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4,230 results for “Energie”
Free Energy-based Refinement of DNA Force Field via Modification of Multiple Non-bonding Energy Terms
<p>Relevant files of the benchmark DNA simulations.</p> <p>*.xtc --> truncated OPESE trajectory file.</p> <p>*.tar --> compressed initial structures.</p> <p>*.mdp --> GROMACS molecular dynamics parameter file.</p> <p>*.dat --> PLUMED input file for OPESE simulation.</p> <p> </p>
The dataset of "Evaluation of Digital Supply Chain Technology's Impact on Sustainability Under the Moderate Effect of Supply Chain Dynamism: An Empirical Research in the Chinese Energy Supply Chain"
<p>This dataset involves the data from the questionnaire, which come from the project "Evaluation of Digital Supply Chain Technology’s Impact on Sustainability Under the Moderate Effect of Supply Chain Dynamism: An Empirical Research in the Chinese Energy Supply Chain". It comprises three dimensions questions, technology, sustainability and supply chain dynamism. The datas come from two Chinese energy firms, <span>China Resources Power Zhejiang Company and Hunan HuaDian Changsha Electric Co., Ltd.</span></p>
Serious games for Serious Energy Solutions project dataset
<p>This dataset includes the chat transcripts from two iterations of playing the Serious Game New Shores: A game for Democracy with a more diverse (reflecting the public) and a less diverse group (reflecting policymakers). It also includes the results for all players in the 10 rounds of the two game iterations and the final reports produced by the serious game for each iteration. The aim of the project is to investigate the impact of diversity on decision-making for sustainability using a serious game as a research tool.</p>
Dataset for article "Prediction of thermal shock induced cracking in multi-material ceramics using a stress-energy criterion" published in Engineering Fracture Mechanics
<p>Dataset contains graphical outputs of the numerical analysis performed using Finite element method in finite elements software Ansys Mechanical. It contains also photoes of the tested specimens. Further, material data used for the numerical analysis and measured by authors are included in the csv file and all necessary input codes for the FE system Ansys creating data for graphs in the publication are provided in the subfolder "Models-Ansys" within "Data" directory.</p> <p> </p>
Experimental and simulated data for the article "Reassessing the role and lifetime of Qx in the energy transfer dynamics of Chlorophyll a"
<p>The .zip file contains:</p> <ul> <li>Linear absorption spectra of Chl a in EtOH, acetone, and benzonitrile (BN)</li> <li>Low-temperature emission and excitation anisotropy datasets of Chl a in isopropanol</li> <li>Transient absorption (TA) datasets of Chl a in EtOH, acetone, and BN after B- and Q-band excitation (including pump spectra)</li> <li>Transient absorption anisotropy (TAA) datasets of Chl a in acetone after B-band excitation (including a pump spectrum)</li> <li>Optimized geometries for the Q-band ESA calculations</li> <li><span>Geometries for normal modes used for PES construction</span></li> </ul>
Energy Decomposition Analysis for excited states: An Extension based on TDDFT
<p>The data contain the test results of the new exc-EDA methods, which include geometry optimisation of the test systems (fluorenone-methanol, quinoline-water, benzene-TCNE and pyridine-water) and the exc-EDA-results with and without TDA and different XC-functionals. In addition, data of exc-EDA calculations for oligomers of pentacene are also included. All calculations were performed with a developer version of AMS.</p>
Machine Learning for Energy Consumption Prediction of Numerical Controlled Programs - NC Files
<p>The NC files housed within this DOI represent the Data the Machine Learning Models were Trained/Validated/Tested on, during the execution of the work in the thesis, " Machine Learning for Energy Consumption Prediction of Numerically Controlled Programs." Theses files were created by Samuel D. Stencel, a Gradute Research Assistant at Purdue University.</p> <p> </p>
Data to estimate energy efficiency and environmental friendliness of Ukrainian GDP from indicators of structural, economic, and social development in Ukraine
<p><span>Data to estimate regression dependences of energy efficiency and environmental friendliness of GDP from indicators of structural, economic, and social development in Ukraine </span></p>
High-resolution Industrial Production Energy (HIPE)
<p>The High-resolution Industrial Production Energy (HIPE) data set contains smart meter readings of ten machines and the main terminal of a power-electronics production plant over three months.</p> <p><a href="https://doi.org/10.1145/3208903.3210278" target="_blank" rel="noopener">The accompanying publication (published by ACM)</a> describes the data set and outlines open challenges and use cases with industrial energy data. This includes a dis­cussion of cha­rac­ter­is­tics of in­dus­tri­al machines and of differences to residential appliances.</p> <p>Links:</p> <ul> <li>Publication: <a href="https://doi.org/10.1145/3208903.3210278" target="_blank" rel="noopener">https://doi.org/10.1145/3208903.3210278</a></li> <li>Description: <a href="https://www.energystatusdata.kit.edu/hipe.php">https://www.energystatusdata.kit.edu/hipe.php</a></li> </ul>
Questionnaire responses on participation in an energy cooperative (france, 2018)
<ul> <li>Dataset of a survey conducted in an energy cooperative</li> <li>395 responses (biased toward active participants)</li> <li>Data on : <ul> <li>Socio-demographic</li> <li>Motivation to become member</li> <li>Participation in governance</li> <li>Volunteer participation</li> <li>Investment participation</li> <li>Satisfaction with the governance</li> <li>Satisfaction with information provided by the cooperative</li> <li>Perceived control over governance</li> <li>Trust in the cooperative</li> <li>Ecological orientation</li> <li>Perceived skills</li> </ul> </li> </ul> <ul> <li>Données issues d'une enquête menée dans une coopérative d'énergie (SCIC)</li> <li>395 réponses (surreprésentation des participants actifs)</li> <li>Données sur : </li> <ul> <li>Socio-démographie</li> <li>Motivation à devenir membre</li> <li>Participation à la gouvernance</li> <li>Participation bénévole</li> <li>Investissement</li> <li>Satisfaction à l'égard de la gouvernance</li> <li>Satisfaction à l'égard des informations fournies par la coopérative</li> <li>Contrôle perçu sur la gouvernance</li> <li>Confiance dans la coopérative</li> <li>Orientation écologique</li> <li>Compétences perçues</li> </ul> </ul>
Data to calculate metal demand from IAM energy projections and add flexibility to the technological mix
<p>In the "Data" folder, you’ll find all necessary data to run the <strong>"IAM_metal_optimisation.py"</strong> script, available on GitHub (<a href="https://github.com/Pelotte/iam-metal-demand-optimizer/tree/master" target="_new" rel="noopener">https://github.com/Pelotte/iam-metal-demand-optimizer/tree/master</a>).</p> <p>The <strong>"IAM_metal_optimisation.py"</strong> script is a tool designed to:</p> <ol> <li>Quantify metal supply and demand by sector through 2050, using energy projections from various IAMs and SSP-RCP scenarios.</li> <li>Optimize the IAM technological mix, minimizing adjustments needed to prevent metal demand from exceeding supply constraints.</li> </ol> <p>This tool supports all IAMs with power projections for SSP-RCP scenarios (except SSP3) provided in the IPCC’s Sixth Assessment Report (AR6), Working Group III, and available in the IIASA database.</p> <p>Data for RCP 2.6, SSPs 1, 2, 4, 5, of the SSP marker IAM models of the IPCC, are organized in the "Capacity Factor IAM," "GDP IAM," and "Power Capacity IAM" folders. See the GitHub README for more details.</p>
Dataset and R code support the manuscript titled "Streamlining Linear Free Energy Relationships of Proteins through Dimensionality Analysis and Linear Modeling"
<p>This dataset and R code support the manuscript titled "Streamlining Linear Free Energy Relationships of Proteins through Dimensionality Analysis and Linear Modeling" submitted to the Journal of Chemical Information and Modeling.</p> <p>Table S 1: Chemicals with their experimental values of logKch , and values of logKow and<span> </span>logKaw used to calibrate chicken muscle protein-water 2p-LFER model.</p> <p>Table S 2: Chemicals with their experimental values of logKfish and values of logKow and<span> </span>logKaw used to calibrate fish muscle protein-water 2p-LFER model.</p> <p>Table S 3: Chemicals with their experimental values of logKBSA and values of logKow and<span> </span>logKaw used to calibrate bovine serum albumin-water 2p-LFER model.</p> <p>Table S 4: Chemicals with their experimental values of logKpw and values of logKow and<span> </span>logKaw used to calibrate combined chicken and fish muscle protein-water 2p-LFER model.</p> <p>Table S 5: Diversity of data for logKpw.</p> <p>Table S 6: Diversity of data for logKBSA.</p> <p>Table S 7: Comparison of Experimental and 2p-LFER Predicted Partition Coefficients for ionizable PFAS Compounds.</p> <p>Table S 8: List of neutral fluorotelomer PFAS Compounds.</p> <p>Table S 9: List of experimental in vivo and in vitro partitioning data for different tissues and species.</p> <p>Table S 10: List of experimental Milk-water partition coefficient and predicted values of Milk-water partitioning.</p> <p>Table S 11: Training set for logKpw</p> <p>Table S 12: Validation set for log Kpw</p> <p>Table S 13: Training set for log KBSA</p> <p>Table S 14: Validation set for log KBSA</p>
Data from " Allostery can convert binding free energies into concerted domain motions in enzymes"
<p>Data from " Allostery can convert binding free energies into concerted domain motions in enzymes"</p> <p> </p> <p>Electrophysiology data corresponding to the main text figures and supporting information figures. One representative set was chosen for each triplicate and included in this data set. For details are found in the ‘read me explanation.txt’</p> <p>PDB used for this paper can be found at; 4ake [http://doi.org/10.2210/pdb4AKE/pdb] and 1ake [http://doi.org/10.2210/pdb1AKE/pdb]</p> <p>Full uncropped scans of any cropped gel/blot images are provided.</p> <p>The zip folder contains the MATLAB code package HMM inference, specifically tailored to nanopore ionic current flow data, as analyzed in the publication and can also be found at: https://github.com/yulanvanoppen/nanopore-HMM</p> <pre><br> </pre>
Marine stepping-stones: Connectivity of Mytilus edulis populations between offshore energy installations
Recent papers postulate that epifaunal organisms use artificial structures as stepping-stones to spread to areas that are too distant to reach in a single generation. With thousands of artificial structures present in the North Sea, we test the hypothesis that these structures are connected by water currents and act as an interconnected reef. Population genetic structure of the Blue mussel, Mytilus edulis was expected to follow a pattern predicted by particle tracking models (PTM). Correlation between population genetic differentiation, based on microsatellite markers, and particle exchange was tested. Specimens of M. edulis were found at each location, although the PTM indicated that locations >85 km offshore were isolated from coastal sub-populations. Fixation coefficient FST correlated with the number of arrivals in the PTM. However, the number of effective migrants per generation as inferred from coalescent simulations did not show a strong correlation with the arriving particles. Isolation by distance analysis showed no increase in isolation with increasing distance and we did not find clear structure among the populations. The marine stepping-stone effect is obviously important for the distribution of M. edulis in the North Sea and it may influence ecologically comparable species in a similar way. In the absence of artificial shallow hard substrates, M. edulis would be unlikely to survive in offshore North Sea waters. Although we found an indication that FST was lower between connected locations, isolation by distance analysis showed no increase in isolation with increasing distance. Finally, we did not find clear structure among the populations.
Determinants of heart rate in Svalbard reindeer reveal mechanisms of seasonal energy management
<p>Seasonal energetic challenges may constrain an animal's ability to respond to changing individual and environmental conditions. Here we investigated variation in heart rate, a well-established proxy for metabolic rate, in Svalbard reindeer, a species with strong seasonal changes in foraging and metabolic activity. In 19 adult females we recorded heart rate, subcutaneous temperature and activity using biologgers. Mean heart rate more than doubled from winter to summer. Typical drivers of energy expenditure, such as reproduction and activity, explained a relatively limited amount of variation (2–6% in winter and 16–24% in summer), compared to seasonality which explained 75% of annual variation in heart rate. The relationship between heart rate and subcutaneous temperature depended on individual state via body mass, age and reproductive status, and the results suggested that peripheral heterothermy is an important pathway of energy management in both winter and summer. While the seasonal plasticity in energetics make Svalbard reindeer well-adapted to their highly seasonal environment, intraseasonal constraints on modulation of their heart rate may limit their ability to respond to severe environmental change. This study emphasizes the importance of encompassing individual state and seasonal context when studying energetics in free-living animals.</p>
Influence of temperature and salinity on the cellular stress response and energy reserves of Hediste diversicolor.
<p>Raw data on survival rates, wet weight, cellular stress response, oxidative stress and energy reserves of the ragworm Hediste diversicolor collected at Ria de Aveiro (Portugal) and subjected to a combination of different temperatures (24, 27 and 30 ºC) and salinities (20 and 30) over time (14 and 28 days). The biomarkers analysed include: heat shock protein 70 kDa, total ubiquitin, catalase, superoxide dismutase, glutathione-S-transferase, total antioxidant capacity, lipid peroxidation, glucose, glycogen, total protein and total lipids.</p>
Energy demand and its temporal flexibility: approaches, criticalities and ways forward
<p>Data set of the reviewed documents in the contribution 'Energy demand and its temporal flexibility: approaches, criticalities and ways forward' under consideration for publication in 'Renewable & Sustainable Energy Reviews'</p>
Code and data for publication "pyGRETA, pyCLARA, pyPRIMA: A pre-processing suite to generate flexible model regions for energy system models"
<p>This dataset contains the code of the three pre-processing tools <a href="https://github.com/tum-ens/pyGRETA">pyGRETA</a>, <a href="https://github.com/tum-ens/pyPRIMA">pyPRIMA</a> and <a href="https://github.com/tum-ens/pyCLARA">pyCLARA</a> and an examplary database for the scope of Austria.</p> <p>To run the code with full functionality additional data is needed. Check the documentation of the tools for further information.</p> <p> </p> <p>Sources for data can be found here: </p> <p>pyGRETA: https://pygreta.readthedocs.io/en/stable/user_manual.html#recommended-input-sources</p> <p>pyPRIMA: https://pyprima.readthedocs.io/en/stable/user_manual.html#recommended-input-sources</p> <p>pyCLARA: https://pyclara.readthedocs.io/en/stable/user_manual.html#recommended-input-sources</p>
Energy consumption of 15 electric vehicles (one day resolution)
<p><strong>Energy consumption of 15 electric vehicles (one day resolution)</strong></p> <p>Sérgio Ramos, João Soares, Zahra Foroozandeh, Inês Tavares, Zita Vale</p> <p><strong>Paper title: TODO</strong></p> <p>Type: EV consumption</p> <p>Duration: One year</p> <p>Resolution: One day</p> <p>Application: Paper submitted on</p> <p>Sheets description:</p> <ul> <li>EV 1-15: Contains the information of the energy consumption and initial State of Charge of each EV (kWh).</li> </ul>
Energy consumption and PV generation data of 15 prosumers (15 minute resolution)
<p><strong>Energy consumption and PV generation data of 15 prosumers (15 minute resolution)</strong></p> <p>Sérgio Ramos, João Soares, Zahra Foroozandeh, Inês Tavares, Zita Vale</p> <p><strong>Paper title: (All papers)</strong></p> <p>Type: Energy consumption and PV generation data</p> <p>Duration: Year 2019 (15 minute – 35 040 periods)</p> <p>Resolution: 15 minutes</p> <p>Application: Paper submitted on</p> <p>Sheets description:</p> <ul> <li>Total PV production: Contains the generation of the PV panels;</li> <li>Common services: Contains information of the energy consumption of the common services of the building;</li> <li>Consumer 1-15: Contains the information of the energy consumption of each consumer.</li> </ul>
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.