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70 results for “spectrum analysis.”
Solar and interplanetary magnetic field data analyzed in "Optimal frequency-domain analysis for spacecraft time series: Introducing the missing-data multitaper power spectrum estimator"
<p>This dataset contains simultaneous measurements of the interplanetary magnetic field magnitude <B> and the sun's radio flux at 10.7 cm <F10.7>. <B> measurements come from a series of spacecraft located at the L1 point, while <F10.7> was measured by the ongoing monitoring program by Canada's Dominion Radio Astrophysical Observatory. Bartels rotation-averaged data were downloaded from NASA's OMNIWeb, https://omniweb.gsfc.nasa.gov/html/ow_data.html. The file contains other solar wind plasma parameters that were not used in the analysis.</p>
Data for: Cardiac and Respiratory Self-Gating in Radial MRI using an Adapted Singular Spectrum Analysis (SSA-FARY)
<p>Magnetic Resonance Imaging measurement data used in our paper about self-gating with SSA-FARY (DOI: <a href="https://doi.org/10.1109/TMI.2020.2985994">10.1109/TMI.2020.2985994</a>). Cardiac data was obtained from eight volunteers with no known illness using single-slice radial (SS), simultaneous multi-slice radial (SMS), and stack-of-stars (SoS) FLASH and bSSFP sequences and is provided in a file format used by the BART toolbox (DOI: <a href="http://doi.org/10.5281/zenodo.592960">10.5281/zenodo.592960</a>).</p>
Audio files for spectrum analysis demonstration
<div>This data set consists of 6 real-world audio files (in .wav format, 48000Hz, mono) that are carefully crafted as examples for spectral analysis (i.e for teaching or as sample test data for algorithms).</div> <div> </div> <div>The files have clear discernible sound with an added true random background ambient noise (composed of: distant fan noise + distant street traffic + close harddisk clicking noise). The sound is clearly discernible by a human, despite the noise. </div> <div> </div> <div>- There are some musical sounds (the note G3 on several instruments; fundamental frequency 196Hz) on a tubular bell, classical piano, trumpet, violin. The sounds of the instrument was generated from MIDI banks with FluidSynth software, played on a loudspeaker and re-recorded with an analogical microphone (with the ambient noises). Audio processing was performed with Tenacity software;</div> <div>- Sample from human speech (wovel “o”), with the same processing as above; </div> <div>- The “Noise” file is purely digitally generated (white noise).</div> <div> </div> <div> </div> <div>Each audio set is composed of three files: </div> <div>- The audio file (*.wav), each sampled at 48000 Hz, Mono. </div> <div>- an amplitude file (*_amplitude.csv, corresponding linear amplitudes recorded by the microphone of the .wav file). Numeric format in simple text format (.csv) with labeled column names. </div> <div>-a spectrum file (*_spectrum.csv, frequency/amplitude(dB) ) with the results of a FFT (Fast Fourier Transform). Numeric format in simple text format (.csv) with labeled column names. </div> <div> </div> <div>Detailed description of each set is provided below.</div> <div> </div> <div> <ul> <li><strong>Bell_G3.wav</strong></li> <li>Bell_G3_amplitude.csv:<br>Length processed: 113851 samples 2.37190 seconds.<br>Sample Rate: 48000 Hz. <br>Sample values on linear scale. 1 channel (mono).<br>Length processed: 113851 samples, 2.37190 seconds.<br>Peak amplitude: 0.59001 (linear) -4.58276 dB. <br>Unweighted RMS: -19.87796 dB.<br>DC offset: 0.00069 linear, -63.18732 dB.</li> <li>Bell_G3_spectrum.csv:<br>FFT transform (Hz / dB)</li> </ul> </div> <div> <ul> <li><strong>Noise.wav</strong></li> <li>Noise_amplitude.csv:<br>Length processed: 31765 samples 0.66177 seconds.<br>Sample Rate: 48000 Hz. <br>Sample values on linear scale. 1 channel (mono).<br>Length processed: 31765 samples, 0.66177 seconds.<br>Peak amplitude: 0.52797 (linear) -5.54788 dB.<br>Unweighted RMS: -16.61153 dB.<br>DC offset: -0.00013 linear, -77.53051 dB</li> <li>Noise_spectrum.csv)<br>FFT transform (Hz / dB)</li> </ul> </div> <div> <ul> <li><strong>Piano_G3.wav</strong></li> <li>Piano_G3_amplitude.csv:<br>Sample Rate: 48000 Hz.<br>Sample values on linear scale. 1 channel (mono).<br>Length processed: 133063 samples, 2.77215 seconds.<br>Peak amplitude: 0.41070 (linear) -7.72946 dB.<br>Unweighted RMS: -23.95101 dB.<br>DC offset: 0.00030 linear, -70.58058 dB.</li> <li>Piano_G3_spectrum.csv:<br>FFT transform (Hz / dB)</li> </ul> </div> <div> <ul> <li><strong>Trumpet_G3.wav</strong></li> <li>Trumpet_G3_amplitude.csv:<br>Sample Rate: 48000 Hz.<br>Sample values on linear scale. 1 channel (mono).<br>Length processed: 66931 samples, 1.39440 seconds.<br>Peak amplitude: 0.29551 (linear) -10.58853 dB. <br>Unweighted RMS: -22.00611 dB.<br>DC offset: 0.00076 linear, -62.39740 dB.</li> <li>Trumpet_G3_spectrum.csv:<br>FFT transform (Hz / dB)</li> </ul> </div> <div> <ul> <li><strong>Violin_G3.wav</strong></li> <li>Violin_G3_amplitude.csv:<br>Sample Rate: 48000 Hz.<br>Sample values on linear scale. 1 channel (mono).<br>Length processed: 59252 samples, 1.23442 seconds.<br>Peak amplitude: 0.41633 (linear) -7.61119 dB.<br>Unweighted RMS: -18.36738 dB.<br>DC offset: 0.00021 linear, -73.46784 dB.</li> <li>Violin_G3_spectrum.csv:<br>FFT transform (Hz / dB)</li> </ul> </div> <div> <ul> <li><strong>Wovel_O.wav</strong></li> <li>Wovel_O_amplitude.csv<br>Sample Rate: 48000 Hz.<br>Sample values on linear scale. 1 channel (mono).<br>Length processed: 4975 samples, 0.10365 seconds.<br>Peak amplitude: 0.46174 (linear) -6.71214 dB. <br>Unweighted RMS: -14.88086 dB.<br>DC offset: 0.00009 linear, -80.54917 dB.</li> <li>Wovel_O_spectrum.csv:<br>FFT transform (Hz / dB)</li> </ul> </div> <div> </div> <div>These files are created by A. Iftime and released under Creative Commons Licence, 2024. </div> <div> </div> <div>You might cite the dataset as: </div> <div>“Audio files for spectrum analysis demonstration” [dataset] (2024), in “Medical Biophysics for 1st year medical students”, by Călinescu O., Babeș R., Iftime A., Băran I., Ionescu D., Ganea C., in publishing </div>
Data from: Analysis of leaf microbiome composition of near-isogenic maize lines differing in broad-spectrum disease resistance
<p>Data and code associated with the submitted manuscript "Analysis of leaf microbiome composition of near-isogenic maize lines differing in broad-spectrum disease resistance". Detailed descriptions of each file can be found in the README.txt . The raw sequence data associated with this work can be downloaded from the NCBI Sequence Read Archive, listed under BioProject #PRJNA565009<strong>.</strong></p>
Data files for Constraints on axionlike particles from a combined analysis of three flaring Fermi flat-spectrum radio quasars
<p>In this repository, we provide data files in connection to our publication “Constraints on axionlike particles from a combined analysis of three flaring Fermi flat-spectrum radio quasars” submitted for publication in Physical Review D and available on the Arxiv: <a href="https://arxiv.org/abs/2211.03414">https://arxiv.org/abs/2211.03414</a></p> <p><br> In the paper, we analyze data from the Fermi Large Area Telescope (LAT) of three flat spectrum radio quasars (FSRQs): 3C454.3, 3C279, and CTA102, to search for signatures of oscillations between photons and axion-like particles (ALPs).<br> In this repository, we provide the following data:</p> <ul> <li>Files ending on *_data_seds.npy contain the spectral energy distributions (SEDs) measured with the Fermi LAT and extracted using the fermipy software</li> <li>Files ending on *_LLs.npy contain the log-likelihood values of our fits over a grid of ALP masses and photon-ALP couplings</li> <li>Files ending on *_Lambdas.npy contain the log-likelihood ratio test values of our fits over a grid of ALP masses and photon-ALP couplings</li> <li>Files ending on *_LL_thresh.npy contain the threshold values for the log-likelihood ratio test for which we can claim an exclusion at the 95% confidence level over a grid of ALP masses and photon-ALP couplings</li> <li>Files ending on*_contours.npy contain the upper limit contours.</li> </ul> <p>Files starting with "ALL" contain the likelihoods combined over all sources</p> <p>We also provide a minimal jupyter notebook, analysis_arrays.ipynb, that demonstrates how to read in the files.</p>
Research Mapping of Trauma Experiences in Autism Spectrum Disorders: A Bibliometric Analysis. Bibliometrix file
<p>This is the Bibliometrix file of the paper entitled: Research Mapping of Trauma Experiences in Autism Spectrum Disorders: A Bibliometric Analysis.</p>
Auto Continuous Positive Airway Pressure (CPAP) Based Energy Spectrum Analysis of Flow for Treatment of Obstructive Sleep Apnea Hypopnea Syndrome (OSAHS)
ClinicalTrials.gov study NCT00750165. IPD Sharing: Not stated. Countries: 1. Publications: 1.
data set related to article Brain Network Organization Correlates with Autistic Features in Preschoolers with Autism Spectrum Disorders and in Their Fathers - Preliminary Data from a DWI Analysis
<p>This record contains raw data related to article Brain Network Organization Correlates with Autistic Features in Preschoolers with Autism Spectrum Disorders and in Their Fathers - Preliminary Data from a DWI Analysis</p>
DATA for Nano Ranking Analysis: determining NPF event occurrence and intensity based on the concentration spectrum of formed (sub-5 nm) particles
<p>data used for: </p><p>Nano Ranking Analysis: determining NPF event occurrence and intensity based on the concentration spectrum of formed (sub-5 nm) particles</p><p>https://doi.org/10.5194/ar-2023-5</p>
Strength, depth, and geometry of magnetic sources in the crust of the Moon from localized power spectrum analysis
<p>This archive contains data files that can be used to reproduce Figures 7-10 in the article</p> <blockquote> <p>Wieczorek, M. A. (2018) Strength, depth, and geometry of magnetic sources in the crust of the Moon from localized power spectrum analysis, J. Geophys. Res. Planets.</p> </blockquote> <p>The data files contain the final inversion results for the model using magnetized sills, where the full magnetic field to spherical-harmonic degree 449 was employed. For each localized analysis, the best 6 orthogonal localization windows were used that maximized their power within a spherical cap with an angular radius of 8 degrees and with a spherical-harmonic bandwidth of 58. The analyses were performed at the vertices of a quasi equal-area grid with a spacing corresponding to five degrees of latitude. For these models, the file names start with "sills_449_8_58_5". Each file contains the latitude and longitude (in degrees) of the localization analysis, as well as one other value.</p> <p><br> FILE DESCRIPTIONS</p> <p>sills_449_8_58_5_minchi2r.dat</p> <p>This file contains the minimum reduced chi<sup>2</sup> value of the best-fitting model for each analysis. Uncertainties on the inversion parameters were obtained from Monte Carlo simulations that showed 68.2% and 95.4% of the analyses should have reduced chi<sup>2</sup> values less than 2.133 and 4.082, respectively. Where 1-sigma uncertainties could not be calculated (when the best-fitting misfits were above the 1-sigma limits) the limit was set to +/- 999.e99.</p> <p>sills_449_8_58_5_db.dat<br> sills_449_8_58_5_db_1m.dat<br> sills_449_8_58_5_db_1p.dat</p> <p>The best-fitting depths to the bottom of the magnetized region and their +/- 1-sigma limits (1p/1m).</p> <p>sills_449_8_58_5_dt.dat<br> sills_449_8_58_5_dt_1m.dat<br> sills_449_8_58_5_dt_1p.dat</p> <p>The best-fitting depths to the top of the magnetized region and their +/- 1-sigma limits.</p> <p>sills_449_8_58_5_rdisk.dat<br> sills_449_8_58_5_rdisk_1m.dat<br> sills_449_8_58_5_rdisk_1p.dat</p> <p>The best-fitting angular radii (in km) of the magnetized sills and their +/- 1-sigma limits.</p> <p>sills_449_8_58_5_rkm2v2.dat<br> sills_449_8_58_5_rkm2v2_1m.dat<br> sills_449_8_58_5_rkm2v2_1p.dat</p> <p>The best-fitting (N M^2 V^2)^(1/2) values in A m^2 of the magnetized sills and their +/- 1-sigma limits.<br> </p>
Large-scale metagenomic analysis of oral microbiomes reveals markers for autism spectrum disorders, MetaPhlAn 3 profiles
Open the record for dataset details and reuse information.
Figure 2 in Food spectrum analysis of the Asian toad, Duttaphrynus melanostictus (Schneider, 1799) (Anura: Bufonidae), from Timor Island, Wallacea
Figure 2. Ordination of non-metric multidimensional scaling analysis (NMDS) based on Bray-Curtis dissimilarities of the food item composition of toads from different habitats. I = park grounds of the Timor Lodge Hotel, Dili, Dili District; II = dry riverbed at the confluence of the Comoro and Bemos rivers, 8 km south of the Comoro River bridge, Dili District; III = banana plantation south of the confluence of the Comoro and Bemos rivers, Aileu District; IV = dry forest at the fringes of Lake Maubara, Liquiça District; V = Corypha forest west of Raeme, Liquiça District. Symbols close to each other in the ordination space are most similar. Their distribution well indicates that food composition does not differ between habitats.
Figure 1 in Food spectrum analysis of the Asian toad, Duttaphrynus melanostictus (Schneider, 1799) (Anura: Bufonidae), from Timor Island, Wallacea
Figure 1. Duttaphrynus melanostictus and habitats in Timor-Leste sampled during June 2013. Habitat types are listed in the same order as they appear in Table 1. (a) Unvouchered D. melanostictus specimen from the park grounds of the Timor Lodge Hotel, Dili, Dili District. (b) Park grounds of the Timor Lodge Hotel, Dili, Dili District (Habitat I). (c) Dry riverbed at the confluence of the Comoro and Bemos rivers, 8 km south of the Comoro River bridge, Dili District (Habitat II). (d) Banana plantation south of the confluence of the Comoro and Bemos rivers, Aileu District (Habitat III). (e) Dry forest at the fringes of Lake Maubara, Liquiça District (Habitat IV). (f) Corypha forest west of Raeme, Liquiça District (Habitat V). Photographs (a–c) by Sven Mecke, (d) by Max Kieckbusch and (e–f) by Mark O'Shea.
High-Resolution Sporadic E Layer Observation Based on Ionosonde using a Cross-Spectrum Analysis Imaging Technique
<p>The package includes the data used in Figures 1 to 6 in the paper “High-Resolution Sporadic E Layer Observation Based on Ionosonde using a Cross-Spectrum Analysis Imaging Technique".</p> <p>Since the raw data of the ionosonde is quite large and difficult to upload, the echo data of the Es layer after high-resolution imaging processing is packed together and uploaded here.</p> <p>All data can be imported and viewed directly by MATLAB with the function of "imagesc".</p> <p>Due to internal delay, the actual range should be obtained by subtracting 5 range bins.</p>
Trends of the Pre-hospital Emergency Care Spectrum in Beijing From 2005 to 2014: A Retrospective Analysis
ClinicalTrials.gov study NCT02645877. IPD Sharing: NO. Countries: 1. Publications: 1.
Establishment of Social Skills Training Group in Adolescents With Autism Spectrum Disorder and Effectiveness Analysis
ClinicalTrials.gov study NCT05341011. IPD Sharing: NO. Countries: 1. Publications: 7.
Using Ultrasound Spectrum Analysis (USA) to Guide Dose Escalated Prostate Brachytherapy
ClinicalTrials.gov study NCT01227642. IPD Sharing: Not stated. Countries: 1. Publications: 1.
A Kinematic Analysis of Motor Planning and Movement Execution of Children With Autism Spectrum Condition
ClinicalTrials.gov study NCT06144775. IPD Sharing: NO. Countries: 1. Publications: 7.
Placenta Accreta Spectrum Disorder Conservative Managment Versus Hysterectomy Prospective Analysis
ClinicalTrials.gov study NCT06105034. IPD Sharing: Not stated. Countries: 1. Publications: 17.
Supplementary material 1 from: Gonzalez Cruz J, Johnson M (2024) Towards a spectrum of dissent: A content analysis of Hawai'i's invasive species media. NeoBiota 92: 315-348. https://doi.org/10.3897/neobiota.92.115766
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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.