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952 results for “Noise”
Raw data from: Airport noise disturbs foraging behavior of Japanese pipistrelle bats
<p><span>The expansion of anthropogenic noise poses an emerging threat to </span><span>the </span><span>survival and reproductive success of various organisms. Previous investigations have focused on the detrimental effects of anthropogenic noise on the foraging behavior in some terrestrial and aquatic animals. Nevertheless, the role of airport noise in impairing foraging activities of most wild animals has been neglected. Here, we aimed to assess whether foraging behavior in free-living Japanese pipistrelle bats (<em>Pipistrellus</em> <em>abramus</em>) can be disturbed by airport noise. We used audio recording </span><span>to </span><span>monitor foraging activities of bats at 11 sites around the runway of a municipal airport. We quantified noise level and spectra, aircraft activity, habitat type, nightly temperature, wind speed, and moon phase for each site. The analysis revealed that noise level and aircraft activity were significant negative predictors for the number of bat passes and feeding buzzes around the runway, even after controlling for the effects of other environmental factors. There was no marked spectral overlap between bat echolocation pulses and airport noise in the presence and absence of low-flying aircraft. The spectro-temporal parameters of echolocation vocalizations emitted by bats were dependent on noise level, aircraft activity, and habitat type. These results provide correlative evidence that airport noise can reduce foraging activities of wild pipistrelle bats. Our findings add to the current knowledge of adverse impacts of airport noise on foraging bats in artificial ecosystems and provide a basis for further research on the mechanisms behind noise pollution near airports.</span></p>
t1-Noise Elimination by Continuous Chemical Shift Anisotropy Refocusing
<p>Data archived here corresponds to the experimental and simulation data discussed in the Solid-State Nucl. Magn. Reson. paper:<br> "t1-Noise Elimination by Continuous Chemical Shift Anisotropy Refocusing". This includes the recoupling time optimizations and 2D D-HMQC spectra performed using the SR4^2_1, TONE with SR4^2_1 and the CSA-free SR6^3_2 recoupling sequences on 15N-glycine, Y-MOF-76, Histidine hydrochloride, and Al(acac)3, in addition to the SIMPSON simulations of the various sequences as a function of the MAS rate offset.</p>
Impact of training set size on the ability of deep neural networks to deal with label noise
<p>This is the data set accompanying the publication 'Impact of training set size on the ability of deep neural networks to deal with label noise'</p> <p> </p> <p><strong>License</strong></p> <p>This work is shared under the <em><code>Creative Commons Attribution ShareAlike 4.0 International License</code></em><code><em> </em>(CC BY-SA 4.0)</code><em>: </em>https://creativecommons.org/licenses/by-sa/4.0/</p> <p>The dataset is taken from the 6th SpaceNet challenge (https://spacenet.ai/sn6-challenge/) which also falls under the <code>CC BY-SA 4.0 license</code>. The original dataset was modified by removing objects from the buildings json files and converting the json files to png images.</p> <p>Creators of the SpaceNet dataset:</p> <p>Shermeyer, J., Hogan, D., Brown, J., Etten, A.V., Weir, N., Pacifici, F., Hänsch, R., Bastidas, A., Soenen, S., Bacastow, T.M., & Lewis, R.</p> <p>SpaceNet partners: https://spacenet.ai/about-us/</p> <p> </p>
Physiological responses of narwhals to anthropogenic noise: a case study with seismic airguns and vessel traffic in the Arctic
<p>Limited polar geographical range, narrowly defined migratory routes, and deep-diving behaviors make narwhals exceptionally vulnerable to anthropogenic disturbances including oceanic noise. Although behavioral studies indicate marked responses of cetaceans to disturbance, the link between fear reactions and possible injury from noise exposure is limited for most species.</p> <p>To address this, we deployed custom-made heart rate-accelerometer-depth recorders on 13 adult narwhals in Scoresby Sound, East Greenland across a five-year period (2014-2018). Physiological responses of the cetaceans were monitored in the absence (n = 13 animals) or presence (n = 2 animals across 3 acoustic events) of experimentally directed, seismic airgun pulses and associated vessels (full volume source level = 241 dB re 1 μPa-m).</p> <p>We found that anthropogenic noise resulted in marked cardiovascular, respiratory and locomotor reactions by two narwhals exposed to seismic pulses across three acoustic events. The general behavioral response to seismic and vessel noise included an 80% reduction in the duration of gliding during dive descents by seismic-exposed narwhals compared to controls, and the prolongation of high-intensity activity (ODBA > 0.20 g) with elevated stroke frequencies exceeding 40 strokes per minute. Noise exposure also resulted intense (< 10 bpm) bradycardia that was decoupled from stroking frequency. This decoupling instigated increased variability in heart rate, with the heart switching rapidly between bradycardia and exercise tachycardia during noise exposure. Maximum respiratory frequency following seismic exposure, 12 breaths.min<sup>-1</sup>, was 1.5 times control levels.</p> <p>Overall, the effect of seismic/ship noise exposure on wild narwhals was a 2.0 – 2.2-fold increase in the energetic cost of diving, which paradoxically occurred during suppression of the cardiac exercise response. This unusual relationship between diving heart rate and exercise intensity represents a new metric for characterizing the level of fear reactions of wild marine mammals exposed to different environmental stressors. Together, the multi-level reactions to anthropogenic noise by this deep-diving cetacean demonstrated how a cascade of effects along the entire oxygen pathway could challenge physiological homeostasis especially if disturbance is prolonged.</p>
Wind Noise Dataset
<p> Wind Noise Dataset including artificially generated and mobilephone recorded samples.</p>
Data from: Phylogenetic signal detection from an ancient rapid radiation: effects of noise reduction, long-branch attraction, and model selection in crown clade Apocynaceae
Crown clade Apocynaceae comprise seven primary lineages of lianas, shrubs, and herbs with a diversity of pollen aggregation morphologies including monads, tetrads, and pollinia, making them an ideal group for investigating the evolution and function of pollen packaging. Traditional molecular systematic approaches utilizing small amounts of sequence data have failed to resolve relationships along the spine of the crown clade, a likely ancient rapid radiation. The previous best estimate of the phylogeny was a five-way polytomy, leaving ambiguous the homology of aggregated pollen in two major lineages, the Periplocoideae, which possess pollen tetrads, and the milkweeds (Secamonoideae plus Asclepiadoideae), which possess pollinia. To assess whether greatly increased character sampling would resolve these relationships, a plastome sequence data matrix was assembled for 13 taxa of Apocynaceae, including nine newly generated complete plastomes, one partial new plastome, and three previously reported plastomes, collectively representing all primary crown clade lineages and outgroups. The effects of phylogenetic noise, long-branch attraction, and model selection (linked versus unlinked branch lengths among data partitions) were evaluated in a hypothesis-testing framework based on Shimodaira–Hasegawa tests. Discrimination among alternative crown clade resolutions was affected by all three factors. Exclusion of the noisiest alignment positions and topologies influenced by long-branch attraction resulted in a trichotomy along the spine of the crown clade consisting of Rhabdadenia + the Asian clade, Baisseeae + milkweeds, and Periplocoideae + the New World clade. Parsimony reconstruction on all optimal topologies after noise exclusion unambiguously supports parallel evolution of aggregated pollen in Periplocoideae (tetrads) and milkweeds (pollinia). Our phylogenomic approach has greatly advanced the resolution of one of the most perplexing radiations in Apocynaceae, providing the basis for study of convergent floral morphologies and their adaptive value.
Seismic ambient noise CCFs at Suwanosejima volcano, Japan
<p>The dailyCCF.tar contains data of daily seismic ambient noise CCFs at Suwanosejima volcano, Japan (April 1, 2017-December 31, 2021). These CCFs have been used to create the results in the accompanying paper "Seismic scattering property changes correlate with ground deformation at Suwanosejima volcano, Japan" by Takashi Hirose, Hideki Ueda, and Eisuke Fujita, submitted to the Journal of Geophysical Research: Solid Earth (https://doi.org/10.1002/essoar.10510785.2).</p>
Dataset for "Emerging tremors and increasing seismic noise precede micro-earthquakes triggered in a fluid-activated shale fault slip experiment (2015, Mt Terri URL, Switzerland)"
<p>This dataset contains the raw data of the injection experiment, performed in the Mt Terri Underground Platform in 2015 and used in the article:</p> <p><strong>De Barros, L., </strong>Guglielmi, Y., F. Cappa, C. Nussbaum, J. Birkholzer, 2023. Induced microseismicity and tremor signatures illuminate different slip behaviors in a natural shale fault reactivated by a fluid pressure stimulation (Mont Terri), <em>Geophysical Journal International</em>, 10.1093/gji/ggad231<br> <br> From a horizontal gallery, three vertical boreholes allowed the deployment of an injection probe (called SIMFIP; Guglielmi et al., 2014) and the monitoring sensors in the upper compartment of a N50°-60°SE fault zone. The 2.4 m long injection chamber of the SIMFIP probe was centered at 340.6 m depth, where a 3D displacement sensor was anchored on the borehole walls. A second SIMFIP probe is located 3.1 m northwest of the injection at a depth of 337.65 m, with another deformation sensor. Both deformation sensors measured the full strain tensor thanks to a Bragg optic fiber network, jointly with a fluid pressure sensor. A third borehole, located 2 m north of the monitoring probe, was dedicated to seismic monitoring. Two sets of collocated sensors, composed of a vertical geophone, a 3C accelerometer and an acoustic sensor, were positioned 9 m apart, above and below the main fault zone. These seismic sensors have a flat response in the ranges 0.01-0.5 kHz, 0.01-4 kHz and 0.5-10 kHz, respectively. Finally, the flowrate and pressure were also measured at the injection pump, located in the gallery.<br> For more details on the injection, we refer the reader to:<br> • Jeanne, P., Guglielmi, Y., Rutqvist, J., Nussbaum, C., Birkholzer, J., 2018. Permeability Variations Associated With Fault Reactivation in a Claystone Formation Investigated by Field Experiments and Numerical Simulations. J. Geophys. Res. Solid Earth 123, 1694–1710. https://doi.org/10.1002/2017JB015149<br> • Guglielmi, Y., Nussbaum, C., Cappa, F., De Barros, L., Rutqvist, J., Birkholzer, J., 2021. Field-scale fault reactivation experiments by fluid injection highlight aseismic leakage in caprock analogs: Implications for CO2 sequestration. Int. J. Greenh. Gas Control 111, 103471. https://doi.org/10.1016/j.ijggc.2021.103471<br> • Guglielmi, Y., Nussbaum, C., Jeanne, P., Rutqvist, J., Cappa, F., Birkholzer, J., 2020. Complexity of Fault Rupture and Fluid Leakage in Shale: Insights From a Controlled Fault Activation Experiment. J.Geophys. Res. Solid Earth 125, e2019JB017781. https://doi.org/10.1029/2019JB017781<br> • Guglielmi, Y., Cappa, F., Lançon, H., Janowczyk, J.B., Rutqvist, J., Tsang, C.F., Wang, J.S.Y., 2014. ISRM Suggested Method for Step-Rate Injection Method for Fracture In-Situ Properties (SIMFIP): Using a 3-Components Borehole Deformation Sensor. Rock Mech. Rock Eng. 47, 303–311. https://doi.org/10.1007/s00603-013-0517-1</p>
Ambient noise tomography of Gran Canaria island (Canary Islands) for geothermal exploration
<p>This file contains the 3-D S-wave velocity model of Gran Canaria island.</p> <p><strong>Abstract</strong></p> <p>Ambient noise tomography (ANT) has proved to be efficient in resolving crustal structures for different purposes. Despite the numerous studies carried out in Gran Canaria in the past for purposes of geothermal exploration, ANT had never been used before on this island. We applied this technique to understand Gran Canaria island's shallow structure, determining the 3-D S-wave velocity model of the island and focusing on its implications for geothermal exploration. We used data from 30 seismic stations installed between October 2019 and February 2020. Our findings revealed five relevant velocity anomalies helpful in understanding the island's geology and its geothermal potential. In particular, we identified two high-velocity anomalies in the central part of the island aligned with the primary northwest-southeast structural trends of Gran Canaria. We interpret them as evidence of intrusive volcanic bodies emplaced during the early stages of the island's geological history. We also identified three low-velocity zones located in different parts of the island. We maintain that these anomalies could be associated with porous and highly fractured materials produced during the more recent volcanic episodes. In addition, we observed a spatial correlation of anomalies in the electric conductivity identified in previous studies and strong lateral gradients in our S-wave velocity model. We interpret them as evidence of hydrothermal circulation and thermal anomalies in correspondence of lateral contacts between different geological units and/or faults.</p> <p> </p>
The ambient noise cross-correlation function and teleseismic events, the Love-wave phase velocities, Rayleigh-wave phase and group velocities and H/V, Vsv and Vsh model in the study region (CNCC)
<p>The cross-correlation functions form EOBSArray (COR_CNCC), The Love-wave phase velocities (Love_phase), Rayleigh-wave phase (Rayleigh_phase) and group velocities (Rayleigh_group) and H/V (HtoV),and 3-D Vsv and Vsh model and related uncertainties (Vsv_Vsh_model) in the study region (CNCC) are archieved in the file named CNCC_data.7z.</p>
Input files for elPaSo for the paper: Efficient Solution Strategies for Cabin Noise Assessment of wave-resolving Aircraft Fuselage Models
<div> <div>This dataset showcases the input and output data for the paper: "Efficient Solution Strategies for Cabin Noise Assessment of wave-resolving Aircraft Fuselage Models".</div> <div> </div> The model data are made available in the folder "models" and contain the three models corresponding to the frequency-dependent mesh of the aircraft fuselage model. <div>Three frequency-dependent meshes are placed in subfolders, where the number indicates up to which frequency in Hz the respective model can be used. Here, the ".cub5" files are the mesh files created by the meshing tool Coreform Cubit. For the application of the FEM elPaSo is used. Here, the ".hdf5" files serve as the elPaSo input.</div> <div>Once computed, the results are written in the "eGenOutput*.hdf5" files. The results for the degrees of freedom across the frequency domain can be found here.</div> </div>
AlleNoise - large-scale text classification benchmark dataset with real-world label noise
<div> <div> <div> <div> <p><span>AlleNoise</span><span> is a benchmark dataset for large-scale multi-class text classification with real-world label noise. It consists of e-commerce product titles from Allegro.com with corresponding category labels. The noise distribution comes from actual users of a major e-commerce marketplace, so it realistically reflects the semantics of human mistakes. In addition to the noisy labels, we provide human-verified clean labels and a meaningful, hierarchical taxonomy of categories. Code and data is available at https://github.com/allegro/AlleNoise.<br></span></p> </div> </div> </div> </div>
Raw and post-processed data from the study "Mapping the spectrotemporal regions influencing perception of French stop consonants in noise"
<p>The current dataset contains all data needed to replicate the study from Carranante et al. "Mapping the spectrotemporal regions influencing perception of French stop consonants in noise"<strong><br></strong></p> <p><strong>Use these data:</strong></p> <ol> <li>Download all these data, place them in a local directory of your computer. If you have MATLAB and you downloaded a local copy of the fastACI toolbox (open access at: <a href="http://github.com/aosses-tue/fastACI">GitHub</a>) you can recreate the figures of our paper.</li> <li>After initialising the toolbox (type 'startup_fastACI;', without quotation marks in MATLAB) and then type either of the following commands, to recreate the figure you want. To recreate the figures in the main text:<br> <pre><code>publ_carranante2024_figs('fig1','zenodo'); </code></pre> <p>To generate the figures of the supplementary materials:</p> <pre><code>publ_carranante2024_figs('fig1_suppl','zenodo');</code></pre> </li> </ol> <p><strong>References:</strong></p> <ul> <li>Paper not published yet</li> <li><strong>fastACI toolbox</strong>: Alejandro Osses, Léo Varnet. fastACI toolbox: the MATLAB toolbox for investigating auditory perception using reverse correlation (v1.2). Zenodo. doi:<a href="https://doi.org/10.5281/zenodo.7314014">10.5281/zenodo.7314014</a>. Supplement to: <a href="http://github.com/aosses-tue/fastACI/tree/v1.2">https://github.com/aosses-tue/fastACI/tree/v1.2</a></li> </ul>
Data for "The 20-year highest tropical cyclone-generated waves associated with the maximum energy of seismic noises" (Subset 4)
<p>This is dataset of ocean wave simulations used in the paper "The 20-year highest tropical cyclone-generated waves associated with the maximum energy of seismic noises" by Shimura et al. (submitted).</p> <p>The dataset contains </p> <ul> <li>significant wave height (Subset 1),</li> <li>wave induced surface pressure (Subset 2)</li> <li>long-period componet of wave heights (Subset 3)</li> <li>long-period component of surface pressure (Subset 4)</li> </ul> <p>during 2004 from 2023 summer. </p>
Data for "The 20-year highest tropical cyclone-generated waves associated with the maximum energy of seismic noises" (Subset 1)
<p>This is dataset of ocean wave simulations used in the paper "The 20-year highest tropical cyclone-generated waves associated with the maximum energy of seismic noises" by Shimura et al. (submitted).</p> <p>The dataset contains </p> <ul> <li>significant wave height (Subset 1),</li> <li>wave induced surface pressure (Subset 2)</li> <li>long-period componet of wave heights (Subset 3)</li> <li>long-period component of surface pressure (Subset 4)</li> </ul> <p>during 2004 from 2023 summer. </p>
Data for "The 20-year highest tropical cyclone-generated waves associated with the maximum energy of seismic noises" (Subset 2)
<p>This is dataset of ocean wave simulations used in the paper "The 20-year highest tropical cyclone-generated waves associated with the maximum energy of seismic noises" by Shimura et al. (submitted).</p> <p>The dataset contains </p> <ul> <li>significant wave height (Subset 1),</li> <li>wave induced surface pressure (Subset 2)</li> <li>long-period componet of wave heights (Subset 3)</li> <li>long-period component of surface pressure (Subset 4)</li> </ul> <p>during 2004 from 2023 summer. </p>
Pediatric CT Noise Texture Augmentation
<p>Dataset of routine and quarter dose anthropomorphic phantom (<a href="https://aapm.onlinelibrary.wiley.com/doi/10.1118/1.4926847">XCAT</a>) CT simulations using the <a href="https://github.com/JeffFessler/mirt">Michigan image Reconstruction Toolbox (MIRT)</a>.</p>
Codes: An early warning indicator trained on stochastic disease-spreading models with different noises
<p>This dataset contains the training data (Version V1) and all the codes (Version V2) of the paper entitled "An early warning indicator trained on stochastic disease-spreading models with different noises." </p> <p>Time series and corresponding residuals from white noise (equation 2.5), environmental noise (equation 2.8), and demographic noise (equation 2.9) are stored in the training_data_WhiteN, training_data_EnvN, and training_data_DemN folders, respectively. All residuals of the time series are contained in the training_resids folder, which also includes labels and groups of the training data. For details on the data generation process, please refer to section 3.1 in the paper. </p>
Computation noise promotes zero-shot adaptation to uncertainty during decision-making in artificial neural networks
<p>This dataset contains the behavioral choice data obtained from N = 230 participants that played a two-armed bandit task (139 females, age: 34 +/- 10 years) in partial and complete feedback conditions, as described in (Findling, Skvortsova et al., 2019, Nature Neuroscience, https://doi.org/10.1038/s41593-019-0518-9).</p> <div> <div> <div> <p>The experiment was performed on the Prolific platform (prolific.co) and the research was carried out following the principles and guidelines for experiments including human participants provided in the declaration of Helsinki and approved by the relevant authorities (Inserm Ethical Review Committee, IRB #00003888). All participants provided written informed consent prior to their inclusion.</p> </div> </div> </div>
Dataset and code for 'Signal to Noise Ratio and Spectral Sampling Constraints on Olivine Detection and Compositional Determination in the Intermediate Infrared Region'
<p>Feature fitting code and spectra of olivine samples used in paper "<em>Signal to Noise Ratio and Spectral Sampling Constraints on Olivine Detection and Compositional Determination in the Intermediate Infrared Region: Applications in Planetary Sciences</em>"</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.