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77 results for “surface patterns”
Comparison of surface thermal patterns of horses and donkeys in IRT images
<p>The dataset contains infrared thermography (IRT) images of horses and donkeys along with annotations of 15 ROIs corresponding to areas with potential impact of large equine muscles. All animals were healthy and rested. Imaged animals: sixteen horses and eighteen donkeys. Measured animal features such as hair length, and skin thickness are included.</p>
Dataset: Machine Learning Based Prediction of Polaron-Vacancy Patterns on the TiO$_2$(110) Surface
Open the record for dataset details and reuse information.
Data for "Impact of warmer sea surface temperature on the global pattern of intense convection: insights from a global storm resolving model"
<p>Data relevant to a manuscript on X-SHiELD, for submission to GRL.</p>
Data for "Antarctic ice-sheet meltwater reduces transient warming and climate sensitivity through the sea-surface temperature pattern effect"
<p>Data of the Historical Hosing simulations presented in "Antarctic ice-sheet meltwater reduces transient warming and climate sensitivity through the sea-surface temperature pattern effect" submitted to Geophysical Research Letters</p> <p>Authors: Yue Dong, Andrew G. Pauling, Shaina Sadai, Kyle C. Armour </p> <p>Abstract:</p> <p>Coupled global climate models (GCMs) generally fail to reproduce the observed sea-surface temperature (SST) trend pattern since the 1980s. The model-observation discrepancies may arise in part from the lack of realistic Antarctic ice-sheet meltwater imbalance in GCMs. Here we employ two sets of CESM1-CAM5 simulations forced by anomalous Antarctic meltwater fluxes over 1980--2013 and into the 21st century. Both show a reduced global warming rate and an SST trend pattern that better resembles observations. The meltwater drives surface cooling in the Southern Ocean and the tropical southeast Pacific, in turn increasing low-cloud cover and driving radiative feedbacks to become more stabilizing (corresponding to a lower effective climate sensitivity). These feedback changes contribute more than ocean heat uptake efficiency changes in reducing the global warming rate. Accurately projecting historical and future warming thus requires improved representation of Antarctic meltwater and its impacts in models. </p>
Figure 11 in Main Pattern of the Caspian Sea Surface Oil Pollution Revealed by Satellite Data
Figure 11. Main pattern and sources of sea surface oil pollution of the Caspian sea, revealed on the basis of satellite remote sensing data: 1 – Natural leakages of liquid hydrocarbons; 2 – Seabed mud volcanoes; 3 – Natural hydrocarbon seafloor seeps off the Sefid Rud Cape; 4 – Natural hydrocarbon seafloor seeps westward of Cheleken Peninsula; 5 – offshore oil-producing platforms in the Cheleken oil field; 6 – Kashagan oil field; 7 – LUKOIL oil-producing area. Main shipping routes depicted by green lines.
Figure 10 in Main Pattern of the Caspian Sea Surface Oil Pollution Revealed by Satellite Data
Figure 10. Manifestations of the fire aftereffects in satellite images: a) the smoke plume from a burning platform. A part of a color composite (R: 620-670 nm, G: 545-55 nm, B: 459-479 nm) MODIS Aqua image of 8 December 2015, 09:00 UTC; b) sea surface oil pollution caused by the accident at the platform. A part of SAR Sentinal-1A image of 13 December 2015, 14:37 UTC. The area of oil pollution due to the accident is 263 km2.
Figure 9. Fresh oil spill from a in Main Pattern of the Caspian Sea Surface Oil Pollution Revealed by Satellite Data
Figure 9. Fresh oil spill from a moving vessel seen in SAR imagery of the Caspian Sea. SAR Sentinel-1A, 7 June 2019, 14:38 UTC. Length of oil spill - 89 km.
Figure 5 in Main Pattern of the Caspian Sea Surface Oil Pollution Revealed by Satellite Data
Figure 5. Examples of the manifestations of oil slicks from a natural seep on the seafloor in the Cheleken area in satellite images. Parts of SAR-C Sentinel-1A images: a) September 16, 2017, 14:28 UTC; b) July 25, 2018, 14:28 UTC; c) June 8, 2019, 02:36 UTC. Parts of OLI-TIRS Landsat-8 images (color composites of 4, 2 and 1 spectral channels): d) June 28, 2013, 07:09 UTC; e) June 15, 2014, 07:07 UTC; August 14, 2016, 07:13 UTC.
Figure 1 in Main Pattern of the Caspian Sea Surface Oil Pollution Revealed by Satellite Data
Figure 1. Map of the Caspian Sea. Dashed lines indicate the division into Northern, Middle and Southern Caspian.
Рис. 27. Связь степени пигментации PI ΑорсаΛьной поверхности мезосомы Mesobuthus eupeus с коΛичеством особей в посеΛениях (r = 0.854; p <0.05). Fig. 27. Correlation between the degree of pigmentation PI of the dorsal surface of the Mesobuthus eupeus mesosome and the number of specimens in conglomerations (r = 0.854; p <0.05). in Materials on the colour pattern variability of Mesobuthus eupeus (C.L. Koch, 1839) (Arachnida: Scorpiones) in southeastern Shirvan and Gobustan (Eastern Azerbaijan)
Рис. 27. Связь степени пигментации PI ΑорсаΛьной поверхности мезосомы Mesobuthus eupeus с коΛичеством особей в посеΛениях (r = 0.854; p <0.05). Fig. 27. Correlation between the degree of pigmentation PI of the dorsal surface of the Mesobuthus eupeus mesosome and the number of specimens in conglomerations (r = 0.854; p <0.05).
Global pattern formation of net ocean surface heat flux response to greenhouse warming
<p>Datasets used for figures in the following paper.</p> <p>Hu, S., Xie, S. P., and Liu, W. (2020) Global pattern formation of net ocean surface heat flux changes in a warming climate. J. Clim., doi: https://doi.org/10.1175/JCLI-D-19-0642.1.</p>
The Value of Polyp Surface Pattern Recognition in the Identification of Neoplasia: a Prospective Study
ClinicalTrials.gov study NCT01182623. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Relationship Between Initial Plaque Characteristics and Stent Surface Coverage Patterns
ClinicalTrials.gov study NCT01024179. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Data from: Effects of land use, topography, climate and socio-economic factors on geographical variation pattern of inland surface water quality in China
Open the record for dataset details and reuse information.
Modern sedimentation patterns in Lake Issyk Kul (Kyrgyzstan), derived from surface sediment and inlet stream samples
<p>Dataset of surface samples from Lake Issyk Kul, Kyrgyzstan</p>
Dataset - Patterning of the Surface Electrical Potential on Chalcogenide Glasses by a Thermoelectrical Imprinting Process
<p>Dataset related to the article:</p> <p>Patterning of the Surface Electrical Potential on Chalcogenide Glasses by a Thermoelectrical Imprinting Process Ricardo Alvarado, Lara Karam, Redouane Dahmani, Antoine Lepicard, Florian Calzavara, Andréa Piarristeguy, Annie Pradel, Thierry Cardinal, Fréderic Adamietz, Evelyne Fargin, Matthieu Chazot, Kathleen Richardson, Luc Vellutini, Marc Dussauze. The Journal of Physical Chemistry C. 2020, volume 124, issue 42, pp. 23150–23157</p> <p>https://doi.org/10.1021/acs.jpcc.0c06507</p> <p>The data collected correspond to (1) the surface potential measured by KPFM Format: AFM data types</p>
Expression pattern of Pseudomonas aeruginosa biofilm-residing bacteria exposed to gentamicin or surface acoustic waves or gentamicin and surface acoustic waves combined
GEO Series GSE28081. Pseudomonas aeruginosa; Pseudomonas aeruginosa PAO1. 8 samples. Type: Expression profiling by array.
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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.