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113 results for “Radio Frequency”
Reproduction package for 'Low-frequency radio observations of recurrent nova RS Ophiuchi with MeerKAT and LOFAR'
<p>This is a basic reproduction package for the paper "Low-frequency radio observations of recurrent nova RS Ophiuchi with MeerKAT and LOFAR".</p><p> </p><p> </p>
Data Set: Radio Frequency Senser (RFS) example waveforms, altitudes, and density plot
<p>This data set contains data for the paper entitled "Radio Frequency Sensor: radio frequency lightning detection in geostationary orbit", submitted to <em>Radio Science </em>in December 2023.</p> <p>This data set contains three types of RFS data. 1) The first are time domain waveforms of three lightning events, in both the RFS high band (116 – 142 MHz) and the RFS low band (10-60 MHz), sampled at 155 MHz. The waveforms are right-hand circularly polarized waveforms. 2) The second type of data is altitudes and locations of trans-ionospheric pulse pairs (TIPPs) over time. The locations were determined by time coincidence with geolocated World Wide Lightning Location Network strokes. 3) The third type is RFS events per square kilometer per year in latitude and longitude. The RFS event were located by time correlation to Earth Networks Global Lightning Network lightning strokes.</p> <p><strong>Data set 1:</strong></p> <p>Consists of six ASCII files – 3 high band & 3 low band example RFS right-hand circularly polarized waveforms. Each ascii file contains a header with the RFS event time in UTC, the label of “RFS high band (77.5 – 155 MHz)” or “low band (0 – 77.5 MHz)”, and sample rate (155 MHz). Data following the header are time samples of electric field in uV/m sampled at 155 MHz.</p> <p>Filenames are:</p> <p>RFS_waveform_HighBand_20230607_010803.txt</p> <p>RFS_waveform_HighBand_20230607_015553.txt</p> <p>RFS_waveform_HighBand_20230607_034055.txt</p> <p>RFS_waveform_LowBand_20230607_010803.txt</p> <p>RFS_waveform_LowBand_20230607_015553.txt</p> <p>RFS_waveform_LowBand_20230607_034055.txt</p> <p> </p> <p><strong>Data set 2:</strong></p> <p>Filename = ‘RFS_TIPPs_20230607_0100-0500_UTC.txt’</p> <p>1 ASCII comma separated value (CSV) file. Columns are:</p> <p>1. UTC date yyyy/mm/dd</p> <p>2. UTC seconds of day</p> <p>3. WWLLN-determined latitude (degrees, wwlln_latitude in header)</p> <p>4. WWLLN-determined longitude (degrees, wwlln_longitude in header)</p> <p>5. TIPP-estimated height (km, height in header)</p> <p> </p> <p><strong>Data set 3:</strong></p> <p>Filename = ‘RFS_map.csv’</p> <p>1 CSV file of a 2-dimensional data set.</p> <p>1. Row 1, Longitude (degrees, in 0.25-degree steps)</p> <p>2. Column 1, Latitude (degrees, in 0.5-degree steps)</p> <p>3. 2-D grid in latitude and longitude: events per square kilometer per year</p> <p>Notes: Since the RFS coverage range goes across longitude = -180/180 degrees, longitudes go from 147.75 to 180, then start at -180 to -12.75. Latitude range goes from -58.5 to 68.5, as there were no detected RFS events outside these latitudes.</p> <p>The three examples given in data set 1 are those shown in LA-UR-23-32419, Figure 2. The TIPP data in data set 1 is shown in LA-UR-23-32419, Figure 4, and comprises data from 07 June 2023 between 01:00-05:00 UTC. Data set 3 contains RFS event rates per sq. km per year for data from 1 March 2022 – 1 March 2023, with the caveats described in LA-UR-23-32419.</p>
Investigation of two-dimensional radio-frequency sheath properties using a microscale fluid model
<p>In previous work (Kohno H. and Myra J.R. 2023 Comput. Phys. Commun. 291 108841), we developed a numerical scheme based on a two-dimensional microscale radio-frequency (RF) sheath model with periodically curved wall boundaries. Here, we expand the capability of this scheme through modification of the boundary conditions (BCs) on the conducting walls, which allows the ion flow to turn back to the plasma at locations on the walls where the electromagnetic force on the ions is reversed from its usual direction. Numerical simulations are carried out to investigate the dependences of the surface-integrated admittances on the wall bump height, ion magnetization, ion mobility, and the magnetic field angle, and to visualize the sheath structures in several cases. One of the main results is the ion cyclotron admittance resonance observed under the condition of low ion mobility (high normalized frequency). It is shown that the amplitude of the resonance peak depends on the wall bump height and the ion velocity is reversed on the sides of the bump in an RF cycle for the resonance cases. Furthermore, the differences in the admittances between the one- and two-dimensional microscale models are assessed for the purpose of understanding non-locality of the sheath near the wall surface for the parameters considered in this study. This information will be essential for improving the sheath BC for macroscale calculations in the future.</p>
High Cadance Radio Frequency Interference Filters
<p>SQL databases for synthetic and real pulse for the paper "High Cadence Radio Frequency Interference Filters".</p> <p>These databases contain Numpy array and can be read by http://stackoverflow.com/a/31312102/190597<br><br><a href="https://zenodo.org/api/records/6487651/draft/files/injected_pulse.db/content" target="_blank" rel="noopener noreferrer">injected_pulse.db</a> is the database for synthic pulses injected into GREENBURST observations. <br><br><a href="https://zenodo.org/api/records/6487651/draft/files/real_pulse.db/content" target="_blank" rel="noopener noreferrer">real_pulse.db</a> is the database for pulses from pulsars observed with GREENBURST.</p>
Data and code for "Observation and stabilization of photonic Fock states in a hot radio-frequency resonator"
<p>This folder contains all the code necessary to produce the figures of the paper entitled "Observation and stabilization of photonic Fock states in a hot radio-frequency resonator" written by Mario F. Gely, Marios Kounalakis, Christian Dickel, Jacob Dalle, Rémy Vatré, Brian Baker, Mark D. Jenkins and Gary A. Steele</p> <p><strong>Content: </strong></p> <p>data/<br> Contains multiple folders each corresponding to a measurement. <br> These are all time stamped. <br> Inside each of these folders is a python file which corresponds to the measurement script run using the open source STlab library (see version closest to the time stamp on https://github.com/steelelabgit/stlab).<br> There is also a DAT file containing the measurement data and an accompanying text file which provides the name and end values of the swept parameters<br> This data will be opened and manipulated in the ipython notebooks</p> <p>analysis_results/<br> Contains the results of the ipython notebooks _*.ipynb<br> These are run on a computer cluster and generate information used in other ipython notebooks</p> <p>adaptive_rwa_solver_bootstrap_diagonal*.py<br> Libraries used to run the adaptive rotating wave approximation simulations</p> <p>load_data.py<br> Modules used to load data from data/</p> <p>plotting_functions.py<br> Modules used to plot 3D data as well as to generate default matplotlib settings</p> <p>_*.ipynb<br> Notebooks run on a computer cluster (using python 2.7) to generate the information stored in analysis_results/ and used in other ipython notebooks</p> <p>1D_S4BC_S9.ipynb<br> Notebook which generates the figures 1D, S4(B,C) and S9 of the paper. <br> Other notebooks follow this same naming convention</p> <p>*.pdf<br> *.png<br> Plots generated from the ipython notebooks which are then imported in Adobe Illustrator to construct figures</p>
Low Frequency Radio Pulses Produced by Terrestrial Gamma-ray Flashes
<p>The data supports the manuscript entitled “Low Frequency Radio Pulses Produced by Terrestrial Gamma-ray Flashes<br> ” that is under review in GRL. These files can be opened by MATLAB. The data can be used freely for scientific purposes with appropriate citation.</p>
Data of "Multilayer spintronic neural networks with radio-frequency connections"
<p>This dataset corresponds to the open data of the publication <strong>"Multilayer spintronic neural networks with radio-frequency connections"</strong>.</p>
Assessment of the Effectiveness of Local Ablathermy Radio Frequency Bronchial Tumors Primitive
ClinicalTrials.gov study NCT01841060. IPD Sharing: NO. Countries: 1. Publications: 1.
Concomitant Utilization of Radio Frequency Energy for Atrial Fibrillation (CURE-AF) Study
ClinicalTrials.gov study NCT00431834. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Radio Frequency Microneedling for Suprapatellar Skin
ClinicalTrials.gov study NCT03507036. IPD Sharing: NO. Countries: 1. Publications: 5.
Measurement and modeling of the radio frequency sheath impedance in a large magnetized plasma
<p>The accompanying files contain digital data for figures in the article "Measurement and modeling of the radio frequency sheath impedance in a large magnetized plasma" by J. R. Myra, C. Lau, B. Van Compernolle, S. Vincena and J. Wright, submitted to the journal Physics of Plasmas.</p> <p><strong>Abstract</strong><br> The DC and RF properties of radio frequency (RF) driven sheaths were studied in the Large Plasma Device (LAPD) at the University of California, Los Angeles. The experiments diagnosed RF sheaths on field lines connected to a grounded plate at one end and an ion cyclotron range of frequencies (ICRF) antenna at the other end. The experimental setup permitted measurement of the RF sheath impedance at the plate as a function of DC sheath voltage, with the latter controlled by varying the RF current applied to the antenna. The DC current-voltage characteristics of these sheaths and the RF sheath impedance measurements were compared with modeling. Hot electrons, present in the LAPD plasma, were inferred to contribute significantly to both the DC and RF currents and hence the RF impedance. It was postulated that at very low power hot electrons could not access the region of the plasma subject to RF waves, resulting in an increased RF impedance. Within some experimental limitations and significant assumptions, an RF sheath impedance model was verified by the experimental data.</p>
Radio-Frequency Control and Video Signal Recordings of Drones
<p>This database contains <a href="https://en.wikipedia.org/wiki/In-phase_and_quadrature_components">IQ-baseband</a> recordings of 10 consumer/prosumer drones’ radio-control and video signals in an interleaved (I1 Q1 I2 Q2 I3 Q3 ...) 16-bit signed integer, little-endian, format. The drones were recorded at 2.44 GHz and 5.8 GHz center frequencies (with the exception of Yuneec Typhoon H at 5.7 GHz) if the drone supported both. In the dataset, these center frequencies were denoted with 2G and 5G in the filename, respectively. The sampling frequency was 120 MHz at 2.44 GHz and 200 MHz at 5.8 GHz. The recording length at 2.44 GHz was 120e6 samples, which corresponds to a recording period of 1 s and 100e6 samples at 5.8 GHz, which corresponds to a recording period of 0.5 s. </p> <p>The measurements were conducted in the isolated anechoic chamber of Tampere University, where the drones were on a turntable. The controller was next to the drone, and the measurement antenna was at the opposite side of the chamber. The published data are chosen in a way that a complete hopping sequence of the control signal is captured in each single recording, if possible. There were a few drones, for which two separate recordings were provided; these recordings are not consecutive, but it should be possible to combine them to extract the hopping sequence. Some drones also did not have a discernible pattern, or it was too long for our recording period. </p> <p>The recordings of the Parrot Mambo are separated into two files, since it was not possible to record a clean signal with simultaneously active video and control links. </p> <p>The following drone models are included in the first version of the database: </p> <ul> <li>DJI Inspire 2 (2.44 and 5.8 GHz) </li> <li>DJI Matrice 100 (2.44 GHz) </li> <li>DJI Matrice 210 (2.44 and 5.8 GHz) </li> <li>DJI Mavic Mini (2.44 GHz) </li> <li>DJI Mavic Pro (2.44 GHz) </li> <li>DJI Phantom 4 (2.44 GHz) </li> <li>DJI Phantom 4 Pro Plus (2.44 and 5.8 GHz) </li> <li>Parrot Disco (2.44 GHz) </li> <li>Parrot Mambo (2.44 GHz) </li> <li>Yuneec Typhoon H (2.44 and 5.7 GHz) </li> </ul> <p>For further information contact Jaakko Marin.</p>
Data from: How to quantify animal activity from radio-frequency identification (RFID) recordings
Automated animal monitoring via radio-frequency identification (RFID) technology allows efficient and extensive data sampling of individual activity levels, and is therefore commonly used for ecological research. However, processing RFID data is still a largely unresolved problem, which potentially leads to inaccurate estimates for behavioural activity. One of the major challenges during data processing is to isolate independent behavioural actions from a set of superfluous, non-independent detections. As a case study, individual blue tits (Cyanistes caeruleus) were simultaneously monitored during reproduction with both video recordings and RFID technology. We demonstrated how RFID data can be processed based on the time spent in- and outside a nest box. We then validated the number and timing of nest visits obtained from the processed RFID dataset by calibration against video recordings. The video observations revealed a limited overlap between the time spent in- and outside the nest box, with the least overlap at 23 seconds for both sexes. We then isolated exact arrival times from redundant RFID registrations by erasing all successive registrations within 23 seconds after the preceding registration. After aligning the processed RFID data with the corresponding video recordings, we observed a high accuracy in three behavioural estimates of parental care (individual nest visit rates, within-pair alternation and synchronization of nest visits). We provide a clear guideline for future studies that aim to implement RFID technology in their research. We argue that our suggested RFID data processing procedure improves the precision of behavioural estimates, despite some inevitable drawbacks inherent to the technology. Our method is useful, not only for other cavity breeding birds, but for a wide range of (in)vertebrate species that are large enough to be fitted with a tag and that regularly pass near or through a fixed antenna.
Measuring intraoperative surgical instrument use with radio-frequency identification
<p><strong>Objective:</strong> Surgical instrument oversupply drives cost, confusion, and workload in the operating room (OR). With an estimated 78-87% of instruments being unused, many health systems have recognized the need for supply refinement. By manually recording instrument use and tasking surgeons to review instrument trays, previous quality improvement initiatives have achieved an average 52% reduction in supply. While demonstrating the degree of instrument oversupply, previous methods for identifying required instruments are qualitative, expensive, lack scalability and sustainability, and are prone to human error. In this work, we aim to develop and evaluate an automated system for measuring surgical instrument use.</p> <p><strong>Materials and Methods:</strong> We present the first system to our knowledge that automates the collection of real-time instrument use data with radio-frequency identification (RFID). Over 15 breast surgeries, ten carpometacarpal (CMC) arthroplasties, and four craniotomies, instrument use was tracked by both a trained observer manually recording instrument use and the RFID system.</p> <p><strong>Results:</strong> The average Cohen's Kappa agreement between the system and the observer was 0.81 (near perfect agreement), and the system enabled a supply reduction of 50.8% in breast and orthopedic surgery. Over 10 monitored breast surgeries and one CMC arthroplasty with reduced trays, no eliminated instruments were requested, and both trays continue to be used as the supplied standard. Setup time in breast surgery decreased from 23 minutes to 17 minutes with the reduced supply.</p> <p><strong>Conclusion:</strong> The RFID system presented herein achieves a novel data stream that enables accurate instrument supply optimization.</p>
Discovery of 24 radio-bright quasars at 4.9<z<6.6 using low-frequency radio observations
<p>Properties of newly discovered high-z quasars (4.9<z<6.6) derived from photometric and spectroscopic observations. The radio measurements have been obtained using the LOFAR Two Metre Sky Survey (LoTSS-DR2; 144 MHz), VLA FIRST (1.4 GHz), and Very Large Array Sky Survey (VLASS; 2-4 GHz). The spectroscopic observations have been conducted using the Faint Object Camera and Spectrograph on the Subaru telescope, LRS2 on the Hobby-Eberly Telescope, and LRIS on Keck. The rest-frame UV magnitudes have been derived by combining the optical to mid-infrared observations and performing spectral energy distribution fitting using the template fitting code EAZY (Brammer et al 2008).</p>
Low Frequency Radio Pulses Produced by Terrestrial Gamma-ray Flashes
<p>The data supports the manuscript entitled “Low Frequency Radio Pulses Produced by Terrestrial Gamma-ray Flashes” that is published in GRL. These files can be opened by MATLAB. The data can be used freely for scientific purposes with appropriate citation.</p>
Data for '3D Radio Frequency Mapping and Polarization Observations Show Lightning is Ignited by Cosmic-ray Shower' by Shao et al., 2024
<p>Data for manuscript "<a name="_Hlk177653706"></a><strong><span>3D Radio Frequency Mapping and Polarization Observations Show Lightning is Ignited by Cosmic-ray Shower" <br></span></strong></p>
CopenHeartRFA - Integrated Rehabilitation of Patients Treated for Atrial Fibrillation With Radio Frequency Ablation
ClinicalTrials.gov study NCT01523145. IPD Sharing: NO. Countries: 1. Publications: 3.
Efficacy and Safety of Endovenous Radio Frequency (EVRF) for Treatment of Varicose Veins in Singapore
ClinicalTrials.gov study NCT04384315. IPD Sharing: NO. Countries: 1. Publications: 6.
Radio Frequency Ablation (RFA STUDY )
ClinicalTrials.gov study NCT02631278. IPD Sharing: Not stated. Countries: 1. Publications: 5.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.