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1,300 results for “Sounds”
FIG. 4 in Greek khrόmis between sound and smell. Anthropozoology of a fish
FIG. 4. — Brown meagres (Sciaena umbra Linnaeus, 1758) in their natural environment (Image E. Sáez Goñalons & V. Martínez Moll, wikimedia.org; CC BY 3.0).
FIG. 2. — A in Greek khrόmis between sound and smell. Anthropozoology of a fish
FIG. 2. — A, Round-based zither (kithára). Detail from a red-figure vase painting, about 430 BCE – cf. Lexicon Iconographicum Mythologiae Classicae, Apollon 691a (Image by the author); B, Wide-eyed flounder, Bothus podas (Delaroche, 1809), a fish called kítharos by the ancient Greeks for its similarity to a roundbased kithára. Cf. Guasparri 2005: 216 (Image courtesy of Laguna Project).
FIG. 1 in Greek khrόmis between sound and smell. Anthropozoology of a fish
FIG. 1 — Definiens and definiendum: a human finger compared to Solen marginatus Pulteney, 1799, one among other mollusks called dáktulos (lit. 'finger'), or όnux (lit. 'nail') in Ancient Greek – e.g., Thompson 1947: 184 (Image by the author).
FIG. 6. — A in Greek khrόmis between sound and smell. Anthropozoology of a fish
FIG. 6. — A Mediterranean damselfish (Chromis chromis (Linnaeus, 1758)) in its natural environment (Image A. Kok, wikimedia.org;
Encounters in the Republic of Heaven [attached sound examples]
<p>Sound examples attached to the article by Trevor Wishart <em>Encounters in the Republic of Heaven </em></p>
PsPM-SCRV7: Skin conductance responses to white noise sounds in quick succession
<p>This dataset includes skin conductance response (SCR) measurements for each of 22 healthy unmedicated participants (11 males and 11 females aged 24.7+/-4.5 years) in response to white noise stimulation (1s length; 10ms ramp; ~85dB) under 5 experimental conditions: single stimuli, double stimuli with ISI of 2.5s, 5.5s or 9s and triple stimuli with ISIs randomly determined to be 2s, 5.5s or 9s.</p>
PsPM-SCRV2: Skin conductance responses to loud sounds at different inter trial intervals.
<p>This dataset includes skin conductance response (SCR) measurements, keypress responses and keypress response times to acoustic stimuli for each of 24 healthy unmedicated participants (12 males and 12 females aged 24+/-4.6 years, identical sample as in SCRV_1). The stimuli are 1s long white noise bursts at 95dB presented over headphones. Mean ISI is varied in a block-wise fashion (3s, 9s, 19s). The experiment follows a single factorial design with three levels of the mean ISI.</p>
PsPM-SCRV10: Skin conductance responses to loud sounds, simultanously recorded from palm, fingers and foot
<p>This dataset includes skin conductance response (SCR) measurements recorded from 3 locations (see section 'Data files' below) for each of 26 healthy unmedicated participants (12 males and 14 females aged 24.4+/-4.9 years) in response to an auditory stimulus (single white noise bursts, 1s length; 10ms ramp; ~85dB). Participants are asked to press a foot pedal upon hearing a stimulus.</p>
PsPM-SCRV3: Skin conductance responses to loud sounds and aversive/neutral pictures.
<p>This dataset includes skin conductance response (SCR) measurements, keypress responses and keypress response times to acoustic and visual stimuli for each of 22 healthy unmedicated participants (11 males and 11 females aged 22+/-4.8 years. The auditory stimuli are 1s long white noise bursts at 95dB presented over headphones. Visual stimuli are aversive pictures drawn from the International Affective Picture System. ITI are selected randomly on each trial from 29s, 34s or 39s.</p>
Rising tones and rustling noises: metaphors in gestural depictions of sounds
<p>Data for the observational and the experimental study. The quality of the video has been downsized to make the sharing tractable. </p> <p>Videos are arranged by referent sound. The filenames follow this format: subject number_referentsound.mp4</p>
Dataset supplementing the publication Einhäuser, W., Thomassen, S., & Bendixen, A. (2017). Using binocular rivalry to tag foreground sounds: towards an objective visual measure for auditory multistability. Journal of Vision, 17:34, 1-19.
<p>These files supplement the publication Einhäuser, W., Thomassen, S., & Bendixen, A. (2017). Using binocular rivalry to tag foreground sounds: towards an objective visual measure for auditory multistability. Journal of Vision, 17:34, 1-19. The data are free for scientific use, provided this reference is appropriately cited.</p> <p>exp1_data.mat contains all the data of experiment 1 as cell arrays of size 8x16x8 (subject x block x trial) or 8x16 (subject x block). Specifically:<br> xEye: the horizontal eye position in raw (pixel coordinates)<br> gain: the OKN slow phase gain computed from the xEye data as described in the paper; in audio-visual blocks the sign is chosen such that positive gain corresponds to the direction of the grating associated with the low tone; in unambiguous visual blocks (1,16) positive sign corresponds to the direction of the grating.<br> ixLow, ixHigh, ixNone, ixBoth: indices for xEye and gain of the same subject and block for which the button corresponding to the low tone, the high tone, both buttons or no button was pressed.</p> <p>exp2_data.mat and exp3_data.mat contain the data of experiment 2 and experiment 3, respectively, and are organized analogously to exp1_data.mat.</p> <p>figure3.m through figure6.m use these data to plot the respective paper figures to exemplify usage of the data.</p> <p> </p>
Rising tones and rustling noises: metaphors in gestural depictions of sounds. Data
<p>Data for the article. </p> <p>The file ObservationalData.mat contains the following variables:</p> <p>- Data is 4 x 8 x 10 x 3 x 10 matrix. Dimension 1 corresponds to the four annotators. Dimension 2 corresponds to the 8 referent sounds. Dimension 3 corresponds to the 10 imitators. Dimension 4 corresponds to the three response fields. Dimension 5 corresponds to the different possible answers. When the content of the matrix is 0, it means that the annotator has not indicated this answer for this particular sound and response field. When the content of the matrix is 1, this means that the annotator has selected this answer.</p> <p>- Annotators is the list of annotators: 'HS4' 'OH4' 'GL4' 'PS2'</p> <p>- SoundNames is the list of sound names: ‘Upward sweep' 'Downward sweep' 'Stationnary noise' 'Scraping' 'Filling' 'Door' 'Refrigerator' 'Printer'</p> <p>- Imitators are the imitator IDs: '08' '16' '20' '22' '25' '26' '28' '29' '30' '32'</p> <p>- Fields are the field names: 'Main gestural features' 'Main vocal features' 'Direction of the gestures'</p> <p>- NMax are the number of possible answers for each field: 10, 8, 7</p> <p> </p> <p> </p> <p> </p> <p>Data for the experimental study are stored in two files: GesturalDescriptor.txt and VocalDescriptor.txt</p> <p>Each file is a table, where each row is an observation: one imitator imitating one referent sound. The columns correspond to the imitators, the referent sounds, the factors (granularity, profile, and toneless), and the features.</p>
Data for H Wierstorf, Perceptual Assessment of Sound Field Synthesis, PhD thesis, TU Berlin, (2014)
<p>This publication contains data that was used to generate figures in the thesis:</p> <p>H. Wierstorf, Perceptual Assessment of Sound Field Synthesis, PhD thesis, TU Berlin, (2014), http://dx.doi.org/10.14279/depositonce-4310</p> <p>The code to generate all the figures is available at https://github.com/hagenw/phd-thesis excluding the data provided by this data set. The data contains no measured data, but the result of numerical simulations for which the actual code to generate it, is also part of the repository at github.</p>
Fig. 1 in Scaling of Sound Pressure Level and Body Size in Cicadas (Homoptera: Cicadidae; Tibicinidae)
Fig. 1. Mean call sound pressure level (SPL) at 50 cm as a function of mean body mass for 30 cicada species. Call SPL was calculated from the mean power output determined for each species (n = 1 -40). Body mass is the mean value determined for the males of each species, not the specific individuals that were calling (n = 9-223).
Fig. 2 in Scaling of Sound Pressure Level and Body Size in Cicadas (Homoptera: Cicadidae; Tibicinidae)
Fig. 2. Alarm call SPL as a function of body mass. The alarm calls were measured 50 cm from individual insects using the apparatus described. Each cicada was rotated in space while producing the alarm call to eliminate any variation between species caused by possible asymmetries in the sound field.
Evolutionary novelties underlie sound production in baleen whales
<p>Experimental and modelling data from the paper "Evolutionary novelties underlie sound production in baleen whales." </p>
Asteroseismic Inversions for Internal Sound Speed Profiles of Main-sequence Stars with Radiative Cores
<p>This repository contains the accompanying inlists and run_star_extras files for Buchele et al. (2024): Asteroseismic Inversions for Internal Sound Speed Profiles of Main-sequence Stars with Radiative Cores.</p> <p> </p> <p>The MESA version used is r22.05.1. We have modified the /star/private/pulse_fgong.f90 file in the MESA source code to output the Gamma1 derivatives that are necessary to compute u-Y kernels by replacing the file with the version from <a href="https://github.com/MESAHub/mesa/pull/431">https://github.com/MESAHub/mesa/pull/431</a>. Additionally, we use the MESA SDK versions 22.6.1 and the GYRE version 6.0 that is included with the r22.05.1 release of MESA. </p> <p> </p> <p>The directory grid_base contains the inlist which set the parameters that do not change across the tracks of our grid</p> <p> </p> <ul> <li> <p>Inlist_all includes parameters that are constant across all tracks and evolutionary stages </p> </li> <li> <p>Inlist_prems includes parameters for the pre-main sequence evolution of all tracks </p> </li> <li> <p>Inlist_ms includes parameters for the main sequence evolution of all tracks </p> </li> <li> <p>run_star_extras.f90 includes the code which stops the evolution of a track when the central hydrogen abundance reaches the target value </p> </li> <li> <p>gyre.in includes parameters for calculating of frequencies using GYRE</p> </li> </ul> <p> </p> <p>The directory reference_models provides the inlists to generate our reference model for each star in our sample. This directory also includes the FGONG structure files of the computed reference models. Each file is labeled with the identifier used in the text, typically the KIC number. </p> <p> </p> <p>The physics_tweaks directory provides the inlists to generate the models with modified input physics. The suffixes refer to the physics that was changed in each model, as follows: </p> <ul> <li> <p>core_kap: Core opacity</p> </li> <li> <p>pp2: change to the He3+He4->Be7 reaction rate</p> </li> <li> <p>cno: change to the N14 + p -> O15. </p> </li> </ul>
Supplementary material for "Mutual predictiveness of sound correspondences for reconstruction and language subgrouping: The case of Gyalrongic preinitials"
<p>This is the supplementary material of the paper "Mutual predictiveness of sound correspondences for reconstruction and language subgrouping: The case of Gyalrongic preinitials", to be published in Diachronica. It includes the datasets, codes and images involved in the research. Publication is still several months away, and I am trying to collect and identify more cognates as well as correct mistakes. </p> <p>Version 2 has included a few more cognates. I have added a file explaning my cognate judgements and annotations, and removed some doubtful forms after verification with native speakers. </p> <div> <div> <div> <div> <p>Comments, corrections and suggestions about cognate judgement, annotation and bibliographical references are welcome. I will correct and update the data from time to time.</p> </div> </div> </div> </div> <p> </p>
Supporting Data for Figures in "Localized, tidal energy extraction in Puget Sound can adjust estuary resonance and friction, modifying barotropic tides system-wide"
<p>Supporting data for figures in "Localized, tidal energy extraction in Puget Sound can adjust estuary resonance and friction, modifying barotropic tides system-wide" by Preston S. Spicer, Parker MacCready, and Zhaoqing Yang. The manuscript is being considered for publication in Journal of Geophysical Research: Oceans (2024). The article analyzes the effect of a tidal turbine farm on incident and reflected tidal energy fluxes in the Salish Sea. Files are in MATLAB data and .m format with some .txt and shape files. Files named figX.m create the corresponding Figure X using provided .mat and other files. Variable names and units correspond to graphed data of each figure in the journal article.</p>
UNS-Exterior Spatial Sound Events 2023 (UNS-ESSE2023)
<p><span>This dataset was generated within the UNS2: Localising Audio Events in Crowds use case of the H2020 MARVEL project. The purpose of the dataset is to offer audio samples collected outdoors in an urban area that could be used for development of sound event localisation and detection (SELD) models for acoustic monitoring in urban environments.</span></p> <p><span>The dataset was generated within a staged recording process. Audio samples were collected by utilising Infineon Audiohub Nano 8-channel microphone array board with a sampling rate of 48 kHz. The audio was synthetised by mixing target sound events from the FSD50K dataset “gunshot” and “gunfire”, “boom”, and “shatter” with samples of the class “chatter”, that was used as a background noise, extracted also from the FSD50k dataset. The scenario included different SNR values for the events in the mixtures and the measurement of the Sound Pressure Level (SPL) before and after the recording. Sound events were reproduced using eight JBL VP7212MDP10 speakers, which were positioned circularly around the microphone array board in equidistant positions. Data collection was performed for two different distances: 5 m and 10 m. One of the speakers was used to reproduce the target events (overlaid on the background noise), where the selected speaker varied during the data collection, while the others were used to reproduce background noise only. The recording setup was placed outdoors, involving additional ambient noise of the urban city area, which is a case closer to the real-world scenario comparing to the datasets recorded in the laboratory conditions. Together with the audio files, spatiotemporal annotation of the sound events is provided. These annotations include temporal onset and offset of the target events, azimuth, source distance, SNR level and SPL values for background ambience noise. </span></p> <p><span>This work was funded by the European Union’s Horizon 2020 research and innovation program MARVEL under grant agreement No 957337. This publication reflects the authors’ views only. The European Commission is not responsible for any use that may be made of the information it contains.</span></p>
ScienceDex guides
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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.