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994 results for “2d”
Tailoring optical properties of 2D semiconductors in van der Waals heterostructures
<p>Dataset for the publication 'Tailoring the dielectric screening in WS<sub>2</sub>-graphene heterostructures'</p>
Ultrasound Stochastic Tomography simulation data for In-silico 2D Breast Phantom model with tumour
<p>An anatomically realistic numerical breast phantom model (with realistic acoustic properties of speed of sound, density, and attenuation coefficient of tissues) derived from [1] is presented with details of a ultrasound tomography experiment in simulation. Details of source wavelets, geometry of transducer set, observed data at each transducer for each shots are provided with phantom model.</p> <p>References</p> <p>[1] <a href="https://anastasio.bioengineering.illinois.edu/downloadable-content/oa-breast-database/">https://anastasio.bioengineering.illinois.edu/downloadable-content/oa-breast-database/</a></p>
Dataset for the paper High durability and stability of 2D nanofluidic devices for long-term single-molecule sensing
<p>Information regarding the Dataset, corresponding to the paper: “Thakur, M., Cai, N., Zhang, M. et al. High durability and stability of 2D nanofluidic devices for long-term single-molecule sensing. npj 2D Mater Appl 7, 11 (2023). https://doi.org/10.1038/s41699-023-00373-5”</p> <p>This folder contains the raw data and complete package of codes used to analyze, view, save, and plot data for the publication titled "High durability and stability of 2D nanofluidic devices for long-term single-molecule sensing". The code folder, "OpenNanopore-nanopore-tools", can be used to plot raw data which corresponds to the figures in the paper and supplementary information. </p>
Immobilized fluorescently stained zebrafish through the eXtended Field of view Light Field Microscope 2D-3D dataset
<p><strong>Immobilized fluorescently stained zebrafish through the eXtended Field of view Light Field Microscope 2D-3D dataset</strong></p> <p>This dataset comprises three immobilized fluorescently stained zebrafish imaged through the eXtended Field of view Light Field Microscope (XLFM, also known as Fourier Light Field Microscope). The images were preprocessed with the <a href="https://github.com/pvjosue/SLNet_XLFMNet">SLNet</a>, which extracts the sparse signals from the images (a.k.a. the neural activity).</p> <p>If you intend to use this with Pytorch, you can find a data loader and working source code to load and train networks <a href="https://github.com/pvjosue/CWFA">here</a>.</p> <p>This dataset is part of the publication: Fast light-field 3D microscopy with out-of-distribution detection and adaptation through Conditional Normalizing Flows.</p> <p> </p> <p>The fish present are:</p> <ul> <li>1x NLS GCaMP6s</li> <li>1x Pan-neuronal nuclear localized GCaMP6s Tg(HuC:H2B:GCaMP6s)</li> <li>1x Soma localized GCaMP7f Tg(HuC:somaGCaMP7f)</li> </ul> <p> </p> <p>The dataset is structured as follows::</p> <p>XLFM_dataset</p> <ul> <li><em>Dataset/</em> <ul> <li><em>GCaMP6s_NLS_1/</em> <ul> <li><em>SLNet_preprocessed/</em> <ul> <li><em>XLFM_image/</em> <ul> <li><em>XLFM_image_stack.tif</em>: tif stack of 600 preprocessed XLFM images.</li> </ul> </li> <li><em>XLFM_stack/</em> <ul> <li><em>XLFM_stack_nnn.tif</em>: 3D stack corresponding to frame nnn.</li> </ul> </li> <li><em>Neural_activity_coordinates.csv</em>: 3D coordinates of neurons found through the <a href="https://www.biorxiv.org/content/10.1101/061507v2">suite2p framework</a>.</li> </ul> </li> <li><em>Raw/</em> <ul> <li><em>XLFM_image/</em> <ul> <li><em>XLFM_image_stack.tif:</em> tif stack of 600 raw XLFM images.</li> </ul> </li> </ul> </li> </ul> </li> <li>(other samples)</li> </ul> </li> <li><em>lenslet_centers_python.txt</em>: 2D coordinates of the lenset in the XLFM images.</li> <li><em>PSF_241depths_16bit.tif: 3D PSF of the microscope can be used for 3D deconvolution. Spanning 734 × 734 × 550𝜇𝑚3 used to deconvolve this volumes. </em></li> </ul> <p> </p> <p>In this dataset, we provide a subset of the images and volumes.</p> <p>Due to space constraints, we provide the 3D volumes only for:</p> <ul> <li><em>SLNet_preprocessed/XLFM_stack/</em> <ul> <li>10 interleaved frames between frames 0-499 (can be used for training a network).</li> <li>20 consecutive frames, 500-520 (can be used for testing).</li> </ul> </li> <li><em>raw/</em> <ul> <li>No volumes are provided for raw data, but they can be reconstructed through 3D deconvolution.</li> </ul> </li> </ul> <p> </p> <p>Enjoy, and feel free to contact us for any information request, like the full PSF, 3 more samples or longer image sequences.</p> <p> </p> <p> </p> <p> </p>
Numerical Modeling of Asteroid Impact in 2D Cylindrical Coordinates
<p>Additional material and code for the Bachelor Thesis "Numerical Modeling of Asteroid Impact in 2D Cylindrical Coordinates" </p>
Data for Transient 2D IR spectroscopy and multiscale simulations reveal vibrational couplings in the Cyanobacteriochrome Slr1393-g3
<p>Data used in the Manuscript Transient 2D IR spectroscopy and multiscale simulations reveal vibrational couplings in the Cyanobacteriochrome Slr1393-g3</p>
Input and output data from simulations of 2D valves and 3D inflow-outflow model using particle methods
<p>Input and output data of open-source softwares for computational fluid dynamics simulation involving fluid-structure interaction.</p> <p> </p> <p><strong>Data from two studies</strong></p> <ol> <li>Verifications of the weakly-compressible smoothed particle hydrodynamics (WCSPH) method, open-source code <a href="https://www.sphinxsys.org">SPHinXsys</a>, when applied to the flow of idealized 2D valve models.</li> <li>Validations of inflow-outflow model in moving particle semi-implicit (MPS) method, open-source code <a href="https://github.com/rubensamarojr/polymps/tree/inOutflow">PolyMPS</a>.</li> </ol> <p> </p> <p><strong>Folders and Files</strong></p> <p><strong>valve-2D.zip </strong>is the folder with data from the idealized models of vertical and curved 2D valves:</p> <ul> <li>Vertical valves with parameters provided in <a href="https://doi.org/10.1016/j.jcp.2010.08.005">Gil et al., 2010</a></li> <li>Curved valves with parameters provided in <a href="http://doi.org/10.1007/s00466-013-0890-3">Wick, 2014</a></li> <li>source files (.cpp): input data (physical and numerical parameters) for SPHinXsys</li> <li>text files: SPHinXsys (.dat) and Reference (.tsv) results</li> <li>python files (.py): Generates the graphics</li> </ul> <p> </p> <p><strong>inflow-outflow-3D.zip </strong>is the folder with data from the inflow-outflow model in MPS:</p> <ul> <li>Fluid physical properties of water <ul> <li><span>\(\rho=1000kg/m^3 , \,\, \nu=10^{-6}m/s^{-2}\)</span></li> </ul> </li> <li>Pipes of length <span>\(L=0.15m\)</span>: <ul> <li>circular section of diameter <span>\(D=0.1m\)</span>.</li> <li>square section of sides <span>\(S=0.1m\)</span>.</li> </ul> </li> <li>Constante pressure variation (<span>\(\Delta P = 30 \,\, or \,\, 50 \,\, Pa\)</span>) between inflow and outflow: <ul> <li><span>\(\frac{\partial p}{\partial x} = - \frac{\Delta P}{L}, \\ \Delta P = P_{outflow} - P_{inflow}\)</span></li> </ul> </li> </ul> <ul> <li>Sinusoidal pressure variation (<span>\(\Delta P =700Pa \,\, , \,\, T = 2.0s\)</span>) between inflow and outflow <ul> <li><span>\(\frac{\partial p}{\partial x} = - \frac{\Delta P}{L} \sin \omega t \, \\ \omega = \frac{2\pi}{T} \\ Delta P = P_{outflow} - P_{inflow}\)</span></li> </ul> </li> <li>input data (.json, .grid, .stl): physical properties, numerical parameters and geometries for PolyMPS can be found at <a href="https://github.com/rubensamarojr/polymps/tree/inOutflow/input">https://github.com/rubensamarojr/polymps/tree/inOutflow/input</a></li> <li>text files (.txt): PolyMPS and OpenFOAM results</li> <li>python files (.py): Generates the graphics</li> </ul> <p> </p> <p><strong>References</strong></p> <p><a href="https://doi.org/10.1016/j.jcp.2010.08.005">A. J. Gil. The Immersed Structural Potential Method for haemodynamic applications. J. Comput. Phys., 229 (2010), pp. 8613-8641</a></p> <p><a href="https://doi.org/10.1007/s00466-013-0890-3">T. Wick. Flapping and contact FSI computations with the fluid–solid interface-tracking/interface-capturing technique and mesh adaptivity. Comput Mech 53, 29–43 (2014)</a></p> <p><a href="https://doi.org/10.1016/j.cma.2014.10.040">D. Kamensky, et al. An immersogeometric variational framework for fluid–structure interaction: Application to bioprosthetic heart valves Comput. Methods Appl. Mech. Engrg., 284 (2015), pp. 1005-1053</a></p> <p><a href="https://doi.org/10.1016/j.cma.2015.12.023">C. Kadapa et al. A fictitious domain/distributed Lagrange multiplier based fluid–structure interaction scheme with hierarchical B-Spline grids. Comput. Methods Appl. Mech. Engrg., 301 (2016), pp. 1-27</a></p> <p><a href="https://doi.org/10.1016/j.jcp.2015.10.015">Jie Liu. A second-order changing-connectivity ALE scheme and its application to FSI with large convection of fluids and near contact of structures. J. Comput. Phys., 304 (2016), pp. 308-423</a></p>
CAIRT Complete Data Fusion 2D - Input/Output Dataset
<p>This package contains input/output data of tool Complete_Data_Fusion_2D (CDF_2D)(https://doi.org/10.5281/zenodo.8290163) which performs the 2D data fusion of CAIRT with IASI-NG, Sentinel 5 (S5) simulated measurements, both flying on MetOp-SG A which CAIRT will be in formation with.</p>
Strain Evolution in 2D-Digital Composites-T= 1-15 time steps.
<p>Strain Evolution in 2D - Digital Composites for first 15 time steps.</p> <p>Abaqus simulation script can be found <a href="https://github.com/M3RG-IITD/StrainEvolution">here</a></p>
Dataset for "Universal scaling of the dynamic BKT transition in quenched 2D Bose gases"
<p>This repository contains data and numerical simulation code for Sunami et. al., "Universal scaling of the dynamic BKT transition in quenched 2D Bose gases".</p> <p>The data is stored in the format of hdf5 (Hierarchical Data Format), which can be read from standard programming environment such as python (h5py), matlab (`h5read`), and many others.</p> <p>Numerical simulation scripts consist of functions.c, MonteCarloSampling.cpp and phase12_den_sample_time.cpp. Please see the section for numerical simulation in the Supplementary Material.</p> <p>The description for each hdf5 file in this repository is provided in readme.txt.</p>
Datasets for 2D Vertical Convection: Base States and Leading Linear Modes using Snek5000-cbox
<p>This repository contains two types of datasets related to 2D vertical convection analysis, generated using the snek5000-cbox simulation framework. The first dataset includes base states computed with the Selective Frequency Damping (SFD) method, considering various aspect ratios and Prandtl numbers. The second dataset provides the decomposed amplitude, phase, frequency, and omega of the leading linear mode, accompanied by the corresponding base states for different aspect ratios and Prandtl numbers. All datasets are stored in the .h5 file format for easy access and analysis. The scripts used to produce the datasets are provided in the repository https://github.com/snek5000/snek5000-cbox/tree/main/doc/scripts/2022sidewall_conv_instabilities.</p>
Datasets for 'Estmating autonomous vehicle localization error using 2D Geographic Information'
<p>Datasets for 'Estmating autonomous vehicle localization error using 2D Geographic Information'</p>
2D and 3D coral models imaged in Curaçao: George, Mullinix, et al PeerJ 2021
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Hot carrier extraction from 2D semiconductor photoelectrodes
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Data from: Multi-gesture drag-and-drop decoding in a 2D iBCI control task
Open the record for dataset details and reuse information.
Data from: Cornerstones are the key stones: Using interpretable machine learning to probe the clogging process in 2D granular hoppers
Open the record for dataset details and reuse information.
2D Herbig Ae/Be disk models for HD far-infrared lines (Kama et al. 2020)
<p>In this work 2D physical-chemical models of Herbig Ae/Be protoplanetary disks have been run to relate HD far-infrared line fluxes to gas masses. The tables give DALI model parameters and matching HD far-infrared line fluxes used in Kama et al. 2020 (A&A 634, A88 (2020); doi:10.1051/0004-6361/201937124)</p>
Dataset: 2D particle-in-cell (PIC) simulation of the magnetic reconnection for the paper "Electron mixing and isotropization in the exhaust of asymmetric magnetic reconnection with a guide field"
<p>This repository contains pubilicly available numerical data of a 2D magnetic reconnection event, which includes the field data and plasma moment data. The simulation is performed with the VPIC code. The simulated data are used for the paper "Electron mixing and isotropization in the exhaust of asymmetric magnetic reconnection with a guide field". </p>
Fig. 3.2 in Handbook of best practice and standards for 2D+ and 3D imaging of natural history collections
Fig. 3.2. Camera positions of a single rotation when taking pictures of an object.
Fig. 4.1 in Handbook of best practice and standards for 2D+ and 3D imaging of natural history collections
Fig. 4.1. Scorpion pictured in UV fluorescence. Focus stacking image.
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.