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2,001 results for “X-Ray”
Out-of-equilibrium charge redistribution data in a copper-oxide based superconductor by time-resolved X-ray photoelectron spectroscopy
<p>This dataset was measured using a momentum microscope by time-resolved X-ray photoelectron spectroscopy (XPS) on the prototypical high-temperature superconductor: optimally doped BSCCO at FEL FLASH, DESY in Hamburg. With time-resolved XPS, unique access to the dynamics of individual atoms in the unit cell is granted by means of chemical shifts of the core levels. Though the induced changes are small, with a rigorous fitting procedure, it is possible to extract significant changes observed mainly at the oxygen atoms in the copper oxide planes, while other oxygen atoms as well as strontium remain largely unaffected. Although it was acquired not in the superconducting phase, the observed dynamics point to a significant coupling of energy scales involving charge-transfer processes and optical excitations. Such findings can thus provide another puzzle piece for a better understanding of high-temperature superconductivity.</p>
A high-throughput 3D X-ray histology facility for biomedical research and preclinical applications - Underlying Data
<p><strong>Video files and logs</strong></p> <p>Single-slice and thick-slice roll* source videos are included. Each video is accompanied by a .txt log that contains information about the source file, slice thickness, and a brief description of the visualization mode.</p> <p>List of files:</p> <ul> <li>20211019-23h59m_20xAvgInt.mp4</li> <li>20211019-23h59m_20xAvgInt.txt</li> <li>20211019-23h59m_20xMaxInt.mp4</li> <li>20211019-23h59m_20xMaxInt.txt</li> <li>20211019-23h59m_20xStDev.mp4</li> <li>20211019-23h59m_20xStDev.txt</li> <li>20211019-23h59m_XYSliceRoll.mp4</li> <li>20211019-23h59m_XYSliceRoll.txt</li> <li>20211019-23h59m_XZSliceRoll.mp4</li> <li>20211019-23h59m_XZSliceRoll.txt</li> <li>20211019-23h59m_YZSliceRoll.mp4</li> <li>20211019-23h59m_YZSliceRoll.txt</li> </ul> <p>* <em>Thick-slice rolling is a 2D thick-slice viewing that allows rolling of a pre-selected number of slices (n) along the z-axis of the 3D data. A single thick-slice roll forwards is accomplished by translating the thick-slice by one single slice forwards; that is moving forward by one (+1) slice from the first and nth element and reapplying the criteria or operations to the new slice sub-stack.</em></p> <p><strong>Volume XRH data</strong><br> These are processed raw volume file saved in .raw and/or .tiff format, which are resliced to a histology-relevant orientation and/or have been enhanced using noise reduction (3D median filter) and/or ct-artefact removal techniques (e.g. cBC identifies a bandpass filter used to remove intensity variations originating from the histology cassette).</p> <p>List of volume files:</p> <ul> <li><strong>32220_20200703_XRH_2504_OLK_DEMO02019-FFPE_1620x1959x164x16bit.raw</strong> <ul> <li>sample: Human lung adenocarcinoma</li> <li>histology-relevant resliced volume (2x2x2 3D medial filter applied)</li> <li>import as 1620 x 1959 x 164 x 16-bit, big-endian; voxel edge size (mm): 0.0160042 isotropic</li> </ul> </li> <li><strong>cBC_32220_20200703_XRH_2504_OLK_DEMO02019-FFPE_1588x1674x164x16bit.raw</strong> <ul> <li>sample: Human lung adenocarcinoma</li> <li>cassette artefacts background correction (bandpass) of volume 32220_20200703_XRH_2504_OLK_DEMO02019-FFPE_1620x1959x164x16bit.raw</li> <li>import as 1620 x 1959 x 164 x 16-bit, big-endian; voxel edge size (mm): 0.0160042 isotropic</li> </ul> </li> <li><strong>Med3D_HPass_2111_20190606_MEDX_2234_EH_HN2_recon_2000x1952x501x32bit.raw</strong> <ul> <li>sample: Human head and neck tumour</li> <li>histology-relevant resliced volume (1x1x1 3D medial filter applied)</li> <li>import as 2000 x 1952 x 501 x 32-bit, big-endian; voxel edge size (mm): 0.00999782 isotropic</li> </ul> </li> </ul> <p><strong>Conventional Histology and correlative imaging</strong></p> <ul> <li><strong>HN2_Level001_MEDX080_Manual_BW_Series4.tif</strong> <ul> <li>H&E histology slice of the human head and neck tumour sample shown in "Med3D_HPass_2111_20190606_MEDX_2234_EH_HN2_recon_2000x1952x501x32bit.raw"</li> </ul> </li> <li><strong>HN2_Level001_MEDX080_Manual_BW</strong> <ul> <li>manual landmark selection used for registering the conventional histology slice onto the μCT slice</li> </ul> </li> <li><strong>HN2_MEDX_rotated_0080.tif</strong> <ul> <li>Slice 80 from volume "Med3D_HPass_2111_20190606_MEDX_2234_EH_HN2_recon_2000x1952x501x32bit.raw" that corresponds to histological slice "HN2_Level001_MEDX080_Manual_BW"</li> </ul> </li> </ul>
Supplementary Data for Low-loss stable storage of 1.2 Angstrom X-ray pulses in a 14 m Bragg cavity
<p>Supplementary Data for Margraf, R. et al. "Low-loss stable storage of 1.2 Angstrom X-ray pulses in a 14 m Bragg cavity," Nature Photonics, 2023.</p>
PTX-498: A multi-center pneumothorax segmentation chest X-ray image dataset
<p>Pneumothorax is a common medical emergency defined as the abnormal collection of air in the pleural space between the lung and chest wall. Its typical symptoms include chest pain and dyspnea, leading to oxygen deficiency or even life-threatening in severe cases. Therefore, an efficient and automatic pneumothorax diagnosis algorithm would be useful in many clinical scenarios. Recently, deep learning methods have achieved impressive progress in medical image segmentation tasks. However, a large-scale dataset is one of the critical components for the success of deep learning. On the other hand, there are few public chest X-ray images with pneumothorax.</p> <p>To stimulate the researchers' interest in the pneumothorax diagnosis algorithm, <strong>we released a new data set PTX-498 here. It contains 498 chest X-ray images of pneumothorax collected from three hospitals, and each image contains pixel-level annotations.</strong> All images were resized to 1024×1024. The raw image intensity was clipped according to the window width and level inside the dicom tag and then normalized to 0 to 255. The contours of the pneumothorax area were labelled by two senior radiologists using ITK-SNAP. The dataset was anonymized and every record related to patients' privacy was removed. Only the image data and the corresponding labels were included in PTX-498.</p> <p><strong>Please use the latest v2-fix version which removes duplicate images and uses the window width and level from the original dicom tag for normalization.</strong></p> <p><strong>Citation: If you are interested in this dataset and applying it in your research, please cite the following article.</strong><br> Paper link: https://doi.org/10.1016/j.neucom.2021.05.029<br> Cite this article as Yunpeng Wang, Kang Wang, Xueqing Peng, Lili Shi, Jing Sun, Shibao Zheng, Fei Shan, Weiya Shi, Lei Liu*. DeepSDM: Boundary-aware pneumothorax segmentation in chest X-ray images [J]. Neurocomputing, 2021, 454: 201-211.</p> <div> <div class="gtx-trans-icon"> </div> </div>
Hyperspectral 2D fan-beam X-ray CT dataset of 5 materials
<p>Hyperspectral X-ray CT dataset acquired at the DTU 3D imaging center. The phantom consists of 5 materials: Aluminium (10 mm) and PVC (7.8 mm) in solid blocks. Sugar, H2O2, and H2O in circular glass containers.</p> <p>3D array with dimension: 128 x 370 x 258 < channel, angle, horizontal ></p> <p> </p> <p>Detector parameters:</p> <p>Number of detector pixels: 258 (concatenated from 2 detector modules with 128 pixels each and 2 pixel interpolated across a gap between detectors)</p> <p>Pixel size: 0.077 cm</p> <p>Sep=0.153 Pixels' gap length (cm)</p> <p>det_space=(ndet)*pixel_size+Sep # physical width of detector in cm (pixels*pixel_size), including the gap</p> <p> </p> <p>Acquisition Parameters</p> <p>360 # Angular span of projections in degrees</p> <p>370 # Number of projections. note: last projection taken is not a duplicate of the first projection. At angle: 360/370 degrees from first projection.</p> <p>115.0 # Source-Detector distance in cm</p> <p>0 # Vertical source shift from perfect placement</p> <p>0 # Vertical detector shift from perfect placement</p> <p>57.5 # Source-AxisOfRotation distance in cm</p> <p> </p> <p>rot_axis_x = 0 # x-position offset of AxisOfRotation</p> <p>rot_axis_y = 0 # y-position offset of AxisOfRotation</p>
small angle x-ray scattering from Zr-Cu-Ag metallic glass coatings
<p>small angle x-ray scattering from Zr-Cu-ag metallic glass coating to confirm whether they became amorphous or not. The coating is on PBT substrate. </p>
X-ray and optical light curves of the M dwarf dipper star TIC 234284556
<p>We observed the star TIC 234284556 with XMM-Newton in soft X-rays and in the optical for ca. 35 hours (127.8 ks), starting 2022-04-16 22:58:46, ObsID 0881050101.</p> <p>We provide here two extracted soft X-ray light curves (energy band 0.2-2 keV) collected with XMM-Newton's PN camera, namely for a circular extraction region with 20 arcsec radius centered on the position of the M dwarf star TIC 234284556 (pn_lca_02_2.fits) with 100 seconds time binning, and a background light curve with the same energy range and time binning extracted for a PN background region with a three times larger radius (pn_lcabg_02_2.fits). We also provide optical light curves in the V band, collected with XMM-Newton's Optical Monitor with 10 seconds cadence (file names P0881050101OMS0**TIMESR0000.FIT).</p> <p>A barycentric correction, using the XMM-SAS task "barycen", has been applied to the PN and OM time columns. The time coordinate is given in seconds since BJD 2450814.5 (1998-01-01 00:00:00).</p>
Diffraction data underpinning the structure of StayGold determined by X-ray crystallography (PDB code 8BXT)
<p>Raw diffraction data underpinning the crystal structure of StayGold fluorescent protein.</p> <p>This is the raw data underpinning PDB entry 8BXT.</p>
Reproduction package for the publication 'Prospects for detecting the circum- and intergalactic medium in X-ray absorption using the extended intracluster medium as a backlight'
<p>The uploaded files can be used to reproduce the dataset and figures in the paper<strong> Prospects for detecting the circum- and intergalactic medium in X-ray absorption using the extended intracluster medium as a backlight</strong> by Lýdia Štofanová, Aurora Simionescu, Nastasha A. Wijers, Joop Schaye, Jelle Kaastra, Yannick M. Bahé, and Andrés Arámburo-García.</p><p>NOTE: Files will be published with a new version. </p>
Supplementary Materials for "Simultaneous single-shot radiographic imaging using a laser-driven x-ray and proton micro-source"
<p>Simulation Data Repository, please read the contained README file in the contained simulation/ directory.</p> <p>This directory contains a copy of the used PIConGPU source code, version 0.5.0-dev-60ad9eb85 and analysis scripts.</p> <p>The PIConGPU source code is archived including its complete git history (git version 2.17.1) in source/picongpu.tar.gz with the input parameter template inside in share/picongpu/examples/Wneedle .</p> <p>Generally, PIConGPU source code is available via <a href="https://doi.org/10.5281/zenodo.591746">https://doi.org/10.5281/zenodo.591746</a> with its public git repository being maintained on <a href="https://github.com/ComputationalRadiationPhysics/picongpu">https://github.com/ComputationalRadiationPhysics/picongpu</a> .</p> <p>The two simulations’ exact input is modified accordingly in the directory input/ inside: 2D_a0-45_Z-10_ppc-20_002_light.tar.gz (p-polarized; along X) 2D_a0-45_Z-10_ppc-20_003_light.tar.gz (s-polarized; along Z).</p> <p>“Heavy” simulation data (checkpoints in simOutput/checkpoints/, full-resolution field and particle output in simOutput/bp/ ) has been stripped from this archive and are archived on NERSC’s HPSS tape archive.</p> <p>Analysis scripts are provided as Jupyter notebooks (DensityPlot_polX.ipynb and DensityPlot_polZ.ipynb) and depend on the following software:</p> <p>- adios 1.13.1 python bindings with enabled c-blosc transformations<br> - numpy 1.17.1<br> - matplotlib 3.1.1<br> - PIConGPU post-processing helper modules located in each simulation root directory under “input/lib/python/”<br> <br> The detailed conda environment can be found in the README.</p>
IODP Expedition 361 X-ray diffraction (XRD)
<p>X-ray diffraction (XRD) is used to identify minerals and their proportions in sediment or hard rock sample powders on a Bruker AXS D4 Endeavor X-ray diffractometer. Results are returned as diffractograms in a viewable format (either PDF or PNG).</p>
Data Accompanying "Dynamics of Water Absorption in Callovo-Oxfordian Claystone Revealed With Multimodal X-Ray and Neutron Tomography"
<p>These are the datasets analysed in the publication "Dynamics of Water Absorption in<br> Callovo-Oxfordian Claystone Revealed With Multimodal X-Ray and Neutron Tomography" by Stavropoulou <em>et al.</em> in 2020 in Frontiers in Earth Science, DOI: <a href="https://doi.org/10.3389/feart.2020.00006">https://doi.org/10.3389/feart.2020.00006</a></p> <ol> <li>File 1 contains the 3D reconstructed x-ray and neutron tomography volumes analysed in the paper. State 002 is taken as a reference and the greylevels of all images in the times series for both x-ray and neutrons are rescaled using two characteristic image features (top-cap and air in the case of x-rays) linearly to align with 002. Neutron volumes are rescaled to the same pixel size as 2-bin x-ray volumes, and a mean registration is applied to align neutrons with x-rays.<br> Furthermore, a bilateral filter is applied to the neutron tomographies (domain sigma = 1, range sigma=3000).<br> Full scale images are available at <a href="https://doi.ill.fr/10.5291/ILL-DATA.UGA-42">https://doi.ill.fr/10.5291/ILL-DATA.UGA-42</a><br> </li> <li>File 2 contains the joint histograms for registered pairs of images, as visible in Figure 4 and Figure 5.<br> </li> <li>File 3 contains the results of the digital volume correlation performed with the <a href="https://ttk.gricad-pages.univ-grenoble-alpes.fr/spam/intro.html">spam</a> tookit.<br> The overall "registration" is used to create Figure 6<br> The global correlations available in "gdic" are used to create Figures 7, 8 and 9.</li> </ol>
Nanoscale Imaging of High-Field Magnetic Hysteresis in Meteoritic Metal Using X-Ray Holography
<p>Data of magnetisation (two datasets) of the cloudy zone of Tazewell IIICD iron meteorite. Data was obtained using X-ray holography. Magnetization data is a 3D matrix containing magnetisation data in form of data[x location][y location][applied field], applied field values is provided in a separate file.</p> <p>Further details about this dataset and conditions of measurements can be found in Blukis et al., 2020 submitted to Geochemistry, Geophysics, Geosystems</p>
Time- and angle-resolved photoemission spectroscopy data and time-resolved X-ray diffraction data of TbTe3
<p>Time- and angle-resolved photoemission spectroscopy data of bulk terbium tritelluride (TbTe3, unidirectional charge-density-wave phase, T=100K) using a laser-based femtosecond XUV source and a hemispherical analyzer for photoelectron detection at the Fritz-Haber-Institute, Berlin, Germany. The 3D (angle, energy, pump-probe-delay) datasets include the photoemission intensities for various pump-laser fluences.</p> <p>The time-resolved X-ray diffraction data were obtained at the Femto hard X-ray slicing source at the Swiss Light Source, and include the charge-density-wave superlattice (2 10 1+q_CDW) peak intensities as functions of pump-probe-delay for various pump-laser fluences.</p> <p>The data and associated metadata are stored in the NeXus data format (https://www.nexusformat.org/).</p>
X-ray computed tomography of bedded halite and halite crystals from the Bonneville Salt Flats
<p>X-ray computed tomography of bedded halite and halite crystals from the Bonneville Salt Flats, Utah. </p>
Computational atomic coordinate files for Quantification of Ni-N-O bond angles and NO activation by X-ray emission spectroscopy
<p>Geometry optimized coordinates and other atomic coordinate files in xyz format used to calculate X-ray emission spectra of beta-diketiminate nickel nitrosyl complexes.</p>
Analysis of insulin glulisine at the molecular level by X-ray crystallography and biophysical techniques
<p>Raw diffraction images for the study:- Gillis, R.B., Solomon, H.V., Govada, L. <em>et al.</em> Analysis of insulin glulisine at the molecular level by X-ray crystallography and biophysical techniques. <em>Sci Rep</em> <strong>11, </strong>1737 (2021). https://doi.org/10.1038/s41598-021-81251-2 </p> <p>PDB code 6GV0.</p>
IODP Expedition 368X X-ray diffraction (XRD)
<p>X-ray diffraction (XRD) is used to identify minerals and their proportions in sediment or hard rock sample powders on a Bruker AXS D4 Endeavor X-ray diffractometer. Results are returned as diffractograms in a viewable format (either PDF or PNG).</p>
Raw X-Ray CT data of CFC-Cu_GS laser flash coupon
<p>Raw X-Ray CT data for CFC-Cu_GS laser flash coupon. The coupon was manufactured at Politecnico di Torino, Italy (Dr Valentina Casalegno) and X-ray tomography scanning was performed at the Manchester X-ray Imaging Facility, University of Manchester, UK (Dr Llion Evans).</p> <p>This data was used for the publications:</p> <p> - Evans, Ll.M. et al. "Thermal characterisation of ceramic/metal joining techniques for fusion applications using X-ray tomography", Fusion Engineering and Design, Volume 89, Issue 6, June 2014, Pages 826-836, http://dx.doi.org/10.1016/j.fusengdes.2014.05.002.</p> <p> - Evans, Ll.M. et al. "Transient Thermal Finite Element Analysis of CFC-Cu ITER Monoblock Using X-ray Tomography Data", Fusion Engineering and Design 2015, DOI: 10.1016/j.fusengdes.2015.04.048.</p>
X-ray Reflection Table Models
<p>Xspec Table Models of Monte Carlo X-ray reflection simulations from Giant Molecular Clouds.</p> <p>See, http://arxiv.org/abs/1609.00175, for description of the models.</p> <p>The number on the end of each file name represents the iron abundance relative to solar.</p>
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.