Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
17
datasets available to search
ShareScore release 0.9.0
Dataset results
17 results for “time of arrival data”
A catalog of associated, machine-learning-derived phase arrival times for ten days of seismic data in the Yellowstone region
<p>This dataset contains the associated phase picks and event information from applying a deep learning phase picker to continuous data recorded over March 25 – April 3, 2014, on 20 three-component stations and 14 vertical-component stations in the Yellowstone region. This 10-day period contains an M<sub>w</sub> 4.8 event, the largest earthquake in the Yellowstone region since 1980. The catalog and deep learning phase picker are described in Armstrong et al. (submitted).</p> <p>The arrivals were associated using the method described by Baker et al. (2021) and located using HypoInverse2000 (Klein, 2002). There are 1,053 events in this catalog, including 855 that were previously unidentified. Events that also appear in the University of Utah Seismograph Stations catalog have an event identifier (evid) beginning with “6”, while new events begin with “9”. </p> <p>Columns include:</p> <ul> <li>A simple event number</li> <li>the network, station, channel, and location code for the arrival time</li> <li>the arrival time in UTC (arrival_time) and Unix (arrival_time_epoch) format</li> <li>any static correction applied to the arrival time</li> <li>the P-pick first motion polarity as determined by a machine learning model - up (1), down (-1), or unknown (0)</li> <li>the arrival time residual </li> <li>the take off angle in degrees </li> <li>the event latitude and longitude in degrees</li> <li>the event depth in km</li> <li>the event origin time in UTC (origin_time) and Unix (origin_time_epoch) format</li> <li>the azimuthal gap of the event in degrees</li> <li>the root mean square error (RMS) of the event location</li> <li>the event identifier (evid) - begins with a “6” for events in the UUSS catalog and a “9” for new events</li> </ul> <p> </p>
Data from: Timing and probability of arrival for sea lice dispersing between salmon farms
<p>Sea lice are a threat to the health of both wild and farmed salmon and an economic burden for salmon farms. With a free-living larval stage, sea lice can disperse tens of kilometers in the ocean between salmon farms, leading to connected sea lice populations that are difficult to control in isolation. In this paper, we develop a simple analytical model for the dispersal of sea lice between two salmon farms. From the model we calculate the arrival time distribution of sea lice dispersing between farms, as well as the level of cross-infection of sea lice. We also use numerical flows from a hydrodynamic model, coupled with a particle tracking model, to directly calculate the arrival time of sea lice dispersing between two farms in the Broughton Archipelago, BC, in order to fit our analytical model and find realistic parameter estimates. Using the parametrized analytical model we show that there is often an intermediate inter-farm spacing that maximizes the level of cross-infection between farms, and that increased temperatures will lead to increased levels of cross-infection.</p>
Data from: Timing and probability of arrival for sea lice dispersing between salmon farms
Open the record for dataset details and reuse information.
Arrival-time data manually picked up of Pn wave in Hainan Island and surrounding areas
<p>This file is the arrival-time data manually picked up of Pn wave in Hainan Island and surrounding areas. It is only used for scientific research.</p>
Arrival-time data automatically picked up by PickNet of Pn wave in Tanlu Fault Zone and surrounding areas
<p>This file is the arrival-time data automatically picked up by PickNet of Pn wave in Tanlu Fault Zone and surrounding areas. Only these Pn arrival times are used for tomographic inversion.</p> <p> </p>
Arrival-time data of the Longmenshan Fault Zone in East Tibet
<p>This file is the manually arrival-time data of the Longmenshan Fault Zone in East Tibet, including P, S and PmP arrival times.</p>
Data from: Sex-specific arrival times on the breeding grounds: hybridizing migratory skuas provide empirical support for the role of sex ratios
In migratory animals, protandry (earlier arrival of males on the breeding grounds) prevails over protogyny (females preceding males). In theory, sex differences in timing of arrival should be driven by the operational sex ratio, shifting toward protogyny in female-biased populations. However, empirical support for this hypothesis is, to date, lacking. To test this hypothesis, we analyzed arrival data from three populations of the long-distance migratory south polar skua (Catharacta maccormicki). These populations differed in their operational sex ratio caused by the unidirectional hybridization of male south polar skuas with female brown skuas (Catharacta antarctica lonnbergi). We found that arrival times were protandrous in allopatry, shifting toward protogyny in female-biased populations when breeding in sympatry. This unique observation is consistent with theoretical predictions that sex-specific arrival times should be influenced by sex ratio and that protogyny should be observed in populations with female-biased operational sex ratio.
Data from: Timing of arrival in the breeding area is repeatable and affects reproductive success in a non-migratory population of blue tits
<ol> <li>Events in one part of the annual cycle often affect the performance (and subsequently fitness) of individuals later in the season (carry-over effects). An important aspect of this relates to the timing of activities. For example, many studies on migratory birds have shown that relatively late spring arrival in the breeding area reduces both the likelihood of getting a mate or territory and reproductive success.</li> <li>In contrast, relatively little is known about movements of individuals in non-migratory populations during the non-breeding season. Few studies have investigated the timing of arrival at the breeding area in such species, possibly due to the assumption that most individuals remain in the area during the non-breeding season.</li> <li>In this study, we used four years of data from a transponder-based automated recording system set up in a non-migratory population of blue tits (<i>Cyanistes caeruleus</i>) to describe individual variation in arrival at the breeding site. We investigated whether this variation can be explained by individual characteristics (sex, body size, or status), and we assessed its effect on aspects of reproductive success in the subsequent breeding season.</li> <li>We found substantial variation in arrival date and demonstrate that this trait is individual-specific (repeatable). Females arrived later than males, but the arrival dates of social pair members were more similar than expected by chance, which suggests that individuals may mate assortatively depending on their arrival in the breeding area. Arrival predicted both whether an individual would end up breeding that season, and several aspects of its breeding success.</li> <li>Our study suggests that individuals of non-migratory species leave the breeding area during the non-breeding season. Hence, it may be useful to consider variation in the scale of movements between breeding and non-breeding sites, rather than using a simple dichotomy between "resident" and "migratory" species. We conclude that the timing of pre-breeding events, in particular arrival date, may be an overlooked, but important, fitness-relevant trait in non-migratory species.</li> </ol>
Cumulative arrival time distribution data for "Upscaling transport in heterogeneous media featuring local-scale dispersion: flow channeling, macro-retardation and parameter prediction"
<div> <div>This archive contains arrival time CDF data for a variety of transport simulations in heterogeneous Darcy flow fields, alongside metadata describing the flow fields. The flow fields were spatially periodic, intersected by uniformly-spaced imaginary planes. Arrival times represent length of time from particle departure from one plane until arrival at the next.</div> <div> </div> <div>Consult the README.md file at the top level of the archive for more information. The file format used to store the CDF data is documented in the Python script at the top level of the archive.</div> </div>
Data for "A Method of Three-Dimensional Location for LFEDA Combining the Time of Arrival Method and the Time Reversal Technique"
<p>The data used to generate and be displayed in figures and tables in this manuscript can be downloaded here. Please use Matlab to open files in mat format and use Microsoft Excel to open files in xlsx format. The data can be used freely for scientific purposes with appropriate citation.</p>
Data from: Timing of arrival in the breeding area is repeatable and affects reproductive success in a non-migratory population of blue tits
Open the record for dataset details and reuse information.
Data from: Sex-specific arrival times on the breeding grounds: hybridizing migratory skuas provide empirical support for the role of sex ratios
Open the record for dataset details and reuse information.
Data from: Timing of mutualist arrival has a greater effect on Pinus muricata seedling growth than interspecific competition
Open the record for dataset details and reuse information.
Data from: Factors related to time of stroke onset versus time of hospital arrival: A SITS registry-based study in an Egyptian Stroke Center
<p><b>Background: </b>high-quality data on time of stroke onset and time of hospital arrival is required for proper evaluation of points of delay that might hinder access to medical care after the onset of stroke symptoms.</p> <p><b>Purpose: </b>Based on (SITS Dataset) in Egyptian stroke patients, we aimed to explore factors related to time of onset versus time of hospital arrival for acute ischemic stroke (AIS).</p> <p><span><b>Material and Methods:</b> We included 1,450 AIS patients from two stroke centers of Ain Shams University, Cairo, Egypt. We divided the day to four quarters and evaluated relationship between different factors and time of stroke onset and time of hospital arrival. The factors included: age, sex, duration from stroke onset to hospital arrival, type of management, type of stroke (TOAST classification), National Institute of Health Stroke Scale (NIHSS) on admission and favorable outcome modified Rankin Scale (mRS ≤2). </span></p> <p><span><b>Results: </b>Pre-hospital: highest stroke incidence was in the first and fourth quarters. There was no significant difference in the mean age, sex, type of stroke in relation to time of onset. NIHSS was significantly less in onset in third quarter of the day. Percentage of patients who received thrombolytic therapy was higher with onset in the first 2 quarters of the day (p=<0.001). In-hospital: there was no difference in percentage of patients who received thrombolytic therapy nor in outcome across 4 quarters of arrival to hospital.</span></p> <p><span><b>Conclusion:</b> pre-hospital factors still need adjustment to improve percentage of thrombolysis, while in-hospital factors showed consistent performance.</span></p>
Data from: Predation can select for later and more synchronous arrival times in migrating species
For migratory species, the timing of arrival at breeding grounds is an important determinant of fitness. Too early arrival at the breeding ground is associated with various costs, and we focus on one understudied cost: that migrants can experience a higher risk of predation if arriving earlier than the bulk of the breeding population. We show, using both a semi-analytic and simulation model, that predation can select for later arrival. This is because of safety in numbers: predation risk becomes diluted if many other individuals, either con- or heterospecific, are already residing in the area. Predation risk dilution can also select for more synchronous arrival because deviating from the current population-wide norm to earlier or later dates leads to higher predation risk or to failures in territory acquisition, respectively. The fact that selection for high arrival synchrony can in some cases be more important than selection for a specific date (early or late) within the season is an example of an 'evolutionary priority effect': whichever strategy – in this case a particular arrival time – becomes established in a population can remain stable over long periods of time; there are many possible equilibria (multiple stable states) which the population can remain at. Mixed arrival strategies are also possible under some circumstances.
Data from: Predation can select for later and more synchronous arrival times in migrating species
Open the record for dataset details and reuse information.
Data from: Factors related to time of stroke onset versus time of hospital arrival: A SITS registry-based study in an Egyptian Stroke Center
Open the record for dataset details and reuse information.
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.