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138 results for “Broadband”
Nonhuman Primate Reaching with Multichannel Sensorimotor Cortex Electrophysiology: broadband for indy_20160927_06
<p>This dataset supplements <a href="https://doi.org/10.5281/zenodo.583331">https://doi.org/10.5281/zenodo.583331</a> .<br> <br> <strong>General description.</strong> These data consist of extracellular neural recordings ("broadband") from primate subject "Indy", session identifier "indy_20160927_06".</p> <p><strong>Filtering. </strong>The data are sampled at 24414.0625 Hz and are unfiltered, except for an anti-aliasing filter built-in to the recording amplifier: a 4th order low-pass with a roll-off of 24 dB per octave at 7.5 kHz, operating at the sampling rate.</p> <p><strong>File format.</strong> The data are contained in an HDF5 formatted file, organized according to the <a href="https://github.com/NeurodataWithoutBorders/specification">Neurodata Without Borders (NWB) version 1.0.6</a> specification.</p> <p><strong>Datasets. </strong>A few of the relevant dataset paths are listed here for convenience. In the below, <em>n</em> refers to the number of recording channels and <em>k</em> refers to the number of samples.</p> <ul> <li>"/acquisition/timeseries/broadband/data" - k x n <ul> <li>The broadband neural recordings.</li> </ul> </li> <li>"/acquisition/timeseries/broadband/data/conversion" (scalar attribute) <ul> <li>When multiplied by each sample converts the data into units of volts.</li> </ul> </li> <li>"/acquisition/timeseries/broadband/timestamps" - k x 1 <ul> <li>Timestamps for each sample, seconds.</li> </ul> </li> <li>"/general/extracellular_ephys/electrode_map" - n x 3 <ul> <li>The relative coordinates of each electrode contact (x, y, z), meters.</li> </ul> </li> </ul> <p>Please refer to the <a href="https://doi.org/10.5281/zenodo.583331">master dataset</a> for further information.</p>
Nonhuman Primate Reaching with Multichannel Sensorimotor Cortex Electrophysiology: broadband for indy_20160927_04
<p>This dataset supplements <a href="https://doi.org/10.5281/zenodo.583331">https://doi.org/10.5281/zenodo.583331</a> .<br> <br> <strong>General description.</strong> These data consist of extracellular neural recordings ("broadband") from primate subject "Indy", session identifier "indy_20160927_04".</p> <p><strong>Filtering. </strong>The data are sampled at 24414.0625 Hz and are unfiltered, except for an anti-aliasing filter built-in to the recording amplifier: a 4th order low-pass with a roll-off of 24 dB per octave at 7.5 kHz, operating at the sampling rate.</p> <p><strong>File format.</strong> The data are contained in an HDF5 formatted file, organized according to the <a href="https://github.com/NeurodataWithoutBorders/specification">Neurodata Without Borders (NWB) version 1.0.6</a> specification.</p> <p><strong>Datasets. </strong>A few of the relevant dataset paths are listed here for convenience. In the below, <em>n</em> refers to the number of recording channels and <em>k</em> refers to the number of samples.</p> <ul> <li>"/acquisition/timeseries/broadband/data" - k x n <ul> <li>The broadband neural recordings.</li> </ul> </li> <li>"/acquisition/timeseries/broadband/data/conversion" (scalar attribute) <ul> <li>When multiplied by each sample converts the data into units of volts.</li> </ul> </li> <li>"/acquisition/timeseries/broadband/timestamps" - k x 1 <ul> <li>Timestamps for each sample, seconds.</li> </ul> </li> <li>"/general/extracellular_ephys/electrode_map" - n x 3 <ul> <li>The relative coordinates of each electrode contact (x, y, z), meters.</li> </ul> </li> </ul> <p>Please refer to the <a href="https://doi.org/10.5281/zenodo.583331">master dataset</a> for further information.</p>
Nonhuman Primate Reaching with Multichannel Sensorimotor Cortex Electrophysiology: broadband for indy_20160921_01
<p>This dataset supplements <a href="https://doi.org/10.5281/zenodo.583331">https://doi.org/10.5281/zenodo.583331</a> .<br> <br> <strong>General description.</strong> These data consist of extracellular neural recordings ("broadband") from primate subject "Indy", session identifier "indy_20160921_01".</p> <p><strong>Filtering. </strong>The data are sampled at 24414.0625 Hz and are unfiltered, except for an anti-aliasing filter built-in to the recording amplifier: a 4th order low-pass with a roll-off of 24 dB per octave at 7.5 kHz, operating at the sampling rate.</p> <p><strong>File format.</strong> The data are contained in an HDF5 formatted file, organized according to the <a href="https://github.com/NeurodataWithoutBorders/specification">Neurodata Without Borders (NWB) version 1.0.6</a> specification.</p> <p><strong>Datasets. </strong>A few of the relevant dataset paths are listed here for convenience. In the below, <em>n</em> refers to the number of recording channels and <em>k</em> refers to the number of samples.</p> <ul> <li>"/acquisition/timeseries/broadband/data" - k x n <ul> <li>The broadband neural recordings.</li> </ul> </li> <li>"/acquisition/timeseries/broadband/data/conversion" (scalar attribute) <ul> <li>When multiplied by each sample converts the data into units of volts.</li> </ul> </li> <li>"/acquisition/timeseries/broadband/timestamps" - k x 1 <ul> <li>Timestamps for each sample, seconds.</li> </ul> </li> <li>"/general/extracellular_ephys/electrode_map" - n x 3 <ul> <li>The relative coordinates of each electrode contact (x, y, z), meters.</li> </ul> </li> </ul> <p>Please refer to the <a href="https://doi.org/10.5281/zenodo.583331">master dataset</a> for further information.</p>
Nonhuman Primate Reaching with Multichannel Sensorimotor Cortex Electrophysiology: broadband for indy_20160916_01
<p>This dataset supplements <a href="https://doi.org/10.5281/zenodo.583331">https://doi.org/10.5281/zenodo.583331</a> .<br> <br> <strong>General description.</strong> These data consist of extracellular neural recordings ("broadband") from primate subject "Indy", session identifier "indy_20160916_01".</p> <p><strong>Filtering. </strong>The data are sampled at 24414.0625 Hz and are unfiltered, except for an anti-aliasing filter built-in to the recording amplifier: a 4th order low-pass with a roll-off of 24 dB per octave at 7.5 kHz, operating at the sampling rate.</p> <p><strong>File format.</strong> The data are contained in an HDF5 formatted file, organized according to the <a href="https://github.com/NeurodataWithoutBorders/specification">Neurodata Without Borders (NWB) version 1.0.6</a> specification.</p> <p><strong>Datasets. </strong>A few of the relevant dataset paths are listed here for convenience. In the below, <em>n</em> refers to the number of recording channels and <em>k</em> refers to the number of samples.</p> <ul> <li>"/acquisition/timeseries/broadband/data" - k x n <ul> <li>The broadband neural recordings.</li> </ul> </li> <li>"/acquisition/timeseries/broadband/data/conversion" (scalar attribute) <ul> <li>When multiplied by each sample converts the data into units of volts.</li> </ul> </li> <li>"/acquisition/timeseries/broadband/timestamps" - k x 1 <ul> <li>Timestamps for each sample, seconds.</li> </ul> </li> <li>"/general/extracellular_ephys/electrode_map" - n x 3 <ul> <li>The relative coordinates of each electrode contact (x, y, z), meters.</li> </ul> </li> </ul> <p>Please refer to the <a href="https://doi.org/10.5281/zenodo.583331">master dataset</a> for further information.</p>
Data: Effects of broadband sound exposure on the interaction between foraging crab and shrimp – a field study
<p>Data abstract:</p> <p>Data on foraging crabs and shrimps during trials with or without broadband sound exposures. Trials were conducted in situ using baited cameras.</p> <p> </p> <p>Paper abstract:</p> <p>Aquatic animals live in an acoustic world in which they often rely on sound detection and recognition for various aspects of life that may affect survival and reproduction. Human exploitation of marine resources leads to increasing amounts of anthropogenic sound underwater, which may affect marine life negatively. Marine mammals and fishes are known to use sounds and to be affected by anthropogenic noise, but relatively little is known about invertebrates such as decapod crustaceans. We conducted experimental trials in the natural conditions of a quiet cove. We attracted shore crabs (<em>Carcinus maenas</em>) and common shrimps (<em>Crangon crangon</em>) with an experimentally fixed food item and compared trials in which we started playback of a broadband artificial sound to trials without exposure. During trials with sound exposure, the cumulative count of crabs that aggregated at the food item was lower, while variation in cumulative shrimp count could be explained by a negative correlation with crabs. These results suggest that crabs may be negatively affected by artificially elevated noise levels, but that shrimps may indirectly benefit by competitive release. Eating activity for the animals present was not affected by the sound treatment in either species. Our results show that moderate changes in acoustic conditions due to human activities can affect foraging interactions at the base of the marine food chain.</p> <p> </p> <p>Reference:</p> <p>Hubert, J., Campbell, J., van der Beek, J.G., den Haan, M.F., Verhave, R., Verkade L.S., and Slabbekoorn H. (2018) Effects of broadband sound exposure on the interaction between foraging crab and shrimp - a field study. Environ. Pollut. 243, 1923–1929. DOI:10.1016/j.envpol.2018.09.076</p>
Nonhuman Primate Reaching with Multichannel Sensorimotor Cortex Electrophysiology: broadband for indy_20160915_01
<p>This dataset supplements <a href="https://doi.org/10.5281/zenodo.583331">https://doi.org/10.5281/zenodo.583331</a> .<br> <br> <strong>General description.</strong> These data consist of extracellular neural recordings ("broadband") from primate subject "Indy", session identifier "indy_20160915_01".</p> <p><strong>Filtering. </strong>The data are sampled at 24414.0625 Hz and are unfiltered, except for an anti-aliasing filter built-in to the recording amplifier: a 4th order low-pass with a roll-off of 24 dB per octave at 7.5 kHz, operating at the sampling rate.</p> <p><strong>File format.</strong> The data are contained in an HDF5 formatted file, organized according to the <a href="https://github.com/NeurodataWithoutBorders/specification">Neurodata Without Borders (NWB) version 1.0.6</a> specification.</p> <p><strong>Datasets. </strong>A few of the relevant dataset paths are listed here for convenience. In the below, <em>n</em> refers to the number of recording channels and <em>k</em> refers to the number of samples.</p> <ul> <li>"/acquisition/timeseries/broadband/data" - k x n <ul> <li>The broadband neural recordings.</li> </ul> </li> <li>"/acquisition/timeseries/broadband/data/conversion" (scalar attribute) <ul> <li>When multiplied by each sample converts the data into units of volts.</li> </ul> </li> <li>"/acquisition/timeseries/broadband/timestamps" - k x 1 <ul> <li>Timestamps for each sample, seconds.</li> </ul> </li> <li>"/general/extracellular_ephys/electrode_map" - n x 3 <ul> <li>The relative coordinates of each electrode contact (x, y, z), meters.</li> </ul> </li> </ul> <p>Please refer to the <a href="https://doi.org/10.5281/zenodo.583331">master dataset</a> for further information.</p>
Nonhuman Primate Reaching with Multichannel Sensorimotor Cortex Electrophysiology: broadband for indy_20160630_01
<p>This dataset supplements <a href="https://doi.org/10.5281/zenodo.583331">https://doi.org/10.5281/zenodo.583331</a> .<br> <br> <strong>General description.</strong> These data consist of extracellular neural recordings ("broadband") from primate subject "Indy", session identifier "indy_20160630_01".</p> <p><strong>Filtering. </strong>The data are sampled at 24414.0625 Hz and are unfiltered, except for an anti-aliasing filter built-in to the recording amplifier: a 4th order low-pass with a roll-off of 24 dB per octave at 7.5 kHz, operating at the sampling rate.</p> <p><strong>File format.</strong> The data are contained in an HDF5 formatted file, organized according to the <a href="https://github.com/NeurodataWithoutBorders/specification">Neurodata Without Borders (NWB) version 1.0.6</a> specification.</p> <p><strong>Datasets. </strong>A few of the relevant dataset paths are listed here for convenience. In the below, <em>n</em> refers to the number of recording channels and <em>k</em> refers to the number of samples.</p> <ul> <li>"/acquisition/timeseries/broadband/data" - k x n <ul> <li>The broadband neural recordings.</li> </ul> </li> <li>"/acquisition/timeseries/broadband/data/conversion" (scalar attribute) <ul> <li>When multiplied by each sample converts the data into units of volts.</li> </ul> </li> <li>"/acquisition/timeseries/broadband/timestamps" - k x 1 <ul> <li>Timestamps for each sample, seconds.</li> </ul> </li> <li>"/general/extracellular_ephys/electrode_map" - n x 3 <ul> <li>The relative coordinates of each electrode contact (x, y, z), meters.</li> </ul> </li> </ul> <p>Please refer to the <a href="https://doi.org/10.5281/zenodo.583331">master dataset</a> for further information.</p>
Nonhuman Primate Reaching with Multichannel Sensorimotor Cortex Electrophysiology: broadband for indy_20160627_01
<p>This dataset supplements <a href="https://doi.org/10.5281/zenodo.583331">https://doi.org/10.5281/zenodo.583331</a> .<br> <br> <strong>General description.</strong> These data consist of extracellular neural recordings ("broadband") from primate subject "Indy", session identifier "indy_20160627_01".</p> <p><strong>Filtering. </strong>The data are sampled at 24414.0625 Hz and are unfiltered, except for an anti-aliasing filter built-in to the recording amplifier: a 4th order low-pass with a roll-off of 24 dB per octave at 7.5 kHz, operating at the sampling rate.</p> <p><strong>File format.</strong> The data are contained in an HDF5 formatted file, organized according to the <a href="https://github.com/NeurodataWithoutBorders/specification">Neurodata Without Borders (NWB) version 1.0.6</a> specification.</p> <p><strong>Datasets. </strong>A few of the relevant dataset paths are listed here for convenience. In the below, <em>n</em> refers to the number of recording channels and <em>k</em> refers to the number of samples.</p> <ul> <li>"/acquisition/timeseries/broadband/data" - k x n <ul> <li>The broadband neural recordings.</li> </ul> </li> <li>"/acquisition/timeseries/broadband/data/conversion" (scalar attribute) <ul> <li>When multiplied by each sample converts the data into units of volts.</li> </ul> </li> <li>"/acquisition/timeseries/broadband/timestamps" - k x 1 <ul> <li>Timestamps for each sample, seconds.</li> </ul> </li> <li>"/general/extracellular_ephys/electrode_map" - n x 3 <ul> <li>The relative coordinates of each electrode contact (x, y, z), meters.</li> </ul> </li> </ul> <p>Please refer to the <a href="https://doi.org/10.5281/zenodo.583331">master dataset</a> for further information.</p>
Nonhuman Primate Reaching with Multichannel Sensorimotor Cortex Electrophysiology: broadband for indy_20160624_03
<p>This dataset supplements <a href="https://doi.org/10.5281/zenodo.583331">https://doi.org/10.5281/zenodo.583331</a> .<br> <br> <strong>General description.</strong> These data consist of extracellular neural recordings ("broadband") from primate subject "Indy", session identifier "indy_20160624_03".</p> <p><strong>Filtering. </strong>The data are sampled at 24414.0625 Hz and are unfiltered, except for an anti-aliasing filter built-in to the recording amplifier: a 4th order low-pass with a roll-off of 24 dB per octave at 7.5 kHz, operating at the sampling rate.</p> <p><strong>File format.</strong> The data are contained in an HDF5 formatted file, organized according to the <a href="https://github.com/NeurodataWithoutBorders/specification">Neurodata Without Borders (NWB) version 1.0.6</a> specification.</p> <p><strong>Datasets. </strong>A few of the relevant dataset paths are listed here for convenience. In the below, <em>n</em> refers to the number of recording channels and <em>k</em> refers to the number of samples.</p> <ul> <li>"/acquisition/timeseries/broadband/data" - k x n <ul> <li>The broadband neural recordings.</li> </ul> </li> <li>"/acquisition/timeseries/broadband/data/conversion" (scalar attribute) <ul> <li>When multiplied by each sample converts the data into units of volts.</li> </ul> </li> <li>"/acquisition/timeseries/broadband/timestamps" - k x 1 <ul> <li>Timestamps for each sample, seconds.</li> </ul> </li> <li>"/general/extracellular_ephys/electrode_map" - n x 3 <ul> <li>The relative coordinates of each electrode contact (x, y, z), meters.</li> </ul> </li> </ul> <p>Please refer to the <a href="https://doi.org/10.5281/zenodo.583331">master dataset</a> for further information.</p>
Nonhuman Primate Reaching with Multichannel Sensorimotor Cortex Electrophysiology: broadband for indy_20160622_01
<p>This dataset supplements <a href="https://doi.org/10.5281/zenodo.583331">https://doi.org/10.5281/zenodo.583331</a> .<br> <br> <strong>General description.</strong> These data consist of extracellular neural recordings ("broadband") from primate subject "Indy", session identifier "indy_20160622_01".</p> <p><strong>Filtering. </strong>The data are sampled at 24414.0625 Hz and are unfiltered, except for an anti-aliasing filter built-in to the recording amplifier: a 4th order low-pass with a roll-off of 24 dB per octave at 7.5 kHz, operating at the sampling rate.</p> <p><strong>File format.</strong> The data are contained in an HDF5 formatted file, organized according to the <a href="https://github.com/NeurodataWithoutBorders/specification">Neurodata Without Borders (NWB) version 1.0.6</a> specification.</p> <p><strong>Datasets. </strong>A few of the relevant dataset paths are listed here for convenience. In the below, <em>n</em> refers to the number of recording channels and <em>k</em> refers to the number of samples.</p> <ul> <li>"/acquisition/timeseries/broadband/data" - k x n <ul> <li>The broadband neural recordings.</li> </ul> </li> <li>"/acquisition/timeseries/broadband/data/conversion" (scalar attribute) <ul> <li>When multiplied by each sample converts the data into units of volts.</li> </ul> </li> <li>"/acquisition/timeseries/broadband/timestamps" - k x 1 <ul> <li>Timestamps for each sample, seconds.</li> </ul> </li> <li>"/general/extracellular_ephys/electrode_map" - n x 3 <ul> <li>The relative coordinates of each electrode contact (x, y, z), meters.</li> </ul> </li> </ul> <p>Please refer to the <a href="https://doi.org/10.5281/zenodo.583331">master dataset</a> for further information.</p>
Estimations of Sensor Misorientation for Broadband Seismic Stations in and around Africa
<p>To ensure the accuracy of future rotation-based seismological studies using data recorded by broadband seismic stations in Africa and environs, we investigate the sensor orientation of 1075 stations belonging to 41 seismic networks deployed in and around the African continent in the past three decades. We applied three independent waveform-based orientation estimation methods that involve the measurement of P-wave particle motion based on the principal component analysis, minimizing the P-wave energy on the transverse component of motion, and measuring intermediate-period Rayleigh-wave arrival angles from teleseismic earthquakes. This dataset is the compilation of the entire result of this study.</p>
A Broadband Fabry-Perot Cavity Antenna for WLAN and V2V Applications
<p><span>In this paper, a Fabry-Perot cavity (FPC) antenna with a partially reflective surface (PRS) consisting of two dielectric slabs with identical thickness and permittivity to increase the gain with wide bandwidth is presented. The PRS is placed in front of a broadband U-shaped microstrip patch antenna to create an air-filled cavity between the PRS and the ground plane of the antenna structure. The configuration of the two dielectric slabs aims to create a positive phase gradient of the reflection coefficient, which strongly controls the gain bandwidth performance. The proposed PRS was first designed and analyzed using a transmission line model and then verified by a full wave simulation. The measurement results show that the proposed FPC antenna achieves a gain improvement of up to 4 dB </span><span>compared to</span><span> the antenna without the PRS, with a 3-dB gain bandwidth of 15.25% and broadside peak gain of 10.43 dBi. In addition, the measured impedance bandwidth is approximately </span><span>20.25% and </span><span>ranges from </span><span>5.14 to 6.298 GHz, which covers the </span><span>required </span><span>f</span><span>requency band </span><span>of wireless local area network (WLAN) and vehicle-to-vehicle (</span><span>V2V) applications.</span></p>
Frozen sound: An ultra-low frequency, ultra-broadband, non-reciprocal acoustic absorber
<p>The files contains the main results found in the paper 'Frozen sound: An ultra-low frequency, ultra-broadband, non-reciprocal acoustic absorber'. </p> <p>Each file contain an absorption coefficient in the form of a vector with its corresponding frequency.</p> <p>TA: Refers to the thermoacoustic absorber, i.e in the presence of cooling.</p> <p>NoTA: Refers to the porous material without cooling.</p>
Broadband Laser-Induced Luminescence Generated in the Visible and Near-Infrared Ranges from Nontransparent CsPbCl3:Yb3+ Perovskite Ceramics
<p>ABSTRACT</p> <p>All inorganic perovskites with the general formula ABX<sub>3</sub> (A = alkaline cation, B = lead ions, and X = halide anion) in the form of colloids have become very popular in recent years due to their extraordinary spectroscopic properties, which can be additionally modulated by changing their structural composition. Here, we report for the first time a novel study considering nontransparent CsPbCl<sub>3</sub>:10%Yb<sup>3+</sup> ceramics that exhibit broadband laser-induced emission (LIE) with warm color (CRI = 96) upon exposure to a high-power-density infrared beam. It was found that the analyzed phenomenon strongly depends on the excitation power density and the pressure around the sample. Moreover, threshold behavior was observed, characterized by a significant increase in luminescence intensity already from the excitation of 0.2 W. The investigated material exhibits extremely strong photoconductivity. During the spectroscopic measurements of LIE, it was found that the current value varies by more than 4 orders of magnitude. Because of the relatively low sample temperature during the experiment, a LIE generation mechanism based on the creation of ytterbium mixed valence ion pairs and intervalence charge transfer (IVCT) transitions was proposed.</p>
Over-coupled resonator for broadband surface enhanced infrared absorption (SEIRA)
<p>This repository contains all datasets and MATLAB codes used in the paper "Over-coupled resonator for broadband surface enhanced infrared absorption (SEIRA)"</p> <p>3 folders can be found</p> <ul> <li>BMM contains a main python script that reproduces the electromagnetic computations of the article</li> <li>CMT : contains 3 scripts <ul> <li><strong>Absorption2D.m</strong> computes a 2D map of the absorption from the resonator from eq.1 of the main text as a function of f and (ω − ωr )/γnr .</li> <li><strong>DeltaRm.m</strong> plots the analytical expression of Delta Rm computed in the SI as a function of f.</li> <li><strong>DRanalytics.m</strong> plots the reflexion with the absorber as a function of omega. The expression is derived from the coupled mode formalism as described in the supplemental information.</li> </ul> </li> <li>Data_exp: contains raw experimental datasets of the figures.</li> <li>over_coupling_package : contains scripts to reproduce the electromagnetic simulations presented in the paper</li> </ul> <p>===============================</p> <p>PAPER ABSTRACT:</p> <p>Detection of molecules is a key issue for many applications. Surface enhanced infrared absorption (SEIRA) uses arrays of resonant nanoantennas with good quality factors which can be used to locally enhance the illumination of molecules. The technique has proved to be an effective tool to detect small amount of material. However nanoresonators can detect molecules on a narrow bandwidth so that a set of resonators is necessary to identify a molecule fingerprint. Here, we introduce an alternative paradigm and use low quality factor resonators with large radiative losses (over-coupled resonators). The bandwidth enables to detect all absorption lines between 5 and 10 µm, reproducing the molecular absorption spectrum. Counterintuitively, despite a lower quality factor, the system sensitivity is improved and we report a reflectivity variation as large as one percent per nanometer of molecular layer of PMMA. This paves the way to specific identification of molecules. We illustrate the potential of the technique with the detection of the explosive precursor 2,4-dinitrotoluene (DNT). There is a fair agreement with electromagnetic simulations and we also introduce an analytic model of the SEIRA signal obtained in the over-coupling regime.</p>
Broadband Sound and Sleep
ClinicalTrials.gov study NCT05774977. IPD Sharing: YES. Countries: 1. Publications: 6.
Broadband localization of light at the termination of a topological photonic waveguide
Open the record for dataset details and reuse information.
Physics Based Broadband Simulations for EarthquakeEarly Warning
<p>This data-set was generated for U.S. Geological Survey External Hazards Program award G19AP00010. It includes rupture models of the 2014 M8.1 Iquique, Chile earthquake as well as simulated ruptures on the Cascadia Subduction Zone. For each rupture there are also associated broadband (100Hz) waveforms. Details on how the ruptures and data were generated are available in the following publication:</p> <p>Goldberg, D. E., & Melgar, D. (2020). Generation and validation of broadband synthetic P waves in semistochastic models of large earthquakes. Bulletin of the Seismological Society of America, 110(4), 1982-1995</p>
CSRM Level 2 dataset: Seismometer orientation measurements of broadband seismic stations in the China Digital Seismograph Network
<p>This dataset contains detailed information on the azimuths of more than one thousand stations in the China Digital Seismic Network (CDSN) since 2014. Deng <em>et al</em>. (2024) utilized 5,456,816 three-component waveform data recorded by 1,056 broadband seismic stations of the CDSN from 2014 to 2022 to evaluate and correct the azimuths of the network. The primary research method employed was far-field <em>P</em>-wave polarization analysis, including principal component analysis and minimum tangential energy methods. By integrating the advantages of these two methods, they conducted a detailed analysis of the azimuths across the CDSN and carried out in-depth examinations and cause analyses for stations with significant azimuth deviations (>5°). Through a comprehensive analysis of the calculation results, network operation logs, and on-site inspections, they obtained detailed information on the azimuths of more than one thousand stations in the CDSN since 2014. <strong>Appendix I</strong> lists azimuth deviations for 956 stations, while <strong>Appendix II</strong> documents temporal variations in the azimuths for 104 stations.</p> <p>本数据库包含自 2014 年以来中国数字地震台网超过千个台站方位角的详细信息。Deng等 (2024) 依托中国数字地震台网 2014 至 2022 年间 1056 个宽频带地震台站所记录的 5,456,816 个三分量波形数据, 开展了台网方位角的评估与校正工作。研究方法主要采用远场 <em>P</em> 波偏振分析, 包括主成分分析和最小切向能量法。结合这两种方法的优点, 他们对中国数字地震台网的方位角进行了详细分析, 并对方位角偏差较大的台站 (>5°) 进行了深入检查与原因分析。通过对计算结果、台网运维日志及现场检查的综合分析, 他们获得了自 2014 年以来中国数字地震台网超过千个台站方位角的详细信息 (<strong>附件一</strong>列出了 956 个台站的方位角偏差, <strong>附件二</strong>记录了 104 个随时间变化的方位角信息) 。</p> <p><strong>Reference</strong>: Deng, W., Han, G., Li, J., & Sun, L. Seismometer Orientation Measurements of Broadband Seismic Stations in the China Digital Seismograph Network. <strong><a href="https://doi.org/10.1785/0120240075">Paper link</a></strong></p> <p>If you face any problem or issue in the usage of this dataset, please feel free to communicate with the corresponding author Juan Li (<strong>juanli@mail.iggcas.ac.cn</strong>).</p>
Broadband seismic constraints on the nature of the basement of the Junggar Basin, the southwestern Central Asian Orogenic Belt
<p>The cross-correlation function (CCF) of ambient noise recordings between two receivers under the equipartition assumption.</p> <p>Sacdir is a directory that stores cross-correlation functions between all pairs of seismic stations, with the output format in SAC.</p> <p>Sacdir contains the cross-correlation results of seismic data from 96 permanent stations and 59 temporary stations in the Xinjiang region, spanning 13 months from June 2021 to June 2022, totaling 11,935 pairs.</p> <p>The "CCFs-pairs.txt" file shows the table listing the geographic coordinates of the station pairs of all the CCFs files (in SAC-format) in the Sacdir directory. </p> <p>The processing program is modified from: [CC-FJpy: A Software Package for Ambient Noise Cross-Correlation and Frequency-Bessel Transform Method](https://github.com/ColinLii/CC-FJpy)</p>
ScienceDex guides
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Allen Brain Atlas
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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.