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Dataset results
229 results for “Energy use”
Dataset 3 for paper: "Estimation of free energy of ligand binding using Multi-eGO"
<p>Dataset 3 contains Abeta42 dataset:</p> <ul> <li>APO: reference and multi-eGO simulations</li> <li>HOLO: reference and multi-eGO simualtions</li> <li>Titration at multiple concentrations with two different multi-eGO parameters</li> </ul>
Dataset 2 for paper "Esimation of free energy of ligand binding using Multi-eGO"
<p>Dataset2 contains Kinase dataset and part of Lysozyme-Benzene dataset:</p> <p>LYZ-BNZ:</p> <ul> <li>Unbiased binding simulations</li> </ul> <p>Kinase:</p> <ul> <li>APO trainng, reference, and multi-eGO simulations</li> <li>HOLO training, reference and multi-eGO simulations of both Dasatinib and PP1</li> <li>Thermodynamic integration of both Dasatinib and PP1</li> </ul> <p> </p> <p> </p>
Dataset 1 for paper: "Estimation of free energy of ligand binding using Multi-eGO"
<p>The dataset 1 contains Lysozyme-Benzene dataset:</p> <ul> <li>APO training, reference and multi-eGO simulations</li> <li>HOLO training, reference and multi-eGO simulations</li> <li> Thermodynamic integration calculations, Volume based metadynamics</li> </ul>
Results and plotting scripts for the manuscript 'SuCCESs – a global IAM for exploring the interactions between energy, materials, land-use and climate systems in long-term scenarios'
<p><br>This archives the results for the manuscript 'SuCCESs – a global IAM for exploring the interactions between energy, materials, land-use and climate systems in long-term scenarios'</p> <p>For the model version used to create these results, please see: https://doi.org/10.5281/zenodo.13981520</p> <p>Files to reproduce the figures, in R language:<br>SuCCESs validation.R - Reads GDX files and produces plots for energy and emissions.<br>SuCCESs validation MC.R - The same, but with the Monte Carlo GDXs.</p> <p>External data sources:</p> <p>***<br>GHG emissions are from IGCC and PRIMAP</p> <p>IGCC: https://climatechangetracker.org/igcc (CC-BY license)</p> <p>PRIMAP:<br>Gütschow, Johannes; Jeffery, M. Louise; Gieseke, Robert; Gebel, Ronja; Stevens, David; Krapp, Mario; Rocha, Marcia (2016): The PRIMAP-hist national historical emissions time series, Earth Syst. Sci. Data, 8, 571-603, https://doi.org/10.5194/essd-8-571-2016<br>Gütschow, Johannes ; Busch, Daniel ; Pflüger, Mika (2024): The PRIMAP-hist national historical emissions time series (1750-2023) v2.6. Zenodo. https://doi.org/10.5281/zenodo.13752654<br>https://primap.org/primap-hist/ (CC-BY-4.0 license)</p> <p>***<br>Historical energy production and use data are from IEA Energy Statistics Data Browser (CC BY 4.0 licence).<br>https://www.iea.org/data-and-statistics/data-tools/energy-statistics-data-browser?country=WORLD&fuel=CO2%20emissions&indicator=CO2BySource</p> <p>***<br>IAM results are from the SSP database: https://tntcat.iiasa.ac.at/SspDb </p> <p>Keywan Riahi, Detlef P. van Vuuren, Elmar Kriegler, Jae Edmonds, Brian C. O’Neill, Shinichiro Fujimori, Nico Bauer, Katherine Calvin, Rob Dellink, Oliver Fricko, Wolfgang Lutz, Alexander Popp, Jesus Crespo Cuaresma, Samir KC, Marian Leimbach, Leiwen Jiang, Tom Kram, Shilpa Rao, Johannes Emmerling, Kristie Ebi, Tomoko Hasegawa, Petr Havlík, Florian Humpenöder, Lara Aleluia Da Silva, Steve Smith, Elke Stehfest, Valentina Bosetti, Jiyong Eom, David Gernaat, Toshihiko Masui, Joeri Rogelj, Jessica Strefler, Laurent Drouet, Volker Krey, Gunnar Luderer, Mathijs Harmsen, Kiyoshi Takahashi, Lavinia Baumstark, Jonathan C. Doelman, Mikiko Kainuma, Zbigniew Klimont, Giacomo Marangoni, Hermann Lotze-Campen, Michael Obersteiner, Andrzej Tabeau, Massimo Tavoni.<br>The Shared Socioeconomic Pathways and their energy, land use, and greenhouse gas emissions implications: An overview, Global Environmental Change, Volume 42, Pages 153-168, 2017,<br>DOI:110.1016/j.gloenvcha.2016.05.009</p> <p>Rogelj, J., Popp, A., Calvin, K.V., Luderer, G., Emmerling, J., Gernaat, D., Fujimori, S., Strefler, J., Hasegawa, T., Marangoni, G., Krey, V., Kriegler, E., Riahi, K., van Vuuren, D.P., Doelman, J., Drouet, L., Edmonds, J., Fricko, O., Harmsen, M., Havlik, P., Humpenöder, F., Stehfest, E., Tavoni, M., Scenarios towards limiting global mean temperature increase below 1.5 °C. Nature Climate Change 8, 2018, 325-332.<br>DOI:10.1038/s41558-018-0091-3</p>
Using Machine Learning With Supplementary NC Code To Predict Machining Energy - Excel Documents
<p>The Excel Files Housed within this DOI represent the raw data collected during machining each of the test parts, and the excel documents made which prevent model summaries for each model created., during the execution of the, "Using Machine Learning With Supplementary NC Code to Predict Machining Energy. These files were created by Samuel D. Stencel, a Graduate Research Assistant and Purdue University.</p>
The influence coefficients used in Wind Energy Science paper "A computationally efficient engineering aerodynamic model for swept wind turbine blades"
<p>The influence coefficients for the convective correction with full double-precision floating-point accuracy. This is the supplement for the research article: "A computationally efficient engineering aerodynamic model for swept wind turbine blades", submitted to Wind Energy Science journal.</p> <p>Code language: Fortran</p>
Supplementary Table S1 from "Temperature-Dependent Estimation of Gibbs Energies Using an Updated Group-Contribution Method"
<p>Supplementary Table S1 containing reaction and compound thermodynamic data used for making temperature and ion concentration corrections to thermodynamic estimates for aqueous biochemical reactions.</p>
Supplementary Data for "Comprehensive Phase Diagrams of MoS2 Edge Sites Using Dispersion-Corrected DFT Free Energy Calculations"
<p>MoS2 Phase Diagrams to accompany DOI: 10.1021/acs.jpcc.8b02524</p>
Supplementary Data for Manuscript : "Application of OSL surface exposure dating with the use of two-dimensional OSL laser scanning instruments and energy-dispersive x-ray spectroscopy'
<p>Contains all supplementary works mentioned in the manuscript.</p>
Supplementary Documents for Manuscript 'Investigating the use of two-dimensional OSL laser scanning instruments and energy-dispersive x-ray spectroscopy for OSL exposure dating'
<p>Appendix Data for Manuscript 'Investigating the use of two-dimensional OSL laser scanning instruments and energy-dispersive x-ray spectroscopy for OSL exposure dating' - with added "Readme's" for relevant databases.</p>
Dataset for the paper "Deblending and Purification of Hydrogen from Natural Gas Mixtures using the Electrochemical Hydrogen Pump", International Journal of Hydrogen Energy, doi.org/10.1016/j.ijhydene.2023.05.065
<p>The data in this spreadsheet was used to produce the figures in the paper</p> <p>Authors:C Jackson, GT Smith, ARJ Kucernak</p> <p>Title:Deblending and Purification of Hydrogen from Natural Gas Mixtures using the Electrochemical Hydrogen Pump</p> <p>Journal:International Journal of Hydrogen Energy</p> <p>DOI:https://doi.org/10.1016/j.ijhydene.2023.05.065</p> <p>Please cite the above reference if you wish to use this data</p> <p>DOI of data:10.5281/zenodo.7963348</p>
Supporting Information for "Broadening the scope of binding free energy calculations using a Separated Topologies approach"
<p>Supporting Information for the publication "Broadening the scope of binding free energy calculations using a Separated Topologies approach" including input files for the datasets used in that study.</p>
Replication Package for "An Exploratory Literature Study on Sharing and Energy Use of Language Models for Source Code"
<p>This repository contains the replication package for the paper <em>"</em>An Exploratory Literature Study on Sharing and Energy Use of Language Models for Source Code" by Max Hort, Anastasiia Grishina, and Leon Moonen, accepted for publication in the 17th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM 2023).</p> <p>The paper is deposited on arXiv, will be available later at the publisher's site (<a href="https://ieeexplore.ieee.org/Xplore/home.jsp">IEEE</a>), and a copy is included in this repository.</p> <p>The replication package is archived on Zenodo with DOI: <a href="https://doi.org/10.5281/zenodo.8058667">10.5281/zenodo.8058667</a>. The data is distributed under the CC BY 4.0 license.</p> <p> </p> <p><strong>Citation</strong></p> <p>If you build on this data or code, please cite this work by referring to the paper:</p> <pre><code>@inproceedings{hort2023:sharing, title = {An Exploratory Literature Study on Sharing and Energy Use of Language Models for Source Code}, author = {Max Hort and Anastasiia Grishina and Leon Moonen}, booktitle = {17th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM 2023)}, year = {2023}, publisher = {IEEE} note = {To appear. Pre-print on arXiv.} }</code></pre>
Supplementary Documents for Manuscript 'Investigating the use of two-dimensional OSL laser scanning instruments and energy-dispersive x-ray spectroscopy for OSL exposure dating'
<p>This file contains all the supplementary material for the manuscript 'Investigating the use of two-dimensional OSL laser scanning instruments and energy-dispersive x-ray spectroscopy for OSL exposure dating' sent to Radiation Measurements on 8/20/2023.</p>
Energy dissipation of a carbon monoxide molecule manipulated using a metallic tip on copper surfaces
<p>Computational dataset for our research papers on energy dissipation of a carbon monoxide molecule manipulated using a metallic tip on copper surfaces:<br><br></p> <p>N. Okabayashi, T. Frederiksen, A. Liebig, and F. J. Giessibl<br><em>Dynamic friction unraveled by observing an unexpected intermediate state in controlled molecular manipulation</em><br><a href="https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.131.148001">Phys. Rev. Lett. <strong>131</strong>, 148001 (2023)</a></p> <p>N. Okabayashi, T. Frederiksen, A. Liebig, and F. J. Giessibl<br><em>Energy dissipation of a carbon monoxide molecule manipulated using a metallic tip on copper surfaces</em><br><a href="https://journals.aps.org/prb/abstract/10.1103/PhysRevB.108.165401">Phys. Rev. B <strong>108</strong>, 165401 (2023)</a></p>
Computing free energies of fold-switching proteins using MELD x MD
<p>In this Zenodo repository, we provide the MELD script and data for a few representative systems in the DP-MELD.zip, GA_GB-MELD.zip, and RfaH-MELD.zip files. The contents of the repository are described below:</p> <ol> <li> <p>MELD Simulation:</p> <ul> <li>Filename: DP-MELD.zip, GA_GB-MELD.zip, and RfaH-MELD.zip</li> <li>Description: These archives contain the necessary files and scripts for the MELD simulation.</li> </ul> </li> <li> <p>Setup Script:</p> <ul> <li>Filename: setup.py</li> <li>Description: This script is used to set up the MELD simulation.</li> </ul> </li> <li> <p>Trajectory Analysis Script:</p> <ul> <li>Filename: Clustering.sh</li> <li>Description: This script analyzes the trajectories obtained from the MELD simulation.</li> </ul> </li> <li> <p>Protein Information:</p> <ul> <li>Location: TEMPLATES folder</li> <li>Files: <ul> <li>Protein topology file: .top</li> <li>Coordinate file: .crd</li> <li>PDB file: .PDB</li> </ul> </li> <li>Description: These files provide input information for a few representative proteins.</li> </ul> </li> <li> <p>Residue-Residue Contact Information:</p> <ul> <li>Files: <ul> <li>contact_model1.dat</li> <li>contact_model2.dat</li> </ul> </li> <li>Description: These files contain information about the contacts between residues.</li> </ul> </li> <li> <p>Replica Trajectory Files:</p> <ul> <li>Filename: trajectory.00.dcd</li> <li>Description: These files contain the trajectories obtained from the simulation for the corresponding bottom replica.</li> </ul> </li> <li>Clustering Output: <ul> <li>Folders: Cluster_6 or Cluster_3.5</li> <li>Description: These folders contain the results of the clustering analysis, including the computed population and the average conformers for each cluster.</li> </ul> </li> </ol> <p>Furthermore, we provide an additional archive called unfold.zip:</p> <ol> <li>Unfolded Ensemble: <ul> <li>Filename: unfold.zip</li> <li>Description: This archive contains the unfolded ensemble, which is used to determine the force required for rebalancing two group springs for the MELD run between two conformers (A and B) before executing the MELD simulation.</li> </ul> </li> </ol>
Survey data on norwegian household energy use, with focus on solar PV, flexible energy use, and retrofitting in 2023 (variables dictionary)
<p>A variable dictionary (both in Norwegian and English) is added. Please note that Norwegian characters like <strong>ø</strong> may not display correctly in the webpage preview.<br>To view them properly, download the CSV file—all characters will appear correctly there.</p>
Vey Low-Energy Ketogenic Therapy in Adults With Type 1 Diabetes and Obesity on Intensive Insulin Therapy Using Advanded Hybrid Closed Loop System
ClinicalTrials.gov study NCT07185555. IPD Sharing: Not stated. Countries: 1. Publications: 16.
Review of Efficacy of Used ultraSonic Energy Device
ClinicalTrials.gov study NCT04226482. IPD Sharing: NO. Countries: 1. Publications: 38.
Use of Low-level Laser Therapy on Children Aged One to Five Years With Energy-protein Malnutrition
ClinicalTrials.gov study NCT03355313. IPD Sharing: YES. Countries: 1. Publications: 11.
ScienceDex guides
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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.