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4,230 results for “Energie”
Sector-coupled model for the German energy system in 2019
<p>This repository contains input data for the open-source Python tool <a href="https://github.com/openego/eTraGo">eTraGo</a> (<strong>e</strong>lectricity <strong>Tra</strong>nsmission <strong>G</strong>rid <strong>o</strong>ptimization) version 0.10.0.<br>This data will be uploaded to the <a href="https://openenergy-platform.org/">OpenEnergy Platform</a> which can be accessed by eTraGo. This dataset is an intermediate solution until the data is uploaded.</p> <p>The published data includes the sector-coupled transmission grid data for the scenario <em>status2019</em>. It was created with the open-source tool <a href="https://github.com/openego/powerd-data">powerd-data</a> within the research project <a href="https://h2-powerd.de/">PoWerD</a>. All input data sets as well as the code are available under open source licenses.</p> <p>We thank the Federal Ministry for Economic Affairs and Climate Action for funding the research project PoWerD (grant number: 03EI1042C)</p> <p>The data is stored as a PostgreSQL database in the attached backup file. First, the required schemas and extensions have to be created within the database by running the following SQL statements:</p> <p><code>CREATE EXTENSION postgis;</code></p> <p>Afterwards, the data can be restored by using e.g. pgAdmin or via PostgreSQL's <a href="https://www.postgresql.org/docs/current/app-pgrestore.html">pg_restore</a> command (replace <code>HOST</code>, <code>DATABASE_NAME</code>, <code>PORT</code> and <code>USER</code> by your settings):</p> <p><code>pg_restore --host HOST --port PORT --username USER --no-password --dbname </code><code>DATABASE_NAME --no-owner --no-privileges --verbose "PoWerD_status2019_v3.backup"</code></p>
Moisture-based green energy harvesting over 600 hours via photocatalysis-enhanced hydrovoltaic effect
<p>Source Date</p>
data for "Importance of Strains in Kinetic Energy Conversion for Submesoscale Processes from an Anisotropic Perspective "
Open the record for dataset details and reuse information.
Data for the paper: Increasing the flexibility and feasibility of CSP by the addition of a low temperature energy storage system
Open the record for dataset details and reuse information.
UWB Ranging and Localization Dataset for "High-Accuracy Ranging and Localization with Ultra-Wideband Communication for Energy-Constrained Devices"
<pre><strong>UWB Ranging and Localization Dataset for "High-Accuracy Ranging and Localization with Ultra-Wideband Communication for Energy-Constrained Devices" </strong> This dataset accompanies the paper "<strong>High-Accuracy Ranging and Localization with Ultra-Wideband Communication for Energy-Constrained Devices</strong>," by <em>L. Flueratoru, S. Wehrli, M. Magno, S. Lohan, D. Niculescu</em>, accepted for publication in the IEEE Internet of Things Journal. Please refer to the paper for more information about analyzing the data. If you find this dataset useful, please consider citing our paper in your work. This dataset is split into two parts: "ranging" and "localization." Both parts contain measurements acquired with 3db Access and Decawave MDEK1001 UWB devices. In the "3db" and "decawave" datasets, when a recording has the same name, it means that the measurements were acquired at the exact same locations with the two types of devices. The "3db" ranging dataset contains, apart from these, more measurements acquired in various LOS and NLOS scenarios. In the directory "images" you can find photos of some of the setups. The "ranging" and "localization" directories both contain a "data" directory which holds the datasets and a "code" directory with Python scripts that show how to read and analyze the data. The 3db Access <em>ranging</em> recordings contain the following data: - True distance - Measured distance - Channel on which the measurements were acquired (can be 6.5, 7, or 7.5 GHz) - Time of arrival as identified by the chipset - Channel impulse response (CIR) - Line-of-sight (LOS)/non-line-of-sight (NLOS) scenario (encoded as 0 and 1, respectively) - If NLOS, the type of NLOS obstruction and its tickness. The Decawave <em>ranging</em> recordings contain the following data: - True distance - Measured distance - Line-of-sight (LOS)/non-line-of-sight (NLOS) scenario (encoded as 0 and 1, respectively) - If NLOS, the type of NLOS obstruction and its tickness. The MDEK kit operates only on the 6.5 GHz channel and cannot output the CIR without further code modifications, which is why this data is not available for the Decawave dataset. The <em>localization</em> dataset includes the following data: - True location as measured by an HTC Vive system - Estimated location using a Gauss-Newton trilateration algorithm (please refer to the paper for more details) - Distance measurements between each anchor and the tag. </pre>
Photostable Ruthenium(II) Isocyanoborato Luminophores and Their Use in Energy Transfer and Photoredox Catalysis
<p>Electronic data accompanying the publication in <em>JACS Au</em> <strong>2021</strong>,<em>1</em>, 819–832; https://pubs.acs.org/doi/10.1021/jacsau.1c00137</p>
Weather dataset (Typical Downscaled Year, Extreme Cold Year, Extreme Warm Year) for building energy simulations (.epw format) in future climate (2069-2098, RCP 8.5), Kortrijk Kennedy Park, Belgium
<p>Typical Downscaled Year (TDY), Extreme Cold Year and Extreme Warm Year based on the methodology of Nik (2016), is extracted for the location of Kortrijk Kenny Park (50° 48' 2"N 3°16'13" E) from the EC-Earth driven convection-permitting climate model COSMO-CLM for the Belgian domain extended with land-surface scheme TERRA_URB(v2.0) making use of the SURY (Semi-empirical URban canopY) parameterization ( Wouters et al. 2016). The integrations are identical to the ones which are described in Vanden Broucke et al. (2019). The climate model has a spatial resolution of 2.8 km and an hourly temporal resolution and is available for the recent past (1976-2004) and future (2070-2098, RCP 8.5 climate change scenario) as 30-year datasets. For this dataset, the TDY, ECY, and EWY are extracted for the future period. A bias correction is applied for the following variables: temperature (as described in Ramon et al. 2020), solar radiation and relative humidity as described in Ramon et al. (202X).</p>
Weather dataset (Typical Downscaled Year, Extreme Cold Year, Extreme Warm Year) for building energy simulations (.epw format) in recent past climate, Sint-Katelijne-Waver, Belgium
<p>Typical Downscaled Year (TDY), Extreme Cold Year and Extreme Warm Year based on the methodology of Nik (2016), is extracted for the location of Sint-Katelijne-Waver (51°3'25"N 4°11'24" E) from the EC-Earth driven convection-permitting climate model COSMO-CLM for the Belgian domain extended with land-surface scheme TERRA_URB(v2.0) making use of the SURY (Semi-empirical URban canopY) parameterization ( Wouters et al. 2016). The integrations are identical to the ones which are described in Vanden Broucke et al. (2019). The climate model has a spatial resolution of 2.8 km and an hourly temporal resolution and is available for the recent past (1976-2004) and future (2070-2098) as 30-year datasets. For this dataset, the TDY, ECY, and EWY are extracted for the recent past period. A bias correction is applied for the following variables: temperature (as described in Ramon et al. 2020), solar radiation and relative humidity as described in Ramon et al. (202X).</p>
Comprehensive result data for a pathway for the German energy sector compatible with a 1.5°C carbon budget
<p>This data set covers the results of an energy scenario for Germany within a 1.5°C carbon budget. It represents all relevant results from an energ system modelling excersise, coupling two complementary models.</p> <p>The data set consists of two excel files</p> <ul> <li>Comprehensive results of the energy balance based Energy System Model (ESM) for the heat, transport and power sectors for Germany, disaggregated by consumption sectors (residential, service & commerce, industry, transport)</li> <li>Comprehensive results of the linear optimization energy system model REMix for power, heat and sector coupling</li> </ul> <p>Methodology, models and scenario assumption are detailed in:</p> <p>Simon, S., Xiao, M., Harpprecht, C., Pregger, T., Gardian, H., & Sasanpour, S. (submitted). A pathway for the German energy sector compatible with a 1.5°C carbon budget. <em>Sustainability</em>.</p>
Alchemical Free Energy Estimators and Molecular Dynamics Engines: Accuracy, Precision and Reproducibility - Dataset
<p>This zip contains all input structures for paper the: Alchemical Free<br> Energy Estimators and Molecular Dynamics<br> Engines: Accuracy, Precision and Reproducibility</p> <p>Authors: Alexander D. Wade, Agastya P. Bhati, Shunzhou Wan, Peter V.Coveney</p> <p>The structures of the folders are protein/ligand_transformation/alchemical_leg/input/files</p> <p>The ligand transformation are derived from previous work by wang et al. (https://pubs.acs.org/doi/10.1021/ja512751q)</p> <p>There are two files for the solvent alchemical leg: complex.pdb and complex.prmtop</p> <p>complex.pdb is structure file that also denotes the alchemical atoms in the pdb beta column. complex.prmtop is an AMBER parameter/topology file</p> <p>For the complex alchemical leg there is an additional file constraints.pdb that contains the constraint information in the pdb beta column.</p> <p>These files can be used with TIES_MD (https://ucl-ccs.github.io/TIES_MD/) or other molecular dynamics engines that take AMBER input.</p>
Supplementary material 1 from: Adamov EO, Rachkov VI, Kashirsky AA, Orlov AI (2021) Global outlook on large-scale nuclear power development strategies. Nuclear Energy and Technology 7(4): 263-270. https://doi.org/10.3897/nucet.7.74217
Global outlook on large-scale nuclear power development strategies
Results from the test of the MCDA-MSS with the 56 case studies from the energy systems analysis literature
<p>Results from the test of the MCDA-MSS with the 56 case studies from the energy systems analysis literature</p>
Dataset: Cool birds: First evidence of energy-saving nocturnal torpor in free-living common swifts Apus apus resting in their nests
<p><a name="_Hlk94722524"></a><span>Daily torpor is a means of saving energy by controlled lowering of the metabolic rate (MR) during resting, usually coupled with a decrease in body temperature. We studied nocturnal daily torpor <span>under natural conditions</span> in free-living <span>common swifts <em>Apus apus</em> resting in their nests as a family using two non-invasive approaches. First, we monitored nest temperature (T<sub>nest</sub>) in up to 50 occupied nests per breeding season in 2010-2015. Drops in T<sub>nest</sub> were the first indication of torpor. Among </span></span><a name="_Hlk97457770"></a><span><span>16,673 </span></span><span><span>observations, we detected 423 events of substantial drops in T<sub>nest</sub> of on average 8.6°C. Second, we measured MR of the families inside nest boxes prepared for calorimetric measurements during cold periods in the breeding seasons of 2017 and 2018. We measured oxygen consumption and carbon dioxide production using a mobile indirect respirometer and calculated the percentage reduction in MR. During six torpor events observed, MR was gradually reduced by on average 56% from the reference value followed by a decrease in T<sub>nest</sub> of on average 7.6 °C. In contrast, MR only decreased by about 33% on nights without torpor. Our field data gave an indication of daily torpor, which is used as a strategy for energy saving in free-living common swifts.</span></span></p>
Lean mass dynamics in hibernating bats and implications for energy and water budgets
<p>Hibernation requires balancing energy and water demands over several months with no food intake for many species. Many studies have considered the importance of fat for hibernation energy budgets because it is energy dense and can be stored in large quantities. However, protein catabolism in hibernation has received less attention and whole animal changes in lean mass have not previously been considered. We used quantitative magnetic resonance body composition analysis to measure fat and lean mass in two systems of hibernating bats, emphasizing the importance of lean mass for energy and water budgets. For cave myotis ( Myotis velifer ), lean mass represented 38 and 25% (male and female respectively) of pre-hibernation mass gain. In Townsend's big-eared bats ( Corynorhinus townsendii ), lean mass accounted for 18 – 35% of mass change during hibernation, but lean only contributed 3 – 7% of the energy budget. Water is produced from the catabolism of both fat and lean, but net water production is much less than gross water production when accounting for the water required to excrete urea. Although most mammals can't rely on protein catabolism for metabolic water production due to the water cost of excreting urea, we propose a variation on the protein-for-water strategy whereby hibernators could temporally compartmentalize the benefits of protein catabolism to periods of torpor, and the water cost to periodic arousals when free drinking water is typically available. Combined, our analyses demonstrate that lean mass is dynamic in hibernation, with important functional consequences for both energy and water budgets. </p>
Which lower-limb joints compensate for destabilising energy introduced by unilateral treadmill belt accelerations delivered during walking in humans?
<p>Dataset including kinematics, kinetics, and mechanical powers during human walking with unilateral treadmill perturbations delivered in early or late stance.</p>
Lumiflavin molecular structures and energies
<p>List of lumiflavin molecular structures in Cartesian coordinates with respective energy, obtained in the work "Molecular Properties and Tautomeric Equilibria of Isolated Flavins".</p>
An accurate binding free energy method from end-state MD simulations (ANI_LIE test files)
<p>Required files are added.</p>
Dataset for Latella, I., Ben-Abdallah, P. Graphene-based autonomous pyroelectric system for near-field energy conversion. Sci Rep 11, 19489 (2021)
<p>This dataset contains data associated to plots published in the paper I. Latella and P. Ben-Abdallah, Graphene-based autonomous pyroelectric system for near-field energy conversion, Sci Rep 11, 19489 (2021), https://doi.org/10.1038/s41598-021-98656-8.</p> <p> </p>
Data Repo for "Crossover of high-energy spin fluctuations from collective triplon excitations to incoherent gapped magnetic modes in the cuprate ladders of Sr14-xCaxCu24O41"
<p>Data set for the paper "Crossover of high-energy spin fluctuations from collective triplon excitations to incoherent gapped magnetic modes in the cuprate ladders of Sr14-xCaxCu24O41"</p> <p>Preprint Available at: https://arxiv.org/abs/2201.05027</p> <p> </p>
UFO model for stop pair production to ttbar and missing energy
<p>stop pair production with ttbar and missing energy</p>
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.