10.1021/acs.jctc.3c00613</a>. A preprint is freely available at <a href="https://doi.org/10.26434/chemrxiv-2023-vb01m-v2">https://doi.org/10.26434/chemrxiv-2023-vb01m-v2</a>. Each folder contains a <em>Readme.md</em> for further description.</p>
Carboxymethyl starch as a reducing and capping agent in the hydrothermal synthesis of selenium nanostructures for use with 3D-printed hydrogel carrier
<p>The hydrothermal method is a cost-effective and eco-friendly route for preparing various nanomaterials. It can utilize a capping agent, such as a polysaccharide, to govern and define the nanoparticle morphology. Elemental selenium nanostructures (spheres and rods) were synthesized and stabilized using a tailor-made carboxymethyl starch (CMS, degree of substitution = 0.3) under hydrothermal conditions. CMS is particularly convenient because it acts simultaneously as the capping and reducing agent, as verified by several analytical techniques, while the reaction relies entirely on green solvents. Furthermore, the effect of sodium selenite concentration, reaction time, and temperature on the nanoparticle size, morphology, microstructure, and chemical composition was investigated to identify the ideal synthesis conditions. A pilot experiment demonstrated the feasibility of implementing the synthesized nanoparticles into vat photopolymerization 3D-printed hydrogel carriers based on 2-hydroxyethyl methacrylate (HEMA). When submersed into the water, the subsequent particle release was confirmed by dynamic light scattering (DLS), promising great potential for use in bio-3D printing and other biomedical applications.</p>
Dataset for Role of Astrophorina sponges (Demospongiae) in food-web interactions at the Flemish Cap (NW Atlantic)
<p>The data include the functions used to develop the trophic/ non-trophic interaction web models, the input files for these models and the Rmarkdown files with the model output.</p>
Confederate Naval Cap (Toon)
Confederate Naval Caps were made of steel gray cloth. They were not to be less than three inches and a half, nor more than four inches in height. They were also not to be more than ten, or less than nine inches and a half, at the top, and had a patent leather visor, to be worn by all officers in their service dress. *1 model (low poly) with textures and materials. Source: Objaverse 1.0 / Sketchfab
ScienceDex guides
Understand access before you commit
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.