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.
47,429
datasets available to search
ShareScore release 0.9.0
Dataset results
47,429 results for “5”
Trento 1936 - Building 5
<u>Coordinates</u>: N/A <br><u>Length</u>: 47.93 m<br><u>Width</u>: 14.74 m<br><u>Height</u>: 80.18 m<br><u>Points</u>: 34 <br><u>Vertices</u>: 204 <br><u>Primitives</u>: 68 <br><br><u>Main Files:</u><br><table><tbody><tr><th>Filename</th><th>.glb</th><th>.obj</th><th>.xml</th></tr><tr><td><a href="https://zenodo.org/api/records/12688774/files/building_5.obj/content">building_5.obj</a></td><td></td><td><a href="https://zenodo.org/api/records/12688774/files/building_5.obj/content">Link</a></td><td></td></tr><tr><td><a href="https://zenodo.org/api/records/12688774/files/building_5.glb/content">building_5.glb</a></td><td><a href="https://zenodo.org/api/records/12688774/files/building_5.glb/content">Link</a></td><td></td><td></td></tr><tr><td><a href="https://zenodo.org/api/records/12688774/files/11577530_metsmods.xml/content">11577530_metsmods.xml</a></td><td></td><td></td><td><a href="https://zenodo.org/api/records/12688774/files/11577530_metsmods.xml/content">Link</a></td></tr><tr><td><a href="https://zenodo.org/api/records/12688774/files/11577530_edm.xml/content">11577530_edm.xml</a></td><td></td><td></td><td><a href="https://zenodo.org/api/records/12688774/files/11577530_edm.xml/content">Link</a></td></tr></tbody></table><br><br><u>Thumbnails:</u><br><table><tbody><tr><th>Perspective</th><th>1000x1000</th><th>512x512</th><th>256x256</th><th>128x128</th></tr><tr><td>Perspective 1</td><td><a href="https://zenodo.org/api/records/12688774/files/building_5_perspective_1.png/content">Link</a></td><td><a href="https://zenodo.org/api/records/12688774/files/building_5_perspective_1_512x512.png/content">Link</a></td><td><a href="https://zenodo.org/api/records/12688774/files/building_5_perspective_1_256x256.png/content">Link</a></td><td><a href="https://zenodo.org/api/records/12688774/files/building_5_perspective_1_128x128.png/content">Link</a></td></tr><tr><td>Perspective 2</td><td><a href="https://zenodo.org/api/records/12688774/files/building_5_perspective_2.png/content">Link</a></td><td><a href="https://zenodo.org/api/records/12688774/files/building_5_perspective_2_512x512.png/content">Link</a></td><td><a href="https://zenodo.org/api/records/12688774/files/building_5_perspective_2_256x256.png/content">Link</a></td><td><a href="https://zenodo.org/api/records/12688774/files/building_5_perspective_2_128x128.png/content">Link</a></td></tr><tr><td>Perspective 3</td><td><a href="https://zenodo.org/api/records/12688774/files/building_5_perspective_3.png/content">Link</a></td><td><a href="https://zenodo.org/api/records/12688774/files/building_5_perspective_3_512x512.png/content">Link</a></td><td><a href="https://zenodo.org/api/records/12688774/files/building_5_perspective_3_256x256.png/content">Link</a></td><td><a href="https://zenodo.org/api/records/12688774/files/building_5_perspective_3_128x128.png/content">Link</a></td></tr><tr><td>Perspective 4</td><td><a href="https://zenodo.org/api/records/12688774/files/building_5_perspective_4.png/content">Link</a></td><td><a href="https://zenodo.org/api/records/12688774/files/building_5_perspective_4_512x512.png/content">Link</a></td><td><a href="https://zenodo.org/api/records/12688774/files/building_5_perspective_4_256x256.png/content">Link</a></td><td><a href="https://zenodo.org/api/records/12688774/files/building_5_perspective_4_128x128.png/content">Link</a></td></tr><tr><td>Perspective Top</td><td><a href="https://zenodo.org/api/records/12688774/files/building_5_perspective_top.png/content">Link</a></td><td><a href="https://zenodo.org/api/records/12688774/files/building_5_perspective_top_512x512.png/content">Link</a></td><td><a href="https://zenodo.org/api/records/12688774/files/building_5_perspective_top_256x256.png/content">Link</a></td><td><a href="https://zenodo.org/api/records/12688774/files/building_5_perspective_top_128x128.png/content">Link</a></td></tr></tbody></table><br><br><br><u>Changelog</u>: <br> - v<a href="https://doi.org/10.5281/zenodo.12548501">0.0.2</a>: Thumbnails added, Description updated with Link Tables.<br> - v<a href="https://doi.org/10.5281/zenodo.12688774">0.0.3</a>: Added XMLs for Europeana Data Model (EDM) and MetsMods.<br>
Amsterdam - Zwanenburgerstraat 5
<u>Coordinates</u>: N/A <br><u>Length</u>: 14.72 m<br><u>Width</u>: 12.51 m<br><u>Height</u>: 17.56 m<br><u>Vertices</u>: 3177 <br><u>Primitives</u>: 2655 <br><br> The Length, Width, Height, Vertices and Primitives listed above have been derived directly from the OBJ file.<br><br><u>Main Files:</u><br><table><tbody><tr><th>Filename</th><th>.glb</th><th>.obj</th><th>.mtl</th><th>.xml</th><th>.zip</th></tr><tr><td><a href="https://zenodo.org/api/records/12750791/files/textures.zip/content">textures.zip</a></td><td></td><td></td><td></td><td></td><td><a href="https://zenodo.org/api/records/12750791/files/textures.zip/content">Link</a></td></tr><tr><td><a href="https://zenodo.org/api/records/12750791/files/Zwanenburgerstraat_5.glb/content">Zwanenburgerstraat_5.glb</a></td><td><a href="https://zenodo.org/api/records/12750791/files/Zwanenburgerstraat_5.glb/content">Link</a></td><td></td><td></td><td></td><td></td></tr><tr><td><a href="https://zenodo.org/api/records/12750791/files/Zwanenburgerstraat_5.obj/content">Zwanenburgerstraat_5.obj</a></td><td></td><td><a href="https://zenodo.org/api/records/12750791/files/Zwanenburgerstraat_5.obj/content">Link</a></td><td></td><td></td><td></td></tr><tr><td><a href="https://zenodo.org/api/records/12750791/files/Zwanenburgerstraat_5.mtl/content">Zwanenburgerstraat_5.mtl</a></td><td></td><td></td><td><a href="https://zenodo.org/api/records/12750791/files/Zwanenburgerstraat_5.mtl/content">Link</a></td><td></td><td></td></tr><tr><td><a href="https://zenodo.org/api/records/12750791/files/11253081_edm.xml/content">11253081_edm.xml</a></td><td></td><td></td><td></td><td><a href="https://zenodo.org/api/records/12750791/files/11253081_edm.xml/content">Link</a></td><td></td></tr><tr><td><a href="https://zenodo.org/api/records/12750791/files/11253081_metsmods.xml/content">11253081_metsmods.xml</a></td><td></td><td></td><td></td><td><a href="https://zenodo.org/api/records/12750791/files/11253081_metsmods.xml/content">Link</a></td><td></td></tr></tbody></table><br><br><br><br><br><u>Changelog</u>: <br> - v<a href="https://doi.org/10.5281/zenodo.12750791">0.0.2</a>: Added XMLs for Europeana Data Model (EDM) and MetsMods.<br>
Input files for "Faster Simulations with a 5 fs Time Step for Lipids in the CHARMM Force Field"
<p>The performance of all-atom molecular dynamics simulations is limited by an integration time step of 2 fs, which is needed to resolve the fastest degrees of freedom in the system, namely, the vibration of bonds and angles involving hydrogen atoms. The virtual interaction sites (VIS) method replaces hydrogen atoms by massless virtual interaction sites to eliminate these degrees of freedom while keeping intact nonbonded interactions and the explicit treatment of hydrogen atoms. We have modified the existing VIS algorithm for most lipids in the popular CHARMM36 force field by increasing the hydrogen atom masses at regular intervals in the lipid acyl chains and obtained lipid properties and pore formation free energies in very good agreement with those calculated in simulations without VIS. Our modified VIS scheme enables a 5 fs time step resulting in a significant performance gain for all-atom simulations of membranes. The method has the potential to make longer time and length scales accessible in all-atom simulations of membrane–protein complexes.</p> <p>The file set contains individual lipid topologies for virtual interaction sites for standard CHARMM lipids, as well as a README file with instructions on how to implement the VIS algorithm for membranes or membrane-protein complexes</p> <p>Please Cite: <a href="//pubs.acs.org/doi/10.1021/acs.jctc.8b00267">10.1021/acs.jctc.8b00267</a></p> <p> </p>
Capillary- and stored-elastic-energy-driven anisotropic sub-grain coarsening (PRX2D) (Part 5)
<p><strong>Further details in the TopologyTracer documentation</strong><br> https://github.com/mkuehbach/TopologyTracer/tree/master/docs/build</p> <p><strong>Further details microstructure synthesis in the IMMMicrostructur generator documentation</strong><br> https://github.com/GraGLeS/IMM_MicrostructureGenerator/tree/master/docs/build/html</p> <p><strong>Repository content</strong></p> <p>Texture_Faces_171_to_259.zip<br> Grain boundary network geometry and grain meta data tracking data for time step 171 to 259 with 1 time step resolution</p>
Agriculture - General: Animal Production and Health 5
<p>This dataset contains the digitized treatments in Plazi based on the original journal article Michelsen, Verner (2012): Revision of the European Delia pruinosa species group (Diptera: Anthomyiidae) feeding as larvae in seed capsules of Silene L. (Caryophyllaceae). Zootaxa 3434: 31-48, DOI: 10.5281/zenodo.282060</p>
Agriculture - Forestry 5
<p>Over the last 5 years several REDD+ pilot projects were implemented in Tanzania to generate information on forest carbon stocks to contribute to the REDD+ strategy. The generated information constitutes a good source of important biodiversity data that can be used in conservation and sustainable development. Lyimo P, Munishi P, Gideon H (2018). Tree species Occurrence Data of Coastal Miombo in Western Tanzania.. Version 1.6. Sokoine University of Agriculture, Department of Ecosystems and Conservation. Occurrence dataset <a href="https://doi.org/10.15468/nyhbez">https://doi.org/10.15468/nyhbez</a> accessed via GBIF.org</p>
Agriculture - General: Animal Production and Health, Natural Resources and Environment 5
<p>2001 till 2002 and 2004, inventory of entomofauna in forestwalls banks, diches, road verges in The Netherlands using pitfalls and sweeping net</p> <p>Jagers op Akkerhuis G, Dimmers W (2016). Alterra (NL) - Comparison of entomofauna in four different habitats. Version 1.1. Alterra, Wageningen UR. Occurrence dataset <a href="https://doi.org/10.15468/mkoqqh">https://doi.org/10.15468/mkoqqh</a> accessed via GBIF.org</p>
Agriculture - General: biological diversity 5
<p>Dataset of Invasive species - initial compilation of aquatic invasive species National Biodiversity Data Centre (2016). National Invasive Species Database. Occurrence dataset <a href="https://doi.org/10.15468/pkjqbk">https://doi.org/10.15468/pkjqbk</a> accessed via GBIF.org</p>
Soil available water capacity in mm derived for 5 standard layers (0-10, 10-30, 30-60, 60-100 and 100-200 cm) at 250 m resolution
<p>Available Water Capacity (in mm) derived by calculating Water Retention Difference (difference between the field capacity and wilting point; see <a href="https://www.nrcs.usda.gov/wps/portal/nrcs/detail/soils/ref/?cid=nrcs142p2_054247">NRCS Soil Survey Laboratory Methods Manual</a>), and then summing up WRD for all standard layers (0–200 cm). Soil water content (volumetric) in percent for 33 kPa and 1500 kPa suctions predicted at 6 standard depths (0, 10, 30, 60, 100 and 200 cm) at 250 m resolution is available <a href="https://doi.org/10.5281/zenodo.2609113"><strong>here</strong></a>. These estimates ignore depth to bedrock i.e. existence of any impenetrable layer (total available capacity over the whole land mass is likely about 10–15% smaller). Antarctica is not included.</p> <p>To access and visualize some of the maps use: <a href="http://www.openlandmap.org/">OpenLandMap.org</a></p> <p>If you discover a bug, artifact or inconsistency in the maps, or if you have a question please use some of the following channels:</p> <ul> <li>Technical issues and questions about the code: <a href="https://gitlab.com/openlandmap/global-layers/issues">https://gitlab.com/openlandmap/global-layers/issues</a></li> <li>General questions and comments: <a href="https://disqus.com/home/forums/landgis/">https://disqus.com/home/forums/landgis/</a></li> </ul> <p>All files internally compressed using "COMPRESS=DEFLATE" creation option in GDAL. File naming convention:</p> <ul> <li>sol = theme: soil,</li> <li>available.water.capacity = available water capacity in mm,</li> <li>usda.mm = determination method: Water Retention Difference in mm,</li> <li>m = mean value,</li> <li>250m = spatial resolution / block support: 250 m,</li> <li>b0..10cm = vertical reference: 0-10 cm layer below surface,</li> <li>1950..2017 = time reference: period 1950-2017,</li> <li>v0.1 = version number: 0.1,</li> </ul>
FT34 Tuerlinckx (2) 5-key tenoroon: measurements, photos, endoscopic video
<p>Dataset of FT34 Tuerlinckx 5-key tenoroon containing detailed external and internal measurements, photos, and an endoscopic video. </p>
FT22 Proff 5-key tenoroon: measurements, photos, endoscopic video
<p>Dataset of FT22 Proff 5-key tenoroon containing detailed external and internal measurements, photos, and an endoscopic video. </p> <p> </p>
Festival of Frequency Measurement 1 October 2019 for WWV 5 MHz - Toby Haynes VE7CNF
<p>Festival of Frequency Measurement 1 October 2019 for WWV 5 MHz</p> <p>Toby Haynes VE7CNF<br> Location: 49.266918N 122.900887W Grid CN89ng Burnaby, BC, Canada<br> Start Time: 2019 Sept 30 at 23:58 UTC<br> End time: 2019 Oct 2 at 00:02 UTC<br> Antenna: "Inverted L" vertical with ICOM AH-4 auto tuner, 50 ft high, 70 ft horizontal top wire.<br> Receiver: ICOM IC-7410 with internal TCXO reference and internal USB sound card chip with separate clock crystal.<br> Receiver in USB mode with carrier frequency 4998.5 kHz to give a 1500 Hz audio tone for the WWV 5 MHz carrier.<br> Measurement: 1500 Hz tone frequency estimated using program FLDigi v4.1.08 in frequency analysis mode.</p> <p>There was a drop in the WWV 5 MHz signal level around 15:00 UTC, after which the reduced SNR caused more variation in the FLDigi frequency measurements.</p> <p>Frequency calibration:</p> <p>Before and after the data set, the receiver frequency error was determined by using the receiver and FLDigi to measure a reference 5 MHz sine wave from a Rigol DG1032 function generator with external 10 MHz GPS-disciplined frequency reference (Trimble).<br> The "VE7CNF raw_2019-09-30-1810 UTC.csv" file includes the reference measurements and the data set.</p> <p>The two reference signal measurements were:<br> Receiver frequency error +0.066 Hz averaged for 1 minute starting 2019 Sept 30 at 18:10:25 UTC <br> Receiver frequency error +0.028 Hz averaged for 1 minute starting 2019 Oct 2 at 00:03:10 UTC</p> <p>Receiver frequency error at each time during the data set was then estimated, assuming that the error changed linearly over time betwen the two reference measurements. The estimated receiver frequency errors were applied to correct the data set in "VE7CNF CN89ng 5 MHz_2019-09-30-2358 UTC.csv."</p> <p>The measured WWV 5 MHz frequency error vs time is graphed in "VE7CNF_WWV5MHz_2019-10-01UTC.JPG," with a moving 1-minute average applied to the frequency error. The frequency dropped around 01:30 (local sunset was 01:51 UTC) and increased around 14:00 (local sunrise was 14:13 UTC).<br> <br> </p>
WWV 5 MHz
<p>Festival of Frequency Measurement 01 October 2019<br> Event : WWV Centennial<br> UTC date : 01 October 2019<br> Beacon Frequency : 5 MHz<br> Submitter : Martin H Potter, VE3OAT<br> Data recorded at : 45.2525N 75.5910W<br> City : Greely<br> Region : Ontario, CANADA</p> <p>WARNING : Data recorded during 1330-2230 UTC considered NOT USEFUL/INVALID due<br> to weak or non-existent signal reception. <br> <br> Data file : VE3OAT 45.25 -75.59 5 MHz.csv<br> Data start time : 2019 Sep 30 23:56 UTC<br> Antenna : 80/40 m band inverted-V dipoles with common feed<br> Antenna orientation : NW-SE<br> Receiver : Yaesu FTdx1200 transceiver<br> Frequency reference : internal, undisciplined<br> Receiver mode : USB<br> IF bandwidth : 1800 Hz<br> AGC : fast<br> Digital Noise Reduction (DNR) : off<br> Frequency measurement method : Reciever in USB mode tuned to 4999.000 kHz,<br> audio output to computer sound card, frequency measured and recorded by<br> Fldigi v4.1.06 software.<br> Computer sound card : calibrated by Fldigi "WWV" function</p> <p>Observation : At 0345 UTC, rapid "flutter" fading of the signal was noted with<br> smearing of the displayed signal frequency. </p>
WWV Centennial N1IRO 5 MHz Recording
<p>Festival of Frequency Measurement 1 October 2019</p> <p>N1IRO, William McGrath</p> <p>43.935242, -72.657349</p> <p>Start time 22:15 UTC<br> End Fed 130ft Dipole pointed SE (SW max reception)</p> <p>Kenwood TS-2000 receiver</p> <p>GPSDO reference</p> <p>FLDIGI recording as instructed.</p> <p>24 hour recording of 5 MHz at station N1IRO, Randolph, VT.</p> <p> </p>
Molecular dynamics simulations of the interaction of mutant human CYP2J2 (R117A) with arachidonic acid (POSES 5-6)
<p><strong>Description of files in this dataset:</strong></p> <p><strong>MD_mutR117A_CYP2J2_AA_StateX_repeatY.zip</strong> : Series of zipped directories for molecular dynamics simulations of arachidonic acid in the active site of the R117A mutant CYP2J2. X is the docking pose number that constitutes the starting point of the simulation (the 6 lowest-energy poses from docking were selected as the starting points of the simulations - this dataset is State(pose) 1). Y is the repeat (each simulation was repeated 3 times, hence there are 3 repeats per pose). </p> <p>Each directory contains the following sub-directories:</p> <p>001.leap : Amber parameter and coordinate files; PDBs; ligands; leap commands</p> <p>002.min : Minimisation stage</p> <p>003.heat : Heating stage</p> <p>004.equil: Equilibration stage</p> <p>005.md : Production stage</p> <p>006.analysis : Basic energy graphs</p> <p>007.cpptraj: Contains only the file strip.md.nc (Amber trajectories stripped of water in netCDF format)</p>
Molecular dynamics simulations of the interaction of wild type human CYP2J2 with arachidonic acid (POSES 5 and 6)
<p><strong>Description of files in this dataset:</strong></p> <p><strong>MD_wt_CYP2J2_AA_StateX_repeatY.zip</strong> : Series of zipped directories for molecular dynamics simulations of arachidonic acid in the active site of wild type CYP2J2. X is the docking pose number that constitutes the starting point of the simulation (the 6 lowest-energy poses from docking were selected as the starting points of the simulations - this dataset is State(pose) 1). Y is the repeat (each simulation was repeated 4 times, hence there are 4 repeats per pose). </p> <p>Each directory contains the following sub-directories:</p> <p>001.leap : Amber parameter and coordinate files; PDBs; ligands; leap commands</p> <p>002.min : Minimisation stage</p> <p>003.heat : Heating stage</p> <p>004.equil: Equilibration stage</p> <p>005.md : Production stage</p> <p>006.analysis : Basic energy graphs</p> <p>007.cpptraj: Contains only the file strip.md.nc (Amber trajectories stripped of water in netCDF format)</p>
MAR-M-247 creep assessment through a modified theta projection model - Figures 2 and 5
<p>These two programs provide a way to rebuild the MAR-M-247 creep data presented in the paper:</p> <p>G. Maggiani, M.J. Roy, S. Colantoni, P.J. Withers, MAR-M-247 creep assessment through a modified theta projection model, Materialia, Volume 7, 2019, 100392, ISSN 2589-1529, https://doi.org/10.1016/j.mtla.2019.100392. http://www.sciencedirect.com/science/article/pii/S2589152919301887)<br> </p> <p>In Paper_Figure_2.m two coefficients of the paper itself are corrected and a comparison with what written in the paper and the corrected value is provided. One typo error for theta 1 at 982°C and 140 MPa where 6.9 must be 1.9. The other is for 1038°C 50 MPa theta4. In the paper it is written e^-11 while it actually should have been e^-10.</p> <p>Paper_Figure_5.m more decimal values are provided for the coefficients a, b, c and d that are used to rebuild the theta values.</p> <p> </p> <p> </p>
Vertebrate traits: Vertebrate trait records, 5 November 2018
<p>This zip archive records all of the current trait records in EOL__s graph database, for vertebrate taxa. It contains four .csv files: pages.csv listing taxa and their names, traits.csv with trait records, metadata.csv with auxiliary records referred to by trait records, and terms.csv listing all of the relationship URIs in the database. For a description of the schema, see</p> <p>https://github.com/EOL/eol_website/blob/master/doc/trait-schema.md</p> <p>See dataset description. Generated 5 November 2018 from the live graph database. Uploaded 10 December 2018.</p>
SSP-aligned projected European water withdrawal/consumption at 5 arcminutes
<p><u><span>Release 0.9.1 – What is new?</span></u></p> <p><span><span>·<span> </span></span></span><span>Industrial water withdrawals were initially overestimated due to a problem with the input data, but they are now fixed.</span></p> <p><span><span>·<span> </span></span></span><span>Historical water withdrawal covering 1960-2020 added. Consistency between historical and projected water withdrawals is maintained.</span></p> <p><u><span>Contents and naming conventions</span></u></p> <p><span>Annual European water withdrawal: </span></p> <p><span>{scenario}_{sector} _year_millionm3_5min_Europe_{from_year}_{to_year}.nc</span></p> <p><span>Scenarios: historical, ssp1, ssp2, ssp3, ssp5</span></p> <p><span>Sector: dom, ind; stand for domestic/industrial</span></p> <p><span><span> </span>From/to_year: 1960/2020, 2020/2100; historical/ssp projections.</span></p> <p><span>Each file holds two variables: {sector}ww and {sector}wc representing gross and net (i.e. consumptive use) water withdrawal. For exmaple, for the industrial sector, there are two variables: <em>indww </em>and <em>indwc.</em><u> </u>The fraction ‘<em>1 – indwc/indww</em> ‘ represents the share of return flows. </span></p> <p>-------------------------</p> <p>The dataset provides annual water withdrawal and consumption estimates for Europe at a spatial resolution of 5 arcminutes, covering the periods 1960-2020 (historical) and 2020-2100 for four SSPs (1, 2, 3, and 5). Below, we outline the procedure used to downscale the population projections to a 5-arcminute resolution and describe the main equations applied to project water withdrawal and consumption under different SSPs.</p> <p>The development of the high-resolution (5 arcminute) projected water withdrawal and consumption for Europe follows the methodology outlined by Wada et al. (2011a, 2011b). This new release incorporates new projections for population, GDP per capita, and urbanization patterns from the latest SSP database (v3.0.1; available at <a href="https://data.ece.iiasa.ac.at/ssp/" target="_new">https://data.ece.iiasa.ac.at/ssp/</a>). Since this update is still in progress as of August 25<sup>th</sup>, 2024, some necessary input data are sourced from an earlier version of the SSP data (SSP 2013, see Table 1). <strong>All data and methods used to generate the results provided in this dataset are described in the Readme - Data and Methods file.</strong></p> <p><a name="_Ref175610392"></a>Table 1: Data availability in different versions of the SSP database as of August 25<sup>th</sup> 2024.</p> <table> <tbody> <tr> <td> <p><strong>Data</strong></p> </td> <td> <p><strong>SSP DatabaseVersion</strong></p> </td> <td> <p><strong>Module</strong></p> </td> </tr> <tr> <td> <p>Population</p> </td> <td> <p>SSP v3.0.1 2024</p> </td> <td> <p>Domestic</p> </td> </tr> <tr> <td> <p>GDP per capita</p> </td> <td> <p>SSP v3.0.1 2024</p> </td> <td> <p>Domestic/industrial</p> </td> </tr> <tr> <td> <p>Energy use per capita</p> </td> <td> <p>SSP 2013</p> </td> <td> <p>Industrial</p> </td> </tr> <tr> <td> <p>Electricity use per capita</p> </td> <td> <p>SSP 2013</p> </td> <td> <p>Industrial</p> </td> </tr> </tbody> </table>
Dataset supporting the paper "Bipolar single-molecule electroluminescence and electrofluorochromism. Physical Review Research 5, 033027 (2023)"
<p>Dataset corresponding to theoretical calculations in the paper "Bipolar single-molecule electroluminescence and electrofluorochromism. Physical Review Research 5, 033027 (2023)" DOI: https://doi.org/10.1103/PhysRevResearch.5.033027</p> <p>Please cite as:</p> <p>Tzu-Chao Hung, Roberto Robles, Brian Kiraly, Julian H. Strik, Bram A. Rutten, Alexander A. Khajetoorians, Nicolas Lorente and Daniel Wegner. Dataset supporting the paper "Bipolar single-molecule electroluminescence and electrofluorochromism. Physical Review Research 5, 033027 (2023)" DOI:10.5281/zenodo.13768737</p> <p>List of files:</p> <p>Several folders corresponding to the figures of the paper. They contain:</p> <p>CONTCAR files: relaxed structures in VASP format. They can be visualized with VESTA (https://jp-minerals.org/vesta/en/).</p> <p>.agr: grace files (https://plasma-gate.weizmann.ac.il/Grace/).</p> <p>Image files in png format.</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.