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3,474 results for “electronics”
Covid-19 Vaccine Monitoring project (CVM)-Electronic Health Record data sources Codelist
<p>This is the code list that was used to identify outcomes and covariates (those tagged as in narrow) in electronic health records of participating data sources in the the CVM study which was addressing the following questions</p> <p> </p> <p>1)<strong> To create and assess readiness of electronic health record data sources for rapid evaluation of safety signals by </strong></p> <ul> <li> <p>Providing an overview of the methods for identification of COVID-19 vaccine exposure in the data sources </p> </li> <li> <p>Monitoring the number of individuals exposed to any COVID-19 vaccine and to compare this to COVID-19 vaccine exposure (benchmark: ECDC vaccine tracker)1 </p> </li> <li> <p>Generation of updated background rates for AESIs </p> </li> </ul> <p><strong>2) To conduct rapid safety assessment studies using electronic healthcare records and support EMA safety assessments. </strong></p> <p>The protocol for this study is publicly available www.encepp.eu/encepp/viewResource.htm?id=42637. The report with results using the code list is publicly available on Zenodo as well. </p> <p> </p> <p> </p> <p> </p>
List of Electron Diffusion Regions (EDR) observed by NASA/MMS
<p><strong>List of Electron Diffusion Regions (EDR) during the phases 1a & 1b of the NASA/MMS mission.</strong><br> EDR from Lenouvel_et_al._[2021] and Lenouvel_(unpublished) were detected with two distinct machine learning algorithms. The first algorithm (MLP) is detailed in Lenouvel_et_al._[2021]. Both algorithms (MLP and CNN) are described in Q. Lenouvel's PhD manuscript and in "Advanced Methods for Analyzing In-Situ Observations of Magnetic Reconnection" submitted to Space Science Reviews by Hasegawa et al..<br> For completeness, other EDR events reported in the literature are added to the list. All references are given below. Note that some events were observed by other MMS spacecraft at slightly different times.</p> <p>Burch, J. L., and T. D. Phan, Magnetic reconnection at the dayside magnetopause: Advances with MMS, Geophysical Research Letters, 43 (16), 8327–8338, https://doi.org/10.1002/2016GL069787, 2016.<br> Burch, J. L., et al., Electron-scale measurements of magnetic reconnection in space, Science, 352 (6290), aaf2939, https://doi.org/10.1126/science.aaf2939, 2016.<br> Chen, L.-J., et al., Electron energization and mixing observed by mms in the vicinity of an electron diffusion region during magnetopause reconnection, Geophysical Research Letters, 43 (12), 6036–6043, https://doi.org/10.1002/2016GL069215, 2016.<br> Chen, L.-J., et al., Electron diffusion region during magnetopause reconnection with an intermediate guide field: Magnetospheric multiscale observations, Journal of Geophysical Research: Space Physics, 122 (5), 5235–5246, https://doi.org/10.1002/2017JA024004, 2017.<br> Cozzani, G., et al., In situ spacecraft observations of a structured electron diffusion region during magnetopause reconnection, Phys. Rev. E 99, 043204 (2019); https://doi.org/10.1103/PhysRevE.99.043204<br> Dong, X.-C., et al., Observation of nonuniform energy dissipation in the electron diffusion region of magnetopause reconnection, Geophysical Research Letters, 48 (13), e2020GL091928, https://doi.org/10.1029/2020GL091928, 2021.<br> Ergun, R. E., et al., Drift waves, intense parallel electric fields, and turbulence associated with asymmetric magnetic reconnection at the magnetopause, Geophysical Research Letters, 44 (7), 2978–2986, https://doi.org/10.1002/2016GL072493, 2017.<br> Eriksson, S., et al., Magnetospheric multiscale observations of the electron diffusion region of large guide field magnetic reconnection, Phys. Rev. Lett., 117, 015,001, https://doi.org/10.1103/PhysRevLett.117.015001, 2016.<br> Fuselier, S. A., et al., Large-scale characteristics of reconnection diffusion regions and associated magnetopause crossings observed by mms, Journal of Geophysical Research: Space Physics, 122 (5), 5466–5486, https://doi.org/10.1002/2017JA024024, 2017.<br> Genestreti, K. J., et al., Mms observation of asymmetric reconnection supported by 3-d electron pressure divergence, Journal of Geophysical Research: Space Physics, 123 (3), 1806–1821, https://doi.org/10.1002/2017JA025019, 2018.<br> Graham, D. B., et al., Instability of agyrotropic electron beams near the electron diffusion region, Phys. Rev. Lett., 119, 025,101, https://doi.org/10.1103/PhysRevLett.119.025101, 2017.<br> Khotyaintsev, Y. V., et al., Electron jet of asymmetric reconnection, Geophysical Research Letters, 43 (11), 5571–5580, https://doi.org/10.1002/2016GL069064, 2016.<br> Lenouvel, Q., Identification par apprentissage machine et analyse de régions de diffusion électronique à la magnétopause terrestre observées par MMS, Thèse de doctorat en Astrophysique, Sciences de l'Espace, Planétologie, Université de Toulouse, http://thesesups.ups-tlse.fr/5558/, 2022.<br> Lenouvel, Q., et al., Identification of electron diffusion regions with a machine learning approach on mms data at the earth’s magnetopause, Earth and Space Science, 8 (5), e2020EA001530, https://doi.org/10.1029/2020EA001530, 2021.<br> Li, W. Y., et al., Electron Bernstein waves driven by electron crescents near the electron diffusion region, Nature Communications, 11 (1), 141, https://doi.org/10.1038/s41467-019-13920-w, 2020.<br> Norgren, C., et al., Finite gyroradius effects in the electron outflow of asymmetric magnetic reconnection, Geophysical Research Letters, 43 (13), 6724–6733, https://doi.org/10.1002/2016GL069205, 2016.<br> Phan, T. D., et al., Mms observations of electron-scale filamentary currents in the reconnection exhaust and near the x line, Geophysical Research Letters, 43 (12), 6060–6069, https://doi.org/10.1002/2016GL069212, 2016.<br> Webster, J. M., et al., Magnetospheric Multiscale Dayside Reconnection Electron Diffusion Region Events, Journal of Geophysical Research (Space Physics), 123 (6), 4858–4878, https://doi.org/10.1029/2018JA025245, 2018.</p> <p> </p>
Field Emission Scanning Electron microscopy from Zr-Cu-Ag metallic glass coatings after antibacterial test with E.Coli
<p>Field Emission Scanning Electron Microscopy Figures from metallic glass (Zr-Cu-Ag) antibacterial coatings. Coatings have the name SP in their file name. The non-coated comparison is PBT. This is after the antibacterial test with <em>E.coli</em> after 24 hours. </p>
Simulation results for study on pulsed electron lenses for space charge mitigation
<p>Simulation results for beam loss in the FAIR SIS100 synchrotron for a comprehensive study on pulsed electron lenses for space charge mitigation. The affiliated manuscript "Pulsed electron lenses for space charge mitigation" describing the study parameters is published on arxiv.org (https://arxiv.org/abs/2310.02365) and submitted for journal publication.</p> <p>For the "ffsc" files, each file contains the tabulated beam survival rate of 1000 simulated particles for a given bare tune. A file typically gathers results from scanning the betatron tune quadrant 18.5 <= Qx,y <= 19.0 in tune steps of 0.01.</p> <p>Explanation of file names:</p> <p>- "ffsc": using the fixed frozen Gaussian field map model for space charge (as established in https://doi.org/10.1103/PhysRevAccelBeams.25.054402 );</p> <p>- "nel": number of pulsed electron lenses placed symmetrically in the straight sections of the SIS100 ring;</p> <p>- "alpha": linear compensation degree, alpha=1.0 corresponds to a total electron lens tune implied tune shift equal to the linear rms-equivalent KV space charge tune shift;</p> <p>- "N": intensity in percent units of the FAIR design intensity for Uranium-28+ beams, i.e. N=100 corresponds to the FAIR design intensity;</p> <p>- "2D" or "3D": the 3D results correspond to the full simulation model with (nonlinear) synchrotron motion, the 2D results assume a fixed longitudinal phase-space distribution and only simulate the transverse dynamics (thus, periodic resonance crossing is suppressed by construction).</p>
Dataset of the paper "Improving the Stability of Photodoped Metal Oxide Nanocrystals with Electron Donating Graphene Quantum Dots"
<p>The dataset provides the data for the publication: "Improving the Stability of Photodoped Metal Oxide Nanocrystals with Electron Donating Graphene Quantum Dots"</p>
Supporting data for "In situ Quantitative Tensile Tests on Antigorite in a Transmission Electron Microscope"
<p>Abstract: The determination of the mechanical properties of serpentinites is essential towards the understanding of the mechanics of faulting and subduction. Here, we present the first in situ tensile tests on antigorite in a transmission electron microscope. A push-to-pull deformation device is used to perform quantitative tensile tests, during which force and displacement are measured, while the microstructure is imaged with the microscope. The experiments have been performed at room temperature on beams prepared by focused ion beam. The specimens are not single crystals despite their small sizes. Orientation mapping indicated that some grains were well-oriented for plastic slip. However, no dislocation activity has been observed even though engineering tensile stress went up to 700 MPa. We show also that antigorite does not exhibit an pure elastic-brittle behaviour since, despite the presence of defects, the specimens underwent plastic deformation and did not fail within the elastic regime. Instead, we observe that strain localizes at grain boundaries. All observations concur to show that under our experimental conditions, grain boundary sliding is the dominant deformation mechanism. This study sheds a new light on the mechanical properties of antigorite and calls for further studies on the structure and properties of grain boundaries in antigorite and more generally in phyllosilicates.</p>
CLIC Calorimeter 3D images: Electron showers at Fixed Angle
<p>Energy deposits from single-particle showers in the ECAL+HCAL calorimeters of the CLIC detector</p> <p>Simulation performed with GEANT4 (https://geant4.web.cern.ch) and DD4HEP software (https://dd4hep.web.cern.ch/dd4hep/)</p> <p>Electrons entering the detector at variable energy and fixed direction (perpendicular to the ECAL inner surface)</p> <p>See https://arxiv.org/abs/1912.06794 for details</p>
datasets for "VLF Transmitters and Lightning Generated Whistlers 2: Diffusion of Radiation Belt Electrons"
<p>Supporting information for "VLF Transmitters and Lightning Generated Whistlers 2: Diffusion of Radiation Belt Electrons," submitted to Journal of Geophysical Research Space Physics. Diffusion coefficients for selected values of L and energy due to Very Low Frequency (VLF) transmitters and lightning generated whistlers (LGW), as well as Da0a0 and energy drag rates |dE/dt|/E from Coulomb collisions. Also provided are precipitation lifetimes, which include Da0a0 from plasmaspheric hiss but do not account for energy drag. Calculations are presented for high and low-density plasmasphere models, for all four combinations of ducted or nonducted VLF and LGW waves.</p>
Diagnostic electron microscopy of viruses with low-voltage electron microscopes. Raw image files with brief description.
<p>The zipped data container contains the raw (unprocessed) images that we have used for the preparation of our manuscript entiteled:</p> <p>"Diagnostic electron microscopy of viruses with low-voltage electron microscopes" <a href="https://doi.org/10.1369%2F0022155420929438">https://doi.org/10.1369/0022155420929438</a></p> <p>Lars Möller, Gudrun Holland, Michael Laue</p> <p>Advanced Light and Electron Microscopy (ZBS 4), Centre for Biological Threats and Special Pathogens, Robert Koch Institute, D-13353 Berlin, Germany</p> <p>The brief description of the data set comprises the abstract of the manuscript, the figures (including captions) and a description of the materials and methods used for their generation.</p>
Dataset used in manuscript Tailored Nanoscale Plasmon-Enhanced Vibrational Electron Spectroscopy
<p>This file contains the raw dataset used in the manuscript "Tailored Nanoscale Plasmon-Enhanced Vibrational Electron Spectroscopy" published in L. H. G. Tizei et al Nano Letters, 2020 (doi: 10.1021/acs.nanolett.9b04659)</p> <p><br> Data has been acquired using Nion Swift (https://nionswift.readthedocs.io/en/stable/). Experimental details can be found in L. H. G. Tizei et al Nano Letters, 2020 (doi: 10.1021/acs.nanolett.9b04659).<br> <br> The dataset has been analyzed using the following Python libraries:</p> <p>Numpy, Scipy, Hyperspy, Matplotlib</p> <p>EELS hyperspectral images have been aligned using the Hyperspy "align1D" method. Aligned EELS hyperspectral images are saved in files finished with "_Aligned.hspy":</p> <p>For the strong coupling experiments:<br> Tip 1 is on hBN<br> Tip 2 is on vacuum</p> <p>For each of the nanowires tips, a file with the fitted coefficients are available, as well as a plot of the data and the fitted curve.</p> <p>Datasets have been fitted with gaussian and/or lorentizan functions, as described in the published text.</p> <p>Any question can be forwarded to the corresponding authors of the published text.</p> <p> </p>
A small dataset for analyzing spectroscopic parameters from low-cost electronic structure methods
<p>This dataset comprises two files: `lee_bayesian_dataset.csv` and `raw_outputs.tar.xz`. The former corresponds to an aggregated table of data used for subsequent analysis, and the latter are raw output files from Gaussian '09. This dataset corresponds to 6916 calculations of 76 representative molecules with high-resolution gas-phase rotational constants.</p> <p> </p> <p>This version corresponds to the data used for our publication:</p> <p>Bayesian Analysis of Theoretical Rotational Constants from Low-Cost Electronic Structure Methods</p> <p>https://pubs.acs.org/doi/10.1021/acs.jpca.9b09982</p>
Tilted fluctuation electron microscopy data from simulated and deposited amorphous Ta
<p>These datasets were used to compare fluctuation electron microscopy analysis methods on simulated and sputter deposited amorphous tantalum. The Ta is 8 nm thick in both the simulated and deposited samples. The deposited Ta is sandwiched between two layers of amorphous 10 nm-thick SiN<sub>x</sub>. Data are also provided for SiN<sub>x</sub> deposited on SiN<sub>x</sub>.</p> <p>Deposited Ta FEM patterns were collected on a TitanX at 200 kV with a convergence angle of 0.51 mrad and a camera length of 300 mm. Simulated Ta FEM patterns were generated using the Prismatic STEM simulation software (see references).</p> <p>The samples were tilted between 0<sup>o</sup> and 45<sup>o</sup> in 15<sup>o</sup> increments. </p> <p><strong>Deposited Ta: </strong></p> <p>.dm4 (Gatan DigitalMicrograph) files are provided with the raw scanning nanodiffraction data for each tilt angle</p> <p>.png images of the mean CBED pattern for each tilt angle are provided</p> <p><strong>Simulated Ta:</strong></p> <p>.h5, .xyz (atomic coordinates), and .txt (Prismatic input parameters defined) files are provided with the raw scanning nanodiffraction data for each tilt angle</p> <p>.png images of the mean CBED pattern for each tilt angle are provided</p> <p> </p> <p>The atomic coordinates for the simulated Ta were provided by Jun Ding. Simulated FEM patterns were produced by Luis Rangel DaCosta using Prismatic STEM simulation software. Neal Reynolds grew the experimental Ta and SiN<sub>x</sub> thin films.</p>
Electron microscopy of SARS-CoV-2 particles - Dataset 05
<p>The dataset contains transmission electron microscopy image stacks (tomograms) of ultrathin sections through extracellular SARS-CoV-2 particles in Vero cell cultures. The dataset contains 17 image stacks of slightly variable pixel dimensions, which were recorded at either 1.17 or 0.96 nm pixel size (12 bit). Image stacks were size calibrated and stored in 16 bit TIF format. Visualization can be done using ImageJ or Fiji. Each image stack in TIF format is supplemented by a file containing the corresponding raw image tilt series (MRC format; plus meta data files) generated by the tomography acquisition software and by a file with the aligned tiltseries. A PDF document describes the methods used for generation of the image files. The dataset was generated as dataset 05 for a comparative morphometric analysis of SARS-CoV and SARS-CoV-2. Further datasets which were used for the analysis are available in this repository (see dataset description document).</p> <p>Related publication: Laue M, Kauter A, Hoffmann T, Möller L, Michel J, Nitsche A. Morphometry of SARS-CoV and SARS-CoV-2 particles in ultrathin plastic sections of infected Vero cell cultures. Sci Rep. 2021 Feb 10;11(1):3515. doi: 10.1038/s41598-021-82852-7. PMID: 33568700; PMCID: PMC7876034.</p> <p> </p>
Fast Pixelated Detectors in Scanning Transmission Electron Microscopy. Part II: Post Acquisition Data Processing, Visualisation, and Structural Characterisation
<p>Scanning transmission electron microscopy data related to paper "Scanning transmission electron microscopy data related to paper "Fast Pixelated Detectors in Scanning Transmission Electron Microscopy. Part II: Post Acquisition Data Processing, Visualisation, and Structural Characterisation", <a href="https://doi.org/10.1017/S1431927620024307">https://doi.org/10.1017/S1431927620024307</a>.</p>
Transmission Electron Microscopy Dataset for Image Deblurring
<p>The dataset consists of images corrupted by motion blur together with corresponding high-quality images from two different samples, one of thin sectioned kidney tissue and one of a calibration grid. The data was collected using a MiniTEM microscope (Vironova AB). The motion corrupted images are created by moving the sample under the microscope. Each low-quality (motion blurry) imaging sequence has corresponding high-quality images (captured by stopping the microscope at each position in the sequence). The high-quality frames have a size of 2048 x 2048 pixels with an overlap of 50% between adjacent frames. The low-quality (motion blurry) frames are captured with a size of 1024x1024 with the same motion direction (approximately vertically upwards). All images were captured at a field of view of 32μm, and with a per image exposure time of 15ms and stored as 16 bit tiff files. Both samples are imaged with the same settings and have four imaging sequences each.</p> <p>The dataset contains the raw image files as well as a partitioning into training, validation and testing. For these images, five low-quality images have been registered to each high-quality image. For the five registered images the intersection of all is cropped and stored. 1 of the 4 imaging sequences are chosen as the test set and the last part of another of the imaging sequences as a validation set. The rest is put in the training set.</p> <p><em><strong>Folder Structures:</strong></em></p> <ul> <li><strong>Raw data:</strong> <ul> <li>Raw data is the unprocessed data and each sample folder contains 4 image sequences. In each of these folders low-quality (motion blurry) images are stored in folder “Low” and corresponding high-quality images are stored in “GT”</li> </ul> </li> <li><strong>TrainValTest:</strong> <ul> <li>TrainValTest consist of data where the low-quality frames have been registered to the high-quality frames and divided into a training, validation and test set.</li> <li>Each of the Train, Val, Test folders contains 3 subfolders. “Low” contains folders names the same as the files in “GT” where each folder contains five low-quality (motion blurry) images, registered the that corresponding high-quality image. “GT” contains the corresponding high-quality images down sampled to the same spatial size as the low-quality images. “GT_hr” contains the same images as “GT” but not down sampled.</li> </ul> </li> </ul>
Data for: On-the-fly ab initio semiclassical evaluation of third-order response functions for two-dimensional electronic spectroscopy
<p>Data for publication: T. Begusic, J. Vanicek, On-the-fly ab initio semiclassical evaluation of third-order response functions for two-dimensional electronic spectroscopy, <em>J. Chem. Phys.,</em> <strong>153</strong>, 184110 (2020).</p> <p>Contains simulated linear and two-dimensional spectra of the S<sub>1</sub> - S<sub>0</sub> electronic transition of phenol, excited-state and ground-state ab initio trajectories at the PBE0/6-311G(d,p) level of theory, and other supporting data related to the abovementioned publication.</p>
Data from: Excess Electronic Recoil Events in XENON1T
<p>This file provides data points described in the publication of Phys. Rev. D 102, 072004 (2020), "Excess electronic recoil events in XENON1T” and is made available by the XENON Collaboration.</p>
Electron density and altitude of the main ionospheric peak of Mars as observed by Mars Express instruments. Archived data for the paper "Seasonal and geographical variability of the Martian ionosphere from Mars Express observations", submitted to JGR-Planets
<p>This repository contains archived data for the manuscript "Seasonal and geographical variability of the Martian ionosphere from Mars Express observations", published in Journal of Geophysical Research-Planets. Details about the methods to generate the data can be found in the paper.</p> <p>5 data files plus 2 readme text files are included.</p> <p>The file MEx_ionpeak.dat (described in the readme file README_ionpeak.txt) contains the peak electron densities and peak altitudes resulting from 34539 observations. Each record includes 14 columns. The content of each column is:</p> <p>Column 1: Instrument providing the observation (MARSIS or MaRS)<br> Column 2: Mars Year at which the observation was obtained (from MY27 to MY33)<br> Column 3: Solar Longitude (Ls) of the observation (unit: degrees)<br> Column 4: Latitude of the observation (unit: degrees)<br> Column 5: Longitude of the observation (unit: degrees)<br> Column 6: Solar Zenith Angle (SZA) of the observation (unit: degrees)<br> Column 7: F10.7 solar proxy index at 1 Astronomic Unit (unit: solar flux units)<br> Column 8: Peak electron density measured by the instrument (unit: cm-3)<br> Column 9: Peak electron density at the subsolar point, i.e., corrected for the SZA variation (unit: cm-3)<br> Column 10: Peak electron density at the subsolar point and at F10.7 (1AU)=100, i.e., corrected for the SZA and the solar radiation output variations (unit: cm-3)<br> Column 11: Peak electron density at the subsolar point, at F10.7 (1AU)=100 and corrected for the seasonal variation (unit: cm-3)<br> Column 12: Peak altitude measured by the instrument (unit: km)<br> Column 13: Peak altitude at the subsolar point, i.e. corrected for the SZA variation (unit: km)<br> Column 14: Peak altitude at the subsolar point and corrected for the seasonal variation (unit: km)</p> <p> </p> <p>The files eprofiles_MaRS.dat, eprofiles_MARSIS_prof1.dat, eprofiles_MARSIS_prof2.dat and eprofiles_MARSIS_prof3.dat contain 4 electron density profiles. They are described in the file README_eprofiles.txt. Each file includes 2 columns, the first one being the altitude (unit: km) and the second one the electron density (unit: cm-3).</p> <p> </p> <p>Contact: Francisco Gonzalez-Galindo, ggalindo@iaa.es<br> </p>
Research data supporting "4D Electron Tomography of Dislocations Undergoing Electron Irradiation"
<p>All TEM micrographs and electron diffraction patterns for tomography</p>
Research data supporting for Application of electron tomography of dislocations in beam-sensitive quartz to the determination of strain components
<p>This archives contains all the raw data (micrographs) supporting the publication</p>
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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)
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DANDI Archive for NWB datasets
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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.