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15 results for “Energy evolution”
Mining API Interactions to Analyze SoftwareRevisions for the Evolution of Energy Consumption (MSR'2021 Dataset)
<p><strong>Motivation</strong></p> <p>This repository contains the data-set used as a basis for our MSR'2021 paper <em>Mining API Interactions to Analyze Software Revisions for the Evolution of Energy Consumption</em>.</p> <p><strong>Description of the dataset</strong></p> <p>The dataset is stored in a file <em>msr_2021_dataset.csv</em> and contains the following data:</p> <ul> <li>id - an individual identifier</li> <li>sampleNr - a number identifying the group this sample relates to</li> <li>name - the name of the library examined</li> <li>className - the class name as an abbreviation</li> <li>method - the name of the executed method</li> <li>duration - duration of method execution</li> <li>durationAdjusted - duration after alignment between method trace and energy profile</li> <li>energyConsumption - computed energy consumption</li> <li>watts - recorded wattage</li> <li>`package-names` - per package uAPI profile</li> <li>uApi - the computed uAPI profile value</li> </ul> <p>The files <em>joule_anova_posthoc_result.csv</em> and <em>uAPI_anova_posthoc_result.csv</em> contain the results of the ANOVA and Tukey HSD posthoc analysis to determine accuracy and F1-score of the presented approach.</p> <p> </p> <p><strong>License</strong></p> <p>Creative Commons CC-BY</p>
Covid-19 - impact on evolution of energy demand
<p><strong>Consumo_elect_COVID_2020 & Consumo elect_COVID_2019</strong></p> <p>Dataset with register of energy demand in Spain. Timeframe: January to March (2019 & 2020)</p> <p> </p> <p><strong>Casos_COVID_ESPAÑA</strong></p> <p>Dataset with register of the evolution of the spread of Covid-19 in Spain. Break-down of data per region (CCAA). Timeframe: January to March 2020</p> <p> </p> <p><strong>Casos_COVID_mundo</strong></p> <p>Dataset with register of the evolution of the spread of Covid-19 in Spain. Break-down of data per country. Timeframe: January to March 2020</p>
Evolution of the price of electricity and the renewable energy production in Spain
<p>The dataset contains the evolution of electricity prices in Spain for the period 2020-11-01 to 2022-10-31. The average energy prices (in MWh) as a function of the market, the produced energy (in MW), as well as the renewable energy produced (in MW) by type (wind, solar, hydroelectric, etc.) are provided with a granularity of hours for the period of time mentioned above.</p> <p>The data has been obtained from the webpage: <a href="https://www.esios.ree.es/es/">https://www.esios.ree.es/es/</a>.</p> <p><strong>Disclaimer: </strong>Express consent was provided by Red Eléctrica de España (source and proprietary of the data) to gather the data using web scraping under the framework of a practicum from the Master in Data Science from the Universitat Oberta de Catalunya (UOC). Under no circumstance do they support the reuse of the data. We express our intention to use the data for the purpose of the activity and decline any commercial interest in the use of the data extracted.</p> <p>The data is published under a license: <strong>CC BY-NC-SA 4.0.</strong></p>
The contribution of plasma sheet bubbles to stormtime ring current buildup and evolution of the energy composition
<p>Supporting information for "The contribution of plasma sheet bubbles to stormtime ring current buildup and evolution of the energy composition" by Sciola et al. 2023 submitted to the Journal of Geophysical Research: Space Physics</p>
Data associated with: Haze evolution in temperate exoplanet atmospheres through surface energy measurements
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Dataset for publication "Composite MAX phase/MXene/Ni electrodes with a porous 3D structure for hydrogen evolution and energy storage application
<p>Dataset for publication "Composite MAX phase/MXene/Ni electrodes with a porous 3D structure for hydrogen evolution and energy storage application". The dataset contains relevant data and figures from the publication. Description on how to work with the dataset is given in the readme file. DOI for the original paper: DOI <a title="Link to landing page via DOI" href="https://doi.org/10.1039/D3RA07335A">https://doi.org/10.1039/D3RA07335A</a>.</p>
Output data: China's energy-water-land system co-evolution under carbon neutrality goal and climate impacts
<p>Outputs for Wang, J., Duan, Y., Wang, C., 2023. China’s energy-water-land system co-evolution under carbon neutrality goal and climate impacts. (In progress)</p> <p>Folder demeter contains the spatially downscaled land use/land cover datasets.<br> Folder tethys contains the spatially downscaled water withdrawal datasets.</p> <p>The sub-folder names correspond to the scenarios described in the paper.</p> <p>For landcover datasets, land type ratios in each grid are presented. Land types include water, forest, shrub, grass, urban, snow, sparse and crops.</p> <p>For water withdrawal datasets, “wd” = “water withdrawal spatially downscaled”, “twd” = “water withdrawal spatially and temporally downscaled”, “dom”=”domestic/municipal sector”, “elec”=”electricity sector”, ”irr”=”irrigation sector”, “liv”=”livestock sector”, “mfg”=”manufacturing/industry sector”, “min”=”mining/primary energy sector”, “nonag”=”non-agricultural sector”, “total”=”all sectors”.<br> </p>
GCAM-USA Raw Outputs for Khan et al. 2021 - Evolution of energy-water-agriculture interconnectivity across the U.S.
<p>GCAM-USA outputs for paper: Khan et al. 2021, Evolution of energy-water-agriculture interconnectivity across the U.S.</p>
Selection on dispersal drives evolution of metabolic capacities for energy production in female wing‐polymorphic sand field crickets, Gryllus firmus
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Data from: Effects of body plan evolution on the hydrodynamic drag and energy requirements of swimming in ichthyosaurs
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k-evolution: a relativistic N-body code for clustering dark energy
<p>This directory contains all the necessary data, codes, and notebooks to reproduce the results of the paper titled "k-evolution: a relativistic N-body code for clustering dark energy" (<a href="https://arxiv.org/abs/1910.01104">https://arxiv.org/abs/1910.01104</a>).</p> <p><br> This paper has also been published in JCAP which can be accessed at this link: <a href="https://iopscience.iop.org/article/10.1088/1475-7516/2019/12/011">https://iopscience.iop.org/article/10.1088/1475-7516/2019/12/011</a>.</p> <p>Directories</p> <ul> <li><strong>Analysis_notebooks_data</strong>: This directory includes the data and jupyter notebooks to reproduce the figures presented in the paper.</li> <li><strong>codes</strong>: This directory contains the data generated as part of the project.</li> <li><strong>supplementary</strong>: This directory contains the supplementary materials associated with the project.</li> </ul> <p>How to Use</p> <ol> <li>Download the files to your local machine.</li> <li>Navigate to the directory where the files are saved.</li> <li>Install the necessary packages</li> <li>Navigate to the "<strong>Analysis_notebooks_data</strong>" directory and open the Jupyter notebooks in your preferred environment.</li> <li>Run the cells in the notebooks to reproduce the figures.</li> <li>Navigate to the "<strong>codes</strong>" directory and use the appropriate code to generate and post-process the simulation data.</li> <li>Navigate to the "<strong>Analysis_notebooks_data</strong>" directory to access the simulation data.</li> </ol> <p><br> If you have any feedback or request feel free to email farbod.hassani@gmail.com</p>
Evolution of Total Energy Expenditure and Its Various Components in Active Rheumatoid Arthritis (RA)Treated With Anti-TNF Agents and Comparison With Healthy Subjects
ClinicalTrials.gov study NCT03346590. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Evolution of the Energy Expenditure During Hematopoietic Stem Cell Transplantation
ClinicalTrials.gov study NCT04535570. IPD Sharing: NO. Countries: 1. Publications: 0.
Relationship Between Evolution of Resting Energy Expenditure and Tumoral Response to Chemotherapy in Patients Suffering From Pancreas Cancer
ClinicalTrials.gov study NCT02921646. IPD Sharing: NO. Countries: 1. Publications: 0.
An Energy-Based Prognostic Framework to Predict Fatigue Damage Evolution in Composites
In this work, a prognostics framework to predict the evolution of damage in fiber-reinforced composites materials under fatigue loads is proposed. The assessment of internal damage thresholds is a challenge for fatigue prognostics in composites due to inherent uncertainties, existence of multiple damage modes, and their complex interactions. Our framework, considers predicting the balance of release strain energies from competing damage modes to establish a reference threshold for prognostics. The approach is demonstrated on data collected from a run-to-failure tension-tension fatigue experiment measuring the evolution of fatigue damage in carbon-fiber-reinforced polymer (CFRP) cross-ply laminates. Results are presented for the prediction of expected degradation by micro-cracks for a given panel with the associated uncertainty estimates.
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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.