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Dataset results
90 results for “Scenario based”
Ensemble Ecological Niche Models, in 2019 and across RCP 2.6, 4.5, and 8.5 scenarios in 2050 and 2100, of 1508 European Marine Species based on Ecological Niche Models developed with Artificial Neural Networks, Maximum Entropy, Support Vector Machines, and AquaMaps at 0.5° Resolution
<p>Ensemble Ecological Niche Models, in 2019 and across RCP 2.6, 4.5, and 8.5 scenarios in 2050 and 2100, of 1508 European marine species based on Ecological Niche Models developed with (i) Artificial Neural Networks, (ii) Maximum Entropy, (iii) Support Vector Machines, and (iv) AquaMaps at 0.5° Resolution. The data report, for each 0.5° cell, how many models (from 0 to 4) overcome a model-specific decision threshold to assess species presence in the cell.</p>
Determining the Consistency Between Nurses and Artificial Intelligence (ChatGPT-5) in Delivering Scenario-Based Discharge Education to Coronary Artery Bypass Graft Patients: A Methodological Study
ClinicalTrials.gov study NCT07263724. IPD Sharing: NO. Countries: 1. Publications: 1.
Data from: Model-based comparisons of phylogeographic scenarios resolve the intraspecific divergence of cactophilic Drosophila mojavensis
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Data from: Impacts of silicon-based grass defences across trophic levels under both current and future atmospheric CO2 scenarios
Silicon (Si) has important functional roles in plants, including resistance against herbivores. Environmental change, such as increasing atmospheric concentrations of CO2, may alter allocation to Si defences in grasses, potentially changing the feeding behaviour and performance of herbivores, which may in turn impact on higher trophic groups. Using Si-treated and untreated grasses (Phalaris aquatica) maintained under ambient (400 ppm) and elevated (640 and 800 ppm) CO2 concentrations, we show that Si reduced feeding by crickets (Acheta domesticus), resulting in smaller body mass. This, in turn, reduced predatory behaviour by praying mantids (Tenodera sinensis), which consequently performed worse. Despite elevated CO2 decreasing Si concentrations in P. aquatica, this reduction was not large enough to affect the feeding behaviour of crickets or their predator. Our results suggest that Si-based defences in plants have adverse impacts on both primary and secondary trophic taxa, and these are not likely to decline under future climate change scenarios.
CCG Starter Kits - Base SAND file for Africa Natural Gas Scenario
<p>This file is the Base SAND file for Africa with natural gas.</p> <p>This is published as part of the MethodsX paper titled <strong>How to put together a Starter Data Kit from scratch? An extensive methodology to compile zero-order energy transition models. </strong>The main goal of the files published for this paper is to develop a set of credible data and an initial investment model for several developing countries.</p>
CCG Starter Kits - Base SAND file for Asia - Coal and Natural Gas Scenario
<p>This file is the Base SAND file for Asia with coal and natural gas.</p> <p>This is published as part of the MethodsX paper titled <strong>How to put together a Starter Data Kit from scratch? An extensive methodology to compile zero-order energy transition models. </strong>The main goal of the files published for this paper is to develop a set of credible data and an initial investment model for several developing countries.</p>
CCG Starter Kits - Base SAND file for Africa Coal and Natural Gas Scenario
<p>This file is the Base SAND file for Africa including coal and natural gas.</p> <p>This is published as part of the MethodsX paper titled <strong>How to put together a Starter Data Kit from scratch? An extensive methodology to compile zero-order energy transition models. </strong>The main goal of the files published for this paper is to develop a set of credible data and an initial investment model for several developing countries.</p>
Experiments for 'Scenario-Based Verification of Uncertain Parametric MDPs'
<p>This artifact accompanies the 2022 article in the International Journal on Software Tools for Technology Transfer (STTT) with the same title. The artifact contains a docker container, which can be unzipped and then loaded with:</p> <pre><code>docker load -i upMDPs_STTT.tar</code></pre> <p>Please refer to the README in the ZIP file for more information, or to the Git repository on <a href="https://gitlab.science.ru.nl/tbadings/sttt-scenario">https://gitlab.science.ru.nl/tbadings/sttt-scenario</a>.</p> <p>The Python source code from which the Docker container is created is available in the <code>upMDPs_STTT_source.zip</code> file. This zip file contains the exact content of the Git repository above (accessed on August 20, 2024).</p>
Effects of Scenario-based Education Initiative and OSCE for Recognition and Management of Delirium
ClinicalTrials.gov study NCT05623475. IPD Sharing: NO. Countries: 1. Publications: 0.
Data from: The number of markers and samples needed for detecting bottlenecks under realistic scenarios, with and without recovery: a simulation-based study
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Data from: Impacts of silicon-based grass defences across trophic levels under both current and future atmospheric CO2 scenarios
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VEMAP 1: U.S. Climate Change Scenarios Based on Models with Increased CO2
The Vegetation/Ecosystem Modeling and Analysis Project (VEMAP) is an ongoing multiinstitutional, international effort addressing the response of biogeography and biogeochemistry to environmental variability in climate and other drivers in both space and time domains. The objectives of VEMAP are the intercomparison of biogeochemistry models and vegetation type distribution models (biogeography models) and determination of their sensitivity to changing climate, elevated atmospheric carbon dioxide concentrations, and other sources of altered forcing. Climate scenarios from eight climate change experiments are included in the data set. Seven of these experiments are from atmospheric general circulation model (GCM) 1xCO2 and 2xCO2 equilibrium runs. These GCMs were implemented with a simple "mixed-layer" ocean representation that includes ocean heat storage and vertical exchange of heat and moisture with the atmosphere, but omits or specifies (rather than calculates) horizontal ocean heat transport. The eighth scenario is from a limited-area nested regional climate model (RegCM) experiment for the U.S. which was supported by the Model Evaluation Consortium for Climate Assessment (MECCA). The CCC and GFDL R30 runs are among the high resolution GCM experiments reported in IPCC (1990). Changes in monthly mean temperature and relative humidity were represented as differences (2xCO2 climate value - 1xCO2 climate value) and those for monthly precipitation, solar radiation, vapor pressure, and horizontal wind speed as change ratios (2xCO2 climate value/1xCO2 climate value). GCM grid point change values were derived from archives at the National Center for Atmospheric Research (NCAR; Jenne 1992) and spatially interpolated to the 0.5 degree VEMAP grid. Wind speed changes are for the lowest model level. For GISS runs, we calculated winds from vector components and then determined the change ratio. Values from the 60-km RegCM grid were reprojected to the 0.5 degree grid. Vapor pressure (and relative humidity) were not available for the CCC run; relative humidity changes were not determined for the RegCM experiment. A key issue in the generation of altered climates based on climate model output is the strong possibility of physical inconsistencies in the new climates. Change ratios from the NCAR archive have an imposed upper limit of 5.0, providing some constraint on these changes. An exception is that the GISS wind speed change ratios do not have this limit imposed (most GISS wind speed change ratios were less than 5). For a discussion of the utility and limitations of using climate model experiment outputs for exploring ecological sensitivity to climate change, see Sulzman et al. (1995). The 8 climate model experiments are: CCC - Canadian Climate Centre (Boer, McFarlane, and Lazare 1992) GISS - Goddard Institute for Space Studies (Hansen et al. 1984) GFDL - Geophysical Fluid Dynamics Laboratory. Three experiments: (1) GFDL R15: R15 (4.5 degree by 7.5 degree grid) runs without Q- flux corrections (Manabe and Wetherald, 1987). (2) GFDL R15 Q-flux: R15 resolution (4.5 degree by 7.5 degree grid) runs with Q-flux corrections (Manabe and Wetherald 1990, Wetherald and Manabe 1990). (3) GFDL R30: R30 (2.22 degree by 3.75 degree grid) run with Q-flux corrections (Manabe and Wetherald 1990, Wetherald and Manabe 1990). OSU - Oregon State University (Schlesinger and Zhao 1989) UKMO - United Kingdom Meteorological Office (Wilson and Mitchell 1987) RegCM (MM4) - National Center for Atmospheric Research (NCAR) nested regional climate model (climate version of the Pennsylvania State University/NCAR mesoscale model MM4; Giorgi, Brodeur and Bates 1994). Conterminous U.S. simulations were on a 60-km interval grid and were driven by 1x and 2xCO2 equilibrium GCM runs (Thompson and Pollard 1995a, 1995b). 1x and 2xCO2 RegCM runs were each 3 years in length. Climate changes were based on averages for these runs. A complete users guide to the VEMAP Phase I database which includes more information about this data set can be found at ftp://daac.ornl.gov/data/vemap-1/comp/Phase_1_User_Guide.pdf. ORNL DAAC maintains additional information associated with the VEMAP Project. Data Citation: This data set should be cited as follows: Kittel, T. G. F., N. A. Rosenbloom, T. H. Painter, D. S. Schimel, H. H. Fisher, A. Grimsdell, VEMAP Participants, C. Daly, and E. R. Hunt, Jr. 2002. VEMAP Phase I Database, revised. Available on-line from Oak Ridge National Laboratory Distributed Active Archive Center, Oak Ridge, Tennessee, U.S.A.
Implementation of Inverse Model Policy based on KineNN in Physical Robot for Pick and Place Scenario
<p>Inverse Model Policy based on KineNN was trained in a simulation. After that, the policy is evaluated with the physical robot. The policy is used to drive the robot to specific target such as: Pick Position, Safe Pick Position, Place Position, Safe Place Position. </p>
WBTmax-China dataset basing on EC-Earth3 simulations (Historical and 4 SSPs scenarios)
<p>The WBTmax-China dataset is comprised the NEX-GDDP-CMIP6 dataset (tasmax, huss) and ERA5 dataset (sp) using the algorithm described in Davies-Jones (2008), implemented by Buzan (2015), and ported to Matlab by Dr Robert Kopp (Rutgers, 2016). The NEX-GDDP-CMIP6 dataset is comprised of global downscaled climate scenarios derived from the General Circulation Model (GCM) runs conducted under the Coupled Model Intercomparison Project Phase 6 (CMIP6) and across two of the four “Tier 1” greenhouse gas emissions scenarios known as Shared Socioeconomic Pathways (SSPs). This dataThe purpose of this dataset is to provide a set of high resolution, bias-corrected climate change projections that can be used to evaluate extreme heat over China.</p> <p> </p> <p>Due to the data size limit, only monthly maximum WBT and yearly maximum WBT data are provided here. Daily data can also be shared on request (ncao@gdou.edu.cn).</p>
EFFECT OF SCENARIO-BASED SIMULATION ON BASIC LIFE SUPPORT SKILLS AND SELF-EFFICACY IN NURSING STUDENTS
ClinicalTrials.gov study NCT07366125. IPD Sharing: NO. Countries: 1. Publications: 0.
The Effect of Benner's Jigsaw Teaching Technique Based on the Novice to Expert Model and Scenario-Based Peripheral Intravenous Catheterization Instruction on Skill Acquisition of Nursing Students: An
ClinicalTrials.gov study NCT07298681. IPD Sharing: NO. Countries: 1. Publications: 0.
Scenario-Based Simulation
ClinicalTrials.gov study NCT06870227. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Effectiveness of Scenario-Based Online Simulation in Chest Trauma in Nurses
ClinicalTrials.gov study NCT06902870. IPD Sharing: NO. Countries: 1. Publications: 0.
Improving Critical Thinking and Clinical Reasoning in Nursing Students Through Post-Operative Scenario-Based Simulation
ClinicalTrials.gov study NCT06751446. IPD Sharing: YES. Countries: 1. Publications: 0.
The Effectiveness of Gamified Scenario-based Teaching in Improving Nurses' Awareness and Confidence in Clinical Emergency Care
ClinicalTrials.gov study NCT07365540. IPD Sharing: Not stated. Countries: 1. Publications: 0.
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.