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1,987 results for “mode”
A Pan-European, Quantile Machine learning (QML) based, Total, Fine-Mode and Coarse-Mode Aerosol Optical Depth dataset (QML AOD))
<p>The V 1.1.0 product is an improved Aerosol Optical Depth (AOD) product based on Gap-filled MAIAC AOD, which provide first full-coverage, high-resolution monitoring of fine-mode and coarse-mode aerosols in Europe from 2003-20. This dataset has successfully rectified the previously identified issue of weak associations between satellite AOD and PM2.5 in Europe, which was primarily attributable to current limitations of AOD data. Our innovative approach has yielded stronger correlations with PM10, PM2.5, and PMcoarse than previous AOD product, laying a critical groundwork for improving PM10, PM2.5, and PMcoarse predictions in further epidemiological studies or environmental monitoring.</p> <p>We have uploaded three QML AOD datasets in Geotiff format, covering the region from -27° to 72° latitude and from -25° to 45° longitude. These datasets will be useful for researchers and policymakers to better understand the impacts of aerosols on the environment and human health.</p> <p> Note: v1.0.0 product do not include MAIAC AOD in their models.</p> <p>Please read more details in our paper </p> <h1><span>Estimation of pan-European, daily total, fine-mode and coarse-mode Aerosol Optical Depth at 0.1° resolution to facilitate air quality assessments</span></h1> <p><a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.scitotenv.2024.170593" target="_blank" rel="noreferrer noopener"><span>https://doi.org/10.1016/j.scitotenv.2024.170593</span></a></p>
Comparing Perturbation Modes for Evaluating Instabilities in Neuroimaging: Processed NKI-RS Subset (08/2019)
<p>The processed subset of the NKI-RS dataset for evaluation of various perturbation modes when studying instabilities. Linked to the <a href="https://arxiv.org/abs/1908.10922">pre-print found here</a>, can be visualized using the <a href="https://github.com/gkiar/stability-mca/blob/master/code/dipy_exploratory/mca_dipy_exploratory_analysis.ipynb">plotting code here</a>, and generated with various <a href="https://github.com/gkiar/stability/tree/master/code/experiments/paper0_comparing_perturbation_modes">scripts and launch configurations found here</a>.</p>
Higher-Mode Contact Resonance Operation of a High-Aspect- Ratio Piezoresistive Cantilever Microprobe (Data)
<p>Raw data, Ansys Workbench Projects and figures used for the article "Higher-Mode Contact Resonance Operation of a High-Aspect- Ratio Piezoresistive Cantilever Microprobe", published in the proceedings of SMSI 2020, which did not take place because of Covid-19 virus pandemic.</p> <p>The data can be opened by a text editor<br> Ansys projects are compressed using 7-Zip and can be opened by Ansys Workbench.</p>
New insights into the generalized Rutherford equation for nonlinear neoclassical tearing mode growth from 2D reduced MHD simulations
<p>Two dimensional reduced MHD simulations of neoclassical tearing mode growth and suppression by ECCD are performed. The perturbation of the bootstrap current density and the EC drive current density perturbation are assumed to be functions of the perturbed flux surfaces. In the case of ECCD, this implies that the applied power is flux surface averaged to obtain the EC driven current density distribution. The results are consistent with predictions from the generalized Rutherford equation using common expressions for $\Delta^\prime_{\rm bs}$ and $\Delta^\prime_{\rm ECCD}$. These expressions are commonly perceived to describe only the effect on the tearing mode growth of the helical component of the respective current perturbation acting through the modification of Ohm's law. Our results show that they describe in addition the effect of the poloidally averaged current density perturbation which acts through modification of the tearing mode stability index. Except for modulated ECCD, the largest contribution to the mode growth comes from this poloidally averaged current density perturbation.</p>
Datasets for: AERO-MAP: A data compilation and modelling approach to understand the fine and coarse mode aerosol composition
<p>This repository contains the data compilation, gridded datasets, model output, model source code changes and model inputs for the paper: “AERO-MAP: A data compilation and modelling approach to understand the fine and coarse mode aerosol composition “.</p> <p>The only change from the December 20, 2024 version is that a new variable "Distinct" is added which indicates whether the dataset is also included in the GHOST dataset by Bowdalo et al., 2024: https://essd.copernicus.org/articles/16/4417/2024/essd-16-4417-2024.pdf. All PM2.5 and PM10 datasets from GHOST are included in this dataset, but GHOST will be regularly updated.</p> <p> </p> <p>There are two subdirectories as tar files:</p> <p>collectoutputfiles.zip: which contains the detailed data descriptions in a csv files, gridded data in netcdf and model output in netcdf format. More details in the README file in that zipped directory.</p> <p>modelfiles.zip: which contains the Source code changes and input files needed to reproduce the simulations in the paper. More details in the README file in that zipped directory.</p>
Multiple Evolution Modes of Megaripples in the Qaidam Basin and Implications for Ripple-Like Aeolian Landforms on Mars
<p>The dataset includes wind regime data for Golmud, Sebei, and the west bank of the Narin Gol River in the Qaidam Basin, as well as sediment grain size and morphological parameters of the megaripples. In addition, we provide R language source code for data processing and visualization.</p><p>The primary directory contains the data and the source code in the R language. The data includes sediment grain size, morphological parameters and wind regime analysis data of megaripples. Modifying the working path and installation package is necessary to call the R source code for data loading.</p>
Thermally mediated transmission-mode deflection of terahertz waves by lamellar metagratings containing a phase-change material
<p>The data generated by MATLAB, whcih were used to plot a part of the figures. </p> <p>Research supported by Narodowe Centrum Nauki, project no UMO-2020/39/I/ST3/02413.</p>
Non-linear three-mode coupling of gravity modes in rotating slowly pulsating B stars: Stationary solutions and modeling potential
<p>This repository contains the material available online that accompanies <a href="https://arxiv.org/abs/2311.02972" target="_blank" rel="noopener">Van Beeck et al. (2024)</a> (ArXiv link). </p> <p>It contains zipped archives that contain inlists and final data products for the MESA stellar evolution code\(^1\) (version 15140), the GYRE stellar pulsation/oscillation code\(^2\) (version 6.0.1) and the AESolver stellar oscillation mode coupling code\(^3\).</p> <p>In the technical information section below you may find a description of the contents of this repository. The abstract of <a href="https://arxiv.org/abs/2311.02972" target="_blank" rel="noopener">Van Beeck et al. (2024)</a> is also available below.</p> <p> </p> <p><em>Footnotes :</em></p> <p><em>\(^1\): see <a href="https://docs.mesastar.org/en/r15140/" target="_blank" rel="noopener">https://docs.mesastar.org/en/r15140/</a> for additional details about the MESA stellar evolution code.</em></p> <p><em>\(^2\): see <a href="https://gyre.readthedocs.io/en/v6.0.1/">https://gyre.readthedocs.io/en/v6.0.1/</a> for additional details about the GYRE stellar pulsation/oscillation code.</em></p> <p><em>\(^3\): the AESolver code can be downloaded from its Github repository: <a href="https://github.com/JVB11/AESolver" target="_blank" rel="noopener">https://github.com/JVB11/AESolver</a>; its documentation may be consulted at <a href="https://jvb11.github.io/AESolver/" target="_blank" rel="noopener">https://jvb11.github.io/AESolver/</a>.</em></p>
Dataset for "Effect of the atomic structure of complexions on the active disconnection mode during shear-coupled grain boundary motion"
<p>This repository contains the data of the simulations and theoretical<br>calculations of the paper "Effect of the atomic structure of complexions on the active disconnection mode during shear-coupled grain boundary motion".</p>
Diagrammatic representation of ZCM, TAT, and PIM modes
<p>This representation is a vector adaptation of Figure 1 present in the Fekedulegn et al. article. If you use it, don't forget to cite the authors below (you don't need to cite me).</p> <p>Fekedulegn, D., Andrew, M. E., Shi, M., Violanti, J. M., Knox, S., & Innes, K. E. (2020). Actigraphy-based assessment of sleep parameters. <em>Annals of Work Exposures and Health</em>, <em>64</em>(4), 350-367. <a href="https://doi.org/10.1093/annweh/wxaa007/">https://doi.org/10.1093/annweh/wxaa007/</a>.</p>
Experimental data and scripts used for the paper "Experiments and low-order modelling of intermittent transitions between clockwise and anticlockwise spinning thermoacoustic modes in annular combustors"
<p>The folder contains the experimental data, the scripts an the instructions to generate the figures of the paper.</p> <p>Because of difficulties for uploading large files on zenodo, the heaviest files, which are the acoustic measurement files (.TDMS format), are not included in the zip file, but are put aside of it.</p> <p>For the scripts to work correctly, all the tdms files should be moved in the folder Faure-BeaulieuA_StochasticTransitionsAzimuthalMode_PROCI_20200713/01_input_data/</p>
Normal mode splitting function predictions for mantle anisotropy
<p>Predictions for normal mode splitting functions for 6 models of mantle anisotropy, accompanying the paper published in Geophysical Journal International by Restelli, Koelemeijer & Ferreira (2023). This is version 2 related to the revised manuscript. </p> <p>More details can be found in the README. </p>
Statistical analysis for: Mode I fracture of beech-adhesive bondline at three different temperatures
<p>This dataset collects a raw dataset and a processed dataset derived from the raw dataset. There is a document containing the analytical code for statistical analysis of the processed dataset in .Rmd format and .html format. <br> <br> The study examined some aspects of mechanical performance of solid wood composites. We were interested in certain properties of solid wood composites made using different adhesives with different grain orientations at the bondline, then treated at different temperatures prior to testing. </p> <p>Performance was tested by assessing fracture energy and critical fracture energy, lap shear strength, and compression strength of the composites. This document concerns only the fracture properties, which are the focus of the related paper. </p> <p>Notes: </p> <p>* the raw data is provided in this upload, but the processing is not addressed here. <br> * the authors of this document are a subset of the authors of the related paper.<br> * this document and the related data files were uploaded at the time of submission for review. An update providing the doi of the related paper will be provided when it is available.</p>
Series data for the 22PN nonlinear memory effect in the l=2, m=0 mode.
<p>Dataset associated with the preprint arXiv:2407.19017, “Waveform models for the gravitational-wave memory effect: Extreme mass-ratio limit and final memory offset” by Arwa Elhashash and David A. Nichols. It contains the 22 post-Newtonian-order series data for the l=2, m=0 spin-weighted spherical harmonic mode of the gravitational-wave memory signal from an extreme-mass ratio inspiral with nonspinning black holes.</p>
[Dataset] Simultaneous laser ultrasonic measurement of sound velocities and thickness of plates using combined mode local acoustic spectroscopy
<p>Research data for the purpose of reproducing the results presented in the journal publication titled "Simultaneous laser ultrasonic measurement of sound velocities and thickness of plates using combined mode local acoustic spectroscopy"</p>
Dataset of B-mode fatty liver ultrasound images
<p>The dataset used and described in: M. Byra, G. Styczynski, C. Szmigielski, P. Kalinowski. Ł. Michałowski4. R. Paluszkiewicz. B. Ziarkiewicz-Wróblewska, K. Zieniewicz. P. Sobieraj, A. Nowicki. Transfer learning with deep convolutional neural network for liver steatosis assessment in ultrasound images. International Journal of Computer Assisted Radiology and Surgery, 2018. DOI: 10.1007/s11548-018-1843-2. </p> <p>Please refer to the above work if you use the dataset in your research. </p> <p>Contact:<br> Michal Byra<br> Department of Ultrasound<br> Institute of Fundamental Technological Research<br> Polish Academy of Sciences, Warsaw, Poland<br> mbyra@ippt.pan.pl<br> byra.michal@gmail.com</p>
Exploring mechanisms that affect coral cooperation: symbiont transmission mode, cell density and community composition
<p>This repository contains code to accompany the manuscript titled</p> <p><strong>Exploring mechanisms that affect coral cooperation: symbiont transmission mode, cell density and community composition</strong></p> <p>by <strong>Carly D. Kenkel and Line K. Bay</strong><br> </p> <p>In this study, we used a phylogenetically controlled design to investigate the role of vertical symbiont transmission, an evolutionary mechanism predicted to enhance cooperation and holobiont fitness of reef-building corals. Six species of coral, three vertical transmitters and their closest horizontally transmitting relatives, were fragmented and subjected to a two-week thermal stress experiment. Symbiont cell density, photosynthetic function and translocation of photosynthetically fixed carbon between symbionts and hosts were quantified to assess changes in physiological metrics of fitness and cooperation. Amplicon sequencing of the <em>Symbiodinium</em> ITS-2 locus was used to investigate differences in symbiont community composition among focal species. We did not observe universally higher levels of cooperation in vertically transmitting species. However, the reduction in cooperation at the onset of bleaching was marginally associated with symbiont community diversity. Analysis of ITS2 amplicon sequence data suggest that it may not be vertical transmission <em>per se</em> that influences host-symbiont cooperation, but genetic uniformity of the symbiont community.</p> <p>Repository contents:</p> <ul> <li> <p><strong>TraitDataAnalysis.R:</strong> Annotated R script for generating figures and re-creating statistical analyses</p> <ul> <li> <p><strong>RsquaredGLMM.R:</strong> Accessory R script for running RsquaredGLMM analyses, called by <strong>TraitDataAnalysis.R</strong></p> </li> <li> <p><strong>NSF_RunningPam.csv</strong>: Input file for statistical analysis. Contains photophysiological data. Column headers are as follows:</p> <ul> <li> <p>Tank: Number of experimental tank in which experimental coral fragment was held</p> </li> <li> <p>Treatment: short-hand notation for sample treatments (e.g. ctrl1-5 = control temperature, genotypes 1-5)</p> </li> <li> <p>Water: source sump for temperature controlled water jackets for each set of treatment tanks</p> </li> <li> <p>Position: numerical rack position of coral fragment within experimental treatment tank</p> </li> <li> <p>Species: Coral species (Amil=<em>A. millepora</em>, Maqe=<em>M. aequituberculata</em>, Gast=<em>G. astreata</em>, Gach=<em>G. acrhelia</em>, Plob=<em>P. lobata</em>, Gcol=<em>G. columna</em>)</p> </li> <li> <p>Genotype: source colony origin of individual coral fragments within species</p> </li> <li> <p>Temp: experimental temperature treatment (ctrl: 27°C ; heat: 31°C)</p> </li> <li> <p>Treat: whether experimental corals received C14-labeled bicarbonate (bicarb), artemia or were sampled separately for Gene Expression Analysis (not presented in this manuscript)</p> </li> <li> <p>EQY: Effective quantum yield of <em>Symbiodinium</em> photosystem II as measured using PAM fluorometry</p> </li> <li> <p>Date: Actual calendar date of measure</p> </li> <li> <p>Transmission: coral symbiont transmission mode</p> </li> <li> <p>Reef: reef site of original coral collection</p> </li> <li> <p>Date: experimental date of measure</p> </li> </ul> </li> <li> <p><strong>TraitData.csv:</strong> Input file for statistical analysis. Contains all physiological trait data.</p> <ul> <li> <p>Includes columns as described above for the Running_Pam file in addition to columns containing raw trait data as described in the manuscript.</p> </li> </ul> </li> <li> <p><strong>TraitData_DaysAsCols.csv:</strong> Reformatted input file with trait data split by sampling day across columns</p> </li> </ul> </li> <li> <p><strong>DADA2Analysis.R:</strong> Annotated R script for generating figures and running ITS2 amplicon analyses</p> <ul> <li> <p>GeoSymbio_ITS2_LocalDatabase_verForPhyloseq.fasta: FASTA file of the GeoSymbio ITS2 reference database <a href="https://sites.google.com/site/geosymbio/">https://sites.google.com/site/geosymbio/</a>, formatted for use with the R prograom Phyloseq</p> </li> <li> <p>SeqVars_6Feb.fasta: FASTA file of identified sequence variants resulting from DADA2 analysis</p> </li> <li> <p>OutputDADA_6Feb.csv: Counts of sequence variants by sample</p> </li> <li> <p>Raw FASTQ paired end read files can be downloaded from NCBI's SRA: PRJNA338365</p> </li> </ul> </li> </ul>
Data for: Strong bottom currents in large, deep Lake Geneva generated by higher vertical-mode Poincaré waves
<p>Combining entire summer season current and temperature observations and 3D numerical modeling, we demonstrate that previously undetected vertical mode-two and vertical mode-three Poincaré waves in 309-meter deep Lake Geneva (Switzerland/France) generate strong bottom-boundary layer currents at 300-m depth. The data include measurements from moored Acoustic Doppler Current Profilers (ADCPs), vertical thermistor lines, and the corresponding 3D modeling results. The three-dimensional model used in this study is based on the MIT General Circulation Model (MITgcm, <a href="http://mitgcm.org/">http://mitgcm.org/</a>, <a href="https://doi.org/10.1029/96JC02775">https://doi.org/10.1029/96JC02775</a>). The main MITgcm model configuration files are available online at <a href="https://doi.org/10.5281/zenodo.13144189">https://doi.org/10.5281/zenodo.13144189</a>.</p> <p>The related scientific publication can be found at <a href="https://doi.org/10.1038/s43247-024-01653-8">https://doi.org/10.1038/s43247-024-01653-8</a></p>
Data supporting publication: Revealing Mode Formation in Quasi-Bound States in the Continuum Metasurfaces via Near-Field Optical Microscopy
<p>This repository includes the data corresponding to the figures shown in the journal article entitledRevealing Mode Formation in Quasi-Bound States in the Continuum Metasurfaces via Near-Field Optical Microscopy, published in Advanced Materials on 02.08.2024</p>
Astrophysical constraints on neutron star f -modes with a nonparametric equation of state representation
<p>Data release for Mohanty et al. "<em>Astrophysical constraints on neutron star f-modes with a nonparametric equation of state representation"</em></p> <p>The data release consists of three files: </p> <ol> <li><a href="https://zenodo.org/api/records/13952437/draft/files/EoS_posterior_samples_PSR.h5/content" target="_blank" rel="noopener noreferrer">EoS_posterior_samples_PSR.h5</a> </li> <li><a href="https://zenodo.org/api/records/13952437/draft/files/EoS_posterior_samples_PSR+GW.h5/content" target="_blank" rel="noopener noreferrer">EoS_posterior_samples_PSR+GW.h5</a> </li> <li><a href="https://zenodo.org/api/records/13952437/draft/files/EoS_posterior_samples_PSR+GW+NICER.h5/content" target="_blank" rel="noopener noreferrer">EoS_posterior_samples_PSR+GW+NICER.h5</a> </li> </ol> <p>Each file contains 9,835 samples of EOS draws. The equation of state id's matches those of Legred et. al. 2022</p> <p>The data structure follows Legred, I. (2022) “<em>Impact of the PSR J0740+6620 radius constraint on the properties of high-density matter: Neutron star equation of state posterior samples</em>”. Zenodo. doi: 10.5281/zenodo.6502467.</p> <p>Samples were generated using stanspy, a general relativistic neutron star code written by Sailesh Ranjan Mohanty. </p> <p>Please see the readme (adapted from Legred et. al. 2022 Zenodo. doi: 10.5281/zenodo.6502467) </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.