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638 results for “Oscillation”
Data and code for figures in "Optical Backaction-Evading Measurement of a Nanomechanical Oscillator"
<p>Data and code for figures in "Optical Backaction-Evading Measurement of a Nanomechanical Oscillator"</p>
Dataset of predicted dynamic specific yield under periodic water table oscillations
<p>This dataset accompanies the submitted paper in the Water Resources Research: An approximate model for predicting the specific yield under periodic water table oscillations.</p> <p>The dataset includes 299 numerical experiments on predicting dynamic specific yield with different soil properties and different amplitudes of groundwater level oscillations. With this dataset, we proposed an approximate model for predicting the specific yield under diurnal and seasonal water level fluctuations.</p>
Adriatic-Ionian Bimodal Oscillating System - Coriolis Rotating Platform Experiment
<p>Numerical modelling has not yet offered satisfactory description of the functioning of the Adriatic/ Ionian and Levantine system.<br> So far, the explanation for the inversion of the near-surface circulation has been mainly sought in the wind stress curl.<br> Recent results have however suggested that the wind forcing cannot explain such inversions.<br> Scientific objective of this study is to show from physical modelling that the inversions of the NIG circulation<br> in an idealized Adriatic-Ionian/ Eastern Mediterranean circulation system can be generated<br> only bu changing the inflowing water density (from the Adriatic) with respect to the residing water in the Ionian basin.</p>
Fault reactivation during fluid pressure oscillations: transition from stable to unstable slip
<p>This is the ReadMe file corresponding to the study entitled: "Fault reactivation during fluid pressure oscillations: transition from stable to unstable slip"</p> <p>By Noël C., Passelègue X.F, Giorgetti C., Violay M.</p> <p>This study has been published in the Journal of Geophysical Research: Solid Earth under Copyright on October 2019. <br> doi:</p> <p>This Read-Me file has been last edited on October 2019</p> <p>This readme file describes the data repository and supplementary files accompanying the above publication. <br> For any further queries please contact corentin.noel@epfl.ch</p>
Data from : "The massive 2016 marine heatwave in the Southwest Pacific: an "El Niño - Madden-Julian Oscillation" compound event"
<p>File : PD-JRA-v1-c6_TMLtrend_1993-2022.nc</p> <p>Daily mixed layer temperature budget between 1993 and 2022 from a NEMO simulation.</p> <p>Data were extracted over the Southwest Pacific region [142.5°E-222.5°E;45°S;1°N].</p> <p>These data were used in Dutheil et al., (2024) The massive 2016 marine heatwave in the Southwest Pacific: an “El Niño - Madden-Julian Oscillation” compound event</p>
Pacific decadal oscillation influences tropical oxygen minimum zone extent and obscures anthropogenic changes
<p>Model outputs needed to reproduce the figures in the article : "Pacific decadal oscillation influences tropical oxygen minimum zone extent and obscures anthropogenic changes"</p>
The 2023 global warming spike was driven by El Niño/Southern Oscillation (Data)
<p>GFDL FLOR and CM2.1 surface temperature datasets used in:<br>Raghuraman et al., 2024, Atmospheric Chemistry and Physics,<br>"The 2023 global warming spike was driven by El Niño/Southern Oscillation"</p> <p>Point of Contact: Shiv Priyam Raghuraman, sraghur2@illinois.edu</p> <p>All other model data files used in paper can be downloaded from their respective websites (see paper's "Data availability" section).</p>
Data from: Data-driven analysis of oscillations in Hall thruster simulations & Data-driven sparse modeling of oscillations in plasma space propulsion
<p>Data from: Data-driven analysis of oscillations in Hall thruster simulations</p> <p> </p> <p>- Authors: Davide Maddaloni, Adrián Domínguez Vázquez, Filippo Terragni, Mario Merino</p> <p>- Contact email: <a href="mailto:dmaddalo@ing.uc3m.es">dmaddalo@ing.uc3m.es</a></p> <p>- Date: 2022-03-24</p> <p>- Keywords: higher order dynamic mode decomposition, hall effect thruster, breathing mode, ion transit time, data-driven analysis</p> <p>- Version: 1.0.4</p> <p>- Digital Object Identifier (DOI): <a href="https://doi.org/10.5281/zenodo.6359505">10.5281/zenodo.6359505</a></p> <p>- License: This dataset is made available under the <a href="http://opendatacommons.org/licenses/by/1.0/">Open Data Commons Attribution License</a></p> <p> </p> <p>Abstract</p> <p> </p> <p>This dataset contains the outputs of the HODMD algorithm and the original simulations used in the journal publication:</p> <p>Davide Maddaloni, Adrián Domínguez Vázquez, Filippo Terragni, Mario Merino, "Data-driven analysis of oscillations in Hall thruster simulations", 2022 <em>Plasma Sources Sci. Technol.</em> 31:045026. Doi: <a href="https://iopscience.iop.org/article/10.1088/1361-6595/ac6444">10.1088/1361-6595/ac6444</a>.</p> <p>Additionally, the raw simulation data is also employed in the following journal publication:</p> <p>Borja Bayón-Buján and Mario Merino, "Data-driven sparse modeling of oscillations in plasma space propulsion", 2024 <em>Mach. Learn.: Sci. Technol.</em> 5:035057. Doi:<a href="https://iopscience.iop.org/article/10.1088/2632-2153/ad6d29"> 10.1088/2632-2153/ad6d29</a></p> <p> </p> <p>Dataset description</p> <p> </p> <p>The simulations from which data stems have been produced using the full 2D hybrid PIC/fluid code <a href="https://ep2.uc3m.es/assets/docs/pubs/conference_proceedings/domi19b.pdf">HYPHEN</a>, while the HODMD results have been produced using an adaptation of the original <a href="https://doi.org/10.1137/15M1054924">HODMD algorithm</a> with an improved <a href="https://doi.org/10.1063/1.4863670">amplitude calculation routine</a>.</p> <p>Please refer to the relative article for further details regarding any of the parameters and/or configurations.</p> <p> </p> <p>Data files</p> <p> </p> <p>The data files are in standard Matlab .mat format. A recent version of <a href="https://www.mathworks.com/products/matlab.html">Matlab</a> is recommended.</p> <p>The HODMD outputs are collected within 18 different files, subdivided into three groups, each one referring to a different case. For the file names, "case1" refers to the nominal case, "case2" refers to the low voltage case and "case3" refers to the high mass flow rate case. Following, the variables are referred as:</p> <ul> <li>"n" for plasma density</li> <li>"Te" for electron temperature</li> <li>"phi" for plasma potential</li> <li>"ji" for ion current density (both single and double charged ones)</li> <li>"nn" for neutral density</li> <li>"Ez" for axial electric field</li> <li>"Si" for ionization production term</li> <li>"vi1" for single charged ions axial velocity</li> </ul> <p>In particular, axial electric field, ionization production term and single charged ions axial velocity are available only for the first case. Such files have a cell structure: the first row contains the frequencies (in Hz), the second row contains the normalized modes (alongside their complex conjugates), the third row collects the growth rates (in 1/s) while the amplitudes (dimensionalized) are collected within the last row. Additionally, the time vector is simply given as "t", common to all cases and all variables.</p> <p>The raw simulation data are collected within additional 15 variables, following the same nomenclature as above, with the addition of the suffix "_raw" to differentiate them from the HODMD outputs.</p> <p> </p> <p>Citation</p> <p> </p> <p>Works using this dataset or any part of it in any form shall cite it as follows.</p> <p>The preferred means of citation is to reference the publication associated to this dataset, as soon as it is available.</p> <p>Optionally, the dataset may be cited directly by referencing the DOI: 10.5281/zenodo.6359505.</p> <p> </p> <p>Acknowledgments</p> <p> </p> <p>This work has been supported by the Madrid Government (Comunidad de Madrid) under the Multiannual Agreement with UC3M in the line of ‘Fostering Young Doctors Research’ (MARETERRA-CM-UC3M), and in the context of the V PRICIT (Regional Programme of Research and Technological Innovation). F. Terragni was also supported by the Fondo Europeo de Desarrollo Regional, Ministerio de Ciencia, Innovación y Universidades - Agencia Estatal de Investigación, under grants MTM2017-84446-C2-2-R and PID2020-112796RB-C22.</p>
Data and codes for the article "Quantum collective motion of macroscopic mechanical oscillators"
Open the record for dataset details and reuse information.
CESM experiments for intraseasonal oscillation intensity changes in El Niño and La Niña developing summers
<p> Experiments are conducted using version 5.2 of Community Atmospheric Model (CAM-5.2; https://www.cesm.ucar.edu/models/cesm1.1/cam/). CAM is the atmosphere component of Community Earth System Model (CESM) developed by the National Center for Atmospheric Research (NCAR). The model resolution used in this study is f19_g16, with f19 finite volume grid (1.9º latitude by 2.5º longitude) for the atmosphere and land components combined with the gx1v6 displaced pole grid (approximately 1º) for the ocean and ice components.</p> <p> Four sets of numerical experiments are performed in this study:</p> <ol> <li>Full SST forcing simulation (full-SST run): The CAM is forced by global monthly OI SST and integrated from January 1982 to December 2020.</li> <li>Climatological SST forcing simulation (CLM-SST run): The CAM is integrated for 30 years forced by global climatological mean monthly SST obtained from OI SST data for the period of January 1982 to December 2020.</li> <li>Tropical central-eastern Pacific SST forcing simulation (CEP-SST run): The SST forcing field is composed of two parts: total monthly SST in the domain of 15°S-15°N and 160°E-80°W and climatological mean monthly SST in the other regions. The CAM is integrated from January 1982 to December 2020.</li> <li>Sensitivity experiments of tropical central-eastern Pacific SST anomalies during ENSO events: Composite SST anomalies in El Niño and La Niña events in the region of 15°S-15°N and 160°E-80°W and the above SST anomaly fields multiplied by -1 are added to climatological mean monthly SST from May to December. Climatological mean monthly SST is used in the other regions and months. The CAM is integrated for 30 years in these experiments. These experiments are referred to as EPEL, EPLA, EPEL-reverse and EPLA-reverse, respectively.</li> </ol>
Effect of the Quasi-Biennial Oscillation on the Madden Julian Oscillation teleconnections in the Southern Hemisphere
<p>Perturbation experiments described on the manuscript "Effect of the Quasi-Biennial Oscillation on the Madden Julian Oscillation teleconnections in the Southern Hemisphere" </p>
Data for: The El Nino-Southern Oscillation dramatically reduces the frequency of reproduction and reproductive rate of a tropical forest bird
<p>Although climate change has been implicated in population declines of tropical forest birds, there is a critical lack of data on the mechanisms underlying these declines. Attempts to link climatic factors to variation in adult survival, fecundity, or nest success have been largely inconclusive. Recent community-scale analyses have suggested that tropical birds may be less likely to breed under adverse conditions, but long-term data on individual reproduction are needed to test this hypothesis. Here we leverage 12 years of data on a lowland forest bird, the greater ani (<i>Crotophaga major</i>), to investigate how demographic parameters vary with phase of the El Niño – Southern Oscillation (ENSO), a major driver of climatic conditions in tropical wet forest. The likelihood of breeding and annual reproductive rate both decreased dramatically in El Niño-like years, with only 37.5% of adults attempting breeding in 2015 (a strong El Niño year). For birds that did breed, however, clutch size and daily nest predation rate were unaffected by climate. Of the local climate variables investigated, dry season length and the frequency of high temperatures were most closely associated with reproductive failure. These results indicate that El Niño conditions alter the demography of greater anis by reducing the likelihood of reproduction, a response that may be more widespread than currently recognized. We suggest that reduced reproduction under adverse conditions represents an important and understudied aspect of the life histories of tropical forest birds.</p>
Harbour protection with dual chamber oscillating water column devices (HARBOUR OWC) - 1/25 scale model tank test
Among various devices of wave energy converters (WEC), oscillating water column (OWC) devices are one of the concepts successfully deployed around the world. Hence, the necessity to design and develop the recent concept of dual-chamber OWC device attached to an existing coastal breakwater emerged. Former investigation in a wave flume already characterized the hydrodynamic performance of the device for a 1:25 scale model with frontal wave excitations. From this study, the effect of the incident wave direction is highlighted and the effect of the air compressibility on the device performances can be determined. The enclosed dataset refers to the experimental work developed at LNEC within the project Harbour OWC (PTDC/EME-REN/30866/2017) and considers the 3D effect of the incoming waves with a 14º angle of incidence. Data of free surface elevation along the tank and inside the device along with total pressure are presented.
Forced Oscillations On The Orocopia Schist Under Saturated Conditions (Effective Stress 9 MPa) (2)
<p>Forced Oscillations on Orocopia Schist under Saturated Conditions (Effective Stress 9 MPa)</p> <p>Test #199<br> Type of Experiment: Forced Oscillations</p> <p>Sample: Orocopia Schist (#4)</p> <p>Experimental Conditions: </p> <ul> <li>Confining pressure: 10 MPa</li> <li>Pore Pressure: 1 MPa</li> <li>Seating Differential Stress: 10 MPa</li> <li>Amplitude of oscillating Stress: 1 MPa (Peak-to-peak)</li> <li>LVDTs: 2 high-resolution axial LVDTs but 4 radial LVDTs (no high-resolution)</li> </ul> <p>More details are in the Excel file, including the initial processing of the data before calibration and a list of experiments.</p>
Forced Oscillations On The Orocopia Schist Under Saturated Conditions (Effective Stress 2 MPa) (1)
<p>Forced Oscillations on Orocopia Schist under Saturated Conditions (Effective Stress 2 MPa)</p> <p>Test #191<br> Type of Experiment: Forced Oscillations</p> <p>Sample: Orocopia Schist (#4)</p> <p>Experimental Conditions: </p> <ul> <li>Confining pressure: 10 MPa</li> <li>Pore Pressure: 8 MPa</li> <li>Seating Differential Stress: 10 MPa</li> <li>Amplitude of oscillating Stress: 1 MPa (Peak-to-peak)</li> <li>LVDTs: 2 high-resolution axial LVDTs but 4 radial LVDTs (including 1 high-resolution)</li> </ul> <p>More details are in the Excel file, including the initial processing of the data before calibration and a list of experiments.</p>
Forced Oscillations On The Orocopia Schist Under Saturated Conditions (Effective Stress 9 MPa) (1)
<p>Forced Oscillations on Orocopia Schist under Saturated Conditions (Effective Stress 9 MPa)</p> <p>Test #190<br> Type of Experiment: Forced Oscillations</p> <p>Sample: Orocopia Schist (#4)</p> <p>Experimental Conditions: </p> <ul> <li>Confining pressure: 10 MPa</li> <li>Pore Pressure: 1 MPa </li> <li>Seating Differential Stress: 10 MPa</li> <li>Amplitude of oscillating Stress: 1 MPa (Peak-to-peak)</li> <li>LVDTs: 2 high-resolution axial LVDTs but 4 radial LVDTs (including 1 high-resolution)</li> </ul> <p>More details are in the Excel file, including the initial processing of the data before calibration and a list of experiments.</p>
Forced Oscillations On PMMA (1)
<p>Test #184<br> Type of Experiment: Forced Oscillations</p> <p>Sample: PMMA (#1)</p> <p>Experimental Conditions: </p> <ul> <li>Confining pressure: 3 MPa</li> <li>Pore Pressure: 0 MPa</li> <li>Seating Differential Stress: 2.5 MPa</li> <li>Amplitude of oscillating Stress: 0.8 MPa (Peak-to-peak)</li> <li>LVDTs: 2 high-resolution axial LVDTs and no radial LVDTs</li> </ul> <p>More details are in the Excel file, including the initial processing of the data before calibration and a list of experiments.</p>
Forced Oscillations On PMMA (2)
<p>Test #197<br> Type of Experiment: Forced Oscillations</p> <p>Sample: PMMA (#1)</p> <p>Experimental Conditions: </p> <ul> <li>Confining pressure: 10 MPa</li> <li>Pore Pressure: 0 MPa</li> <li>Seating Differential Stress: 5 MPa</li> <li>Amplitude of oscillating Stress: 1.0 MPa (Peak-to-peak)</li> <li>LVDTs: 2 high-resolution axial LVDTs and 4 radial LVDTs (no high resolution)</li> </ul> <p>More details are in the Excel file, including the initial processing of the data before calibration and a list of experiments.</p>
Forced Oscillations On Aluminum (1)
<p>Test #188<br> Type of Experiment: Forced Oscillations</p> <p>Sample: Aluminum (#1)</p> <p>Experimental Conditions: </p> <ul> <li>Confining pressure: 10 MPa</li> <li>Pore Pressure: 0 MPa</li> <li>Seating Differential Stress: 10 MPa</li> <li>Amplitude of oscillating Stress: 1.0 MPa (Peak-to-peak)</li> <li>LVDTs: 2 high-resolution axial LVDTs and 4 radial LVDTs (1 high resolution)</li> </ul> <p>More details are in the Excel file, including the initial processing of the data before calibration and a list of experiments.</p>
Potential Impact of Winter–Spring North Atlantic Tripole SSTAs on the Following Autumn–Winter El Niño–Southern Oscillation: Bridging Role of the Tibetan Plateau
<p>This is the key model data of "Potential Impact of Winter–Spring North Atlantic Tripole SSTAs on the Following Autumn–Winter El Niño–Southern Oscillation: Bridging Role of the Tibetan Plateau". The data includes the last 25 years data of the CTRL experiment, and 25 years data of the CTRL_NTP experiment, the NA_ST experiment, and the NA_ST_NTP experiment, respectively. "2D" is two-dimensional variables , "3D" is three-dimensional variables, and "pottmp" is ocean potential temperature.</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.