Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
5
datasets available to search
ShareScore release 0.9.0
Dataset results
5 results for “temperature feature”
Spectrum and Temperature Evolution of Lightning Channel and Dependence on Discharge Feature
<p>Temperature is one of the crucial parameters reflecting the energy and current transfer characteristics in the lightning discharge channel. According to the spectra of eight return strokes recorded simultaneously by two high-speed slitless spectrographs with different time resolutions, the spectral-structure and temperature evolution of the return stroke channels over time was quantitatively analyzed. Different from the previous report, one of the spectrographs has recorded the ionic lines in the spectra within approximately 200 microseconds during the return stroke. The ionic line intensity decayed rapidly with time as the current declined, while the atomic line intensity decreased more slowly. The spectral-structure evolution characteristics indicate that the ionic lines in the spectra existed throughout the discharge current process (including the continuing current (CC) stage). Additionally, it further suggests that the ionic line intensities are associated with the discharge currents and that their radiation mechanism is closely related to the collision excitation under the action of strong currents. The temperature calculated using the ionic lines can reflect the thermodynamic properties of the current-carrying channel. The temperature calculated using atomic lines is significantly lower than that calculated using the ionic lines in the same spectrum. The radiation mechanism of the atomic lines differs from that of the ionic lines. Compared with the decay of the ionic-line intensity, the decline of the channel temperature is slower, and there is even a slight increase in the CC stage. This property reflects the effect of the current action integral.</p>
Spectrum and Temperature Evolution of Lightning Channel and Dependence on Discharge Feature
<p>Temperature is one of the crucial parameters reflecting the energy and current transfer characteristics in the lightning discharge channel. According to the spectra of eight return strokes recorded simultaneously by two high-speed slitless spectrographs with different time resolutions, the spectral-structure and temperature evolution of the return stroke channels over time was quantitatively analyzed. Different from the previous report, one of the spectrographs has recorded the ionic lines in the spectra within approximately 200 microseconds during the return stroke. The ionic line intensity decayed rapidly with time as the current declined, while the atomic line intensity decreased more slowly. The spectral-structure evolution characteristics indicate that the ionic lines in the spectra existed throughout the discharge current process (including the continuing current (CC) stage). Additionally, it further suggests that the ionic line intensities are associated with the discharge currents and that their radiation mechanism is closely related to the collision excitation under the action of strong currents. The temperature calculated using the ionic lines can reflect the thermodynamic properties of the current-carrying channel. The temperature calculated using atomic lines is significantly lower than that calculated using the ionic lines in the same spectrum. The radiation mechanism of the atomic lines differs from that of the ionic lines. Compared with the decay of the ionic-line intensity, the decline of the channel temperature is slower, and there is even a slight increase in the CC stage. This property reflects the effect of the current action integral.</p>
Temporal Evolution Feature on Spectrum and Temperature of Lightning return stroke Channel
<p>Temperature is one of the crucial parameters reflecting the energy and current transfer characteristics in the lightning discharge channel. According to the spectra of eight lightning return strokes recorded simultaneously by two high-speed slitless spectrographs with different time resolutions, the spectral-structure and temperature evolution of the return stroke channels over time was quantitatively analyzed. Different from the previous report, one of the spectrographs have recorded the ionic lines in the spectra within approximately 200 microseconds during the return stroke. The ionic line intensity decayed rapidly with time as the current declined, while the atomic line intensity decreased more slowly. The spectral-structure evolution characteristics indicate that the ionic lines in the spectra existed throughout the discharge current process (including the continuing current (CC) stage). Additionally, it further suggests that the ionic line intensities are associated with the discharge currents and that their radiation mechanism is closely related to the collision excitation under the action of strong currents. The temperature calculated by the ionic lines can reflect the thermodynamic properties of the current-carrying channel. The temperature calculated using atomic lines is significantly lower than that calculated by the ionic lines in the same spectrum. The radiation mechanism of the atomic lines differs from that of the ionic lines. Compared with the decay of the ionic-line intensity, the decline of the channel temperature calculated by ionic lines is slower. The temperature calculated by atomic lines shown the similar feature, and it is even basically unchanged in the CC stage. This property reflects the persistent heating effect of the current.</p>
Machine Learning Framework for High-Resolution Air Temperature Downscaling Using LiDAR-Derived Urban Morphological Features
<p>This dataset supports the study titled <em>"Machine Learning Framework for High-Resolution Air Temperature Downscaling Using LiDAR-Derived Urban Morphological Features"</em>, published in <em>Urban Climate</em> (<a href="https://doi.org/10.1016/j.uclim.2024.102102" target="_new" rel="noopener">DOI: 10.1016/j.uclim.2024.102102</a>).</p> <p> </p> <p><strong>Content Overview:</strong></p> <ul> <li> <p><strong>Building Label Data for Footprint Detection</strong>:</p> <ul> <li><em>Amsterdam_BDG_Label.rar</em></li> <li><em>MiamiDade_BDG_Label.rar</em></li> </ul> <p>These are the label datasets used for training the building detection segmentation models. They have been instrumental in accurately detecting building footprints in Amsterdam.</p> </li> <li> <p><strong>Amsterdam_3D_Buildings.rar</strong>: CityGML file of 3D building models for Amsterdam, derived from LiDAR data and U-Net3+ model.</p> </li> </ul> <ul> <li> <p><strong>Morphological Features.rar</strong>: Contains urban morphological features (in raster format) extracted from LiDAR data used in the study.</p> </li> <li> <p><strong>Training and Test Data for Air Temperature Estimation</strong>:</p> <ul> <li><em>Train_Test_AvgTemp_Amsterdam.rar</em></li> <li><em>Train_Test_MaxTemp_Amsterdam.rar</em></li> <li><em>Train_Test_MinTemp_Amsterdam.rar</em></li> </ul> <p>This dataset includes training and testing data for estimating air temperatures in three scenarios: average daily temperature, minimum daily temperature, and maximum daily temperature for the city of Amsterdam.</p> </li> </ul>
Supporting video for "Temperature Modulated Micromechanical Thermal Analysis with Microstring Resonators Detects Multiple Coherent Features of Small Molecule Glass Transition"
<p>Supporting video for "Temperature Modulated Micromechanical Thermal Analysis with Microstring Resonators Detects Multiple Coherent Features of Small Molecule Glass Transition" . 720p Version. </p>
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.