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2,895 results for “rays”
Photonics4All Bookmark Blu-Ray (Swedish)
<p>The purpose of the bookmarks for the project Photonics4all is to increase the public awareness of photonics and especially of the technological advances of photonics which have changed and improved everyday life (basic technology introduction).</p> <p>How many Blu-Ray movies can you download through one fibre optic cable?</p> <p>300 movies per second! Submarine communications cables which are laid on the sea bed between land-based stations carry telecommunication signals across the globe underwater. These cables can have total lengths of over 21,000 km and have a capacity of 10 Terabits per second (Tb/s). The information is carried by flashing laser light using a Morse-code like signal through the optical fibre. Nowadays the fibre optic comes straight into our homes to deliver on-line video and TV programmes with fantastic (4K) resolution.</p> <p>In the future, new types of optical switches (rather than electronic switches) made with a recently discovered material graphene will enable 1000 times faster connections.</p> <p>All thanks to progress with Photonics!</p>
Photonics4All Bookmark Blu-Ray (French)
<p>The purpose of the bookmarks for the project Photonics4all is to increase the public awareness of photonics and especially of the technological advances of photonics which have changed and improved everyday life (basic technology introduction).</p> <p>How many Blu-Ray movies can you download through one fibre optic cable?</p> <p>300 movies per second! Submarine communications cables which are laid on the sea bed between land-based stations carry telecommunication signals across the globe underwater. These cables can have total lengths of over 21,000 km and have a capacity of 10 Terabits per second (Tb/s). The information is carried by flashing laser light using a Morse-code like signal through the optical fibre. Nowadays the fibre optic comes straight into our homes to deliver on-line video and TV programmes with fantastic (4K) resolution.</p> <p>In the future, new types of optical switches (rather than electronic switches) made with a recently discovered material graphene will enable 1000 times faster connections.</p> <p>All thanks to progress with Photonics!</p>
Photonics4All Bookmark Blu-Ray (English)
<p>The purpose of the bookmarks for the project Photonics4all is to increase the public awareness of photonics and especially of the technological advances of photonics which have changed and improved everyday life (basic technology introduction).</p> <p>How many Blu-Ray movies can you download through one fibre optic cable?</p> <p>300 movies per second! Submarine communications cables which are laid on the sea bed between land-based stations carry telecommunication signals across the globe underwater. These cables can have total lengths of over 21,000 km and have a capacity of 10 Terabits per second (Tb/s). The information is carried by flashing laser light using a Morse-code like signal through the optical fibre. Nowadays the fibre optic comes straight into our homes to deliver on-line video and TV programmes with fantastic (4K) resolution.</p> <p>In the future, new types of optical switches (rather than electronic switches) made with a recently discovered material graphene will enable 1000 times faster connections.</p> <p>All thanks to progress with Photonics!</p>
X-ray diffraction images for an MDM2/Nutlin-3a complex
<p>This submission includes a zip archive of diffraction images recorded with the MARMOSAIC 225 mm CCD detector at the ESRF beam line ID23-2. Relevant meta data can be found in the headers of those diffraction images or in the Protein Data Bank entry 4HG7.</p>
A high-throughput 3D X-ray histology facility for biomedical research and preclinical applications - Supplementary Data
<p><strong>Videos</strong></p><ul><li><strong>Video 1</strong> A video going through the Z stack in single slices. This is a cross- sectional view of the XRH image stack along the XY plane. XRH datasets are normally oriented (resliced) in a way that a scroll through the stack along the XY plane emulates the physical histology slicing of the tissue.</li><li><strong>Video 2 </strong>A video going through the Y stack in single slices. This is a cross- sectional view of the XRH image stack along the XZ plane. XRH datasets are normally oriented (resliced) in a way that a scroll through the stack along the XY plane emulates the physical histology slicing of the tissue.</li><li><strong>Video 3 </strong>A video going through the X stack in single slices. This is a cross- sectional view of the XRH image stack along the YZ plane. XRH datasets are normally oriented (resliced) in a way that a scroll through the stack along the XY plane emulates the physical histology slicing of the tissue.</li><li><strong>Video 4 </strong>3D X-ray histology (XRH) is a µCT -based workflow tailored to fit seamlessly into current histology workflows in biomedical and pre-clinical research, as well as clinical histopathology. Microanatomical detail can be captured from standard (non-stained) formalin-fixed and paraffin-embedded (FFPE) tissue blocks.</li><li><strong>Video 5</strong> Average Intensity Projection (AIP) of the sample through the Histologically relevant plane. This is a 2D visualisation rendering the Average Intensity of 20x single XY slices along the z-axis of the stack. XRH datasets are normally oriented (resliced) in a way that a scroll through the stack along the XY plane emulates the physical histology slicing of the tissue.</li><li><strong>Video 6 </strong>Maximum Intensity Projection (MIP) of the sample through the Histologically relevant plane. This is a 2D visualisation rendering the Maximum Intensity of 20x single XY slices along the z-axis of the stack. XRH datasets are normally oriented (resliced) in a way that a scroll through the stack along the XY plane emulates the physical histology slicing of the tissue.</li><li><strong>Video 7 </strong>Standard deviation projection of the sample going through the histologically relevant plane. This is a 2D visualisation rendering the Standard Deviation of 20x single XY slices along the z- axis of the stack. XRH datasets are normally oriented (resliced) in a way that a scroll through the stack along the XY plane emulates the physical histology slicing of the tissue.</li></ul><p><i>* <strong>Videos 5 -7</strong> are also referred to as "thick-slice rolls" </i>- <i>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.</i><br> </p><p><strong>The questionnaire used to collect feedback about the needs of the XRH community.</strong></p><ul><li>Survey.docx</li><li>Survey.pdf</li></ul><p><br><strong>Exemplar report of a semi-automatically generated augmented PDF file</strong> that contain sample information, imaging settings, still images with descriptive figure legends, and links to corresponding online videos</p><ul><li>DEMO02019-FFPE_report_99EbPXG.pdf</li></ul><p> </p><p>= = = = = = = = = = = = = = = = <br><strong>System performance data ZIP</strong><br>= = = = = = = = = = = = = = = = </p><p>This ZIP file contains imaging data collected through different systems and setups at the XRH facility at the μ-VIS X-ray Imaging Centre at the University of Southampton for the purpose of acceptance and/or system performance characterisation. Below is an overview of the folder structure and its contents</p><p>The following files are X-ray imaging data collected on September 28, 2017, using the Med-X system and a Jima phantom at 55 kV peak and 7 Watts. </p><ul><li>20170928_MEDX_1642_JIMA_55kVp7W-2.tif</li><li>20170928_MEDX_1642_JIMA_55kVp7W.tif</li><li>20170928_MEDX_1642_JIMA_55kVp7W.tif.profile.xml</li></ul><p>This PDF document is related to a QRM MicroCT bar pattern phantom, and its specifications</p><ul><li>QRM-MicroCT-Barpattern-Phantom.pdf</li></ul><p>Graphs showing the calculated focal-spot size as a function of the X-ray power (W) for the Molybdenum rotating target calculated using Edge Modulation function testing. The performance is then compared with the performance of the Reflection target across the same range of powers. Raw data can be found in XRH_QRM_Refl-vs-Rot-TargetComparison_SingleReconSlices_5umPixelSize folder. Test performed in July 2021. </p><ul><li>XRH_202107_MoRot-testing_EdgeModFunction-QRMrecons+RotReflCompar.png</li></ul><p> </p><p><i><strong>/ XRH-XT-H-225-ST_FocalSpots</strong></i><br>This directory contains radiographic data collected using the XRH system with a JIMA phantom and MoRt (Molybdenum rotating), TT (Transmission), and Reflection targets.</p><ul><li>20200113_XRH_Jima test MoRT 55kV 15W.tif, 20200113_XRH_Jima test MoRT 55kV 30W.tif, etc.: <br>These files represent radiographs taken on January 13, 2020, using the XRH system, Jima phantom, MoRT target at 55 kVp and varying wattages.</li><li>20200207_XRH_JIMA 80kV TT1a.tif, 20200207_XRH_JIMA 80kV TT1b.tif, etc.<br>Similar to the above, these files are from February 7, 2020, and use 80 kVp with a TT target.</li><li>20231115_XRH_reflW_80kVp6W.tif, 20231115_XRH_reflW_80kVp6W_02.tif, etc.<br>These files are from November 15, 2023, and collected using the XRH system with a Reflection target at 80 kVp and 6 Watts.</li></ul><p><i><strong>/ XRH_QRM_Refl-vs-Rot-TargetComparison_SingleRadioFromCTs_5umPixelSize</strong></i><br>This directory contains single radiographs taken with a pixel size of 5 micrometers using the Molybdenum rotating (MoRt), and the Reflection target using tungsten (W) and Molybdenum (Mo) metals.</p><p><i><strong>/ XRH_QRM_Refl-vs-Rot-TargetComparison_SingleReconSlices_5umPixelSize</strong></i><br>This directory contains sinlge reconstruction slices of the setups mentioned above. Slices are exported from CT volumes and were used for the Edge Modulation function study. </p><p>For interpretation of the filenames in the folders listed above please see below and refer to specific files and folders for detailed information and results related to each imaging session:</p><ul><li><i><xx>kVp or <xx>kV </i>:Imaging at a peak voltage of <xx> kVp.</li><li><i><y>W</i> :Imaging at <y> Watts;<i> </i>"." is represented with "-"; i.e. 20210705_XRH_2766_PJB_TEST03552-EQPMT_W_6-9W is acquired using a power of 6.9 W</li><li><i>MoRt, TT, Refl </i> :Molybdenum, Transmission, and Reflection targets, respectively.</li><li><i>_W_ and _Mo_ </i> :Tungsten and Molybdenum target materials.</li><li><i>_horiz</i> :Reconstruction slices in line with the X-ray beam's propagation direction.</li><li><i>_vert</i> :Reconstruction slices normal to the X-ray beam's propagation direction and parallel to the detector plane.</li></ul>
Synchrotron X-ray Computed Tomography scan of a wasp
<h4>Contents:</h4><ul><li><i>bee_yazeed-20231001T170032.h5</i> - SXCT scan of a wasp performed at beamline <a href="https://www.sesame.org.jo/beamlines/beats">ID10-BEATS</a> of SESAME.</li><li><i>SESAME_wasp_yazeed.avi -</i> 3D video rendering of phase-contrast CT reconstruction of <i>bee_yazeed-20231001T170032</i>. The dataset was reconstructed using <a href="https://github.com/gianthk/alrecon/tree/master">alrecon</a>. The video was created using ORS Dragonfly.</li></ul><h4>H5 dataset information:</h4><ul><li>Raw experimental data (sinogram, flat fields and dark fields) and metadata are stored in a common .H5 file.</li><li>The HDF5 file is organized hierarchically following the <a href="https://dxfile.readthedocs.io/en/latest/">Scientific Data Exchange (DXfile)</a> community standard.</li></ul><h4>How to reconstruct:</h4><ul><li>You can use <a href="http://www.silx.org/">Silx</a> to read and explore the .H5 dataset.</li><li>The file can be read within Python using the <a href="https://dxchange.readthedocs.io/en/latest/">DXChange</a> package.</li><li>See the <a href="https://beats.readthedocs.io/reconstruction.html">ID10-BEATS beamline user guide</a> for a detailed description on how to process and reconstruct the scan.</li></ul>
IODP Expedition 391 Portable X-ray fluorescence (p-XRF)
Energy-Dispersive X-Ray Fluorescence (ED-XRF) is a rapid, non-destructive technique for determining qualitative and quantitative changes in chemical composition. Aboard the JOIDES Resolution, pXRF is used for measuring points on section halves, rock pieces, and sometimes powders. Spots are typically irradiated at multiple conditions to excite and measure a wide range of elements. The peak intensity changes (we do not provide concentrations) are then used to help recognize and define major chemo-stratigraphic units without the need for destructive sampling.
IODP Expedition 391 X-ray diffraction (XRD)
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).
IODP Expedition 391 X-ray fluorescence (XRF)
Elemental peak intensities in section halves were measured by an Avaatech X-ray fluorescence (XRF) Core Scanner postexpedition. Each measurement position may be measured at multiple XRF conditions in order to excite and measure specific ranges of elements (e.g., 10 kV and no filter for light elements). Peak intensity changes (concentrations not provided) are then used to help recognize and define major chemostratigraphic units without the need for destructive sampling. Data are presented in comma-delimited (CSV) files by section and by energy/instrumental conditions.
IODP Expedition 397T X-ray diffraction (XRD)
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).
Extracted Source Properties Catalog for "Monitoring the X-ray Variability of Bright X-ray Sources in M33"
<p>Supplemental data to the article "Monitoring the X-ray Variability of Bright X-ray Sources in M33" accepted for publication in ApJ. Contains all extracted source properties for the 56-source final catalog, including single-ObsID extractions and merged values. See ReadMe for column descriptions and additional comments.</p>
ARCADE: Automatic Region-based Coronary Artery Disease diagnostics using x-ray angiography imagEs Dataset
<p>ARCADE: Automatic Region-based Coronary Artery Disease diagnostics using x-ray angiography imagEs Dataset Phase 2 consist of two folders with 300 images in each of them as well as annotations. </p> <p>ARCADE: Automatic Region-based Coronary Artery Disease diagnostics using x-ray angiography imagEs Dataset Phase 1 consists of two datasets of XCA images for each of two tasks of ARCADE challenge. The first task includes in total 1200 coronary vessel tree images, which are divided into train(1000) and validation(200) groups, images for training are followed with annotations, depicting the division of a heart into 26 different regions based on the Syntax Score methodology[1]. Similarly, the second task includes a different set of 1200 images with same train-val division proportion with annotated regions containing atherosclerotic plaques. This dataset, carefully annotated by medical experts, enables scientists to actively contribute towards the advancement of an automated risk assessment system for patients with CAD. </p> <p>The dataset structure is as follows: top-level directories "syntax" and "stenosis" contain files for the two dataset objectives, namely: i) vessel branch classification according to the SYNTAX methodology; and ii) stenosis detection. Inside both directories, there are 3 subsets of the dataset, such as "train", "val", and "test". Inside each of those folders, there are 2 lower-level directories - "images", and "annotations". Inside the "images" folder there are images in ".png" format, extracted from DICOM recordings. The "annotations" folders contain single ".JSON" files, which are named in correspondence to the objective, i.e. "train.JSON", "val.JSON", and "test.JSON".</p> <p>The structure of ".JSON" contains three top-level fields: "images", "categories", and "annotations". The "images" field contains the unique "id" of the image in the dataset, its "width" and "height" in pixels, and the "file_name" sub-field, which contains specific information about the image. The "categories" field contains a unique "id" from 1 to 26, and a "name", relating it to the SYNTAX descriptions. The "annotations" field contains a unique "id" of the annotation, "image_id" value, relating it to the specific image from the "images" field, and a "category_id" relating it to the specific category from the "categories" field. The "segmentation" sub-field contains coordinates of mask edge points in "XYXY" format. Bounding box coordinates are given in the "bbox" field in the "XYWH" format, where the first 2 values represent the x and y coordinates of the left-most and top-most points in the segmentation mask. The height and width of the bounding box are determined by the difference between the right-most and bottom-most points and the first two values. Finally, the "area" field provides the total area of the bounding box, calculated as the area of a rectangle.</p> <p> </p> <p>The corresponding Dataset Article will be provided later. </p> <p>[1] Syntax score segment definitions. https://syntaxscore.org/index.php/tutorial/definitions/14-appendix-i-segment-definitions</p>
IODP Expedition 383 Portable X-ray fluorescence (p-XRF)
Energy-Dispersive X-Ray Fluorescence (ED-XRF) is a rapid, non-destructive technique for determining qualitative and quantitative changes in chemical composition. Aboard the JOIDES Resolution, pXRF is used for measuring points on section halves, rock pieces, and sometimes powders. Spots are typically irradiated at multiple conditions to excite and measure a wide range of elements. The peak intensity changes (we do not provide concentrations) are then used to help recognize and define major chemo-stratigraphic units without the need for destructive sampling.
Corrected IODP Gamma Ray Attenuation (GRA) densities and calculated porosities derived from the LILY Database
<div>The dataset <strong>GRA_Densities_Corrected_and_Porosities_2023-12-26.csv</strong> is derived from an analysis of data from the LILY Database (<a href="https://doi.org/10.5281/zenodo.8408296">https://doi.org/10.5281/zenodo.8408296</a>) as described in Childress et al. (2024, <a href="https://doi.org/10.1029/2023GC011287">https://doi.org/10.1029/2023GC011287</a>). The file contains over 3.7 million corrected gamma ray attenuation (GRA) bulk density data derived from the LILY database file GRA_DataLITH.csv. It also contains over 3.7 million porosity estimates that are computed from the corrected GRA bulk density using grain densities computed for each lithology from Moisture and Density (MAD) grain densities (derived from LILY file MAD_DataLITH.csv).</div> <div> </div> <div><strong>Citation: </strong>Please cite Childress et al. (2024) when using these data:</div> <div>Childress, L.B., Acton, G.D., Percuoco, V.P., Hastedt, M., 2024. The LILY Database: Linking Lithology to IODP Physical, Chemical, and Magnetic Properties Data, <em>Geochemistry, Geophysics, Geosystems, 25</em>, <a href="https://doi.org/10.1029/2023GC011287">https://doi.org/10.1029/2023GC011287</a>.</div> <div> </div> <div><strong>GRA_Densities_Corrected_and_Porosities_2023-12-26.csv</strong> file size uncompressed is 950 Mb.</div> <div> </div> <div><strong>Data File format:</strong></div> <ul> <li>Exp: expedition number</li> <li>Site: site number</li> <li>Hole: hole number</li> <li>Core: core number</li> <li>Type: Type indicates the coring tool used to recover the core (typical types are F, H, R, X; see Table S3 in Childress et al., 2024, <a href="https://doi.org/10.1029/2023GC011287">https://doi.org/10.1029/2023GC011287</a>).</li> <li>Sect: section number</li> <li>Offset (cm): position of the observation, measured relative to the top of a section.</li> <li>Depth CSF-A (m): location of the observation expressed relative to the top of a hole.</li> <li>Bulk density (GRA): bulk GRA density measured on whole core sections in g/cm^3.</li> <li>Timestamp (UTC): date and time the observation was made.</li> <li>Instrument: abbreviation or mnemonic for the GRA sensing device used to make this observation (GRA1 or GRA2).</li> <li>Instrument group: abbreviation or mnemonic for the data collection device (logger) used to acquire this observation (WRMSL).</li> <li>Text ID: automatically generated unique database identifier for a sample, visible on printed labels.</li> <li>Prefix: Prefix of the lithology</li> <li>Principal: Principal lithology</li> <li>Suffix: Suffix of the lithology</li> <li>Full Lithology: full lithologic name = Prefix + Principal + Suffix</li> <li>Simplified Lithology: categorization of lithologies (see Supporting Information in Childress et al., 2024, <a href="https://doi.org/10.1029/2023GC011287">https://doi.org/10.1029/2023GC011287</a>)</li> <li>Lithology Type: Sedimentary, Igneous, or Metamorphic</li> <li>Degree of Consolidation: consolidation state of the lithology.</li> <li>Lithology Subtype: categorization of lithologies (see Supporting Information in Childress et al., 2024, <a href="https://doi.org/10.1029/2023GC011287">https://doi.org/10.1029/2023GC011287</a>).</li> <li>Expanded Core Type: the actual coring type used, because some coring types were incorrectly grouped in the "Type" column (see Childress et al., 2024 for an explanation)</li> <li>Latitude (DD): Latitude in decimal degrees</li> <li>Longitude (DD): Longitude in decimal degrees</li> <li>Water Depth (mbsl): water depth in meters below sea level</li> <li>Grain Density: grain density associated with the Principal lithology, computed from MAD data</li> <li>Mean MAD Bulk Density: mean MAD bulk density associated with the Principal lithology.</li> <li>Std MAD Bulk Density: standard deviation in the MAD bulk densities for each Principal lithology.</li> <li>Correction Basis: the GRA bulk densities are corrected based on coring tool used. If the RCB was used, then the lithology cored by the RCB is used in determining the size of the correction.</li> <li>Median Difference: The correction that will be applied based on the median difference between the raw GRA bulk density and the colocated MAD bulk density for a specific Correction Basis.</li> <li>GRA Bulk Density Corrected: The corrected GRA bulk density in g/cm^3.</li> <li>Porosity: porosity computed from the corrected GRA bulk densities and grain density.</li> <li>Deviation: difference between "GRA Bulk Density Corrected" and "Mean MAD Bulk Density", which is the deviation the corrected density has from that expected for its Principal lithology.</li> <li>N Deviations: The number of standard deviations by which the observation differs from the expected value (= Deviation/(Std MAD Bulk Density)), which is useful for identifying outliers.</li> </ul> <h3>GitHub Repository:</h3> <ul> <li>Contains a few notebooks to demonstrate how to work with the LILY database</li> <li><a title="IODP LILY GitHub Repository" href="https://github.com/IODP?tab=repositories">IODP LILY GitHub Repository</a> </li> </ul>
Data products and software for `X-ray diagnostics of Cassiopeia A's "Green Monster": evidence for dense shocked circumstellar plasma`
<div> <h2>Data Reproduction Package for the publication ‘X-ray diagnostics of Cassiopeia A’s “Green Monster”: evidence for dense shocked circumstellar plasma’</h2> </div> <div> <h3>Authors: Jacco Vink, Manan Agarwal, Patrick Slane, Ilse De Looze, Dan Milisavljevic, Daniel Patnaude, and Tea Temim.</h3> </div> <div> <h3>Link to paper: <a href="https://doi.org/10.3847/2041-8213/ad2fc5">https://doi.org/10.3847/2041-8213/ad2fc5</a> </h3> <p> </p> </div> <div> <h4>This package was prepared by Jacco Vink and Manan Agarwal (University of Amsterdam)</h4> </div> <div> <h3>Summary</h3> </div> <div> <p>This data reproduction package contains the data files in FITS format used to<br>generate the figures in the paper. The data files concern the revised manuscript, which incorporates changes made in response to the journal’s referee report.</p> </div> <div> <p>The paper is based on Chandra X-ray Observatory (CXO) data of Cassiopeia A taken in 2004. The raw archival data used, maintained by the Chandra Data Archive, can be retrieved using the following DOI link: <a href="https://doi.org/10.25574/cdc.209">https://doi.org/10.25574/cdc.209</a>.</p> </div> <div> <p>Additional James Webb Space Telescope (JWST) data are stored at the Mikulski Archive for Space Telescopes (MAST) at the Space Telescope Science Institute. The data used in the paper can be downloaded through DOI link <a href="https://doi.org/10.17909/szf2-bg42">https://doi.org/10.17909/szf2-bg42</a>.</p> </div> <div> <p>The data produced from the above raw data are stored in the files:</p> </div> <div> <ul> <li>green_monster_image_data.tar.gz</li> <li>spectral_files_and_models.tar.gz</li> <li>imaging_and_pca_code.tar.gz</li> <li>green_monster_pca_input_output.tar.gz</li> </ul> <p>The repository contains JWST/MIRI mosaics of Cassiopeia A which are described in detail in the paper "A JWST Survey of the Supernova Remnant Cassiopeia A", by D. Milisavljevic, T. Temim, I. De Looze, et al.; see https://arxiv.org/abs/2401.02477, to be published in ApJ letters.<br> </p> </div>
X-ray diffraction dataset for experimental noise filtering
<p>X-ray diffraction data set for the training of noise filtering algorithms. The data set contains groups of low- and high-counting statistics pairs. The sampling times are mostly 1 (20) seconds for low (high) counting data. Three files in HDF5 format are provided, corresponding to a training, validation and test data set. Each data group contains sequences of 41 consecutive frames, corresponding to a scan along the reciprocal h-direction. Next to the raw data, sampling times and monitor values are included. The test data set additionally contains denoised low-count frames obtained from a pre-trained neural network.</p> <p>Additionally, files containing the trained model weights are included for two different architectures described in the main article (10.1038/s42256-024-00790-1).</p> <p>The data has been recorded on a La<sub>1.88</sub>Sr<sub>0.12</sub>CuO<sub>4</sub> single crystal at the beamline P21.1 at the PETRA III storage ring at DESY in Hamburg, Germany. The scattering intensities were recorded using Dectris Pilatus 100K CdTe detector. The diffractometer was operated with 100 keV photons and the sample was cooled to T ~ 30 K. The data contains different signals such as weak 2D charge density wave order, fundamental Bragg peaks, powder lines, spurions and dead pixels.</p>
IODP Expedition 378 Portable X-ray fluorescence (p-XRF)
Energy-Dispersive X-Ray Fluorescence (ED-XRF) is a rapid, non-destructive technique for determining qualitative and quantitative changes in chemical composition. Aboard the JOIDES Resolution, pXRF is used for measuring points on section halves, rock pieces, and sometimes powders. Spots are typically irradiated at multiple conditions to excite and measure a wide range of elements. The peak intensity changes (we do not provide concentrations) are then used to help recognize and define major chemo-stratigraphic units without the need for destructive sampling.
IODP Expedition 378 X-ray diffraction (XRD)
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).
Alpha-Galactosaminidase family GH191 protein from Environmental sample (99.2% identity to Myxococcus fulvus enzyme): X-ray diffraction images
<p><span>This submission includes a zip archive of diffraction images recorded with the Dectris EIGER X 9M detector at the DIAMOND beamline I04-1. The model of the crystal structure and associated information can be found in the Protein Data Bank entry 9EP5. This is a case of crystal pathology – partial disorder. The model has C 2 2 21 symmetry and two molecules per asymmetric unit with occupancies 1 and 1/3. The molecule with partial occupancy overlaps with a symmetry related molecule.</span></p>
IODP Expedition 367 X-ray fluorescence (XRF)
Elemental peak intensities in section halves were measured by an Avaatech X-ray fluorescence (XRF) Core Scanner postexpedition. Each measurement position may be measured at multiple XRF conditions in order to excite and measure specific ranges of elements (e.g., 10 kV and no filter for light elements). Peak intensity changes (concentrations not provided) are then used to help recognize and define major chemostratigraphic units without the need for destructive sampling. Data are presented in comma-delimited (CSV) files by section and by energy/instrumental conditions.
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.