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10,016 results for “Observation”
MESA input/output for Evolutionary and Observational Consequences of Dyson Sphere Feedback
<p>MESA inlists, extras, and output for <a href="https://iopscience.iop.org/article/10.3847/1538-4357/ac3421">Evolutionary and Observational Consequences of Dyson Sphere Feedback,</a> published in the Astrophysical Journal, 2022.</p> <p>Paper DOI: 10.3847/1538-4357/ac3421</p> <p>Files included for Irradiated star experiments (recreating the work of Tout et al. (1989) in MESA) in irradiatedstar.zip:</p> <ul> <li>src/ <ul> <li>run_star_extras.f: MESA extension allowing for a constant temperature bath to irradiate a star.</li> </ul> </li> <li>inlists/ <ul> <li>inlist_zams: Create a zero age main sequence star.</li> <li>inlist_irrad_tams: Evolve a star from ZAMS to TAMS in a constant temperature irradiation bath.</li> <li>inlist_irrad_hefl: Attempt to evolve a star from TAMS to the helium flash in a constant temperature irradiation bath. Note: This model crashes before the helium flash for many parameter choices.</li> </ul> </li> <li>plots/ <ul> <li>tout_recreation_plot.ipynb: Python Jupyter notebook for generating the Figure 1 in the paper.</li> <li>lifetimes.pdf: My MESA recreation of Figure 5 from Tout et al. (1989).</li> </ul> </li> <li>LOGS/ <ul> <li>*_history: MESA output for the evolution of a given stellar mass to a given age in a given temperature bath.</li> </ul> </li> </ul> <p>Files included for Dyson Sphere Feedback experiments in dsfeedback.zip:</p> <ul> <li>src/ <ul> <li>run_star_extras.f: MESA extension allowing for a fraction of a star's luminosity to be dumped back onto the outer layer as extra heat.</li> </ul> </li> <li>inlists/ <ul> <li>inlist_sphere_tams: Evolve a selected model to the end of the main sequence with a given DS feedback fraction.</li> <li>inlist_zams: Create a zero age main sequence star.</li> <li>inlist_zams_lowmass: Create a zero age main sequence star with a timestep limit that helps with lower mass stars.</li> <li>inlist_zamstoage: Evolve a star normally from ZAMS to a selected age (0.6Gyr used here for 2Msun).</li> <li>inlist_zamstosolarage: Evolve a star normally from ZAMS to 4.6 Gyr (used before DS application for 1Msun and lower stars).</li> </ul> </li> <li>plots/ <ul> <li>ds_feedback_plots.ipynb: Python Jupyter notebook for generating the figures 2-9 in the paper.</li> <li>newplots/*: Plots generated from the notebook</li> </ul> </li> <li>LOGS/ <ul> <li>*_history: MESA output for the evolution of a given stellar mass, to a given age, and DS feedback level</li> <li>*_profile: MESA output for the structure of a given stellar mass, at one given age, and DS feedback level</li> </ul> </li> </ul> <p>Email me at mhuston@berkeley.edu if you have any comments or questions!</p> <p>MESA version: 12778</p> <p>MESA SDK version: x86_64-macos-20.4.1</p>
Victorian Water and Climate dataset: long-term streamflow, climate, and vegetation observation records and catchment attributes
<p>This dataset contains streamflow, climate, and vegetation data for 155 minimally impaired catchments in Victoria, Australia. </p> <p>What's included:</p> <p>- Streamflow long-term observation records in daily, monthly, and hydroannual (based on March to February water year) resolution</p> <p>- Catchment climate characteristics in daily, monthly, and hydroannual resolution</p> <p>- Catchment vegetation characteristics in monthly resolution and actual evapotranspiration estimate in monthly and hydroannual resolution</p> <p>- Catchment boundaries</p> <p>- Catchment attributes (topographic, geological, soil, groundwater, vegetation, and human impacts characteristics)</p> <p>- Hydroclimatic characteristics for 3 different periods.</p> <p>Precipitation (p), streamflow (q), and PET (pet) data and their derivatives are in mm (i.e. normalised by catchment area). </p> <p>A paper containing a detailed description of the data including units, data sources, and processing details is submitted, please contact Margarita Saft for a private copy of the draft.</p>
Joint Use of Far-Infrared and Mid-Infrared Observation for Sounding Retrievals: Learning from the Past for Upcoming Far-Infrared Missions
<p>Dataset and software (Matlab) used for the analysis of synoptic weather pattern, information content and retrieval estimates</p>
STROBE checklist for 'Prevalence Rates of Mucopolysaccharidosis in Iraq: a retrospective cross-sectional observational study'
<p>STROBE checklist for ‘Prevalence Rates of Mucopolysaccharidosis in Iraq: a retrospective cross-sectional observational study’</p>
Underlying data for Prevalence Rates of Mucopolysaccharidosis in Iraq: a retrospective cross-sectional observational study
<p>Underlying data for Prevalence Rates of Mucopolysaccharidosis in Iraq: a retrospective cross-sectional observational study</p>
Underlying data for Prevalence Rates of Mucopolysaccharidosis in Iraq: a retrospective cross-sectional observational study
<p>Underlying data for Prevalence Rates of Mucopolysaccharidosis in Iraq: a retrospective cross-sectional observational study</p>
Dataset for "Optimization and Evaluation of Stochastic Unified Convection Using Single-Column Model Simulations at Multiple Observation Sites"
<p>SCAM5 and LES outputs from "Optimization and Evaluation of Stochastic Unified Convection Using Single-Column Model Simulations at Multiple Observation Sites". Includes simulation outputs of stochastic UNICON and original UNICON. The LES intercomparison data of DYCOMSRF01 is available at https://gcss-dime.giss.nasa.gov/pub/DYCOMS-II/GCSS7-RF01/gcss7.nc, and the data of CGILS is available at http://www.atmos.washington.edu/~bloss/CGILS2data.tar.</p>
Data from: Observed and dark diversity dynamics over millennial time scales: Fast-life history traits linked to expansion lags of plants in northern Europe
<p>Global change drivers (e.g. climate and land use) affect the species and functional traits observed in a local site but also its dark diversity—the set of species and traits locally suitable but absent. Dark diversity links regional and local scales and, over time, reveals taxa under expansion lags by depicting the potential biodiversity that remains suitable but is absent locally. Since global change effects on biodiversity are both spatially and temporally scale dependent, examining long-term temporal dynamics in observed and dark diversity would be relevant to assessing and foreseeing biodiversity change. Here, we used sedimentary pollen data to examine how both taxonomic and functional observed and dark diversity changed over the past 14500 years in northern Europe. We found that taxonomic and functional observed and dark diversity increased over time, especially after the Late Glacial and during the Late Holocene. However, dark diversity dynamics revealed expansion lags related to species' functional characteristics (dispersal limitation and stress intolerance) and an extensive functional redundancy when compared to taxa in observed diversity. We highlight that assessing observed and dark diversity dynamics is a promising tool to examine biodiversity change across spatial scales, its possible causes, and functional consequences.</p>
MILAN project: raw images of deep sky objects captured with a Stellina observation station -- [2023-01]
<p>During the MILAN research project (MachIne Learning for AstroNomy), the research team uses Stellina observation stations to collect raw images of deep sky objects. </p> <p>The Stellina observation station has an apochromatic ED doublet with an aperture of 80 mm and a focal length of 400 mm - focal ratio of f/5. It is equipped with a Sony IMX 178 CMOS sensor with a resolution of 6.4 million pixels (3096 x 2080 pixels). An anti-pollution filter is placed in front of the camera sensor. The station also has a fully automated alt-azimuth mount: setup, object tracking and focusing are also automatic. Stellina also has an integrated field rotator that adapts to the target.</p> <p>Thus, the research team built a dataset that faithfully represents what can be obtained during classical Electronically Assisted Astronomy sessions in the Luxembourg Greater Region:<br> - targets: representative set of deep sky objects from the Messier / NGC / IC catalogs during the period.<br> - type of targets: nebulaes, planetary nebula, galaxies, globular clusters, open clusters<br> - for each observation session: sub-frames of 10 seconds exposure time and total cumulative duration of ~15/30 minutes (depending of the target) -- bad sub-frames were not filtered.</p> <p>The dataset is composed of ZIP files -- and each zip file contain raw images in FITS format (Flexible Image Transport System): data come directly from the Sony IMX178 sensor of the Stellina observation station (no debayerisation and no post processing).</p> <p>This research was funded by the Luxembourg National Research Fund (FNR), grant reference 15872557.</p> <p>To refer to or to cite this work, please use: "Parisot, O., Hitzelberger, P., Bruneau, P., Krebs, G., Destruel, C., & Vandame, B. (2023). MILAN Sky Survey, a dataset of raw deep sky images captured during one year with a Stellina automated telescope. Data in Brief, 48, 109133."</p> <p> </p> <p>MILAN project team members: Olivier Parisot (LIST), Patrik Hitzelberger (LIST), Pierrick Bruneau (LIST), Gilles Krebs (VAONIS, Christophe Destruel (VAONIS), Benoît Vandame (VAONIS).</p> <p>More information about the MILAN project: https://www.fnr.lu/results-2021-1-bridges-call/.</p> <p>More information about VAONIS instruments: https://vaonis.com</p> <p>More information about Luxembourg of Science and Technology (LIST): https://www.list.lu</p> <p>Data license for files: Attribution-NonCommercial-NoDerivatives 4.0 International</p>
Underlying data for The impact of COVID-19 severity on pregnancy outcomes among Iraqi women: a retrospective observational study
<p>Underlying data for The impact of COVID-19 severity on pregnancy outcomes among Iraqi women: a retrospective observational study</p>
STROBE checklist for: The impact of COVID-19 severity on pregnancy outcomes among Iraqi women: a retrospective observational study
<p>STROBE checklist for: The impact of COVID-19 severity on pregnancy outcomes among Iraqi women: a retrospective observational study</p>
Underlying data for Evaluation of the antioxidant and anti-inflammatory effect of sublingual glutathione on COPD patients: an observational study
<p>Underlying data for Evaluation of the antioxidant and anti-inflammatory effect of sublingual glutathione on COPD patients: an observational study</p>
Soil moisture observations from shortwave infrared channels reveal tornado tracks: A case in December 10-11, 2021 tornado outbreak
<p>MODIS dataset used for the publication titled 'Soil moisture observations from shortwave infrared channels reveal tornado tracks: A case in December 10-11, 2021 tornado outbreak' on Geophysical Research Letters.</p>
MILAN project: raw images of deep sky objects captured with a Stellina observation station -- [2023-02]
<p>During the MILAN research project (MachIne Learning for AstroNomy), the research team uses Stellina observation stations to collect raw images of deep sky objects. </p> <p>The Stellina observation station has an apochromatic ED doublet with an aperture of 80 mm and a focal length of 400 mm - focal ratio of f/5. It is equipped with a Sony IMX 178 CMOS sensor with a resolution of 6.4 million pixels (3096 x 2080 pixels). An anti-pollution filter is placed in front of the camera sensor. The station also has a fully automated alt-azimuth mount: setup, object tracking and focusing are also automatic. Stellina also has an integrated field rotator that adapts to the target.</p> <p>Thus, the research team built a dataset that faithfully represents what can be obtained during classical Electronically Assisted Astronomy sessions in the Luxembourg Greater Region:<br> - targets: representative set of deep sky objects from the Messier / NGC / IC catalogs during the period.<br> - type of targets: nebulaes, planetary nebula, galaxies, globular clusters, open clusters<br> - for each observation session: sub-frames of 10 seconds exposure time and total cumulative duration of ~15/30 minutes (depending of the target) -- bad sub-frames were not filtered.</p> <p>The dataset is composed of ZIP files -- and each zip file contain raw images in FITS format (Flexible Image Transport System): data come directly from the Sony IMX178 sensor of the Stellina observation station (no debayerisation and no post processing).</p> <p>This research was funded by the Luxembourg National Research Fund (FNR), grant reference 15872557.</p> <p>To refer to or to cite this work, please use: "Parisot, O., Hitzelberger, P., Bruneau, P., Krebs, G., Destruel, C., & Vandame, B. (2023). MILAN Sky Survey, a dataset of raw deep sky images captured during one year with a Stellina automated telescope. Data in Brief, 48, 109133."</p> <p> </p> <p>MILAN project team members: Olivier Parisot (LIST), Patrik Hitzelberger (LIST), Pierrick Bruneau (LIST), Gilles Krebs (VAONIS, Christophe Destruel (VAONIS), Benoît Vandame (VAONIS).</p> <p>More information about the MILAN project: https://www.fnr.lu/results-2021-1-bridges-call/.</p> <p>More information about VAONIS instruments: https://vaonis.com</p> <p>More information about Luxembourg of Science and Technology (LIST): https://www.list.lu</p> <p>Data license for files: Attribution-NonCommercial-NoDerivatives 4.0 International</p>
FIGURE 6 in Metriocnemus erythranthei sp. nov. and Limnophyes viribus sp. nov. (Diptera: Chironomidae: Orthocladiinae): leafminers of monkeyflowers, speedwells, and other herbaceous plants, with new observations on the ecology and habitats of other leaf-mining Chironomidae
FIGURE 6. Metriocnemus eurynotus associated with Impatiens sp. cotyledons. a. cotyledon with mine containing two larvae; b–f. larvae in mines; g. two larvae in mine; h. three larvae in mine; i. two larvae interacting; j. older larvae feeding externally; k. pupa on cotyledon surface; l. reared adult female.
FIGURE 7 in Metriocnemus erythranthei sp. nov. and Limnophyes viribus sp. nov. (Diptera: Chironomidae: Orthocladiinae): leafminers of monkeyflowers, speedwells, and other herbaceous plants, with new observations on the ecology and habitats of other leaf-mining Chironomidae
FIGURE 7. Metriocnemus sp. "Oregon", larva (a–c). a. habitus; b. antenna; c. labrum and premandible; d. mandible; e. mentum; f. posterior portion of the larva.
FIGURE 4 in Metriocnemus erythranthei sp. nov. and Limnophyes viribus sp. nov. (Diptera: Chironomidae: Orthocladiinae): leafminers of monkeyflowers, speedwells, and other herbaceous plants, with new observations on the ecology and habitats of other leaf-mining Chironomidae
FIGURE 4. Metriocnemus erythranthei sp. nov., larvae and leaf mines on Erythranthe spp. (a–d), larvae and mines on Veronica sp. (e–h). a. on E. glabrata; b. on E. guttata; c. on E. moschata (larva establishing new mine); d. on E. moschata; e. larva in newly established leaf mine; f. larva mining leaf; g. larvae in new leaf mines; h. larva in stem mine, with mining in the adjacent petiole.
FIGURE 12 in Metriocnemus erythranthei sp. nov. and Limnophyes viribus sp. nov. (Diptera: Chironomidae: Orthocladiinae): leafminers of monkeyflowers, speedwells, and other herbaceous plants, with new observations on the ecology and habitats of other leaf-mining Chironomidae
FIGURE 12. Secondary inhabitants in leaf mines of Metriocnemus erythranthei on Veronica sp. a., larva of M. eurynotus (upper left) and two larvae of M. erythranthei (center and upper right); b., larva of Limnophyes sp. (prob. L. viribus) (lower left) in vacated mine.
FIGURE 3 in Metriocnemus erythranthei sp. nov. and Limnophyes viribus sp. nov. (Diptera: Chironomidae: Orthocladiinae): leafminers of monkeyflowers, speedwells, and other herbaceous plants, with new observations on the ecology and habitats of other leaf-mining Chironomidae
FIGURE 3. Metriocnemus erythranthei sp. nov., pupa (a–c), larval (d–h). a. frontal apotome; b. abdominal tergites; c. abdominal sternites; d. habitus; e. antenna; f. labrum and premandible; g. mandible; h. mentum.
FIGURE 2 in Metriocnemus erythranthei sp. nov. and Limnophyes viribus sp. nov. (Diptera: Chironomidae: Orthocladiinae): leafminers of monkeyflowers, speedwells, and other herbaceous plants, with new observations on the ecology and habitats of other leaf-mining Chironomidae
FIGURE 2. Metriocnemus erythranthei sp. nov., female (a–d). a. antenna; b. wing; c. genitalia ventral view; d. genitalia, dorsal view.
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.