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672 results for “August”
3d model of "The Thinker" by Auguste Rodin
The original scan is made by Musée Rodin over at MyMiniFactory. I needed an embedable link for reseearch purposes. Original Link- Source: Objaverse 1.0 / Sketchfab
HEartS Professional Survey: Charting the effects of COVID-19 on working patterns, income, and well-being among arts professionals in China (October 2020, August 2021)
<p>These data were collected using the HEartS Professional China survey from performing arts workers in China in October 2020 and August 2021. HEartS Professional China is an adaptation of the HEartS Professional surveys which were used in 2020-2021. All the surveys were designed as multi-strategy data collection tools with two main purposes: (1) to chart working patterns, income, sources of support, and indicators of mental and social well-being to identify trends in the effects of the lockdown at the time and (2) to explore the individual work and wellbeing experiences of performing arts professionals in their own words, to identify the subjective effects of lockdown in terms of challenges and opportunities. The survey covers six areas: 1) demographics; (2) information on illness or self-isolation related to COVID-19; (3) work profiles and income; (4) changes to work profiles and income as a result of the pandemic, as well as sources of support; (5) open-response questions about work and wellbeing experiences of lockdown including challenges and opportunities; and (6) validated measures of health, wellbeing, and social connectedness. The HEartS Professional surveys are adaptations of the HEartS Survey which charts the Health, Economic, and Social impacts of the ARTs (<a href="https://doi.org/10.5061/dryad.3r2280gdj">https://doi.org/10.5061/dryad.3r2280gdj</a>).</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 - 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>
Full Data Set of 16814 tweets from 17 different Twitter accounts of Catalonian Public Servants and Delegates collected between August 19 2013 and September 17 2017 in both original language and translated into Spanish later codified under para-diplomacy or nation branding macro-categories. Includes results for each year.
<p>Full Data Set of 16814 tweets from 17 different Twitter accounts of Catalonian Public Servants and Delegates collected between August 19 2013 and September 17 2017 in both original language and translated into Spanish later codified under para-diplomacy or nation branding macro-categories. Includes results for each year out of a significant sample of 1638 tweets.</p>
Brightness data in Rayleigh for OI 630.0 nm (red line) and OI 557.7 (green line) through the night of August 21-22, 2017 obtained using the HiT&MIS from Carbondale, IL
<p>This file contains brightness data in Rayleigh for OI 630.0 nm (red line), OI 557.7 (green line) and NeI 630.5 nm (cloud indicator) through the night of August 21-22, 2017 obtained using the HiT&MIS from Carbondale, IL.</p> <p>This is a python .npz file that contain numpy arrays with uncertainities, so you would need the uncertainties as well as the numpy modules for python.</p> <p>On python it can be opened up as follows:</p> <p>import numpy as np</p> <p>import uncertainties.unumpy as unp</p> <p>dload=np.load("<file location>/eclipse_night_final.npz")#brightnesses are saved as numpy array files<br> int630=dload["int630"] #630 nm red line brightness<br> int557=dload["int557"] #557.7 nm green line brightness<br> int6305=dload["int6305"]# Ne I 630.5 nm brightness for cloud activity<br> time=dload["time"] #capture times (Local times, Central Daylight time)</p> <p># uncertainities can be accessed as</p> <p>b630value=unp.nominal_values(int630) # 630 nm brightnesses values</p> <p>e630=unp.std_devs(int630)# 630 nm uncertainities.</p> <p> </p> <p>please email me at saurav_aryal@student.uml.edu if you have any questions.</p>
Sub-hourly output over Tropical Western Pacific for June, July, August 1997
<p>To evaluate the simulation of deep convection over the Tropical Western Pacific (TWP) in the Canadian Atmospheric Model version 4.3 (CanAM4.3) we compare sub-hourly output against output from the super-parameterized Community Atmospheric Model version 5 (spCAM5). Both models used observed sea-surface temperatures, sea-ice distribution and atmospheric gases and simulated the period January through August, 1997. Model output related to deep convection for CanAM4.3 is saved every 15 minutes over the region bounded by 150 and 170 E and 0 to 10 N while the spCAM5 output was saved every 10 minutes over the same region. The CanAM4.3 data includes results from a single simulation and from a 5 member ensemble of CanAM4.3 simulations.</p> <p><br> <em>Relevant publications:</em></p> <p><br> <strong>Description of CanAM:</strong></p> <p><br> von Salzen, K., Scinocca, J. F., McFarlane, N. A., Li, J., Cole, J. N. S., Plummer, D., Verseghy, D., Reader, M. C., Ma, X., Lazare, M., and Solheim, L.: The Canadian Fourth Generation Atmospheric Global Climate Model (CanAM4). Part I: representation of physical processes. Atmosphere Ocean, 51, 104-125, doi:10.1080/07055900.2012.755610, 2013.</p> <p><strong>Description of CAM5 and spCAM5: </strong></p> <p>Khairoutdinov, M. F. and Randall, D. A.: A cloud resolving model as a cloud parameterization in the NCAR community climate system model: preliminary results. Geophys, Res. Lett., 28: 3617–3620, 2001.</p> <p>Khairoutdinov, M. F. and Randall, D. A.: Cloud resolving modeling of the ARM summer 1997 IOP: Model formulation, results, uncertainties, and sensitivities, J. Atmos. Sci., 60, 607–625, 2003.</p> <p>Neale, R. B., and Coauthors.: Description of the NCAR Community Atmosphere Model (CAM 5.0). NCAR Tech. Note TN-35 486, 274 pp, 2012.</p> <p><strong>Description of simulations and analysis: </strong></p> <p>Mitovski T.,Cole, J. N. S., McFarlane, N. A., von Salzen, K., and Zhang, G. J.: Convective response to large-scale forcing in the Tropical Western Pacific simulated by spCAM5 and CanAM4.3. submitted to GMD, July 2018.</p> <p> </p>
Timelapse of cloud cover during the 21 August 2017 solar eclipse
<p>Timelapse photos of cloud cover during the 21 August 2017 solar eclipse. Location: a small valley in the foothills of the Blue Ridge Mountains, near Charlottesville, VA. Photos were taken using a GoPro camera looking facing approximately SW every 5 seconds between 12:00 - 16:00 EDT (local time).</p>
TESS-AUGUST-2019
<p>Measurements taken by the European Photometer Network (Project STARS4ALL). August 2019</p>
MicroHH LES output for 08 August 2017 over the Southern Great Plains
<p>Data for paper: Improving the Estimate of Higher Order Moments from Lidar Observations Near the Top of the Convective Boundary Layer</p> <div><a href="https://doi.org/10.5194/egusphere-2024-868" target="_blank" rel="noopener">doi: 10.5194/egusphere-2024-868</a></div>
LPL12 - August 2024
<p>Measurements of LPL12 (Ilhas Desertas) in August 2024</p> <p>Madeira</p><p> Light Pollution Laboratorie <a href="https://data.eelabs.eu/api/lpls/LPL12">info</a></p>
LPL8 - August 2024
<p>Measurements of LPL8 (Timanfaya NP) in August 2024</p> <p>Lanzarote</p><p> Light Pollution Laboratorie <a href="https://data.eelabs.eu/api/lpls/LPL8">info</a></p>
LPL5 - August 2024
<p>Measurements of LPL5 (Tejeda) in August 2024</p> <p>Gran Canaria</p><p> Light Pollution Laboratorie <a href="https://data.eelabs.eu/api/lpls/LPL5">info</a></p>
LPL4 - August 2024
<p>Measurements of LPL4 (Ilha do Corvo) in August 2024</p> <p>Corvo</p><p> Light Pollution Laboratorie <a href="https://data.eelabs.eu/api/lpls/LPL4">info</a></p>
LPL12 - August 2024
<p>Measurements of LPL12 (Ilhas Desertas) in August 2024</p> <p>Madeira</p><p> Light Pollution Laboratorie <a href="https://data.eelabs.eu/api/lpls/LPL12">info</a></p>
LPL3 - August 2024
<p>Measurements of LPL3 (Madeira East Coast) in August 2024</p> <p>Madeira</p><p> Light Pollution Laboratorie <a href="https://data.eelabs.eu/api/lpls/LPL3">info</a></p>
LPL1 - August 2024
<p>Measurements of LPL1 (Teide NP) in August 2024</p> <p>Tenerife</p><p> Light Pollution Laboratorie <a href="https://data.eelabs.eu/api/lpls/LPL1">info</a></p>
LPL4 - August 2024
<p>Measurements of LPL4 (Ilha do Corvo) in August 2024</p> <p>Corvo</p><p> Light Pollution Laboratorie <a href="https://data.eelabs.eu/api/lpls/LPL4">info</a></p>
LPL8 - August 2024
<p>Measurements of LPL8 (Timanfaya NP) in August 2024</p> <p>Lanzarote</p><p> Light Pollution Laboratorie <a href="https://data.eelabs.eu/api/lpls/LPL8">info</a></p>
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.