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54 results for “SCUBA”
SCUBA belt transects for abundance data H. cochlea and H. aequicostatus
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SCUBA-D source data
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Iliac Artery Treatment With The Invatec Scuba™ Cobalt Chromium Stent (INTENSE)
ClinicalTrials.gov study NCT00880230. IPD Sharing: Not stated. Countries: 2. Publications: 0.
Does an Occupational Therapy Program Enhance Mental Health Outcomes for Veterans Who Scuba Dive
ClinicalTrials.gov study NCT03928392. IPD Sharing: NO. Countries: 1. Publications: 0.
Underwater images collected by Scuba diving in Hermitage, Réunion - 2021-03-10
<i>This dataset was collected by Scuba diving in Hermitage, Réunion - 2021-03-10.</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> <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>
Underwater images collected by Scuba diving in Hermitage, Réunion - 2021-02-18
<i>This dataset was collected by Scuba diving in Hermitage, Réunion - 2021-02-18.</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> <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>
Underwater images collected by Scuba diving in Hermitage, Réunion - 2021-03-10
<i>This dataset was collected by Scuba diving in Hermitage, Réunion - 2021-03-10.</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> <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>
Practice of Scuba Diving by as Many People as Possible: Effect of Medical Assessment to Provide a Suitable and Individualised Framework for Practice (Plongée Santé)
ClinicalTrials.gov study NCT06555666. IPD Sharing: YES. Countries: 1. Publications: 0.
Rhu-pGSN to Mitigate Proinflammatory Responses to Decompression in Healthy SCUBA Divers
ClinicalTrials.gov study NCT06216366. IPD Sharing: NO. Countries: 1. Publications: 0.
Clinical Study About the Effects of Scuba Diving on Post Traumatic Stress Disorder (PTSD)
ClinicalTrials.gov study NCT04343924. IPD Sharing: NO. Countries: 1. Publications: 0.
Is Blood Flow Through IPAVA and PFO Related to Breath-hold and SCUBA Diving-induced Pulmonary Hypertension?
ClinicalTrials.gov study NCT03945643. IPD Sharing: NO. Countries: 1. Publications: 0.
Patent Foramen Ovale Closure Reduce in SCUBA-divers
ClinicalTrials.gov study NCT03997084. IPD Sharing: NO. Countries: 0. Publications: 0.
Low Level Laser Therapy for Treatment of Tinnitus in Red Sea Scuba Divers
ClinicalTrials.gov study NCT04962750. IPD Sharing: NO. Countries: 0. Publications: 0.
SCUBA Legacy Fundamental and Extended Map Object Catalogs
This table contains the SCUBA Legacy Catalogs, two comprehensive sets of source catalogs using data at 850 and 450um of the various astronomical objects obtained with the Submillimetre Common User Bolometer Array (SCUBA) on the James Clerk Maxwell Telescope (JCMT). The Fundamental Map Data Set contains data only where superior atmospheric opacity calibration data were available. The Extended Map Data Set contains data regardless of the quality of the opacity calibration. Each data set contains 1.2 degrees x 1.2 degrees maps at locations where data existed in the JCMT archive, imaged using the matrix inversion method. The Fundamental Data Set is composed of 1423 maps at 850um and 1357 maps at 450um. The Extended Data Set is composed of 1547 maps at 850um. Neither data set includes high sensitivity, single-chop SCUBA maps of "cosmological fields" nor solar system objects. Each data set was used to determine a respective object catalog, consisting of objects identified within the respective 850um maps using an automated identification algorithm. The Fundamental and Extended Map Object Catalogs contain 5061 and 6118 objects, respectively. Objects are named based on their respective J2000.0 position of peak 850um intensity. The catalogs provide for each object the respective maximum 850um intensity, estimates of total 850um flux and size, and tentative identifications from the SIMBAD Database. Where possible, the catalogs also provide for each object its maximum 450um intensity and total 450um flux and flux ratios. Since the goal of this project was to make maps and then catalog objects therein, all raw jiggle and scan data from SCUBA available in the JCMT archive were downloaded from the CADC in 2006 May. (Photometry and polarimetry data were ignored.) A full description of the instrumental characteristics of SCUBA was made by Holland et al. (1999MNRAS.303..659H). All maps are available at <a href="http://www3.cadc-ccda.hia-iha.nrc-cnrc.gc.ca/community/scubalegacy/">http://www3.cadc-ccda.hia-iha.nrc-cnrc.gc.ca/community/scubalegacy/</a> This table was created by the HEASARC in December 2010 based on <a href="https://cdsarc.cds.unistra.fr/ftp/cats/J/ApJS/175/277">CDS catalog J/ApJS/175/277</a> files table2.dat and table3.dat. This is a service provided by NASA HEASARC .
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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
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.