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249 results for “3D Structure”
Helical dinuclear 3d metal complexes with bis(bidentate) [S,N] ligands: synthesis, structural and computational studies
<h1>Raw data for the publication entitled:</h1> <h2>Helical dinuclear 3d metal complexes with bis(bidentate)<br>[S,N] ligands: synthesis, structural and computational<br>studies</h2> <p><em>Dalton Transactions</em>, <strong>2024</strong>, DOI: 10.1039/D4DT02395A</p> <p>Authors:<br>Jamie Allen, Jörg Saßmannshausen, Kuldip Singh, Alexander F. R. Kilpatrick*</p> <p>These folders contain the raw data which were used to prepare the above publication.</p> <h1>Information regarding the raw files of the DFT calculations.</h1> <p>The zip-files in this section containing the raw-data of the DFT calculations leading to the Zn, Co and Fe calculated structures. As filenames are notoriously bad in handling special characters, the names of the folder appear different from what is being used in the final publication. We try to provide as much information as possible to facilitate the usage of these results.</p> <p>Thus:</p> <table> <tbody> <tr> <th>Abbreviation publication</th> <th>Abbreviation folder</th> <th>Abbreviation filename</th> </tr> </tbody> <tbody> <tr> <td>[Zn(<strong>3</strong>)<sub>2</sub>]</td> <td>Zn3-2</td> <td>SNdipp2Zn</td> </tr> <tr> <td>[Co(<strong>3</strong>) <sub>2</sub>]</td> <td>Co3-2</td> <td>SNdipp2Co</td> </tr> <tr> <td>[Fe(<strong>3</strong>) <sub>2</sub>]</td> <td>Fe3-2</td> <td>SNdipp2Fe</td> </tr> <tr> <td>[Zn<sub>2</sub>(μ-<strong>2</strong>)<sub>2</sub>]</td> <td>Zn2-2</td> <td>zn2</td> </tr> <tr> <td>[Co<sub>2</sub>(μ-<strong>2</strong>)<sub>2</sub>]</td> <td>Co2-2</td> <td>co2</td> </tr> <tr> <td>[Fe<sub>2</sub>(μ-<strong>2</strong>)<sub>2</sub>]</td> <td>Fe2-2</td> <td>fe2</td> </tr> </tbody> </table> <p>Some test calculations were performed as well utilizing Gaussian-09. They can be found in a folders with the suffix <em>-G09</em> or <em>-g09</em>.</p> <p>The closed shell compound [Zn<sub>2</sub>(μ-<strong>2</strong>)<sub>2</sub>] was investigated further. In order to look into the influence of the used Grimme dispersion correction, we re-calculated the final result without that correction. These files are in the Zn2-2-pbe0 folder. Furthermore, we used [Zn<sub>2</sub>(μ-<strong>2</strong>)<sub>2</sub>] and removed one of the Zn atoms and replaced the dangling bonds with H. We then fully optimized that structure. The results are in the Zn2-2-cut folder.</p> <h1> </h1> <h1>Information regarding the raw characterisation data</h1> <p>The raw characterisation data files for all nuclear magnetic resonance (NMR) spectroscopy, infrared (IR) spectroscopy, cyclic voltammetry (CV), single crystal X-ray diffraction (XRD) and solution magnetometry studies are enclosed in separate .zip files.</p>
3D resistivity structure of the Los Humeros geothermal field.
<p>The dataset is the final three-dimensional resistivity model of the high temperature geothermal field Los Humeros, in Mexico.</p> <p>The model is described in deliverable 5.2 of the GEMex Project, funded by the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 727550, and by the Mexican Energy Sustainability Fund<br> CONACYT-SENER, Project 2015-04-268074.</p>
VoroCrack3d: An annotated data set of 3d CT concrete images with synthetic crack structures
<p>VoroCrack3d is an annotated data set of 3d CT images of concrete with synthetic crack structures. Its main purpose is the training and testing of machine learning models for 3d crack segmentation. The data set comprises 1344 images together with their corresponding ground truths. The concrete backgrounds are cropped out sections of size 400x400x400 voxels of CT images of concrete. To this end, several different concrete samples were scanned (normal concrete (NC), high-performance concrete (HPC), ultra-high-performance concrete (UHPC), air pore concrete; without and with reinforcements (straight steel fibers, crimped steel fibers, hooked-end steel fibers, polypropylene fibers, fibers made of glass fiber-reinforced polymer). The original concrete images have a resolution between 2.8 and 106 micrometers.</p> <p>The crack structures are modeled via minimum-weight surfaces in Voronoi diagrams according to the paper</p> <p>[1] C. Jung, C. Redenbach, Crack Modeling via Minimum-Weight Surfaces in 3d Voronoi Diagrams, Journal of Mathematics in Industry, 13, 10 (2023). https://doi.org/10.1186/s13362-023-00138-1.</p> <p>The surfaces are discretized, dilated and superimposed on the concrete backgrounds.</p> <p>The data set offers a high variety regarding concrete types, noise levels and crack widths, shapes, regularity and branching. This makes it suitable for studying the generalizability and robustness of 3d crack segmentation methods.</p> <p>______________________________________________________________________________________________</p> <p>The folder 'data' contains seven subfolders, each containing the data generated from a specific concrete type (NC, HPC, air pore concrete, polypropylene fiber-reinforced concrete, steel fiber-reinforced concrete (straight, crimped and hooked-end steel fibers)).</p> <p>Each subfolder again contains four subfolders according to the point process model that was used for generating the 3d Voronoi diagrams. The point processes and Voronoi diagrams are restricted to windows of size 400x150x400. </p> <p>- 'hc': Hard core point process with 60% volume density and intensity 0.000025 obtained from force-biased sphere packing.<br>- 'matclust': Matérn cluster process with parent intensity 0.0002/50, offspring intensity 50 and cluster radius 20.<br>- 'ppp': Poisson point process with intensity 0.0002.<br>- 'ppp-scaled': Poisson point process with intensity 0.0002 (but inside 200x150x200 window). The resulting Voronoi diagram is stretched in x- and z- direction by a factor of 2.</p> <p>Each of these contains five subfolders: one for the 3d input images, two for the corresponding labels (ground truths; one with and one without pores/fibers), one for the input and label previews (slice z=200 for each of the images) and a misc folder containing the concrete background without crack and, if applicable, the pore/fiber segmentation image.</p> <p>The data itself then contains 48 images:<br>1a-1d: crack with up to seven branches; fixed crack width (~1 voxel).<br>2a-2d: crack with up to four branches; fixed crack width (~1 voxel).<br>3a-3d: crack with up to one branch; fixed crack width (~1 voxel).<br>4a-4d: crack with no branches; fixed crack width (~1 voxel).<br>5a-5d: crack with no branches; fixed crack width (~3 voxels).<br>6a-6d: crack with no branches; fixed crack width (~5 voxels).<br>7a-7d: crack with no branches; fixed crack width (~7 voxels).<br>8a-8d: crack with up to seven branches; multiscale crack (bernoulli parameter 0.01);<br>9a-9d: crack with up to seven branches; multiscale crack (bernoulli parameter 0.02);<br>10a-10d: crack with up to seven branches; multiscale crack (bernoulli parameter 0.05);<br>11a-11d: crack with up to seven branches; multiscale crack (bernoulli parameter 0.1);<br>12a-12d: crack with up to seven branches; multiscale crack (bernoulli parameter 0.2);</p> <p>The names 'a'-'d' indicate level of added noise added to the image:<br>a: None.<br>b: Uniformly on [-sigma,sigma] <br>c: Uniformly on [-2*sigma,2*sigma] <br>d: Uniformly on [-4*sigma,4*sigma] <br>Negative values are mapped to 0. <br>For inputs of type int, noise values are rounded to the nearest integer.<br>(sigma = standard deviation of voxel greyvalues in image)</p> <p>Note that the grey values in the ground truths correspond to the local crack width. They can be thresholded to obtain binary masks.</p> <p>For more details, we refer to [1].</p>
Enhanced 3D velocity structure, seismicity relocation and basement characterization of Changning shale gas and salt mining regions in Sichuan Basin
<p>This repository contains the datasets and results of the joint inversion-based Vp/Vs model consistency constrained double difference seismic tomography carried out for the manuscript titled “Enhanced 3D velocity structure, seismicity relocation and basement characterization of Changning shale gas and salt mining regions in Sichuan Basin.” Included are the following: column descriptions of data files, catalog earthquake information (CX_event.dat), relocated events after inversion (CX_tomoDDMC.reloc), inverted Vp model (CX_Vpmodel.dat), inverted Vs model (CX_Vsmodel.dat) and inverted Vp/Vs model (CX_VpVsmodel.dat). Please consult the manual for tomoDD by Zhang and Thurber (2003) for detailed formats of these files. In addition, an averaged velocity model (MOD_averaged) computed based on the inversion results is included, and the converged model (Vp_model_reinverted) resulting from the reinversion, as well as basement structure data for Figure 14.</p>
Multi-material 3D Printing of Thermoplastic Elastomers for Development of Soft Robotic Structures with Integrated Sensor Elements
<p>Embedded sensing can benefit soft robots with the ability to interact with their environment but producing embedded soft sensors can be challenging. Multi-material Fused Deposition Modeling (FDM) additive manufacturing allows producing complex structures, by combining more than one kind of polymeric material. For multi-material FDM, conductive thermoplastic elastomer filaments have been developed. This allows the printing of flexible functional structures, based on thermoplastic elastomer structures with conductive paths that are of great interest for stretchable electronics and soft robotic applications. In this study, stretchable piezoresistive elastomer strain sensor composites were successfully produced by using multi-material FDM. A piezoresistive thermoplastic elastomer was printed on the top of a nonconductive, flexible thermoplastic elastomer strip using FDM multi-material 3D printer. FDM elastomer filaments with different shore hardness as substrate materials for the gripper structure were used. The hardness of the elastomer affected the printability and the adhesion to the conductive elastomer material, which was used as a strain sensor material. The hardness affected the strain sensor properties too. The piezoresistive response, dynamic behavior, drift, relaxation and sensitivity of the printed multi-material strips were investigated by tensile tests. Soft robotic grippers with integrated sensing elements to detect deformation while touching the objective were selected as a case study. The soft grippers with the integrated sensors exhibited intelligent response by recognizing when they were griping a small or big object and when an obstacle was inhibiting their function.</p>
Experimental Seismic Data Obtained Using a 3D-Printed Model of the Los Angeles Basin Structure
<p>These data were obtained and analyzed by Park et al., (2022) "Seismic wave simulation using a 3D printed model of the Los Angeles Basin" (doi:10.1038/s41598-022-08732-w).</p> <p> </p>
Interactive 3D PDF file for the structures 10 hr juvenile of Oikopleura dioica and supplementary movie S1-20 with high resolution
<p>The larvacean, Oikopleura dioica is a planktonic chordate, which is an emerging model organism with short life cycle of 5 days and belongs to tunicates (urochordates). Organ formation in the trunk proceeds in seven hours form hatching of tailbud larvae at three hours after fertilization (hpf) to completion of organ formation in fully functional juveniles that start feeding at 10 hpf and are just miniature of adult form.</p> <p>The juveniles were fixed at 10.5 hours post fertilization, 30 min after the tail shift (Nishida, H., 2008 Development of the appendicularian Oikopleura dioica: culture, genome, and cell lineages. Dev. Growth Differ. 50, S239–S256.). The data would be used as a basic morphological data of this animal to explore organ structures and cellular composition.</p> <p>This PDF file allows one to view 3D juvenile of O. dioica in any desired directions. One can show or hide the organs and rotate them by mouse. Open this PDF file and activate it as described in Adobe Acrobat User Guide (https://helpx.adobe.com/acrobat/using/displaying-3d-models-pdfs.html). Click Toggle "Model Tree button" with three small rectangulars in the tool bar. Then in the left panel, one can select the organs and nuclei you want to see. Select lighting as "daylight". Select solid or transparency mode.<br> The Juvenile 3D image was reconstructed with Amira software using 1967 serial section images of SBF-SEM (Serial block face scanning electron microscopy) that are available at https://doi.org/10.5061/dryad.d51c5b012.</p> <p>The Zip file also contains supplementary movie S1-20 (avi file) with high resolution and the legends (PDF file).</p> <p>This data is related to the paper, 3D reconstruction of structures of hatched larva and young juvenile of the larvacean Oikopleura dioica using SBF-SEM. (https://www.nature.com/articles/s41598-021-83706-y).</p>
3D model of a box-type structure under a small cairn near the Bear Trap in Northwest Greenland
<p>This dataset consists of files that can be used to view a high-resolution 3D model of a box-type structure under a small cairn in the vicinity of ‘The Bear Trap’. The interior of the stone box appears to have been completely empty. Similar small stone box structures have been identified and discussed by Schedermann (e.g. 1990: 159) for Arctic Small Tool tradition (ASTt) sites on Skraeling Island and by McGee (1979) for Port Refuge in the Canadian High Arctic. Similar and equally enigmatic features have also been described by Knuth (1966/67: 203) for far north and northeast Greenland. They have been alternatively attributed to numerous PalaeoEskimo cultural complexes, but without dated materials from the site current attribution of the feature’s function, significance or date are not possible.</p> <p>The 3D model was created from 280 digital photographs that were processed usingAgisoft Metashape Pro v1.7. More information is provided in processing report and the readme file that accompanies this dataset. </p> <p>The image survey was conducted as part of the Vaigat Iceberg-Microbial Oil Degradation and Archaeological Heritage Investigation (VIMOA) project, which was funded by the Danish Centre for Marine Research and supported by the Arctic Research Centre at Aarhus University, the National Museum of Denmark, the Greenland Institute of Natural Resources, and The Greenland National Museum and Archives in Nuuk. Proper permits for the survey were obtained in advance from the Greenland National Museum and Archives in Nuuk. Walsh et al. (2020) provides an overview of the archaeological surveys conducted during the VIMOA project and Walsh et al. (in prep) provides further details specific to The Bear Trap and surrounding archaeological contexts. </p> <p>Knuth, Egil. (1966/67) The ruins of the Musk Ox Highway. <em>Folk</em> 8-9: 191-219.</p> <p>McGee, Robert. (1979) <em>The Palaeoeskimo occupations at Port Refuge, High Arctic Canada</em>. National Museum of Man Mercury Series. Archaeological Survey of Canada Paper No. 92. Ottawa: National Museums of Canada.</p> <p>Schledermann, Peter. (1990) <em>Crossroads to Greenland: 3000 years of prehistory in the Eastern High Arctic</em>.Calgary: The Arctic Institute of North America of the University of Calgary.</p> <p>Walsh et al. (2020) The VIMOA project and archaeological heritage in the Nuussuaq Peninsula of north-west Greenland. <em>Antiquity</em> 94:e6 doi:10.15184/aqy.2019.230</p> <p>Walsh, Matthew J., Daniel F. Carlson, Pelle Tejsner, and Steffen Thomsen. The Bear Trap: Reinvestigating a unique stone structure on the northwest tip of the Nuussuaq Peninsula, Greenland. Submitted to <em>Arctic Anthropology</em></p>
DataSet: Structural and optical properties of gold nanosponges revealed via 3D nano-reconstruction and phase-field models
<p>These are the main raw and processed data for the publication "Structural and optical properties of gold nanosponges revealed<br> via 3D nano-reconstruction and phasefield models".</p> <p>Abstract:<br> Nanoporous gold nanoparticles are subject of intensive research due to their unique morphology, which leads to electric field localizations generating a strongly nonlinear optical response, allowing a wide range of applications. However, accurate predictions of physical properties require detailed knowledge of the sponges’ chaotic nanometer-sized geometrical structures, posing a metrological challenge. Therefore, a main goal is to obtain computer models with equivalent structural and optical properties. To understand the sponges’ morphology, a procedure for their accurate three-dimensional reconstruction using focused ion beam tomography is presented. Next, a small number of morphological key parameters is derived that sufficiently characterize the complex topology. Additionally, a new simulation method for the computer-aided creation of finite-sized sponges with adjustable geometric properties is presented. It is shown that if certain morphological parameters are similar for computer-generated and experimental sponges, their optical response, including number and locations of field localizations, are also similar. Finally, the anisotropy of the experimental sponges is analyzed and an easy-to-use procedure to replicate arbitrary anisotropies in computer-generated sponges is presented.</p>
3D Flow Field of a subaqueous cylindrical pendulum from large eddy simulation with fluid structure interaction
<p>Relevant data of fluid structure interaction large eddy simulation of a subaqueous cylindrical pendulum to reproduce the major findings of the article "Fluid structure interaction of a subaqueous pendulum: Analyzing the effect of wake correction via large eddy simulations" published in Physics of Fluids. The article has been published as open access: https://doi.org/10.1063/5.0086557</p>
Dataset for 'Experimental Quantification of Gas Dispersion in 3D-Printed Logpile Structures Using a Noninvasive Infrared Transmission Technique'
<p>This dataset contains the infrared images of tracer flow that were taken in the investigations of transverse dispersion in 3D-printed logpile structures. Accompanying the files (which are labelled according to the convention of the camera software) is a Python script which can be used to link the images to the operating conditions at which they were obtained. Documentation of this script can be found in the file at the very top. <br> This dataset was used as basis for the journal article 'Experimental Quantification of Gas Dispersion in 3D-Printed Logpile Structures Using a Noninvasive Infrared Transmission Technique', published in ACS Engineering Au under DOI:<a href="https://doi.org/10.1021/acsengineeringau.1c00040">10.1021/acsengineeringau.1c00040</a>. This paper can also be found in this repository at https://zenodo.org/record/6517082</p> <p> </p>
IGM Population of HFF structures using Hi-C, laminB1 DamID, 3D HIPMAp FISH and single cell SPRITE data
<p>This repository accompanies the manuscript "<strong>Integrative Genome Modeling Platform reveals essentiality of rare contact events in 3D genome organizations</strong>", to appear in Nat. Methods (2022), see also https://www.biorxiv.org/content/10.1101/2021.08.22.457288v1.</p> <p>It contains the preprocessed input data files (Hi-C, laminB1 DamID, 3D HIPMAp FISH and single cell SPRITE) for the HFF fibroblast cell line to be used in the Integrative Genome Modeling platform (IGM) developed in the Alber lab at UCLA (https://github.com/alberlab/igm).</p> <p>Also, we provide the configuration file to run IGM with those datasets, as we did in generating the HDSF population discussed in the accompanying manuscript. Such population is also provided as an "hss" file. Documentation and a simple demo/tutorial on how IGM can be run is given on the Alber lab Github @ https://github.com/alberlab/igm.</p> <p>All files can be read in using the <em>h5py</em> and <em>alabtools</em> (available @https://github.com/alberlab/alabtools) Python packages. More detailed information is provided in the manuscript and associated Supplementary Information file. </p> <p>For any inquiry/suggestions/doubts please reach out to Lorenzo Boninsegna (bonimba@g.ucla.edu) or Dr. Frank Alber (falber@g.ucla.edu).</p> <p> </p>
Benchmark Datasets for: EGR: Equivariant Graph Refinement and Assessment of 3D Protein Complex Structures
<p>This archive contains three benchmark datasets associated with the Equivariant Graph Refiner (EGR), two for protein complex structure refinement (PSR Test and Benchmark 2) and the other for protein complex structure assessment (M4S Test). The refinement datasets contain (1) a `pred` directory that contains decoy structure PDB files and (2) a `true` directory that contains native structure PDB files. The quality assessment dataset contains (1) `target_name` directories that each contain decoy structure PDB files for a given protein target and (2) a `label_info.csv` file listing each decoy structure's DockQ score and CAPRI class label.</p>
Full Datasets for: EGR: Equivariant Graph Refinement and Assessment of 3D Protein Complex Structures
<p>This archive contains three datasets associated with the Equivariant Graph Refiner (EGR), two for protein complex structure refinement (PSR Test and Benchmark 2) and the other for protein complex structure assessment (M4S Test). The refinement datasets contain (1) a `pred` directory that contains decoy structure PDB files and (2) a `true` directory that contains native structure PDB files. The quality assessment dataset contains (1) `target_name` directories that each contain decoy structure PDB files for a given protein target and (2) a `label_info.csv` file listing each decoy structure's DockQ score and CAPRI class label.</p>
"Chirality and accurate structure models by exploiting dynamical effects in continuous-rotation 3D ED data". Raw data and JANA refinement files.
<p><strong>Chirality and accurate structure models by exploiting dynamical effects in continuous-rotation 3D ED data</strong><br> 3D ED data sets of 5 compounds and JANA refinement files of 12 compounds</p> <p><strong>Relevant tools</strong><strong>:</strong></p> <ul> <li>PETS2: data reduction and analysis of electron diffraction patterns <ul> <li>Download program and access step-by-step tutorials at <a href="http://pets.fzu.cz/">http://pets.fzu.cz/</a></li> <li>Palatinus, L. <em>et al.</em> Specifics of the data processing of precession electron diffraction tomography data and their implementation in the program PETS2.0. <em>Acta Cryst. B</em><strong>75</strong>, 512–522 (2019). <a href="https://doi.org/10.1107/S2052520619007534">DOI: 10.1107/S2052520619007534</a></li> </ul> </li> <li>JANA2006: crystal structure model refinement program <ul> <li>Download program from <a href="http://jana.fzu.cz/">http://jana.fzu.cz/</a> and access step-by-step tutorials at <a href="http://pets.fzu.cz/">http://pets.fzu.cz/</a></li> <li>Results here were obtained with JANA2006. We recommend using JANA2020.</li> <li>Petricek, V., Dusek, M. & Palatinus, L. Crystallographic Computing System JANA2006: General features. <em>Z. Kristallogr.</em> <strong>229</strong>, 345–352 (2014). <a href="https://doi.org/10.1515/zkri-2014-1737">DOI: 10.1515/zkri-2014-1737</a></li> </ul> </li> <li>DYNGO: Bloch wave program, calculates dynamical diffraction intensities and derivatives <ul> <li>Program automatically included in JANA2006/JANA2020</li> <li>Palatinus, L., Petříček, V. & Corrêa, C. A. Structure refinement using precession electron diffraction tomography and dynamical diffraction: theory and implementation. <em>Acta Cryst. A</em><strong>71</strong>, 235–244 (2015). <a href="https://doi.org/10.1107/S2053273315001266">DOI: 10.1107/S2053273315001266</a></li> </ul> </li> </ul> <p><strong>3D ED data sets:</strong></p> <p>STW_HPM-1 (RT) was measured on a JEOL JEM-2100-LaB6 and diffraction patterns were recorded with an ASI Timepix detector. Another sample of STW_HPM-1 was measured at a temperature of 100 K after cryotransfer with a Titan Krios (CETA-D detector). The other data sets were measured on an FEI Tecnai G2 20 (Olympus SIS Veleta, CCD). Each data set contains the raw diffraction patterns (*.tif) and the basic input files needed to reproduce the data reduction with PETS2 as used in the associated publication (*.pts2, *.celllist, *.cenloc). Step-by-step tutorials are provided for quartz and glycine (and selected steps for abiraterone acetate) at <a href="http://pets.fzu.cz/">http://pets.fzu.cz/</a>.</p> <ul> <li>α-quartz, stepwise continuous-rotation and precession-assisted (2 data sets from the same crystal)</li> <li>natrolite, stepwise continuous-rotation and precession-assisted (2 data sets from the same crystal)</li> <li>cobalt aluminophosphate (CAP), static ED patterns recorded in 0.1° steps (3 data sets from 2 crystals)</li> <li>abiraterone acetate, stepwise continous-rotation (5 data sets from 5 crystals)</li> <li>STW_HPM-1, continuous-rotation (1 data set, room temperature)</li> <li>STW_HPM-1, continuous-rotation (1 data set, <em>T</em> = 100 K, cryotransfer)</li> </ul> <p><strong>JANA refinement and CIF files:</strong></p> <p>CIF (Crystallographic Information Framework) files include two data items. The first is related to the dynamical and the second to the kinematical refinement. Relevant parameters and statistics specific for dynamical refinement are found in the field _refine_special_details.</p> <p>JANA files are provided for the dynamical and kinematical refinement at the stage after the final refinement cycle together with the original input files generated by PETS2. For quartz and natrolite, relevant files for the refinements against precession-assisted 3D ED data are included. For abiraterone acetate and limaspermidine, relevant files for the absolute structure determination are included.</p> <ul> <li>α-quartz</li> <li>albite</li> <li>mordenite</li> <li>natrolite</li> <li>STW_HPM-1</li> <li>cobalt aluminophosphate (CAP)</li> <li>CAU-36</li> <li>α-glycine</li> <li>carbamazepine</li> <li>(+)-limaspermidine</li> <li>abiraterone acetate</li> <li>MBBF4</li> </ul> <p>For the kinematical refinements based on more than one data set, the self-written tool "CompInt" (unpublished) was used. The tool can be found in the file "tool_scalehkl_compint.zip". Input (*.hkl, *.compint) and output files (*.scalehkl) are provided in the respective folder with the JANA files.</p> <p>Raw data sources of other data sets relevant for the associated publication are given in the SI of the associated publication.</p>
3D-structured Supports create complete Data Sets for Electron Crystallography
<p>Each tar file contains the raw files in HDF5 format, together with the XDS.INP file used for data integration.</p> <p>NB: The meta-data in the HDF5 files have no meaning, please refer to the respective XDS.INP file for respective information.</p>
Semi-Supervised Pre-trained Foundation Model for 3D Structural Feature Analysis of Seismic Images
<p>Codes, trained model, and datasets for the paper "Semi-Supervised Pre-trained Foundation Model for 3D Structural Feature Analysis of Seismic Images".</p>
3D Printing Simulation Analysis of skeleton gyroid structure (standard, double and graded)_Spoke11_WP4_Task4.1_MOST
<p>These findings provide a comprehensive understanding of the challenges and considerations in 3D printing complex lattice structures, emphasizing the importance of residual stress management, thermal stability, and print direction alignment for optimal mechanical performance.</p>
3D structures along the reaction pathways of GTP hydrolysis by Arl3-RP2
<p>PDB files of 3D structures along the reaction pathways of GTP hydrolysis by Arl3-RP2 with the reaction coordinate values close to those obtained for minima and transitions states during the umbrella integration analysis of the reaction coordinate distributions.</p> <p>The filename includes the name of the minimum / transition state along the reaction path and the theory level.</p>
Assessment of 3D MINFLUX data for quantitative structural biology in cells
<p>Reanalysed data for "Assessment of 3D MINFLUX data for quantitative structural biology in cells"</p> <p>https://www.biorxiv.org/content/10.1101/2021.08.10.455294v1</p> <p>Contact Hell lab for the raw data</p> <p>https://www.mpibpc.mpg.de/hell</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.