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416 results for “Acoustic data”
Data from: Spatio-temporal scaling of biodiversity in acoustic tropical bird communities
Automated analysis of acoustic communities is a rapidly emerging approach for the characterization and monitoring of biodiversity. To evaluate its utility, we should verify that such "bioacoustics" can accurately detect ecological signal in spatiotemporal acoustic data. Targeting the Biological Dynamics of Forest Fragments Project sites in Brazil, we ask: What is the relative contribution of the spatial, temporal and habitat dimension to variation in bird acoustic communities in a previously fragmented tropical rainforest? Does the functional diversity of bird communities scale similarly to space and time as does species diversity, when both are recorded by bioacoustics means? Overall, is the imprint of landscape fragmentation 30 years ago still audible in the present‐day soundscape? We sampled forty‐four sites in secondary forest and 107 sites in old‐growth forest, resulting in 11,000 hours of audio recordings. We detected 60 bird species with satisfactory precision and recovered a linear log‐log relation between sampling time and species diversity. Sites in primary forest host more species than sites in secondary forest, but the difference decreased with sampling time, as the slope was slightly higher in secondary than primary forests. Functional diversity, as exposed by vocalizing birds, accumulates faster than does species diversity. The similarity among local communities decreases with distance in both time and space, but stability in time is remarkably high: two acoustic samples from the same site one year (or more) apart prove more similar than two samples taken at the same time but from sites situated just a few hundred meters apart. These findings suggest that habitat modification can be heard as a long‐lasting imprint on the soundscape of regenerating habitats and identify Soundscape–Area and Soundscape–Time Relations as a promising tool for biodiversity research, applied biomonitoring and restoration ecology.
Data from: Calling louder and longer: how bats use biosonar under severe acoustic interference from other bats
Active-sensing systems such as echolocation provide animals with distinct advantages in dark environments. For social animals, however, like many bat species, active sensing can present problems as well: when many individuals emit bio-sonar calls simultaneously, detecting and recognizing the faint echoes generated by one's own calls amid the general cacophony of the group becomes challenging. This problem is often termed 'jamming' and bats have been hypothesized to solve it by shifting the spectral content of their calls to decrease the overlap with the jamming signals. We tested bats' response in situations of extreme interference, mimicking a high density of bats. We played-back bat echolocation calls from multiple speakers, to jam flying Pipistrellus kuhlii bats, simulating a naturally occurring situation of many bats flying in proximity. We examined behavioural and echolocation parameters during search phase and target approach. Under severe interference, bats emitted calls of higher intensity and longer duration, and called more often. Slight spectral shifts were observed but they did not decrease the spectral overlap with jamming signals. We also found that pre-existing inter-individual spectral differences could allow self-call recognition. Results suggest that the bats' response aimed to increase the signal-to-noise ratio and not to avoid spectral overlap.
Data from: Spectral and temporal acoustic features modulate response irregularities within primary auditory cortex columns
Assemblies of vertically connected neurons in the cerebral cortex form information processing units (columns) that participate in the distribution and segregation of sensory signals. Despite well-accepted models of columnar architecture, functional mechanisms of inter-laminar communication remain poorly understood. Hence, the purpose of the present investigation was to examine the effects of sensory information features on columnar response properties. Using acute recording techniques, extracellular response activity was collected from the right hemisphere of eight mature cats (felis catus). Recordings were conducted with multichannel electrodes that permitted the simultaneous acquisition of neuronal activity within primary auditory cortex columns. Neuronal responses to simple (pure tones), complex (noise burst and frequency modulated sweeps), and ecologically relevant (con-specific vocalizations) acoustic signals were measured. Collectively, the present investigation demonstrates that despite consistencies in neuronal tuning (characteristic frequency), irregularities in discharge activity between neurons of individual A1 columns increase as a function of spectral (signal complexity) and temporal (duration) acoustic variations.
Data from: Investigation of the effect of cochlear implant electrode length on speech comprehension in quiet and noise compared with the results with users of electro-acoustic-stimulation, a retrospective analysis
Objectives: This investigation evaluated the effect of cochlear implant (CI) electrode length on speech comprehension in quiet and noise and compare the results with those of EAS users. Methods: 91 adults with some degree of residual hearing were implanted with a FLEX20, FLEX24, or FLEX28 electrode. Some subjects were postoperative electric-acoustic-stimulation (EAS) users; the other subjects were in the groups of electric stimulation-only (ES-only). Speech perception was tested in quiet and noise at 3 and 6 months of ES or EAS use. Speech comprehension results were analyzed and correlated to electrode length. Results: While the FLEX20 ES and FLEX24 ES groups were still in their learning phase between the 3 to 6 months interval, the FLEX28 ES group was already reaching a performance plateau at the three months appointment yielding remarkably high test scores. EAS subjects using FLEX20 or FLEX24 electrodes outscored ES-only subjects with the same short electrodes on all 3 tests at each interval, reaching significance with FLEX20 ES and FLEX24 ES subjects on all 3 tests at the 3-months interval and on 2 tests at the 6- months interval. Amongst ES-only subjects at the 3- months interval, FLEX28 ES subjects significantly outscored FLEX20 ES subjects on all 3 tests and the FLEX24 ES subjects on 2 tests. At the-6 months interval, FLEX28 ES subjects still exceeded the other ES-only subjects although the difference did not reach significance. Conclusions: Among ES-only users, the FLEX28 ES users had the best speech comprehension scores, at the 3- months appointment and tendentially at the 6 months appointment. EAS users showed significantly better speech comprehension results compared to ES-only users with the same short electrodes.
Data extracted from acoustic device.
<p>Data extracted from acoustic device.</p>
FIGURE 195 in Review of the Balkan Isophya (Orthoptera: Phaneropteridae) with particular emphasis on the Isophya modesta group and remarks on the systematics of the genus based on morphological and acoustic data
FIGURE 195. Distribution of I. amplipennis and I. speciosa on the Balkan Peninsula.
Data for the assessment of the detection range of acoustic listening stations in the Zeeschelde estuary, Belgium
<p>Data used to determine the detection of acoustic listening stations in an estuarine environment.</p>
Figure 5 in A new genus of African Acrometopini (Tettigoniidae: Phaneropterinae) based on morphology, chromosomes, acoustics, distribution, and molecular data, and the description of a new species
Figure 5. Spectra of the calling songs of two Altihoratosphaga species.
Figure 10 in A new genus of African Acrometopini (Tettigoniidae: Phaneropterinae) based on morphology, chromosomes, acoustics, distribution, and molecular data, and the description of a new species
Figure 10. The distribution of Altihoratosphaga species in East Africa.
Carcharhinus amblyrhynchos and Carcharhinus albimarginatus underwater acoustic telemetry data - Chagos Archipelago 2014-2018
<p>A wide array of technologies are available for gaining insight into the movement of wild aquatic animals. Although acoustic telemetry may lack the fine-scale resolution of some satellite tracking technologies, the substantially longer battery life can yield important long-term data on behaviour and movement for low per-unit cost. Typically, however, receiver arrays are designed to maximise spatial coverage at the cost of positional accuracy leading to potentially longer detection gaps as individuals move out of range between monitored locations. This is particularly true when these technologies are deployed to monitor species in hard-to-access locations. We develop a novel approach to analysing acoustic telemetry data, using the timing and duration of gaps between animal detections to classify movement behaviours into 'restricted' or potential wider 'out of range' movements synonymous with longer distance dispersal. We apply this method to investigate spatial and temporal segregation of inferred movement patterns in two sympatric species of reef shark within a large, remote Marine Protected Area. Drivers of these movements were identified using generalised linear mixed models and multi-model inference. Species, diel period and season were significant predictors of 'out of range' movements. Silvertip sharks were overall more likely to undertake 'out of range' movements, compared to grey reef sharks, indicating spatial segregation, and corroborating previous stable isotope work between these two species. High individual variability in 'out of range' movements in both species was also identified. We present a novel gap analysis of telemetry data to help infer differential movement and space use patterns where acoustic coverage is imperfect and other tracking methods impractical. In remote locations, inference may be the best available tool and this approach shows that acoustic telemetry gap analysis can be used for comparative studies in fish ecology, or combined with other research techniques to better understand functional mechanisms driving behaviour.</p>
Darwin's Hawkmoth (Xanthopan praedicta) responds to bat ultrasound at sonar-jamming rates: Acoustic data set
<p>This paper reveals that <em>Xanthopan praedicta</em> (Lepidoptera: Sphingidae) is part of the bat-moth coevolutionary dynamic. I played recordings of bat echolocation to live <em>X. praedicta</em> and found that males respond with such dense ultrasound they can likely jam bat sonar. Female <em>X. praedicta</em> and two other sphingid species do not produce ultrasonic responses.</p>
Data and scripts for: An analysis of the dynamic range of Distributed Acoustic Sensing for Earthquake Early Warning
Open the record for dataset details and reuse information.
Data from : Evaluating and Predicting the Audibility of Acoustic Alarms in the Workplace Using Experimental Methods and Deep Learning
<h2>Description</h2> <p>This repository serves as a complementary resource accompanying the academic paper titled "Evaluating and Predicting the Audibility of Acoustic Alarms in the Workplace Using Experimental Methods and Deep Learning" published in <em>Applied Acoustics </em>(available at: <a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.apacoust.2024.109955" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.apacoust.2024.109955</a>). It comprises a dataset containing the acoustic data, metadata, and perceptual annotations.</p> <p>In addition, we provide the .<em>h5</em> datasets and PyTorch model weights to run the code corresponding to the neural network section discussed in the paper (publicly accessible at: <a href="https://github.com/effajr/predicting_alarm_audibility">https://github.com/effajr/predicting_alarm_audibility</a>).</p> <p>The repository is composed of five .<em>zip</em> files:</p> <ul> <li><strong>source_audio </strong>: contains the source audio files used to generate the alarms and backgrounds present in the <strong>data</strong> file.</li> <li><strong>data</strong> : contains the audio files corresponding to the alarms and backgrounds, along with the perceptual annotations.</li> <li><strong>metadata</strong> : contains the metadata related to the alarms and backgrounds present in the <strong>data</strong> file, and to the source audio files contained in <strong>source_audio</strong>.</li> <li><strong>features </strong>: contains the .<em>h5</em> files representing the development and evaluation subsets (mel-spectrograms and perceptual labels) used in the deep learning approach presented in the paper.</li> <li><strong>trained_models </strong>: contains the PyTorch model weights for the 10 runs of model training mentionned in the paper.</li> </ul> <h2>How to use the data</h2> <p>To run the code present in the GitHub repository, we recommend extracting the files <strong>data</strong>.zip, <strong>features</strong>.zip and <strong>trained_models</strong>.zip in their corresponding folders in the "<strong>application</strong>" folder (see <a href="https://github.com/effajr/predicting_alarm_audibility">https://github.com/effajr/predicting_alarm_audibility</a>).</p> <h2>Content</h2> <p>Content of <strong>data</strong>.zip </p> <pre>annotations/ ├─ dev/ │ ├─ annotation_compilation_dev.csv : Compilation of all the listening conditions and <br>│ │ individual annotator responses for the development data.<br>│ ├─ dev_conditions.csv : Unique listening conditions (extracted from annotation_compilation_dev.csv). │ ├─ dev_labels.csv : All individual annotator responses for each <br>│ │ unique listening condition (extracted from annotation_compilation_dev.csv). │ ├─ dev_train_valid_split.csv : Random 80%/20% training/validation split used for development <br>│ │ in the experiments reported in the paper. ├─ eval/<br>│ ├─ annotation_compilation_eval.csv : Compilation of all the listening conditions and individual annotator <br>│ │ responses for the evaluation data.<br>│ │ The column 'clearly_audible_mean' represents individual annotator <br>│ │ binary responses evaluated for each listening condition.<br>│ │ The column 'clearly_audible_pf' represents individual annotator <br>│ │ psychometric functions evaluated for each listening condition.<br>│ │<br>│ ├─ eval_conditions.csv : Unique listening conditions (extracted from annotation_compilation_eval.csv). │ ├─ eval_labels_apf.csv : All individual annotator psychometric function values for each <br>│ │ unique listening condition (extracted from annotation_compilation_eval.csv). │ ├─ eval_labels_mv.csv : All individual annotator binary responses for each <br>│ │ unique listening condition (extracted from annotation_compilation_eval.csv)<br>│<br>audio/ : <em>.wav</em> files corresponding to the alarms and backgrounds for Development and <br> Evaluation subsets of the dataset. ├─ dev/ │ ├─ alarms/ │ ├─ backgrounds/ ├─ eval/ │ ├─ alarms/ │ ├─ backgrounds/<br><br><br>Content of <strong>metadata</strong>.zip <br><br>├─ audio_metadata.xlsx : Table of the alarms and background files with short descriptions, <br>│ source file names, and temporal information (in seconds). ├─ source_file_metadata.xlsx : Metadata table of the original files used to generate alarms and backgrounds. </pre>
Fig. 3 in Evolution and systematics of Green Bush-crickets (Orthoptera: Tettigoniidae: Tettigonia) in the Western Palaearctic: testing concordance between molecular, acoustic, and morphological data
Fig. 3 Oscillograms of songs of the Tettigonia armeniaca complex (1–11), T. caudata (12), and T. uvarovi (13) recorded at two or three speeds: 1 T. armeniaca (AM: Djermuk, T = 19 °C), 2 T. armeniaca (TR: Saclidag Pass, T = 21.5 °C), 3 T. armeniaca (TR: Ispir, T = 17 °C) (monosyllabic type), 4 T. armeniaca (TR: Ispir, T = 17 °C) (disyllabic type), 5 T. armeniaca (AM: Saravan, T = 20–25 °C) (outdoor recording), 6 T. armeniaca (AM: Lermontovo vill., T = 20 °C), 7 T. armeniaca (TR: Savsat–Ardahan, T = 26 °C), 8 T. armeniaca (TR: Savsat– Ardahan, T = 26 °C) (variable echeme length), 9 T. armeniaca (TR: Ispir, T = 17 °C) (polysyllabic type of variable length), 10 T. armeniaca (TR: Pulumur, T = 20–22 °C) (shorter echemes), 11 T. armeniaca (TR: Pulumur, T = 20–22 °C) (the same specimen as in 10 longer echemes), 12 T. caudata (GR: Drama; from Massa et al. 2012, T = 25 °C), and 13 T. uvarovi (South Korea; from Kim 2009 as T. dolichoptera; see Rhee 2013). Scale bar for A is 10 s; for B, 2 s; and for C, 200 ms
Data for manuscript "Scanning Acoustic Microscopy Characterization of Cold-Sprayed Coatings Deposited on Grooved Substrates"
<p>Data sets used for generating figures from SAM measurements.</p>
Data for the paper: "A soundscape approach for a short-term acoustic monitoring of a Critically Endangered Cuban frog"
<p>This 4 excel sheets contain the data sets for the paper “A soundscape approach for a short-term acoustic monitoring of a Critically Endangered Cuban frog” . The data comprises the call rate informatione xtracted from te recordings and the Acoustical index data for descibing the soundscape of the area</p>
Data from: High suckling rates and acoustic crypsis of humpback whale neonates maximise potential for mother–calf energy transfer
1. The migration of humpback whales to and from their breeding grounds results in a short, critical time period during which neonatal calves must acquire sufficient energy via suckling from their fasting mothers to survive the long return journey. 2. Understanding neonate suckling behaviour is critical for understanding the energetics and evolution of humpback whale migratory behaviour and for informing conservation efforts, but despite its importance, very little is known about the details, rate and behavioural context of this critical energy transfer. 3. To address this pertinent data gap on calf suckling behaviour, we deployed multi-sensor Dtags on eight humpback whale calves and two mothers allowing us to analyse detailed suckling and acoustic behaviour for a total of 68·8 h. 4. Suckling dives were performed 20·7 ± 7% of the total tagging time with the mothers either resting at the surface or at depth with the calves hanging motionless with roll and pitch angles close to zero. 5. Vocalisations between mother and calf, which included very weak tonal and grunting sounds, were produced more frequently during active dives than suckling dives, suggesting that mechanical stimuli rather than acoustic cues are used to initiate nursing. 6. Use of mechanical cues for initiating suckling and low level vocalisations with an active space of <100 m indicate a strong selection pressure for acoustic crypsis. 7. Such inconspicuous behaviour likely reduces the risk of exposure to eavesdropping predators and male humpback whale escorts that may disrupt the high proportion of time spent nursing and resting, and hence ultimately compromise calf fitness. 8. The small active space of the weak calls between mother and calf is very sensitive to increases in ambient noise from human encroachment thereby increasing the risk of mother–calf separation.
FIGURE 9 in A new species of Indigryllus (Orthoptera, Gryllidae, Eneopterinae, Xenogryllini) from Kerala, India, with first data on acoustics and natural habitat
FIGURE 9. Indigryllus sagani sp. nov.: natural habitat in type locality.
FIGURE 7 in A new species of Indigryllus (Orthoptera, Gryllidae, Eneopterinae, Xenogryllini) from Kerala, India, with first data on acoustics and natural habitat
FIGURE 7. Indigryllus sagani sp. nov.: females of dark morph in their natural habitat.
Source code and data files for the acoustic sensor-based wearable fetal movement monitor
<p>This repository contains data files and source code for the acoustic sensor-based wearable fetal movement monitor.</p>
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
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.