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SWOT Level 1 Onboard Tracking Data from Doppler Orbitography and Radiopositioning Integrated by Satellite (DORIS)

Tracking data measurements from the Doppler Orbitography and Radiopositioning Integrated by Satellite (DORIS) payload receiver onboard SWOT. The tracking data are generated using signals from DORIS ground beacons and are used to perform precise orbit determination of the SWOT spacecraft. They are also used to compute the precise orbit ephemeris(POE), and the medium-accuracy orbit ephemeris (MOE) used for SWOT data processing. Distributed as one file per day in RINEX file format, available with latency of < 2 days.

ATom: Aircraft Flight Track and Navigational Data

This dataset provides flight track and aircraft navigation data from the NASA Atmospheric Tomography Mission (ATom). Flight track information is available for the four ATom campaigns: ATom-1, ATom-2, ATom-3, and ATom-4. Each ATom campaign consists of multiple individual flights and flight navigational information is recorded in 10-second intervals. Data available for each flight includes research flight number, date, and start and stop time of each 10-second interval. In addition, latitude, longitude, altitude, pressure and temperature is included at each 10-second interval. NASA's ATom campaign deploys an extensive gas and aerosol payload on the NASA DC-8 aircraft for systematic, global-scale sampling of the atmosphere, profiling continuously from 0.2 to 12 km altitude. Flights occurred in each of 4 seasons from 2016 to 2018. During each campaign, flights originate from the Armstrong Flight Research Center in Palmdale, California, fly north to the western Arctic, south to the South Pacific, east to the Atlantic, north to Greenland, and return to California across central North America. ATom establishes a single, contiguous, global-scale dataset. One intended use of this flight track data is to facilitate to mapping model results from global models onto the precise ATom flight tracks for comparison.

SWOT Level 1 Onboard Tracking Data from Global Positioning System Payload (GPSP)

GPS tracking data measurements from the GPS Payload (GPSP) receiver onboard SWOT. The tracking data are generated by the GPSP using signals from the GPS constellation of satellites and are used to perform precise orbit determination of the SWOT spacecraft. They are also used to compute the precise orbit ephemeris (POE), and the medium-accuracy orbit ephemeris (MOE) used for SWOT data processing. Distributed as one RINEX file per data downlink regardless of temporal coverage, available with latency of < 2 days.

SPURS-2 research vessel along track SEA-POL rain radar imaging data for E. Tropical Pacific R/V Revelle-2 cruise

The SPURS (Salinity Processes in the Upper Ocean Regional Study) project is NASA-funded oceanographic process study and associated field program that aim to elucidate key mechanisms responsible for near-surface salinity variations in the oceans. The project involves two field campaigns and a series of cruises in regions of the Atlantic and Pacific Oceans exhibiting salinity extremes. SPURS employs a suite of state-of-the-art in-situ sampling technologies that, combined with remotely sensed salinity fields from the Aquarius/SAC-D, SMAP and SMOS satellites, provide a detailed characterization of salinity structure over a continuum of spatio-temporal scales. The SPURS-2 campaign involved two month-long cruises by the R/V Revelle in August 2016 and October 2017 combined with complementary sampling on a more continuous basis over this period by the schooner Lady Amber. Focused around a central mooring located near 10N,125W, the objective of SPURS-2 was to study the dynamics of the rainfall-dominated surface ocean at the western edge of the eastern Pacific fresh pool subject to high seasonal variability and strong zonal flows associated with the North Equatorial Current and Countercurrent. The SEA-POL rain radar instrument was employed over the period 22 Oct.-10 Nov. 2017 during the second SPURS-2 R/V Revelle cruise. SEA-POL (seagoing-polarimetric radar) is a C-band, Doppler polarimetric radar system providing 240-degree sector coverage centered on the ships bow via its 1-degree beam width antenna. SEA-POL was used primarily to map rainfall in SPURS-2. The resulting dataset is a series of gridded netCDF data files for a 20 day period at 5-20 minute intervals comprised of rain rate and rain accumulation fields.

opencc-by-4.0Mar 2020View details →

Inertial Sensor-Based Motion Tracking in Football with Movement Intensity Quantification - Data

Processed data of IMU measurements and VICON measurements, including the necessary Matlab scripts to process the data from research article 'Inertial Sensor-Based Motion Tracking in Football with Movement Intensity Quantification'.

opencc-by-4.0Jul 2020View details →

Figure 5 from: Milotic T, Desmet P, Anselin A, De Bruyn L, De Regge N, Janssens K, Klaassen R, Koks B, Schaub T, Schlaich A, Spanoghe G, T'jollyn F, Vanoverbeke J, Bouten W (2020) GPS tracking data of Western marsh harriers breeding in Belgium and the Netherlands. ZooKeys 947: 143-155. https://doi.org/10.3897/zookeys.947.52570

Figure 5 Number of acceleration records per year and per dataset.

opencc-by-4.0Jul 2020View details →

Figure 4 from: Milotic T, Desmet P, Anselin A, De Bruyn L, De Regge N, Janssens K, Klaassen R, Koks B, Schaub T, Schlaich A, Spanoghe G, T'jollyn F, Vanoverbeke J, Bouten W (2020) GPS tracking data of Western marsh harriers breeding in Belgium and the Netherlands. ZooKeys 947: 143-155. https://doi.org/10.3897/zookeys.947.52570

Figure 4 Number of GPS fixes per year and per dataset.

opencc-by-4.0Jul 2020View details →

Figure 3 from: Milotic T, Desmet P, Anselin A, De Bruyn L, De Regge N, Janssens K, Klaassen R, Koks B, Schaub T, Schlaich A, Spanoghe G, T'jollyn F, Vanoverbeke J, Bouten W (2020) GPS tracking data of Western marsh harriers breeding in Belgium and the Netherlands. ZooKeys 947: 143-155. https://doi.org/10.3897/zookeys.947.52570

Figure 3 Tracking effort: number of observations per day and per individual.

opencc-by-4.0Sep 2020View details →

data set related to article How Attention to Faces and Objects Changes Over Time in Toddlers with Autism Spectrum Disorders: Preliminary Evidence from An Eye Tracking Study

This record contains raw data related to article How Attention to Faces and Objects Changes Over Time in Toddlers with Autism Spectrum Disorders: Preliminary Evidence from An Eye Tracking Study

opencc-zeroSep 2020View details →

Tracking data (acoustic telemetry) of parrotfishes in the Red Sea

Herbivorous fishes such as parrotfishes (Scaridae) play a crucial role in maintaining reef health by grazing macroalgae that would otherwise out-compete corals for space. Full appreciation of this contribution, however, depends on understanding the spatiotemporal patterns of parrotfish habitat utilization. Studies on spatial dynamics of parrotfish have been limited to short temporal spans (days to weeks) or coarse spatial resolution (kilometers). In this study, we used an underwater acoustic tracking system to monitor the movement and activity of 23 individuals, from three parrotfish species, for up to 520 days. We found that parrotfish exhibited surprisingly high degrees of sleeping and foraging site fidelity, between which they commuted daily. Consequently, diurnal activity was restricted throughout the entire study duration, to the same confined areas (7,155 ± 800 m2, mean ± SE). These high activity areas should be compared to the total home range area of 51,990 ± 7,174 m2. These results suggest that the ecological impact of individual parrotfish grazing is far more restricted than expected from their overall home range. The extremely constrained foraging areas raise concerns of the capacity of parrotfish to mitigate phase shifts in coral reefs by spatially adjusting their foraging behaviors. From a broader perspective, this study highlights the importance of looking beyond overall home range, to examine spatiotemporal patterns of specific activities.

opencc-by-4.0Nov 2020View details →

Combining Truck and Vessel Tracking Data to Estimate Performance and Impacts of Inland Waterway Ports

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. 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.

opencc-zeroJan 2021View details →

Tracking and retention time data from Larus fuscus feeding at Doñana ricefields in Andalusia

1. Non-frugivorous waterbirds disperse a wide variety of plants by endozoochory, providing longer dispersal distances than other mechanisms. Many waterbirds visit both agricultural and natural landscapes during their daily movements, but potential bird-mediated dispersal of weed plants within and from agricultural landscapes to other habitats is commonly overlooked. Gulls (Laridae) are expanding in numbers and increasingly exploiting anthropogenic habitats worldwide, with possible growing implications for the spread of weeds. Yet, to date there are no studies on the spatial distribution of weed dispersal by waterbirds. 2. We developed a plant dispersal model based on movements of 19 Larus fuscus using ricefields, via GPS telemetry. We combined daily movements with two curves estimating the retention times (RT) of plant seeds in their guts: 1) an experimental curve based on RT in captivity for four weeds with dry fruits known to be dispersed by gulls: Juncus bufonius, Cyperus difformis, Polypogon monspeliensis and Amaranthus retroflexus; 2) a theoretical curve based on the interspecific scaling relationship between body mass and mean RT. 3. Median dispersal distances of weed plant seeds by gulls ranged between 690-940 m, but maximum distances exceeded 100 km. The theoretical RT model showed higher median dispersal distances than the experimental RT model, but lower maxima (131 and 151 km, respectively). Spatial patterns of weed deposition were very similar between RT methods, and most strongly depended on gull movements. Variation between individual gulls had little influence on seed shadows. About 92% of all seeds (>10,000 intact seeds per day) were dispersed within the ricefield area of 370 km2. The remaining 8% of seeds were deposited beyond ricefields into other habitats, 42% of which reached moist environments (other irrigated agriculture, rivers and natural wetlands) presumably suitable for weed establishment. 4. Synthesis: Gulls can disperse weed plants over long distances across a mosaic of habitats. This implies exchange of weed plant species between human-dominated and natural areas by waterbirds as dispersal vectors. This spatial study highlights the importance of non-frugivorous birds for long-distance plant dispersal, which is generally an overlooked mechanism in studies aiming to predict and manage expansion of weed plants.

opencc-zeroDec 2014View details →

Data from: Tracking marine mammals in 3D using electronic tag data

1. Information about at-depth behaviour of marine mammals is fundamental yet very hard to obtain from direct visual observation. Animal-borne multisensor electronic tags provide a unique window of observation into such behaviours. 2. Electronic tag sensors allow the estimation of the animal's 3-dimensional (3D) orientation, depth and speed. Using tag flow noise level to provide an estimate of animal speed, we extend existing approaches of 3D track reconstruction by allowing the direction of movement to differ from that of the animal's longitudinal axis. 3. Data are processed by a hierarchical Bayesian model that allows processing of multisource data, accounting for measurement errors and testing hypotheses about animal movement by comparing models. 4. We illustrate the approach by reconstructing the 3D track of a 52-min deep dive of a Blainville's beaked whale Mesoplodon densirostris adult male fit with a digital tag (DTAG) in the Bahamas. At depth, the whale alternated regular movements at large speed (>1·5 m s -1) and more complex movements at lower speed (<1·5m s-1) with differences between movement and longitudinal axis directions of up to 28inline image. The reconstructed 3D track agrees closely with independent acoustic-based localizations. 5. The approach is potentially applicable to study the underwater behaviour (e.g. response to anthropogenic disturbances) of a wide variety of species of marine mammals fitted with triaxial magnetometer and accelerometer tags.

restrictedcc-by-4.0Feb 2024View details →

Processed tracking data of Southern Giant Petrels during breeding activity in Harmony Point, Nelson Island, between 2021 and 2023

Processed GPS data for 36 Southern Giant Petrels (Macronectes giganteus) in December and January of 2021/22 and 2022/23 breeding season in Harmony Point (62°17′60″ S, 59°10′60″ W), Nelson Island, Maritime Antarctic Peninusula. All individuals had active nests. Bill size and tarsus length for 50 southern giant petrels ringed in the area. Between 2021 and 2023 50 breeding individuals were captured on the nest, following methods and protocols previously approved (https://zenodo.org/doi/10.5281/zenodo.10640094). For capture, one researcher approached the colony, while the others remained at a distance, preferentially out of sight of the birds. Response behavior to the approaching researcher was used as a proxy for capture selection, for instance, animals that regurgitate or stand on the nest exposing the eggs when the researcher approaches are more likely to leave the nest or might take longer to return to the nest after releasing, increasing the risk of breeding failure (Krüger et al. in prep). Therefore, animals displaying those behaviors were not captured. Before capture, the egg was gently removed from below the bird, covered in thermal tissue and put inside a box, for protection from cold and predation. Then the bird was captured by hand and taken to the site where other two researchers were waiting. Animals had their eyes covered with a head hood. All captured animals were ringed with stainless steel bands (rings), preferentially both animals from the same nest each season. All captured animals had bill and tarsus measured with calipers. Bill was used to determine sex, since males have larger bills with no overlap of measures with females. After release back to the nest, behavioral status of the animal was observed, and after the animal remained sat at the nest, the egg was placed back. GPSs were deployed on the back of the birds using 3M Extreme Hold Duct Tape 2835-B (1.88 inches) and Loctite glue.  In 2021/22 and 2022/2023 seasons 30 and 20 birds were tagged with GPSs, respectively. In 2021/22, 4 females lost the GPS, and in 2022/23 one male and one female lost the GPS. Therefore there was tracking data for 26 and 18 animals, respectively.  Eight animals were repeated in both seasons, totalizing 36 animals tracked in the two seasons. CatLog-P Gen 2 epoxy cased GPSs loggers (Perthold Technology, 50g) and Sputnik XAIS GPSs (Sextant technology, 70g) were used. Southern Giant Petrel weight varies between 4 kg and 6 kg, therefore the heavier instrumentation on the lighter birds would represent less than 2% of body weight, percentage which is accepted to have no significant effect on large procellariforms . Loggers were configurated to record one geographical fix each 5 minutes, and were recovered from the birds after 2 to 4 weeks. See https://github.com/drlucaskruger/SouthernGiantPetrel_Movements_and_Individual_Size for codes. This study was funded by INACH (Programa Áreas Marinas Protegidas 24 03 052) and ANID – Programa Iniciativa Milenio – ICN2021_002 (BASE).

opencc-by-4.0Jun 2022View details →

Microscopy and track data for extraction of accurate cytoskeletal actin velocity distributions

This data accompanies the paper Extraction of accurate cytoskeletal actin velocity distributions from noisy measurements by C M Miller, E Korkmazhan, and A R Dunn. The data include actin speckle microscopy videos and corresponding track files containing coordinates and other information from tracked speckles. These data were collected in both human foreskin fibroblasts (HFFs) and human umbilical vein endothelial cells (HUVECs). Each data "set" contains one group of fixed cells, and one or more groups of live cells.  Further information about the data structure is supplied in the README doc, and further experimental detail in the accompanying paper: https://doi.org/10.1101/2020.08.13.247304

opencc-by-4.0Apr 2024View details →

Raw Data: Enhancing Stroke Risk Prediction in Patients with Transient Ischemic Attack: Insights from a Prospective Cohort Study Implementing Fast-Track Care

Background and aims: Fast-track care have been proved to reduce the short-term risk of stroke after transient ischemic attack (TIA). We aimed to investigate stroke risk and to characterize short-and long-term stroke predictors in a large cohort of TIA patients undergoing fast-track management.Methods: Prospective study, enrolling consecutive TIA patients admitted to a Northern Italy emergency department from August 2010 to December 2017. All patients underwent fasttrack care within 24 hours of admission. The primary outcome was defined as the first stroke recurrence at 90 days, 12 and 60 months after TIA. Stroke incidence with 95% confidence interval (CI) at each timepoint was calculated using Poisson regression. Predictors of stroke recurrence were evaluated with Cox regression analysis. The number needed to treat (NNT) of fast-track care in preventing 90-day stroke recurrence in respect to the estimates based on baseline ABCD2 score was also calculated.We enrolled 1035 patients (54.2% males). Stroke incidence was low throughout the follow-up with rates of 2.2% [95% CI 1.4%-3.3%] at 90 days, 2.9% [95% CI 1.9%-4.2%] at 12 months and 7.1% [95% CI 5.4%-9.0%] at 60 months. Multiple TIA, speech disturbances and presence of ischemic lesion at neuroimaging predicted stroke recurrence at each timepoint. Male sex and increasing age predicted 90-day and 60-month stroke risk, respectively. Hypertension was associated with higher 12-month and 60-month stroke risk.No specific TIA etiology predicted higher stroke risk throughout the follow-up. The NNT for fast-track care in preventing 90-day stroke was ] in the overall cohort and 6.8 [95% CI 4.6-13.5] in patients with baseline ABCD2 of 6 to 7.Our findings support the effectiveness of fast-track care in preventing both short-and long-term stroke recurrence after TIA.

opencc-zeroDec 2017View details →

Data from: Large-scale network integration in the human brain tracks temporal fluctuations in memory encoding performance

Although activation/deactivation of specific brain regions have been shown to be predictive of successful memory encoding, the relationship between time-varying large-scale brain networks and fluctuations of memory encoding performance remains unclear. Here we investigated time-varying functional connectivity patterns across the human brain in periods of 30-40 s, which have recently been implicated in various cognitive functions. During functional magnetic resonance imaging, participants performed a memory encoding task, and their performance was assessed with a subsequent surprise memory test. A graph analysis of functional connectivity patterns revealed that increased integration of the subcortical, default-mode, salience, and visual subnetworks with other subnetworks is a hallmark of successful memory encoding. Moreover, multivariate analysis using the graph metrics of integration reliably classified the brain network states into the period of high (vs. low) memo ry encoding performance. Our findings suggest that a diverse set of brain systems dynamically interact to support successful memory encoding.

opencc-by-4.0Jan 2016View details →

Figure 4 from: Stienen EWM, Desmet P, Aelterman B, Courtens W, Feys S, Vanermen N, Verstraete H, Van de walle M, Deneudt K, Hernandez F, Houthoofdt R, Vanhoorne B, Bouten W, Buijs RJ, Kavelaars MM, Müller W, Herman D, Matheve H, Sotillo A, Lens L (2016) GPS tracking data of Lesser Black-backed Gulls and Herring Gulls breeding at the southern North Sea coast. ZooKeys 555: 115-124. https://doi.org/10.3897/zookeys.555.6173

Figure 4 - Number of birds grouped by number of tracking days and tracking start year.