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814 results for “radio”
Large-Scale Dataset for Radio Frequency based Device-Free Crowd Estimation
<p>This dataset serves to estimate the status, in particular the size, of a crowd given the impact on radio frequency communication links within a wireless sensor network. To quantify this relation, signal strengths across sub-GHz communication links are collected at the premises of the Tomorrowland music festival. The communication links are formed between the network nodes of wireless sensor networks deployed in three of the festival's stage environments. </p> <p>The table below lists the eighteen dataset files. They are collected at the music festival's 2017 and 2018 editions. There are three environments, labeled: ‘Freedom Stage 2017’, ‘Freedom Stage 2018’, and ‘Main Comfort 2018’. Each environment has both 433 MHz and 868 MHz data. The measurements at each environment were collected over a period of three festival days. The dataset files are formatted as Comma-Separated Values (CSV).</p> <pre><code class="language-markdown">| Dataset file | Reference file | Number of messages | |-------------------- |------------------------- |-------------------- | | free17_433_fri.csv | None | 393 852 | | free17_868_fri.csv | None | 472 202 | | free17_433_sat.csv | free17_transactions.csv | 996 033 | | free17_868_sat.csv | free17_transactions.csv | 1 023 059 | | free17_433_sun.csv | free17_transactions.csv | 1 007 066 | | free17_868_sun.csv | free17_transactions.csv | 1 036 456 | | free18_433_fri.csv | None | 765 024 | | free18_868_fri.csv | None | 757 657 | | free18_433_sat.csv | free18_transactions.csv | 711 438 | | free18_868_sat.csv | free18_transactions.csv | 714 390 | | free18_433_sun.csv | free18_transactions.csv | 648 329 | | free18_868_sun.csv | free18_transactions.csv | 656 290 | | main18_433_fri.csv | None | 791 462 | | main18_868_fri.csv | None | 908 407 | | main18_433_sat.csv | main18_counts.csv | 863 666 | | main18_868_sat.csv | main18_counts.csv | 884 682 | | main18_433_sun.csv | main18_counts.csv | 903 862 | | main18_868_sun.csv | main18_counts.csv | 894 496 |</code></pre> <p>In addition to the datasets and reference files, a software example is provided to illustrate the data use and visualise the initial findings and relation between crowd size and network signal strength impact.</p> <p>In order to use the software, please retain the following file structure: </p> <pre><code class="language-markdown">. ├── data ├── data_reference ├── graphs └── software</code></pre> <p>The peer-reviewed data descriptor for this dataset has now been published in MDPI Data - an open access journal aiming at enhancing data transparency and reusability, and can be accessed here: <a href="https://doi.org/10.3390/data5020052">https://doi.org/10.3390/data5020052</a>.<br> Please cite this when using the dataset.</p>
Compact continuum source finding for next generation radio surveys
<p>This is a data set that accompanies the paper "Compact continuum source finding for next generation radio surveys" (2012MNRAS.422.1812H)</p> <p>The image files and source catalogues contained here were used to test the completeness and false detection rate of a number of source finding algorithms including: Aegean, Selavy, Sfind, SExtractor, and IMSAD. These data can be used to assess the performance of future source finding codes, and to verify the the performance of code during development.</p>
Processing of 3-D Polygon Mesh Model and Radio Propagation Simulations in a Cave: Surface Reconstruction from Point Cloud, Simplification of the Mesh, and Ray Tracing
<p><strong>ABOUT</strong></p><p>This repository includes mesh data from cave geometry scanning and processing, and radio propagation data from ray tracing simulations.</p><p>The geometry data is obtained with laser scanning in a cave in Slovenija. </p><p>The geometry processing includes (i) 3-D shape reconstruction - surface reconstruction from point cloud data and (ii) simplification - reduction of the geometric complexity of the 3-D mesh model. </p><p>The radio propagation data is obtained using CloudRT [1] ray-tracing simulator. </p><p>The obtained propagation-related quantities include information about the propagation mechanism, interactions with the geometry, received power, delay, azimuth and elevation angles of arrival and departure, and path loss. </p><p> </p><p><strong>AUTHORS</strong></p><p>Teodora Kocevska, Andrej Hrovat, Tomaž Javornik</p><p>Department of Communication Systems</p><p>Jožef Stefan Institute, SI-1000 Ljubljana, Slovenia</p><p>teodora.kocevska@ijs.si</p><p> </p><p><strong>GEOMETRY PROCESSING</strong></p><p>The cave segment used for the propagation calculations is selected from a point cloud obtained in a cave in Litia, Slovenia. The point cloud is obtained with 3-D laser scanning of the environment. The selected segment is approx. 58 m long. Several parameter configurations were considered for 3-D shape reconstruction, including Poisson surface reconstruction with octree depths of 8, 10, and 12. Geometries that represent the cave shape and have different levels of complexity were created and studied. In the simplification process, one and two-stage simplification was explored using the Quadric Edge Collapse Decimation approach. </p><p> </p><p><strong>RADIO SETUP</strong></p><p>The transmitter (Tx) is fixed at the entrance of the cave and the receiver (Rx) is moved along the cave in 40 positions with a step of 1 m.</p><p>Omnidirectional antennas at the Tx and Rx sites and vertical polarization are considered. The antenna is mounted 1.5 m above the ground.</p><p>The start frequency is 3.5 GHz, the end frequency is 3.6 GHz and the step is 10 MHz. Direct propagation and first-order reflection are considered. </p><p>The cave geometry is represented by a triangular mesh, and the material of the cave is wet earth. The material electromagnetic properties are selected according to the specifications presented in [2].</p><p> </p><p><strong>FOLDER STRUCTURE</strong></p><p>The folder structure is:</p><p> - Polygon_Mesh_Models</p><p> <i># 3-D environment models with varying </i>levels<i> of geometry complexity</i></p><p> - Reconstruction_Segmen1_Poisson_Surface_Reconstruction</p><p> - Simplification_Segment1_Quadric_Edge_Collapse_Decimation</p><p> - Propagation_Data</p><p> <i># Propagation quantities of all rays between a transmitter and receiver</i></p><p> - AllRay_PropData</p><p> - PathLoss</p><p> - readme.txt</p><p> - RayTracing_EnvironmentModel</p><p> <i> # Final environment model used for ray tracing simulations</i></p><p> - Cave_MeshModel.json</p><p> - Cave_MeshModel.skb</p><p> - Cave_MeshModel.skp</p><p> - RayTracing_MaterialProperties</p><p> <i># Properties of the materials in the environment</i></p><p> - materials.json</p><p> - materials.mtl</p><p> - readme.txt</p><p> - Cave_Length.txt</p><p> <i># Length between selected locations in the environment</i></p><p> - Cave_Segment1_visual.png</p><p> <i> # Visualization of the environment segment used for propagation calculation</i></p><p> - readme.txt</p><p> <i># Overall description </i></p><p><strong>REFERENCES</strong></p><p>[1] D. He, B. Ai, K. Guan, L. Wang, Z. Zhong, and T. Kürner, "The Design and Applications of High-Performance Ray-Tracing Simulation Platform for 5G and Beyond Wireless Communications: A Tutorial," in IEEE Communications Surveys & Tutorials, vol. 21, no. 1, pp. 10-27, First quarter 2019, doi: 10.1109/COMST.2018.2865724.</p><p>[2] R. sector of International Telecommunication Union (ITU-R), "Effects of building materials and structures on radio wave propagation above about 100 MHz," International Telecommunication Union, ITU-R Recommendation P.2040-2, 2021.</p><p> </p><p><strong>ACKNOWLEDGEMENT</strong></p><p>This work was supported by the Slovenian Research Agency under grant <strong>J2-3048</strong>.</p><p> </p>
Turnover of the Radio Broadcasting Industry in Europe
<p>Imputed and forecasted values of the radio broadcasting industry from the <a href="https://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=sbs_na_1a_se_r2&lang=en">Annual detailed enterprise statistics for services (NACE Rev. 2 H-N and S95)</a> Eurostat folder.</p> <p>We use backcasting, forecasting, approxmation, last observation carry forward and next observation carry backwards to impute missing values, and to create realistic forecasts up to three periods. </p> <p>Compared to the Eurostat raw data we added value with <br> Increased number of observations: 65%<br> Reduced missing values: -48.1%<br> Increased non-missing subset for regression or AI: +66.67%</p>
A NICER View of the Massive Pulsar PSR J0740+6620 Informed by Radio Timing and XMM-Newton Spectroscopy: Nested Samples for Millisecond Pulsar Parameter Estimation
<p>Posterior sample files associated with the preprint "A <em>NICER</em> View of the Massive Pulsar PSR J0740+6620 Informed by Radio-Timing and <em>XMM-Newton</em> Spectroscopy" by Riley et al. (2021; <a href="https://arxiv.org/abs/2105.06980">arXiv:2105.06980 [astro-ph.HE]</a>; submitted to ApJL).</p> <p>Also included are: the data products; the numeric model files including the telescope calibration products; model modules in the Python language using the X-PSI framework; and Jupyter analysis notebooks.</p> <p>Please refer to the README for detailed information.</p> <p> </p> <p> </p>
A multi-resolution, multi-epoch low Radio Frequency Survey of the Kepler K2 Mission Campaign 1 Field
<p>Data abstract:</p> <p>Contained within are the MWA images used as input data for this study. The production and analysis of these images are described in the linked paper. The final catalogues and light curves are available from VizieR (http://vizier.cfa.harvard.edu/viz-bin/VizieR?-source=J/AJ/152/82).</p> <p>Paper abstract:</p> <p>We present the first dedicated radio continuum survey of a Kepler K2 mission field, Field 1, covering the North Galactic Cap. The survey is wide field, contemporaneous, multi-epoch, and multi-resolution in nature and was conducted at low radio frequencies between 140 and 200 MHz. The multi-epoch and ultra wide field (but relatively low resolution) part of the survey was provided by 15 nights of observation using the Murchison Widefield Array (MWA) over a period of approximately a month, contemporaneous with K2 observations of the field. The multi-resolution aspect of the survey was provided by the low resolution (4‧) MWA imaging, complemented by non-contemporaneous but much higher resolution (20″) observations using the Giant Metrewave Radio Telescope (GMRT). The survey is, therefore, sensitive to the details of radio structures across a wide range of angular scales. Consistent with other recent low radio frequency surveys, no significant radio transients or variables were detected in the survey. The resulting source catalogs consist of 1085 and 1468 detections in the two MWA observation bands (centered at 154 and 185 MHz, respectively) and 7445 detections in the GMRT observation band (centered at 148 MHz), over 314 square degrees. The survey is presented as a significant resource for multi-wavelength investigations of the more than 21,000 target objects in the K2 field. We briefly examine our survey data against K2 target lists for dwarf star types (stellar types M and L) that have been known to produce radio flares.</p>
Simulated radio maps for CAESAR source finder testing
<p>A dataset of simulated astronomical radio maps (fits format, size 2500 x 2500) with both compact and extended sources that can be used to test automated source extraction algorithms. Maps were produced with the CASA tool as described in S Riggi et al, PASA (2019) to test CAESAR source finding performances. The dataset includes:</p> <p>- Simulated maps in FITS format ("recmap_vis-RUNXXX.fits")</p> <p>- List of generated sources in Caesar ROOT format ("sources-RUNXXX.root") and corresponding DS9 regions ("ds9regions-RUNXXX.reg")</p> <p>- List of generated sources (convolved by the clean beam) in Caesar ROOT format ("sources-RUNXXX_conv_rec.root") and corresponding DS9 regions ("ds9regions_sources-RUNXXX_conv.reg")</p>
HI line observations of 290 evolved stars made with the Nancay Radio Telescope - I. Data: online Tables
<p>--- Table B.1: Clear NRT HI detections - basic data </p> <p>Description of the columns:</p> <p>(1) Name: common catalogue name of the target. <br> An ^n after a name indicates that it is clearly not an AGB star, <br> a ^d that we consider its classification as an AGB to be dubious, <br> and a ^* indicates that notes on the object can be found in Appendix A;<br>(2,3) RA,DEC: literature right ascension and declination of the target from Gaia EDR 3, <br> for epoch J2000.0;<br>(4) Type: target type. <br> Primarily the variability type as listed in Version 5.1 of the General Catalogue of Variable Stars, <br> GCVS (A description of GCVS types is given in https://cdsarc.u-strasbg.fr/ftp/cats/B/gcvs/vartype.txt),<br> but if an object is not included in the GCVS, other identifiers are listed in brackets: <br> HPM = high proper motion star, (OH/IR) = OH/IR maser, LPVc = long-period variable candidate, <br> PN = planetary nebula, pPN = proto-planetary nebula, and post-AGB star;<br>(5,6) Spec & ref: spectral type of the star, followed by its literature reference, <br> as retrieved from the SIMBAD database. If none was listed there, the reference is noted as 'SIMBAD';<br>(7,8) Teff & ref: effective temperature of the star, in K, followed by its literature reference; <br>(9) d: distance of the target, based on its parallax (mainly from the Gaia EDR3), in pc.<br> If no Gaia parallax was available a reference to the distance we adopted is given in Appendix A<br> (for RAFGL 3099, mu Cep, and V Peg);<br>(10) Vlit: published radial velocity of the target in the LSR reference frame, in km/s;<br>(11) Vexp: literature expansion velocity measured from CO or OH 1612 MHz line observations, in km/s. <br> If a pair of values was published for a two-velocity component CO line fit, the largest value is listed here;<br>(12) ref: literature references to the published Vlit and Vexp values; <br>(13) line: spectral line on which the published radial velocity measurement (Vlit) was based;<br>(14,15) Mdot & ref: literature mass loss rates, in solar masses per year, <br> followed by its literature reference.</p> <p>Notes to Table B.1:</p> <p>References: see Table B.1 in the Astronomy & Astrophysics paper.</p> <p><br>--- Table B.2: Clear NRT HI detections - HI data </p> <p>Description of the columns:</p> <p>(1) Name: common catalogue name of the target. <br> A ^T after a name indicates that HI line parameters are based on a 'total' spectrum, whereas <br> a ^P indicates that a 'peak' spectrum was used. <br> An ^n indicates that it is clearly not an AGB star, <br> a ^d that we consider its classification as an AGB to be dubious, <br> and a ^* indicates that notes on the object can be found in Appendix A;<br>(2) VHI: our central radial velocity in the LSR reference frame of the Gaussian fitted <br> to the HI profile, in km/s.<br>(3) FWHM: our full width half maximum of the Gaussian fitted to the HI line profile, in km/s;<br>(4) Speak: our peak flux density of the HI line profile, in Jy;<br>(5) diam: our estimated angular size of the HI CSE in the east-west direction, in arcmin;<br>(6) FHI: our integrated line flux of the HI profile, in Jy km/s;<br>(7) MHI: our total HI mass, in Msun;<br>(8) HI ref: references to previously published HI studies,<br> see Table B.2 in the Astronomy & Astrophysics paper.</p> <p><br>--- Table B.3: Possible NRT HI detections - basic data</p> <p>Description of the columns:</p> <p>(1) Name: common catalogue name of the target. <br> An ^n after a name indicates that it is clearly not an AGB star, <br> a ^d that we consider its classification as an AGB to be dubious, <br> and a ^* indicates that notes on the object can be found in Appendix A;<br>(2,3) RA,DEC: literature right ascension and declination of the target from Gaia EDR 3, <br> for epoch J2000.0;<br>(4) Type: target type. <br> Primarily the variability type as listed in Version 5.1 of the General Catalogue of Variable Stars, <br> GCVS (A description of GCVS types is given in https://cdsarc.u-strasbg.fr/ftp/cats/B/gcvs/vartype.txt),<br> but if an object is not included in the GCVS, other identifiers are listed in brackets: <br> HPM = high proper motion star, (OH/IR) = OH/IR maser, LPVc = long-period variable candidate, <br> PN = planetary nebula, pPN = proto-planetary nebula, and post-AGB star;<br>(5,6) Spec & ref: spectral type of the star, followed by its literature reference, <br> as retrieved from the SIMBAD database. If none was listed there, the reference is noted as 'SIMBAD';<br>(7,8) Teff & ref: effective temperature of the star, in K, followed by its literature reference; <br>(9) d: distance of the target, based on its parallax (mainly from the Gaia ED33), in pc.<br> If no Gaia parallax was available a reference to the distance we adopted is given in Appendix A<br> (for RAFGL 3099, mu Cep, and V Peg);<br>(10) Vlit: published radial velocity of the target in the LSR reference frame, in km/s;<br>(11) Vexp: literature expansion velocity measured from CO or OH 1612 MHz line observations, in km/s. <br> If a pair of values was published for a two-velocity component CO line fit, the largest value is listed here;<br>(12) Mdot : literature mass loss rates, in solar masses per year, <br>(13) line: spectral line on which the published radial velocity measurement (Vlit) was based;<br>(14) ref: literature references to the published Vlit, Vexp and Mdot values; </p> <p>Notes to Table B.3:</p> <p>References: see Table B.1 in the Astronomy & Astrophysics paper.</p> <p><br>--- Table B.4: Possible NRT HI detections - HI data</p> <p>Description of the columns:</p> <p>See the description of the columns of Table B.2.</p> <p><br>--- Online only Table 5: Upper limits to NRT HI lines </p> <p>Description of the columns:</p> <p>(1) Name: common catalogue name of the target. <br> An ^n after a name indicates that it is clearly not an AGB star, <br> a ^d that we consider its classification as an AGB to be dubious, <br> and a ^* indicates that notes on the object can be found in Appendix A;<br>(2,3) RA,DEC: literature right ascension and declination of the target from Gaia EDR 3, <br> for epoch J2000.0;<br>(4) Type: target type. <br> Primarily the variability type as listed in Version 5.1 of the General Catalogue of Variable Stars, <br> GCVS (A description of GCVS types is given in https://cdsarc.u-strasbg.fr/ftp/cats/B/gcvs/vartype.txt),<br> but if an object is not included in the GCVS, other identifiers are listed in brackets: <br> HPM = high proper motion star, (OH/IR) = OH/IR maser, LPVc = long-period variable candidate, <br> PN = planetary nebula, pPN = proto-planetary nebula, and post-AGB star;<br>(5,6) spec & ref: spectral type of the star, followed by its literature reference, <br> as retrieved from the SIMBAD database. If none was listed there, the reference is noted as 'SIMBAD';<br>(7,8) Teff & ref: effective temperature of the star, in K, followed by its literature reference; <br>(9) d: distance of the target, based on its parallax (mainly from the Gaia EDR3, in pc.<br> If no Gaia parallax was available a reference to the distance we adopted is given in Appendix A<br> (for RAFGL 3099, mu Cep, and V Peg);<br>(10) Vlit: published radial velocity of the target in the LSR reference frame, in km/s;<br>(11) Vexp: literature expansion velocity measured from CO or OH 1612 MHz line observations, in km/s. <br> If a pair of values was published for a two-velocity component CO line fit, the largest value is listed here;<br>(12) Mdot : literature mass loss rates, in solar masses per year, <br>(13) ref: literature references for Vlit, Vexp and Mdot, as applicable;<br>(14) line: spectral line on which the published radial velocity measurement (Vlit) was based;<br>(15) Speak: peak flux density of our HI line profile, in Jy;<br>(16) notes: 'old data' indicates objects observed only in 1992/1993, before the renovation of the NRT; <br> 'blue/red side' indicates that either the blue or red side of the HI profile could be used to measure <br> an upper limit to the line flux;<br>(17) HI ref: references to previously published HI studies;</p> <p>Notes to online only Table 5: </p> <p>HI references: see Table B.2 in the Astronomy & Astrophysics paper.<br>Other references: see Table B.1 in the Astronomy & Astrophysics paper.</p> <p><br>--- Online only Table 6: Confused NRT HI spectra</p> <p>Description of the columns:</p> <p>(1) Name: common catalogue name of the target. <br>(2,3) RA, DEC: literature right ascension and declination of the target from Gaia EDR3, <br> for epoch J2000.0; <br>(4) type: target type. Primarily the variability type as listed in Version 5.1 of the <br> General Catalogue of Variable Stars, GCVS; but if an object is not included in the GCVS, <br> other identifiers are listed in brackets: HPM = high proper motion star, (OH/IR) = OH/IR maser, <br> LPVc = long-period variable candidate, PN = planetary nebula, pPN = proto-planetary nebula, <br> and post-AGB star; <br>(5,6) spec & ref spectral type of the star, followed by its literature reference, <br> as retrieved from the SIMBAD database. If none was listed there, the reference is noted as 'SIMBAD'; <br>(7,8) Vlit & ref: published radial velocity of the target in the LSR reference frame, in km/s; <br>(9) line: spectral line on which the published radial velocity measurement (Vlit) was based; <br>(10) notes: 'old data' denotes objects observed only in 1992/1993, before the renovation of the NRT<br> (see Section 3), for which no observations in digital form are available; <br>(11) HI ref: references to previously published HI studies.</p> <p>Notes to online only Table 6:</p> <p>HI references: see Table B.2 in the Astronomy & Astrophysics paper.<br>Other references: see Table B.1 in the Astronomy & Astrophysics paper.</p>
Effect of net direct current on the properties of radio frequency sheaths: simulation and cross-code comparison
<p>The accompanying files contain digital data for figures in the article "Effect of net direct current on the properties of radio frequency sheaths: simulation and cross-code comparison" by J. R. Myra, M.T. Elias, D. Curreli, and T. G. Jenkins, submitted to the journal Nucl. Fusion.</p> <p>Abstract</p> <p>In order to understand, predict and control ion cyclotron range of frequency (ICRF) interactions with tokamak scrape-off layer plasmas, computational tools which can model radio frequency (RF) sheaths are needed. In particular, models for the effective surface impedance and DC rectified sheath potentials may be coupled with full wave RF simulation codes to predict self-consistent wave fields near surfaces and the resulting power dissipation and plasma-material interactions from ion sputtering. In this study, previous work assuming zero net DC current flow through the sheath is generalized to allow the surface to collect net positive or negative current, as is often observed in experiments. The waveforms, DC potential and RF admittance are investigated by means of analytical theory, nonlinear fluid and particle-in-cell (PIC) codes. Cross-code comparisons provide detailed model verification and elucidate the roles of ion and electron kinetics. When the sheath draws negative (positive) DC current, the voltage rectification is reduced (increased) compared with the zero-current case, and both the real and imaginary parts of the admittance are increased (reduced). A previous four-input parametrization of the sheath rectification and admittance properties is generalized to include a fifth parameter describing the DC sheath current. </p>
SCORPIO ASKAP15 compact radio source catalogue
<p>This dataset provides the compact radio source catalogue data extracted from ASKAP observations (15 antennae) of the SCORPIO field at 912 MHz, carried out in the context of ASKAP EMU Early Science phase. The reference scientific publication is S.Riggi et al., to appear on MNRAS. </p> <p>The dataset includes:</p> <p>- Source catalogue in tabular format: Two ascii/FITS table files with a series of summary parameters for each catalogued source islands and fitted components, respectively. Table format (number of data columns and column description) is detailed in the CAESAR source finder online documentation at <a href="http://caesar-doc.readthedocs.io">https://caesar-doc.readthedocs.io</a>. Additionally, we provide an added-value source component catalogue table (ascii and FITS formats) with extra-information (corrected fluxes, radio/infrared cross-match info, spectral indices, etc.). Its format is described in the reference publication;</p> <p>- Source catalogue in ROOT format: A ROOT file storing the list of catalogued sources and relative components as a CAESAR <em>Source</em> C++ object. For each source the summary parameters plus detailed information at pixel level are available. The detailed format is described in the CAESAR API documentation at <a href="http://caesar-doc.readthedocs.io">https://caesar-doc.readthedocs.io</a>.</p> <p>- Source list in region format: Two DS9 region files with the list of catalogued source islands and fitted components, respectively reported as labelled polygons or ellipses.</p> <p>- Background maps in FITS format: Two FITS files with background and noise maps obtained in the source finding process.</p>
Physics-based parametrization of the surface impedance for radio frequency sheaths
<p>The accompanying files contain digital data for the figures in the article "Physics-based parametrization of the surface impedance for radio frequency sheaths" by J.R. Myra, Physics of Plasmas 24, 072507 (2017).</p> <p>Filenames correspond to the figures or parts thereof. All data is given as ascii text in csv format. The files may be open and plotted by common spreadsheet programs and may be easily read by procedural programs. The first row gives the column headers. These correspond to the labels on the x and y axes of the figures (as represented by ascii text). Most headers are self-explanatory. Exceptional cases are noted below.</p> <p>Fig. 2<br> w = frequency omega<br> yir20 = real part of ion impedance Re[yi] for Vrf = 20<br> yii20 = imaginary part of ion impedance Im[yi] for Vrf = 20<br> yir10 = real part of ion impedance Re[yi] for Vrf = 10<br> yii10 = imaginary part of ion impedance Im[yi] for Vrf = 10<br> yir5 = real part of ion impedance Re[yi] for Vrf = 5<br> yii5 = imaginary part of ion impedance Im[yi] for Vrf = 5<br> yir0 = real part of ion impedance Re[yi] for Vrf = 0<br> yii0 = imaginary part of ion impedance Im[yi] for Vrf = 0</p> <p>The diagonal blue lines in the published figures for Figs. 3 - 8 indicate the line y = x and are not explicilty tabulated here.</p> <p>Abstract:</p> <p>The properties of sheaths near conducting surfaces are studied for the case where both magnetized plasma and intense radio frequency (rf) waves coexist. The work is motivated primarily by the need to understand, predict and control ion cyclotron range of frequency (ICRF) interactions with tokamak scrape-off layer plasmas, and is expected to be useful in modeling rf sheath interactions in global ICRF codes. Employing a previously developed model for oblique angle magnetized rf sheaths [J. R. Myra and D. A. D’Ippolito, Phys. Plasmas 22, 062507 (2015)], an investigation of the four-dimensional parameter space governing these sheath is carried out. By combining numerical and analytical results, a parametrization of the surface impedance and voltage rectification for rf sheaths in the entire four-dimensional space is obtained.</p>
List of HOM/DAM Radio Sources crossings during Juno's 45 first perijoves
<p>This data is associated with Collet 2024 (JGR) A new type of "Jovian hectometric radiation powered by monoenergetic electron beams" in review.</p> <p>This document shows a dataset of HOM/DAM sources detected during the 45 first Juno perijoves. These sources are identified from Juno/Waves measurements with the criterion fce<f<fce+1% from Louis (2019).</p>
RMTable Consolidated Catalog of Faraday Rotation Measures of Astronomical Radio Sources
<p>This is a catalog of Faraday rotation measures (and other related properties) of astronomical radio sources, consolidated from many published catalogs in the astronomical literature from 1980 to the present day. These catalogs have been converted to the RMTable standard and stored in 3 formats: FITS binary table, tab-seperated-value ASCII, and VOTable XML.</p> <p>These catalog files can be read by any suitable reader, but we have created a Python module, RMTable (https://github.com/CIRADA-Tools/RMTable), which streamlines the process of interacting with and creating new RMTables.</p>
Data for "Identification of 4876 Bent-Tail Radio Galaxies in the FIRST Survey using Deep Learning Combined with Visual Inspection"
<p>The data are the full versions of tables that will be published in the manuscript titled "Identification of 4876 Bent-Tail Radio Galaxies in the FIRST Survey using Deep Learning Combined with Visual Inspection" by The Astrophysical Journal Supplement Series.</p> <p>The table file named "FIRST_bt_table1.csv" is the full table for "A catalog of 4876 BTRGs identified from VLA FIRST survey". </p> <p>The table file named "FIRST_bt_table2.csv" is the full table for "Cluster details for BTRGs". </p>
The detection of radio emission from known X-ray flaring star EXO 040830−7134.7
<p>This is the radio light curve of known X-ray flaring star EXO 040830−7134.7 observed by MeerKAT as part of ThunderKAT. These data are part of a publication in the Monthly Notice of the Royal Astronomical Society (Driessen et al., Accepted 2021 November 25. Received 2021 November 25; in original form 2021 August 25).</p> <p>The light curve is from the full-time-integration, full-frequency-integration images of VW Hyi, as processed by the LOFAR Transients Pipeline (<a href="https://tkp.readthedocs.io/en/latest/introduction.html">TraP</a>).</p> <p>The columns in the file are:</p> <ul> <li>mjd: the modified Julian Date (MJD) of the observation. The MJD is given by MJD=JD-2400000.5 where JD is the Julian Date</li> <li>f_int_Jy: the integrated flux density of the source in Jansky (Jy) determined by the LOFAR TraP</li> <li>f_int_err_Jy: the uncertainty on f_int_Jy in Jansky determined by the LOFAR TraP</li> <li>freq_eff_Hz: the effect frequency in Hertz (Hz) as determined by the LOFAR TraP</li> <li>taustart_ts: the ISO 8601 time of the observation in Coordinated Universal Time (UTC)</li> </ul> <p>The files were made using the Pandas package, so we recommend Python users load them using</p> <pre><code>import pandas as pd pd.read_csv(filename, comment='#')</code></pre> <p>If you use the data shared here please ensure that you cite the MNRAS paper (Driessen at al. 2021) and the Zenodo DOI: 10.5281/zenodo.5084298.</p> <p>The MeerKAT telescope is operated by the South African Radio Astronomy Observatory, which is a facility of the National Research Foundation, an agency of the Department of Science and Innovation.<br> LND acknowledges support from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement No 694745).</p>
Amplifying Indigenous Radio: Bibliography of Critical Indigenous Theory
<p>This is a working list of Indigenous critical theoretical approaches drawn on in my research into Indigenous radio.This is a work in progress rather than an exhaustive Bibliography and is open to further updating.</p>
Suomi 100 satellite's HEARER radio spectrometer's measurements on Dec. 9, 2020
<p>Metadata (included also inside the file):</p> <ul> <li>Spacecraft: Suomi 100</li> <li>Name of the instruments: HEARER</li> <li>Instrument type: Radiospectrometer</li> <li>Measurement day: Dec. 9, 2020</li> <li>HEARER's data file ID: m1_1607509173</li> <li>Data: <ul> <li>the 1st column: The number of the data point (an integer between 280000 - 319999)</li> <li>the 2nd column: Observation (an integer): <ul> <li>Measurement frequency: 7.953 MHz</li> <li>Data rate: 1000 data points per a second</li> </ul> </li> </ul> </li> </ul> <p> </p> <ul> <li>The file prepared by Esa Kallio (esa.kallio@aalto.fi), Aalto University, Finland, on Sep. 8, 2022</li> </ul> <p> </p> <ul> <li>Miscellanous:</li> </ul> <p> (the number of the data point, -observation) plots can be found from the publication</p> <p> Kallio et al., Radar – CubeSat Transionospheric HF Propagation Observations: Suomi 100 - Satellite and EISCAT HF Facility, <em>Radio Science.</em></p>
Corresponding Dataset for "Ganymede's Ionosphere observed by a Dual-Frequency Radio Occultation with Juno"
<p> Corresponding Dataset for "Ganymede’s Ionosphere observed <br> by a Dual-Frequency Radio Occultation with Juno"<br> README FILE<br> VERSION 2<br> Dustin Buccino<br> April 22, 2024<br> Jet Propulsion Laboratory<br> California Institute of Technology</p> <p>=============================================================================<br>VERSION 2 INFORMATION<br>=============================================================================</p> <p> Version 2 of this dataset separates the Electron Density profile from the<br>main data files and makes a correction to the egress profile that was<br>discovered. Differences in egress profile are very small and within<br>the uncertainties. Furthermore egress is statistically a non-detection<br>(zero densities), but for sake of accuracy they are reposted to be<br>consistent with the publication.</p> <p>=============================================================================<br>INTRODUCTION<br>=============================================================================</p> <p> This dataset contains processed radio science data and results of the<br>Juno Ganymede radio occultation. This dataset is provided in order to <br>supplement the submitted article to the "Geophysical Research Letters"<br>journal:</p> <p> Buccino, D.R., et al (2022), Ganymede’s Ionosphere observed by a <br> Dual-Frequency Radio Occultation with Juno, Geophysical Research <br> Letters, submitted February 2022.</p> <p><br> Please note the raw data used in this analysis are not provided in this<br>supplementary dataset. The raw Juno Gravity Science Data may be found at <br>the Planetary Data System:</p> <p> Buccino, D. R. (2016). Juno jupiter gravity science raw data set <br> V1.0, JUNO-J-RSS-1 JUGR-V1.0, NASA planetary data system (PDS). <br> Retrieved from https://atmos.nmsu.edu/PDS/data/jnogrv_1001/<br> </p> <p>=============================================================================<br>ARCHIVE INFORMATION<br>=============================================================================</p> <p> This archive contains two files within the root directory.<br> <br> ROOT<br> `- JunoG34OccData_Egress_v2.csv</p> <p> This data file contains the EGRESS data relevant to the radio<br> occultation. The data is a timeseries of impact parameter, sky<br> sky frequency at X-band and Ka-band, the dual-frequency <br> combination, the calibrated dual-frequency, Total Electron <br> Content.</p> <p> `- JunoG34_GRL_Egress_Profile_v2.csv</p> <p> This data file contains the EGRESS Electron density, and <br> 1-sigma electron density uncertainty.</p> <p> `- JunoG34OccData_Ingress_v2.csv</p> <p> This data file contains the INGRESS data relevant to the radio<br> occultation. The data is a timeseries of impact parameter, sky<br> sky frequency at X-band and Ka-band, the dual-frequency <br> combination, the calibrated dual-frequency, Total Electron <br> Content.</p> <p> `- JunoG34_GRL_Ingress_Profile_v2.csv</p> <p> This data file contains the INGRESS Electron density, and <br> 1-sigma electron density uncertainty.</p> <p>=============================================================================<br>FILE FORMAT<br>=============================================================================</p> <p> This dataset contains only a comma-separated text files which are<br>given with the "*.csv" extension.</p> <p><br> CSV FILES<br> -------------------------------------------------------------------------</p> <p> The Comma-Separated Value (CSV) files are plain-text files. Values in<br> each data file are separated using a comma ",". Each column is defined <br> by a header row which provides a description of each column.<br> </p> <p>=============================================================================<br>ACKNOWLEDGMENTS<br>=============================================================================</p> <p>This work was carried out at the Jet Propulsion Laboratory, <br>California Institute of Technology, under contract with the National <br>Aeronautics and Space Administration. Government sponsorship acknowledged.</p> <p>EG, LGC, PT, MZ and AC are grateful to the Italian Space Agency (ASI) for <br>financial support through Agreement No. 2018-25-HH.0 in the context of ESA's <br>JUICE mission, and Agreement No. 2017-40-H.1-2020, and its extension <br>2017-40-H.02020-13-HH.0, for ESA’s BepiColombo and NASAs Juno radio science <br>experiments. EG is grateful to "Fondazione Cassa dei Risparmi di Forlì" for <br>financial support of his PhD fellowship.</p> <p>PS and AH were supported by NASA Contract NNM06AA75C from the Marshall <br>Space Flight Center under subcontract 699054X from Southwest Research <br>Institute.</p> <p><br>=============================================================================<br>PRIMARY POINT OF CONTACT<br>=============================================================================</p> <p>Dustin Buccino<br>Jet Propulsion Laboratory<br>Planetary Radar and Radio Sciences<br>(818) 393 - 1072<br>Dustin.R.Buccino@jpl.nasa.gov</p> <p>=============================================================================<br>ACRONYMS AND ABBREVIATIONS<br>=============================================================================</p> <p> ASCII American Standard Code for Information Interchange<br> DOY Day of year<br> DSN Deep Space Network<br> JPL Jet Propulsion Laboratory<br> NAIF Navigation Ancillary Information Facility<br> NASA National Aeronautics and Space Administration<br> PDS Planetary Data System<br> RS Radio Science<br> RSS Radio Science Subsystem<br> SIS Software Interface Specification<br> TXT Text file<br> UTC Universal Time, Coordinated</p>
Volcanic Lightning and Continual Radio Frequency Impulses at Sakurajima Volcano: A Multiparametric Dataset
<p>This is a multiparametric data set of volcanic activity at Sakurajima volcano in Japan. The data set was collected in May and June 2015. The data set includes the following types of data: Lightning Mapping Array data, slow and fast electric field waveforms, log-RF VHF data, infrasound data, plume height, velocity, and temperature data.</p>
Characterizing the gamma-ray variability of the brightest flat spectrum radio quasars observed with the Fermi LAT
<p>The FITS files contain light curves (prefix "lc"), spectral energy distributions (prefix "sed") and best-fit parameters for the whole region of interest (prefix "bestfit_roi") for the gamma-ray analyses of the six brightest flat spectrum radio quasars observed over 9.5 years with the Fermi Large Area Telescope (LAT). The file names also indicate the considered binning (weekly, daily, orbit, sub-orbital) and the considered time range in MJD.<br> The data products have been generated using the fermipy software, please see the documentation for further explanations of the columns provided in these files: <a href="https://fermipy.readthedocs.io/en/latest/">https://fermipy.readthedocs.io/en/latest/</a></p> <p>The analysis catalog are described in detail in the accompanying paper, which is submitted for publication in the Astrophysical Journal. The preprint of the submitted manuscript can be found here: <a href="https://arxiv.org/abs/1902.02291">https://arxiv.org/abs/1902.02291</a></p> <p>Additionally, the code for high level analysis including the light curves and the gamma-ray absorption in the broad line region can be found on github: <a href="https://github.com/me-manu/GaRLiC">https://github.com/me-manu/GaRLiC </a>and <a href="https://github.com/me-manu/blrabsorption">https://github.com/me-manu/blrabsorption</a></p> <p> </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.