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12,237 results for “2019”
Lake Superior bluff toes and crests from Wisconsin Point to Bark Point, 2009 and 2019
<p>This repository contains shapefiles of bluff toe and crest points delineated from LiDAR data collected in the years 2009 and 2019 for the Wisconsin Lake Superior coast from Wisconsin Point to Bark Point. The shapefiles have a horizontal coordinate reference system of EPSG:32615 and their names describe the year and feature they represent. Additional details regarding the creation of these points can found in the accompanying publication (https://doi.org/10.1016/j.jglr.2024.102366).</p>
Percentage survival of wMel-infected Aedes aegypti in UAV trial II in Nausori, Fiji (2019)
<p><span>Triplicates samples of approximately 100-200 mosquitoes were collected from the emergence cages (rearing control), after cold immobilization at 4°C for 30 minutes (immobilization control), and after the end of each flight. Survival % was compared to that of the rearing control and statistical analysis was performed using ordinary one-way ANOVA, unless otherwise specified in the data sheet. NS = Not statistically significant and ND = Not done</span></p>
Ozone 3D field from IRS OSSE Control run - June 2019
<p>In the frame of Vittorioso's PhD, an Observing System Simulation Experiment has bee set up to evaluate the future benefit of the geostationary IRS sounder on ozone field over Europe. The full set-up is composed of a Nature Run (reality), a Control Run (no assimilation) and an Assimilation Run (assimilation or IRS) over the months June to August 2019.<br>This dataset is Ozone 3D field from the control run for June 2019. One file per day including hourly fields, gathered in 3 tar files.</p>
Ozone 3D field from IRS assimilation run - July 2019
<p>In the frame of Vittorioso's PhD, an Observing System Simulation Experiment has bee set up to evaluate the future benefit of the geostationary IRS sounder on ozone field over Europe. The full set-up is composed of a Nature Run (reality), a Control Run (no assimilation) and an Assimilation Run (assimilation or IRS) over the months June to August 2019.<br>This dataset is Ozone 3D field from the assimilation run for July 2019. One file per day including hourly field, all days in one tar file.</p>
Ozone 3D field from IRS OSSE Control run - July 2019
<p>In the frame of Vittorioso's PhD, an Observing System Simulation Experiment has bee set up to evaluate the future benefit of the geostationary IRS sounder on ozone field over Europe. The full set-up is composed of a Nature Run (reality), a Control Run (no assimilation) and an Assimilation Run (assimilation or IRS) over the months June to August 2019.<br>This dataset is Ozone 3D field from the control run for July 2019. One file per day including hourly fields, gathered in 3 tar files.</p>
Ozone 3D field from IRS assimilation run - August 2019
<p>In the frame of Vittorioso's PhD, an Observing System Simulation Experiment has bee set up to evaluate the future benefit of the geostationary IRS sounder on ozone field over Europe. The full set-up is composed of a Nature Run (reality), a Control Run (no assimilation) and an Assimilation Run (assimilation or IRS) over the months June to August 2019.<br>This dataset is Ozone 3D field from the assimilation run for August 2019. One file per day including hourly field, distributed in 3 tar files.</p>
Ozone 3D field from IRS OSSE Control run - August 2019
<p>In the frame of Vittorioso's PhD, an Observing System Simulation Experiment has bee set up to evaluate the future benefit of the geostationary IRS sounder on ozone field over Europe. The full set-up is composed of a Nature Run (reality), a Control Run (no assimilation) and an Assimilation Run (assimilation or IRS) over the months June to August 2019.<br>This dataset is Ozone 3D field from the control run for August 2019. One file per day including hourly fields, gathered in 3 tar files.</p>
Ozone 3D field from IRS OSSE Nature run - June 2019
<p>In the frame of Vittorioso's PhD, an Observing System Simulation Experiment has bee set up to evaluate the future benefit of the geostationary IRS sounder on ozone field over Europe. The full set-up is composed of a Nature Run (reality), a Control Run (no assimilation) and an Assimilation Run (assimilation or IRS) over the months June to August 2019.<br>This dataset is Ozone 3D field from the nature run for June 2019. One file per day including hourly fields, gathered in 3 tar files.</p>
Ozone 3D field from IRS OSSE Nature run - August 2019
<p>In the frame of Vittorioso's PhD, an Observing System Simulation Experiment has bee set up to evaluate the future benefit of the geostationary IRS sounder on ozone field over Europe. The full set-up is composed of a Nature Run (reality), a Control Run (no assimilation) and an Assimilation Run (assimilation or IRS) over the months June to August 2019.<br>This dataset is Ozone 3D field from the nature run for August 2019. One file per day including hourly fields, gathered in 3 tar files.</p>
Ozone 3D field from IRS OSSE Nature run - July 2019
<p>In the frame of Vittorioso's PhD, an Observing System Simulation Experiment has bee set up to evaluate the future benefit of the geostationary IRS sounder on ozone field over Europe. The full set-up is composed of a Nature Run (reality), a Control Run (no assimilation) and an Assimilation Run (assimilation or IRS) over the months June to August 2019.<br>This dataset is Ozone 3D field from the nature run for July 2019. One file per day including hourly fields, gathered in 3 tar files.</p>
TorNet 2019
<p>TorNet samples from 2019 as described in “A Benchmark Dataset for Tornado Detection and Prediction using Full-Resolution Polarimetric Weather Radar Data”</p> <p>For more detail, visit <a href="https://github.com/mit-ll/tornet">https://github.com/mit-ll/tornet</a></p> <p> </p> <p>DISTRIBUTION STATEMENT A. Approved for public release. Distribution is unlimited.</p> <p> </p> <p>This material is based upon work supported by the Department of the Air Force under Air Force Contract No. FA8702-15-D-0001. Any opinions, findings, conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the Department of the Air Force.</p> <p> </p> <p>© 2022 Massachusetts Institute of Technology.</p> <p> </p> <p>Delivered to the U.S. Government with Unlimited Rights, as defined in DFARS Part 252.227-7013 or 7014 (Feb 2014). Notwithstanding any copyright notice, U.S. Government rights in this work are defined by DFARS 252.227-7013 or DFARS 252.227-7014 as detailed above. Use of this work other than as specifically authorized by the U.S. Government may violate any copyrights that exist in this work.</p>
Fig. 3 in Hylomus saiyans Nguyen & Nguyen & Nguyen & Phung 2019, sp. nov.
Fig. 3 Percentage of each species of sea turtle in the total stranding/bycatch records.
Fig. 10 in Ophiacantha scissionis Lee & Stöhr & Bae & Shin 2019, sp. nov.
Fig. 10. Comparison of gametogenic stages of seven bivalve species from Jeju Island.
Fig. 7 in Ophiacantha scissionis Lee & Stöhr & Bae & Shin 2019, sp. nov.
Fig. 7. Monthly mean changes in egg size of O. circumpicta.
Fig. 6 in Ophiacantha scissionis Lee & Stöhr & Bae & Shin 2019, sp. nov.
Fig. 6. Frequency distribution of gametogenic stages of O. circumpicta.
Fig. 1 in Ophiacantha scissionis Lee & Stöhr & Bae & Shin 2019, sp. nov.
Fig. 1. Map showing the sampling location, Munseom Island, off the south coast of Jeju Island.
Fig. 2 in Ophiacantha scissionis Lee & Stöhr & Bae & Shin 2019, sp. nov.
Fig. 2. Animal and shell of O. circumpicta., Gonad,, Gills.
Auswertung zur Referenzierung von Forschungsdaten in den ECTEL-Proceedings 2019-2023
<p>Der Datensatz enthält eine Auswertung dazu, wie in den Proceedings der European Conference on Technology-Enhanced Learning (ECTEL) von 2019-2023 Forschungsdaten und Softwareartefakte durch Referenzen auffindbar und zugreifbar gemacht werden.</p> <p>Für die Erhebung wurden alle Beitragskategorien der ECTEL-Hauptkonferenz berücksichtigt. Beiträge zu den Workshops wurden nicht berücksichtigt. Alle Beiträge wurden vom Erstautor daraufhin untersucht, ob ihrem Inhalt Forschungsdaten zugrunde liegen. Als Indikatoren dafür wurde die Forschungsmethodik (sofern beschrieben) auf Tätigkeiten überprüft, bei der Forschungsdaten anfallen. Ferner wurden die textuell beschriebenen Ergebnisse sowie Abbildungen (sofern vorhanden) daraufhin untersucht, ob sie Ausschnitte aus Forschungsdaten oder aggregierte Daten enthalten. Im Ergebnis wurde für jeden Beitrag festgehalten, ob ein unmittelbarer Bezug zu Forschungsdaten vorliegt, wobei ein Bezug zu Softwareartefakten als Informatik-spezifische Form von Forschungsdaten gesondert erfasst wurde.</p> <p>Für alle Beiträge, die Forschungsdaten enthalten wurde geprüft, ob im Beitrag Verweise auf den Veröffentlichungsort der Daten in Form einer URL, einer DOI oder eines Verweises auf eine andere schriftliche Publikation enthalten sind. Im Fall von URLs und DOIs wurde ferner geprüft, ob diese Verweise tatsächlich zu einer zugreifbaren Ressource führen. Bei schriftlichen Publikationen wurde überprüft, ob es eine solche Veröffentlichung gibt. Eine inhaltliche Prüfung der Vollständigkeit oder Qualität der referenzierten Daten wurde in keinem der Fälle vorgenommen. Es wurde allerdings erhoben, ob im Beitrag selbst Informationen dazu gegeben wurde, wenn nur ein Teil der Forschungsdaten über die genannten Referenzen verfügbar war, beispielsweise lediglich ein verwendeter Fragebogen, nicht jedoch alle darüber erhobenen Rohdaten.</p>
CLDF dataset derived from the LSDO's "Chin Dialect Data" from 2019
<p>Cite the source of the dataset as:</p> <blockquote> <p>Language and Social Development Organization (2019): Chin dialect data collection. Yangon: LSDO.</p> </blockquote>
CLDF dataset derived from Chacon et al.'s "Diversity of Arawakan Languages" from 2019
<p>Cite the source of the dataset as:</p> <blockquote> <p>Chacon, T. C.; Gonçalves, A. G.; and da Silva, L. F (2019): A diversidade linguística Aruák no Alto Rio Negro em gravações da década de 1950 [The diversity of Arawakan languages from the upper Rio Negro in recordings from the 1950s]. Forma y Función, 32.2, 41-67. DOI: 10.15446/fyf.v32n2.80814.</p> </blockquote>
ScienceDex guides
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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.