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83 results for “frequency response”
Preference ratings and 32 magnitude frequency response curves
<p>This repository comprises two CSV files: PreferenceRatings and MagnitudeFrequencyResponses. The former includes preference ratings obtained from 56 naive assessors (30 Danish---DK, 26 Japanese---JP) of 32 headphone curves over several music programs in several trials. The latter includes the magnitude frequency response curves evaluated by the assessors, expressed as gains of a 30-band graphic equalizer whose bands are centered between 31 Hz and 25 kHz. The curves were either derived from eight popular closed circumaural headphones, measured with a Brüel & Kjær Head and Torso Simulator 5128C, or otherwise obtained from the literature. The details of the methods, results, etc. are published in [1].</p> <p>[1] G. Ravizza, J. Villegas, T. Stegenborg-Andersen, and C. P. Volk, “An over-ear headphone target curve for Brüel & Kjær head and torso simulator type 5128 measurements,” in Proc. 155 Audio Eng. Soc. Conv., Oct 2023.</p> <p> </p>
Improvement of frequency responses of an in-plane electro-thermal cantilever sensor for real-time measurement (Data)
<p>Origin projects, figures and COMSOL simulation used for the article "Improvement of frequency responses of an in-plane electro-thermal cantilever sensor for real-time measurement", published in <em>Journal of Micromechanics and Microengineering </em>on 05 Nov 2019.</p>
Classification and frequency of climate change drivers and responses of small-scale fishers found in literature review
<p>Climate change hazards were classified into resource availability and fishing operations or both following the framework proposed by Cheung et al (2012). Response units were firstly classified into overarching responses and then categorized as suggested by the adaptive-transformative framework of Barnes et al.<sup> </sup>(2020). Adaptation units that did not represent an active adaptation response were classified as remaining. More than one hazard could be attributed to each fishers' response.</p>
Enhancement of unsteady frequency responses of electro-thermal resonance MEMS cantilever sensors (Data)
<p>Origin projects and figures used for the article "Enhancement of unsteady frequency responses of electro-thermal resonance MEMS cantilever sensors", published in the proceedings of the 30th Micromechanics and Microsystems Europe Workshop; 18.08.2019 to 20.08.2019; Wolfson College, Oxford, United Kingdom.</p>
Data to reproduce the results presented in Sehgal et al. 2022. Water Resources Research, https://doi.org/10.1029/2021WR030624 ("Inferring suspended sediment carbon content and particle size at high-frequency from the optical response of a submerged spectrometer")
<p>This repository consists data to reproduce results as presented in: "Inferring suspended sediment carbon content and particle size at high-frequency from the optical response of a submerged spectrometer", Water Resorces Research. Kindly refer to the readme.text file to navigate through the dataset.</p> <p> </p> <p> </p>
Room Impulse Responses for Low-Frequency Sound Field Control
<h2>About</h2> <div> <div> <div> <p>A dataset of room impulse responses (RIRs) measured in the low frequency range, for different measurement signal lengths, in two rooms with different acoustic conditions. Acquired with the purpose of low-frequency sound zones rendering and evaluation, the dataset can be used in general for different sound field control methods.</p> <p>By design, the dataset is composed of two sets of RIRs: one intended for the design of the control strategies, and another one intended for evaluation [1]. The RIRs of the first set, obtained with measurement signals of different length, allow exploring the influence of the acquisition time of the RIRs in the control methods [2]. The RIRs of the second set allow evaluating the sound field generated at and around the position of the RIRs of the first set.</p> <p>The RIRs were acquired with the Synchronized Swept-Sine (SSS) method, proposed by Novak et al. [3], at a samplig frequency of 48 kHz with SSS signals varying from 15 Hz to 600 Hz. The obtained RIRs were re-sampled to 1.2 kHz.</p> <p>Two files with different contents have been added:</p> <ul> <li><strong>RIR_LF_SFC_Light:</strong> contains the documentation, MatLab codes, and the ready-to-use RIRs stored as 3D-arrays in .mat files.<br><br></li> <li><strong>RIR_LF_SFC_Full:</strong> in addition to files in <strong>RIR_LF_SFC_Light</strong>, it contains the original SSS signals and the signals recorded during the measurements. These were used to retrieve the RIRs and therefore, can be used for custom purposes. <br><br></li> </ul> </div> </div> </div> <div> <h2>Citation</h2> <p>Please cite the database with the following paper:</p> <p>@inproceedings{cadavid_ATvsSS_2024,<br>title={Spatial Sampling versus Acquisition Time of Room Impulse<br> Responses for Low-Frequency Sound Zones},<br> author={Cadavid, Jos{\'e} and M{\o}ller, Martin Bo and van Waterschoot, Toon and Bech, S{\o}ren and {\O}stergaard, Jan},<br> booktitle={Audio Engineering Society Convention 156},<br> year={2024},<br> organization={Audio Engineering Society} }</p> <h2>Acknowledgements</h2> <p>The authors would like to thank <a href="https://orcid.org/0000-0002-1452-2227" target="_blank" rel="noopener">Antonin Novak</a>, <a href="https://orcid.org/0000-0002-2175-6603" target="_blank" rel="noopener">Christian S. Pedersen</a>, and Claus Vestergaard for their help with the RIRs measurements.</p> <p>This project has received funding from the European Union’s (EU) Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Actions Grant No. 956369.</p> </div>
BRAIN Journal-Novel Detection Features for SSVEP Based BCI: Coefficient of Variation and Variation Speed-Figure 1: Time vs frequency analysis of 10 Hz SSVEP response
<p>The stability of the SSVEP signal was examined by using wavelet analysis (Wu and Yao 2008). Since there is a trade-off between time and frequency resolution in wavelet analysis, examining the stability of SSVEP with wavelet analysis is getting harder in systems where the visual stimulus frequencies are close to each other, as shown in Figure 1. </p>
High frequency somatosensory MEG: evoked responses, FreeSurfer reconstruction
<p>This dataset contains somatosensory evoked responses recorded with Elekta TRIUX magnetoencephalography (MEG) system. The purpose of the measurements was to examine high-frequency (HF) somatosensory responses. To this end, a large number of responses (couple of thousand) were recorded with a short interstimulus interval (randomized between 300-350 ms). A constant-current electric stimulator was used, with the electrodes placed around the median nerve at the right wrist. The magnitude of the current was individually determined so that the stimulation was slightly below motor threshold; it was approximately 7 mA. The length of the current pulse was set at 200 microseconds.</p> <p>Measurements from two subjects are included. The dataset also contains anatomical MRIs and FreeSurfer reconstructions. Only evoked (averaged) MEG data is included; raw MEG data is in a separate dataset at https://doi.org/10.5281/zenodo.889295</p> <p> </p>
Resources for "BMF CP 97: The roles of health information-seeking ability and e-health literacy in illness response capability and health checkup frequency"
<p><span>The current study is conducted to examine the following research questions:</span></p> <ul> <li><span>How are health information-seeking ability and e-health literacy associated with illness response capability?</span></li> <li><span>How are health information-seeking ability and e-health literacy associated with the frequency of health checkups?</span></li> </ul>
EEG Dataset for 'Decoding of selective attention to continuous speech from the human auditory brainstem response' and 'Neural Speech Tracking in the Theta and in the Delta Frequency Band Differentially Encode Clarity and Comprehension of Speech in Noise'.
<p>The repository contains the unprocessed EEG data recorded for the publications [1, 2]. For convenience, the onsets of the EEG data provided here are time-aligned with the onsets of the audio books in the 'audiobooks' folder, and the EEG data are provided in HDF5 format. Please refer to the original version of this dataset for more details.</p> <p>More details, as well as the original data files, are available at the original repository <a href="https://doi.org/10.5281/zenodo.7086209">here</a>.</p> <p>Examples of using these data (preprocessing, fitting linear models) can be found <a href="https://github.com/Mike-boop/trf-examples">here</a>.</p> <p>The English conditions (clean, lb, mb, hb, fM, fW) comprised a single recording session. The Dutch conditions (cleanDutch, lbDutch, mbDutch, hbDutch) comprised a separate recording session. You see which participants took part in each session in session_info.json.</p> <p>Please note some details about the stimulus presentation for the various listening conditions:</p> <ul> <li>English speech-in-babble-noise (lb, mb, hb): babble noise was played by itself for one second before the audiobook track began. The babble noise was also played for one second after the audiobook track ended. Therefore, you should discard the first second and the last second from these trial during your analysis.</li> <li>Dutch speech-in-babble-noise (lbDutch, mbDutch, hbDutch): the story (narrated in Dutch) was played by itself for one second before the babble noise track began. Then, the babble noise was increased linearly in amplitude for one second. Therefore, you should discard the first two seconds from these trials during your analysis.</li> <li>Dutch in quiet, and Dutch-in-babble-noise (cleanDutch, lbDutch, mbDutch, hbDutch): some English sentences were embedded in the Dutch narratives in order to encourage attention. You should crop these from your analysis. The onsets and offsets of the English sentences (in samples, at 44100Hz) are provided in the audiobooks/*Dutch/english_onsets_info.json files.</li> <li>Competing-speakers conditions (fM, fW): sometimes the attended track is longer than the unattended track, or vice-versa. The onsets of both tracks are aligned. You should crop the trial to the length of the shortest track for your analysis.</li> </ul> <p>If you use this data, please cite the original publications, as well as this repository [1,2,3].</p> <p>[1] Etard O, Kegler M, Braiman C, Forte A E and Reichenbach T. “Decoding of selective attention to continuous speech from the human auditory brainstem response” 2019. <em>NeuroImage</em> <strong>200</strong> 1–11</p> <p>[2] Etard O and Reichenbach T. “Neural speech tracking in the theta and in the delta frequency band differentially encode clarity and comprehension of speech in noise” 2019. <em>J. Neurosci.</em> <strong>39</strong> 5750–9</p> <p>[3] Etard O and Reichenbach T. "EEG Dataset for 'Decoding of selective attention to continuous speech from the human auditory brainstem response' and 'Neural Speech Tracking in the Theta and in the Delta Frequency Band Differentially Encode Clarity and Comprehension of Speech in Noise". Doi: 10.5281/zenodo.7086208</p>
Dataset: Formulation and Implementation of Frequency-Dependent Linear Response Properties with Relativistic Coupled Cluster Theory for GPU-accelerated Computer Architectures
<p>This dataset collects the data (outputs, coordinate files) for the calculations presented in the manuscript "Formulation and Implementation of Frequency-Dependent Linear Response Properties with Relativistic Coupled<br> Cluster Theory for GPU-accelerated Computer Architectures".</p>
Dataset: Frequency-Dependent Quadratic Response Properties and Two-photon Absorption from Relativistic Equation-of-Motion Coupled Cluster Theory
<p>This dataset comprises outputs and post-processing results related to the paper "Frequency-Dependent Quadratic Response Properties and Two-photon Absorption from Relativistic Equation-of-Motion Coupled Cluster Theory", by Xiang Yuan, Loic Halbert, Lucas Visscher and Andre Severo Pereira Gomes.</p>
Data from: Plant-bacteria-soil response to frequency of simulated nitrogen deposition has implications for global ecosystem change
<ol> <li><span>Atmospheric nitrogen (N) deposition, generally, has been simulated through a single or relatively few N applications per year for its ecological effect study. Despite the importance of timing in ecosystem processes, ecological experiments with more realistic N addition frequencies are rare.</span></li> <li><span>We employed a novel design with typical twice (2X) vs. atypical monthly (12X) N applications per year to explore effects of N addition frequency on above- and below-ground biodiversity and function. </span></li> <li><span>Each year, several response variables from either belowground or aboveground growth, N status and cycling, or plant and bacterial diversity differed as a result of N addition frequency. BNPP showed a large frequency effect in the relatively moist year but not in the dry year. Nitrogen addition decreased root growth in the monthly relative to the biannual applications, which could be highly consequential for predicting changes in global carbon and nitrogen cycling. Simulated N deposition tended to perturb biodiversity, but it is noteworthy that 12X applications that spread N deposition more evenly through a year have much less negative impacts on plant and bacterial diversities than 2X amendments per year. Soil N mineralization rate in year 6 was much lower when N additions were monthly compared with a biannual amendment, especially when simulated N deposition was high. </span></li> <li><span>We have established that amendment frequency matters for understanding ecosystem response to N deposition. Experiments that more closely mimic the anthropogenic process of N deposition are needed to best assess ecosystem and potential global biogeochemical changes.</span></li> </ol>
Hibernating female big brown bats (Eptesicus fuscus) adjust huddling and drinking behaviour, but not arousal frequency, in response to low humidity
<p>Many mammals hibernate during winter, reducing energy expenditure via bouts of torpor. The majority of a hibernator's energy reserves are used to fuel brief, but costly, arousals from torpor. Although arousals likely serve multiple functions, an important one is to restore water stores depleted during torpor. Many hibernating bat species require high humidity, presumably to reduce torpid water loss, but big brown bats (<em>Eptesicus fuscus</em>) appear tolerant of a wide humidity range. We tested the hypothesis that hibernating female <em>E. fuscus </em>use behavioural flexibility during torpor and arousals to maintain water balance and reduce energy expenditure. We predicted: (1) <em>E. fuscus </em>hibernating in dry conditions would exhibit more compact huddles during torpor and drink more frequently than bats in high humidity conditions; and (2) frequency and duration of torpor bouts and arousals, and thus, total loss of body mass would not differ between bats in both environments. We housed hibernating <em>E. fuscus</em> in temperature- and humidity-controlled incubators at 50% or 98% relative humidity (8°C, 110 days). Bats in the dry environment maintained a more compact huddle during torpor and drank more frequently during arousals. Bats in both environments<em> </em>had a similar number of arousals, but arousal duration was shorter in the dry environment. However, total loss of body mass over hibernation did not differ between treatments indicating that both groups used similar amounts of energy. Our results suggest that behavioural flexibility allows hibernating <em>E. fuscus</em> to maintain water balance and reduce energy costs across a wide range of hibernation humidities.</p>
Dataset for publication: Test Bench and Frequency Response of a Magnetic Antenna used in GIS PD Measurements
<p>Data set belonging to the <a href="https://ieeexplore.ieee.org/xpl/conhome/9611374/proceeding">2021 IEEE Electrical Insulation Conference (EIC)</a> paper with DOI: <a href="https://doi.org/10.1109/EIC49891.2021.9612372">10.1109/EIC49891.2021.9612372</a></p> <p>The authors preprint is available from Zendodo with DOI: <a href="https://doi.org/10.5281/zenodo.5815710">10.5281/zenodo.5815710</a>. </p> <p>Mier Escurra, Christian; Mor, Armando Rodrigo</p> <p><em>Test Bench and Frequency Response of a Magnetic Antenna used in GIS PD Measurements</em></p>
Supporting data for "The high-frequency tidal response of ocean worlds: Application to Europa and Ganymede"
<p>Data files containing the static Love numbers that are used to compute the dynamic Love numbers.</p> <p> </p>
Global responses of plant abundance, diversity, and fitness to increased fire severity or frequency
<p>Database of responses of plant abundance, diversity, and fitness to increased fire frequency or severity, collected from published scientific articles or reports. The database includes 394 studies published worldwide between 1962 and 2023. Information on the following variables are also provided: fire regime component (fire frequency or severity), time since the last fire, fire type (wildfire or prescribed fire), historical fire regime type (surface or crown fire), plant life form (woody plant, herb, or bryophyte), habitat type, and climate. The database underpins the meta-analysis 'Global plant responses to intensified fire regimes', published in Global Ecology and Biogeography.</p>
Exploring the relation between fundamental frequency and spectral envelope in the perception of musical instrument sounds – sound files and participant responses
<p>This database contains synthesized instrument sounds (sounds.zip), participant responses (data.zip), and a key for the stimulus order (stimKey.zip) as complementary data to [1].</p> <p>Sounds include individual stimuli for two experiments. Experiment 1 contains stimuli used for sound pleasantness and sound brightness ratings. Every rating scale includes three acoustic conditions: congruent, incongruent, and fixed, corresponding to the relation of fundamental frequency (F0) and spectral envelope (SE). See [1] for further details on this matter. Experiment 2 contains stimuli for four synthesized instrument sounds: violin, alto voice, clarinet, and tuba. Sounds were synthesized using congruent spectral envelopes (all), and register fixed spectral envelopes (low, mid, high).</p> <p>All sounds are mono signals with a sampling frequency of 44100 Hz in WAV format.</p> <p>Data includes four sets of participant response data: sound pleasantness ratings (Exp. 1), sound brightness ratings (Exp. 1), sound pleasantness ratings (Exp. 2), and sound plausibility ratings (Exp. 2).</p> <p>StimKey provides values for the first and second principal components of the synthesis space for the pleasantness (1 to 81) and brightness (1 to 16) stimulus numbers for Exp. 1.</p> <p> </p> <p>Names convention for Exp. 2 sounds:</p> <p>InstrumentName_congruencyCondition_F0..wav</p> <p> </p> <p>References:</p> <p>[1] Jacobsen, S. and Siedenburg, K. (2024). Exploring the relation between fundamental frequency and spectral envelope in the perception of musical instrument sounds. Acta Acustica, 8, 48. <a href="https://doi.org/10.1051/aacus/2024038">https://doi.org/10.1051/aacus/2024038</a>.</p>
FrID: Frequency response based identification
<p>Measurements accompayning our article [1] and the repository https://github.com/tbreunung/FrID</p> <p>The folder 'MagMechOsci.zip' contains scripts and data for the magneto-mechanical oscillators studies in Section 3.1. These incldue</p> <ul> <li>Single degree-of-freedom configuration (subfolder: SDOF)</li> <li>Two and three degree-of-freedom configurations (subfolders: Three_Beams and Two_Beams>Separated Modes)</li> <li>Internally resonant configuration (subfolder: Two_Beams>Internal Resonance)</li> </ul> <p>The folder 'ClampedOsci.zip' contains scripts and data for the oscillator with campling nonlinearities studied in Section 3.2 of [1]. </p> <p>In <a href="https://www.youtube.com/watch?v=ggWzUJM4XPM">this tutorial</a> I walk you through the steps on how to use FrID. </p> <p>Consider also listening to <a href="https://www.youtube.com/watch?v=8cQhZ5BIbz4">my research talk</a> on this topic. </p> <p>[1] Breunung, T., & Balachandran, B. (2024). Frequency response based identification of nonlinear oscillators. <em>Journal of Sound and Vibration</em>, 118651. <a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.jsv.2024.118651" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.jsv.2024.118651</a></p>
Data set for "Multi-frequency SuperDARN HF radar observations of the ionospheric response to the October 2023 annular solar eclipse"
<p>This data set contains rawACF and sounding mode data files from the Christmas Valley East (CVE) SuperDARN radar and manually scaled ionogram parameters from the Boulder (BC840) Digisonde used in the paper "Multi-frequency SuperDARN HF radar observations of the ionospheric response to the October 2023 annular solar eclipse" submitted to Geophysical Research Letters.</p>
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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.