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1,013 results for “glass”
X-ray computed tomography and scanning electron microscopy datasets of unidirectional and textured glass fibre composites.
<p>3D x-ray tomography and 2D scanning electron microscopy (SEM) data behind the publications: </p> <p>Salling, F.B, Jeppesen, N., Sonne, M.R., Hattel, J.H., Mikkelsen, L.P. Individual Fibre Inclination Segmentation from X-ray Computed Tomography using Principal Component Analysis, <em>Journal of Composite Materials</em>, <strong>56</strong>, 83-98, <a href="https://doi.org/10.1177%2F00219983211052741">https://doi.org/10.1177/00219983211052741</a>, 2022.</p> <p>to where the reference should be given if used. </p> <p>Details on the data-set is given in the supplementary document found together with the data</p> <p>The data-files is given for the two material case called Mock and UD. For each material case, the data is given as:</p> <ul> <li>.txm-files: 3D reconstructed x-ray scan files <ul> <li>FoV 2mm binning 2 (analyzed in the paper)</li> <li>FoV 4mm binning 1 (additional data-set)</li> </ul> </li> <li>2Dtif.zip-files: 2D tif-stack version of the 3D reconstructed data-set</li> <li>.tif-files: stitched SEM scanning file used for fiber volume fraction determination</li> <li>.hdr-files: meta-data ASCII file behind the SEM scan</li> <li>tif.zip-files: The individual images behind the stitched SEM scanning file</li> <li>fig-files: digital form of the fibre trajectories colored according to their individual mean inclination used in figure xx in reference yy</li> <li>m-files: Matlab-script for calculating the fibre volume fraction (Vf) from the SEM image</li> <li>mat-files: Mat-file with the segmented part in the SEM image used for the Vf calculation</li> </ul>
Dataset for the Manuscript: Surfactants Control Optical Trapping Near a Glass Wall
<p>This repository includes datasets supporting our manuscript that will be transferred to <em>the Journal of Physical Chemistry C</em>. This Version 2 includes extensive new results conducted during the revision process. </p> <ul> <li><strong>'Videos.zip'</strong>: Recordings of trapped particles, estimated trajectories, and calculated MSDs<strong>.</strong></li> <li><strong>'Dynamic Light Scattering.zip'</strong>: Measurement data using dynamic light scattering (DLS). It includes the conductivity, zeta potentials, and hydrodynamic size measurements.</li> <li><strong>'Raw data manual.html'</strong>: A data manual explaining the data details and visualizing the results.</li> </ul> <p>Notes:</p> <p>For finding particle trajectories, we used a Python package, <a href="http://soft-matter.github.io/trackpy/v0.4.2/index.html">Trackpy</a>, developed by Allan et al. We simply followed <a href="http://soft-matter.github.io/trackpy/v0.4.2/tutorial/walkthrough.html">their walkthrough</a> to find particle locations in a video recording and link them to a particle trajectory. The details of our trajectory outputs (_traj.csv files) can be found in <a href="http://soft-matter.github.io/trackpy/v0.4.2/generated/trackpy.locate.html#trackpy.locate">their API reference</a>. </p>
Spin-Glass Behavior in LaCu4Mn Compound
<p>The experimental results of the X-ray powder diffraction, magnetic susceptibility, electrical resistivity, and specific heat measurements of the LaCu<sub>4</sub>Mn compound are presented. LaCu<sub>4</sub>Mn is an intermetallic compound that crystallizes in the hexagonal CaCu<sub>5</sub>-type structure (space group P6/mmm, No. 191), where the atoms on the 3g (1/2, 0, 1/2) site create a kagome lattice, which can cause the spin frustration and leads to a variety of interesting states of matter, such as spin-ice, spin-liquid, and spin-glass states. The Rietveld refinement reveals a random distribution of Mn and Cu atoms on the 3g and 2c site, where about 80% of Mn atoms occupy the 3g site. The lattice parameters are a=5.252(1) Å and c=4.176(1) Å. The low-field zero-field-cooled and field-cooled DC magnetic susceptibilities show splitting below the spin freezing temperature T<sub>f</sub> ≈33 K. At 2 K the magnetization M(H) exhibits hysteresis with coercivity field of ≈5 kOe. The AC susceptibility measurements exhibit a frequency-dependent cusp, associated with a frequency-dependent freezing temperature. Moreover, there is no clear sign of long range magnetic order in specific heat and resistivity measurements.</p>
Designing and implementing smart glass technology for emergency medical services: A sociotechnical perspective
<p>Objective: This study aims to investigate key considerations and critical factors that influence the implementation and adoption of smart glasses in fast-paced medical settings such as emergency medical services (EMS).</p> <p>Materials and Methods: We employed a sociotechnical theoretical framework and conducted a set of participatory design workshops with fifteen EMS providers to elicit their opinions and concerns about using smart glasses in real practice.</p> <p>Results: Smart glasses were recognized as a useful tool to improve EMS workflow given their hands-free nature and capability of processing and capturing various patient data. Out of the eight dimensions of the sociotechnical model, we found that hardware and software, human-computer interface, workflow, and external rules and regulations were cited as the major factors that could influence the adoption of this novel technology. EMS participants highlighted several key requirements for successful implementation of smart glasses in the EMS context, such as durable devices, easy-to-use and minimal interface design, seamless integration with existing systems and workflow, and secure data management.</p> <p>Discussion: Applications of the sociotechnical model allowed us to identify a range of factors, including not only technical aspects, but also social, organizational, and human factors, that impact the implementation and uptake of smart glasses in EMS. Our work informs design implications for smart glass applications to fulfill EMS providers' needs.</p> <p>Conclusion: The successful implementation of smart glasses in EMS and other dynamic healthcare settings needs careful consideration of sociotechnical issues and close collaboration between different stakeholders.</p>
Glass Eel metabolomics Dataset
<p>Glass eel metabolite dataset by HRMS. Polar metabolome and lipidome are included. Supplementary data of "Metabolomics to study the sublethal effects of diazepam and irbesartan on glass eels (<em>Anguilla anguilla</em>)"</p>
Dataset for scanning electron microscopy based local fiber volume fraction analysis of non-crimp fabric glass fiber reinforced composites
<p>SEM data sets, Matlab codes, and output from the local fiber volume fraction analysis from the publications:</p> <p>Mortensen, U.A., Rasmussen, S., Mikkelsen, L.P., Fraisse, A., Andersen, T.L. The impact of the fibre volume fraction on the fatigue performance of glass fiber composites used in the wind turbine industry, <em>Composites Part A</em>, submitted Dec 2022.</p> <p>Mikkelsen, Lars P., Fæster, S., Dahl, V.A. Dataset for scanning electron microscopy based local fiber volume fraction analysis of non-crimp fabric glass fiber reinforced composites. <em>Data in Brief</em>, Submitted, 2023.</p> <p>to where a reference should be given. </p> <p>The files are structured in the following way.</p> <ul> </ul> <p>L1, L2: Low FVF cases 1 and 2; see the publication.<br> H1, H2: High FVF case 1 and 2; see the publication.</p> <p>SEM images:</p> <ul> <li>*.bmp: Single SEM scan</li> <li>*.bmp.hdr: settings for single SEM scan</li> <li>*.tif: Stitched SEM scan</li> <li>*.tif.hdr: settings for stitched SEM scan</li> </ul> <p>*_BundleAnalysis.m: Script for manual segmentation of the individual bundles.</p> <ul> <li>*.zip files: Functions used by the ..._BundleAnalysis.m scripts</li> <li>*-CURVES_AND_AREAS.mat: Matlab saving of bundle definitions used by the ...BUndlesAnalysis.m script</li> <li>*BWbundles.mat: Output from the _BundleAnalysis.m script</li> </ul> <p>*.m: Local fiber volume fraction analysis script of SEM-scan based on output from BundleAnalysis tool</p> <ul> <li>Figxx.png: Reference to specific figures in the publications shown for all 4 cases</li> <li>Fig7.m: Matlab script for plotting figure 7</li> </ul> <p> </p> <p> </p> <p> </p> <p> </p>
Magnetic Properties of Lightning-Induced Glass Produced from Five Mineral Phases
<p>The excel sheet contains raw and corrected vibrating sample magnetometry data of five igneous minerals (< 32 µm powders of albite, labradorite, augite, hornblende, and magnetite) before and after high-current impulse experiments conducted at peak currents of 25 and 40 kA.</p>
Glass-Like Random Catalogues for Two-Point Estimates on the Light Cone (Data Repository)
<p>This is the data repository for the article Glass-Like Random Catalogues for Two-Point Estimates on the Light Cone.</p> <p>arxiv link: https://arxiv.org/abs/2304.02040</p> <p>DOI:</p> <p> </p> <p>The file grlic_data.tar.gz contains three directories: /data, /correlations, and /randoms.</p> <p>Inside the /data folder, the data catalogues used in the article are stored: in "cat_part_1162568" the three columns correspond to the redshift, the cosine of the polar angle, and the azimuthal angle, respectively. The first three columns of the "cat_high_1164853" and "cat_low_1164853" catalogues correspond to the same properties for the high-mass and low-mass halos, respectively. In addition to that, these files also contain additional information about the halos: the number of particles (4th column), their M_200b mass (5th column) and their parent ID (6th colum), which is -1 if the halo is not a subhalo.</p> <p>Inside the /randoms folder, the random catalogues for each of the data catalogues in /data are stored. Files beginning with "part" refer to randoms based on the particle catalogue, in a similar fashion the files beginning with "high" correspond to randoms based on the high-mass halo catalogue and those beginning with "low" refer to the randoms based on the low-mass halo catalogue. Files with "..._glass<x>..." correspond to the glass-like random catalogues, and files with "..._rand<x>..." correspond to the Poisson-sampled randoms, where <x> is the value of <span class="math-tex">\(\alpha\)</span> used. <span class="math-tex">\(\alpha\)</span> is the factor by which the number of objects in the data catalogue is multiplied to get the number of objects in the random catalogues, <span class="math-tex">\(N_R = \alpha N_D\)</span>. For the glass-like randoms based on the high-mass halo catalogue, the additional suffix, "..._deltagrid<y>...", refers to the number of grid-cells used in the Zeldovich approximation, where <y> is the number of grid cells, and "..._Niter<z>..." refers to the number of Zeldovich iterations perfomed, which is given by <z>. Similarly to the data catalogues, the three columns represent the redshift, cosine of the polar angle, and the azimuthal angle of each object in the catalogue.</p> <p>Inside the /correlations folder, there are two subdirectories: /correlations/full and /correlations/multipoles. The /correlations/full directory contains the raw output from CUTE for each correlated pair of catalogues. For example, the subdirectory /correlations/full/low_low contains the outputs for the low-mass halo autocorrelation, or the subdirectory /correlations/full/high_part contains the outputs for the cross-correlation between the high-mass halo catalogue and the particle catalogue. The naming convention of these files is "<type><alpha>_<catalogues>_<i>", where <type> can either be "rand" or "glass", for either the Poisson-sampled or glass-like random catalogues, <alpha> is the factor <span class="math-tex">\(\alpha\)</span> already introduced above, <catalogues> again describes which two data catalogues have been cross- (or auto-) correlated, e.g. "highlow" refers to a cross-correlation between the high-mass halo catalogue and the low-mass halo catalogue, and finally <i> is a number between 0 and 19 for the 20 independent measurements of the correlations. For the high-mass halo catalogue autocorrelations involving glass-like randoms, the additional suffix, "..._deltagrid<y>...", refers to the number of grid-cells used in the Zeldovich approximation, where <y> is the number of grid cells, and "..._Niter<z>..." refers to the number of Zeldovich iterations perfomed, which is given by <z>. The format of the files is the standard CUTE format for the 3D correlation using binning in (mu,r), i.e. see the readme of https://github.com/damonge/CUTE/tree/master/CUTE, section 5. It reads:</p> <pre>For the 3-D correlation functions the output file has 7 columns with x1 x2 xi(x1,x2) D1D2(x1,x2) D1R2(x1,x2) R1D2(x1,x2) R1R2(x1,x2) where (x1,x2) is either (pi,sigma) or (mu,r). </pre> <p>The /correlations/multipoles subdirectory contains the estimated mean multipoles and their variance derived from the 20 individual correlation measurements for each data catalogue and type of random catalogue. Similarly to the /correlations/full subdirectory, it contains a separate directory for each pair of data catalogue for which the correlation was estimated. The files are named according to "<multipole>_<type><alpha>_<catalogues>_mean_var", where <multipole> is either l0 for the monopole, l1 for the dipole, or l2 for the quadrupole. The <type>, <alpha> and <catalogues> are identical to what was described above for the /correlations/full subdirectory. Again, for the high-mass halo catalogue autocorrelations involving glass-like randoms, the additional suffix, "..._deltagrid<y>...", refers to the number of grid-cells used in the Zeldovich approximation, where <y> is the number of grid cells, and "..._Niter<z>..." refers to the number of Zeldovich iterations perfomed, which is given by <z>. The columns in each of these files are the comoving separation d, the mean multipole <span class="math-tex">\(\xi_l\)</span>, and its variance <span class="math-tex">\(\sigma^2\)</span>of each bin.</p>
Supplementary materials to: "SilicH2O: a graphical user interface for processing silicate glass Raman spectra and quantifying H2O"
<p>The dataset contains:</p> <ul> <li>supplementary text and figures as a single pdf</li> <li>Raman and compositional data in two separate excel files</li> </ul> <p> </p>
Hydrogen Diffusion in Silicate Glasses
<p>This repository contains all data and MATLAB(c) scripts that were used to calculate diffusion profiles in the associated publication.</p>
Chemical composition of DCH-67.55 cryptotephra glass shards from Lake Chala
<p>Mean composition data based on <em>n</em> single DeepCHALLA cryptotephra glass shard analyses of major and minor element oxides (by WDS-EPMA, <em>n</em>=32) and trace elements (by LA-ICP-MS, <em>n</em>=19). Also shown are compositions of secondary glass standards measured during the same instrumental runs, and their correspondence with approximate expected values for in-house Lipari glass and with GeoRem-preferred (pref. val.) or true values for MPI-DING glass secondary standards (Marshall et al., 2009; Scot and Skilling, 1999).</p>
Magnetocaloric effect in spin-glass-like GdCu4Mn compound
<p>Dataset for: Magnetocaloric effect in spin-glass-like GdCu<sub>4</sub>Mn compound</p> <p>Materials based on Gd with magnetic frustration may have high magnetocaloric application potential. GdCu<sub>4</sub>Mn crystallizes in hexagonal CaCu<sub>5</sub>-type structure with space group <em>P</em>6/<em>mmm</em> (no. 191, Pearson symbol: <em>hP</em>6). Lattice parameters for the polycrystalline sample are equal to <em>a</em> = 5.114(3) Å and <em>c</em> = 4.151(4) Å. Due to structural disorder, namely random distribution of Cu and Mn atoms on 2<em>c</em> and 3<em>g</em> positions, a spin-glass-like behavior is observed in this material at low temperatures. In addition to the standard measurements of DC magnetization and AC magnetic susceptibility, the spin-glass state was confirmed by the memory effect and relaxation behavior. The absence of clear anomalies in the temperature dependencies of specific heat and electrical resistance suggests the lack of long-range magnetic order.</p>
A Raman Spectroscopic Study of Lightning-Induced Glass Produced from Five Mineral Phases Dataset
<p>Dataset contains raw and corrected Raman spectra for five common mineral < 32 µm powders (albite, labradorite, augite, hornblende, and magnetite) before and after high-current impulse experiments conducted at peak currents of 25 and 40 kA.</p>
Supplemental Material to Article "Quantification of process-induced effects on fatigue life of short-glass-fiber-filled adhesive used in wind turbine rotor blades"
<p>This set supplements the figure data to the article "Quantification of process-induced effects on fatigue life of short-glass-fiber-filled adhesive used in wind turbine rotor blades", DOI: xxx</p>
Data for Non-Redundant Image Clustering of Early Medieval Glass Beads (DSAA 2023)
<p>Archeological glass beads images with measurements (width, height, weight), pretrained models, resampled data (with less color bias) and clustering results from the paper Non-Redundant Image Clustering of Early Medieval Glass Beads (Accepted at DSAA 2023)</p>
Inductively coupled plasma mass spectrometry of ions released from Ti40Zr10Cu36Pd14 bulk metallic glass
<p>Inductively coupled plasma mass spectrometry (ICP-MS) of ions released from Ti40Zr10Cu36Pd14 bulk metallic glass after incubation in artificial saliva for 1 day, 3 days and 7 day to see how much it releases its ion into the medium. </p>
static water contact angle measurements of Ti40Zr10Cu36Pd14 bulk metallic glass and Ti6Al4V surfaces
<p>static water contact angle measurements of Ti40Zr10Cu36Pd14 bulk metallic glass and Ti6Al4V surfaces: the measurments were first taken place on their etched surface and was repeated after they were incubated in orbital shaker in distilled water at 37˚C and 120 rpm for 48 hours. </p> <p> </p>
cytocompatibility analysis of Ti6Al4V and Ti40Zr10Cu36Pd14 bulk metallic glass
<p>using Alamar blue to quantitatively measure the metabolic activity of fibroblast after 24 h and 48 h of cell culture on Ti6Al4V and Ti40Zr10Cu36Pd14 bulk metallic glass. </p>
High though-put proteomics analysis of dental plaque cultured on Ti40Zr10Cu36Pd14 bulk metallic glass and Ti6Al4V surface
<p>High though-put proteomics analysis of dental plaque cultured on Ti40Zr10Cu36Pd14 bulk metallic glass and Ti6Al4V surface</p>
Metabolic activity of aggregatibacter on Ti-based bulk metallic glass compared with Ti6Al4V
<p>Metabolic activity of aggregatibacter on Ti40Zr10Cu36Pd14 bulk metallic glass compared with T6Al4V (used as a control and therefore all values are considered as 100). </p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.