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307 results for “nonlinearity”
Experimental Verification of Nonlinear Effects in Peak Limiting Current Mode Controlled Boost Converter
<p>Compressed file contains results of experimental verification of nonlinear effects in peak limiting current mode controlled boost converter. Circuit diagrams are given in files <strong>power.pdf</strong> and <strong>control.pdf</strong> in the root directory. Directories</p> <p><strong>M-2019-05-02-8kHz-12V</strong></p> <p><strong>M-2019-05-02-8kHz-17V</strong></p> <p><strong>M-2019-05-02-8kHz-24V</strong></p> <p><strong>M-2019-05-02-8kHz-29V</strong></p> <p>contain the experimental results for Vout=12V, Vout=17V, Vout=24V, and Vout=29V. Each directory contains .npy files with numerical data, figures recorded by the oscilloscope, figure that depicts measured output current of the converter as it depends on the assigned control voltage, and programs that controlled the measurements. Out of 15009 files in each directory 15003 files are oscilloscope recordings, <strong>Iout.npy</strong> contains measured output current data, <strong>Vg.npy</strong> contains assigned control voltage data, <strong>figure.py</strong> is a Python 2 program used to plot Iout(Vg), which is stored in <strong>figure-xy.pdf</strong> (xy stands for the actual output voltage), while <strong>oscusb.py</strong> and <strong>overjm.py</strong> are programs used to control the experiment. Experiments are controlled by a computer running under GNU/Linux operating system.</p>
Analysis of Nonlinear Effects in Peak Limiting Current Mode Controlled Converters
<p>This compressed file contains simulation programs, simulation results, figures that depict the results, as well as the animations that illustrate nonlinear effects in peak limiting current mode controlled converters. The simulations are performed using Python 2 programming language using pylab environment (numpy, scipy, matplotlib, ipython) under Ubuntu 18.04 operating system.</p>
Dataset related to the publication "Nonlinear dynamics and chaos in an optomechanical beam", DOI: 10.1038/ncomms14965
<p>This folder contains the raw data from which the graphs in paper "Nonlinear dynamics and chaos in an optomechanical beam", DOI: 10.1038/ncomms14965, have been obtained</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: Deconstruction of a plant-arthropod community reveals influential plant traits with nonlinear effects on arthropod assemblages
1. Studies of herbivores and secondary consumer communities rarely incorporate a comprehensive characterization of primary producer trait variation, thus limiting our understanding of how plants mediate community assembly of consumers. 2. We took advantage of recent technological developments for efficient generation of phytochemical, microbial, and genomic data to characterize individual alfalfa plants (Medicago sativa; Fabaceae) growing in an old-field, semi-naturalized state for 770 traits (including 753 chemical features). Using random forest modeling, we investigated the effect of variation in these traits on arthropod and fungal assemblages while accounting for plant genetic structure. 3. We found that traits indicative of plant vigor, including size, percentage of flowering stems, and leaf area, were positively associated with arthropod richness and abundance. Most phytochemicals were, by comparison, poor predictors, although phytochemical diversity and several individual phenolic compounds were important. Plants with a higher proportion of flowering stems were hotspots of inter-trophic interactions with higher species richness of secondary consumers. The effects of many traits on plant-associated assemblages were best modeled as nonlinear functions, often incorporating threshold effects. Foliar fungal richness was not well predicted by our models, suggesting we have much to learn regarding the role of plant traits on phyllosphere fungi at small spatial scales. 4. Our results support the need for characterization of multiple axes of plant phenotypes in studies of plant-arthropod-microbe communities, and demonstrate the value of modern analytical techniques for understanding the nonlinear ways in which plant traits mediate the structure of associated biotic communities.
Data Supporting: Identification of Nonlinearity Sources in a Flexible Wing
Open the record for dataset details and reuse information.
Data for The Persistence of Memory in Ionic Conduction Probed by Nonlinear Optics
<p>Experimental and computational data and analysis workflows for the manuscript "The Persistence of Memory in Ionic Conduction Probed by Nonlinear Optics" (doi:10.1038/s41586-023-06827-6). </p><p>Python scripts:</p><ol><li>paper_tke_plots_pub.py is for experimental TKE plots</li><li>analysis_pumping_pub.py is for computational TKE plots</li></ol><p>Python requirements for the work-up of experimental data are the typical scientific python stack: numpy, matplotlib, scipy, pandas, sympy. Computational counterpart of the TKE experiment uses essentially the same hopping analysis as our computational study https://www.nature.com/articles/s41563-022-01316-z with its scripting available at https://github.com/apoletayev/anomalous_ion_conduction/ . The python package requirements are, in addition to above, networkx, freud, deepgraph, fastparquet, pyarrow. All python scripts work best when run in a notebook-like fashion cell by cell (e.g. with spyder).<br><br>Experimental data: TKE, OKE, THz transmission.<br>Computational data: example simulations of Na beta-alumina, K beta-alumina, K beta"-alumina. The files include tracking the simulation temperatures, centers of mass of the mobile ions, and hopping. <br><br>Basic usage: download and unzip data. Install python dependencies (e.g. using conda or pip). Run python from the same directory in which the data folders are located. All paths in the scripts are relative.</p>
Public data for nonlinear optical computational histology
<p>Experimental datasets for training and testing nonlinear optical computational histology (NOCH), which include label-free nonlinear optical data: stimulated Raman scattering (SRS) images of human brain tumors and multiphoton (MP) images of human ovarian cancers, and the corresponding H&E slices. The <a href="https://github.com/shenblin/NOCH">contrastive deep learning framework</a> can generate diagnostic quality H&E slides comparable to conventional histopathology. </p> <p>If you find this work useful in your research, please consider citing the paper:</p> <p><a href="https://doi.org/10.1002/advs.202308630">B. Shen, Z. Li, Y. Pan, Y. Guo, Z. Yin, R. Hu, J. Qu, L. Liu, Noninvasive Nonlinear Optical Computational Histology. Adv. Sci. 2023, 2308630.</a></p>
Figure data for: Free-electron interaction with nonlinear optical states in microresonators
<p>This dataset contains the figure data and code for the paper "Free-electron interaction with nonlinear optical states in microresonators".</p>
Nonlinearities in phytoplankton groups across temperate high mountain lakes
<p>1-High mountain lakes are increasingly recognized as sentinel ecosystems of global change. Monitoring phytoplankton changes or reconstructing their composition from sedimentary records can help identify systemic changes in these lakes and their catchments. 2- This study aimed to evaluate the distribution of the major phytoplankton groups in high mountain lakes across environmental gradients and identify tipping points in relative dominance. The phytoplankton groups were estimated using pigment-based chemotaxonomy in 79 lakes in the Pyrenees selected to cover the bedrock and elevation gradients. Fifty-four environment variables were considered, including in-lake and catchment descriptors. 3-Redundancy analyses showed that in-lake descriptors override the explicative capacity of landscape variables. Generalized additive models and multivariate regression trees showed that water hardness, trophic state, and food web descriptors were, in this order, the most influential factors determining phytoplankton group dominance. Calcium concentration of about 200 μeq L-1 defined the threshold between soft waters – with chrysophytes and chlorophytes showing a higher affinity for them – and harder waters that favour diatoms and cyanobacteria. Across the trophic gradient, there was a threshold at ~5 μg L-1 of total phosphorus (TP), chrysophytes being dominant below that TP value and cryptophytes above. The dominance of chlorophytes and cryptophytes increased with the density of macrozooplankton. Chrysophytes were significantly lower and diatoms higher in lakes with fish. 4- Synthesis. The relative abundance of phytoplankton groups in temperate high mountain lakes responds in a nonlinear way to the hardness of the water in the range 20 – 1195 Ca2+ μeq L-1 and the trophic state in the range 0.94 - 19 μg L TP-1. The thresholds across water hardness and trophic state gradients coincide with studies based on other organisms, pointing to a robust typology for mountain lakes that should be considered when selecting global-change sentinel lakes and anticipating abrupt transitions across these thresholds.</p>
Substorm Dataset and code (Substorm Identification With The WINDMI Magnetosphere - Ionosphere Nonlinear Physics Model)
<p>The archive contains MATLAB Live Script (<code>.mlx</code>) and Simulink model (<code>.slx</code>) files.</p> <ul> <li> <p><strong><code>.mlx</code> files:</strong> MATLAB Live Scripts are interactive files that combine code, output, and formatted text in a single document. They are used for data analysis, visualization, and sharing workflows in an easy-to-read format. These files can be opened in MATLAB's Live Editor for an interactive coding experience.</p> </li> <li> <p><strong><code>.slx</code> files:</strong> Simulink model files are used in MATLAB's Simulink environment for graphical modeling and simulation of dynamic systems. They are particularly useful for designing and analyzing systems with time-dependent behaviors, such as control systems or physical processes.</p> </li> </ul>
Nonlinear sound-sheet microscopy: imaging opaque organs at the capillary and cellular scale
<p>This dataset accompanies the article entitled: "Nonlinear sound-sheet microscopy: imaging opaque organs at the capillary and cellular scale".</p> <div> <h3><strong>Wells with E. Coli (Wells_EColi.zip)</strong></h3> <p><strong>Codes are hosted <a title="NSSM github repo" href="https://github.com/MarescaRenaudLabs/NSSM/releases/tag/v1.0.0" target="_blank" rel="noopener">here</a></strong></p> </div> <p>Representative dataset for paper figure 2D,E. The file <code>RFData_planes_figure_2E.mat</code> contains the RFData and the required parameters to reconstruct two orthogonal sound sheets, in SSM and NSSM mode. The file <code>demo_reconstruct_orthogonal_NSSM_images.m</code> shows how to reconstruct the sound sheet data.</p> <p>The file <code>beamformed_volume_figure_2E.mat</code> contains beamformed SSM and NSSM volumes as displayed in figure 2G. The file <code>demo_navigate_3D_NSSM_data.m</code> can be used to view the volumes.</p> <div> <h3><strong>mARG expression in orthopic tumors (mArg_tumors.zip)</strong></h3> <p><strong>Codes are hosted <a title="NSSM github repo" href="https://github.com/MarescaRenaudLabs/NSSM/releases/tag/v1.0.0" target="_blank" rel="noopener">here</a></strong></p> </div> <p>Representative dataset for paper figure 3B. The file <code>RFData_planes_figure_3B.mat</code> contains the RFData and the required parameters to reconstruct two orthogonal sound sheets, in SSM and NSSM mode. The file <code>demo_reconstruct_orthogonal_NSSM_images.m</code> shows how to reconstruct the sound sheet data.</p> <p>The file <code>beamformed_volume_figure_3B.mat</code> contains beamformed SSM and NSSM volumes as displayed in figure 3C. The file <code>demo_navigate_3D_NSSM_data.m</code> can be used to view the volumes.</p> <h3><strong>Nonlinear Soundsheet Localization Microscopy (NSSLM_zenodo_archive.zip)</strong></h3> <p><strong>Codes are hosted <a title="NSSLM github repo" href="https://github.com/MarescaRenaudLabs/NSSLM/releases/tag/v1.0.0" target="_blank" rel="noopener">here</a></strong></p> <p>A zip compressed dataset containing beamformed images and post-processed trajectories for Nonlinear Soundsheet Localization Microscopy.</p> <ul> <li>The files <code>ImgNSSM_00x.mat</code> are 4D data arrays of size (157x160x2x2100). They hold 2 soundsheets repeated for 2100 frames at 1000Hz (more details are provided in the Material and Methods section of accompanying papers). Use this dataset to run script <code>processNSSLM.m</code></li> <li>The file <code>Params.mat</code> is a file containing the <code>ULM</code> structure. This comprises the fields necessary to execute ULM codes from the <a href="https://github.com/AChavignon/PALA" target="_blank" rel="noopener">PALA toolbox</a></li> <li>A folder named Trajectories. This contains 50 files. Each contains the trajectories obtained from NSSLM processing of the entire sequence for soundsheet indexed 1 in the 4D matrix. Use this dataset to run script <code>renderingNSSLM.m</code></li> </ul> <p>Each of these datasets is to be used in conjunction with the different example scripts given on <strong><a title="NSSLM github repo" href="https://github.com/MarescaRenaudLabs/NSSLM/releases/tag/v1.0.0" target="_blank" rel="noopener">here</a></strong>.</p> <h3>Codes hosted on github</h3> <p>For accompanying codes, please refer to:</p> <ul> <li>https://github.com/MarescaRenaudLabs/NSSM/releases/tag/v1.0.0</li> <li>https://github.com/MarescaRenaudLabs/NSSLM/releases/tag/v1.0.0</li> </ul>
Data for: An implicit split-operator algorithm for the nonlinear time-dependent Schrödinger equation
<p>Data for publication: J. Roulet, J. Vanicek, An implicit split-operator algorithm for the nonlinear time-dependent Schrödinger equation, J. Chem. Phys. <strong>155</strong>, 204109 (2021).</p> <p>Contains the data for reproducing the figures in the abovementioned publication.</p>
Models of evolutionary rescue with plasticity and nonlinear environmental change: code and data
<p>Rapid environmental changes are putting numerous species at risk of extinction. For migration-limited species, persistence depends on either phenotypic plasticity or evolutionary adaptation (evolutionary rescue). Current theory on evolutionary rescue typically assumes linear environmental change. Yet accelerating environmental change may pose a bigger threat. Here we present the simulation code and data from a model of a species encountering an environment with accelerating or decelerating change, to which it can adapt through evolution or phenotypic plasticity (within-generational or transgenerational). We show that unless either form of plasticity is sufficiently strong or adaptive genetic variation is sufficiently plentiful, accelerating or decelerating environmental change increases extinction risk compared to linear environmental change for the same mean rate of environmental change. </p>
Data for the paper: "Nonlinear responses of droughts over China to volcanic eruptions at different drought phases"
<p>These files are data used in the paper "Nonlinear responses of droughts over China to volcanic eruptions at different drought phases", which is published on the Geophysical Research Letters (GRL). The uploaded data are simulations from volcanic sensitivity experiments, with volcanic eruptions added in the "late-" and "early-" phases of each of the 15 drought events, respectively. The sensitivity experiments are performed using the Community Earth System Model (CESM) version 1.0.3.</p> <p>The compressed file "data.zip" is comprised of 4 sub-files containing variables of precipitation (prect), 500hPa vertical speed (Omega), East Asia Summer Monsoon index (EASM index), and soil moisture, respectively.</p> <p>In each sub-file, there are 6 txt datasets. Among the 6 ".txt" files, three of them are precipitation(EASM/Omega/Soil Moisture) anomalies centered with volcanic eruptions taking place in the late-phase of the 15 drought events (late-) in the CTRLs (with suffix "ctrl.txt"), volcanic sensitivity experiments with respect to the climatology (with suffix "vol.txt"), and volcanic sensitivity experiments with respect to the CTRLs (with suffix "vol-ctrl.txt"). Another three ".txt" files are simulations with volcanic eruptions taking place in the early-phase of the 15 drought events (early-). Each ".txt" file contains 15 time series, and each time series is 21 years' long, with 10 years before and 10 years after the volcanic eruption.</p>
JET-ILW Nonlinear Pedestal ETG Data
<p>Contains data for paper on nonlinear pedestal electron-temperature-gradient turbulence simulations:</p> <p>*.py # python plotting scripts for generating paper plots.<br> *.txt, *.npy # post-processed data required for plotting scripts.<br> *.png, *.eps, *.pdf # paper plots.<br> *.in # gs2 and stella input files for simulations in this paper.</p> <p>stella used for nonlinear simulations (https://github.com/mabarnes/stella)</p>
Nonlinear down-conversion in a single quantum dot
<p>This repository contains original experimental and theoretical data which belongs to the manuscript "Nonlinear down-conversion in a single quantum dot" by B. Jonas, D. Heinze, E. Schöll, P. Kallert, T. Langer, S. Krehs, A. Widhalm, K. D. Jöns, D. Reuter, S. Schumacher, and A. Zrenner</p>
Architectural effects regulate resource allocation within the inflorescences with nonlinear blooming patterns
<p>These data were generated to investigate the resource allocation pattern within the inflorescence of <em>Salvia przewalskii</em>, a perennial herb with 4-ouvle ovary flowers and flowering sequence-floral position decoupled inflorescences. Spatial and temporal resource allocations within inflorescences have been well-studied in many plants based on flowering sequence or floral position. However, there have been few attempts to investigate architectural effects and resource competition in species where the blooming pattern does not follow a linear positional pattern within the inflorescence. Moreover, most flowering plants show female-biased sex allocation in early or basal flowers, but it is unclear in species with inherent and changeless ovule production. The data demonstrated that pollen production and dry mass deceased from bottom to top flowers but didn't significantly differ following flowering sequence, resulting in male-biased sex allocation in basal flowers. The seed production, fruit set, bud developmental exhibited significant declining trends from proximal to distal positions regardless of the thinning and pollen treatments. Meanwhile, the seed production, fruit set, bud developmental success did not significant difference when thinning conducted according to flowering sequence. Thus, architectural effects plays a crucial role in resource allocation within decoupled flowering inflorescences. Moreover, the inherent floral traits, such as changeless ovule production, may modify architectural effects on sex allocation. </p>
Nonlinear Reconstruction for Operator Learning of PDEs with Discontinuities
<p>Data for the benchmarks problems of the paper "Nonlinear Reconstruction for Operator Learning of PDEs with Discontinuities"</p>
Data that are used to Explain the Forcing Efficacy with Pattern Effect and Feedback Nonlinearity"
<p> This dataset is for the draft "Explaining the Forcing Efficacy with Pattern Effect and Feedback Nonlinearity".</p> <p> The netcdf file "last150yravg_picontrol.nc" represents the time-average fields for the last 150 years of PI-control experiment. Netcdf files beginning with "last20yravg" represent the time-average fields for the last 20 years (Year131-150) of abrupt forcing experiments. Note that "0p5co2" in the file name denotes 0.5xCO2, "4psolar" denotes +4% solar radiation, and "m2psolar" denotes -2% solar radiation.</p> <p> The netcdf files beginning with "fixedsst" represent the time-average fields for fixed-SST experiments, where the file "fixedsst_control.nc" denotes the fixed SST control experiment.</p> <p> The netcdf files beginning with "uni" represent the time-average fields for uniform warming/cooling experiments, where the magnitude of SST change is indicated by the file names (m2K denotes -2K).</p> <p> The text file "GFA_partialR_over_partial_SST" denote the value of partial_R over partial_SST for each grid, and its grid (96x144) is same as other netcdf files in this datasets .</p> <p> </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.