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101 results for “scintillator”
Using GOLD Plasma Bubble Observations for Validation of Geolocation of Plasma Irregularities by Back Propagation of the High-Rate FORMOSA7/COSMIC 2 Scintillation Data
The dataset contains files geolocation of scintillations from COSMIC-2 high rate scnPhs files using back-propagation method. The dataset was used in the paper for validation of the geolocation method. The data are in multi-column ASCII file format.
Scintillation event list database produced for "Multiyear Detection, Classification and Hypothesis of Ionospheric Layer Causing GNSS Scintillation"
<table> <tbody> <tr> <td>Database produced for and associated with journal article https://doi.org/10.1029/2021RS007328</td> </tr> <tr> <td>This database contains scintillation events identified by the "Detect, Classify, Hypothesize" method as described in the journal article. </td> </tr> <tr> <td>Created by Datta-Barua, Seebany.</td> </tr> <tr> <td>Open Access License Creative Commons Attribution 4.0 International</td> </tr> <tr> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td>Sheets labeled "S*_yyyy_freq" contain a list of scintillation events based on data from the SAGA array.</td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td> </td> <td>For S* the abbreviations are:</td> <td>"SP": sigma phi index, i.e., phase scintillation events</td> <td> </td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td> </td> <td> </td> <td>"S4": S4 index, i.e., amplitude scintillation events</td> <td> </td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td> </td> <td> </td> <td>"SPS4": sigma phi and S4, i.e., both-phase-and-amplitude events</td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td> </td> <td>yyyy indicates the four-digit year, from 2014 through 2019</td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td> </td> <td>freq:</td> <td>"L1CA": refers to GPS L1 frequency 1575 MHz</td> <td> </td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td> </td> <td> </td> <td>"L2CL": refers to GPS L2C frequency 1227 MHz</td> <td> </td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td>In each sheet "S*_yyyy_freq" the columns are:</td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td> </td> <td>Column A:</td> <td>Year (2014-2019)</td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td> </td> <td>Column B:</td> <td>day of year (1-366)</td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td> </td> <td>Column C:</td> <td>frequency (1 for L1, 2 for L2C)</td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td> </td> <td>Column D:</td> <td>GPS satellite PRN (1-32)</td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td> </td> <td>Column E:</td> <td>Scintillation start UT hour (0-23)</td> <td> </td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td> </td> <td>Column F:</td> <td>Scintillation start UT minute (0-59)</td> <td> </td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td> </td> <td>Column G:</td> <td>Scintillation end UT hour (0-23)</td> <td> </td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td> </td> <td>Column H:</td> <td>Scintillation end UT minute (0-59)</td> <td> </td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td> </td> <td>Column I:</td> <td>number of receivers operational (4-6)</td> <td> </td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td> </td> <td>Column J:</td> <td>PFISR-based hypothesized layer (1-7, as described below)</td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td> </td> <td> </td> <td>1:</td> <td>E layer (majority peak height < 150 km)</td> <td> </td> <td> </td> </tr> <tr> <td> </td> <td> </td> <td>2:</td> <td>F layer (majority peak height > 195 km)</td> <td> </td> <td> </td> </tr> <tr> <td> </td> <td> </td> <td>3:</td> <td>T layer (150 < majority peak height < 195 km)</td> <td> </td> <td> </td> </tr> <tr> <td> </td> <td> </td> <td>4:</td> <td>I layer (no majority layer)</td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td> </td> <td> </td> <td>5:</td> <td>"N"- no Poker Flat Incoherent Scatter Radar (PFISR) long pulse data and no alternating code data</td> </tr> <tr> <td> </td> <td> </td> <td>6:</td> <td>"NLP" - no PFISR long pulse</td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td> </td> <td> </td> <td>7:</td> <td>"NAC" - no PFISR alternating code</td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td>A blank sheet indicates that there were no events of that type and at that frequency found in that year.</td> <td> </td> <td> </td> <td> </td> </tr> </tbody> </table>
DATASET - Evaluation of a novel inorganic scintillator for applications in LDR brachytherapy using both TE-cooled and room temperature SiPMs
<p>This dataset includes the raw data and the analyzed data which are included in the conference paper entitled: "Evaluation of a novel inorganic scintillator for applications in LDR brachytherapy using both TE-cooled and room temperature SiPMs".</p> <p> </p> <p>Agnese Giazc, Simona Comettic, Romualdo Santoroc, Peter Woulfea,b, Massimo Cacciac, and Sinead O’ Keeffeb<br> aDepartment of Medical Physics, Galway Clinic, Galway H91 HHT0, Ireland; bOptical</p>
Ionospheric Scintillation Data over Indonesia
<p>These scintillation data are obtained from Kototabang (100.3E, 0.2S), Pontianak (109.3E, 0.02S), and Manado (124.9E,1.5N) stations in Indonesia. These datasets were used to create a scientific manuscript titled "Longitudinal range of the eastward-traveling equatorial plasma bubble inducing scintillation" by P. Abadi et al., which is published in the Space Weather Journal (https://doi.org/10.1029/2024SW003908).</p> <p> </p> <p>In addition to this dataset citation, please cite the following reference when you use this dataset:</p> <p>Abadi, P., Otsuka, Y., Saito, S., Yamamoto, M., Perwitasari, S., Muafiry, I. N., et al. (2024). Longitudinal range of the eastward‐traveling equatorial plasma bubble inducing ionospheric scintillation. Space Weather, 22, e2024SW003908. https://doi.org/10.1029/2024SW003908</p> <p> </p>
Model-based Investigation of Electron Precipitation-driven Density Structures and their Effects on Auroral Scintillation
<p>This folder contains the precipitation modeling results and the camera dataset used for this study. It also includes the details of the supplementary material cited in the text in sections 3 (table params), 3.1 (minimum total energy flux), 4.1 (minimum total energy flux), and 4.2 (density profiles for different characteristic energies). </p>
The initial assessment of ionospheric radio occultation data of MSS-1 satellite and its applications in scintillation exploration
<p>This dataset contains the GNSS data in the first three months of MSS-1 operation.</p> <p>The <em>.pdf files are level-2 radio occultation electron density files; </em>.csv are level-2 scintillation files.</p>
GPS data for 'Low-Latitude Ionospheric Density Irregularities and Associated Scintillations Investigated by Combining COSMIC RO and Ground-Based GPS Observations over a Solar Active Period' by Zhe Yang and Zhizhao Liu
<p>This dataset contains the final derived GPS data reported in the paper 'Low-Latitude Ionospheric Density Irregularities and Associated Scintillations Investigated by Combining COSMIC RO and Ground-Based GPS Observations over a Solar Active Period' by Zhe Yang and Zhizhao Liu.</p>
On the relationship between the rate of change of total electron content index (ROTI), irregularity strength (CkL) and the scintillation index (S4)
<p>This dataset contains measurements and analysis results in support of the paper, "Carrano C., K. Groves, and C. Rino (2019), On the relationship between the rate of change of total electron content index (ROTI), irregularity strength (CkL) and the scintillation index (S4), Journal of Geophysical Research: Space Physics, 2019."</p>
Data set for 'Remote control of neural function by X-ray-induced scintillation'
<p>Data set for: Matsubara T, Yanagida T, Kawaguchi N, Nakano T, Yoshimoto J, Sezaki M, Takizawa H, Tsunoda SP, Horigane S, Ueda S, Takemoto-Kimura S, Kandori H, Yamanaka A, Yamashita T (2021) Remote control of neural function by X-ray-induced scintillation. Nature Communications 12: 4478, doi 10.1038/s41467-021-24717-1</p> <p>There are 2 files in this upload:</p> <p>1. The file named "Matsubara_data.zip" (~18 GB) is a zipped version of a folder "Dataset" (~27 GB), which contains images, movies, and other data analyzed in the study. When unzipped, the folder contains subfolders categorized based on experiment types. A 'read me' text file is associated with each small dataset.</p> <p>2. The file named "Matsubara_published.zip" (~5 MB) contains the Open Access pdf of the paper, the Supplementary Information file, and the Source Data file.</p>
From Sintering to Particle Discrimination: New Opportunities in Metal–Organic Frameworks Scintillators
<p>Dataset from publication</p>
The Thousand-Pulsar-Array programme on MeerKAT - X. Scintillation arcs of 107 pulsars
<p>Data used in the publication "The Thousand-Pulsar-Array programme on MeerKAT - X. Scintillation arcs of 107 pulsars" <a href="https://doi.org/10.1093/mnras/stac3149">https://doi.org/10.1093/mnras/stac3149</a>. This release includes both the raw and filtered dynamic spectra, as described in the manuscript.</p> <p>The pipeline used to process produce, filter, and analyse dynamic spectra starting from the pulsar archives is on github: https://github.com/ramain/meerkat-scintpipe</p>
Variable Scintillation Arcs in Millisecond Pulsars observed with the Large European Array for Pulsars
<p>Dynamic spectra used in "Variable Scintillation Arcs in Millisecond Pulsars observed with the Large European Array for Pulsars". </p> <p>The dynamic spectra are simple ascii (the same output produced by psrflux), produced as described in the manuscript. A function to read them in python is included on github: https://github.com/ramain/scintillation/blob/master/scintillation/dynspectools/dynspectools.py, and they should all be compatible with the scintools package.</p>
The data of scintillation
<p>The data includes the 2020-2022 scintillation data of Zhongshan Station in Antarctica. The data includes time, phase scintillation, amplitude scintillation, elevation Angle, satellite number, and geomagnetic latitude and longitude.</p>
Measurements for "Evaluation of Ionospheric Scintillation in GNSS Radio Occultation Measurements and Simulations"
<p>This dataset contains measurements addressed in the manuscript "Evaluation of Ionospheric Scintillation in GNSS Radio Occultation Measurements and Simulations".</p> <p>These files and further measurements from different radio occultation missions are available in: https://cdaac-www.cosmic.ucar.edu (registration required)</p>
Dataset from the ground-based TEC and scintillation receiver in Troll station for February 26-27 and March 18-19, 2018
<p>Here present data from the GNSS Ionospheric Scintillation and TEC Monitor (GISTM) receiver NovAtel GPStation-6 that located at the Norwegian Research Station Troll in Queen Maud Land, Antarctica. The receiver records signals from the GPS, GLONASS, and Galileo satellites. Every minute, it provides extended summary messages, including satellite azimuth/elevation angles, C/NO, lock time, code-minus-carrier, calculations of amplitude (S4) and phase (σϕ) scintillation indices, and TEC. The data present after cut-off elevation angle of 30° to solve multipath effects.</p> <p>Time interval: 22:00-08:00 UT on February 26-27 and 17:00-06:00 UT on March 18-19, 2018.</p> <p>The data is presented as tables. Each .csv file contains data and header.</p>
GNSS signals acquired by a Software Defined Radio (SDR) system subject to ionospheric scintillations
<p>Global Navigation Satellite System (GNSS) signals crossing small-scale electron density irregularities in the ionosphere may be subject to rapid fluctuations of their amplitude and phase known as ionospheric scintillations. Ionospheric scintillations may cause cycle slips and loss of lock of the GNSS signals, thus hindering the accuracy and integrity of precise positioning applications. GNSS scintillation can be studied and monitored by processing the GNSS signals through dedicated ground-based monitoring equipment such as the Ionospheric Scintillation Monitoring Receiver (ISMR). Moreover, Software Defined Radio (SDR) equipment has been demonstrated as a powerful tool to support the analysis of GNSS signals subject to this kind of phenomena. </p> <p>This dataset contains 3 hours of GNSS signal acquired by an SDR system located in Lampedusa, Italy (lat:35.52, lon: 12.63). The dataset was acquired on the 23th March 2023, from 20 to 22 UTC. Within this timespan, a co-located ISMR receiver detected ionospheric scintillations on a few of the GNSS satellites in view. </p> <p>Besides the binary data from the SDR system, a json file containing the Scintillation Indices at 1 min resolution acquired by the ISMR receiver is also provided.</p>
Statistical uncertainty in the frequency dependence of the intensity scintillation index (S4)
<p>This dataset contains scintillation statistics and parameters in support of the paper, "Sun, A. K., Pi, X., Rino, C., and Lee, J. (2023), Statistical uncertainty in the frequency dependence of the intensity scintillation index (S4), Radio Science."</p> <p>The raw GNSS scintillation dataset was collected by Dr. Eurico de Paula at INPE (Instituto Nacional de Pesquisas Espaciais), Brazil.</p>
The ionospheric scintillation indexes observed by Ultra High Frequency (UHF) band scintillation receiver on 15, 16, and 17 August 2015
<p>The dataset reports the ionospheric scintillation indexes observed by Ultra High Frequency (UHF) band scintillation receiver on 15, 16, and 17 August 2015. Every day's data is saved in a TXT file, whose time resolution is one minute.</p>
Data sets for "On the quiet-time occurrence rates, severity and origin of L-band ionospheric scintillations observed from low-to-mid latitude sites located in Puerto Rico" by Gomez Socola et al.
<p>These data sets contain the night-time scintillation index (S4) of the geomagnetically quiet days. </p>
BARREL 2B Rate Counter (RCNT) NaI Scintillator Diagnostics, Level 2, 4 s Data
This data product consists of measurements from rate counters. The rate count data are diagnostic fields, have uncalibrated energy ranges, and wrap near or above 16384 counts/s. The rate count values are stored as 4 s accumulations of counts.The BARREL Mission was a multiple-balloon investigation designed to study electron losses from Earth's Radiation Belts. Selected as a NASA Living with a Star Mission of Opportunity, BARREL was designed to augment the Radiation Belt Storm Probes, RBSP, mission by providing measurements of the spatial and temporal variations of electron precipitation from the radiation belts. The RBSP mission has since been renamed the Van Allen Probes mission. Each BARREL balloon carried an X-ray spectrometer to measure the bremsstrahlung X-rays produced by precipitating relativistic electrons as they collide with neutrals in the atmosphere, and a DC magnetometer to measure ULF-timescale variations of the magnetic field. BARREL observations collected near latitudes close to either the antarctic and arctic circles at stratospheric altitudes at about 30 km. The BARREL instrumentation provided the first balloon measurements of relativistic electron precipitation while comprehensive in situ measurements of both plasma waves and energetic particles were available. Also, the BARREL data has been used to characterize the spatial scale of precipitation at relativistic energies.The initial pair of balloon campaigns that were conducted initially during the Austral summer months of January and February of 2013 and 2014 with launches from two stations located in Antarctica: the British base located at Halley Bay on the Brunt Ice Shelf and the South African SANAE IV base (SANAE stand for South African National Antarctic Expedition) located in Vesleskarvet, Queen Maud Land. For the 2013 and 2014 the balloon campaigns, the launch plan was designed to maintain an array with about five payloads spread across about six hours of magnetic local time, MLT, in the region that magnetically maps to the radiation belts. Thus, the BARREL balloon constellation constituted an evolving and slowly moving array able to study relativistic electron precipitation from the radiation belts.Later campaigns were undertaken in 2015 and 2016 from the Esrange Space Center located in Kiruna, Sweden. The 2015 and 2016 campaigns were undertaken in coordination with the Van Allen Probes mission, the European Incoherent Scatter Scientific Association, EISCAT, incoherent scatter radar system, and other ground and space based instruments. Seven balloon launches occurred during the August 2015 BARREL campaign. A total of eight flights occurred during August 2016.Summing over the four BARREL campaigns, over 50 small, approximately 20 kg, stratospheric balloons were successively launched. The website creeated and hosted by A.J. Halford (see Information URL below) reports that: "By the end of the campaigns, there were over 90 researchers coordinating on a daily basis with the BARREL team working on 7 different satellite missions, 1 other balloon mission, and way too many ground based instruments to count." Although the BARREL mission launched only balloons during the years from 2013 to 2016, research using data collected on these flights is ongoing, so stay tuned for updates! All data and analysis software are freely available to the scientific community.The information listed above in this resource description was compiled by referencing several BARREL related resources including primarily the Millan et al. (2013) Space Science Reviews publication, the BARREL at Dartmouth mission web site, and the website maintained by A.J. Halford.The current release of all BARREL CDF data products are Version 10 files.BARREL will make all its scientific data products quickly and publicly available but all users are expected to read and follow the BARREL Data Usage Policy listed below.BARREL Data Usage PolicyBARREL data products are made freely available to the public and every effort is made to ensure that these products are of the highest quality. However, there may occasionally be issues with either the instruments or data processing that affect the accuracy of data. When possible, a quality flag is included in higher level data products, and known issues are posted in the BARREL data repository. You are also strongly encouraged to follow the guidelines below if you are planning a publication or presentation in which BARREL data are used. This will help you ensure that your science results are valid.* Users should always use the highest version numbers of data and analysis tools. Browse/quick-look plots are not intended for science analysis or publication and should not be used for those purposes without consent of the principal investigator, PI.* Users should notify the BARREL PI of the data use and investigation objectives. This will ensure that you are using the data appropriately and have the most recent version of the data or analysis routines.
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