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638 results for “Oscillation”
Data and Codes used in the study: Very high frequency oscillations in the main peak of a magnetar giant flare
<p>Description is given in the uploaded pdf document: Data_codes_description.pdf</p>
Data and code for "Multimode microwave circuit optomechanics as a platform to study coupled quantum harmonic oscillators"
<p>Components design files, code used to produce figures and measurement scripts for the results in "Multimode microwave circuit optomechanics as a platform to study coupled quantum harmonic oscillators".</p>
Code and data for "Coupling cell shape and velocity leads to oscillation and circling in keratocyte galvanotaxis"
<p>Code and data to reproduce "Coupling cell shape and velocity leads to oscillation and circling in keratocyte galvanotaxis" Biophys. J. doi: <a href="https://doi.org/10.1016/j.bpj.2022.11.021">https://doi.org/10.1016/j.bpj.2022.11.021</a></p>
Dataset for "Global Simulation of the Madden–Julian Oscillation With Stochastic Unified Convection Scheme"
<p>Datasets for "Global Simulation of the Madden–Julian Oscillation With Stochastic Unified Convection Scheme". The global simulation outputs (climatologies and daily anomalies), calculated RMM indexes, and the results of the budget analysis are included.</p>
Sunlight-powered self-excited oscillators for sustainable autonomous soft robotics
<p>As soft robotics fast advances, full autonomy becomes highly sought, especially if their motion can be powered by environmental energy and self-regulated. This would present a self-sustained fashion in terms of both energy supply and motion control. Currently, autonomous movement can be realized by leveraging out-of-equilibrium oscillatory motion of stimuli-responsive polymers under a constant light source. It would be more advantageous if environmental energy can be scavenged to power robots. However, generating oscillation becomes challenging under the limited power density of available environmental energy sources. Herein, we develop fully autonomous soft robots with self-sustainability based on self-oscillation. Aided by multiphysics modeling, we have successfully reduced the required input power density to around one-Sun level through a liquid crystal elastomer (LCE)-based bilayer structure. The autonomous motion of the low-intensity LCE/elastomer bilayer oscillator “LiLBot” under low energy supply was achieved by high photothermal conversion, low modulus, and high material responsiveness simultaneously. The LiLBot features tunable peak-to-peak amplitudes from 4 degrees to 72 degrees and frequencies from 0.3 Hertz to 11 Hertz. The oscillation approach offers a general strategy for desgining autonomous, untethered and sustainable small-scale soft robots, such as sailboat, walker, roller, and synchronized flapping wings.</p>
Phenotypic screening using waveform analysis of synchronized calcium oscillations in primary cortical cultures
<p><span>At present, <em>in</em> <em>vitro</em> phenotypic screening methods are widely used for drug discovery. In the field of epilepsy research, measurements of neuronal activities have been utilized for predicting efficacy of anti-epileptic drugs (AEDs). Fluorescence measurements of calcium oscillations in neurons are commonly used for measurement of neuronal activities, and some anti-epileptic drugs have been evaluated using this assay technique. However, changes in waveforms were not quantified in previous reports. Here, we have developed a high-throughput screening system containing a new analysis method for quantifying waveforms, and our method has successfully enabled simultaneous measurement of calcium oscillations in a 96-well plate. Features of waveforms were extracted automatically and allowed the characterization of some anti-epileptic drugs using principal component analysis. Moreover, we have shown that trajectories in accordance with the concentrations of compounds in principal component analysis plots were unique to the mechanism of anti-epileptic drugs. We believe that an approach that focuses on the features of calcium oscillations will lead to better understanding of the characteristics of existing anti-epileptic drugs and allow prediction of the mechanism of action (MoA) of novel drug candidates.</span></p>
Dark Matter-Induced Stellar Oscillations
<p>Reproduction package for the paper "Dark Matter-Induced Stellar Oscillations".</p>
Memory related processing is the primary driver of human hippocampal theta oscillations
<p>This dataset contains intra-cranial EEG (iEEG) recordings related to the paper: "Memory-related processing is the primary driver of human hippocampal theta oscillations" by Seger et al.</p> <p>The study investigates the role of hippocampal theta oscillations in the human brain during navigation (during which externally oriented sensorimotor processing occurs) and during mental simulation of navigation (when no externally oriented sensorimotor processing is present).</p> <p>The iEEG recordings underwent the initial preprocessing steps as described in the paper and were subsequently downsampled to 250Hz for the purpose of this dataset. The files in this dataset were saved as .MAT files. </p> <p>The dataset includes the following zip files:<br> “Seger_et_al_2023_iEEG_data.zip" </p> <p> </p> <p>Description of data structure:</p> <p>"electrode.info" contains information about subject and electrode contact<br> - electrode.info.subject_ID : participant ID<br> - electrode.info.elec_ID : channel ID <br> - electrode.info.anat_loc : anatomical localization (see paper for methods)<br> - electrode.info.hemi : hemisphere of electrode <br> - electrode.info.env_version : paradigm version </p> <p>"electrode.data" contains all trial level data for this electrode (** Please note that all trial level iEEG data contains a 2 second (500 sample) buffer flanking both ends.)</p> <p>"electrode.data.nav_and_sim_trials" contains all the trial level data for the navigation with mental simulation trials <br> -electrode.data.nav_and_sim_trials.trial_info : information about the navigated / mentally simulated routes (ex. Start and end store, catch trial condition)<br> -electrode.data.nav_and_sim_trials.nav_eeg : raw eeg for each navigation trial<br> -electrode.data.nav_and_sim_trials.nav_eeg_tVect : timeVector corresponding to raw eeg data in ms (t=0 is when the trial begins t(end) - 2000 ms is when trial ends). <br> -electrode.data.nav_and_sim_trials.nav_position : avatar XY position for all time points during navigation trials<br> -electrode.data.nav_and_sim_trials.sim_eeg : raw eeg for each mental simulation trial<br> -electrode.data.nav_and_sim_trials.sim_eeg_tVect : timeVector corresponding to raw eeg data in ms (t=0 is when the trial begins t(end) - 2000 ms is when trial ends). </p> <p>"electrode.data.nav_practice_trials" contains all the trial level data for the navigation practice trials<br> -electrode.data.nav_practice_trials.trial_info : information about the route navigated (ex. Start and end store)<br> -electrode.data.nav_practice_trials.nav_eeg : raw eeg for each practice navigation trial<br> -electrode.data.nav_practice_trials.nav_eeg_tVect : timeVector corresponding to raw eeg data in ms (t=0 is when the trial begins t(end) - 2000 ms is when trial ends). <br> -electrode.data.nav_practice_trials.nav_position : avatar XY position for all time points during practice navigation trials</p> <p><br> "electrode.data.storefront_pres_trials" contains all the trial level data for the storefront presentation trials<br> -electrode.data.storefront_pres_trials.eeg : raw eeg for each storefront presentation<br> -electrode.data.storefront_pres_trials.eeg_tVect : timeVector corresponding to raw eeg data in ms (t=0 is when the trial begins t(end) - 2000 ms is when trial ends). </p> <p>"electrode.data.crosshair_pres_trials" contains all the trial level data for the crosshair presentation trials<br> -electrode.data.crosshair_pres_trials.eeg : raw eeg for each crosshair presentation<br> -electrode.data.crosshair_pres_trials.eeg_tVect : timeVector corresponding to raw eeg data in ms (t=0 is when the trial begins t(end) - 2000 ms is when trial ends).</p>
Changes in BVOC emissions in response to the El Niño-Southern Oscillation | Data & scripts
<p>Data and Python scripts used for the study "Changes in BVOC emissions in response to the El Niño-Southern Oscillation" Vella et al. Preprint published on EGUSphere on 03 May 2023.</p>
Synchronization of spin-driven limit cycle oscillators optically levitated in vacuum
<p>Trajectories of optically levitated particles in vacuum. Trajectories are recorded using quadrant photodiode and ultra-fast CMOS camera. The readme file with more detailed description is added.</p>
The Potential Influence of Maritime Continent Deforestation on El Niño-Southern Oscillation: Insights from Idealized Modeling Experiments
<p>Codes for the Figures and Tables shown in the paper "The Potential Influence of Maritime Continent Deforestation on El Niño-Southern Oscillation: Insights from Idealized Modeling Experiments"</p> <p>Also, the restart and initial data are used to drive CESM1.</p>
A Random Optical Parametric Oscillator
<p>Synchronously pumped optical parametric oscillators (OPOs) provide ultra-fast light pulses at tuneable wavelengths. Their primary drawback is the need for precise cavity control (temperature and length), with flexibility issues such as fixed repetition rates and marginally tuneable pulse widths. Targeting a simpler and versatile OPO, we explore the inherent disorder of the refractive index in single-mode fibres realising the first random OPO -- the parametric analogous of random lasers. This novel approach uses modulation instability (<span class="math-tex">\(\chi^{(3)}\)</span> non-linearity) for parametric amplification and Rayleigh scattering for feedback. The pulsed system exhibits high inter-pulse coherence (coherence time of $\sim$0.4~ms), offering adjustable repetition rates (16.6 - 2000 kHz) and pulse widths (0.69 - 47.9 ns). Moreover, it operates continuously without temperature control loops, resulting in a robust and flexible device, which would find direct application in LiDAR technology. This work sets the stage for future random OPOs using different parametric amplification mechanisms.</p>
Data release: Atmospheric neutrino oscillation analysis with neutron tagging and an expanded fiducial volume in Super-Kamiokande I-V
<p><strong>Super-Kamiokande Atmospheric Neutrino Oscillation Analysis Data Release 2023</strong></p> <p>This data release accompanies the publication "Atmospheric neutrino oscillation analysis with neutron tagging and an expanded fiducial volume in Super-Kamiokande I-V." The information provided is divided into two sub-directories:</p> <ul> <li>bins: Contains data & MC counts in each analysis bin for different oscillation configurations</li> <li>chi2: Contains listings of chisquare values at each point in the oscillation parameter space scanned for the analyses described in the accompanying publication</li> </ul> <p><strong>Bin Information</strong></p> <p>This section describes the provided bin information. The `bin` subdirectory includes a ROOT file which contains binning information, data, and MC counts and MC summary statistics in each bin in the form of several ROOT trees. The contents of the ROOT file are also provided as text files within the same subdirectory.</p> <p>There are 930 bins used for atmospheric neutrino data in the analysis. Each ROOT tree and text file contains sequential listing of information for each of the 930 bins, i.e. the first entry or line of each tree and text file corresponds to the first bin, and so on.</p> <p><em>DISCLAIMER</em>: The data and MC counts and summary statistics provided are not expected to be sufficient to identically reproduce the publication fit results. The publication fit results rely on response functions of the bins to variations in the systematic uncertainty parameters which are not included in this release. Additionally, the MC oscillation probabilities used in the publication were computed individually for each MC event and are not possible to reproduce exactly using the binned event information provided with this release.</p> <p><strong>Bin Definitions</strong></p> <p>The ROOT file contains a `BinInfoTree` which lists the sample name associated with each bin, and the upper and lower bin edges of the 2D binning scheme used to bin atmospheric neutrino events. The sample names describe the selections used to place events in each bin, e.g. "subgev" and "multigev" for sub-GeV and multi-GeV events, respectively. Since data from the different SK phases are divided into different analysis samples, each sample name also lists the range of SK phases included in the same, e.g. sk1-5 for SK I, SK II, SK III, SK IV, and SK V, or sk4-5 for SK IV and SK V only. The contents of this tree are also listed in the `bin/sk_2023_BinInfo.txt` file.</p> <p><strong>Data Counts</strong></p> <p>Observed atmospheric neutrino data counts in each bin are listed in the `DataTree` within the ROOT file. The contents of this tree are also listed in the `bin/sk_2023_Data.txt` file.</p> <p><strong>MC Counts and Summary Statistics</strong></p> <p>MC counts and summary statistics of the true MC energies and directions are provided for each true neutrino type in the ROOT trees named `MC*Tree`. The information is provided for three oscillation configurations: The best-fit oscillation parameters in the normal ordering (NO), the best-fit oscillation parameters in the inverted ordering (IO), and without oscillations (NoOsc).</p> <p>The following summary statistics are provided for both the true neutrino energies and directions (cosine zenith angle) of MC events in each bin: Average, RMS, 2.3%, 15.9%, 50%, 84.1%, and 97.7% quantiles. The quantiles approximately correspond to -2, -1, 0, +1, and +2 sigma deviations from the median.</p> <p>The ROOT tree MC information is duplicated in the text files found under the `bin/[normal,inverted,unoscillated]` subdirectories, corresponding to the three oscillation scenarios.</p> <p><strong>Chisquare Information</strong></p> <p>This section describes the provided chisquare information. We provide listings of the relative chisquare values with respect to the global best-fit point in the normal ordering. The listings are provided as text files: The first columns correspond to the oscillation parameters at each grid point, while the final column lists the chisquare value. Chisquare values are provided for both the theta13-free and theta13-constrained analyses.</p> <p>ROOT files containing the 1D delta chisquare profiles for delta CP, and 2D delta chisquare profiles for allowed values of delta m^2 versus sin2 theta23 at 68% and 90% are also provided. There are two ROOT files corresponding to the contours from the theta13-free and theta13-constrained fits.</p> <p>A ROOT macro which draws the contours is also provided. It can be run using the following command from the chi2 directory:</p> <pre><code>> root draw_sk_contours.cc</code></pre> <p> </p>
Visual and acoustic measurements with an asymetrically oscillating, cavitating NACA0015 hydrofoil in a cavitation tunnel
<p>Supplementary material to a research article. The content is described in the 0_READ-ME_Overview.txt file.</p>
Airway Clearance Technique of Oscillation and Lung Expansion in Bronchiectasis
ClinicalTrials.gov study NCT06393257. IPD Sharing: NO. Countries: 1. Publications: 7.
Treatment of Residual Pockets in Periodontal Patients Using an Oscillating Chitosan Device
ClinicalTrials.gov study NCT06127069. IPD Sharing: NO. Countries: 1. Publications: 1.
VICOR Study-High Frequency Chest Wall Oscillations (HFCWO) in Patients With Acute Respiratory Failure and Hypersecretion
ClinicalTrials.gov study NCT05751707. IPD Sharing: NO. Countries: 1. Publications: 6.
TUS to Disrupt Pathological Oscillations
ClinicalTrials.gov study NCT06932185. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
Examining the Effect of Lateralization Imagery Training on EEG Brain Oscillations in Individuals With Chronic Neck Pain
ClinicalTrials.gov study NCT06679335. IPD Sharing: NO. Countries: 1. Publications: 36.
Investigation of Oscillations Underlying Human Cognitive and Affective Processing Using Intracranial EEG
ClinicalTrials.gov study NCT03268694. IPD Sharing: Not stated. Countries: 1. Publications: 12.
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.