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Surface electromyogram (sEMG) dataset recorded from forearm for 9 hand movements and three electrode array positions
<p>This repository contains raw surface Electromyography signals termed surface Electromyograms (<a href="https://en.wikipedia.org/wiki/Electromyography">sEMG</a>) recorded with 8 circular surface Ag/AgCl pairs of electrodes placed circumferentially around the forearm of the dominant arm in 10 able-bodied individuals (5 Females and 5 Males). The proposed method for processing sEMG data with subjects' characteristics and protocol can be found in <a href="https://doi.org/10.1016/j.bspc.2020.102292">Miljković & Isaković 2021</a>.</p> <p>For each subject, sEMG was recorded from <strong>three recording electrode array positions</strong> termed P1, P2, and P3 for 9 hand movements. We provide a compressed .7z folder with 10 sub-folders for each subject named by <strong>subject ID</strong> (ID1, ID2, ... ID10). Each sub-folder contains 27 .txt data files (for 9 movements × 3 electrode array positions), except for subject ID7 (there are 24 .txt records, since three records for wrist extension EX in P1, P2, and P3 positions got corrupted in subject ID7). Average size of 10 sub-folders is 167.50 ± 27.02 MB with maximum of 194 MB and minimum of 117 MB.</p> <p>The subjects performed following hand movements from the reference resting position –relaxation, R (explained in-detail in <a href="https://doi.org/10.1016/j.bspc.2020.102292">Miljković & Isaković 2021</a>): (1) spherical power grasp, PS, (2) three finger sphere grasp, 3F, (3) two finger prismatic grasp, PP, (4) wrist flexion, FL, (5) wrist extension, EX, (6) radial deviation, RD, (7) ulnar deviation, UD, and then forearm rotation i.e. (8) pronation, PR, and (9) supination, SU. PS, 3F, PP, FL, EX, RD, UD, PR, and SU correspond to <strong>type of hand movement</strong> in naming convention for .txt data files.</p> <p><a href="https://www.youtube.com/playlist?list=PLI3SYeiSufnBo6UDAZt9NJO9ecb-InJqb">Hand movements YoutTube playlist</a> contains explanatory videos for 9 hand movements recorded in this study, and we also provide corresponding .wmv here in the "movies hand movements.7z". Naming convention for .wmv files is <strong>type of hand movement</strong> with both full name and abbreviation for the movement (for example "radialDeviation-RD.wmv").</p> <p>Naming convention for .txt data files within 10 sub-folders is: <strong>subjects ID _ type of hand movement _ recording electrode array position</strong> (for example: "ID1_3F_P1.txt" in sub-folder ID1, "ID9_RD_P3.txt" in sub-folder ID9).</p> <p><strong>Dataset contents</strong></p> <ol> <li><a href="https://zenodo.org/record/4039550/files/EMG%20dataset.7z?download=1">EMG dataset.7z</a>, 267 .txt data files, text format</li> <li><a href="https://zenodo.org/record/4039550/files/movies%20hand%20movements.7z?download=1">movies hand movements.7z</a>, 9 .wmv files, explanatory hand movement videos (also available on <a href="https://www.youtube.com/playlist?list=PLI3SYeiSufnBo6UDAZt9NJO9ecb-InJqb">YouTube</a>)</li> <li><a href="https://zenodo.org/record/4039550/files/README.txt?download=1">README.txt</a>, metadata for data files, text format</li> </ol> <p><strong>Data files contain numerical values with decimal point* according to the following structure</strong></p> <ol> <li>column - CH1** (recorded samples from channel 1)</li> <li>column - CH2** (recorded samples from channel 2)</li> <li>column - CH3** (recorded samples from channel 3)</li> <li>column - CH4** (recorded samples from channel 4)</li> <li>column - CH5** (recorded samples from channel 5)</li> <li>column - CH6** (recorded samples from channel 6)</li> <li>column - CH7** (recorded samples from channel 7)</li> <li>column - CH8** (recorded samples from channel 8)</li> </ol> <p>* For subjects ID1 and ID2 three decimal places are provided, while for other subjects 6 decimal places in .txt data files are provided.</p> <p>** Each data file contains at least 10 repetitions of the corresponding movement. In cases where file contains >10 repetitions (overall 162 .txt data files), we used the first or the last ten for the analysis (except for two files where short and strong artifact appeared during the measurement procedure, and corresponding movement repetitions were discarded) presented in <a href="https://doi.org/10.1016/j.bspc.2020.102292">Miljković & Isaković 2021</a>.</p> <p>Sample rate was set at 1000 Hz and <a href="https://en.wikipedia.org/wiki/Analog-to-digital_converter">A/D card</a> had 16 bits resolution. Gain of the amplifier was set at 1000. For more in-detail explanations of electrode array assemble and positioning for sEMG channels CH1, CH2, ... CH8, please refer to <a href="https://doi.org/10.1016/j.bspc.2020.102292">Miljković & Isaković 2021</a>.</p> <p>If you find these signals useful for your own research or teaching class, please cite both relevant preprint and dataset as:</p> <ol> <li> <p>Miljković, N. and Isaković, M.S., 2021. Effect of the sEMG electrode (re) placement and feature set size on the hand movement recognition. <em>Biomedical signal processing and control</em>, 64:102292. <em><a href="https://doi.org/10.1016/j.bspc.2020.102292">10.1016/j.bspc.2020.102292</a></em></p> </li> <li> <p>Miljković, N. and Isaković, M.S., 2020. Surface electromyogram (sEMG) dataset recorded from forearm for 9 hand movements and three electrode array positions. [Data set]. <em>Zenodo</em> <em><a href="https://zenodo.org/record/4039550">10.5281/zenodo.4039550</a></em>.</p> </li> </ol> <p><strong>ACKNOWLEDGEMENTS</strong> (from <a href="https://doi.org/10.1016/j.bspc.2020.102292">Miljković & Isaković 2021</a>): "Special appreciation the authors owe to Professor Mirjana B. Popović from the University of Belgrade for her kind support,precious guidance, and advice regarding this research which significantly improved the manuscript. Also, the authors would like to thank Dr Matija Štrbac from Tecnalia Serbia Ltd. for providing advice throughout the study.The authors thank all volunteers for their participation."</p>
Crossreactive probes on Illumina DNA methylation arrays: a large study on ALS shows that a cautionary approach is warranted in interpreting epigenome-wide association studies
<p>Data corresponding to the paper "Crossreactive probes on Illumina DNA methylation arrays: a large study on ALS shows that a cautionary approach is warranted in interpreting epigenome-wide association studies."<br> <br> Corresponding scripts can be found at: <a href="https://github.com/pjhop/dnamarray_crossreactivity">https://github.com/pjhop/dnamarray_crossreactivity</a><br> All downstream analyses in <a href="https://github.com/pjhop/dnamarray_crossreactivity/blob/master/analysis/c9_analysis.Rmd">c9_analysis.Rmd</a> and in<a href="https://github.com/pjhop/dnamarray_crossreactivity/blob/master/analysis/supplementary_note.Rmd"> supplementary_note.Rmd</a> can be reproduced using the deposited data as follows:</p> <ul> <li>Clone the dnamarray_crossreactivity repository: < git clone https://github.com/pjhop/dnamarray_crossreactivity.git ></li> <li>Download the data ('data.zip') and place it in the 'dnamarray_crossreactivity' folder.</li> <li>Unzip the data.zip folder</li> </ul> <p>Scripts used to generate the data in each subdirectory can be found at:</p> <ul> <li>data/processed/c9_matches/: <a href="https://github.com/pjhop/dnamarray_crossreactivity/tree/master/analysis/c9_matches">https://github.com/pjhop/dnamarray_crossreactivity/tree/master/analysis/c9_matches</a></li> <li>data/output/ewas/: <a href="https://github.com/pjhop/dnamarray_crossreactivity/tree/master/analysis/ewas">https://github.com/pjhop/dnamarray_crossreactivity/tree/master/analysis/ewas</a></li> <li>data/output/figs/: empty folder, running 'c9_analysis.Rmd' will save figures here.</li> <li>data/misc/: <a href="https://github.com/pjhop/dnamarray_crossreactivity/tree/master/analysis/other">https://github.com/pjhop/dnamarray_crossreactivity/tree/master/analysis/other</a></li> <li>data/extdata: <ul> <li>Zhou <em>et al.</em> annotations (EPIC.hg19.manifest.tsv.gz, HM450.hg19.manifest.pop.tsv.gz, HM450.hg19.manifest.tsv.gz) were downloaded from: <a href="https://zwdzwd.github.io/InfiniumAnnotation">https://zwdzwd.github.io/InfiniumAnnotation</a> (downloaded at 17/09/2020)</li> <li>Naeem <em>et al.</em><em> </em>data (12864_2013_7006_MOESM2_ESM.csv) was downloaded from: <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3943510/">https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3943510/</a></li> <li>Chen <em>et al.</em> data (48639-non-specific-probes-Illumina450k.xlsx) was downloaded from <a href="https://github.com/Jfortin1/funnorm_repro/blob/master/bad_probes/48639-non-specific-probes-Illumina450k.xlsx">https://github.com/Jfortin1/funnorm_repro/blob/master/bad_probes/48639-non-specific-probes-Illumina450k.xlsx</a></li> <li>The anno_450k.txt.gz and anno_EPIC.txt.gz are subsets of the annotation files included in the following package respectively: <a href="https://bioconductor.org/packages/release/data/annotation/html/IlluminaHumanMethylation450kanno.ilmn12.hg19.html">https://bioconductor.org/packages/release/data/annotation/html/IlluminaHumanMethylation450kanno.ilmn12.hg19.html</a> and <a href="https://bioconductor.org/packages/release/data/annotation/html/IlluminaHumanMethylationEPICanno.ilm10b2.hg19.html">https://bioconductor.org/packages/release/data/annotation/html/IlluminaHumanMethylationEPICanno.ilm10b2.hg19.html</a></li> </ul> </li> <li> data/genome_bs: Scripts used to generate these data can be found at <a href="https://github.com/pjhop/DNAmCrosshyb/blob/master/data-raw/bisulfite_convert_hg19.R">https://github.com/pjhop/DNAmCrosshyb/blob/master/data-raw/bisulfite_convert_hg19.R</a> and <a href="https://github.com/pjhop/DNAmCrosshyb/blob/master/data-raw/bisulfite_convert_hg38.R">https://github.com/pjhop/DNAmCrosshyb/blob/master/data-raw/bisulfite_convert_hg38.R</a> .</li> <li> data/raw: Individual-level data is available upon access at: <a href="https://ega-archive.org/studies/EGAS00001004587">https://ega-archive.org/studies/EGAS00001004587</a></li> </ul>
Alternative architecture of the E. coli chemosensory array.
<p>We present molecular models for extended patches of the <em>E. coli</em> chemosensory array. The models display either the canonical p6-symmetric architecture or an alternative p2-symmetric architecture recently observed in <em>E. coli</em> minicells. For more information, please see the associated BioRxiv preprint. Questions regarding the coordinates may be directed to Keith Cassidy (keith.cassidy@bioch.ox.ac.uk).</p> <p> </p>
Data for "How Array Design Creates SNP Ascertainement Bias"
<p>The repository contains the raw SNP data in vcf format for the publication "How Array Design Creates SNP Ascertainment Bias". Note that the variants are <strong>not</strong> filtered at this timepoint. Samples starting with pl_ are pooled sequences of ~10 individuals while samples starting with i_ were individually sequenced. Please find detailed information about samples, raw sequencing data and SNP calling pipeline in the linked preprint (<a href="https://doi.org/10.1101/833541">https://doi.org/10.1101/833541</a>)/ publication (<a href="https://doi.org/10.1371/journal.pone.0245178">https://doi.org/10.1371/journal.pone.0245178</a>). In case you need additional information, please contact<a href="mailto:johannes.geibel@uni-goettingen.de"> johannes.geibel@uni-goettingen.de</a></p>
Genotyping of the Chinese Spring x Renan mapping population with the TaBW280K SNP array
<p>The TaBW280K SNP array (Rimbert et al., PLoS ONE 2018) was used to genotype 430 Single Seed Descent (SSD) individuals<br> derived from a cross between Chinese Spring and Renan (CsRe; Choulet et al., Science 2014). Out of the 280,226 probesets, 85,276 were found to be polymorphic between the two parental lines and PHR on the population. Eventually, 83,721 (98.2%) SNPs were genetically mapped in 21 linkage groups corresponding to the 21 chromosomes of bread wheat, with no unlinked markers. This file contains the genotyping data of the 430 SSD lines.<br> </p>
Head-related impulse responses of a loudspeaker array
<p>Head-related impulse responses measured with a KEMAR dummy head of a loudspeaker array consisting of 13 loudspeakers. The dummy head was placed at three different positions, which allows to combine the measurements to an loudspeaker array consisting of 35 loudspeakers.</p> <p>The measurement equipment was exactly the same as in http://dx.doi.org/10.5281/zenodo.55418</p>
Binaural room impulse responses recorded with KEMAR of a 19-channel linear loudspeaker array
<p>BRIRs for 19 different loudspeakers placed in room Calypso at the Telefunken-building of TU Berlin were measured. The room is a studio listening room. The 19 loudspeakers constituted a linear loudspeaker array with a inter-loudspeaker distance of roughly 15cm. The measurement was done with the KEMAR (type 45BA) with the corresponding large ears (type KB0065 and KB0066) and Fostex PM0.4 loudspeakers. The dummy head was rotated from −90° to 90° in 1° steps. The measurement was repeated with the head wearing AKG K601 open headphones.</p>
Auralization of virtual microphone array sensors considering coherence loss by atmospheric turbulence for two moving monopole sources
Open the record for dataset details and reuse information.
Dataset related to publication: Robust radiative cooling via surface phonon coupling-enhanced emissivity from SiO2 micropillar arrays
<p>Dataset related to the publication:</p><p>Zhenmin Ding, Xin Li, Hulin Zhang, Dukang Yan, Jérémy Werlé, Ying Song, Lorenzo Pattelli, Jiupeng Zhao, Hongbo Xu, Yao Li. Robust radiative cooling via surface phonon coupling-enhanced emissivity from SiO2 micropillar arrays. <i>International Journal of Heat and Mass Transfer</i>, 220, 125004 (2024). doi: <a href="https://doi.org/10.1016/j.ijheatmasstransfer.2023.125004">10.1016/j.ijheatmasstransfer.2023.125004</a></p><p>The repository contains MATLAB/Octave scripts to perform rigorous coupled-wave analysis (RCWA) simulations for a SiO2 layer decorated with micropillars.</p><p>The main script runs a series of rigorous electromagnetic simulations over the atmospheric transparency window wavelength range (8-13 µm) for all combination of three main structural parameters (pillar diameter, spacing and height), within a user-defined range.</p><p>Running the code requires the RETICOLO v9 RCWA code:</p><blockquote><p>Jean-Paul Hugonin, & Philippe Lalanne. (2021). Light-in-complex-nanostructures/RETICOLO: V9. Zenodo. <a href="https://doi.org/10.5281/zenodo.4419063">https://doi.org/10.5281/zenodo.4419063</a></p></blockquote>
Dataset underlying the manuscript: MAViS: Modular Autonomous Virtualization System for Two-Dimensional Semiconductor Quantum Dot Arrays
<p>Datasets underlying the manuscript. Information on how to run the scripts is detailed in the README file.</p>
INFORE22 Acoustic data from SLim Towed Array (SLiTA)
<p>Acoustic data stem from hydrophone array SLiTA (SLim Towed Array [*]) towed by marine robots during INFORE22 experiments on 28<sup>th</sup> February and 1<sup>st</sup> March 2022. Two series of acquisitions are shared, one for each OEX.</p> <p>Data have been generated during the INFORE22 sea trial, run by CMRE from 21st February to 1st March 2022 in the Gulf of La Spezia to experiment and validate the CMRE hybrid robotic network in support of the INFORE maritime use case [**]. See also https://zenodo.org/record/637272</p> <p>Acoustic data are shared in binary format (.dat), and are complemented by Matlab scripts (.m) and header textual descriptors (sliva-header-specification.2.x0.txt). </p> <p>The archive (ACOUSTIC.zip) is split in multiple (60) files of 650MB each, which can me joined/combined with archive software (e.g., 7zip). </p> <p>For a full description of the dataset, see [***]</p> <p><strong>Conditions for use and distributions</strong></p> <p>This dataset is provided by NATO STO CMRE within the condition stated in the H2020 INFORE Grant and Consortium Agreement (GA. no. 825070) . The creation of derived products, as well the use in scientific publications must be pre-approved by CMRE and acknowledged. </p> <p><strong>Non liability clause</strong></p> <p>These data and software are provided in the scope of INFORE by NATO STO CMRE, in compliance with the INFORE open data strategy. Data and software are provided as they are. NATO and NATO STO CMRE decline any responsibility for bugs and any damage or accidental issue that the use of those data and software could cause. </p> <p><strong>References</strong></p> <p>[*] Alain Maguer, Rodney Dymond, Piero Guerrini, Luigi Troiano, Vittorio Grandi, Alberto Figoli, Claudio Olivero, Alessandro Sapienza, Stefano Fioravanti, John Potter Receiving and transmitting acoustic systems for AUV/gliders. Proceedings of the 3rd International Conference and Exhibition on Underwater Acoustic Measurements: Technologies and Results, 21-26 June, 2009, Nafplion, Greece. </p> <p>[**] Gabriele Ferri, Raffaele Grasso, Elena Camossi, Francesca de Rosa, Alessandro Faggiani, Kevin LePage, Konstantina Bereta, Marios Vodas, Dimitris Kladis, Antonis Kontaxakis, Nikos Giatrakos, Antonios Deligiannakis, Maritime Use Case: Final Evaluation Report Work Package 3 Tasks 3.3 INFORE Deliverable D3.3</p> <p>[***] Nikos Giatrakos, Antonios Deligiannakis, Arnau Montagud, Miguel Ponce de León, Thaleia Ntiniakou, Holger Arndt, Stefan Burkard, Konstantina Bereta, Marios Vodas, Dimitris Kladis, Raffaele Grasso, Gabriele Ferri, Arjan Vermeij, Alessandro Faggiani, Elena Camossi, Kevin Le Page: Data Management Plan V3 Work Package 8 Task 8.3 INFORE Deliverable 8.6</p> <p> </p> <p> </p> <p> </p>
Experimental testing of 2D Optical Phased Array (OPA) performance
<p>Radiation pattern of single element antenna in PolyBoard platform (with 0.1- and 0.5-degrees resolution)</p>
ASTRI Mini-Array Instrument Response Functions (Prod2, v1.0)
<p><strong>Aim:</strong></p> <p>This data repository provides access to a set of Instrument Response Functions (IRFs) of the ASTRI Mini-Array, saved in a FITS data file. The IRFs can be used as input to science analysis tools for high-level scientific analysis purposes.</p> <p><strong>Citations:</strong></p> <p>In the case the present ASTRI Mini-Array Instrument Response Functions (IRFs) are used in a research project, we kindly ask to add the following acknowledgement in any resulting publication:</p> <p>"This research has made use of the ASTRI Mini-Array Instrument Response Functions (IRFs) provided by the ASTRI Project [citation]."</p> <p>Please use the following BibTex Entry for [citation] in the reference section of your publication: <a href="https://zenodo.org/record/6827882/export/hx">https://zenodo.org/record/6827882/export/hx</a></p> <p><strong>Instrument:</strong></p> <p>The ASTRI Mini-Array is an international project led by the Italian National Institute for Astrophysics (INAF) to build and operate an array of nine 4-m class Imaging Atmospheric Cherenkov Telescopes (IACTs) at the <em>Observatorio del Teide</em> (Tenerife, Spain) [1]. The telescopes are an evolution of the dual-mirror ASTRI-Horn telescope, successfully installed and tested since 2014 at the INAF “M.C. Fracastoro” observing station in Serra La Nave (Mt. Etna, Italy) [2][3].</p> <p>The ASTRI Mini-Array is designed to perform deep observations of the galactic and extragalactic gamma-ray sky in the TeV and multi-TeV energy band, with a differential sensitivity that surpass the one of current Cherenkov telescope facilities above a few TeV, extending the energy band well above hundreds of TeV [4].</p> <p>The main science goals of the ASTRI Mini-Array in the very high-energy (VHE) gamma-ray band encompass both galactic and extragalactic science [5][6][7]. Important synergies with other ground-based gamma-ray facilities in the Northern Hemisphere and space-borne telescopes are foreseen.</p> <p><strong>Monte Carlo Simulations:</strong></p> <p>The IRFs of the ASTRI Mini-Array were obtained from a dedicated Monte Carlo (MC) production (dubbed ASTRI Mini-Array Prod2, version 1.0). Air showers initiated by gamma rays, protons and electrons were simulated using the CORSIKA package [8] (version 6.99), while the response of the array telescopes was simulated using the sim_telarray package [9] (version 2018-11-07).</p> <p>The layout of the ASTRI Mini-Array telescopes considered in the MC simulations is based on the actual telescope positions at the Teide Observatory site (28.30°N, 16.51°W, 2390 m a.s.l.). The nominal telescope pointing configuration, in which all telescopes point to the same sky position, was assumed in all MC simulations. Air showers produced by the primaries were simulated as coming from a zenith angle of 20° and an azimuth angle of 0° and 180° (corresponding to telescope pointing directions toward the geomagnetic North and South, respectively). Although not-negligible differences in performance (on the order of ≤15% at a zenith angle of 20°) are found between the two azimuthal pointing directions, the final IRFs were obtained by averaging between the two directions. Finally, all MC simulations were generated with a night sky background (NSB) level corresponding to dark sky conditions at the Teide Observatory site.</p> <p><strong>Monte Carlo data reduction and analysis:</strong></p> <p>The MC simulations were reduced and analysed with A-SciSoft [10][11] (version 0.3.1), the scientific software package of the ASTRI Project. The calibration and reconstruction of the MC events were achieved with the standard methods implemented in the data reduction pipeline (see [10][11] for more details). In particular, the background rejection and energy reconstruction were achieved with a procedure based on the Random Forest method [12], while the arrival direction of each shower was estimated from a weighted intersection of the major axes of the images from different telescopes. After the full reconstruction of the MC events, the background (proton and electron) events were re-weighted according to recent experimental measurements of their spectra, while gamma-ray events with a power-law gamma-ray spectrum with a photon index of 2.62. This approach follows a similar procedure adopted in [13].</p> <p>The final analysis cuts were based on the background rejection, shower arrival direction, and event multiplicity parameters. They were defined, in each considered energy bin and off-axis bin, by optimising the flux sensitivity for 50 hr exposure time. Then, five standard deviations (5σ, with σ defined as in Eq. 17 of [14]) were required for a detection in each energy bin and off-axis bin, considering the same exposure time (as in the cut optimization procedure) and a ratio of the off-source to on-source exposure equal to 5. In addition, the signal excess was required to be larger than 10 and at least 5 times the expected systematic uncertainty in the background estimation (assumed to be ∼1%). It should be noted that these analysis cuts, based on the best flux sensitivity, do not provide the best angular and energy resolution achievable by the system. Other analysis cuts, which take into account both differential flux sensitivity and angular/energy resolution in the cut optimization process, may actually provide better performance [4].</p> <p><strong>Instrument Response Functions (IRFs):</strong></p> <p>The IRFs are saved in a FITS data file [15] which contains the following quantities (FITS tables): effective collection area ("EFFECTIVE AREA" table), angular resolution ("POINT SPREAD FUNCTION" table), energy resolution ("ENERGY DISPERSION" table), and residual background rate ("BACKGROUND" table). These quantities are provided as a function of the energy and the off-axis. The energy bins are logarithmic and range between 10<sup>-0.7 </sup>~ 0.2 TeV and 10<sup>2.5 </sup>~ 316 TeV. Five energy bins per decade are used for the angular resolution and residual background rate, while ten energy bins per decade for the effective collection area. In the case of energy resolution, the energy migration matrix is provided with a much finer energy binning. The off-axis bins are linearly spaced between 0° and 6°, with a bin width equal to 1°. In the case of the residual background rate, a 2-dimensional squared spatial binning is used, which ranges between 0° and 6° with a bin width equal to 0.2° in each direction.</p> <p>The IRFs can be used as input to science analysis tools and, in particular, are compliant with the input/output (I/O) data format requested by the science analysis tools Gammapy [16] and ctools [17].</p> <p><strong>Dataset:</strong></p> <p>The dataset consists of one file: "astri_100_43_008_0502_C0_20_AVERAGE_50h_SC_v1.0.lv3.fits".</p> <p>The naming convention is: astri_[ARRAY_ID]_[ORIG_ID]_[REL_ID]_[PACKET_TYPE]_[CLASS_CUT]_[ZENITH]_[AZIMUTH]_[ EXPOSURE_TIME]_[AIM]_[VERSION].lv3.fits</p> <p>where:</p> <ul> <li>[ARRAY_ID] = 100 (100 = ASTRI Mini-Array with 9 telescopes)</li> <li>[ORIG_ID] = 43 (4 = INAF-OAR; 3 = AIV/AIT MC simulations)</li> <li>[REL_ID] = 008 (008 = MC prod2, v1.0)</li> <li>[PACKET_TYPE] = 0502 (0502 = IRF3)</li> <li>[CLASS_CUT] = C0 (C0 = cuts based on sensitivity maximisation)</li> <li>[ZENITH] = 20 [deg]</li> <li>[AZIMUTH] = AVERAGE [deg]</li> <li>[EXPOSURE_TIME] = 50h</li> <li>[AIM] = SC (SC = SCience)</li> <li>[VERSION]= v1.0</li> </ul> <p><strong>Acknowledgments:</strong></p> <p>This work was conducted in the context of the ASTRI Project thanks to the support of the Italian Ministry of University and Research (MUR) as well as the Ministry for Economic Development (MISE) with funds specifically assigned to the Italian National Institute of Astrophysics (INAF). We acknowledge support from the Brazilian Funding Agency FAPESP (Grant 2013/10559-5) and from the South African Department of Science and Technology through Funding Agreement 0227/2014 for the South African Gamma-Ray Astronomy Programme. The Instituto de Astrofisica de Canarias (IAC) is supported by the Spanish Ministry of Science and Innovation (MICIU). This work has also been partially supported by H2020-ASTERICS, a project funded by the European Commission Framework Programme Horizon 2020 Research and Innovation action under grant agreement n. 653477. This work has gone through the internal ASTRI review process.</p> <p>We would also like to thank the computing centres that provided resources for the generation of the Monte Carlo (MC) simulations used to produce the ASTRI Mini-Array Instrument Response Functions (IRFs) released in this work:</p> <ul> <li>CAMK, Nicolaus Copernicus Astronomical Center, Warsaw, Poland</li> <li>CIEMAT-LCG2, CIEMAT, Madrid, Spain</li> <li>CYFRONET-LCG2, ACC CYFRONET AGH, Cracow, Poland</li> <li>DESY-ZN, Deutsches Elektronen-Synchrotron, Standort Zeuthen, Germany</li> <li>GRIF, Grille de Recherche d’Ile de France, Paris, France</li> <li>IN2P3-CC, Centre de Calcul de l’IN2P3, Villeurbanne, France</li> <li>IN2P3-CPPM, Centre de Physique des Particules de Marseille, Marseille, France</li> <li>IN2P3-LAPP, Laboratoire d'Annecy de Physique des Particules, Annecy, France</li> <li>INFN-FRASCATI, INFN Frascati, Frascati, Italy</li> <li>INFN-T1, CNAF INFN, Bologna, Italy</li> <li>INFN-TORINO, INFN Torino, Torino, Italy</li> <li>MPIK, Heidelberg, Germany</li> <li>OBSPM, Observatoire de Paris Meudon, Paris, France</li> <li>PIC, port d’informacio cientifica, Bellaterra, Spain</li> <li>prague_cesnet_lcg2, CESNET, Prague, Czech Republic</li> <li>praguelcg2, FZU Prague, Prague, Czech Republic</li> <li>UKI-NORTHGRID-LANCS-HEP, Lancaster University, United Kingdom</li> </ul> <p><strong>References:</strong></p> <ol> <li>Scuderi, S. et al., "The ASTRI Mini-Array of Cherenkov telescopes at the Observatorio del Teide", Journal of High Energy Astrophysics 35, 52–68 (2022).</li> <li>Giro, E. et al., "First optical validation of a Schwarzschild Couder telescope: the ASTRI SST-2M Cherenkov telescope", A&A 608, A86 (Sept. 2017).</li> <li>Lombardi, S. et al., "First detection of the Crab Nebula at TeV energies with a Cherenkov telescope in a dual-mirror Schwarzschild-Couder configuration: the ASTRI-Horn telescope", A&A 634, A22 (Feb. 2020).</li> <li>Lombardi, S. et al., "Performance of the ASTRI Mini-Array at the Observatorio del Teide", in [37th International Cosmic Ray Conference. 12-23 July 2021. Berlin], 884 (Mar. 2022).</li> <li>Vercellone, S. et al., "ASTRI Mini-Array core science at the Observatorio del Teide", Journal of High Energy Astrophysics 35, 1–42 (2022).</li> <li>D’Aì, A. et al., "Galactic Observatory Science with the ASTRI Mini-Array at the Observatorio del Teide", Journal of High Energy Astrophysics 35, 139–175 (2022).</li> <li>Saturni, F. et al., "Extragalactic Observatory Science with the ASTRI Mini-Array at the Observatorio del Teide", Journal of High Energy Astrophysics 35, 91–111 (2022).</li> <li>Heck, D. et al., [CORSIKA: a Monte Carlo code to simulate extensive air showers.], Report FZKA 6019 (1998).</li> <li>Bernlöhr, K., "Simulation of imaging atmospheric Cherenkov telescopes with CORSIKA and sim_telarray", Astropart. Phys. 30, 149–158 (Oct. 2008).</li> <li>Lombardi, S. et al., "ASTRI SST-2M prototype and mini-array data reconstruction and scientific analysis software in the framework of the Cherenkov Telescope Array", in [Software and Cyberinfrastructure for Astronomy IV], Chiozzi, G. and Guzman, J. C., eds., Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series 9913, 991315 (July 2016).</li> <li>Lombardi, S. et al., "ASTRI data reduction software in the framework of the Cherenkov Telescope Array", in [Software and Cyberinfrastructure for Astronomy V], Guzman, J. C. and Ibsen, J., eds., Society of Photo- Optical Instrumentation Engineers (SPIE) Conference Series 10707, 107070R (July 2018).</li> <li>Breiman, L., "Random Forests", Machine Learning 45, 5–32 (Jan. 2001).</li> <li>Cherenkov Telescope Array Observatory, & Cherenkov Telescope Array Consortium. (2021). CTAO Instrument Response Functions - prod5 version v0.1 (v0.1) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.5499840</li> <li>Li, T.-P. and Ma, Y.-Q., "Analysis methods for results in gamma-ray astronomy", ApJ, 272, 317 (1983)</li> <li>Pence, W. D. et al., "Definition of the Flexible Image Transport System (FITS), version 3.0", A&A 524, A42 (Dec. 2010).</li> <li>Deil, C. et al., "Gammapy - A prototype for the CTA science tools", in [35th International Cosmic Ray Conference (ICRC2017)], International Cosmic Ray Conference 301, 766 (Jan. 2017).</li> <li>Knödlseder, J. et al., "GammaLib and ctools. A software framework for the analysis of astronomical gamma- ray data", A&A 593, A1 (Aug. 2016).</li> </ol>
Earthquake Catalogues for DWARFS (Dense Westland Arrays Researching Fault Segmentation)
<p>This dataset contains earthquake hypocentral information catalogued as part of the DWARFS (Dense Westland Arrays Researching Fault Segmentation) broadband seismometer networks along New Zealand's Alpine Fault, between April 2019-April 2020.</p> <p>'Preferred Lat/Lon/Depth' refers to origin determined by method under 'Method'. HypoDD is the preferred method, but some origins could not be relocated and so we present the NonLinLoc derived origin instead. All magnitudes are Local magnitudes calculated using displacements on the vertical channel (MLv). All times are in UTC time. </p> <p>This dataset accompanies a publication recently submitted (July 2022) to the AGU journal 'Journal of Geophysical Research: Solid Earth' entitled 'Heterogeneity in microseismicity and stress near rupture-limiting section boundaries along the late interseismic Alpine Fault'. </p>
Reference site conditions for floating wind arrays: dataset of reference sites
<h1>IEA Task 49: Integrated Design of Floating Wind Arrays</h1> <h3>This dataset contains atmospheric and oceanographic data of 11 locations around the globe of future floating offshore wind farms.<br>Each dataset was used to perform a metocean analysis for preliminary design, published in the Work Package 1 Report of IEA Task 49.</h3> <div> <div> <div><a name="_msocom_1"></a></div> </div> </div> <table> <tbody> <tr> <td><strong>4COffshore ID</strong></td> <td><strong>Name</strong></td> <td><strong>Latitude [deg]</strong></td> <td><strong>Longitude [deg]</strong></td> <td><strong>Water Depth [m] (GEBCO)</strong></td> <td><strong>Distance from shore [m]</strong></td> <td><strong>Country</strong></td> <td><strong>Dataset curated by</strong></td> </tr> <tr> <td>IT95 </td> <td>Hannibal </td> <td> <div>37.842</div> </td> <td> <div>12.0722</div> </td> <td> <div> -353</div> </td> <td> <div> 35</div> </td> <td>Italy </td> <td>RSE</td> </tr> <tr> <td>US0W </td> <td> Humboldt</td> <td> <div> 40.928</div> </td> <td> <div>-124.708</div> </td> <td> <div> -707</div> </td> <td> <div> 43.8</div> </td> <td>USA</td> <td>NREL</td> </tr> <tr> <td>KR0R </td> <td>Ulsan </td> <td> <div> 35.449</div> </td> <td> <div> 129.949</div> </td> <td> <div> -188</div> </td> <td> <div> 32</div> </td> <td>South Korea </td> <td>UOU</td> </tr> <tr> <td>IE34 </td> <td>Moneypoint One</td> <td> <div> 52.519</div> </td> <td> <div>-10.276</div> </td> <td> <div> -1<a>02</a> </div> </td> <td> <div> 23.4</div> </td> <td>Ireland </td> <td>GDG</td> </tr> <tr> <td>UK6L </td> <td>Havbredey </td> <td> <div>58.862</div> </td> <td> <div> <div> <p>-5.54</p> </div> </div> </td> <td> <div> <div> <p> -91</p> </div> </div> </td> <td> <div> <div> <p> 41.6</p> </div> </div> </td> <td>Scotland </td> <td>DHI</td> </tr> <tr> <td>JP06 </td> <td>Fukushima</td> <td> <div>37.311</div> </td> <td> <div>141.251</div> </td> <td> <div> -90</div> </td> <td> <div> 19.4</div> </td> <td>Japan </td> <td>AIT</td> </tr> <tr> <td>NO44 </td> <td>Utsira nord<strong>*</strong></td> <td> <div>59.276</div> </td> <td> <div>4.541</div> </td> <td> <div> -273</div> </td> <td> <div> 42.4</div> </td> <td>Norway </td> <td>4subsea / UiS,UiB*</td> </tr> <tr> <td>USZ3 </td> <td>Gulf of Maine</td> <td> <div>43.25</div> </td> <td> <div>-69.5</div> </td> <td> <div> -148</div> </td> <td> <div> 138</div> </td> <td>USA </td> <td>NREL</td> </tr> <tr> <td>KR88 </td> <td>Geomundo<strong>**</strong></td> <td> <div>34.039</div> </td> <td> <div>126.901</div> </td> <td> <div> -70</div> </td> <td> <div> 47</div> </td> <td>South Korea </td> <td>IAE**</td> </tr> <tr> <td>FR87 </td> <td>Sud de la Bretagne II</td> <td> <div>47.325</div> </td> <td> <div>-3.659</div> </td> <td> <div> -94</div> </td> <td> <div> 30.7</div> </td> <td>France </td> <td>UiB</td> </tr> <tr> <td>NO66</td> <td>Sørlige Nordsjø II<strong>***</strong></td> <td> <div> 56.78 </div> </td> <td> <div> 4.92 </div> </td> <td> <div> -60</div> </td> <td> <div> 180</div> </td> <td>Norway</td> <td>4subsea / UiS,UiB***</td> </tr> </tbody> </table> <p>* Suplementary dataset published at: https://doi.org/10.5281/zenodo.10048048</p> <p>** Dataset is confidential, for details of usage reach out to the contact person.</p> <p>*** Suplementary dataset published at: https://doi.org/10.5281/zenodo.7057407</p>
Dataset for the manuscript "Collective spin waves in RKKY interlayer-coupled Ni80Fe20/Ru/ Ni80Fe20 nanowire arrays"
<p>These are the dataset relative to paper entitled "<strong><span>Collective spin waves in RKKY interlayer-coupled </span></strong><strong><span>Ni</span></strong><strong><sub><span>80</span></sub></strong><strong><span>Fe</span></strong><strong><sub><span>20</span></sub></strong><strong><span>/Ru/</span></strong><strong><span> </span></strong><strong><span>Ni</span></strong><strong><sub><span>80</span></sub></strong><strong><span>Fe</span></strong><strong><sub><span>20 </span></sub></strong><strong><span>nanowire arrays</span></strong><strong>"</strong></p>
Supporting data for "A 2x2 quantum dot array with controllable inter-dot tunnel couplings"
<p>Supporting data and analysis scripts for all figures in in "A 2x2 quantum dot array with controllable inter-dot tunnel couplings", arXiv:1802.05446 (preprint)</p> <p>This dataset contains a readme file, a data file in hdf5 format containing all the relevant datasets, and a python script file that can be used to access, analyse and plot the datasets in the data file, reproducing the plots in the figures presented in the manuscript.</p>
3D Microphone Array Recording Comparison (3D-MARCo)
<p>3D-MARCo is an open-access database of 3D sound recordings of musical performances and room impulse responses. The recordings were made in the St. Paul’s concert hall in Huddersfield, UK using a total of 71 microphones simultaneously. The main microphone arrays included in the database comprise PCMA-3D, OCT-3D, 2L-Cube, Decca Cubioid, First-order Ambisonics (FOA), Higher-order Ambisonics (HOA) and Hamasaki Square with height. In addition, ORTF, side/height, Voice of God and floor channels as well as a dummy head and spot microphones are included. The sound sources recorded are string quartet, piano trio, piano solo, organ, a cappella group, various single sources and room impulse responses of a virtual ensemble with 13 source positions captured by all of the microphones. 3D-MARCo would be useful for spatial audio research, recording education, critical ear training, etc.</p>
5405 MHz SigMF baseband recording of RCM-2 (Radarsat Constellation) using PlutoPlus SDR and four log periodic array (LPA) antennas
<p>This dataset contains a recording of the <a href="https://www.asc-csa.gc.ca/eng/satellites/radarsat/technical-features/radarsat-comparison.asp">RCM-2</a> (<a href="https://en.wikipedia.org/wiki/RADARSAT_Constellation">Radarsat Constellation</a>) satellite as it passed over Berkeley, California. The recording was made on 2024-08-13 and is about 15 seconds long, containing acquisition of signal pulses and loss of signal at the tail end of the recording. The dataset is stored in SigMF format. The data files are compressed with xz to reduce their size. The IQ sample rate is 20.0 Msps and the center frequency is 5405 MHz.</p> <p>The linear antenna array used to record contained four HT5 antennas, labeled as: "HT5 antenna UWB log-periodic antenna 1300MHz-10GHz". These four antennas were spaced 21 cm apart. The input from these four antennas was combined with a SP-TX-4B splitter/combiner using equal lengths of LMR400 coax, then amplified using an LNA labeled as "RF AMP 04A: TQP3M9037 0.1-6GHz". The LNA was powered via a +5 volt bias-tee. A "Pluto+" or Pluto Plus SDR was used to sample, with SatDump software. </p> <p> </p>
Dataset of the article Optical Tweezer Arrays of Erbium Atoms
<p>Datasets of the experimental data of the article Optical Tweezer Arrays of Erbium Atoms. The dataset is organized in folders, one for each figure. The data is written as tables in text files and it includes theoretical curves and fits of the same figure. A Python script is included to reproduce the figures.</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.