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4,230 results for “Energie”
Research data for: Patchy energy landscapes promote stability of small groups of active particles
<p>Research data supporting the pubblication "Patchy energy landscapes promote stability of small groups of active particles"</p>
Archetype-Based Redshift Estimation for the Dark Energy Spectroscopic Instrument Survey
<p>Supplementary material to DESI's publication "Archetype-Based Redshift Estimation for the Dark Energy Spectroscopic Instrument Survey" by Anand et al. 2024 to comply with the data management plan. The material includes all the data shown in the figures of the results of the paper.</p>
eELib: Open-Source Model Library for Prosumer Power Systems and Energy Management Strategies (data)
<p>Dataset and results used for the simulations in following publication:</p> <p>Carsten Wegkamp, Henrik Wagner, Eike Niehs, Julien Essers, Marcel Lüdecke, Mattias Hadlak, Bernd Engel:<br>"<strong>eELib: Open-Source Model Library for Prosumer Power Systems and Energy Management Strategies</strong>",<br>Open Source Modelling and Simulation of Energy Systems (OSMSES) 2024, Vienna, Austria, 2024</p> <p> </p> <p>This contains the input (scenario) files for the building & grid scenario and the results of the two simulations.<br>It uses the elenia Energy Library (eELib) with release version 1.0.0: https://gitlab.com/elenia1/elenia-energy-library</p>
Energy-Dependent, Self-Adaptive Mesh h(p)-Refinement of a Constraint-Based Continuous Bubnov-Galerkin Isogeometric Analysis Spatial Discretisation of the Self-Adjoint Angular Flux Form of the Multi-Group Neutron Transport Equation with Dual-Weighted Residual Error Measures
<p>This repository holds all of the raw data generated by my (Modern) Fortran code for a paper "Energy-Dependent, Self-Adaptive Mesh h(p)-Refinement of a Constraint-Based Continuous Bubnov-Galerkin Isogeometric Analysis Spatial Discretisation of the Self-Adjoint Angular Flux Form of the Multi-Group Neutron Transport Equation with Dual-Weighted Residual Error Measures".</p> <p>The (Modern) Fortran code solves the SAAF form of the multi-group neutron transport equation using novel NURBS-based, IGA spatial discretisations.</p>
Fig. 1 in Difference in reproduction energy content in muscles on fish from reservoirs in Paraná State, Brazil
Fig. 1. Location of the reservoirs sampled in the present study, Paraná State.
Wind Value: First Conference 2022, Research Opportunities for Wind Energy, Dave Linehan, Video
<p>VIdeo of 9 mins and 35 seconds, on the Research Opportunities for the Wind Energy Sector, by Dave Linehan of Wind Energy Ireland.</p>
Dataset for the paper "Ocean wave energy harvesting with high energy density and self-powered monitoring system"
<p>Dataset for the paper "Ocean wave energy harvesting with high energy density and self-powered monitoring system“.</p>
Dataset for the paper "Haiyi Wang, Xiaoqian Lin, Anthony Kucernak, 'Avoid using Phosphate Buffered Saline (PBS) as an Electrolyte for Accurate OER Studies', ACS ENERGY LETTERS, 2024, doi.org/10.1021/acsenergylett.4c01589
<div>The data in this spreadsheet was used to produce the figures in the paper</div> <div>Authors: Haiyi Wang, Xiaoqian Lin, Anthony Kucernak</div> <div>Title: Avoid using Phosphate Buffered Saline (PBS) as an Electrolyte for Accurate OER Studies</div> <div>Journal: ACS Energy Letters</div> <div>DOI: https://doi.org/10.1021/acsenergylett.4c01589</div> <div>Please cite the above reference if you wish to use this data</div> <div> </div> <div>DOI of data: 10.5281/zenodo.12750914</div> <p> </p>
Dataset for the manuscript "Osmotic Energy Conversion in Serpentinite-Hosted Deep-Sea Hydrothermal Vents"
Open the record for dataset details and reuse information.
Modeling and simulation of a new Urban Lightweight Electric Vehicle concept based on the optimized use of renewable energies and the reduction of CO2 emissions
<p>This work has produced a series of scientifc contributions. This library develops different mathematical expressions and assumptions for the dynamic modelling of an smart-grid located within a solar-powered ULEV are derived. The code was developed using Dymola</p>
Bayesian analysis of (3+1)D relativistic nuclear dynamics with the RHIC beam energy scan data
<p>This dataset contains the MCMC chain (LHD+HPP) without any constraints on the parameters for the (3+1)D Bayesian inference study for the RHIC beam energy scan program.<br>We also provide the nine trained emulator objects, which were generated with the code available at <a title="GPBayesTools-HIC: v1.1.0" href="https://doi.org/10.5281/zenodo.12807892" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.12807892</a>.<br>The training data is given in pickle format as dictionaries for the training points. The first 1000 points in the files correspond to the Latin Hypercube design points and the last 100 points are points sampled from the posterior distribution.</p>
Machine Learning Guided AQFEP: A Fast & Efficient Absolute Free Energy Perturbation Solution for Virtual Screening
<p>Data to reproduce primary figures in the manuscript titled: Machine Learning Guided AQFEP: A Fast & Efficient Absolute Free Energy Perturbation Solution for Virtual Screening.</p> <p>URL: https://chemrxiv.org/engage/chemrxiv/article-details/6583785e66c1381729ac86f5</p>
Raw Data for Energy Consumption Comparison of DMA-Based and FatFs Storage Systems on Wearable Devices
<p>This dataset contains raw oscilloscope measurements comparing the energy consumption of a Direct Memory Access (DMA)-based storage system versus the FatFs file system for wearable devices. The data was collected as part of the study "Direct Memory Access-Based Data Storage for Long-Term Acquisition Using Wearables in an Energy-Efficient Manner".</p> <p>The dataset includes voltage drop measurements across a 2-ohm shunt resistor, captured using an Analog Discovery 2 digital oscilloscope at a 500 kHz sampling rate. Measurements were taken under various conditions:</p> <ul> <li>Storage systems: DMA-based (proposed) and FatFs</li> <li>SD card capacities: 4 GB and 8 GB</li> <li>Write frequencies: 2 Hz and 5 Hz (referring to the frequency of writing a specific data block of 15,872 bytes)</li> <li>With and without a smoothing capacitor</li> </ul> <p>Each CSV file contains 20 million samples, equivalent to 40 seconds of data acquisition. File names encode the experimental conditions, including the storage system, write frequency, number of samples, acquisition rate, acquisition time, data format, SD card size, and absence of the smoothing capacitor.</p> <p>The data is organized into two main folders:</p> <ol> <li>"cap": Contains measurements with the smoothing capacitor</li> <li>"no_cap": Contains measurements without the smoothing capacitor</li> </ol> <p>This raw data can be used to reproduce the energy consumption and write speed analyses presented in the article, as well as for further investigation into the performance of embedded storage systems for wearable devices.</p>
Figure 2. Energy dispersive X in Morphological, optical and thermal properties of α- and γ-aluminum nanoparticles: Assessment of their biological activities against storage mites and mycotoxin producing fungi
Figure 2. Energy dispersive X-ray spectroscopy of α - and γ-Al2O3NPs.
Raw data on Renewable Energies
<p>Raw data corresponding to the paper "Worldwide trends in research, funding and international collaboration on renewable energies"</p>
Water and energy fluxes measurements over a riparian Tamarix spp. stand in the lower Tarim River basin, northwestern China
<p>This dataset includes water and energy fluxes measurements over a riparian <em>Tamarix spp.</em> stand in the lower Tarim River basin, northwestern China. Details of field site and measurements can be found in the paper: Yuan, G., P. Zhang, M.-a. Shao, Y. Luo, and X. Zhu (2014), Energy and water exchanges over a riparian Tamarix spp. stand in the lower Tarim River basin under a hyper-arid climate, Agricultural and Forest Meteorology, 194(0), 144-154.</p> <p>This dataset also accompanies the published paper in the Water Resources Research: Implementing Dynamic Root Optimization in Noah‐MP for Simulating Phreatophytic Root Water Uptake. Water Resources Research 54(3), 1560-1575. With this dataset, we tested the Noah-MP land surface model with implementation of a soil moisture-responsive root dynamics scheme (VOM-ROOT). </p>
The influence of waves on morphodynamic impacts of energy extraction at a tidal stream turbine site in the Pentland Firth: MIKE3 HD result files
<p>This dataset consists of the MIKE3 HD result files from simulations conducted for the paper 'The influence of waves on morphodynamic impacts of energy extraction at a tidal stream turbine site in the Pentland Firth' ( <a href="https://doi.org/10.1016/j.renene.2018.02.035">https://doi.org/10.1016/j.renene.2018.02.035</a> )</p> <p>Sets of 2D area result files are provided for sediment transport results (ST in file name), hydrodynamic results (HD in file name) and spectral wave results (SW in file name) in different datasets. This dataset contains HD files.</p> <p>Each file name provides details of the resuls contained: time of simulation (Jan or Jun); presence (Turb) or abscence (NoTurb) of tidal stream turbines in the simulations; and inclusion of waves in the simulations (tideAndWave or tide_only).</p> <p>Details of the methodology are given in the above paper. Please reference the paper in any use of these results.</p>
DirtyGrid: 3D dust radiative transfer modeling of spectral energy distributions of dusty stellar populations
<p>Output global SEDs of a large grid of 3D stellar+dust radiative transfer models spanning the range of star formation and dust contents of regions of galaxies.</p> <p>Paper describing the DirtyGrid is Law, Gordo, & Misset (2018, ApJ, submitted)</p> <p>Code to make to access this data at: https://github.com/karllark/pydirtygrid</p>
Input Data for paper "Energy Storage Profit Risk under Stochastic Fuel Prices"
<p>This is a supplementary information accompanying "Energy Storage Profit Risk under Stochastic Fuel Prices" paper submitted to <a href="https://www.journals.elsevier.com/energy-economics/">Energy Economics</a>.</p>
Dataset: Direct insertion of NASA Airborne Snow Observatory-derived snow depth time-series into the iSnobal energy balance snow model
<p>This dataset is a companion to the submitted WRR publication entitled ‘Direct insertion of NASA Airborne Snow Observatory-derived snow depth time-series into the iSnobal energy balance snow model’. The file structure is organized as follows:</p> <ul> <li><strong>ASO_50m_depth_surfaces</strong> - This folder contains the Airborne Snow Observatory lidar-derived snow depth products aggregated to 50m gridded spatial resolution. Each file is titled with a date such as ‘TB<em>YYYYMMDD</em>_SUPERsnow_depth.asc’. The coordinates are in UTM zone 11N and use the WGS84 coordinate system.</li> <li><strong>static_grids</strong> <ul> <li>Static grids are used in each of the subsequent folders and are not changed between years.</li> <li>init0000.ipw <ul> <li>Initialization file to begin the model run. Contains the digital elevation model in band 1, surface roughness raster in band 2, and zeroed images of snow properties in bands 3-7.</li> </ul> </li> <li>maxus.nc <ul> <li>netCDF file of 72 separate images of maximum upwind slope for all upwind directions from 0 (north) to 355 degrees in 5-degree increments. Derived using Adam Winstral’s Sx algorithm.</li> </ul> </li> <li>tuolx_dem_50m.ipw <ul> <li>Digital elevation model from ASO snow-free acquisition aggregated to 50m gridded spatial resolution. Same information as band 1 in the init0000.ipw file.</li> </ul> </li> <li>tuolx_hetchy_mask_50m.ipw <ul> <li>Basin mask of the Tuolumne River Basin above Hetch Hetchy Reservoir. Out-of-basin cells denoted as 0, and in-basin cells denoted as 1.</li> </ul> </li> <li>tuolx_vegheight_50m.ipw <ul> <li>Vegetation height raster in meters. Derived from NLCD dataset of vegetation type..</li> </ul> </li> <li>tuolx_vegk_50m.ipw <ul> <li>Emissivity of the vegetation canopy. Derived from NLCD dataset of vegetation type.</li> </ul> </li> <li>tuolx_vegnlcd_50m.ipw <ul> <li>Vegetation type from the National Land Cover Database.</li> </ul> </li> <li>tuolx_vegtau_50m.ipw <ul> <li>Fractional transmissivity of the vegetation canopy. Derived from NLCD dataset of vegetation type.</li> </ul> </li> </ul> </li> <li><strong>level1_raw_data</strong> <ul> <li>{Hourly data interpolated to nearest hour from downloaded raw data (CDEC/MesoWest)}</li> <li>air_temp_level1.csv</li> <li>precip_accum_level1.csv</li> <li>relative_humidity_level1.csv</li> <li>solar_radiation_level1.csv</li> <li>wind_direction_level1.csv</li> <li>wind_speed_level1.csv</li> </ul> </li> </ul> <p>The directories for each water year contain the configuration file for that year along with the vector meteorological data from measurement sites and site metadata in .csv format.</p> <ul> <li><strong>wy2013</strong></li> <li><strong>wy2014</strong></li> <li><strong>wy2015</strong></li> <li><strong>wy2016</strong> <ul> <li> <ul> <li>backup_config.ini {Initialization file used to distribute station data over a regular grid for each water year.}</li> <li>air_temp.csv</li> <li>cloud_factor.csv</li> <li>metadata.csv</li> <li>precip.csv</li> <li>vapor_pressure.csv</li> <li>wind_direction.csv</li> <li>wind_speed.csv</li> <li><strong>data/</strong> <ul> <li>[subdirectory containing all future created forcing grid files]</li> </ul> </li> <li><strong>runs/</strong> <ul> <li>[subdirectory containing all <em>iSnobal</em> output files in addition to reinitialization scripts for ASO snow depth updates]</li> </ul> </li> </ul> </li> </ul> </li> </ul>
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.