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Results files and R objects for Gilmore et al 2024 SNORD116 analysis
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Datasets, trained models and supporting results for machine learning tensorial properties of atomic systems via XPaiNN model.
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Sequencing results of the 21 resequenced herbarium tomato specimens
<p>Sequencing results of the 21 herbarium tomato specimens resequenced on an Illumina NovaSeq 600 platform.</p>
EUHFORIA modeling result of SERPENTINE event SEP-C25-0015
<p>This dataset constitutes the output from the heliospheric magnetohydrodynamic simulation model EUHFORIA related to the <a href="https://serpentine-h2020.eu/">SERPENTINE</a> event <a href="https://data.serpentine-h2020.eu/catalogs/sep-sc25/SEP-C25-0015/">SEP-C25-0015</a>. The model includes the event CME-0015b. The three-dimensional simulation output is provided at 4-hour cadence. If you use this data, please cite the following publication:</p> <ul> <li>Pomoell, J. and Poedts, S.; J. Space Weather Space Clim. (2018), 8, A35 (doi: <a href="https://doi.org/10.1051/swsc/2018020">10.1051/swsc/2018020</a>)</li> </ul> <p> </p>
EUHFORIA modeling result of SERPENTINE event SEP-C25-0024
<p>This dataset constitutes the output from the heliospheric magnetohydrodynamic simulation model EUHFORIA related to the <a href="https://serpentine-h2020.eu/">SERPENTINE</a> event <a href="https://data.serpentine-h2020.eu/catalogs/sep-sc25/SEP-C25-0024/">SEP-C25-0024</a>. The model includes the following CME events: CME-0024a, CME-0024b, CME-0025d and CME-0026a. The simulation has been split into three records, please see also the other two for the complete simulation. The three-dimensional simulation output is provided at 4-hour cadence. If you use this data, please cite the following publication:</p> <ul> <li>Pomoell, J. and Poedts, S.; J. Space Weather Space Clim. (2018), 8, A35 (doi: <a href="https://doi.org/10.1051/swsc/2018020">10.1051/swsc/2018020</a>)</li> </ul> <p> </p>
EUHFORIA flux-rope modeling result of SERPENTINE event SEP-C25-0021
<p>This dataset constitutes the output from the heliospheric magnetohydrodynamic simulation model EUHFORIA related to the <a href="https://serpentine-h2020.eu/">SERPENTINE</a> event <a href="https://data.serpentine-h2020.eu/catalogs/sep-sc25/SEP-C25-0021/">SEP-C25-0021</a>. The model includes the event CME-0021b modeled using a flux-rope CME model. Please also see the associated record using the cone-model run for the same event. The three-dimensional simulation output is provided at 4-hour cadence. If you use this data, please cite the following publication:</p> <ul> <li>Pomoell, J. and Poedts, S.; J. Space Weather Space Clim. (2018), 8, A35 (doi: <a href="https://doi.org/10.1051/swsc/2018020">10.1051/swsc/2018020</a>)</li> </ul> <p> </p>
EUHFORIA modeling result of SERPENTINE event SEP-C25-0026
<p>This dataset constitutes the output from the heliospheric magnetohydrodynamic simulation model EUHFORIA related to the <a href="https://serpentine-h2020.eu/">SERPENTINE</a> event <a href="https://data.serpentine-h2020.eu/catalogs/sep-sc25/SEP-C25-0026/">SEP-C25-0026</a>. The model includes the following CME events: CME-0024a, CME-0024b, CME-0025d and CME-0026a. The simulation has been split into three records, please see also the other two for the complete simulation. The three-dimensional simulation output is provided at 4-hour cadence. If you use this data, please cite the following publication:</p> <ul> <li>Pomoell, J. and Poedts, S.; J. Space Weather Space Clim. (2018), 8, A35 (doi: <a href="https://doi.org/10.1051/swsc/2018020">10.1051/swsc/2018020</a>)</li> </ul> <p> </p>
EUHFORIA modeling result of SERPENTINE event SEP-C25-0018
<p>This dataset constitutes the output from the heliospheric magnetohydrodynamic simulation model EUHFORIA related to the <a href="https://serpentine-h2020.eu/">SERPENTINE</a> event <a href="https://data.serpentine-h2020.eu/catalogs/sep-sc25/SEP-C25-0018/">SEP-C25-0018</a>. The model includes the event CME-0018a. The three-dimensional simulation output is provided at 4-hour cadence. If you use this data, please cite the following publication:</p> <ul> <li>Pomoell, J. and Poedts, S.; J. Space Weather Space Clim. (2018), 8, A35 (doi: <a href="https://doi.org/10.1051/swsc/2018020">10.1051/swsc/2018020</a>)</li> </ul> <p> </p>
EUHFORIA modeling result of SERPENTINE event SEP-C25-0025
<p>This dataset constitutes the output from the heliospheric magnetohydrodynamic simulation model EUHFORIA related to the <a href="https://serpentine-h2020.eu/">SERPENTINE</a> event <a href="https://data.serpentine-h2020.eu/catalogs/sep-sc25/SEP-C25-0025/">SEP-C25-0025</a>. The model includes the following CME events: CME-0024a, CME-0024b, CME-0025d and CME-0026a. The simulation has been split into three records, please see also the other two for the complete simulation. The three-dimensional simulation output is provided at 4-hour cadence. If you use this data, please cite the following publication:</p> <ul> <li>Pomoell, J. and Poedts, S.; J. Space Weather Space Clim. (2018), 8, A35 (doi: <a href="https://doi.org/10.1051/swsc/2018020">10.1051/swsc/2018020</a>)</li> </ul> <p> </p>
EUHFORIA modeling result of SERPENTINE event SEP-C25-0013
<p>This dataset constitutes the output from the heliospheric magnetohydrodynamic simulation model EUHFORIA related to the <a href="https://serpentine-h2020.eu/">SERPENTINE</a> event <a href="https://data.serpentine-h2020.eu/catalogs/sep-sc25/SEP-C25-0013/">SEP-C25-0013</a>. The model includes the event CME-0013a. The three-dimensional simulation output is provided at 4-hour cadence. If you use this data, please cite the following publication:</p> <ul> <li>Pomoell, J. and Poedts, S.; J. Space Weather Space Clim. (2018), 8, A35 (doi: <a href="https://doi.org/10.1051/swsc/2018020">10.1051/swsc/2018020</a>)</li> </ul> <p> </p>
EUHFORIA modeling result of SERPENTINE event SEP-C25-0016
<p>This dataset constitutes the output from the heliospheric magnetohydrodynamic simulation model EUHFORIA related to the <a href="https://serpentine-h2020.eu/">SERPENTINE</a> event <a href="https://data.serpentine-h2020.eu/catalogs/sep-sc25/SEP-C25-0016/">SEP-C25-0016</a>. The model includes the event CME-0016a. The three-dimensional simulation output is provided at 4-hour cadence. If you use this data, please cite the following publication:</p> <ul> <li>Pomoell, J. and Poedts, S.; J. Space Weather Space Clim. (2018), 8, A35 (doi: <a href="https://doi.org/10.1051/swsc/2018020">10.1051/swsc/2018020</a>)</li> </ul> <p> </p>
Computational results data for the assoziated publication "Network Interdiction Problems in Urban Transportation: Theoretical Insights and Computational Characteristics"
<p>This repository contains two Excel tables with computational results for our paper "Network Interdiction Problems in Urban Transportation: Theoretical Insights and Computational Characteristics". Each Excel table includes multiple worksheets, each representing different scenarios and models evaluated in our study.</p> <p><strong>Worksheets Overview</strong></p> <p>Each Excel table contains the following worksheets:<br>1. <strong>ML</strong>: Results for the "ML" big M values.<br>2. <strong>MH</strong>: Results for the "MH" big M values.<br>3. <strong>MF</strong>: Results for the "MF" big M values.<br>4. <strong>Path</strong>: Results for the path model.<br>5. <strong>FMInstances</strong>: Results from applying our models on the original Fontaine and Minner (2018) instances.</p> <p><strong>Columns Description</strong></p> <p>Each worksheet contains the following columns:</p> <p>- <strong>Name of Instance</strong>: A complex string with the identifier of the used instance. The relevant part is "_RXXX_", where XXX is the random seed used to generate the instance.<br>- <strong>Number users</strong>: The number of users/commodities in the network.<br>- <strong>B:</strong> The budget (always set to infinity in our instances).<br>- <strong>GUROBI_RUNTIME</strong>: The time limit set for the computations.<br>- <strong>Modelkind</strong>: The type of model used. Possible values are:<br> - INDICATOR: Compact model.<br> - FMbenders: Benders model from Fontaine and Minner (2018).<br> - ICM: Benders-like cuts.<br> - PathModel: Path enumeration model.<br>- <strong>BigM computation</strong>: Time required to compute all the big M values used (not included in the time limit).<br>- <strong>runtime</strong>: Runtime of the selected model.<br>- <strong>BBnodes</strong>: Number of nodes in the Branch & Bound tree.<br>- <strong>gap</strong>: Gap reported by Gurobi after reaching the time limit.<br>- <strong>Cuts BLC</strong>: Number of Benders-like cuts included.<br>- <strong>Time BLC</strong>: Time required for separating Benders-like cuts.<br>- <strong>M improve BLC</strong>: Frequency of improvements to a big M when using the improved big M term in Benders-like cuts.<br>- <strong>Mcutoff_AVE</strong>: Average (non-zero) improvement of a big M when using the improved big M term in Benders-like cuts.<br>- <strong>Cuts FMBenders</strong>: Number of Benders cuts generated in the Fontaine and Minner (2018) model.<br>- <strong>Time FMBenders</strong>: Time required to generate the Benders cuts in the Fontaine and Minner (2018) model.<br>- <strong>Runtime path enum</strong>: Time required to enumerate all paths for the path-based model (not included in the time limit).<br>- <strong>Average Num Path</strong>: Average number of paths generated for a single commodity/user. Multiply this value by the number of users to obtain the absolute number of paths generated.</p> <p><strong>Note on FCP</strong></p> <p>All the results found for the instances already had integer flow solutions. Additionally, we conducted experiments where we explicitly forced the solutions to be integer for the Benders-like cuts model. We observed that the runtimes remained the same, with only some natural insignificant hardware-induced fluctuations. Therefore, we omit reporting these results again.</p> <p><br>For further information or questions, please refer to our paper "Network Interdiction Problems in Urban Transportation: Theoretical Insights and Computational Characteristics" or contact the authors.</p>
Data to reproduce the results presented in Lake et al. 2024. Journal of Hydrology, https://doi.org/10.1016/j.jhydrol.2024.131930. ("High-frequency spatial sediment source fingerprinting using in situ absorbance data")
<p>This repository contains data on the used absorbance data, measured at the field site, as described in Lake et al., 2024 (<span>h</span><span>t</span><span>t</span><span>p</span><span>s</span><span>:</span><span>/</span><span>/</span><span>d</span><span>o</span><span>i</span><span>.</span><span>o</span><span>r</span><span>g</span><span>/</span><span>1</span><span>0</span><span>.</span><span>1</span><span>0</span><span>1</span><span>6</span><span>/</span><span>j</span><span>.</span><span>j</span><span>h</span><span>y</span><span>d</span><span>r</span><span>o</span><span>l</span><span>.</span><span>2</span><span>0</span><span>2</span><span>4</span><span>.</span><span>1</span><span>3</span><span>1</span><span>9</span><span>3</span><span>0).</span> Furthermore, data on the turbidity, used calibration curves and R code to prepare the input data for the MixSIAR model are included in the data repository.</p>
Figure 4 in Building capacity to implement conservation breeding programs for frogs in Madagascar: Results from year one of Mitsinjo's amphibian husbandry research and captive breeding facility
Figure 4. Seven species of frogs were included in a husbandry research and technician training program during the first year of the project. The IUCN Red List status, in parenthesis, follows species. A) Heterixalus betsileo (LC). B) Mantidactylus betsileanus, (LC). C) Heterixalus punctatus (LC). D) Blommersia blommersae (LC). E) Guibemantis aff. albolineatus "Andasibe" (DD). F) Stumpffia sp. "Ranomafana" (DD). G) Boophis pyrrhus (LC).
Figure 3 in Building capacity to implement conservation breeding programs for frogs in Madagascar: Results from year one of Mitsinjo's amphibian husbandry research and captive breeding facility
Figure 3. Terraria and aquaria at the breeding facility. A) Terraria setup on shelving and plumbed so wastewater flows into a drain in the floor. B) A terrarium housing a group of Boophis pyrrhus. C) Aquaria for raising tadpoles. D) Boophis pyrrhus tadpoles produced at the facility.
Figure 9 in Building capacity to implement conservation breeding programs for frogs in Madagascar: Results from year one of Mitsinjo's amphibian husbandry research and captive breeding facility
Figure 9. Pilot study and training exercise on the optimal larval diet for Mantidactylus betsileanus.
Figure 1. The facility was constructed between November 2010 and March 2011 in Building capacity to implement conservation breeding programs for frogs in Madagascar: Results from year one of Mitsinjo's amphibian husbandry research and captive breeding facility
Figure 1. The facility was constructed between November 2010 and March 2011 from the foundations of an old abandoned forest station. A) Original abandoned building in January 2009. B) Facility construction November 2010. C) Facility construction December 2010. D) Facility construction January 2011.
Figure 8 in Building capacity to implement conservation breeding programs for frogs in Madagascar: Results from year one of Mitsinjo's amphibian husbandry research and captive breeding facility
Figure 8. Locally-sourced crickets from Andasibe being bred at Mitsinjo's facility. A) Field cricket (Modicogryllus sp.). B) Large field cricket (Modicogryllus sp.). C) Large black cricket (Gryllus sp.). D) Tropical house cricket (Gryllodes sigillatus). E) Cave cricket (Rhaphidophoridae). F) Shelves with boxes housing field crickets and tropical house crickets.
Figure 2 in Building capacity to implement conservation breeding programs for frogs in Madagascar: Results from year one of Mitsinjo's amphibian husbandry research and captive breeding facility
Figure 2. Overview of the biosecure Mitsinjo amphibian captive breeding and husbandry research center as of April 2012.
Figure 5 in Building capacity to implement conservation breeding programs for frogs in Madagascar: Results from year one of Mitsinjo's amphibian husbandry research and captive breeding facility
Figure 5. Lectures and discussions during January-March 2011 helped train Mitsinjo technicians in captive frog husbandry techniques.
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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.