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210 results for “Energy modeling”
Dataset for Analysis of Various Spatial Resolutions for Modelling Sector-Coupled Energy Systems
<p>Dataset for preprocessing Balmorel data in this Danish case study.</p>
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>
UFO model for stop pair production to ttbar and missing energy
<p>stop pair production with ttbar and missing energy</p>
Ranking Variable Importance for US Commercial Buildings via Sensitivity Analysis of Building Energy Models
<p>This zip file contails all code and simulation results which was used for the analysis. </p>
Fig. 2 in Modeling energy flow in a large Neotropical reservoir: a tool do evaluate fishing and stability
Fig. 2. Relative biomass (2a) and relative catch (2b) of the main species of the ITAIPU-2 model, with increasing of fishing effort. Fishing effort = 1 is equivalent to that registered in 1998. This value was multiplied by 2, 3 and 4, in order to get other fisheries scenarios. Simulations made in Ecopath with Ecosim (Subroutine: Run Ecossim, module: Results).
Ocean Dynamics in the DOE Energy, Exascale, Earth System Model (E3SM)
<p>Climate research at the U.S. Department of Energy (DOE) includes the development of ocean, sea-ice, atmosphere, land-vegetation and land-ice models. The ability to run high-resolution global simulations efficiently on the world’s largest computers is a priority for the DOE. This movie shows simulations from the variable-resolution ocean model, the Model for Prediction Across Scales (MPAS-Ocean), which is developed at Los Alamos National Laboratory. MPAS-Ocean is a component of the DOE’s newly released Energy, Exascale, Earth System Model (E3SM). Applications of E3SM include the simulation of 20th-century and future climate scenarios, as well as special configurations where model resolution is enhanced in regions of particular interest, like coastal areas, the Arctic, or below Antarctic ice shelves.</p> <p>Website: <a href="https://e3sm.org">https://e3sm.org</a>. </p>
The Gambia Energy Models
<p>The Gambia Energy models. EMPA 2023</p>
Data from: Economic uncertainty, geopolitical risk and U.S. energy price risk spillover: An empirical study based on the risk spillover model
<p>This data is mainly used to analyze the risk correlation among economic uncertainly,geopolitical risk and energy price,and can also be applied to the TVP-VAR model to analyze the correlation between different variables using the time-varying parameter model,which has great potential for reuse. The risk relationship between economic uncertainly.At the same time,since it is macroeconomic data,it does not involve any moral and ethical issues.</p>
Data from: Economic uncertainty, geopolitical risk and U.S. energy price risk spillover: An empirical study based on the risk spillover model
Open the record for dataset details and reuse information.
Multi-organ Transcriptome Atlas of a Mouse Model of Relative Energy Deficiency in Sport (REDs)
GEO Series GSE243060. Mus musculus. 419 samples. Type: Expression profiling by high throughput sequencing.
A systems biology approach reveals a link between systemic cytokines and skeletal muscle energy metabolism in a rodent smoking model and human COPD
GEO Series GSE56099. Cavia porcellus. 49 samples. Type: Expression profiling by array; Expression profiling by high throughput sequencing.
Partial inhibition of mitochondrial complex I attenuates neurodegeneration and restores energy homeostasis and synaptic function in a symptomatic Alzheimer’s mouse model
GEO Series GSE149248. Mus musculus. 14 samples. Type: Expression profiling by high throughput sequencing.
Banxia Xiexin decoction promotes gastric lymphatic pumping by regulating lymphatic smooth muscle cell contraction and energy metabolism in a stress-induced gastric ulceration rat model
GEO Series GSE252116. Rattus norvegicus. 9 samples. Type: Expression profiling by high throughput sequencing.
Probabilistic Model-Based Analysis to Improve Software Energy Efficiency - Presentation
<p>Presentation</p> <p>Paper: Probabilistic Model-Based Analysis to Improve Software Energy Efficiency</p> <p>SBES 2020 - Research Track</p>
urbisphere_gb-london_UR-4: Derivation of building thermal and radiative parameters for building energy modelling
<h2>Files in this archive </h2> <ul> <li>GB_layer_info.zip <ul> <li>Output and specifications from uBEMM_v1_27-3-2024.xlsx for further processing (*.csv)</li> </ul> </li> <li>GB_layer_processed.zip <ul> <li>Processed layer-specific thermal and radiative material parameters for UK building typologies (external wall, roofs, ground floors; *.csv)</li> </ul> </li> <li>GB_effective_parameters.zip <ul> <li>Processed effective thermal and radiative parameters of external walls, roofs, ground floors, windows, internal walls and internal floors for UK building typologies (*.csv)</li> </ul> </li> <li>uBEMM_v1_27-3-2024.xlsx <ul> <li>Tool to characterise building structure layers based on bulk thermal parameters</li> </ul> </li> <li>code.zip <ul> <li>Code for processing of building materials (Python3)</li> </ul> </li> <li>urbisphere_gb-london_UR-4.pdf <ul> <li>Documentation</li> </ul> </li> </ul> <h2>Data purpose </h2> <p>The data support APEx, <em>urbisphere</em>-London and ASSURE modelling activities of building energy exchanges in London. </p> <h3>Linked with</h3> <ul> <li>Hertwig et al. 2024. urbisphere_presentations_UR-1: Modelling anthropogenic heat emissions from residential buildings-comparison between Berlin and London. EMS Annual Meeting 2023 [Poster]. Zenodo. https://doi.org/10.5281/zenodo.10889863</li> </ul>
The effects of fair allocation principles on energy system model designs
<p>This is the associated dataset to <a href="https://github.com/OskarVagero/highRES-Europe-WF/tree/MENOFS">https://github.com/OskarVagero/highRES-Europe-WF/tree/MENOFS </a>, which contains the data necessary to replicate the study. </p> <p>In addition to the data required to replicate the study, we also include six pre-generated model results (.db), which represent the "top performers", as well as the cost-optimal model run. </p> <ul> <li>Weather data is based on ERA5, from ECMWF (https://doi.org/10.1002/qj.3803) </li> <li>Demand data is based on the Interannual Electricity Demand Calculator (https://zenodo.org/records/10820928)</li> <li>Existing hydropower capacity is based on the JRC Hydropower database (https://zenodo.org/records/5215920)</li> <li>Historic electricity generation from hydropower is based on the U.S. Energy Information Administration (https://www.eia.gov/international/data/world/electricity/electricity-generation)</li> </ul> <p>More details on how to use the data can be found in the GitHub repository. </p>
Streamlining Linear Free Energy Relationships of Proteins through Dimensionality Analysis and Linear Modeling
<p><span>This dataset and accompanying 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. The dataset primarily contains tables detailing the various chemicals, dependent, and independent variables used to develop two-parameter linear models for predicting muscle protein-water and serum albumin-water partition coefficients in this study. Additionally, it includes information on both observed and predicted values of these partition coefficients by newly developed models. The R code comprises scripts used for generating figures and results presented in the manuscript.</span></p> <p><span>The R code comprises scripts used for generating figures and results presented in the manuscript.</span></p> <p><span>These files are currently under restricted access for peer review purposes and will be made publicly available upon acceptance of the manuscript.</span></p>
Supplementary material for the article entitled "Socioeconomic Analysis of the Proposed Opening of the Brazilian energy Market Through the Combination of Forecast Method with the Optimized Tariff Model"
<p>This supplementary material includes the input data used for the simulations conducted in the article.</p>
Modelling of Energy Expenditure From Heart Rate, Accelerometry and Other Physiological Parameters
ClinicalTrials.gov study NCT01209572. IPD Sharing: Not stated. Countries: 1. Publications: 0.
The Effects of Low Energy Availability and High Impact Jumping on Markers of Bone (re)Modelling in Females
ClinicalTrials.gov study NCT04790019. IPD Sharing: NO. Countries: 1. Publications: 0.
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.