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Lithium-Ion Batteries in Automated Guided Vehicles (AGVs) dataset for article "Automated Battery Power Fade Estimation for Fast Charge and Discharge Operations"
<p>Dataset of aggregated information related to discharge-only cycles of lithium-ion battery packs employed in Automated Guided Vehicle systems.</p> <p>The dataset supports the study in conference article "Automated Battery Power Fade Estimation for Fast Charge and Discharge Operations"</p>
Fast Method for Calibrated Self-Discharge Measurement of Lithium-Ion Batteries including Temperature Effects and Comparison to Modelling
<p>Self-discharge data related to the manuscript entitled: 'Fast Method for Calibrated Self-Discharge Measurement of Lithium-Ion Batteries including Temperature Effects and Comparison to Modelling', submitted to Energy Reports on 26 April 2023.</p>
Supplementary Data: Fast and accurate AMS-02 antiproton likelihoods for global dark matter fits
<p>The files in this record contain supplementary data for the study, "Fast and accurate AMS-02 antiproton likelihoods for global dark matter fits". Samples have been created using <a href="https://gambitbsm.org/" target="_blank" rel="noopener">GAMBIT</a> and figures can be reproduced with <a href="http://github.com/patscott/pippi" target="_blank" rel="noopener">pippi</a>.</p>
Nuclear Data Uncertainty Propagation for the Molten Salt Fast Reactor Design (dataset)
<p>This repository contains the dataset, post-processing script and models needed to reproduce the results presented in the article "Nuclear Data Uncertainty Propagation for the Molten Salt Fast Reactor Design", published in the special issue of Nuclear Science and Engineering dedicated to the 1st Young Molten Salt Reactor Conference (held in Lecco in June 6th and 9th 2022).</p> <p>The dataset includes:</p> <ul> <li>the perturbed nuclear data files (in ACE and ENDF-6 formats) generated with the open-source, python package <a href="https://github.com/luca-fiorito-11/sandy">SANDY</a> and processed with the processing code <a href="https://github.com/njoy">NJOY</a> by using the <a href="https://github.com/nicoloabrate/ndl">NDL</a> code.</li> <li>the <a href="https://serpent.vtt.fi/serpent/">Serpent 2</a> Monte Carlo calculations for two models of the Molten Salt Fast Reactor design, conceived during the <a href="http://samofar.eu/">SAMOFAR</a> EU project</li> </ul> <p>The python scripts include pre- and post-processing tools used to generate the perturbed data and to analyse the Serpent 2 output.</p>
Voltage-based strategies for preventing battery degradation under diverse fast-charging conditions
<p>Here are the simulated datasets for the work 'Voltage-based strategies for preventing battery degradation under diverse fast-charging conditions', published in ACS Energy Letters, September 2023. The utilization of these datasets is demonstrated in the associated GitHub project folder https://github.com/zachkonz/Voltage-based-plating-prevention.</p>
Figs 3-6 in The fast-running flies (Diptera, Hybotidae, Tachydromiinae) of Singapore and adjacent regions
Figs 3-6. Elaphropeza biuncinata (Melander, 1928). 3. head, ♂, lateral view. 4. head, ♂, frontal view. 5. Platypalpus sp. scutum dorsal view. 6. E. biuncinata thorax, lateral view.
Fig. 237 in The fast-running flies (Diptera, Hybotidae, Tachydromiinae) of Singapore and adjacent regions
Fig. 237. Species accumulation curve: number of species in relation to the number of sampled habitats (x-axis).
Figs 220-224 in The fast-running flies (Diptera, Hybotidae, Tachydromiinae) of Singapore and adjacent regions
Figs 220-224. Stilpon neesoonensis sp. nov., ♂. 220. head lateral, lateral view. 221. mid leg, anterior view. 222. right epandrial lamella, lateral view. 223. epandrium with cerci, dorsal view. 224. left surstylus and cercus, dorso-lateral view.
Figs 207-209 in The fast-running flies (Diptera, Hybotidae, Tachydromiinae) of Singapore and adjacent regions
Figs 207-209. Stilpon goesi Shamshev & Grootaert, 2006, ♂ terminalia. 207. right surstylus, lateral view. 208. epandrium with cerci, dorsal view. 209. left surstylus, lateral view. Scale bar= 0.1 mm (after Shamshev & Grootaert 2006).
Figs 214-219 in The fast-running flies (Diptera, Hybotidae, Tachydromiinae) of Singapore and adjacent regions
Figs 214-219. Stilpon malayensis Shamshev & Grootaert, 2004, ♂. 214. wing, dorsal view. 215. mid leg, anterior view. 216. right surstylus, dorsal view. 217. epandrium with cerci, dorsal view. 218. left cercus, lateral view. 219. left surstylus, lateral view. (after Shamshev & Grootaert 2004).
Figs 229-231 in The fast-running flies (Diptera, Hybotidae, Tachydromiinae) of Singapore and adjacent regions
Figs 229-231. Stilpon singaporensis sp. nov., ♂. 229. right epandrial lamella, lateral view. 230. epandrium with cerci, dorsal view. 231. left surstylus, lateral view. Scale bar= 0.1 mm.
Figs 204-206 in The fast-running flies (Diptera, Hybotidae, Tachydromiinae) of Singapore and adjacent regions
Figs 204-206. Stilpon arcuatum sp. nov., ♂ terminalia. 204. epandrium with cerci, dorsal view. 205. left surstylus, lateral view. 206. left cercus, lateral view.
Figs 172-177 in The fast-running flies (Diptera, Hybotidae, Tachydromiinae) of Singapore and adjacent regions
Figs 172-177. Nanodromia, ♂. 172. N. hutan sp. nov., hind leg, anterior view. 173. N. hutan sp. nov., tip of hind tibia, dorsal view. 174. N. phukhao Grootaert & Shamshev, 2003, hind tibia, dorsal view. 175. N. narmjeud Grootaert & Shamshev, 2003, bladder-like gland between tergite 4 and 5, dorsal view. 176. N. narmkroi Grootaert & Shamshev, 2003, gland-like fields between tergites 4-5 and 5-6, dorsal view. 177. N. phukhao Grootaert & Shamshev, 2003, gland-like fields between tergites 4-5 and 5-6, dorsal view. (Figs 174-177 after Grootaert & Shamshev 2003).
Figs 169-171 in The fast-running flies (Diptera, Hybotidae, Tachydromiinae) of Singapore and adjacent regions
Figs 169-171. Nanodromia hutan sp. nov., ♂ terminalia. 169. right epandrial lamella, lateral view. 170. epandrium with cerci, dorsal view. 171. left surstylus, lateral view.
Figs 58-62 in The fast-running flies (Diptera, Hybotidae, Tachydromiinae) of Singapore and adjacent regions
Figs 58-62. Chersodromia nigripennis Shamshev & Grootaert, 2005, ♂. 58. palpus, lateral view. 59. antenna, lateral view. 60. right epandrial lamella, lateral view. 61. epandrium and cerci, dorsal view. 62. left surstylus, lateral view. (after Shamshev & Grootaert 2005).
Figs 101-104 in The fast-running flies (Diptera, Hybotidae, Tachydromiinae) of Singapore and adjacent regions
Figs 101-104. Drapetis mandai sp. nov., ♂. 101. antenna, lateral view. 102. right surstylus, dorsal view. 103. epandrium and cerci. 104. left surstylus, lateral. Scale bar= 0.1 mm.
Figs 44-51 in The fast-running flies (Diptera, Hybotidae, Tachydromiinae) of Singapore and adjacent regions
Figs 44-51. Chersodromia sylvicola sp. nov., ♂. 44. antenna, lateral view. 45. wing, dorsal view. 46. head, lateral view. 47. head, frontal view. 48. right epandrial lamella, lateral view. 49. epandrium with cerci, dorsal view. 50. left surstylus, lateral view. 51. hind tibia, anterior view.
Figs 31-36 in The fast-running flies (Diptera, Hybotidae, Tachydromiinae) of Singapore and adjacent regions
Figs 31-36. Chersodromia bulohensis sp. nov., ♂. 31. head, lateral view. 32. wing, dorsal view. 33. hind femur and tibia, anterior view. 34. right epandrial lamella, lateral view. 35. epandrium with cerci, dorsal view. 36. hypandrium with detail of left surstylus, ventral view.
Dataset for "Fmmgen: Automatic Code Generation of Operators for Cartesian Fast Multipole and Barnes-Hut Methods"
<p>This repository provides the dataset, build and run scripts for the paper "Fmmgen: Automatic Code Generation of Cartesian Fast Multipole and Barnes-Hut Operators", by Ryan Alexander Pepper and Hans Fangohr.</p> <p><br> <strong>Organisation</strong><br> The repository is organised as follows:</p> <p><strong><em>sim-scripts</em></strong></p> <p>sim-scripts/ contains the source code, build and run scripts for running the FMM calculations described in the paper. To reproduce the results from the paper, you need as prerequisites:<br> * An installation and license of the Intel Compiler (Parallel Studio 2019 Update 3 was used for the paper).<br> * An installation of the GNU compiler suite.<br> * GNU Make<br> * Python 3.6<br> * A copy of fmmgen v1.0 (available at https://github.com/rpep/fmmgen or https://zenodo.org/record/3842591)<br> * An installation of Fidimag v3.0 (available at http://github.com/computationalmodelling/fidimag or http://dx.doi.org/10.5281/zenodo.3841935)</p> <p>With these prerequisites, simply run from the sim-scripts directory:<br> ```<br> # To build the executables<br> make build<br> # To run the studies<br> make run<br> ```</p> <p>The four scripts are:<br> * run-harmonic-cse-comparison.sh - Runs the Fast Multipole Method for 50000 Coulomb particles, varying the order of expansion, and evaluating the performance benefits of various optimisation strategies introduced in the code generation stage.</p> <p>* run-scaling-comparison.sh - Runs comparisons between the Barnes-Hut and Fast Multipole Methods for different expansion orders and values of theta, the 'opening angle' parameter.</p> <p>* run-error-comparison.sh - Runs the FMM and Barnes-Hut calculations, saving the fields and performing the direct calculation, allowing evaluation of the errors for the two methods.</p> <p>* run-fidimag-tests.sh - Runs the Fidimag scaling tests for a series of magnetic dipoles placed on a lattice.</p> <p><strong><em>results</em></strong></p> <p>results contains the output data from the sim-scripts scripts. Note: running the scripts will overwrite this data!</p> <p><br> <strong><em>figure-scripts</em></strong></p> <p>This contains Python scripts needed to reproduce the figures from the paper. These generated figures are included in the repository for convenience. To run these scripts, you require:</p> <p>* Python >= 3.6<br> * Matplotlib >= 3.1.1<br> * Seaborn >= 0.9.1<br> * NumPy >= 1.17.1</p> <p><strong><em>figures</em></strong></p> <p>This contains the output figures included in the paper.<br> </p>
Morphodynamic stability of river and tidal bifurcations around bars tested in the Fast Flow Facility
<p>Multithread rivers such as the Jamuna and Mekong have networks of channels and bars that change with every flood. Tidal systems such as the Scheldt, Humber and Columbia estuaries and short tidal basins in the Wadden Sea and in Florida, have perpetually changing and interacting channels and shoals formed by ebb and flood currents. Current models fail to forecast these natural dynamics, yet main channels are economically important shipping fairways, whilst shoal areas that emerge and submerge daily are ecologically valuable habitats. Human interference, changing river discharge and sealevel rise threaten all functions. Furthermore, there are strong indications that fairway deepening leads to reduced urban safety due to enhanced flow resistance by groynes in rivers and enhanced tidal range in estuaries (e.g. Bolla Pittaluga et al. 2015 in AWR, Seminara et al., in EH 2011). This enhances dike failure risk during low water level and flooding during high water level. We urgently need dynamic forecasting models to optimise management strategies for these multiple functions (Wang et al. 2012 in Ocean Coastal Manage., Coco et al. 2013 in Mar. Geol.).</p> <p>Here we target firstly river bifurcations and secondly the mutually evasive ebb- or flood-dominated channels that form around bars and are found in all sandy tidal systems in the world (van Veen 1950/2002 in J. R. Dutch Geograph. Soc.). The cause for the mutual evasion is still incompletely understood despite the fact that they also appear in our numerical model results and experiments (Canestrelli et al., in JGR 2010; Kleinhans et al. 2015 in JGR). The nodes where ebb and flood channels connect can be seen as asymmetric bifurcations where one channel is preferred during ebb and the other during flood. Such bifurcations are critical elements that partition flow and sediment through the channel network, govern bar merging and splitting and are locations where bed steps form in shipping lanes, as in river bifurcations. Stability and equilibrium configurations are mostly unknown for tidal bifurcations except for one recent theory (Wang et al in prep.). In particular, we have a fair understanding of the tidal dynamics, but this is incomplete for the morphodynamics, especially related to understanding the sediment division at the bifurcation.</p> <p>We take advantage of the better but yet incomplete understanding of river bifurcations. The stability of river bifurcations has been studied for two decades in fieldwork, experimentation, linear stability theory and numerical modelling (e.g. Wang et al. 1995, JHR, see review in Kleinhans et al. 2013, ESPL) and our recent theory (Bolla Pittaluga et al. 2015 in GRL) synthesises many of the earlier results as follows: In bedload-dominated rivers, symmetrical bifurcations are unstable and develop towards a highly asymmetrical division of discharge and sediment. The same is the case for suspended sediment-dominated rivers, but the theory predicts stable bifurcations for intermediate sediment mobility. However, there is very little data for conditions intermediate between low and high mobility rivers. Moreover, we have no idea whether bifurcations in reversing tidal flow are unstable for similar configurations and conditions as in rivers. Here we mean configurations that are entirely free of topographic forcings on the flow: straight channels split into two channels over some length and depth.</p> <p>Our objective was therefore to experimentally investigate bifurcation stability in a range of sediment mobilities in unidirectional flow and reversing tidal flow ceteris paribus.</p>
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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.