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638 results for “oscillations”
Tradeoffs and benefits explain scaling, sex differences, and seasonal oscillations in the remarkable weapons of snapping shrimp (Alpheus spp.)
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In vitro cell cycle oscillations exhibit a robust and hysteretic response to changes in cytoplasmic density
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Phase response analyses support a relaxation oscillator model of locomotor rhythm generation in Caenorhabditis elegans
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Data and code for figures: Ultralow-Noise Photonic Microwave Synthesis using a Soliton Microcomb-based Transfer Oscillator
<p>This repository contains the data and code for the paper "Ultralow-Noise Photonic Microwave Synthesis using a Soliton Microcomb-based Transfer Oscillator".</p>
Accompanying dataset for "Nappe oscillations on free-overfall structures, data from laboratory experiments (audio and video)"
<p>This dataset accompanies the manuscript "Nappe Oscillations on Free-Overfall Structures: Data from Laboratory Experiments" submitted to Scientific Data.</p> <p>This dataset contains raw audio and video data, which complement the dataset uploaded at: <a href="https://zenodo.org/record/3381078#.XlUGVSFKiUk">https://zenodo.org/record/3381078#.XlUGVSFKiUk</a></p> <p>The names of the folders describe each one of the 52 experiments, with respect to the submitted paper in Scientific Data:</p> <p>- M1 and M2 denote Model 1 and Model 2, respectively.</p> <p>- C and UC denote confined and unconfined nappe, respectively.</p> <p>- QR, THR, HR, R, and RR denote the crest type of the weir as explained in the paper.</p> <p>- W is the width of the crest and L is the falling height.</p>
Data from: Nonlinearities between inhibition and T-type calcium channel activity bidirectionally regulate thalamic oscillations
<p>Absence seizures result from 3-5 Hz generalized thalamocortical oscillations that depend on highly regulated inhibitory neurotransmission in the thalamus. Efficient reuptake of the inhibitory neurotransmitter GABA is essential, and reuptake failure worsens seizures. Here, we show that blocking GABA transporters (GATs) in acute brain slices containing key parts of the thalamocortical seizure network modulates epileptiform activity. As expected, we found that blocking either GAT1 or GAT3 prolonged oscillations. However, blocking both GATs unexpectedly suppressed oscillations. Integrating experimental observations into single-neuron and network-level computational models shows how a non-linear dependence of T-type calcium channel opening on GABA<sub>B</sub> receptor activity regulates network oscillations. Receptor activity that is either too brief or too protracted fails to sufficiently open T-type channels necessary for sustaining oscillations. Only within a narrow range does prolonging GABA<sub>B</sub> receptor activity promote channel opening and intensify oscillations. These results have implications for therapeutics that modulate GABA transporters.</p>
Data from: Climate oscillation and alien species invasion influences oceanic seabird distribution
Spatial and temporal distribution of seabird transiting and foraging at sea is an important consideration for marine conservation planning. Using at-sea observations of seabirds (n = 317), collected during the breeding season from 2012 to 2016, we built boosted regression tree (BRT) models to identify relationships between numerically dominant seabird species (red-footed booby, brown noddy, white tern and wedge-tailed shearwater), geomorphology, oceanographic variability, and climate oscillation in the Chagos Archipelago. We documented positive relationships between red-footed booby and wedge-tailed shearwater abundance with the strength in the Indian Ocean Dipole, as represented by the Dipole Mode Index (6.7% and 23.7% contribution respectively). The abundance of red-footed boobies, brown noddies and white terns declined abruptly with greater distance to island (17.6%, 34.1% and 41.1% contribution respectively). We further quantified the effects of proximity to rat-free and rat-invaded islands on seabird distribution at sea, and identify breaking point distribution thresholds. We identified areas of increased abundance at sea and habitat use-age under a scenario where rats are eradicated from invaded nearby islands and recolonised by seabirds. Following rat eradication, abundance at sea of red-footed booby, brown noddy, and white terns increased by 14%, 17% and 3% respectively, with no important increase detected for shearwaters. Our results have implication for seabird conservation and island restoration. Climate oscillations may cause shifts in seabird distribution, possibly through changes in regional productivity and prey distribution. Invasive species eradications and subsequent island recolonization can lead to greater access for seabirds to areas at-sea, due to increased foraging or transiting through, potentially leading to distribution gains and increased competition. Our approach predicting distribution after successful eradications enables anticipatory threat-mitigation in these areas, minimising competition between colonies and thereby maximising the risk of success and the conservation impact of eradication programmes.
Driven Wattwins, a 2-DOF isotropic horological oscillator
<p>Videos of a silicon prototype of Wattwins, a 2-DOF compliant mechanical oscillator, driven by a watch movement. The two first eigenfrequencies of the oscillator are tuned and matched in order to have elliptical trajectories at the end effector with a constant rotational frequency at 15.5Hz.</p>
A Laboratory Forced-Oscillation Apparatus
<p>In this file, we present supplementary materials for the paper titled </p> <p><em><strong>"A Laboratory Forced-Oscillation Apparatus for Measurements of Elastic and Anelastic Properties of Rocks at Seismic Frequencies" </strong></em></p> <p>by <strong>Vassily Mikhaltsevitch, Maxim Lebedev, Rafael Chavez, </strong><strong>Euripedes</strong> <strong>A. </strong><strong>Vargas Jr. and </strong><strong>Guilherme F. </strong><strong>Vasquez</strong></p>
Data associated with "Up and Down states during slow oscillations in slow wave sleep and different levels of anesthesia"
<p>Data collection uploaded is associated with the publication "Up and Down states during slow oscillations in slow wave sleep and different levels of anesthesia" by the same authors in Frontiers in Systems Neuroscience 2021 DOI: 10.3389/fnsys.2021.609645</p> <p>Raw recordings are in *.smr, readable with Spike 2 (Cambridge Electronics Design <a href="http://ced.co.uk/downloads/latestsoftware">CED Downloads | Latest software</a></p> <p> </p>
Dataset accompanying publication: "Modulation of Cortical Oscillations by Low-Frequency Direct Cortical Stimulation is State-Dependent"
<p>Dataset accompanying publication:</p> <p>"Modulation of Cortical Oscillations by Low-Frequency Direct Cortical Stimulation is State-Dependent", Alagapan, Schmidt, Lefebvre, Hadar, Shin and Frohlich</p> <p>For questions, contact flavio_frohlich@med.unc.edu</p> <p>The mat file consists of the following Matlab variables</p> <ol> <li><strong>Electrode Distance</strong>: 3 x 1 cell array containing the arrays (trial x electrode) of distance from stimulating electrode to recording electrode for the three ECoG participants. (First array corresponds to P001, Second array corresponds to P005 and Third array corresponds to P008)</li> <li><strong>Spectra_Electrode_EC</strong>: 3 x 1 cell array consisting of nTrial x nFreq x nChannels x nEpochs matrices for each subject’s eyes-closed experiment. nTrial corresponds to number of trials, nFreq corresponds to frequencies at which spectral power is calculated, nChannels corresponds to number of electrodes in the analysis and nEpochs corresponds to “Before Stimulation”, “During Stimulation” and “After Stimulation” epochs.</li> <li><strong>Spectra_Electrode_EO</strong>: 3 x 1 cell array consisting of nTrial x nFreq x nChannels x nEpochs matrices for each subject’s eyes-open experiment. The dimensions are the same as above. The first array consists of task-engaged dataset from Participant P001.</li> <li><strong>MI_Summary</strong>: 8 x 1 cell array consisting of 3 x 1 cell arrays of modulation indexes for the three participants. The 8 arrays stand for the modulation indexes in different epochs and different frequencies. Refer <strong>MI_Summary_Names</strong></li> <li><strong>MI_Summary_Names</strong>: 8 x 1 cell array consisting of strings denoting the arrays in <strong>MI_Summary</strong>. <strong>During</strong> in text corresponds to “During Stimulation” epoch and <strong>After</strong> corresponds to “After Stimulation” epoch.</li> <li><strong>f</strong>: Frequencies at which spectral power was estimated.</li> <li><strong>NetworkModel</strong>: Matlab struct containing the time series generated by the network model and corresponding spectra. The <strong>timeseries</strong> consists of 4 columns – 1<sup>st</sup> column corresponds to time, 2<sup>nd</sup> column corresponds to task-engaged state data, 3<sup>rd</sup> column corresponds to eyes-open state data and 4<sup>th</sup> column corresponds to eyes-closed state data. The <strong>spectra </strong>struct consists of spectral powers estimated in the different epochs. 1<sup>st</sup> column of each epoch array corresponds to task-engaged state, 2<sup>nd</sup> column corresponds to eyes-open state and the 3<sup>rd</sup> column corresponds to eyes-closed state.</li> <li><strong>SummationModel</strong>: Matlab struct containing the time series generated by the summation model and the peak values in spectra before and during stimulation by varying the two strength parameters. The columns correspond to stimulation strength while rows correspond to oscillation strength. The oscillation strength parameter was varied from 0.5 to 50 in steps of 0.5 and the stimulation strength parameter was varied from 0.1 to 10 in steps of 0.1. </li> </ol> <p> </p>
Statistical Test of Distance-Duality Relation with Type Ia Supernovae and Baryon Acoustic Oscillations (2nd version)
<p>This package contains data and processing tools for replicating the research presented in the paper "Statistical Test of Distance-Duality Relation with Type Ia Supernovae and Baryon Acoustic Oscillations" (2016, preprint, arXiv:1604.04631 https://arxiv.org/abs/1604.04631).</p> <p>An earlier version (https://zenodo.org/record/49825) has already been made available. In this updated version, we use the recently released consensus BOSS BAO measurement results (arXiv:1607.03155) as the source of angular-diameter distances. The choices of complementary cosmological parameters are expanded to include extensions to the Planck base-ΛCDM model parameters. In addition, various programming bugs are fixed.</p> <p>The compressed archive file "ddmc-nosample-v2.tar.bz2" contains only the compressed SNIa data, the BAO measurements, and the Planck chain files. The random samples can be re-created by the tools included in the package. This is the file suitable for low-speed download.</p> <p>The file "ddmc-v2.tar.bz2" contains the full set of random sample output files and analysis results in addition to those in the "ddmc-nosample-v2.tar.bz2" file.</p> <p>The file "CHECKSUM-sha1" contains the SHA1 hash values for verifying file integrity.</p> <p>Please read the README files in each package for more details and instructions.</p>
Statistical Test of Distance-Duality Relation with Type Ia Supernovae and Baryon Acoustic Oscillations (1st version)
<p>This package contains data and processing tools for replicating the research presented in the paper "Statistical Test of Distance-Duality Relation with Type Ia Supernovae and Baryon Acoustic Oscillations" (2016, preprint, arXiv:1604.04631 https://arxiv.org/abs/1604.04631).</p> <p>The compressed archive file "ddmc-nosample.tar.bz2" contains only the compressed SNIa data, the BAO data parameters, and the Planck chain files. The random samples can be re-created by the tools included in the package. This is the file suitable for low-speed download.</p> <p>The file "ddmc.tar.bz2" contains the full set of random sample output files and analysis results in addition to those in the "ddmc-nosample.tar.bz2" file.</p> <p>The file "CHECKSUM-sha1" contains the SHA1 hash values for verifying file integrity.</p> <p>Please read the README files in each package for more details and instructions.</p>
Electromagnetic Analysis of the HPM Oscillator-Reltron
<p>In this paper, electromagnetic analysis of the reltron, which is a compact, simple and efficient high power microwave (HPM) source has been presented. The beam wave interaction process of the reltron oscillator has been analyzed to understand the device physics. The split cavity oscillator and relativistic klystron principles have been extended to demonstrate the electric field responsible for beam bunching and the electron beam modulation process in the reltron. The analytical formulation to obtain the RF energy growth and efficiency of the device has also been presented. To validate the analytical results and to evaluate the overall performance of the device, beam present simulation of reltron has been performed using commercial 3D PIC simulation code "CST Particle Studio". With the parameters of a previously reported experimental reltron device, the present analytical calculation provided ~240 MW RF output power with ~38% efficiency while the PIC simulation provided RF output power of ~225 MW with ~36% efficiency at 2.75 GHz frequency. The obtained analytical and simulation results have also been found in agreement of ~6% with this experimental work.</p>
Oscillation test results for different Vdd values at positions X10Y90 and X44Y108
<p>16 files (X10Y90_X_XXV.bin and X44Y108_X_XXV.bin), where X_XX refers to the value of Vdd = oscillation counts generated by a TERO TRNG at placements X10Y90 and X44Y108 on a Xilinx Spartan 6 FPGA, with different voltage levels. Used in above mentioned paper in Figure 3.</p>
Data and code for figures in "A dissipative quantum reservoir for microwave light using a mechanical oscillator"
<p>Data and code used to produce the figures in "A dissipative quantum reservoir for microwave light using a mechanical oscillator".</p> <p>The code is tested with Python 2.7.10, Matplotlib 2.0.0b4, Scipy 0.18.0.</p>
Data for: Slab buckling as a driver for rapid oscillations in plate motion and subduction rate
<p>Data to make the figures in the manuscript: Slab buckling as a driver for rapid oscillations in plate motion and subduction rate by van der Wiel & Pokorny. The readme explains the .txt files.</p>
Co-occurring ripple oscillations facilitate neuronal interactions between cortical locations in humans
<h3>Contact:</h3><h3>Ilya Verzhbinsky</h3><h3>ilya@health.ucsd.edu</h3><p> </p><p>This is the processed data used to generate the results in the manuscript:</p><p>Co-occurring ripple oscillations facilitate neuronal interactions between cortical locations in humans. <i>PNAS</i> (2023).</p><p>To analyze this data, please first access the code at the following repository: <a href="https://github.com/iverzh/coripple-prediction"><strong>https://github.com/iverzh/coripple-prediction</strong></a></p><p>All downloaded zip files should be uncompressed and placed in a directory named <i>out/ </i>in the <i>CoRipplePredictionPNAS/</i> folder.</p><p> </p><p> </p><p> </p>
Experimental validation of simplicial complexes in multivariable coupled oscillators. Coupling: Lineal (Class III) vs NoLineal (Class III)
<p>The data sets correspond to the experimental implementation of synchronization phenomenon in <strong>simplicial complexes</strong>. In this particular case, the simplicial complex consists of 3-node network, where each node is an electronic Rössler-like oscillator whose parameters were fixed to operate in <strong>chaotic regime</strong>. In simplicial complexes, it is possible to model two types of interactions among nodes: <strong>pair-wise interactions (linear interactions)</strong> and <strong>high-order interactions (non-linear interactions)</strong>.</p> <p>The complete experiment consists of coupling simultaneously by means of linear and non-linear interactions the simplicial complex, the coupling occurs in state variables x (class III) and y (class II). The full data sets are organized in four Dataset, whose name explicitly indicates in which state variable occurs each coupling. In these case, Linearx-nonlinearx means that the linear coupling occurs in variable <em><strong>x</strong></em> (class III) whereas the non-linear coupling occurs in variable<em><strong> x</strong></em> (class III).</p> <p>Now, each folder contains 10000 files which come from varying the linear coupling and the nonlinear coupling 100 times each one. The file name is composed as follows: rootname XX YY, where XX corresponds to the variation number in linear coupling, whereas YY corresponds to the variation number in non-linear coupling.</p> <p>Internally in each file we can find 6 columns and 30,000 rows. Each pair of columns corresponds to the<strong><em> x</em></strong> and <strong><em>y</em></strong> variables of each oscillator and the rows correspond to time-varying samples.</p>
Experimental validation of simplicial complexes in multivariable coupled oscillators. Coupling: Lineal (Class III) vs NoLineal (Class II)
<p>The data sets correspond to the experimental implementation of synchronization phenomenon in<strong> simplicial complexe</strong>s. In this particular case, the simplicial complex consists of 3-node network, where each node is an electronic Rössler-like oscillator whose parameters were fixed to operate in <strong>chaotic regime</strong>. In simplicial complexes, it is possible to model two types of interactions among nodes: <strong>pair-wise interactions</strong> (linear interactions) and <strong>high-order interactions</strong> (non-linear interactions).</p> <p>The complete experiment consists of coupling simultaneously by means of linear and non-linear interactions the simplicial complex, the coupling occurs in state variables x (class III) and y (class II). The full data sets are organized in four Dataset (second), whose name explicitly indicates in which state variable occurs each coupling. In these case, Linearx-nonlineary means that the linear coupling occurs in variable <em><strong>x</strong></em> (class III) whereas the non-linear coupling occurs in variable <em><strong>y</strong></em> (class II).</p> <p>Now, each folder contains 10000 files which come from varying the linear coupling and the nonlinear coupling 100 times each one. The file name is composed as follows: rootname XX YY, where XX corresponds to the variation number in linear coupling, whereas YY corresponds to the variation number in non-linear coupling.</p> <p>Internally in each file we can find 6 columns and 30,000 rows. Each pair of columns corresponds to the <em><strong>x</strong></em> and <em><strong>y</strong></em> variables of each oscillator and the rows correspond to time-varying samples.</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.