Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
952
datasets available to search
ShareScore release 0.9.0
Dataset results
952 results for “Noise”
Data from: Noise pollution filters bird communities based on vocal frequency
BACKGROUND: Human-generated noise pollution now permeates natural habitats worldwide, presenting evolutionarily novel acoustic conditions unprecedented to most landscapes. These acoustics are not only harmful to humans, but threaten wildlife, and especially birds, via changes to species densities, foraging behavior, reproductive success, and predator-prey interactions. Explanations for the negative effects of noise on birds include the disruption of acoustic communication through energetic masking, potentially forcing species that rely upon acoustic communication to abandon otherwise suitable areas. However, this hypothesis has not been adequately tested because confounding stimuli often co-vary with noise and are difficult to separate from noise exposure. METHODOLOGY/PRINCIPAL FINDINGS: Using a natural experiment that controls for confounding stimuli, we evaluate whether species vocal features or urban-tolerance classification explain their responses to noise measured through habitat use. Two data sets representing nesting and abundance responses reveal that noise filters bird communities nonrandomly. Signal duration and urban tolerance failed to explain species-specific responses, but birds with low-frequency signals that are more susceptible to masking from noise avoided noisy areas and birds with higher pitched vocalizations remained. Signal frequency was also negatively correlated with body mass, suggesting that larger birds may be more sensitive to noise due to the link between body size and vocal frequency. CONCLUSIONS/SIGNIFICANCE: Our findings suggest that acoustic masking by noise may be a strong selective force shaping the ecology of birds worldwide. Larger birds with lower frequency signals may be excluded from noisy habitat, whereas smaller species persist via transmission of higher pitched signals. We discuss our findings as they relate to interspecific relationships among body size, vocal amplitude and frequency and suggest that they are immediately relevant to the global problem of increases in noise by providing critical insight as to which species traits influence tolerance of these novel acoustics.
Data from: Bats perceptually weight prey cues across sensory systems when hunting in noise
Anthropogenic noise can interfere with environmental information processing and thereby reduce survival and reproduction. Receivers of signals and cues in particular depend on perceptual strategies to adjust to noisy conditions. We found that predators that hunt using prey sounds can reduce the negative impact of noise by making use of prey cues conveyed through additional sensory systems. In the presence of masking noise, but not in its absence, frog-eating bats preferred and were faster in attacking a robotic frog emitting multiple sensory cues. The behavioral changes induced by masking noise were accompanied by an increase in active localization through echolocation. Our findings help to reveal how animals can adapt to anthropogenic noise and have implications for the role of sensory ecology in driving species interactions.
Classifying Handedness in Chiral Nanomaterials Using Label Noise-Robust Deep Learning
<p>Images of individual Te chiral nanoparticles and labels of their handedness for classifier training.</p>
Noise stimuli, particiants with dyslexia (ACI experiment)
<p>Noise stimuli involved in the Auditory Classification Image experiment (gaussian noise). 10.000 stimuli for each participant. wav format, 48 kHz</p>
Noise stimuli (ACI experiment)
<p>Noise stimuli involved in the Auditory Classification Image experiment (gaussian noise). 10.000 stimuli for each participant. wav format, 48 kHz</p>
Supplementary material: Modeling and Compensating Temperature-dependent Non-uniformity Noise in IR Microbolometer Cameras
<p><strong>Abstract</strong>: Images rendered by uncooled microbolometer-based infrared (IR) cameras are severely degraded by the spatial non-uniformity (NU) noise. The NU noise imposes a fixed-pattern over the true images, and the intensity of the pattern changes with time due to the temperature instability of such cameras. In this paper, we present a novel model and a compensation algorithm for the spatial NU noise and its temperature-dependent variations. The model separates the NU noise into two components: a constant term, which corresponds to a set of NU parameters determining the spatial structure of the noise, and a dynamic term, which scales linearly with the fluctuations of the temperature surrounding the array of microbolometers. We use a black-body radiator and samples of the temperature surrounding the IR array to offline characterize both the constant and the temperature-dependent NU noise parameters. Next, the temperature-dependent variations are estimated online using both a spatially uniform Hammerstein-Wiener estimator and a pixelwise least mean squares (LMS) estimator. We compensate for the NU noise in IR images from two long-wave IR cameras. Results show an excellent non-uniformity correction performance and a root mean square error of less than 0.25◦C, when array’s temperature varies approximately 15◦C.</p>
Dataset of the seismic noise measurements performed from 2009 to 2012 in Subequana Valley (central Italy)
<p>Use is free, provided the aforementioned reference is appropriately cited.<br> The dataset represents the seismic noise measurements performed in Subequana Valley (central Italy) and used in the publication “Gori, S., Falcucci, E., Ladina, C., Marzorati, S., and Galadini, F.: Active faulting, 3-D geological architecture and Plio-Quaternary structural evolution of extensional basins in the central Apennine chain, Italy, Solid Earth, 8, 319-337, doi:10.5194/se-8-319-2017, 2017”.<br> The measurements are archived in SAC format (http://ds.iris.edu/files/sac-manual/manual/file_format.html”).<br> Each SAC file contains information on the measurement parameters. Main header fields:<br> delta: sampling (s)<br> stla: measurement latitude (°N)<br> stlo: measurement longitude (°E)<br> stel: measurement elevation (m a.s.l.)<br> user0: sensor sensitivity (V/m/s)<br> user1: datalogger sensitivity (µV/count)<br> kstnm: measurement code<br> kevnm: experiment name<br> kuser0: gain<br> kuser1: unit of measure<br> kuser2: type of the sensor<br> kcmpnm: seismic channel<br> knetwk: network code of the experiment<br> kinst: type of the datalogger</p> <p>Description of files:<br> - CSVnoise_fromCV35_toCV87.zip: the archive of SAC files relative to noise measurements from CV35 to CV87<br> - CSVnoise_fromCV90_toC119.zip: the archive of SAC files relative to noise measurements from CV90 to C119<br> - CSVnoise_fromC120_toC218.zip: the archive of SAC files relative to noise measurements from C120 to C218</p>
Lateral Variations in Upper Mantle Discontinuities beneath Northeast China Revealed by Seismic Ambient Noise
<div>Data description:</div> <div> </div> <div>CCdata.zip:</div> <div>Re-sampling Cross-Correlation functions (4Hz) which contain three seismic arrays.</div> <div>CEA contains HL, JL, LN and NM networks. </div> <div>NECESSarray contains YP network. NECsaids contains DB network. </div> <div>All the stations are located east of 122E, between 41N and 46N. </div> <div>The cross-correlations are used to retrieved body-wave reflections from mantle transition zone discontinuities.</div> <div> </div> <div>Syntheticdata.zip:</div> <div>contains four parts: rawdata1d, rawdata2d, stackedwaveform-2d, and compare-1d</div> <div> </div> <div>rawdata1d: </div> <div>raw synthetic waveforms calculated by Qseis (Wang, 1999) after data-processings.</div> <div>H is increased from 0 to 30 km. </div> <div>The distance is 100 km. </div> <div> </div> <div>rawdata2d: </div> <div>raw synthetic waveforms calculated by SPECFEM2D (Tromp et al., 2008).</div> <div>Three models with depressed d660 (model 1-3) and with a slab on the d660 (model 4). </div> <div>100 receiver stations (surface), from 305 km to 1295 km in 10 km increments.</div> <div>49 vertical single-force sources (surface), from 320 km to 1280 km in 20 km increments </div> <div> </div> <div>stackedwaveform-2d:</div> <div>The final depth results with different models.</div> <div> </div> <div>compare-1d:</div> <div>The waveforms used to compare the rf and cc.</div> <div> </div> <div>Code:</div> <div>These codes can be used to make the figures of synthetic and NCFs results. </div> <div> </div> <div> </div> <div>NECsaidsDescription.docx:</div> <div>Detailed description about the NECsaids project conducted in northeast China from October, 2010 to September, 2017.</div> <div> </div> <div>station_loc.txt:</div> <div>Coordinate file (station, longitude, latitude) of the stations.</div> <div> </div> <div>Reference</div> <div>Wang, R. (1999). A simple orthonormalization method for stable and efficient computation of Green's functions. Bulletin of the Seismological Society of America, 89(3), 733-741. doi: 10.1785/BSSA0890030733</div> <div>Tromp, J., Komatitsch, D. and Liu, Q. Y. (2008). Spectral-element and adjoint methods in seismology. Commun Comput Phys 3, 1-32.</div>
Data and Code for Yeager et al., 2022: Enhanced Skill and Signal-to-noise in an Eddy-Resolving Decadal Prediction System
The sensitivity of decadal prediction system performance to model resolution is examined by comparing results from low- and high-resolution (LR and HR) predictions conducted with the Community Earth System Model (CESM). The primary difference between the two systems is the horizontal grid spacing of the ocean and atmosphere models (1° for both in LR; 0.1° and 0.25°, respectively, in HR), permitting a first direct comparison of how skill and signal-to-noise characteristics change when moving to the ocean eddy-resolved modeling regime. HR exhibits significantly increased skill and enhanced signal-to-noise for atmospheric fields compared to LR. This result suggests that mesoscale atmosphere-ocean interaction, which is present in HR but absent in LR, is a key mechanism involved in the transmission of predictable signals from the ocean to the atmosphere. Climate predictions can potentially be improved (and the signal-to-noise paradox alleviated) through explicit representation of ocean eddies and their interactions with the atmosphere.
Data associated with "Robust Structured Illumination Microscopy with Bayesian Noise Control"
<p>Experimental and synthetic data saved in tiff and/or zarr formats and SIM reconstruction scripts written in Python (Wiener and FISTA-SIM0. These also include estimated SIM patterns which are needed for B-SIM</p><ul><li>Synthetic data consisting of variably spaced line pairs. Found in <a href="https://zenodo.org/uploads/10037823">2023_10_02_synthetic_line_pairs.zip</a></li><li>Experimental data. Fluorescence images of one of the variably spaced line pair patterns on an ArgoSIM calibration slide. Found in <a href="https://zenodo.org/uploads/10037823">2023_08_02_folder=002_argosim_slide.zip</a></li><li>Experimental data. MitoTracker Red labelled mitochondria in live HeLa cells. Found in <a href="2023_08_07_folder=011_mitos_live_hela.zip">2023_08_07_folder=011_mitos_live_hela.zip</a></li><li>Camera calibration maps, including gain, variance, and offset. Found in <a href="camera_calibration.zip">camera_calibration.zip</a></li></ul>
Effect sizes of divergence in urban noise and song minimum frequency of grey-cheeked fulvettas Alcippe morrisonia morrisonia
<p><span>Noise pollution, one of the most prominent features of urbanization, is an important factor influencing the vocal behavior of urban wildlife. Studies have reported that many songbirds raise their song minimum frequencies in response to urban noise. It has been proposed that this increased minimum frequency (IMF) of songs is an adaptation that allows urban populations to cope with the masking effect of noise pollution. However, urban populations of some songbirds do not exhibit significant IMF compared with nonurban populations; thus, the notion that IMF is an adaptation to urban noise has been questioned. Furthermore, the effects of IMF might be influenced by both noise levels and the acoustic structures of songs. Here, we employed dichotomous and gradient effect size approaches to investigate IMF regarding two distinct acoustic structures (whistled and harmonic) in songs of six grey-cheeked fulvetta (</span><em><span>Alcippe morrisonia morrisonia</span></em><span>)</span><span> populations in Taiwan, three with high noise pollution and three with low noise pollution. We found that when using the dichotomous approach, </span><span>paired populations with significant divergence in noise levels exhibited weak or insignificant divergence in the minimum frequencies for both whistled and harmonic phrases</span><span>. In contrast, we found that when using the gradient approach, the effect size of noise-level divergence was strongly correlated with the effect size of divergence in the minimum frequency of the harmonic phrase and only moderately correlated with the effect size of divergence in the minimum frequency of the whistled phrase. These findings suggest that noise pollution has a more pronounced effect on the divergence in the minimum frequency of harmonic phrases used in short-range communication compared to the whistled phrases used in long-range communication. We conclude that for population comparisons on the IMF, adopting a gradient approach could provide insights into the impact of noise pollution on the acoustic structures of songs across various communication ranges.</span></p>
Effect of the loading condition on the statistics of crackling noise accompanying the failure of porous rocks
<p>We test the hypothesis that loading conditions affect the statistical features of crackling noise accompanying the failure of porous rocks by performing discrete element simulations of the tensile failure of numerical rock samples and comparing the results to those of compressive simulations of the same specimens. Cylindrical samples are constructed by sedimenting randomly sized spherical particles connected by beam elements representing the cementation of granules. Under a slowly increasing tensile load, the cohesive contacts between particles break in bursts whose size fluctuates over a broad range. Close to failure breaking avalanches are found to localize on a highly stressed region where the catastrophic avalanche starts and the specimen falls apart into two pieces along a spanning crack. The fracture plane has a random position and orientation falling most likely close to the center of the specimen perpendicular to the load direction. In spite of the strongly different strengths and spatial structure of damage of tensile and compressive failure of numerical rocks, our calculations revealed that the size, energy, and duration of crackling avalanches, and the waiting time between consecutive events all obey scale free statistics with power law exponents which agree within the error bars in the two loading cases.</p>
Dataset: Thermal noise calibration of functionalized cantilevers for force microscopy: effects of the colloidal probe position.
<p>Dataset for article "Thermal noise calibration of functionalized cantilevers for force microscopy: effects of the colloidal probe position"</p><p>The raw data is in the 6 zip files (AIO*.zip), which contains thermal noise spectra measured on the raw cantilevers close to the free end (folders AIO#, where #=1, 2 or 3 for samples A, B or C), or on the loaded cantilever at various positions along its length (folders AIO#-ScanHF, where #=1, 2 or 3 for samples A, B or C). The file format is Matlab data file (.mat), it include the vectors f (for frequency axis, in Hz) and p (power spectrum density, in m^2/Hz). Other variables are erreur (some internal check that the calibration of the interferometer is pertinent) and PointW (mean intensity collected by the interferometer, and mean contrast on the 2 quadrature signals). For the loaded cantilever, we also record the laser spot position (XFaisceau and YFaisceau, in µm, origin close to the free end on the cantilever), some timing information to track for drifts, and ellipse (a calibration step of the quadrature phase interferometer).</p><p>The SEM images of the samples are included in the zip file SEMimages.zip</p><p>All analysis scripts (Matlab .m files) are included:</p><ul><li>AnalyseAll.m reads the raw data files and extract all the pertinent information, saving it to file AnalyseAll.mat</li><li>Analysis_cp analyses the pre-processed data with the single contact point model</li><li>Analysis_endload analyses the pre-processed data with the rigid end load model</li><li>figspectrum.m creates Fig. 4 of the article</li><li>plot_cp_endload.m creates Fig. 5 and 6 of the article</li></ul><p>All other scripts (.m) are dependencies that are necessary for the 3 former scripts to run. All scripts are commented and should be self explanatory. Of interest are the scripts mode_shape_cp.m and mode_shape_endload.m, which compute the resonant mode shape of a loaded cantilever for the two models, when given the parameters on the load size and position.</p>
Data Release for "Revisiting the evidence for precession in GW200129 with machine learning noise mitigation"
<p>Cleaned gravitational-wave data frame for the Livingston interferometer around GW200129 using NLSub, a machine-learning algorithm. For more details, see the publication on ArXiv: <a href="https://arxiv.org/abs/2311.09921">https://arxiv.org/abs/2311.09921</a>.</p><p>The data frame can be loaded in Python using e.g. GWPy TimeSeries class:</p><blockquote><p>from gwpy.timeseries import TimeSeries<br>tseries = TimeSeries.read('L-L1_DCS-CALIB_STRAIN_CLEAN_C01_NLSUB_P2300358_v4-1264314077-4078.hdf5')</p></blockquote><p> </p>
Ambient noise from the atmosphere within the seismic hum period band: A case study of hurricane landfall
<p>Spectral analysis results, synthetic Green's functions, and seismic modeling results of this study.</p> <p>This work can be found at GitHub: <a href="https://github.com/NickJi98/Atm_Noise_2024_EPSL.git">https://github.com/NickJi98/Atm_Noise_2024_EPSL.git</a></p>
Mechanisms for Layered Anisotropy and Anomalous Magmatism of Alaska Subduction System Revealed by Ambient Noise Tomography and the Wave Gradiometry Method
<p>Depth Coverage: 2.0 - 230.0 km<br>Areal Coverage: Latitude: 54.8 to 72.0 Longitude: -168.0 to -129.0<br>Model Description: A high-resolution 3D azimuthal anisotropic shear wave velocity model beneath Alaska and its surroundings on a ~50‐km grid extracted by ambient noise tomography and wave gradiometry method .</p> <p>Columns in the subfile, from left to right, are latitude, longitude, shear wave velocity, fast direction, and the magnitude of anisotropy, respectively. </p>
Upper Crustal Structure of the Xinfengjiang Reservoir from Ambient Noise Double Beamforming Tomography and Its Implications for Induced Seismicity
<p>The file "CC.tar.gz" contains the linearly stacked ZZ component cross-correlations for all station pairs.</p> <p>The file "Model.tar.gz" contains the 3-D upper crustal model of the Xinfengjiang Reservoir via ambient noise Double-Beamforming tomograpy.</p>
Ambient noise data and velocity model from DEEPEN array in Hengill geothermal field, Iceland
<p>This repository contains the data and velocity model associated with the manuscript entitled "<em>Crustal characterization of the Hengill geothermal fields: Insights from isotropic and anisotropic seismic noise imaging using a 500-node array</em>" by Wu et al. (2024), to be published in <em>Journal of Geophysical Research: Solid Earth</em>. </p> <p>The dataset is the nine component cross-correlation functions (ZZ, ZN, ZE, NZ, NN, NE, EZ, EN, EE) after stacking over seismic array deployment time period (summer 2021) and after spatial averaging (bin stacking). The bin locations are provided in "bin_locations.txt".</p> <p>The derived VOIGT velocity and radial anisotropy model can be found in "Hengill_Voigt_Aniso_DEEPEN_4share.txt".</p> <p> </p>
Data accompanying: Sweet-spot operation of a germanium hole spin qubit with highly anisotropic noise sensitivity
<p>These are the data accompanying the publication titled: 'Sweet-spot operation of a germanium hole spin qubit with highly anisotropic noise sensitivity'.</p>
Extra-P Version Used for Noise-Resilient Empirical Performance Modeling with Deep Neural Networks
<p>This is the Extra-P source code that was used for the analysis and evaluation of the IPDPS 2021 paper "Noise-Resilient Empirical Performance Modeling with Deep Neural Networks". It also contains the checkpoints and saved models for the DNN part of the adaptive modeler as well as the gathered synthetic evaluation data.</p>
ScienceDex guides
Understand access before you commit
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.