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346 results for “ships”
Charlton Ship Timber 10
A ship's timber on the Thames foreshore at Charlton (near the Anchor & Hope Pub), London. http://www.thamesdiscovery.org/riverpedia/charlton-riverpedia Photos taken in April 2021 with a Sony a6000 and processed in Agisoft Metashape. Source: Objaverse 1.0 / Sketchfab
Charlton Ship Timber 3
A ship's timber on the Thames foreshore at Charlton (near the Anchor & Hope Pub), London. http://www.thamesdiscovery.org/riverpedia/charlton-riverpedia 91 photos taken in April 2021 with a Sony a6000 and processed in Reality Capture. Source: Objaverse 1.0 / Sketchfab
Small Old Ship Cannon
Small cannon made of steel with little gold on it curvature. - Made in Blender 3D - LowPoly - 30-min modeling process Source: Objaverse 1.0 / Sketchfab
Viking ship - Snekkar
Although less prestigious than the Dreki (from which derives "Drakkar"), Snekkars formed the bulk of the Scandinavian "Langskips". The Snekkar ("Snake Ship") is a very ancient Scandinavian term for distinguishing certain warships among Langskips. The name "snake" which by analogy to the Drakkar of the Western archaeologists will give the famous "Snekkar", was a reference not peculiar to the figurehead but to the length of the ship or rather to its length/width ratio of 7/1 which Is the lowest of all Scandinavian vessels. Some wrecks discovered had an inferior ratio of 11/1. Such a ship was unstable and designed for pure speed. Therefore Snekkars were very fast warships. Source: Objaverse 1.0 / Sketchfab
Wooden Ship's Pulley
📍 [San Francisco, CA](https://scaniver.se/L37.79766,-122.39377) Made with [Scaniverse](https://scaniverse.com) on an iPhone 13 Pro. I'm posting one 3D scan each day in June. [See the entire collection](https://skfb.ly/ouVY8). Source: Objaverse 1.0 / Sketchfab
3D Digital Archive_HAI-KUNG Research Ship
1976年12月2日,海功號自基隆出發,途經印度洋、南非開普敦後,遠航南極恩得比海域探勘南極蝦漁場,歷時114天,滿載而歸,其「南極探險」為台灣的歷史寫下了重要的一頁。 Source: Objaverse 1.0 / Sketchfab
Self-collection for HPV Testing to Improve Cervical Cancer Prevention (SHIP) Trial (LMI-001-A-S01)
ClinicalTrials.gov study NCT06498661. IPD Sharing: YES. Countries: 2. Publications: 0.
Self-collection for HPV Testing to Improve Cervical Cancer Prevention (SHIP) Trial (LMI-001-A-S03)
ClinicalTrials.gov study NCT06611540. IPD Sharing: YES. Countries: 1. Publications: 0.
Health Impact of L.Reuteri Consumption in Crew Members of a Naval Ship at Sea
ClinicalTrials.gov study NCT02775019. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
Self-collection for HPV Testing to Improve Cervical Cancer Prevention (SHIP) Trial (LMI-001-A-S04)
ClinicalTrials.gov study NCT07281430. IPD Sharing: YES. Countries: 1. Publications: 0.
Application of Ship - Shaped Adhesive Tape Fixing in Patients Undergoing Tracheal Intubation
ClinicalTrials.gov study NCT04707521. IPD Sharing: Not stated. Countries: 1. Publications: 0.
PREhospital Routage of Acute STroke Patients With Suspected Large Vessel Occlusion: Mothership Versus Drip and Ship
ClinicalTrials.gov study NCT04121013. IPD Sharing: NO. Countries: 1. Publications: 0.
Self-collection for HPV Testing to Improve Cervical Cancer Prevention (SHIP) Trial (LMI-001-A-S02)
ClinicalTrials.gov study NCT06611553. IPD Sharing: YES. Countries: 2. Publications: 0.
Arctic Ocean Drift Tracks from Ships, Buoys, and Manned Research Stations, 1872-1973, Version 1
Thirty-four drift tracks in the Arctic Ocean pack ice are collected in a unified tabular data format, one file per track. Data are from drifting ships, manned research stations on ice floes (ice islands) and data buoys. Track names are FRAM (ship, 1893 to 1896), NP-01 through NP-20 (Soviet North Pole stations on ice floes, 1937, 1950, 1954 to 1970), IGY-A and IGY-B (International Geophysical Year ice camps, 1957 to 59), T-3 (Fletcher's Ice Island, 1959 to 1970), ARLIS-II (Arctic Research Laboratory Ice Station II ice camp, 1961 to 1965), BTAE (British Transarctic Expedition, 1968 to 1969), seven buoys deployed during the AIDJEX (Arctic Ice Dynamics Joint Experiment) pilot study (1972), TEGG (Austrian ship Tegetthoff, 1872 to 1873) and St. Anna (Russian ship, 1912 to 1914).
KORUS-AQ Research Vessel (R/V) Onnuri Ship Data
KORUSAQ_RVOnnuriShip_Data features data collected onboard the Research Vessel Onnuri during the KORUS-AQ field campaign. This product features trace gas data and absorption coefficient spectra. Data collection for this product is complete.The KORUS-AQ field study was conducted in South Korea during May-June, 2016. The study was jointly sponsored by NASA and Korea’s National Institute of Environmental Research (NIER). The primary objectives were to investigate the factors controlling air quality in Korea (e.g., local emissions, chemical processes, and transboundary transport) and to assess future air quality observing strategies incorporating geostationary satellite observations. To achieve these science objectives, KORUS-AQ adopted a highly coordinated sampling strategy involved surface and airborne measurements including both in-situ and remote sensing instruments.Surface observations provided details on ground-level air quality conditions while airborne sampling provided an assessment of conditions aloft relevant to satellite observations and necessary to understand the role of emissions, chemistry, and dynamics in determining air quality outcomes. The sampling region covers the South Korean peninsula and surrounding waters with a primary focus on the Seoul Metropolitan Area. Airborne sampling was primarily conducted from near surface to about 8 km with extensive profiling to characterize the vertical distribution of pollutants and their precursors. The airborne observational data were collected from three aircraft platforms: the NASA DC-8, NASA B-200, and Hanseo King Air. Surface measurements were conducted from 16 ground sites and 2 ships: R/V Onnuri and R/V Jang Mok.The major data products collected from both the ground and air include in-situ measurements of trace gases (e.g., ozone, reactive nitrogen species, carbon monoxide and dioxide, methane, non-methane and oxygenated hydrocarbon species), aerosols (e.g., microphysical and optical properties and chemical composition), active remote sensing of ozone and aerosols, and passive remote sensing of NO2, CH2O, and O3 column densities. These data products support research focused on examining the impact of photochemistry and transport on ozone and aerosols, evaluating emissions inventories, and assessing the potential use of satellite observations in air quality studies.
Legates Surface and Ship Observations of Precipitation Climatology 0.5 x 0.5 degree V1 (RAIN_LEGATES) at GES DISC
The Legates Surface and Shipboard Rain Gauge Observations data set consists of a global climatology of monthly mean precipitation values. A global climatology of mean monthly precipitation was developed using traditional land-based gauge measurements as well as extrapolations of oceanic precipitation from coastal and island observations. Data were obtained from a variety of source archives. These data were screened for coding errors, merged, and redundant stations were removed. The resulting data base contains 24,635 independent terrestrial station records and 2223 oceanic gridpoint estimates. Precipitation gauge catches, however, are known to underestimate actual precipitation. Errors in the gauge catch result from wind-field deformation above the orifice of the gauge, wetting losses, and evaporation from the gauge and amount globally to nearly 8, 2, and 1 percent of the catch, respectively. A procedure was developed to estimate these errors and was used to obtain better estimates of global precipitation. Spatial variations in gauge type, air temperature, wind speed, and natural vegetation have been interpolated to the nodes of a 0.5 degrees of latitude by 0.5 degrees of longitude lattice using a spherically-based interpolation algorithm. The data set is used to validate general circulation model simulations of the present-day precipitation climate, for ground-based comparison with satellite-derived precipitation estimates, and as a basis for global water balance studies.
PISTON 2018 Research Vessel (RV) Mirai Ship Data
PISTON-ONR-NOAA_RVMirai_2018 is the Propagation of Intra-Seasonal Tropical Oscillations (PISTON) 2018 Research Vessel (RV) Mirai data product. This product is the result of a joint effort that involved NASA as well as the Office of Naval Research (ONR), and National Oceanic and Atmospheric Administration (NOAA). Data was collected collection for this product using multiple instruments on the RV Thompson platform including C-band radar and rawinsondes. Data collection is complete.The PISTON field campaign, sponsored by the Office of Naval Research (ONR) and the National Oceanic and Atmospheric Administration (NOAA), was designed to gain understanding and enhance the prediction capability of multi-scale tropical atmospheric convection and air-sea interaction in this region. PISTON targeted the Boreal Summer Intraseasonal Oscillation (BSISO), which defines the northward and eastward movement of convection associated with equatorial waves, the MJO, tropical cyclones, and the Maritime Continent monsoon during northern-hemispheric (boreal) summertime. PISTON completed three total shipboard cruises, deployed eight drifting ocean profiling floats and two full-depth ocean moorings, collaborated with a Japanese research vessel collecting similar data, and also made use of soundings from nearby islands. These activities took place in the Philippine Sea, which is in the tropical northwestern Pacific Ocean north of Palau, between August 2018 - September 2019, with each dataset spanning a slightly different amount of time. There were two US research vessels involved in PISTON: R/V Thomas G. Thompson in Aug-Sept and Sept-Oct 2018 and R/V Sally Ride in Sept 2019. The first 2018 cruise coincided collaborative activities with R/V Mirai (this doi). The 2019 cruise coincided with the NASA CAMP2Ex airborne field experiment (Clouds, Aerosol and Monsoon Processes-Philippines Experiment, please see more info below). The two specialized moorings were deployed north of Palau and collected data from August 2018 - Oct 2019 to document a time series of ocean characteristics beneath typhoons and other tropical weather disturbances. Toward the same goal, eight profiling ocean floats were also deployed ahead of typhoons in 2018. For characterization of clouds and precipitation, the PISTON shipboard instrument payload included a scanning C-band dual-polarization Doppler radar (SEA-POL), a vertically-pointing Doppler W-band radar, and multiple vertically- and horizontally-scanning lidars. Rawinsondes were launched from the ships for atmospheric profiling. Additional radiosonde and precipitation radar data were collected from R/V Mirai via an international collaboration. Regular soundings were also archived from islands neighboring the Philippines and the Philippine Sea: Dongsha Island, Taiping Island, Yap, Palau, and Guam. Additional atmospheric sampling from the PISTON R/V Thompson 2018 and Sally Ride 2019 cruises included an electric field meter and disdrometer in 2018, and all-sky camera images in 2019. To document near-surface meteorological conditions, air-sea fluxes, and upper-ocean variability including ocean vertical profiles on these cruises, instruments were deployed on and towed from the ship. Additional profiles of ocean acoustics and oceanic chemistry were not archived but are available upon request by James N. Moum, Oregon State University, jim.moum@oregonstate.edu. A forecast team analyzed and predicted conditions of the weather and ocean throughout the PISTON experiment, which were not archived but are available upon request for future modeling and observational analysis studies (contacts: Sue Chen, US Naval Research Lab Monterey, sue.chen@nrlmry.navy.mil and Michael M. Bell, Colorado State University, mmbell@colostate.edu). There are five total DOIs related to PISTON, separated by ship (and therefore year) as well as other platforms/locations that span multiple years:https://doi.org/10.5067/SUBORBITAL/PISTON2018-ONR-NOAA/RVTHOMPSON/DATA001 https://doi.org/10.5067/SUBORBITAL/PISTON2019-ONR-NOAA/RVSALLYRIDE/DATA001https://doi.org/10.5067/SUBORBITAL/PISTON2018-2019-ONR-NOAA/AUTONOMOUS/DATA001 https://doi.org/10.5067/SUBORBITAL/PISTON2018-2019-ONR-NOAA/ISLANDS/DATA001https://doi.org/10.5067/SUBORBITAL/PISTON2018-ONR-NOAA/RVMIRAI/DATA001 (this doi)The CAMP2Ex 2019 data DOI is:https://doi.org/DOI: 10.5067/Suborbital/CAMP2EX2018/DATA001The CAMP2Ex (Clouds, Aerosol and Monsoon Processes-Philippines Experiment, 2019) and PISTON (Propagation of Intra-Seasonal Tropical Oscillations, 2018-2019) were two field studies conducted collaboratively in the Southeast Asian region. While each study had its own set of science objectives, there were common and complementary science goals and instrument payloads between these two projects. Consequently, a synergistic partnership was established at the very beginning of the projects and a coordinated sampling strategy was developed to extend spatial coverage and obtain temporal context information,
Global Ocean Ship-based Hydrographic Investigations Program (GO-SHIP)
Measurements from the GO-SHIP (Global Ocean Ship-based Hydrographic Investigations Program) project, which is a network of sustained hydrographic sections, supporting physical oceanography, the carbon cycle, and marine biogeochemistry and ecosystems.
Biological Global Ocean Ship-based Hydrographic Investigations Program (Bio-GO-SHIP)
Bio-GO-SHIP aims to become an international collaboration to measure, understand, and predict the distribution and biogeochemical role of pelagic plankton communities. The project leverages the global-reaching [GO-SHIP](https://www.go-ship.org/) platform and its complementary hydrographic measurements. The mission of Bio-GO-SHIP is to quantify the molecular diversity, size spectrum, chemical composition, and abundances of plankton communities across large spatial, vertical, and eventually temporal scales. This will be achieved through systematic, high-quality, and calibrated sampling of omics, plankton imaging, particle chemistry, and optical techniques as operational oceanographic tools. Integration with regular GO-SHIP measurements and their analyses of the physical and chemical environment will allow us to understand (and eventually predict) how plankton communities respondto ocean changes and how biological processes feeds backon carbon, oxygen and nutrient cycles.
Processing and Distribution of Hyperspectral Radiometer Data from Ships of Opportunity for Monitoring Phytoplankton in the Ocean
Ocean-colour sensors mounted on satellites can view the entire ocean over a period of a few days. However, to calibrate these sensors and validate the data, satellite observations must be compared with accurate and reliable in situ measurements, collected at the ocean surface. There are many regions of the ocean where these in situ measurements are rarely collected. Ocean-colour sensors can be mounted on research vessels and ships of opportunity. In this project, an ocean-colour sensor (Seabird HyperSAS Solar Tracker) was mounted on a yacht that visits remote regions of the planet where few observations have been collected. This project aims to process this data to a level for use by the scientific community for scientific applications, such as satellite validation.
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.