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46 results for “Case Studies Results”
Inter-Chemical Correlation results for the study: HHEARx2016-1534 (A Nested Case-Control Study of Prenatal Exposure to Phthalates and Psychosocial Stress: Adverse Pregnancy Outcomes and the Mediating Role of Placental Function)
Title: A Nested Case-Control Study of Prenatal Exposure to Phthalates and Psychosocial Stress: Adverse Pregnancy Outcomes and the Mediating Role of Placental Function <br>Species: Homo sapiens <br>Number of samples: 5789 <br>Number of named analytes: 17 <br>Datasource url: https://hheardatacenter.mssm.edu/PublicFile/ViewPublicFile?projectid=14 <br>
Case study result data set for Energy Economics article "Demystifying market clearing and price setting effects in low-carbon energy systems"
<p>The data set contains country-specific power generation and consumption time series data for the European energy system, including both traditional and new market participants due to cross-sectoral integration.</p> <p>Country codes: ALPHA-3<br> Unit: Megawatt (electric) (interval average values, i.e. MWh/h)</p> <p><strong>Generation technology types</strong></p> <ul> <li>batteryStorage (Li-Ion)</li> <li>conventionalHydro (aggregated for different equivalent hydropower systems)</li> <li>natural_gas_CC_COND (Combined Cycle Gas Turbine)</li> <li>natural_gas_CC_EXCOND (Combined Cycle Gas Turbine as extraction condensing CHP plant for district heating)</li> <li>natural_gas_GT_COND (Open-Cycle Gas Turbine)</li> <li>natural_gas_GT_EXCOND (Open-Cycle Gas Turbine as extraction condensing CHP plant for industry)</li> <li>offshoreWind (aggregated for different LCOE and IEC wind turbine classes)</li> <li>offshoreWindExplicit (offshore wind generation considered for offshore grid investments in the North Seas area, aggregated for different LCOE classes)</li> <li>onshoreWind (solar PV, aggregated for different LCOE classes)</li> <li>other (geothermal, waste)</li> <li>pumpedHydro (aggregated for different equivalent hydropower systems)</li> <li>solar (solar PV, aggregated for different LCOE classes)</li> <li>uran_ST_COND (steam turbine condensing power plant)</li> </ul> <p><strong>Consumption technology types</strong></p> <ul> <li>BEV (Battery Electric Vehicles, aggregated for different market segments)</li> <li>PHEV (Battery Electric Vehicles, aggregated for different market segments)</li> <li>airConditioning</li> <li>batteryStorage (Li-Ion)</li> <li>conventionalLoad</li> <li>heatPump (aggregated for different combinations of building, e.g. residential and non-residential, and technology, e.g. air-source, ground-source, types)</li> <li>hybridHeatPump (aggregated for different combinations of building, e.g. residential and non-residential, and technology, e.g. air-source, ground-source, types)</li> <li>hybridTruck (Hybrid Overhead-Line truck)</li> <li>largeScaleDirectResistiveHeating (Centralised CHP systems)</li> <li>natural_gas_CC_EXCOND_electrodeHeater</li> <li>natural_gas_CC_EXCOND_heatpumpHeater</li> <li>natural_gas_GT_EXCOND_electrodeHeater</li> <li>natural_gas_GT_EXCOND_heatpumpHeater</li> <li>powerToGas</li> <li>pumpedHydro (aggregated for different equivalent hydropower systems)</li> </ul>
HEATDesalination - Case-study lowest-cost optimisation results
<p>Optimisation results for the lowest lifetime cost system consisting of solar photovoltaic (PV), hybrid photovoltaic-thermal (PV-T) and solar-thermal collectors alongside battery and hot-water storage systems for meeting the electrical and thermal (hot-water) needs of three multi-effect distillation (MED) plants.</p> <p>The updated results are from optimisations runs carried out in response to peer-review comments.</p>
Danish case study simulation results (consumption, offered & accepted flexibility, revenues & expenses)
<p>This file contains results of the simulations of the Danish case study generated during Horizon 2020 MAGNITUDE project. The case study considers the provision of domestic hot water from 350 heat pumps installed in multi-storey apartment buildings. Heat pumps receive energy from electrical grid and use heat from ultra-low temperature district heating (ULTDH) as heat source. The overall system is referred to as Multi-Energy System (MES). MES can provide flexibility to either intra-day (ID) market or redispatch (RE) services to local distribution system operator. Results show how much flexibility was offered and activated, and the resulting consumption and production profiles due to that. In addition, the revenues and expenses based on the historical prices for Denmark in 2018 had been calculated.</p>
Case study result data set for Energy Economics (submitted) article "On Wholesale Electricity Prices and Market Values in a Carbon-Neutral Energy System"
<p>The data set contains wholesale power price time series data for Germany and France focussing on price setting effects in a long term low carbon European energy system context (scenario year 2050) generated with the model SCOPE SD of Fraunhofer Institute for Energy Economics and Energy System Technology IEE. The single time series are focussing on the price setting effects of different flexible technologies including both traditional and new market participants due to cross-sectoral integration.</p> <p>Unit: Euro/Megawatthour</p> <p><strong>Abbreviations:</strong></p> <ul> <li>BEV - Battery Electric Vehicles</li> <li>GER - Germany</li> <li>FRA - France</li> <li>OCGT - Open Cycle Gas Turbine</li> <li>PHEV - Plug-In Hybrid Vehicles</li> <li>RES - Renewable energy sources (here: wind and solar power)</li> <li>th. - thermal</li> </ul>
TRANSIT long-distance multimodal trips model results - a Spanish case study
<p>The files downloaded present the results per scenario considered obtained with the agent-based model developed for the assessment of the Intermodal Timetable Synchronisation solution proposed in the scope of the TRANSIT project (<a href="https://www.transit-h2020.eu/">https://www.transit-h2020.eu/</a>).</p> <p>An agent-based modelling framework called <a href="https://github.com/StefanoPenazzi/jtap/tree/main">J-TAP</a> has been developed and put at work to implement a Spanish long-distance multimodal trips model. The enhanced version of J-TAP used in this work can be found on a <a href="https://github.com/NommonSolutionsAndTechnologies/jtap">github repository</a>.</p> <p>The case study is focused on modelling the long-distance travel patterns of the residents in the Valencia (Spain) area. The destinations considered include the whole of Spain. The period under study is a full year from March 2019 to February 2020 (both inclusive).The files are structured in three different scenarios:</p> <ol> <li><strong>CS01 - Baseline</strong>. The current state of the network is considered and the actual long-distance travel patterns are obtained.</li> <li><strong>CS02 - HSR connection with Madrid-Barajas airport</strong>. The long-distance travel patterns are modelled with hard measures, the high-speed rail is connected to Madrid-Barajas airport.</li> <li><strong>CS03 - HSR connection with Madrid-Barajas airport and timetable synchronisation</strong>. The effects of the timetable synchronisation are modelled.</li> </ol> <p>Each scenario includes the following files:</p> <ul> <li>ctapModelParameters. A folder containing all the information extracted from the <a href="https://neo4j.com/product/graph-data-science/?utm_program=emea-prospecting&utm_source=google&utm_medium=cpc&utm_campaign=emea-search-offers&utm_adgroup=dynamic&utm_content=dynamic&utm_placement=&utm_network=g&gclid=Cj0KCQiAwJWdBhCYARIsAJc4idAo4CEi9lU8TXwmBym8MNHpEIZHPBs3x_4phxbu76y1XKbYlFoZCjIaAiGhEALw_wcB">neo4j</a> graph database created to model the multimodal network and the agents. J-TAP contains packages that simplify network creation in the graph database. This information is stored in .json files (e.g., "Os2DsTravelCostParameter.json" contains the generalised cost for each OD pair and transport mode, "AttractivenessParameter.json" contains the attractiveness by destination, activity, time of the year and agent, etc.). The solver included in the J-TAP framework uses this information to calculate the agents plans.</li> <li>population.json. The result of the J-TAP optimisation. It includes the fitness value for each agent plan evaluated during the J-TAP execution. The best plan for each agent is selected as the plan performed by the agent. An agent plan includes: <ul> <li>activities - Sequence of activities.</li> <li>locations - Sequence of locations</li> <li>ts - Initial time of the activity</li> <li>te - Final time of the activity</li> </ul> </li> <li>LinkTimeFlow.csv. It is obtained after processing the previous file. It contains the number of agents using each link in the network (i.e., road, rail, air and cross links) in each time interval. The first column represents the link id and the rest of columns indicates the number of agents in each interval.</li> </ul> <p>The J-TAP simulation framework is explained in detail in TRANSIT's deliverable <a href="http://www.nommon-files.es/transit/TRANSIT-D5.1_Modelling_Framework_v02.00.00.pdf">D5.1. TRANSIT Modelling and Simulation Framework</a> and the complete description of the case studies and scenarios tested is included in TRANSIT's deliverable <a href="http://www.nommon-files.es/transit/TRANSIT-D6.1_Assessment_of_Intermodal_Concepts_00.02.00.pdf">D6.1. Impact Assessment of New Intermodal Concepts and Passenger Information Services: Conclusions and Recommendations</a>.</p> <p>Thank you for downloading the dataset! It would be very helpful if you share your view on the data show with us. </p>
CAIRT FL2S Results of Case Study Scenario 10 (CSS10) for Asian Summer Monsoon
<p>Results of the fast level-2 simulator (FL2S) of CAIRT developed within the Earth Explorer 11 Phase 0 Science and Requirements Consolidation Study (SciReC) – CAIRT. The files contain altitude-time cross-sections of atmospheric parameters along simulated CAIRT-orbits. The variable extensions denote the original field ('_ori'), the application of the averaging kernel ('_ak'), additional application of noise ('_aknoi'), application of systematic uncertainties ('_sys'), and application of all effects ('_aknoisys'). Further information is available from the authors.</p>
CAIRT FL2S Results of Case Study Scenario 4 (CSS4) for Volcanic Eruption
<p>Results of the fast level-2 simulator (FL2S) of CAIRT developed within the Earth Explorer 11 Phase 0 Science and Requirements Consolidation Study (SciReC) – CAIRT. The files contain altitude-time cross-sections of atmospheric parameters along simulated CAIRT-orbits. The variable extensions denote the original field ('_ori'), the application of the averaging kernel ('_ak'), additional application of noise ('_aknoi'), application of systematic uncertainties ('_sys'), and application of all effects ('_aknoisys'). Further information is available from the authors.</p>
CAIRT FL2S Results of Case Study Scenario 7 (CSS7) for Southern Hemisphere Winter
<p>Results of the fast level-2 simulator (FL2S) of CAIRT developed within the Earth Explorer 11 Phase 0 Science and Requirements Consolidation Study (SciReC) – CAIRT. The files contain altitude-time cross-sections of atmospheric parameters along simulated CAIRT-orbits. The variable extensions denote the original field ('_ori'), the application of the averaging kernel ('_ak'), additional application of noise ('_aknoi'), application of systematic uncertainties ('_sys'), and application of all effects ('_aknoisys'). Further information is available from the authors.</p>
CAIRT FL2S Results of Case Study Scenario 3 (CSS3) for Biomass Burning
<p>Results of the fast level-2 simulator (FL2S) of CAIRT developed within the Earth Explorer 11 Phase 0 Science and Requirements Consolidation Study (SciReC) – CAIRT. The files contain altitude-time cross-sections of atmospheric parameters along simulated CAIRT-orbits. The variable extensions denote the original field ('_ori'), the application of the averaging kernel ('_ak'), additional application of noise ('_aknoi'), application of systematic uncertainties ('_sys'), and application of all effects ('_aknoisys'). Further information is available from the authors.</p>
CAIRT/IASI-NG/CAIRT+IASI-NG FL2S results of Case Study Scenario 4 for limb-nadir application
<p>Results of the fast level-2 simulator (FL2S) for Case Study Scenarios 4 (only SO2 files) for limb-nadir application. The files contain altitude-time cross-sections of atmospheric parameters along simulated CAIRT-orbits. The variable extensions denote the original field ('_ori'), the application of the averaging kernel ('_ak') and additional application of noise ('_aknoi') for CAIRT alone, IASI-NG alone, and the combined product CAIRT+IASI-NG.</p>
CAIRT FL2S Results of Case Study Scenario 6 (CSS6) for Auroral NO
<p>Corrected version. Results of the fast level-2 simulator (FL2S) of CAIRT developed within the Earth Explorer 11 Phase 0 Science and Requirements Consolidation Study (SciReC) – CAIRT. The files contain altitude-time cross-sections of atmospheric parameters along simulated CAIRT-orbits. The variable extensions denote the original field ('_ori'), the application of the averaging kernel ('_ak'), additional application of noise ('_aknoi'), application of systematic uncertainties ('_sys'), and application of all effects ('_aknoisys'). Further information is available from the authors. </p>
Interim Data and Results for Case Study: Funding rules that promote equity in climate adaptation outcomes
<p>Interim exposure data and results for the published case study. External raw data is available <a href="https://zenodo.org/records/14260630">here</a> and the remaining raw data is generated via code. This is too large to share on Zenodo. There are stochastic aspects in going from raw exposure to interim exposure data and interim exposure data to results, which is why we make the specific interim exposure data and results of the published study available here. Other interim data is not stochastic and can be reproduced following the code reproduction instructions (see https://github.com/abpoll/j40_gc). Please see the underlying study for more details about the methods. The data here can be generally reproduced (not bit-wise) following the code and instructions at this repository: https://zenodo.org/records/14261361.</p> <p> </p> <p>The interim exposure data is named "exp" and the results data is named "results."</p>
Simulation results for ProSSE and datafile for case study
<p>This repository includes the data files for the simulation study and the case study in the publication.</p> <p>The simulation_result.Rdata is an R data file that stores simulated data and results. The data is used to generate Figures 2-7, S1, and S2.</p> <p>The casestudy_trees.Rdata is an R data file that stores the posterior samples of the species tree of the Australian rainbow skinks and the model fitting on these trees. The data file is used to generate Figure 8.</p>
Results of SPOT surveys for tourists, residents and entrepreneurs in the case studies - dataset
<p>This is a dataset of three surveys conducted within the scope of the SPOT project. The purpose of this dataset is to provide the results of the surveys for tourists, residents and entrepreneurs of the fifteen participating case studies. </p>
Sonic Boom Propagation Results for Case Study 1 of the MORE&LESS Project
<p>This dataset provides the output of sonic boom simulations under various flight conditions, including predictions using Carlson’s method and higher-fidelity nonlinear propagation simulations (using propaBoom). The data is categorized by flight phase (climb, cruise, descent) and atmosphere models (ISA, SBPW3). Each flight phase includes ray tracing results and sonic boom signatures for multiple azimuth angles.</p> <p>The dataset includes:</p> <ul> <li><strong>Carlson Method Predictions</strong>: Peak overpressure and signal duration for various off-track angles.</li> <li><strong>Nonlinear Propagation Simulations</strong>: Ray tracing data (ground intersections and angles) and shock wave signatures at the beginning of the non-linear shock wave propagation and at ground level.</li> </ul> <p>Files are provided in CSV format for easy analysis using standard tools (e.g., Excel, pandas). The dataset contains simulation results for different azimuth angles, e.g., acoustic pressure, and ray intersections for thorough investigation of sonic boom propagation effects.</p> <p><strong>Folder Structure</strong>:</p> <ul> <li><code>carlson_predictions.zip</code>: Carlson method results for climb, cruise, and descent operating conditions.</li> <li><code>nonlinear_propagation_predictions.zip</code>: High-fidelity simulation outputs including ray tracing and propagated ground signatures.</li> <li><code>readme.md</code>: Readme file with information on the datasets.</li> </ul> <p><strong>Usage</strong>: Researchers can use these datasets to compare sonic boom prediction methods under the effects of flight conditions and atmospheric variations on sonic boom ground signatures.</p> <p><strong>Contact</strong>: For any questions or inquiries regarding this dataset, please contact Jacob Jäschke (jacob.jaeschke[at]tuhh.de) (<a title="Orcid Profile of Jacob Jäschke" href="https://orcid.org/0000-0002-5155-4877" target="_blank" rel="noopener">https://orcid.org/0000-0002-5155-4877</a>).</p>
openENTRANCE - Case Study 7 - Power-to-Heat Demand Flexibility: Results
<p>In case study 7 of the openENTRANCE project, Plan4EU, an electricity dispatch model for Europe, is soft-linked to the Flexibility Function, an indirect demand response model, via Frigg, a novel framework for integrating realistic demand response in energy system analysis. This modelling setup is applied to analyse the role of power-to-heat demand flexibility (end-consumer demand response and heat storage) in the Danish electricity system of 2050. This dataset contains results as presented in the related project report.</p>
Results related to the case study 4 of the openENTRANCE project - SCOPE SD version 2023
<p>This dataset contains scenarios results for Case Study 4 of the openENTRANCE project.</p> <p>You can find additional information, including model results and case study setup, at Deliverable D6.2 of the openENTRANCE project at <a href="https://openentrance.eu/">openENTRANCE – open ENergy TRanstion ANalyses for a low-Carbon Economy</a>. </p> <p>Further information on the SCOPE SD model is given in: Frischmuth, F., Härtel, P.: Hydrogen sourcing strategies and cross-sectoral flexibility trade-offs in net-neutral energy scenarios for europe. Energy (2022). https://doi.org/10.1016/j.energy.2021.121598</p> <p>The data file follows the IAMC data format and the conventions established by the openENTRANCE project. See <a href="https://github.com/openENTRANCE/openentrance">https://github.com/openENTRANCE/openentrance</a> for details.</p> <p>Visit the openENTRANCE Scenario Explorer at <a href="https://data.ene.iiasa.ac.at/openentrance">https://data.ece.iiasa.ac.at/openentrance</a> for more information.</p> <p> </p>
Simulation results for ProSSE and datafile for case study
Open the record for dataset details and reuse information.
CAIRT/IASI-NG/CAIRT+IASI-NG FL2S results of Case Study Scenario 3 for limb-nadir application
<p>Results of the fast level-2 simulator (FL2S) for Case Study Scenarios 3 (only CO and PAN files) for limb-nadir application. The files contain altitude-time cross-sections of atmospheric parameters along simulated CAIRT-orbits. The variable extensions denote the original field ('_ori'), the application of the averaging kernel ('_ak') and additional application of noise ('_aknoi') for CAIRT alone, IASI-NG alone, and the combined product CAIRT+IASI-NG. </p>
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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.