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586 results for “March”
LPL8 - March 2022
<p>Measurements of LPL8 (Timanfaya NP) in March 2022</p><p>Lanzarote</p><p> Light Pollution Laboratorie <a href="https://data.eelabs.eu/api/lpls/LPL8">info</a></p>
LPL1 - March 2022
<p>Measurements of LPL1 (Teide NP) in March 2022</p><p>Tenerife</p><p> Light Pollution Laboratorie <a href="https://data.eelabs.eu/api/lpls/LPL1">info</a></p>
SG - March 2022
<p>Measurements of SG (Global) in March 2022</p><p></p><p> Light Pollution Laboratorie <a href="https://data.eelabs.eu/api/lpls/SG">info</a></p>
LPL5 - March 2022
<p>Measurements of LPL5 (Tejeda) in March 2022</p><p>Gran Canaria</p><p> Light Pollution Laboratorie <a href="https://data.eelabs.eu/api/lpls/LPL5">info</a></p>
LPL3 - March 2022
<p>Measurements of LPL3 (Madeira East Coast) in March 2022</p><p>Madeira</p><p> Light Pollution Laboratorie <a href="https://data.eelabs.eu/api/lpls/LPL3">info</a></p>
LPL4 - March 2022
<p>Measurements of LPL4 (Ilha do Corvo) in March 2022</p><p>Corvo</p><p> Light Pollution Laboratorie <a href="https://data.eelabs.eu/api/lpls/LPL4">info</a></p>
Biosentiers excursion of the 28th of March, 2018
<p>This short video was captured during an experimental field trip with pupils in Yverdon-les-Bains on the 28th of March, 2018. It shows two pupils using the mobile location-based augmented reality application “BioSentiers”. Following a georeferenced Point of Interest (POI), the pupils approach and find a tree specimen and access biological data on its species. The video the pupils as well as an embedded view of the user interface as they are using the application.<br> <br> The video shows the problem with using location-data on a consumer-grade mobile device: the poor accuracy of the data causes the virtuals objects to drift, jump and sometimes disappear. Because of this, the pupils are forced to interact more with the screen than they may want to, and for non-educational-related purposes.</p>
Pléiades DEM of 23 March 2017 - Khumbu region, Nepal
<p>This digital elevation model (DEM) was generated from a Pléiades stereo acquisition of 23 March 2017. The stereo processing was done using Amses Stereo pipeline. The DEM is posted at a 4 m resolution in UTM45\WGS84.</p>
SPEAR ATS data (March-April)
<p>Data for supporting the finding in the manuscript "Skillful forecasts of springtime CONUS tornado activity up to a year in advance" by Tseng et al. (2022)</p>
March 2018 SAR Greenland
<p>Greenland SAR data corresponding with the iceberg layer. Feel free to use to practice overlaying layers in QGIS.</p>
Lietuvos Respublikos Seimo posėdžių debatų stenogramų tekstynas nuo 1990 m. kovo mėn. 10 d. = Corpus of the Transcripts of the Plenary Debates of the Seimas of the Republic of Lithuania starting from March 10th, 1990
<p>Šiame duomenų rinkinyje kaupiamos Lietuvos Respublikos <strong>Seimo posėdžių debatų stenogramos</strong>. Stenogramos parsiunčiamos automatizuotu būdu iš LR Seimo <a href="https://www.lrs.lt/sip/portal.show?p_r=35727&p_k=1&p_a=sale_ses_pos&p_kade_id=1&p_ses_id=1">portalo</a> ir/arba <a href="https://e-seimas.lrs.lt/portal/documentSearch/lt">paieškos įrankių</a> (abiejų sąrašų įrašai sutikrinami ir sudaromas bendras stenogramų sąrašas (su nuorodomis į šaltinius), kuris pridėtas prie šio duomenų rinkinio). Duomenų rinkinys apima stenogramas <strong>nuo 1990 m. kovo mėn. 10 d.</strong> iki paskutinės pilnos eilinės LR Seimo sesijos. Duomenų rinkinio atnaujinimas vykdomas pasibaigus paskutinei eilinei LR Seimo sesijai.</p> <p>Stenogramos parsiunčiamos DOC/DOCX formatais ir <strong>transformuojamos į TXT bei CSV ir XLSX formatus</strong>:</p> <p>1. Konvertavimas į TXT formatą vykdomas naudojant du įrankius: MultiDoc Converter (www.multidoc-converter.com/en/index.html) ir EmEditor (www.emeditor.com).</p> <p>2. TXT formato stenogramos konvertuojamos į struktūruotus CSV ir XLSX failus naudojant R skriptus, kurie pridedami prie šio duomenų rinkinio.</p> <p>3. Prie duomenų rinkinio pridėtas dokumentas, kuri aprašo CSV ir XLSX failų struktūrą.</p>
Data for continuous and discrete measurements of carbonate parameters in a productive coastal region in the Northwestern Pacific (36°09'13.5''N, 129°24'04.9''E) from January to September in 2019 and from March to December in 2020
<p><span>Photosynthetic organisms shift the dynamics of surface pCO<sub>2</sub> driven by the sea surface temperature change (thermodynamic driver) by assimilating C from seawater. Here we measured net C uptake </span><span>in a macroalgal habitat</span> <span>of coastal Korea for two years (2019–2020) and found that the macroalgal habitat</span> <span>contributed </span><span>5.8 g</span><span> C m</span><sup><span>-</span><span>2</span></sup><span> month</span><sup><span>-</span><span>1</span></sup><span> of </span><span>the net C uptake during the growing period (the cooling period, September</span><span>-</span><span>May). This massive C uptake changed the thermodynamics-driven seasonal dynamics such that the air</span><span>-</span><span>sea equilibrium of </span><span>pCO<sub>2</sub></span><span> was pushed into disequilibrium. T</span><span>he </span><span>surface </span><span>pCO<sub>2</sub></span><span> dynamics during the cooling period were </span><span>mostly influenced by the seasonal decrease in temperature and the proliferation of macroalgae, while the dynamics </span><span>during the warming period </span><span>(the stagnant period, </span><span>June</span><span>-</span><span>August) </span><span>closely followed that predicted based solely on the change in sea surface temperature only </span><span>(thermodynamic driver)</span><span>.</span><span> In contrast to the phytoplankton-dominated offshore waters (where phytoplankton populations are large in spring and summer), the impact of coastal water macroalgae on surface </span><span>pCO<sub>2</sub></span><span> dynamics was most pronounced during the cooling period, when the magnitude of </span><span>pCO<sub>2</sub></span><span> change was as much as twice that resulting from temperature change. Our study shows that</span><span> t</span><span>he distinctive features of the macroalgal habitat—in particular the seasonal temperature extremes (~18°C difference), the </span><span>active macroalgal metabolism,</span><span> and anthropogenic </span><span>nutrient</span><span> inputs—collectively influenced</span><span> the seasonal decoupling of seawater and air </span><span>pCO<sub>2</sub></span><span> dynamics</span><span>.</span></p>
Lowpoly Marching Band Hat (Yellow)
A shako (Marching Band Hat) is a tall, cylindrical military cap, usually with a visor, and sometimes tapered at the top. It is usually adorned with some kind of ornamental plate or badge on the front, metallic or otherwise, and often has a feather, plume, or pompom attached at the top. *1 model (low poly) with textures and materials. Source: Objaverse 1.0 / Sketchfab
Fakenews on 2016 US elections viral tweets (November 2016 - March 2017)
<p>Collection of tweets related to the 2016 US election that went viral between election day (Nov 8th) and March 2017. Viral tweets are those that achieved the 1000-retweet threshold during the collection period. We queried Twitter's streaming API using the hashtags <em>#MyVote2016</em>, <em>#ElectionDay</em>, <em>#electionnight</em>, and the user handles <em>@realDonaldTrump</em> and<em> @HillaryClinton</em>.</p> <p>Tweets have been labelled as containing fake news or not by two sets of people. A fake news is one the following:</p> <ul> <li>Serious fabrication</li> <li>Large-scale hoaxes</li> <li>Jokes taken at face value</li> <li>Slanted reporting of real facts</li> <li>Stories where the 'truth' is contentious</li> </ul>
Joule Heating calculation during St Patrick's day storm of March 2015, using GCMs and Emprirical formulation
<p>This dataset contains globally integrated, and height integrated Joule heating on St Patrick's day storm of March 2015.</p> <p>Date calculated based on Empirical formulations, GITM and TIEGCM driven by two different specifications of high-latitude electric fields, namely the Weimer 2005 and the Assimilative Mapping of Ionospheric Electrodynamics (AMIE) models.</p> <p> </p>
Black Swift Technologies S0 Data from 24 March 2023 Data Collection Mission
<p>The file contains data from the whole flight on 24 March 2023. The part analyzed in the manuscript is near the end of the flight when the S0 was near 10 m altitude. </p> <p> </p> <p>File Contents Include: </p> <p>Format:<br> netcdf4<br>Global Attributes:<br> Conventions = 'CF-1.8, WMO-CF-1.0'<br> wmo__cf_profile = 'FM 303- draft'<br> featureType = 'trajectory'<br> platform_name = ''<br> flight_id = 'P3 Drop Test'<br>Dimensions:<br> obs = 15788<br>Variables:<br> lat <br> Size: 15788x1<br> Dimensions: obs<br> Datatype: single<br> Attributes:<br> standard_name = 'latitude'<br> units = 'degrees_north'<br> axis = 'Y'<br> lon <br> Size: 15788x1<br> Dimensions: obs<br> Datatype: single<br> Attributes:<br> standard_name = 'longitude'<br> units = 'degrees_east'<br> axis = 'X'<br> altitude <br> Size: 15788x1<br> Dimensions: obs<br> Datatype: double<br> Attributes:<br> standard_name = 'altitude'<br> units = 'km'<br> axis = 'Z'<br> positive = 'up'<br> long_name = 'altitude_above_sea_level'<br> time <br> Size: 15788x1<br> Dimensions: obs<br> Datatype: double<br> Attributes:<br> standard_name = 'time'<br> units = 'seconds since 2023-03-24T22:18:57Z'<br> axis = 'T'<br> calendar = 'standard'<br> temp <br> Size: 15788x1<br> Dimensions: obs<br> Datatype: double<br> Attributes:<br> standard_name = 'air_temperature'<br> units = 'K'<br> coordinates = 'lat lon altitude time'<br> dew_point <br> Size: 15788x1<br> Dimensions: obs<br> Datatype: double<br> Attributes:<br> standard_name = 'dew_point_temperature'<br> units = 'K'<br> coordinates = 'lat lon altitude time'<br> rel_hum <br> Size: 15788x1<br> Dimensions: obs<br> Datatype: double<br> Attributes:<br> standard_name = 'relative_humidity'<br> units = '1'<br> coordinates = 'lat lon altitude time'<br> air_press <br> Size: 15788x1<br> Dimensions: obs<br> Datatype: double<br> Attributes:<br> standard_name = 'air_pressure'<br> units = 'Pa'<br> coordinates = 'lat lon altitude time'<br> wind_speed<br> Size: 15788x1<br> Dimensions: obs<br> Datatype: double<br> Attributes:<br> standard_name = 'wind_speed'<br> units = 'm s-1'<br> coordinates = 'lat lon altitude time'<br> wind_dir <br> Size: 15788x1<br> Dimensions: obs<br> Datatype: double<br> Attributes:<br> standard_name = 'wind_from'<br> units = 'degree'<br> coordinates = 'lat lon altitude time'<br> wind_u <br> Size: 15788x1<br> Dimensions: obs<br> Datatype: double<br> Attributes:<br> standard_name = 'x_wind'<br> units = 'm s-1'<br> coordinates = 'lat lon altitude time'<br> wind_v <br> Size: 15788x1<br> Dimensions: obs<br> Datatype: double<br> Attributes:<br> standard_name = 'y_wind'<br> units = 'm s-1'<br> coordinates = 'lat lon altitude time'<br> wind_w <br> Size: 15788x1<br> Dimensions: obs<br> Datatype: double<br> Attributes:<br> standard_name = 'downward_air_velocity'<br> units = 'm s-1'<br> coordinates = 'lat lon altitude time'<br> tsurf <br> Size: 15788x1<br> Dimensions: obs<br> Datatype: double<br> Attributes:<br> standard_name = 'sea_surface_temperature'<br> units = 'degC'<br> coordinates = 'lat lon altitude time'<br> laseralt <br> Size: 15788x1<br> Dimensions: obs<br> Datatype: double<br> Attributes:<br> standard_name = 'laser_height'<br> units = 'm'<br> coordinates = 'lat lon altitude time'<br> long_name = 'laser_height_corrected_with_attitude'</p>
Fig. 14 in New records of rare species in the Mediterranean Sea (March 2021)
Fig. 14: The obtained specimen of H. hygomii (TL = 21 mm) from the Aegean Sea.
Fig. 16 in New records of rare species in the Mediterranean Sea (March 2021)
Fig. 16: Taeniura grabata from Finike Bay, southern coast of Turkey.
Fig. 7 in New records of rare species in the Mediterranean Sea (March 2021)
Fig. 7: Petromyzon marinus from Calabria, Southern Italy.
Fig. 9 in New records of rare species in the Mediterranean Sea (March 2021)
Fig. 9: Specimens of S. viridensis (numbers 1 and 2) and S. sphyraena caught in Tarska Cove.
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.