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181 results for “Aurorae”
Aurora SDG Research Dashboard and Classifier - Instructions Videos
<p>Instruction videos about the Aurora SDG Research Dashboard, SDG Classifier, Badges and API.</p><p><a href="https://zenodo.org/doi/10.5281/zenodo.10040524">Also read the User Guides</a>.</p>
Upward, MeV-class electron beams over Jupiter's Main Aurora; Selected data for
<p>This submission provides selected ASCII data that is utilzed in a scientific study entitled: "Upward, MeV-class electron beams over Jupiter’s Main Aurora". A PDF of the manuscript is included here. The 13 authors of this study are identified in the PDF manuscirpt. The data files are labeled according to the figure numbers and panels used in the manuscript. The PDF of the paper serves to document the qualities of the data submitted. The abstract of the manuscript is as follows: </p> <p>Abstract: Jupiter’s poleward (Zone II) main aurora exhibits bi-directional electron acceleration; upward acceleration dominates but downward acceleration generates strong aurora. During Juno’s first perijove (PJ1), the upward acceleration manifested as narrow electron angular beams (within ~5 of the magnetic field) over the 30-1200 keV energy range of Juno’s Jupiter Energetic Particle Detector Investigation (JEDI). These beams can be simply connected (non-uniquely) to >10 to perhaps 100’s of MeV electrons that penetrated the radiation shielding of the camera head of the Magnetometer Investigation’s Advanced Stellar Compass (ASC). The most intense of those multiple MeV populations are shown to have been highly directional and propagating upwards. How auroral processes generate such beams is unknown. With azimuthal symmetry assumed (not demonstrated here), these beams provided >1026 s-1 of >30 keV electrons to Jupiter’s vast magnetosphere, a possibly critical and dominating source of energetic electrons to that region and ultimately to Jupiter’s radiation belts.</p>
Kinetochore life histories reveal an Aurora B dependent error correction mechanism in anaphase
<p>Dataset of kinetochore tracks in human RPE1 cells showing chromosome dynamics and segregation from prometaphase through to anaphase as described in detail in Sen, Harrison, Burroughs and McAinsh, 2021, https://doi.org/10.1101/2021.03.30.436326 Tracks correspond to 3D time-lapse movies of Ndc80-eGFP and were acquired in the 488nm channel using 1\% laser power, 50 ms exposure time/z-plane, 93 z-planes, 307 nm z-step, which results in 4.7 s/z-stack time frame. Cells are subject to nocodazole arrest-and-release or equivalent treatment with DMSO as indicated in the folder names, and some cells are subject to additional treatment with ZM to inhibit Aurora B (also indicated in folder names). Tracks were produced using kinetochore tracking software, KiT v2.3 (see Armond et al., 2016, Bioinformatics), available from https://github.com/cmcb-warwick/KiT/ </p>
ACCESS-AM2 model output for 2017-2018 MARCUS and 2018-2019 CAMMPCAN RSV Aurora Australis voyages
<p>The dataset includes model output from the ACCESS-AM2 model corresponding to the MARCUS (Measurements of Aerosols, Radiation and Clouds over the Southern Oceans) 2017-2018 voyages and the CAMMPCAN (Chemical and Mesoscale Mechanisms of Polar Cell Aerosol Nucleation) 2018-2019 voyages. The MARCUS voyages included a limited number of CAMMPCAN instruments while the CAMMPCAN voyages included the full suite of instruments. </p> <p>The model version used was ACCESS-AM2 (Australian Community Climate and Earth-System Simulator - Atmospheric Model Version 2) run with CMIP6 AMIP configuration, nudged with ERA5 reanalysis and full chemistry switched on. The model was configured with a horizontal resolution of 1.25◦ latitude and 1.875◦ longitude and 85 vertical levels. ACCESS-AM2 uses the UK Met Office’s Unified Model Global Atmosphere (UM10.6 GA7.1) as the atmosphere module, the Community Atmosphere Biosphere Land Exchange model version 2.5 (CABLE2.5) as the land-surface module and the Global Model of Aerosol Processes (GLOMAP-mode) as the aerosol module. More information on the ACCESS-AM2 model can be found at <a href="https://doi.org/10.1071/ES19033">https://doi.org/10.1071/ES19033</a>.</p> <p>The data is at daily means spanning 29-10-2017 to 26-03-2018 (149 days) for MARCUS, and 25-10-2018 to 24-03-2019 (151 days) for CAMMPCAN.</p> <p>Files included in this upload include:</p> <ul> <li>aa1718_cg893_track.nc: aerosol, chemistry, and meteorology model data for the MARCUS voyages</li> <li>cg893_daily_mean_MARCUS_size_distributions.nc: calculated aerosol size distribution model data for the MARCUS voyages </li> <li>aa1819_cg893_track.nc: aerosol, chemistry, and meteorology model data for the CAMMPCAN voyages</li> <li>cg893_daily_mean_CC_size_distributions.nc: calculated aerosol size distribution model data for the CAMMPCAN voyages</li> </ul> <p>File names refer to Aurora Australis, voyage years (either 2017-2018 or 2018-2019), followed by the model run and data type.</p> <p>An overview of the variable field names, variable long names, height profile availability and units available in the dataset is provided in VariablesOverview.xlsx. </p> <p>A Jupyter Notebook is also included and contains scripts that can be used to create figures for preliminary analysis using the model data.</p> <p>Additional information:</p> <ul> <li>MARCUS details: <a href="https://asr.science.energy.gov/meetings/stm/presentations/2017/473.pdf">https://asr.science.energy.gov/meetings/stm/presentations/2017/473.pdf</a></li> <li>CAMMPCAN details: <a href="https://findanexpert.unimelb.edu.au/project/102792-cammpcan-%E2%80%93-chemical-and-mesoscale-mechanisms-of-polar-cell-aerosol-nucleation">https://findanexpert.unimelb.edu.au/project/102792-cammpcan-%E2%80%93-chemical-and-mesoscale-mechanisms-of-polar-cell-aerosol-nucleation</a></li> <li>MARCUS Observations: <a href="https://doi.org/10.26179/5e54ab5e5d56f">https://doi.org/10.26179/5e54ab5e5d56f</a></li> <li>CAMMPCAN Observations: <a href="https://doi.org/10.26179/5e546f452145d">https://doi.org/10.26179/5e546f452145d</a> </li> </ul> <p>The GitHub repository containing the code used to produce these datasets can be found here: <a href="https://github.com/llamprey/aurora_voyages">https://github.com/llamprey/aurora_voyages</a></p> <p> </p> <p>Versions:</p> <p>1.0.0: Initial Version.</p> <p>1.1.0: Fixed bug where CN and CCN fields were incorrectly calculated.</p> <p>1.2.0: Updated aerosol size distribution files</p>
Aurorasaurus Real-Time Citizen Science Aurora Data
<p>Aurorasaurus citizen science data is a collection of auroral sightings submitted to the project via its website (aurorasaurus.org) or apps and mined from social media. It is a robust data set and particularly abundant during strong geomagnetic storms. This data is offered to the scientific community for research use through an open-access database in its raw and scientific formats for the 2015-2016 period, each of which is described in detail in the following technical report:</p> <p>Kosar, B. C., MacDonald, E. A., Case, N. A., & Heavner, M. (2018). Aurorasaurus Database of Real‐Time, Crowd‐Sourced Aurora Data for Space Weather Research. <em>Earth and Space Science</em>, <em>5</em>(12), 970-980.</p> <p>For more information on the project, please contact the project leaders at aurorasaurus.info@gmail.com.</p> <p> </p>
Dataset: Aurora Cannabis Inc. (ACB) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Dataset: Aurora Innovation, Inc. (AUR) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Dataset: Aurora Innovation, Inc. (AUROW) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Dataset: Aurora Cannabis Inc. (ACB) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Dataset: Aurora Mobile Limited (JG) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Single molecule data for unphosphorylated Aurora-A (Gilburt et al, Chemical Science 2019)
<p>Raw and partially processed single molecule intensity histogram and dwell time histogram data for the following publication:</p> <p>James A H Gilburt, Paul Girvan, Julian Blagg, Liming Ying, Charlotte A Dodson (2019) Ligand discrimination between active and inactive activation loop conformations of Aurora-A kinase is unmodified by phosphorylation. Chemical Science. DOI: 10.1039/c8sc03669a</p> <p><strong><em>Please cite our publication in any use of this data.</em></strong></p> <p> </p>
Aurora Subglacial Basin GlaDs inputs, outputs and geophysical data
<p>The GlaDS_ASB_outputs.txt file includes the following:</p> <p>Glacier Drainage System (GlaDS) model inputs: node easting (m), node northing (m), bed elevation (m), ice thickness (m), basal velocity (m/year) and basal water production (m/year). GlaDS model results for water pressure as a fraction of overburden (Pw/Pi) and water depth (m):base line model, high conductivity, low conductivity, static water and static velocity model runs. </p> <p>Specularity content data for Aurora Subglacial Basin as an xyz file called: filtered.spec.asb.xyz with easting (m), northing (m) and specularity content. </p> <p>The ICECAP basal interface specularity content profiles can also be found at the U.S Antarctic Program (USAP) Data Center: <a href="https://doi.org/10.15784/601371">https://doi.org/10.15784/601371</a></p>
AURORA Energy Tracker App Dashboard on 9 September 2024
<p>Snapshots of the AURORA Energy Tracker dashboard, showing data collected on 9 September 2024 regarding average user, energy labels and gender distribution.</p> <p>The dashboard is available at https://dashboard.aurora-h2020.eu/en-GB and shows data from 6 February 2024. Note that AURORA is an ongoing citizen science project and the data on this page is provided without guarantee.</p>
Multicolored aurora in Iceland, by Marco Migliardi on behalf of Associazione Astronomica Cortina, Italy
<p>First place in the 2021 IAU OAE Astrophotography Contest, category Aurorae (still images)</p> <p>Aurorae are the result of ionisation and excitation processes in Earth's upper atmosphere, caused by charged particles from the solar wind or from coronal mass ejections. The different colours in an aurora display indicate the species of atmospheric atoms and molecules involved. The most common colour is a bright green, which, together with deep red, originates from atomic oxygen. Blue, purple and pink hues are much rarer and originate from molecular nitrogen. The reflection of the aurora in the water indicates the brightness of intense aurorae at higher latitudes.</p> <p>Credit: Marco Migliardi on behalf of Associazione Astronomica Cortina/IAU OAE.</p>
Iceland aurora, by Emanuele Balboni, Italy
<p>Third place in the 2021 IAU OAE Astrophotography Contest, category Aurorae (still images)</p> <p>The blurred motions of the aurora caught during the exposure time of this photograph beautifully illustrate its dynamic nature. While certain forms of aurorae, like homogeneous arcs and bands or diffuse glows, can remain static for hours, others, like rayed arcs or bands (also called "curtains"), can change within seconds in shape and brightness.</p> <p>Credit: Emanuele Balboni/IAU OAE</p>
Figs. 134–139. Lacvietina aurora. 134. Aedeagus, ventral. 135. Aedeagus, lateral. 136 in Revision of the Asian Tribe Megarthropsini (Coleoptera: Staphylinidae: Tachyporinae)
Figs. 134–139. Lacvietina aurora. 134. Aedeagus, ventral. 135. Aedeagus, lateral. 136. Tergum VIII, apex, male (setae omitted). 137. Sternum VIII, male. 138. Sternite VII, male. 139. Sternite VI, male.
Figs. 140–146. Lacvietina aurora. 140. Tergum VIII, female. 141. Sternum VIII, female. 142. Spermatheca. 143 in Revision of the Asian Tribe Megarthropsini (Coleoptera: Staphylinidae: Tachyporinae)
Figs. 140–146. Lacvietina aurora. 140. Tergum VIII, female. 141. Sternum VIII, female. 142. Spermatheca. 143. Elytron, apical margin, left (setae omitted). 144. Tergites IX and tergum X, female. 145. Segment IX, ventral, female. 146. Mesosternum and metasternum.
Aurora A and cortical flows promote polarization and cytokinesis by inducing asymmetric ECT-2 accumulation - Data Archive
<p>This archive contains all the images and raw data generated for: Katrina M Longhini & Michael Glotzer, “Aurora A and cortical flows promote polarization and cytokinesis by inducing asymmetric ECT-2 accumulation”</p> <p>The data is organized by figure then experiment. Each embryo folder contains formatted embryos, which are rotated, cropped, and photobleach corrected. Each recording starts at time 0 on the respective graph.</p> <p>The “AccumulationDataNew” files contain all the data generated from the “3pixel_membranefinder_w_dir.ijm” and “membrane_ROI_TimeSeries_max_scaled_dirs.ijm” scripts organized in a Tidy format generated in R using the first portion of the script “Edited_Membrane_Accumulation_Line_Script.Rmd”. These Fiji and R Markdown scripts are located in the “Analysis Scripts“ folder.</p> <p>All data visualization scripts are included in the “Analysis Scripts” folder.</p> <p>Sequences of plasmids generated for this paper are located in the “Plasmid Sequences” folder.</p>
"Aurora" statue
"Aurora" statue at the Sceaux park, France. Sculpture by René Letourneur in 1949-1950. Photogrammetry made with RealityCapture 1.2 Source: Objaverse 1.0 / Sketchfab
Aurora Drive Drone and iPhone Video
Created in RealityCapture from 459 images. 200 images from a dji drone and the remainder came from iphone 12 pro max 4k video converted to still png's Source: Objaverse 1.0 / Sketchfab
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International Brain Laboratory public data
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OpenNeuro
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