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1,300 results for “Sounds”
Data from: Using sounds for making decisions: greater tube-nosed bats prefer antagonistic calls over non-communicative sounds when feeding
Bats vocalize extensively within different social contexts. The type and extent of information conveyed via their vocalizations and their perceptual significance, however, remains controversial and difficult to assess. Greater tube-nosed bats, Murina leucogaster, emit calls consisting of long rectangular broadband noise burst (rBNBl) syllables during aggression between males. To experimentally test the behavioral impact of these sounds for feeding, we deployed an approach and place-preference paradigm. Two food trays were placed on opposite sides and within different acoustic microenvironments, created by sound playback, within a specially constructed tent. Specifically, we tested whether the presence of rBNBl sounds at a food source effectively deters the approach of male bats in comparison to echolocation sounds and white noise. In each case, contrary to our expectation, males preferred to feed at a location where rBNBl sounds were present. We propose that the species-specific rBNBl provides contextual information, not present within non-communicative sounds, to facilitate approach towards a food source.
Data from: A 2.6‐g sound and movement tag for studying the acoustic scene and kinematics of echolocating bats
1. To study sensorimotor behaviour in wild animals, it is necessary to synchronously record the sensory inputs available to the animal, and its movements. To do this, we have developed a biologging device that can record the primary sensory information and the associated movements during foraging and navigating in echolocating bats. 2. This 2.6 -gram tag records the sonar calls and echoes from an ultrasonic microphone, while simultaneously sampling fine-scale movement in three dimensions from wideband accelerometers and magnetometers. In this study, we tested the tag on an European noctula (Nyctalus noctula) during target approaches and on four big brown bats (Eptesicus fuscus) during prey interception in a flight room. 3. We show that the tag records both the outgoing calls and echoes returning from objects at biologically relevant distances. Inertial sensor data enables the detection of behavioural events such as flying, turning, and resting. In addition, individual wing-beats can be tracked and synchronized to the bat's sound emissions to study the coordination of different motor events. 4. By recording the primary acoustic flow of bats concomitant with associated behaviours on a very fine time-scale, this type of biologging method will foster a deeper understanding of how sensory inputs guide feeding behaviours in the wild.
Data from: Long-term sound and movement recording tags to study natural behaviour and reaction to ship noise of seals
The impact of anthropogenic noise on marine fauna is of increasing conservation concern with vessel noise being one of the major contributors. Animals that rely on shallow coastal habitats may be especially vulnerable to this form of pollution. Very limited information is available on how much noise from ship traffic individual animals experience, and how they may react to it due to a lack of suitable methods. To address this, we developed long‐duration audio and 3D‐movement tags (DTAGs) and deployed them on three harbor seals and two gray seals in the North Sea during 2015–2016. These tags recorded sound, accelerometry, magnetometry, and pressure continuously for up to 21 days. GPS positions were also sampled for one seal continuously throughout the recording period. A separate tag, combining a camera and an accelerometer logger, was deployed on two harbor seals to visualize specific behaviors that helped interpret accelerometer signals in the DTAG data. Combining data from depth, accelerometer, and audio sensors, we found that animals spent 6.6%–42.3% of the time hauled out (either on land or partly submerged), and 5.3%–12.4% of their at‐sea time resting at the sea bottom, while the remaining time was used for traveling, resting at surface, and foraging. Animals were exposed to audible vessel noise 2.2%–20.5% of their time when in water, and we demonstrate that interruption of functional behaviors (e.g., resting) in some cases coincides with high‐level vessel noise. Two‐thirds of the ship noise events were traceable by the AIS vessel tracking system, while one‐third comprised vessels without AIS. This preliminary study demonstrates how concomitant long‐term continuous broadband on‐animal sound and movement recordings may be an important tool in future quantification of disturbance effects of anthropogenic activities at sea and assessment of long‐term population impacts on pinnipeds.
Gentoo penguins (Pygoscelis papua) react to underwater sounds
<p>Marine mammals and diving birds face several physiological challenges under water, affecting their thermoregulation and locomotion as well as their sensory systems. Therefore, marine mammals have modified ears for improved underwater hearing. <a name="_Hlk5740480">Underwater hearing in marine birds have been studied in a few species, but for the record-holding divers, such as penguins, there are no detailed data</a>. We played underwater noise bursts to gentoo penguins<i> (Pygoscelis papua)</i> in a large tank at sound pressure levels between 100 and 120 dB re 1 µPa rms. The penguins showed a graded reaction to the noise bursts, ranging from no reactions at 100 dB to strong reactions in more than 62% of the playbacks at 120 dB re 1 µPa. The responses were always directed away from the sound source. The fact that penguins can detect and react to underwater stimuli may indicate that they make use of sound stimuli for orientation and prey detection during dives. Further, it suggests that penguins may be sensitive to anthropogenic noise, like many species of marine mammals.</p>
Data from: Aircraft sound exposure leads to song frequency decline and elevated aggression in wild chiffchaffs
Abstract: 1. The ubiquitous anthropogenic low-frequency noise impedes communication by masking animal signals. To overcome this communication barrier, animals may increase the frequency, amplitude and delivery rate of their acoustic signals, making them more easily heard. However, a direct impact of intermittent, high-level aircraft noise on birds' behaviour living close to a runway has not been studies in detail. 2. We recorded common chiffchaffs Phylloscopus collybita songs near two airports and nearby control areas, and we measured sound levels in their territories at Manchester airport. The song recordings were made in between aircraft movements, when ambient sound levels were similar between airport and control populations. We also conducted playback experiments at the airport and a control population to test the salience of airport, and control population specific songs. 3. In contrast to the general pattern of increased song frequency in noisy areas, we show that common chiffchaffs at airports show a negative relationship between noise exposure level and song frequency. 4. Experimental data show that chiffchaffs living near airports also respond more aggressively to song playback. 5. Since the decrease in song frequency results in increased overlap with aircraft noise, these findings cannot be explained as an adaptation to improve communication. The increased levels of aggression suggests that chiffchaffs, like humans, might be affected behaviourally by extreme noise pollution. These findings should influence environmental impact assessments for airport expansions globally.
Data from: Uncovering spatial variation in acoustic environments using sound mapping
Animals select and use habitats based on environmental features relevant to their ecology and behavior. For animals that use acoustic communication, the sound environment itself may be a critical feature, yet acoustic characteristics are not commonly measured when describing habitats and as a result, how habitats vary acoustically over space and time is poorly known. Such considerations are timely, given worldwide increases in anthropogenic noise combined with rapidly accumulating evidence that noise hampers the ability of animals to detect and interpret natural sounds. Here, we used microphone arrays to record the sound environment in three terrestrial habitats (forest, prairie, and urban) under ambient conditions and during experimental noise introductions. We mapped sound pressure levels (SPLs) over spatial scales relevant to diverse taxa to explore spatial variation in acoustic habitats and to evaluate the number of microphones needed within arrays to capture this variation under both ambient and noisy conditions. Even at small spatial scales and over relatively short time spans, SPLs varied considerably, especially in forest and urban habitats, suggesting that quantifying and mapping acoustic features could improve habitat descriptions. Subset maps based on input from 4, 8, 12 and 16 microphones differed slightly (< 2 dBA/pixel) from those based on full arrays of 24 microphones under ambient conditions across habitats. Map differences were more pronounced with noise introductions, particularly in forests; maps made from only 4-microphones differed more (> 4 dBA/pixel) from full maps than the remaining subset maps, but maps with input from eight microphones resulted in smaller differences. Thus, acoustic environments varied over small spatial scales and variation could be mapped with input from 4–8 microphones. Mapping sound in different environments will improve understanding of acoustic environments and allow us to explore the influence of spatial variation in sound on animal ecology and behavior.
Data from: Wall structure and material properties cause viscous damping of swimbladder sounds in the oyster toadfish Opsanus tau
Despite rapid damping, fish swimbladders have been modelled as underwater resonant bubbles. Recent data suggest that swimbladders of sound-producing fishes use a forced rather than a resonant response to produce sound. The reason for this discrepancy has not been formally addressed, and we demonstrate, for the first time, that the structure of the swimbladder wall will affect vibratory behaviour. Using the oyster toadfish Opsanus tau, we find regional differences in bladder thickness, directionality of collagen layers (anisotropic bladder wall structure), material properties that differ between circular and longitudinal directions (stress, strain and Young's modulus), high water content (80%) of the bladder wall and a 300-fold increase in the modulus of dried tissue. Therefore, the swimbladder wall is a viscoelastic structure that serves to damp vibrations and impart directionality, preventing the expression of resonance.
Data from: Sperm whales reduce foraging effort during exposure to 1-2 kHz sonar and killer whale sounds
The time and energetic costs of behavioral responses to incidental and experimental sonar exposures, as well as control stimuli, were quantified using hidden state analysis of time series of acoustic and movement data recorded by tags (DTAG) attached to 12 sperm whales (Physeter macrocephalus) using suction cups. Behavioral state transition modeling showed that tagged whales switched to a non-foraging, non-resting state during both experimental transmissions of low-frequency active sonar from an approaching vessel (LFAS; 1–2 kHz, source level 214 dB re 1 μPa m, four tag records) and playbacks of potential predator (killer whale, Orcinus orca) sounds broadcast at naturally occurring sound levels as a positive control from a drifting boat (five tag records). Time spent in foraging states and the probability of prey capture attempts were reduced during these two types of exposures with little change in overall locomotion activity, suggesting an effect on energy intake with no immediate compensation. Whales switched to the active non-foraging state over received sound pressure levels of 131–165 dB re 1 μPa during LFAS exposure. In contrast, no changes in foraging behavior were detected in response to experimental negative controls (no-sonar ship approach or noise control playback) or to experimental medium-frequency active sonar exposures (MFAS; 6–7 kHz, source level 199 re 1 μPa m, received sound pressure level [SPL] = 73–158 dB re 1 μPa). Similarly, there was no reduction in foraging effort for three whales exposed to incidental, unidentified 4.7–5.1 kHz sonar signals received at lower levels (SPL = 89–133 dB re 1 μPa). These results demonstrate that similar to predation risk, exposure to sonar can affect functional behaviors, and indicate that increased perception of risk with higher source level or lower frequency may modulate how sperm whales respond to anthropogenic sound.
Sounds of senescence: Male swamp sparrows respond less aggressively to the song of older individuals
Age-related changes in assessment signals occur in a diverse array of animals, including humans. Age-related decline in vocal quality in humans is known to affect perceived attractiveness by potential mates and voters, but whether such changes have functional implications for non-human animals is poorly understood. Most studies of age-related change in animal signals focus on increases in signal quality that occur soon after the age of first breeding ("delayed maturation"), but a few have shown that signal quality declines in older individuals after a mid-life peak ("behavioral senescence"). Whether other individuals are able to detect this senescent decline of assessment signals has not previously been tested. Here we use playback experiments to show that wild male swamp sparrows (Melospiza georgiana) respond more aggressively to songs from two-year-old males as compared to songs from the same males when they are ten years old. Senescence in signals that, like birdsong, affect reproductive success though intra-sexual competition or mate choice may be of evolutionary significance.
Data from: Weather conditions determine attenuation and speed of sound: environmental limitations for monitoring and analysing bat echolocation
Echolocating bats are regularly studied to investigate auditory-guided behaviours and as important bioindicators. Bioacoustic monitoring methods based on echolocation calls are increasingly used for risk assessment and to ultimately inform conservation strategies for bats. As echolocation calls transmit through the air at the speed of sound, they undergo changes due to atmospheric and geometric attenuation. Both the speed of sound and atmospheric attenuation, however, are variable and determined by weather conditions, particularly temperature and relative humidity. Changing weather conditions thus cause variation in analysed call parameters, limiting our ability to detect and correctly analyse bat calls. Here, I use real-world weather data to exemplify the effect of varying weather conditions on the acoustic properties of air. I then present atmospheric attenuation and speed of sound for the global range of weather conditions and bat call frequencies to show their relative effects. Atmospheric attenuation is a non-linear function of call frequency, temperature, relative humidity and atmospheric pressure. While atmospheric attenuation is strongly positively correlated with call frequency, it is also significantly influenced by temperature and relative humidity in a complex non-linear fashion. Variable weather conditions thus result in variable and unknown effects on the recorded call, affecting estimates of call frequency and intensity, particularly for high frequencies. Weather-induced variation in speed of sound reaches up to about ±3%, but is generally much smaller and only relevant for acoustic localisation methods of bats. The frequency- and weather-dependent variation in atmospheric attenuation has a three-fold effect on bioacoustic monitoring of bats: it limits our capability (1) to monitor bats equally across time, space, and species, (2) to correctly measure frequency parameters of bat echolocation calls, particularly for high-frequencies, and (3) to correctly identify bat species in species-rich assemblies or for sympatric species with similar call designs.
Elastolin Norman horseman (with sound)
Source: Objaverse 1.0 / Sketchfab
Single Sound Clarity (Strings) Dataset
<p>Data generated as part of research to determine how single sound clarity depends on boosts and cuts in different frequency regions and on the original spectral centroids and fundamentals of the programme items (plucked and bowed violin, and plucked and bowed cello). Data comprise audio files, listening test interfaces, results and MATLAB code for plot generation.</p> <p><strong>References</strong></p> <p>BBC SNN (2015): K. Hermes, T.Brookes, C.Hummersone, “Towards measuring and modelling music mix quality: measuring single sound spectral clarity”, BBC Sound Now & Next Technology Fair, London, UK, 19-20 May 2015</p>
TUT Sound events 2016, Development dataset
<p>TUT Sound events 2016, development dataset consists of 22 audio recordings from two acoustic scenes:</p> <ul> <li>Home (indoor), 10 recordings, totaling 36:16</li> <li>Residential area (outdoor), 12 recordings, totalling 42:00</li> </ul>
Vocal imitations of non-vocal sounds
<p>Vocal imitations of everyday sounds. There are two families (interactions and products), 10 imitators (I#), 8 categories, and 2 sounds per categories</p>
TUT Sound events 2017, Development dataset
<p>TUT Sound events 2017, development dataset consists of 24 audio recordings from a single acoustic scene:</p> <ul> <li> Street (outdoor), totaling 1:32:08</li> </ul>
Sound Static Data Race Verification for C: Is the Race Lost?
<p>This artifact contains the benchmarks, tools and scripts for reproduction, along with our reference results used for the paper.</p> <h1>Contents</h1> <p dir="auto">The reproduction package contains materials for reproducing Tables 2, 4, 5, 10, and 14 from the paper. These tables provide the data supporting research questions 2 and 3, as well as additional evaluation results.</p> <p dir="auto">We provide two versions of the artifact:</p> <ol> <li>The source version includes benchmarks, scripts and reference results such that they can easily be accessed and reused outside of the virtual machine.</li> <li>The virtual machine version additionally includes tools and their dependencies such that the results can be reproduced by execution.</li> </ol> <p dir="auto">The <strong>source version</strong> contains:</p> <ul> <li><code>README.md</code>/<code>README.pdf</code> — This file.</li> <li><code>concrat-benchmarks/</code> — Concrat benchmarks (RQ 3) and execution scripts. <ul> <li><code>results-paper/</code> — Reference results used for Table 2.</li> </ul> </li> <li><code>extracted-micro-benchmarks/</code> — Extracted micro-benchmarks (with their racy variations) and execution scripts (RQ 2). <ul> <li><code>results-paper/</code> — Reference results used for Table 4 (Finding 2).</li> </ul> </li> <li><code>concrat-benchmarks-excluded/</code> — Excluded Concrat benchmarks (RQ 3).</li> <li><code>sv-benchmarks/</code> — SV-COMP 2023 NoDataRace-Main category benchmarks.</li> <li><code>joern/</code> — Joern scripts for Table 5 (RQ 3). <ul> <li><code>concrat-benchmarks-paper/</code> — Reference results for Concrat benchmarks used for Table 5 (Finding 3).</li> <li><code>concrat-benchmarks-excluded-paper/</code> — Reference results for excluded Concrat benchmarks used for Table 5 (Finding 3).</li> <li><code>sv-benchmarks-paper/</code> — Reference results for SV-COMP benchmarks used for Table 5 (Finding 3).</li> <li><code>extracted-micro-benchmarks-paper/</code> — Reference results for extracted micro-benchmarks used for Table 14.</li> </ul> </li> <li><code>sv-benchmarks.sh</code> — Script to download SV-COMP 2023 NoDataRace-Main category benchmarks.</li> <li><code>tools/download.sh</code> — Script to download SV-COMP 2023 tools from their reproduction packages.</li> <li><code>properties/no-data-race.prp</code> — Property file for executing SV-COMP tools.</li> <li><code>tsan-races/</code> — Scripts to run ThreadSanitizer on Concrat benchmarks. <ul> <li><code>logs/</code> — Reference results used for Table 2 and Table 10.</li> </ul> </li> </ul> <p dir="auto">The <strong>virtual machine version</strong> contains all of the above in <code>/home/vagrant</code>, but also:</p> <ul> <li><code>concrat-benchmarks/</code> <ul> <li><code>results-test/</code> — Results from kick-the-tires (initially empty).</li> <li><code>results/</code> — Full evaluation results (initially empty).</li> <li><code>results-reduced/</code> — Reduced evaluation results (initially empty).</li> </ul> </li> <li><code>extracted-micro-benchmarks/</code> <ul> <li><code>results-test/</code> — Results from kick-the-tires (initially empty).</li> <li><code>results/</code> — Full evaluation results (initially empty) (Finding 2).</li> <li><code>results-reduced/</code> — Reduced evaluation results (initially empty) (Finding 2).</li> </ul> </li> <li><code>joern/</code> <ul> <li><code>concrat-benchmarks/</code> — Results for Concrat benchmarks (initially empty) (Finding 3).</li> <li><code>concrat-benchmarks-excluded/</code> — Results for excluded Concrat benchmarks (initially empty) (Finding 3).</li> <li><code>sv-benchmarks/</code> — Results for SV-COMP benchmarks (initially empty) (Finding 3).</li> </ul> </li> <li><code>tools/</code> (subdirectories) — Downloaded SV-COMP 2023 tools from their reproduction packages.</li> </ul> <h1>Hardware Dependencies</h1> <p dir="auto">The executable artifact is a <a href="https://www.virtualbox.org/">VirtualBox</a> virtual machine, because <a href="https://github.com/sosy-lab/benchexec">BenchExec</a> does not run in Docker. <strong>Full evaluation</strong> requires:</p> <ul> <li>8 CPU cores,</li> <li>26 GB RAM,</li> <li>7 GB disk space,</li> <li>~2 days and 15 hours.</li> </ul> <p dir="auto">Considering the significant runtime, we also provide a reduced evaluation. <strong>Reduced evaluation</strong> requires:</p> <ul> <li>8 CPU cores,</li> <li>16 GB RAM,</li> <li>7 GB disk space,</li> <li>~2 hours.</li> </ul>
APES electron precipitation data from the VISIONS-2 Sounding rocket flight
<p>This is a Matlab save file containting the data from the APES instrument from the VISIONS-2 sounding rocket flight. It contains the precipitating electron flux in both units of number flux and energy flux.</p>
Fig. 2 in New Stridulatory Structures in a Tiger Beetle (Coleoptera: Carabidae: Cicindelinae): Morphology and Sound Characterization
Fig. 2. Sound signals of Oxycheila tristis. a) comparison between the oscillograms obtained for a female and a male; b) details of oscillogram and respective sonograms showing the frequency modulation, at the beginning (1) and in the middle (2) of a syllable produced by a male; c) comparison between the averaged spectra of the sound signals produced by four males and three females (error bars represent range).
Fig. 1 in New Stridulatory Structures in a Tiger Beetle (Coleoptera: Carabidae: Cicindelinae): Morphology and Sound Characterization
Fig. 1. Sound producing structures of the tiger beetle Oxycheila tristis. a) diagram of the dorsal view of an adult with the position of the structures indicated; b–h) scanning electron micrographs of the sound producing structures; b) plectrum, on the internal surface of the femur, with details of the ridges on two sections (c, d); e) pars stridens on the anterior part of the epipleura, with a detail of the ridges (f); g) pars stridens on the posterior part of the epipleura, with a detail of the ridges (h).
Fig. 4 in Audiospectrographical analysis of cicada sound production: a catalogue (Hemiptera, Cicadidae)
Fig. 4. Cumulative number of calling songs of different cicadas described through audiospectrographic analysis since 1948.
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.