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40 results for “Sound analysis”
PIE LTER, stable isotope chemistry (carbon, nitrogen and sulfur) for food web analysis of functional groups in the Plum Island Sound Estuary, Massachusetts.
Stable isotopes of primary producers will be compared to stable isotopes of functional groups of organisms at primarily three sites within the estuary that have different dominant sources of organic matter. The three sites are: Lower (IBYC, SO-3, mouth of Plum Island Sound, 2-3 km upstream of the mouth of the estuary), Middle (OTL, PR-10.1, upper Sound, lower Parker, 8-11 km upstream of the mouth of the estuary) and Upper (P2, PR-21.9, upper Parker, above Middle Rd Bridge (22 km upstream of the mouth of the estuary). The Lower site is dominated by marine phytoplankton, the Middle site is dominated by a mixture of salt marsh and phytoplankton and the Upper site is dominated by oligohaline phytoplankton and fresh marsh. Ten functional groups will be sampled at each site (Surface sediment, benthic diatoms, Nereis, mummichog, ribbed mussels, POM, blue mussels, pelagic copepods (Acartia), silversides and soft shell clams (Mya). Marsh, benthic algae and phytoplankton inputs or benthic vs. pelagic pathways will be evident in the isotopic signals of these functional groups. Samples will be collected between the middle and end of August to reflect a growing season using recently produced OM. Samples of 15 – 20 individuals will be pooled for analysis. Some silverside samplings will have 3 different pooled samples for determination of variance. Often times the same species are not collected at each site due to habitat differences (salinity/discharge) so additional species are collected to try to accomplish task of getting functional groups collected.
Table S3. List of Locustella sound recordings included in bioacoustic analysis surrounding description of the Taliabu Grasshopper-Warbler. The table provides information on sound library sources and sampling localities of recordings as well as raw data on all 11 bioacoustic parameters measured (see Supplementary Materials section SM3 for more details on parameters). Recordings whose source is labeled as "private recording" were obtained by colleagues and are available upon demand from the corresponding author.
<p>supplement to Rheindt, Frank E., Prawiradilaga, Dewi M., Ashari, Hidayat, Suparno, Gwee, Chyi Yin, Lee, Geraldine W. X., Wu, Meng Yue, Ng, Nathaniel S. R. (2020): A lost world in Wallacea: Description of a montane archipelagic avifauna. Science 367: 167-170, DOI: 10.1126/science.aax2146</p>
Figures 4a-4c in Bioacoustic analysis of a compound sound with stridulation and forced air produced by the larva of Phileurus valgus (Olivier, 1789) (Coleoptera: Scarabaeidae: Dynastinae: Phileurini)
Figures 4a-4c. Oscillograms (above) and spectrograms (down) of sounds emitted by Phileurus valgus larvae. a) Bioacoustic stridulation (isolated) patterns. b) Bioacoustic sound patterns of compound sound (stridulatory + forced air). c) Bioacoustic pattern of compound sound pulse and some forced air sound pulses (6 pulses after the compound sound). / Oscilogramas (arriba) y espectrogramas (abajo) de los sonidos emitidos por las larvas de Phileurus valgus. a) Patrones bioacústicos de estridulación (aislada). b) Patrones bioacústicos de sonido compuesto (estridulación + aire forzado). c) Patrón bioacústico de pulso de sonido compuesto y algunos pulsos de sonido de aire forzado (6 pulsos después del sonido compuesto).
Figures 3a-3b in Bioacoustic analysis of a compound sound with stridulation and forced air produced by the larva of Phileurus valgus (Olivier, 1789) (Coleoptera: Scarabaeidae: Dynastinae: Phileurini)
Figures 3a-3b. Comparison of oscillogram and spectrogram of forced air sound pulse. a. Phileurus valgus. b. Phileurus didymus. / Comparación del oscilograma y el espectrograma del pulso sonoro de aire forzado. a. Phileurus valgus. b. Phileurus didymus.
Figures 1a-1d in Bioacoustic analysis of a compound sound with stridulation and forced air produced by the larva of Phileurus valgus (Olivier, 1789) (Coleoptera: Scarabaeidae: Dynastinae: Phileurini)
Figures 1a-1d. Diagrams of the experiments. a-c) Direct interaction (larva-larva) and response experiment. d) Direct manipulation experiment. / Diagramas de los experimentos. a-c) Experimento de interacción directa (larva-larva) y respuesta. d) Experimento de manipulación directa.
Figures 2a-2c in Bioacoustic analysis of a compound sound with stridulation and forced air produced by the larva of Phileurus valgus (Olivier, 1789) (Coleoptera: Scarabaeidae: Dynastinae: Phileurini)
Figures 2a-2c. Comparison of numbers of pulses in stridulation, oscillogram (above). Spectrogram (down). a) 4 pulses. b) 10 pulses. c) 12 pulses. / Comparación del número de pulsos en la estridulación, oscilograma (arriba). Espectrograma (abajo). a) 4 pulsos. b) 10 pulsos. c) 12 pulsos.
Figure 1 in Acoustic analysis of vocalization and the behavioral response associated to sound production of the nine banded armadillo Dasypus novemcinctus (Mammalia, Cingulata, Dasypodidae)
Figure 1. Oscillogram (top) and spectrogram (bottom) of the agonistic vocalizations of Dasypus novemcinctus, HCLP-S 1028, recorded from individual M1. (A) A single vocalization composed of the pattern A-I, A-I, B-I, B-II; (B) A single vocalization composed of the pattern A-I, A-II, B-I, A-II, B-I, B-II.
Figure 2. M1 in Acoustic analysis of vocalization and the behavioral response associated to sound production of the nine banded armadillo Dasypus novemcinctus (Mammalia, Cingulata, Dasypodidae)
Figure 2. M1 (marked with white tape at the middle of its moveable bands) Behavior (A) when cornered after being submitted to the presence of other male subject, (B) at a second moment, when the other animal approaches from its back, and then (C) M1 bends its body left to prevent the contact, with the other male scratching the basis of its tail. In (D) the other male bipedally projects its belly against M1's back, and the latter finally changes its position.
Auditory Scene Analysis dataset (Multichannel universal sound separation & polyphonic audio classification)
<p>We constructed a new dataset for <strong>multichannel universal sound separation</strong> and <strong>polyphonic audio classification</strong> tasks.</p> <p>We constructed a new dataset for multichannel USS and polyphonic audio classification tasks. The proposed dataset is designed to reflect various conditions, including moving sources with temporal onsets and offsets. For foreground sound sources, signals from 13 audio classes were selected from open-source databases (Pixabay and FSD50K, Librispeech, MUSDB18, Vocalsound). These signals were resampled to 16 kHz and pre-processed by either padding zeros or cropping to 4 seconds. Each sound source has a 75% probability of being a moving source, with speeds ranging from 0 to 3 m/s. The dataset features between 2 to 4 foreground sound sources, along with one background noise from the diffused TAU-SNoise dataset with a signal-to-noise ratio (SNR) ranging from 6 to 30 dB. The simulations were conducted using gpuRIR. Room dimensions were set to a width and length between 5 and 8 meters, and a height between 3 and 4 meters, with reverberation times ranging from 0.2 to 0.6 seconds. These parameters were sampled from uniform distributions. We simulated spatialized sound sources using a 4-channel tetrahedral microphone array with a radius of 4.2 cm. The procedure for dataset generation and details about class configuration and durations of audio clips are provided in the paper. This dataset poses a significant challenge for separation tasks due to the inclusion of moving sources, onset and offset conditions, overlapped in-class sources, and noisy reverberant environments.</p> <p>The procedure for dataset generation and details about class configuration and durations of audio clips are provided in the paper. This dataset poses a significant challenge for separation tasks due to the inclusion of moving sources, onset and offset conditions, overlapped in-class sources, and noisy reverberant environments.</p>
Analysis of Breath Sounds During Surgery
ClinicalTrials.gov study NCT07280546. IPD Sharing: YES. Countries: 1. Publications: 3.
Analysis of Snore Sound Following Minimal Invasive Surgery in Sleep-disordered Breathing Patients
ClinicalTrials.gov study NCT01955083. IPD Sharing: Not stated. Countries: 1. Publications: 1.
data & analysis scripts of " Behavioral effects of rhythm, carrier frequency and temporal cueing on the perception of sound sequences"
<p>Analysis scripts and data accompanying the manuscript "Behavioral effects of rhythm, carrier frequency and temporal cueing on the perception of sound sequences"</p>
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.
Figs 1 - 3. The three graphic representation s in Audiospectrographical analysis of cicada sound production: a catalogue (Hemiptera, Cicadidae)
Figs 1 - 3. The three graphic representation s of sound: the calling song of the PalaearcticspeciesCicadaon i Linnaeus 1758, 1: oscillogram (amplitude vs time). 2: spectrogram or sonagram (frequenc y vs time). 3: spectrum (amplitude vs frequency). Sound analysis software: SYNTANA T. Aubin CNRS U A 149 1 (Aubin 1994).
Call Graph Soundness in Android Static Analysis
<div> <pre>## Artifact Folder Structure Below is a brief explanation of each directory of our artifacts: - **dataset/**: Contains the dataset used in our study. - **dynamic_analysis/**: Contains everything needed to reproduce our dynamic analysis experiments. - **static_analysis/**: Contains everything needed to reproduce our static analyses experiments. - **instrumentation/**: Contains the necessary files to instrument the apps for the dynamic analysis. - **SLR/**: Contains the excel files with the papers collected during our Systematic Literature Review (SLR). Please ensure that all the necessary files and resources are present in the respective directories before running any experiments.</pre> </div>
Analysis of Orbital Sounding in Context with In Situ Ground Penetrating Radar at Jezero Crater, Mars
<p>This release includes all the SHARAD data used to produce analysis and figures in the paper, "Analysis of Orbital Sounding in Context with In Situ Ground Penetrating Radar at Jezero Crater, Mars", by M.C. Raguso et al., submitted to Geophysical Research Letters in February 2024.</p> <p>The manuscript is currently under review. The dataset will be released following the completion of the review process.</p> <p>This release also includes slides (pdf format) presented during the RIMFAX Science Team meeting (09/6/22-09/09/22).</p> <p>Preferred citation (DataCite format): </p> <p>Raguso, M.C., & Nunes, D.C. (2024). Analysis of Orbital Sounding in Context with In Situ Ground Penetrating Radar at Jezero Crater, Mars. [Dataset]. Zenodo. <a href="https://doi.org/10.5281/zenodo.10681430">https://doi.org/10.5281/zenodo.10681430</a></p> <p><em>For inquiries regarding the contents of this dataset, please contact the Corresponding Author listed in the README.txt file.</em></p>
Call Graph Soundness in Android Static Analysis
<pre>## Artifact Folder Structure Below is a brief explanation of each directory of our artifacts: - **dataset/**: Contains the dataset used in our study. - **dynamic_analysis/**: Contains everything needed to reproduce our dynamic analysis experiments. - **static_analysis/**: Contains everything needed to reproduce our static analyses experiments. - **instrumentation/**: Contains the necessary files to instrument the apps for the dynamic analysis. - **SLR/**: Contains the excel files with the papers collected during our Systematic Literature Review (SLR). - **results/**: Contains the results of our static analysis. Please ensure that all the necessary files and resources are present in the respective directories before running any experiments.</pre>
Data from: Logistic regression analysis of factors influencing the effectiveness of intensive sound masking therapy in patients with tinnitus
Objectives: To investigate factors influencing the effectiveness intensive sound masking therapy on tinnitus using Logistic Regression Analysis. Design: The study used a retrospective cross-section analysis. Participants: 102 patients with tinnitus were recruited at the Sun Yat-sen Memorial Hospital of Sun Yat-sen University, China. Intervention: Intensive sound masking therapy was used as an intervention approach for patients with tinnitus. Primary and secondary outcome measures: participants underwent audiological investigations and tinnitus pitch and loudness matching measurements, followed by intensive sound masking therapy. The Tinnitus Handicap Inventory (THI) was used as the outcome measure pre- and post-treatment. Multivariate logistic regression was performed to investigate the association of demographic and audiological factors with effective therapy. Results: According to the THI score changes pre-and post-sound masking intervention, fifty-one participants were categorised into an effective group, the remaining 51 participants were placed in a non-effective group. Those in the effective group were significantly younger than those in the non-effective group (p=0.012). Significantly more participants had flat audiogram configurations in the effective group (p=0.04). Multivariable logistic regression analysis showed that age (OR=0.96, 95% CI: 0.93, 0.99, p=0.007), audiometric configuration (p=0.027) and THI score pre-treatment (OR=1.04, 95% CI: 1.02, 1.07, p<0.001) were significantly associated with therapeutic effectiveness. Further analysis showed that patients with flat audiometric configurations were 5.45 times more likely to respond to intervention than those with high-frequency steeply sloping audiograms (OR=5.45, 95% CI: 1.67, 17.86, p=0.005). Conclusion: Audiometric configuration, age and THI scores appear to be predictive for the effectiveness of sound masking treatment. Gender, tinnitus characteristics and hearing threshold measures seem not to be related to treatment effectiveness. Further randomized control study is needed to provide further evidence of the effectiveness of prognostic factors in tinnitus interventions.
Tuble 1 in Audiospectrographical analysis of cicada sound production: a catalogue (Hemiptera, Cicadidae)
Tuble 1 (continued)
labk) (coniinucd) in Audiospectrographical analysis of cicada sound production: a catalogue (Hemiptera, Cicadidae)
labk) (coniinucd)
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Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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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.