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32
datasets available to search
ShareScore release 0.9.0
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32 results for “Reservoir Modeling”
Data from: Strategies for understanding and reducing the Plasmodium vivax and Plasmodium ovale hypnozoite reservoir in Papua New Guinean children: a randomised placebo-controlled trial and mathematical model
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Data from: Modeling the impact of Plasmodium falciparum sexual stage immunity on the composition and dynamics of the human infectious reservoir for malaria in natural settings
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Simplified Green-Ampt model, imbibition-based estimates of permeability, and implications for leak-off in shale reservoirs
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Regression committee machine and petrophysical model jointly driven parameter reservoirs prediction from wireline logs for tight sandstone
<pre>This data comes from this study: "Regression committee machine and petrophysical model jointly driven parameter reservoirs prediction from wireline logs for tight sandstone". It is the intelligent prediction result of porosity, permeability and water saturation of two wells in the Ordos Basin, China</pre>
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).
Sacramento River RAFT water temperature model simulations based on hypothetical reservoir perturbations in the historical record
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Modelled annual evaporation of 187 reservoirs across the globe
<p>This dataset is the result of a MSc in biological sciences. The final thesis with detailed methods will be available shortly.</p>
Geometries, Driving Factors, And Connectivity Of Background Fractures At The Latemar Carbonate Platform (N. Italy): Relevance For Subsurface Reservoir Modelling_DATASETS
<p>The datasets (original field photographs and drone images) presented here are drawn from the extensive fieldwork by the author(s) at the Latemar carbonate platform in northern Italy. These datasets show different rock units in the Latemar platform riddled with diverse structural elements, including fractures (veins, joints, faults) and stylolites. In addition, the datasets are part of the paper titled "<strong>Geometries, Driving </strong><strong>F</strong><strong>actors, And Connectivity Of Background Fractures At The Latemar Carbonate Platform (N. Italy): Relevance For Subsurface Reservoir Modelling", </strong>submitted for publication in the Tectonics Journal. </p> <p>The drone images are taken with DJI Phantom 4® and processed using Agisoft PhotoScan® - a photogrammetry tool. The workflow in processing the drone images is publicly available in the published work of Bisdom et al. (2017).</p>
Dataset for efficient modelling of ionic and electronic interactions by resistive memory- based reservoir graph neural network
<p>Dataset for training the resistive memory-based reservoir graph neural network.</p> <p>In the atomic force calculation experiment, <span lang="EN-HK"><span>a Li</span><sub>3</sub><span>PO</span><sub>4</sub><span> dataset is derived from the melting and quenching trajectory via AIMD simulations. The training, validation, and testing datasets consist of 40,000, 5,000, and 5,000 samples, respectively. </span></span></p> <p><span lang="EN-HK"><span>In the Hamiltonian calculation, a dataset </span><span lang="EN-HK">of various graphene (72 atoms) configurations are generated by AIMD simulations at room temperature, with Hamiltonian data calculated via the OpenMX code</span><span lang="EN-HK">.</span><span lang="EN-HK"> <span>The training, validation, and testing datasets consist of 270, 90, and 90 samples (including atomic structure and Hamiltonian matrix), respectively.</span></span></span></p> <p>Code: https://github.com/hustmeng/RGNN.git</p> <p>1-Atomic_force_dataset.zip and 2-Hamiltonian_dataset.zip are original data.</p> <p>3-Graph_atomic_force.zip and 4-Graph_training_Hamiltonian.zip are graphs. </p> <p> </p> <p>References:</p> <p> </p> <p>1. C.W. Park, M. Kornbluth, J. Vandermause, C. Wolverton, B. Kozinsky, J.P. Mailoa, Accurate and scalable graph neural network force field and molecular dynamics with direct force architecture, npj Comput. Mater. 7(1) (2021) 73. https://github.com/ken2403/gnnff.git</p> <p>2. H. Li, Z. Wang, N. Zou, M. Ye, R. Xu, X. Gong, W. Duan, Y. Xu, Deep-learning density functional theory Hamiltonian for efficient ab initio electronic-structure calculation, Nat. Comput. Sci. 2(6) (2022) 367-377. https://github.com/mzjb/DeepH-pack.git</p> <p>3. D. Pfau, J.S. Spencer, A.G.D.G. Matthews, W.M.C. Foulkes, Ab initio solution of the many-electron Schrödinger equation with deep neural networks, Phys. Rev. Res. 2(3) (2020) 033429. https://github.com/google-deepmind/ferminet.git</p> <p> </p>
Understanding and Modeling Reservoirs, Vehicles and Transmission of ESBL-producing Enterobacteriaceae in the Community and Long Term Care Facilities
ClinicalTrials.gov study NCT03477084. IPD Sharing: NO. Countries: 1. Publications: 0.
Single cell transcriptomic analysis of acute and early ART-treated HIV-1-infected CD4+T cells from a reservoir-marking humanized mouse model
GEO Series GSE236107. Homo sapiens; Mus musculus. 14 samples. Type: Expression profiling by high throughput sequencing.
Enhancing reservoir water level time series in the Mekong river basin by improving area-elevation models and integrating multi-source satellite data
<p>This is a reservoir water surface area and water levels dataset including 32 major reservoirs in Mekong River basin. For all the 32 reservoirs, water levels were inverted by using improved DEM-derived A-E model (combined with actual reservoir parameters limitation), improved DEM-derived A-E model (combined with actual reservoir parameters limitation) or satellite-derived A-E model based on the Landsat-derived surface area. An initial time series was constructed based on the optimal improved A-E model according to their own altimetry data availability. Then all the altimetry water levels (if available) were merged into the initial time series to construct the final time series water levels.Altimetry water level was preferred when the date of two datasets was identical.</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.