Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
739
datasets available to search
ShareScore release 0.9.0
Dataset results
739 results for “Prints”
MXene and MoS3−x Coated 3D-Printed Hybrid Electrode for Solid-State Asymmetric Supercapacitor
<p>All raw dataset of the published article "MXene and MoS3−x Coated 3D-Printed Hybrid Electrode for Solid-State Asymmetric Supercapacitor", DOI: 10.1002/smtd.202100451</p>
Optical tomography measurements and reconstructions of a multiple-scattering 3d-printed microphantom
<p>This dataset contains 2 sets of measurements of a 3d-printed microphantom, carried out with optical diffraction tomography system at Warsaw University of Technology. The measurements are conducted for 2 different wavelengths: 633nm and 835nm. Also, tomographic reconstructions of these datasets are shown. The reconstructions were computed with 3 algorithms: GPSC [1], MSBP-I [2] and MSBP-E [3]. Additionally, model of the 3D-printed microphantom is given.</p> <p>All files are *.mat files.</p> <p>In the reconstruction files there are 4 variables:</p> <ul> <li>REC - reconstruction matrix with information about 3D refractive index values in the microphantom</li> <li>dx - sample size in the reconstruction in x-y direction</li> <li>dz - sample size in the reconstruction in z direction (if not given, dz=dx)</li> <li>niter - number of iterations that were computed to generate the reconstruction</li> </ul> <p>The variables in the sinogram files are:</p> <ul> <li>dx - sample size in tomographic projections</li> <li>lambda - wavelength</li> <li>M - magnification in the optical system</li> <li>n_immersion - refractive index of the immersion medium</li> <li>NA - numerical aperture of the optical system</li> <li>rayXY - x-y coordinates of vectors representing illumination directions from which tomographic projections were acquired</li> <li>SINOamp - amplitude distribution of tomographic projections</li> <li>SINOph - phase distributions of tomographic projections</li> </ul> <p>The variables in the phantom model files are:</p> <ul> <li>dx - sample size</li> <li>n_immersion - refractive index of simulated immersion</li> <li>n_phantom - refractive index of the phantom model</li> </ul> <p>[1] W. Krauze, “Optical diffraction tomography with finite object support for the minimization of missing cone artifacts,”277<br> Biomed. optics express 11, 1919–1926 (2020)<br> [2] S. Chowdhury, M. Chen, R. Eckert, D. Ren, F. Wu, N. Repina, and L. Waller, “High-resolution 3D refractive index292<br> microscopy of multiple-scattering samples from intensity images,” Optica 6, 1211 (2019).<br> [3] U. S. Kamilov, I. N. Papadopoulos, M. H. Shoreh, A. Goy, C. Vonesch, M. Unser, and D. Psaltis, “Learning approach288<br> to optical tomography,” Optica 2, 517 (2015).</p>
Mouse Lockboxes - 3D printing files and videos
<p>This repository contains 3D printable STL files for the mouse lockboxes (LB) and videos of mice solving the lockboxes. Lockboxes are mechanical puzzles consisting of one or more steps, which are baited with a food reward. The mice manipulate the lockboxes on a voluntary basis.</p> <p><strong>LB sets</strong>: Two LB sets were designed, each consisting of four single mechanism LBs (1-step) and a combined mechanism LBs (4-step). For the latter, the fours single mechanisms block each other and have to be removed in the correct order to open the box. The LB can be baited with a food reward to motivate the animals to open them.<br>In the folder titled <em>"LB_solutions"</em>, there are GIFs of each single and combined mechanism LB, which demonstrate how the LBs are supposed to be opened.<br>In the construction manual <em>("Instruction_Manual_Lock_Boxes.pdf")</em>, the STL files for each LB are listed and construction plans are provided. The STL files can be found in the folder titled <em>"LB_sets.zip"</em>.</p> <p><strong>Door system</strong>: The door systems can be used to connect two cages.</p> <p><strong>Printing</strong>: We used an Ultimaker 3 Extended and an Ultimaker S3, 0.4 mm nozzles, and PLA of different colors as material. The gcode was generated with Cura_SteamEngine 4.4.0. Since the mice may gnaw on the LB, it is advisable to choose a higher value for the thickness of walls and top, e.g., 1.5 mm. For most elements, the normal profile (0.15 mm) can be used; for small elements such as the seals, the fine profile is beneficial.</p> <ul> <li>Wall Thickness: 1 mm</li> <li>Wall Line Count: 10</li> <li>Top/Bottom Thickness: 1 mm</li> <li>Top Layers: 10</li> <li>Bottom Layers: 3</li> <li>Infill Density: 20 %</li> <li>Infill Pattern: Triangles</li> <li>Support should be generated for the following elements: LB#1_single_drawer.stl, LB#1_single_cube.stl, LB#1_single_disc.stl, LB#2_single_lever.stl, LB#2_single_stick.stl, LB#1_combined_stick.stl, LB#1_combined_cube.stl, LB#1_combined_disc.stl, LB#2_combined_ lever.stl, LB#2_combined_ stick1.stl, LB#2_combined_ stick2.stl</li> <li>Build Plate Adhesion is necessary for the following elements: LB#1_single_drawer.stl, LB#1_single_lever.stl; LB#1_single_seal1.stl, LB#1_single_cube.stl, LB#1_single_seal2.stl, LB#2_single_lever.stl, LB#2_single_stick.stl, LB#2_single_seal4.stl, LB#2_single_seal5.stl, LB#2_single_seal6.stl, LB#1_combined_stick.stl, LB#1_combined_lever.stl, LB#1_combined_cube.stl, LB#1_combined_seal1.stl, LB#1_combined_seal2.stl, LB#2_combined_lever.stl, LB#2_combined_stick1.stl, LB#2_combined_stick2.stl, LB#2_combined_ball.stl, LB#2_combined_seal3.stl, LB#2_combined_seal6.stl</li> </ul> <p><strong>Videos</strong>: The videos in the folder titled "videos" demonstrate how mice solve the lockboxes.</p>
Dataset of imaged commercial and custom-made printing filament materials for Computed Tomography imaging of organ body phantoms
<p>The dataset includes a total of 29 filament materials 7 custom-made materials and the selection of 22 commercially available materials.</p> <p>All the materials were printed with a Longer LK4 Pro printer into cubes with dimensions 20 mm x 20 mm x 10 mm.</p> <p>A part of each filament was grinded into pellets, placed into metallic cylinder container and then were heated up to their melting points to receive a homogeneous cylindrical sample of this material.</p> <p>The cubes and the cylindrical samples were scanned at a clinical CT scanner at three anode voltages (kV) and a slice thickness of 0.6 mm.</p>
FONDUE-FR-PRINT-17 - Transcriptions of French 17th c. prints
<p>HTR Groundtruth for French 17th c. prints, produced with <a href="https://github.com/mittagessen/kraken">Kraken</a> and <a href="https://gitlab.com/scripta/escriptorium">eScriptorium</a>.</p> <p>Original data is available on <a href="https://github.com/FoNDUE-HTR/FONDUE-FR-PRINT-17">GitHub</a>.</p>
Dataset for '3D printing of customizable transient bioelectronics and sensors'
<p>This data set contains the data collected during the FNS project Green Piezo (Grant no. 179064) in association with the recent publication entitled “3D printing of customizable transient bioelectronics and sensors”.</p> <p>This work aims to study and demonstrate the fabrication by 3D printing of devices made of transient materials, i.e. materials that can break down and degrade in an environment of choice. Biodegradable electronic devices have potential in tackling the issue of electronic waste and present an opportunity for new types of implantable and/or wearable devices that can resorb after their lifecycle is completed. A bioresorbable elastomer and a conductive carbon-based ink are printed by direct-ink writing, thanks to an in depth study of their dispense behavior. Several sensors are shown as demonstrators (strain, pressure, electrodes). The data that was collected in the frame of this work is present in this repository. More information about the contents of the dataset is present in the included README file.</p>
3D printed map for blind or visually impaired people
<p>This data set is composed of three parts each having its proper origins, formats and rights. This data set was used to apply the methods of relief editing and image processing to facilitate the production of accessible documentation by having in hand an easy to use interface.</p>
Rakhtera (रखतेरा Guna). Inscription above foot prints near a large rock-cut image of Ādinātha.
<p><a href="https://siddham.network/inscription/vs1555/">INIG1555</a> Rakhetra (रखतेरा Guna). Inscription (IN1555 IG) above foot prints (OB1555 IG) near a large rock-cut image of Ādinātha.</p>
Rakhterā (रखतेरा or Rakhetrā, Ashoknagar). General view of the niche with foot prints near a large rock-cut image of Ādinātha.
<p><a href="https://siddham.network/object/vs1555/">OBIG1555</a> Rakhterā (रखतेरा or Rakhetrā, Ashoknagar). General view of the niche with foot prints near a large rock-cut image of Ādinātha.</p>
Set of images published in publication "Cleaning strategies for 3D-printed porous scaffolds used for bone regeneration fabricated via ceramic vat photopolymerization"
<p>Figures of publication "Cleaning strategies for 3D-printed porous scaffolds used for bone regeneration fabricated via ceramic vat photopolymerization".</p> <p><a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.ceramint.2024.10.160" target="_blank" rel="noreferrer noopener"><span><span>https://doi.org/10.1016/j.ceramint.2024.10.160</span></span></a></p>
Data on the actual use of open data/ open source on pre-prints at arXiv/bioRxiv
<p>Articles submitted (1st edition) to the preprint server arXiv/bioRxiv were converted to text and analysed as follows :</p> <ul> <li>For arXiv articles, nationality was assigned to the manuscript using the first occurrence of the email address in the manuscript.</li> <li>For bioRxiv articles, we assigned nationality using the country tag information in the metadata about the first author.</li> <li>We listed the URLs that appeared in each manuscript.</li> <li>We checked how many articles contained a particular URL (e.g. github; https://github.com ) by year, month and nationality.</li> </ul> <p>This dataset describes the results of the above work.</p>
Dataset for BRDF representation in response to the build orientation in 3D-printed digital materials
<p>This dataset folder contains data for the project "BRDF representation in response to the build orientation in 3D-printed digital materials"<br> For more information please contact Ali Payami Golhin (payami.ag@gmail.com)</p> <p>Abbreviations:<br> C:Cyan; M:Magenta; Y:Yellow; K:Black<br> GoG: Glossy on Glossy finish; GoM: Glossy on Matte finish</p> <p>Folder "Color values": presents data for CIEXYZ, CIELab, CIELCh for 328 measurement geometries for each CMYK resins<br> Folder "Spectral data": presents reflctance data for 328 measurement geometries for each CMYK resins. The first column in each file represent wavelength (nm) and the second column contains spectral data<br> File "PCA.xlsx": presents PCA (PC1) scores for CMYK colors</p>
efantnu/drep-2021-collab-MINESParisTech-NTNU: Pre-print version IEEE Access
<p>This repository contains the data sets of the paper "Allocation of spinning reserves in autonomous grids considering frequency stability constraints and short-term solar power variations" authored by Erick F. Alves, Louis Polleux, Gilles Guerassimoff, Magnus Korpås, Elisabetta Tedeschi. With these files, it is possible to reproduce most simulations and results obtained in the paper.</p> <p>Folder organization</p> <ul> <li>Results: final results and values of intermediate steps of the optimization model implemented in Gurobi 9.1 and described in section III-A and III-B of the paper.</li> <li>Validation: test system implemented in OpenModelica for validation of the results and described in section III-C of paper.</li> <li>Solar convex hulls: hourly convex hulls obtained using the procedure detailed in Appendix A.</li> <li>Solar irradiance profiles: high-resolution irradiance timeseries from NREL used to identify the worst-case solar PV ramp scenarios.</li> </ul>
Dataset for 'Zinc hybrid sintering for printed transient sensors and wireless electronics'
<p>This data set contains the data collected during the FNS project Green Piezo (Grant no. 179064) in association with the recent publication entitled “Zinc hybrid sintering for printed transient sensors and wireless electronics”.</p> <p>This work aims to study and develop a method for the efficient sintering of printed zinc metal, with the aim to facilitate the fabrication of biodegradable electronics by additive manufacturing. Biodegradable electronic devices have potential in tackling the increasingly pressing challenge of electronic waste, and present opportunities for the fabrication of novel bioresorbable medical devices that can harmlessly degrade in the body and eliminate the need for re-operation. The method that is presented in this publication combines electrochemical and photonic sintering approaches to enable the fabrication of highly-conductive degradable metal tracks. Several sensors are shown as demonstrators (temperature, strain, pressure). The data that was collected in the frame of this work is present in this repository. It relates to both the study of the process introduced above as well as the characterization of the demonstrators. More information about the contents of the dataset is present in the included README files.</p>
Republic Print Dataset
<p>The republic print dataset consists of 107 ground truthed scans </p> <p>Using annotation software provided through the Transkribus Platform we annotated scans, concerning mostly 18th century printed documents from the National Archive of the Netherlands, with their layout consisting of baselines and regions. The resulting ground truth was used to train a machine learning model yielding very accurate results. The ground truth was made available as an open access dataset.</p>
Dataset for 'Printed ecoresorbable temperature sensors for environmental monitoring'
<p>This data set contains the data collected during the FNS project Green Piezo (Grant no. 179064) in association with the recent publication entitled “Printed ecoresorbable temperature sensors for environmental monitoring”.</p> <p>This work aims to study the effect of photonic sintering parameters on the temperature behavior of printed zinc resistors, with the aim to fabricate eco-friendly and ecoresorbable temperature sensors on paper. Biodegradable electronic devices have potential in tackling the increasingly pressing challenge of electronic waste and printing methods allow to reduce toxic byproducts of fabrication and wasted material. The sintering method that is optimized here is based on our previous work combining electrochemical and photonic sintering approaches to enable the fabrication of highly-conductive degradable metal tracks. We optimize the sintering parameters to obtain zinc resistors with a high temperature coefficient of resistance and a linear temperature response curve. The data that was collected in the frame of this work is present in this repository. More information about the contents of the dataset is present in the included README files.</p>
Dataset for 'Organic Electrochemical Transistors Printed from Degradable Materials as Disposable Biochemical Sensors'
<p>This data set contains the data collected during the FNS project Green Piezo (Grant no. 179064) in association with the publication entitled “Organic Electrochemical Transistors Printed from Degradable Materials as Disposable Biochemical Sensors”.</p> <p>This work aims to study the fabrication of organic electrochemical transistors using more environmentally-friendly materials, in particular carbon contacts and polylactic acid (PLA) as substrate. Organic electrochemical transistors (or OECTs) offer applications in biosensing, for example for point-of-care devices. We use a combination of additive manufacturing methods (screen printing and inkjet printing) to manufacture these transistors and solve the issues with fabricating them on a low-temperature substrate such as PLA. We also assess these transistors as disposable sensors for the detection of various ion concentrations as well as glucose. The data that was collected in the frame of this work is present in this repository. More information about the contents of the dataset is present in the included README files.</p>
Fig. 5 in A new and improved electric fish finder with resources for printed circuit board fabrication
Fig. 5. Design schematic for electric fish finder enclosure. Grey arrows show distances from edges to the center of drill holes/ objects. Grey dotted circles represent drill holes. The sealing washer marked with an asterisk has no waterproofing function and is used instead to trap the exposed terminal of a wire from the channel ground against the internal metal surface of the enclosure (see CHGND in Fig. 2).
OCR17: GT for 17th French prints
<p>Machine learning starts with machine teaching: with our dataset, we distribute the data that we have gathered and created to train reliable OCR models for 17th c. French prints.</p>
Screen captures illustrating molecular 3D model sharing through Sketchfab, Google Poly and NIH Print Exchange
<p>Sharing 3D models illustrated by 6 screen captures. </p> <p> </p> <p>1: cardboard stereo view with Sketchfab of example 1 (ACE-spike coronavirus complex)</p> <p> </p> <p>2: tuning of VR/AR settings on the Sketchfab platform (example 1)</p> <p> </p> <p>3: Sketchfab web view of example 1</p> <p> </p> <p>4: Sketchfab 3D Model inspector applied to example 1 model</p> <p> </p> <p>4: Google Poly web view of example 1</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.