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101 results for “vessel data”
Data from: Imaging markers of small vessel disease and 'brain frailty' and outcomes in acute stroke
Objective: We assessed the association of baseline imaging markers of cerebral small vessel disease (SVD) and 'brain frailty' with clinical outcome after acute stroke in the Efficacy of Nitric Oxide in Stroke (ENOS) trial. Methods: ENOS randomised 4011 patients with acute stroke (<48 hours of onset) to transdermal glyceryl trinitrate (GTN) or no GTN for 7 days. The primary outcome was functional outcome (modified Rankin Scale, mRS) at day 90. Cognition was assessed via telephone at day 90. Stroke syndrome was classified using the Oxfordshire Community Stroke Project classification. Brain imaging was adjudicated masked to clinical information and treatment, and assessed SVD (leukoaraiosis, old lacunar infarcts/lacunes, atrophy) and 'brain frailty' (leukoaraiosis, atrophy, old vascular lesions/infarcts). Analyses used ordinal logistic regression adjusted for prognostic variables. Results: In all participants and those with lacunar syndromes (LACS, 1397, 34.8%), baseline CT imaging features of SVD and 'brain frailty' were common and independently associated with unfavourable shifts in mRS at day 90: all participants (SVD score OR 1.15, 95% CI 1.07-1.24; 'brain frailty' score OR 1.25, 95% CI 1.17-1.34); those with LACS (SVD score OR 1.30, 95% CI 1.15-1.47; 'brain frailty' score OR 1.28, 95% CI 1.14-1.44). 'Brain frailty' was associated with worse cognitive scores at 90 days in all and in LACS participants. Conclusions: Baseline imaging features of SVD and 'brain frailty' were common in lacunar stroke and all stroke, predicted worse prognosis after all acute stroke with a stronger effect in lacunar stroke, and may aid future clinical decision-making. Registration: ISRCTN99414122.
Combining Truck and Vessel Tracking Data to Estimate Performance and Impacts of Inland Waterway Ports
<p>The purpose of this project is to estimate the performance of multi-modal supply chains that use inland waterway ports. This is accomplished by developing a method to fuse publicly available datasets including truck and marine vessel tracking data and lock performance data. The study builds on a growing body of research related to multi-modal freight performance measurement, specifically freight fluidity measures. Freight fluidity measurement attempts to capture freight system performance from a multi-modal supply chain perspective. In this study, we effectively combine marine Automatic Identification System (AIS) data with truck Global Positioning System (GPS) data. Both data sources track vessel and vehicle movements and can be used to determine measures such as travel times, dwell times, and other freight activity characteristics.</p> <p>Two models are developed. These are referred to as the Multi-Commodity Assignment Problem (GMAP) and GMAP +. The GMAP model quantifies annualized commodities transloaded at inland waterway port terminals by fusing two mode-specific datasets, truck GPS and marine AIS. The GMAP+ model then assigns commodity flows to vessel trips. Additionally, as a data product, the GMAP and GMAP+ models are used to generate catchment area maps that depict water and truck flows for inland waterway ports in Arkansas. </p> <p> </p>
Data from two moorings and a Moving Vessel Profiler in the Bay of Biscay (ETOILE campaign - 09/07/2017 to 02/08/2017 )
<p>This data set includes all the data from the ETOILE campaign (https://doi.org/10.17600/17010800) used in the paper:</p> <p>Moncuquet A., N. L. Jones, A. P. Zulberti, F. Dufois, L. Bordois, P. Lazure. <strong>Observations of mode-one nonlinear internal waves of opposite polarity in changing background conditions, </strong>submitted to Journal of Geophysical Research in September 2023.</p> <p>==========================================================================</p> <p>The ETOILE campaign (https://doi.org/10.17600/17010800) has been designed to study internal dynamics in the Bay of Biscay.<br> The data archived here are from 2 moorings with ADCPs and temperature/pressure sensors deployed from 09/07/2017 to 02/08/2017. It also includes vertical profiles of CTD measurements performed between the 25th of and 29th of July 2017 using a moving vessel profiler (MVP).</p> <ul> <li><strong>Outer shelf mooring (2L)</strong></li> </ul> <p>The 2L mooring was moored along the 150 m isobath.<br> The 2L mooring had 9 thermistors distributed between 70cm above the bottom and 20 m below the surface, with an acquisition frequency of 1 minute. The bottoms mounted ADCP (RDI Sentinel 300 kHz) was deployed with an acquisition frequency of 2s. The ADCP and the mooring line were separated by 1.4km and respectively located at 43°59.9N, 2°02.537W and 44°00.1N, 2°01.5W.<br> <br> The folder named "2L_mooring" includes the following files:<br> - 2L_MooringLine.mat: a matlab format file with pressure and temperature data.<br> - ADCP_2L_UVW.mat: a matlab format file with ADCP velocity data in earth coordinates.<br> - ADCP_2L_EAS.mat: a matlab format file with ADCP backscatter data.<br> - ADCP_2L_PG.mat: a matlab format file with ADCP "Percentage Good" RDI values.</p> <ul> <li><strong>Inner shelf mooring (2C)</strong></li> </ul> <p>The 2C mooring was moored along the 60 m isobath.<br> The 2C mooring had 6 thermistors distributed between 70cm above the bottom and 20 m below the surface, with an acquisition frequency of 1 minute. The bottoms mounted ADCP (RDI Sentinel 300 kHz) was deployed with an acquisition frequency of 2s. The ADCP and the mooring line were collocated and located at 44°00N, 1°31W.</p> <p>The folder named "2C_mooring" includes the following files:<br> - 2C_MooringLine.mat: a matlab format file with pressure and temperature data.<br> - ADCP_2C_UVW.mat: a matlab format file with ADCP velocity data in earth coordinates.<br> - ADCP_2C_EAS.mat: a matlab format file with ADCP backscatter data.<br> - ADCP_2C_PG.mat: a matlab format file with ADCP "Percentage Good" RDI values.</p> <ul> <li><strong>MVP profiles</strong></li> </ul> <p>The MVP is a self-profiling system capable of measuring pressure P, conductivity sigma, temperature T, salinity S and density rho, behind a travelling vessel at high frequency. The MVP profiled along a 52 km long transect down to 300 m depth for the first two days at a boat speed of 4 knots. The last two days the MVP profiled down to 100 m along a 15 km long transect at a boat speed of 6 knots. A bottom safe margin of 13 m was used to prevent the MVP from hitting the bottom. </p> <p>The folder named "MovingVesselProfiler" includes the MVP files in a native ascii format, with one file per profile (including both downcast and upcast). The file headers includes all the metadata including the time and position of each profile.<br> </p>
RNA Sequencing Analysis in Large Vessel Occlusion Stroke DATA Bank
ClinicalTrials.gov study NCT03490552. IPD Sharing: Not stated. Countries: 1. Publications: 0.
A Study to Collect Data on the Use of Eylea in Babies Born Too Early Who Have a Condition of the Eye Where Blood Vessels Grow Abnormally in the Retina (Retinopathy of Prematurity)
ClinicalTrials.gov study NCT05705258. IPD Sharing: NO. Countries: 1. Publications: 0.
A Study to Collect Data on the Treatment Pattern of Xarelto + Acetylsalicylic Acid in the Routine Clinical Practice in Patients Who Are Suffering From a Condition That Narrows the Blood Vessels Supply
ClinicalTrials.gov study NCT04401761. IPD Sharing: NO. Countries: 10. Publications: 0.
Data from: Imaging markers of small vessel disease and ‘brain frailty’ and outcomes in acute stroke
Open the record for dataset details and reuse information.
OWLETS-2 SERC Research Vessel Data
OWLETS2_Ship_Data_1 is the Ozone Water-Land Environmental Transition Study (OWLETS-2) data collected onboard the Smithsonian Environmental Research Center (SERC) Vessel. OWLETS was supported by the NASA Science Innovation Fund (SIF). Data includes ozone and nitrogen dioxide measurements, meteorological parameters, and ship navigational data collected via in-situ instrumentation. OWLETS and OWLETS-2 were supported by the NASA Science Innovation Fund (SIF). Data collection is complete.Coastal regions have typically posed a challenge for air quality researchers due to a lack of measurements available over water and water-land boundary transitions. Supported by NASA’s Science Innovation Fund (SIF), the Ozone Water-Land Environmental Transition Study (OWLETS) field campaign examined ozone concentrations and gradients over the Chesapeake Bay from July 5, 2017 – August 3, 2017, with twelve intensive measurement days occurring during this time period. OWLETS utilized a unique combination of instrumentation, including aircraft, TOLNet ozone lidars (NASA Goddard Space Flight Center Tropospheric Ozone Differential Absorption Lidar and NASA Langley Research Center Mobile Ozone Lidar), UAV/drones, ozonesondes, AERONET sun photometers, and mobile and ship-based measurements, to characterize the land-water differences in ozone and other pollutants. Two main research sites were established as part of the campaign: an over-land site at NASA LaRC, and an over-water site at the Chesapeake Bay Bridge Tunnel. These two research sites were established to provide synchronous vertical measurements of meteorology and pollutants over water and over land. In combination with mobile observations between the two sites, pollutant gradients were able to be observed and used to better understand the fundamental processes occurring at the land-water interface. OWLETS-2 was completed from June 6, 2018 – July 6, 2018 in the upper Chesapeake Bay region. Research sites were established at the University of Maryland, Baltimore County (UMBC), Hart Miller Island (HMI), and Howard University Beltsville (HUBV), with HMI representing the over-water location and UMBC and HUBV representing the over-land sites. Similar measurements were carried out to further characterize water-land gradients in the upper Chesapeake Bay. The measurements completed during OWLETS are of importance in enhancing air quality models, and improving future satellite retrievals, particularly, NASA’s Tropospheric Emissions: Monitoring of Pollution, which is scheduled to launch in 2022.
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.
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,
LMOS NOAA Research Vessel In-Situ Ozone Data
LMOS_TraceGas_ShipInSitu_Data_1 is the Lake Michigan Ozone Study (LMOS) in-situ trace gas data collected onboard the NOAA Research Vessel during the LMOS field campaign. This product is a result of a joint effort across multiple agencies, including NASA, NOAA, the EPA, Electric Power Research Institute (EPRI), National Science Foundation (NSF), Lake Michigan Air Directors Consortium (LADCO) and its member states, and several research groups at universities. Data collection is complete.Elevated spring and summertime ozone levels remain a challenge along the coast of Lake Michigan, with a number of monitors exceeding the 2015 National Ambient Air Quality Standards (NAAQS) for ozone. The production of ozone over Lake Michigan, combined with onshore daytime “lake breeze” airflow is believed to increase ozone concentrations at locations within a few kilometers of the shore. This observed lake-shore gradient motivated the Lake Michigan Ozone Study (LMOS). Conducted from May through June 2017, the goal of LMOS was to better understand ozone formation and transport around Lake Michigan; in particular, why ozone concentrations are generally highest along the lakeshore and drop off sharply inland and why ozone concentrations peak in rural areas far from major emission sources. LMOS was a collaborative, multi-agency field study that provided extensive observational air quality and meteorology datasets through a combination of airborne, ship, mobile laboratories, and fixed ground-based observational platforms. Chemical transport models (CTMs) and meteorological forecast tools assisted in planning for day-to-day measurement strategies. The long term goals of the LMOS field study were to improve modeled ozone forecasts for this region, better understand ozone formation and transport around Lake Michigan, provide a better understanding of the lakeshore gradient in ozone concentrations (which could influence how the Environmental Protection Agency (EPA) addresses future regional ozone issues), and provide improved knowledge of how emissions influence ozone formation in the region.
KORUS-AQ Research Vessel (R/V) JangMok Ship Data
KORUSAQ_RVJangMokShip_Data features data collected onboard the Research Vessel JangMok during the KORUS-AQ field campaign. This product features trace gas and meteorological and navigational data. 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.
Identification of differential gene expression in blood vessels from patients with uremia (data set 2)
GEO Series GSE38751. Homo sapiens. 10 samples. Type: Expression profiling by array.
RNA sequencing data for hypoxic and normoxic vessels
GEO Series GSE182564. Mus musculus. 2 samples. Type: Expression profiling by high throughput sequencing.
Expression data from vessels of differing embryonic origin
GEO Series GSE50250. Mus musculus. 12 samples. Type: Expression profiling by array.
Inland container vessel data
<p>This file contains data of inland container vessels waiting on the Rhine Alpine corridor, with a special focus on the port of Antwerp and Rotterdam.</p>
Identification of differential gene expression in blood vessels from patients with uremia (data set 1)
GEO Series GSE38750. Homo sapiens. 34 samples. Type: Expression profiling by array.
Inland vessel data
<p>This data file contains data of inland vessels on the Rhine Alpine corridor</p>
GNSS and IMU data recorded during a vessel sail
<p>Example data point of this data set:</p> <pre><code>"0": { "timestamp": 1674573910407, "acceleration_x_ms2": -0.121791042, "acceleration_y_ms2": -0.025389839, "acceleration_z_ms2": -0.049855232, "gps_lat": 51.1537593172, "gps_lon": 2.8057965827, "sog_kmh": 0.39, "rot_deg_min": "1.3", "heading_deg": 230.313, "imu_lat": null, "imu_lon": null, "roll_rate_deg_min": null, "pitch_rate_deg_min": null, "yaw_rate_deg_min": null, "roll_deg": null, "pitch_deg": null, "yaw_deg": null }</code></pre> <p> </p>
Expression data from collecting lymphatic vessels
GEO Series GSE34135. Mus musculus. 4 samples. Type: Expression profiling by array.
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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OpenNeuro
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