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.
3,264
datasets available to search
ShareScore release 0.9.0
Dataset results
3,264 results for “FAST”
Figs 117-122 in The fast-running flies (Diptera, Hybotidae, Tachydromiinae) of Singapore and adjacent regions
Figs 117-122. Elaphropeza bicaudata (Melander, 1928). 117. antenna, ♂, lateral view. 118. cerci, lateral view. 119. epandrium and cerci, dorsal view. 120. left surstylus, lateral view. 121. ♀ ovipositor, lateral view. 122. hind femur and tibia, ♂, anterior view. Scale bar= 0.1 mm (after Shamshev & Grootaert 2007).
Figs 144-147 in The fast-running flies (Diptera, Hybotidae, Tachydromiinae) of Singapore and adjacent regions
Figs 144-147. Elaphropeza lowi sp. nov., ♂. 144. postpedicel and stylus of antenna, lateral view. 145. right epandrial lamella, lateral view. 146. epandrium with cerci, dorsal view. 147. left surstylus, lateral view.
Figs 140-143 in The fast-running flies (Diptera, Hybotidae, Tachydromiinae) of Singapore and adjacent regions
Figs 140-143. Elaphropeza gohae sp. nov., ♂. 140. postpedicel and stylus of antenna, lateral view. 141. right epandrial lamella and cerci, lateral view. 142. epandrium with cerci, dorsal view. 143. left surstylus, lateral view.
Figs 136-139 in The fast-running flies (Diptera, Hybotidae, Tachydromiinae) of Singapore and adjacent regions
Figs 136-139. Elaphropeza chanae sp. nov., ♂. 136. postpedicel and stylus of antenna, lateral view. 137. right epandrial lamella, lateral view. 138. epandrium with cerci, dorsal view. 139. left surstylus, lateral view.
Figs 156-160 in The fast-running flies (Diptera, Hybotidae, Tachydromiinae) of Singapore and adjacent regions
Figs 156-160. Elaphropeza semakau sp. nov., ♂. 156. postpedicel and stylus of antenna, lateral view. 157. right epandrial lamella, lateral view. 158. epandrium with cerci, dorsal view. 159. left surstylus, lateral view. 160. tip of hypandrium, ventral view.
Figs 152-155 in The fast-running flies (Diptera, Hybotidae, Tachydromiinae) of Singapore and adjacent regions
Figs 152-155. Elaphropeza feminata Shamshev & Grootaert, 2007, ♂. 152. postpedicel and stylus of antenna, lateral view. 153. right epandrial lamella, lateral view. 154. epandrium with cerci, dorsal view. 155. left surstylus, lateral view. (after Shamshev & Grootaert 2007).
Figs 55-57 in The fast-running flies (Diptera, Hybotidae, Tachydromiinae) of Singapore and adjacent regions
Figs 55-57. Chersodromia malaysiana sp. nov., ♂ terminalia. 55. right epandrial lamella, lateral view. 56. epandrium and cerci, dorsal view. 57. left surstylus, lateral view.
Dataset From: Measuring slow heteroaggregation rates in the presence of fast homoaggregation
<p>The dataset for the publication "Measuring slow heteroaggregation rates in the presence of fast homoaggregation". DOI: 10.1016/j.jcis.2020.01.075.</p> <p>Files containing data have .dat extension and are in text format.</p>
Vacuum Rabi splitting of a dark plasmonic cavity mode revealed by fast electrons_exterimental dataset
<p>This file contains the raw unprocessed experimental data for the results published in Ora Bitton et al., Vacuum Rabi splitting of a dark plasmonic cavity mode revealed by fast electrons, <em>Nat Commun</em> <strong>11, </strong>487 (2020). </p>
fish swimming fast
Drawing uploaded to scidraw.io on: 17 August 2019
fish swimming fast
Drawing uploaded to scidraw.io on: 17 August 2019
Datasets used in "Fast phylogenetic inference from typing data"
<p>Real datasets used in the paper "<a href="https://doi.org/10.1186/s13015-017-0119-7">Fast phylogenetic inference from typing data</a>", by João A Carriço, Maxime Crochemore, Alexandre P Francisco, Solon P Pissis, Bruno Ribeiro-Gonçalves, and Cátia Vaz, Algorithms for Molecular Biology 13 (1), 1-14, 2018. Check the paper for more information on the datasets.</p>
Supplementary material 2 from: Buzan E, Potušek S, Urzi F, Pokorny B, Šprem N (2020) Genetic characterisation of wild ungulates: successful isolation and analysis of DNA from widely available bones can be cheap, fast and easy. ZooKeys 965: 141-156. https://doi.org/10.3897/zookeys.965.54862
Microsatellite loci for muscle tissue samples and recent bone samples
Figure 1 from: Buzan E, Potušek S, Urzi F, Pokorny B, Šprem N (2020) Genetic characterisation of wild ungulates: successful isolation and analysis of DNA from widely available bones can be cheap, fast and easy. ZooKeys 965: 141-156. https://doi.org/10.3897/zookeys.965.54862
Figure 1 Micro-locations of sampling bone material for DNA isolation (see arrows) A roe deer mandibles B ethmoid bone of chamois C wild boar mandible D chamois skull.
Supplementary material 1 from: Buzan E, Potušek S, Urzi F, Pokorny B, Šprem N (2020) Genetic characterisation of wild ungulates: successful isolation and analysis of DNA from widely available bones can be cheap, fast and easy. ZooKeys 965: 141-156. https://doi.org/10.3897/zookeys.965.54862
Tables S1–S4
Data Augmentation at the LHC through Analysis-specific Fast Simulation with Deep Learning: W+jet training/test dataset
<p>W+jet events at generator and reconstruction level, used to train analysis-specific generative models.</p> <p>Events are represented as an array of relevant high-level features. Reco objects are matched to Gen objects and a minimal selection is applied to define the generator support in the N-dim space identified by the input features.</p> <p>About 2M events, used for training/validation/testing</p> <p>Details in https://arxiv.org/abs/2010.01835</p>
Fast saccadic eye-movements in humans suggest that numerosity perception is automatic and direct.
<p><span>Fast saccades are rapid automatic oculomotor responses to salient and ecologically important visual stimuli such as animals and faces. Discriminating the number of friends, foe or prey may also have an evolutionary advantage. In this study participants were asked to saccade rapidly towards the more numerous of two arrays. Participants could discriminate numerosities with high accuracy and great speed, as fast as 190 ms. Intermediate numerosities were more likely to elicit fast saccades than very low or very high numerosities. Reaction-times for vocal responses (collected in a separate experiment) were slower, did not depend on numerical range, and correlated only with the slow, not the fast saccades, pointing to different systems. The short saccadic-reaction times we observe are surprising given that discrimination using numerosity estimation is thought to require a relatively complex neural circuit, with several relays of information through parietal and pre-frontal cortex. Our results suggest that fast numerosity-driven saccades may be generated on a single feed-forward pass of information recruiting a primitive system that cuts through the cortical hierarchy and rapidly transforms the numerosity information into a saccade command.</span></p>
kezhoulumelody/WC_Response_Data: Mechanisms of Fast Walker Circulation Response to CO2 Forcing - Data
<p>Data share</p>
Fast Fashion Eco Commitment Dataset
<p>This dataset contains intormation on prices, composition and "eco tagging" (i.e. being marketed as an eco friendly product) for 277 items in the Spanish Zara catalogue (Inditex group) as retrieved from their webside on 2020-11-07. Further, the dataset is structured in two dimensions:</p> <p>Items Dimension (on row per item):</p> <ul> <li> <p>'item_code': primary key. Numeric code assigned to each clothin item</p> </li> <li> <p> 'item_name': str, name of the item.</p> </li> <li> <p>'item_desc': str, description of the item.</p> </li> <li> <p>'join_life': bool, weather or not the item is eco-tagged</p> </li> <li> <p>'joinlife_title': str, ecologic marking</p> </li> <li> <p>'joinlife_desc': str, description of the ecologic action taken</p> </li> <li> <p>'item_price': num, price of the item in cents of €</p> </li> </ul> <p> </p> <p>Composition Dimension (one row per clothing material):</p> <ul> <li> <p>'item_code': int, foreign key to merge with Items Dimention</p> </li> <li> <p>'part_name': str, part of the clothing item (e.g. Inside/Outside)</p> </li> <li> <p>'material': str, name of the material.</p> </li> <li> <p>'percent': srt, percentage of the material realtive to the clothing part.</p> </li> </ul> <p> </p> <p>Disclaimer: This dataset was created within the framework of Univeristat Oberta de Catalunya's Msc in Data Science as a research project and its purpose is purely educational.</p>
Slab dehydration in Sumatra: Implications for fast and slow earthquakes and arc magmatism
<p>The catastrophic 2004 Sumatra-Andaman Mw9.1 earthquake associated with destructive tsunamis has characterized Sumatra as one of the most dangerous convergence zones. Nevertheless, the effects of the thermohydrous state on the strongly coupled megathrust of the incoming plate remain enigmatic. By using a 3-D thermomechanical model to compute the temperature variation and the complicated phase transition process of the water-bearing descending plate which generates unstable thrust slips, we find that Sumatran earthquakes at varying depths are likely under the control of the inter- or intraplate hydrothermal regime, which occurs in or close to the petrological metamorphism transition area. The slab dehydration of the water-rich mid-ocean-ridge basalts (MORB) and the ultramafic rocks in the oceanic lithosphere releases a large amount of fluid to the continental wedge and further facilitates arc magmatism. The fluids are prone to upwelling following the subduction channel along the plate interface and thus contribute to the clustering of earthquakes updip of the dehydration front beneath offshore Sumatra. Brittle failure and dehydration embrittlement at depth, along with the temperature differences caused by variant slab geometry, are conjectured to greatly influence the occurrence of fast and slow earthquakes in Sumatra.</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.