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1,670 results for “forcing”
Idealized single-forcing GCM simulations with GFDL CM2.1: daily data
<p>This repository contains daily model output from experiments run using the Geophysical Fluid Dynamics Laboratory (GFDL) Climate Model 2.1 (CM2.1), a coupled atmosphere-ocean general circulation model. The experiments were designed to isolate the effect of a single orbital forcing on climate by changing one forcing while holding all others to preindustrial levels. The seven single-forcing idealized equilibrium simulations comprised low and high obliquity experiments in which obliquity was set to the extremes of the past 600 ky, four precession experiments representing equally spaced phases of the precession cycle, and an experiment in which eccentricity was set to 0. A preindustrial experiment was run with all forcings set to preindustrial values. Simulations were run for at least 500 years and these files contain 100 years of daily output.<br> <br> Provided here are daily output of geopotential height at 500 hPa (hght.500) and daily maximum and minimum temperature at a reference height of 2m (t_ref_max and t_ref_min, respectively).<br> <br> Preindustrial experiment values (and values of forcings set to preindustrial in other experiments):<br> - Obliquity: 23.439°<br> - Longitude of perihelion: 102.93°<br> - Eccentricity: 0.0167<br> - CO2: 286 ppm<br> - Ice sheets: 0 ka BP<br> <br> Low and high obliquity experiments (lo_obliq & hi_obliq):<br> - Low obliquity: 22.079°<br> - High obliquity: 24.480<br> - All else preindustrial<br> <br> Precession experiments (0_AEQ, 90_WSOL, 180_VEQ, & 270_SSOL):<br> - 0_AEQ longitude of perihelion: 0° (NH autumnal equinox)<br> - 90_WSOL longitude of perihelion: 90° (NH winter solstice)<br> - 180_VEQ longitude of perihelion: 180° (NH vernal equinox)<br> - 270_SSOL longitude of perihelion: 270° (NH summer solstice)<br> - Eccentricity: 0.0493<br> - All else preindustrial<br> <br> 0 eccentricity experiment:<br> - Eccentricity: 0<br> - Longitude of perihelion: N/A<br> - All else preindustrial<br> <br> <br> The experiments were run by Michael Erb and climatological data for these variables and more are available here: http://doi.org/10.5281/zenodo.1194480.<br> <br> <br> Contact:<br> Grainne O’Neill grainneroneill@gmail.com</p>
Simulation files for POPC lipid membrane with Slipids-VIS force field for Gromacs MD simulation engine
<p>The tar.gz archive contains simulation input files that were used in the publication Transmembrane potential modeling: Comparison between methods of constant electric field and ion imbalance.</p> <p>http://pubs.acs.org/doi/abs/10.1021/acs.jctc.5b01202</p> <p>The files are meant to be used with <strong>Gromacs</strong> simulation package (gromacs.org).</p> <p>A modified Slipids force field, <strong>Slipids-VIS</strong>, is introduced. It uses Virtual Interaction sites in order to speed up simulation. The technique is described in the aforementioned work. The archive contains working topology for <strong>POPC</strong> lipid molecules and 6fs timestep without any significant loss of accuracy.</p>
Supplementary underlying data for "Evaluating parameterization protocols for hydration free energy calculations with the AMOEBA polarizable force field"
<p>This dataset includes additional underlying data for the publication "Evaluating parameterization protocols for hydration free energy calculations with the AMOEBA polarizable force field"</p> <p>Contents:</p> <p>Tukey Honest Significant Difference (HSD) results for solutes 1-47 across all seven parameter sets, as *.txt. These are pairwise comparisons of results between all possible parameter sets. Significant differences are treated as p < 0.05.</p>
Atomic Force Microscopy Images of Cell Specimens
<p>This data set consists of seven atomic force microscopy images in MI format as well as corresponding previews in PNG format.</p> <p>The microscopy images are of cell material and have been scanned with AFM equipment from Keysight Technologies. Details on the individual images:</p> <ul> <li>image_0.mi - Chinese hamster ovary cells</li> <li>image_1.mi - Chinese hamster ovary cells</li> <li>image_2.mi - human bladder carcinoma cells</li> <li>image_3.mi - human bladder carcinoma cells</li> <li>image_4.mi - Chinese hamster ovary cells</li> <li>image_5.mi - Chinese hamster ovary cells</li> <li>image_6.mi - Chinese hamster ovary cells</li> </ul> <p>The images can be opened using, e.g. Gwyddion: http://gwyddion.net/<br /> The Python package Magni can be used to load the images into Python (using the magni.afm.io module): https://github.com/SIP-AAU/Magni</p> <p>The images are provided as-is without warranty of any kind.</p>
Algorithms for Reconstruction of Undersampled Atomic Force Microscopy Images Dataset
<p>This deposition contains the results from a simulation of reconstructions of undersampled atomic force microscopy (AFM) images. The reconstructions were obtained using a variety of interpolation and reconstruction methods.</p> <p>The deposition consists of:</p> <ol> <li>An HDF5 database containing the results from simulations of reconstructions of undersampled atomic force microscopy images (reconstruction_goblet_ID_0_of_1.hdf5).</li> <li>The Python script which was used to create the database (reconstruction_goblet.py).</li> <li>Auxillary Python scripts needed to run the simulations (optim_reconstructions.py, it_reconstruction.py, interp_reconstructions.py, gamp_reconstructions.py, and utils.py).</li> <li>MD5 and SHA256 checksums of the database and Python script files (reconstruction_goblet.MD5SUMS, reconstruction_goblet.SHA256SUMS).</li> </ol> <p>The HDF5 database is licensed under CC BY 4.0 (http://creativecommons.org/licenses/by/4.0/) . Since the CC BY 4.0 license is not well suited for source code, the Python script is licensed under the BSD 2-Clause license (http://opensource.org/licenses/BSD-2-Clause) .</p> <p><strong>The files are provided as-is with no warranty as detailed in the above mentioned licenses.</strong></p> <p>The simulation results in the database are based on "Atomic Force Microscopy Images of Cell Specimens" and "Atomic Force Microscopy Images of Various Specimens" by Christian Rankl licensed under CC BY 4.0 (http://creativecommons.org/licenses/by/4.0/). The original images are available at http://dx.doi.org/10.5281/zenodo.17573 and http://dx.doi.org/10.5281/zenodo.60434. The original images are provided as-is without warranty of any kind. Both the original images as well as adapted images are part of the dataset. </p>
Haptically perceived softness of deformable stimuli can be manipulated by applying external forces during the exploration
<p>The perception of softness is the result of the integration of information provided by multiple cutaneous and kinesthetic signals. The relative contributions of these signals to the combined percept of softness was not yet addressed directly. We transmitted subtle external vertical forces to the exploring human finger during the exploration of deformable silicone rubber stimuli to dissociate the force estimates provided by the kinesthetic signals and the efference copy from cutaneous force estimates. This manipulation introduced a conflict between the cutaneous and the kinesthetic/efference copy information on softness. We measured Points of Subjective Equality (PSE) of manipulated references to stimuli which were explored without external forces. PSEs shifted as a linear function of external force in predicted directions - to higher compliances with pushing and to lower compliances with pulling force. We found relative contribution of kinesthetic/efference copy information to perceived softness being 23% for rather hard and 29% for rather soft stimuli. Our results suggest that an integration of the kinesthetic/efference copy information and cutaneous information with constant weights underlies softness perception. The kinesthetic/efference copy information seems to be slightly more important for the perception of rather soft stimuli.</p> <p>Metzger, A., & Drewing, K. (2015). Haptically perceived softness of deformable stimuli can be manipulated by applying external forces during the exploration. In World Haptics Conference (WHC), 2015 IEEE (pp. 75-81). IEEE.</p> <p> </p> <p>The Zip file contains all data relative to the publication. The data of each participant is contained in a separate folder. This folder contains a *.raw file for each session of the experiment and a "data" folder, which contains movement trajectories (*.trj files) and the staircase reversals for each condition (*.pse files) in separate folders for each session.</p> <p>A description of the variables is contained in the file VARIABLE_CODES.txt</p>
Supplemental dataset to "Cloud sync in response to wave-like large-scale forcings"
<p>This dataset deposits the supplemental materials for the manuscript "Cloud sync in response to wave-like large-scale forcings".</p> <p><a href="https://zenodo.org/api/records/14164798/draft/files/math_note.pdf/content" target="_blank" rel="noopener noreferrer">math_note.pdf</a> A hand-written math derivation note for equations in the appendices. </p> <p><a href="https://zenodo.org/uploads/15304862" target="_blank" rel="noopener noreferrer">movie_wL_006_T24hours.avi</a> A movie of near-surface (z=25m) water vapor mixing ratio for the wL=0.006m/s and T=24 hours experiment (the reference CM1 simulation).</p> <p><a href="https://zenodo.org/api/records/15304862/draft/files/movie_wL_006_T18hours.avi/content" target="_blank" rel="noopener noreferrer">movie_wL_006_T18hours.avi</a> A movie of near-surface (z=25m) water vapor mixing ratio for the wL=0.006m/s and T=18 hours experiment.</p> <p><a href="https://zenodo.org/api/records/15304862/draft/files/movie_wL_006_T12hours.avi/content" target="_blank" rel="noopener noreferrer">movie_wL_006_T12hours.avi</a> A movie of near-surface (z=25m) water vapor mixing ratio for the wL=0.006m/s and T=12 hours experiment.</p> <p><a href="https://zenodo.org/api/records/15304862/draft/files/movie_wL_000.avi/content" target="_blank" rel="noopener noreferrer">movie_wL_000.avi</a> A movie of near-surface (z=25m) water vapor mixing ratio, without large-scale wave-like forcing.</p> <p><a href="https://zenodo.org/api/records/15304862/draft/files/input_sounding/content" target="_blank" rel="noopener noreferrer">input_sounding</a> The initial sounding for all CM1 simulations. </p> <p><a href="https://zenodo.org/api/records/15304862/draft/files/namelist.input/content" target="_blank" rel="noopener noreferrer">namelist.input</a> The namelist file for launching all CM1 simulations. </p> <p><a href="https://zenodo.org/api/records/15304862/draft/files/postprocessing_CM1.zip/content" target="_blank" rel="noopener noreferrer">postprocessing_CM1.zip</a> The postprocessing code of the CM1 simulations, including intermediate output files (.mat) in data postprocessing. </p> <p><a href="https://zenodo.org/api/records/14164798/draft/files/microscopic_model.zip/content" target="_blank" rel="noopener noreferrer">microscopic_model.zip</a> The MATLAB code for the microscopic model. </p> <p><a href="https://zenodo.org/api/records/15304862/draft/files/cm1.F/content" target="_blank" rel="noopener noreferrer">cm1.F</a> The CM1 script where the large-scale vertical velocity is programmed. You can copy it directly to your CM1/src/ path. </p> <p> </p> <p>Feel free to send an email to Dr. Hao Fu (haofu@nju.edu.cn) if you have any questions!</p> <p> </p>
Microtubules growing and shortening under constant force
<div class="abstract"> <div class="abstract-content selected"> <p>Kinetochores are macromolecular machines that couple chromosomes to dynamic microtubule tips during cell division, thereby generating force to segregate the chromosomes. Accurate segregation depends on selective stabilization of correct 'bi-oriented' kinetochore-microtubule attachments, which come under tension as the result of opposing forces exerted by microtubules. Tension is thought to stabilize these bi-oriented attachments indirectly, by suppressing the destabilizing activity of a kinase, Aurora B. However, a complete mechanistic understanding of the role of tension requires reconstitution of kinetochore-microtubule attachments for biochemical and biophysical analyses <em>in vitro</em>. Here we show that native kinetochore particles retaining the majority of kinetochore proteins can be purified from budding yeast and used to reconstitute dynamic microtubule attachments. Individual kinetochore particles maintain load-bearing associations with assembling and disassembling ends of single microtubules for >30 min, providing a close match to the persistent coupling seen<em> in vivo</em> between budding yeast kinetochores and single microtubules. Moreover, tension increases the lifetimes of the reconstituted attachments directly, through a catch bond-like mechanism that does not require Aurora B. On the basis of these findings, we propose that tension selectively stabilizes proper kinetochore-microtubule attachments in vivo through a combination of direct mechanical stabilization and tension-dependent phosphoregulation.</p> </div> </div>
Quantifying local stiffness and forces in soft biological tissues using droplet optical microcavities
<p>Dataset for publication Quantifying local stiffness and forces in soft biological tissues using droplet optical microcavities</p>
SST forcing files and Model Builds for "Inter-basin versus intra-basin sea surface temperature forcing of the Western North Pacific subtropical high's westward extensions"
<p>This repository provides archives of the Community Earth System Model version 2.2.0 (CESM2.2.0) and case directories for the simulations used in the "Inter-basin versus intra-basin sea surface temperature forcing of the Western North Pacific subtropical high's westward extensions" manuscript. The repository includes:</p><ul><li>The original sea surface temperature forcing files used in each experiment (SST_Forcing Files) </li><li>The F2000CLIMO compset model builds forced for each experiment </li></ul>
Genomic landscape of introgression from the ghost lineage in a gobiid fish uncovers the generality of forces shaping hybrid genomes
<p>Extinct lineages can leave legacies in the genomes of extant lineages through ancient introgressive hybridization. The patterns of genomic survival of these extinct lineages provide insight into the role of extinct lineages in current biodiversity. However, our understanding of the genomic landscape of introgression from extinct lineages remains limited due to challenges associated with locating the traces of unsampled "ghost" extinct lineages without ancient genomes. Herein, we conducted population genomic analyses on the East China Sea (ECS) lineage of <em>Chaenogobius annularis</em>, which was suspected to have originated from ghost introgression, with the aim of elucidating its genomic origins and characterizing its landscape of introgression. By combining phylogeographic analysis and demographic modeling, we demonstrated that the ECS lineage originated from ancient hybridization with an extinct ghost lineage. Forward simulations based on the estimated demography indicated that the statistic <em>γ</em> of the HyDe analysis can be used to distinguish the differences in local introgression rates in our data. Consistent with introgression between extant organisms, we found reduced introgression from extinct lineage in regions with low-recombination rates and with functional importance, thereby suggesting a role of linked selection that has eliminated the extinct lineage in shaping the hybrid genome. Moreover, we identified enrichment of repetitive elements in regions associated with ghost introgression, which was hitherto little-known but was also observed in the reanalysis of published data on introgression between extant organisms. Overall, our findings underscore the unexpected similarities in the characteristics of introgression landscapes across different taxa, even in cases of ghost introgression.</p>
Simulations used in the Ocean Science Journal submission titled "Internal and forced ocean variability in the Mediterranean Sea " by Benincasa et al., 2024
<p>Temperature (votemper) and current speed datasets from the EAS5 (Clementi et al., <em>Mediterranean Sea Analysis and Forecast (CMEMS MED-Currents, EAS5 system),</em> 2019; Coppini et al., <em>The Mediterranean forecasting system. Part I: evolution and performance</em>, EGUsphere, pp. 1–50, 2023) simulations used in the manuscript titled "<em>Internal and forced ocean variability in the Mediterranean Sea"</em> and submitted to the journal Ocean Science by Benincasa et al. </p> <p>The daily fields are at 2 depth levels ( 0 = 0 m, 2 = 30 m) and in the 2 seasons (JFMA = winter, JASO = summer) for the entire Mediterranean Sea. The vertical profile of the temperature field up to about 950 m depth is available at 8 locations distributed over the basin. The depth levels are found in <em>depth.pkl</em>: the first column represents the depth of the various levels, whereas the second is the increments between 2 consecutive depth levels. </p>
Data Sets: Unsteady Land-Sea Breeze Circulations in the Presence of a Synoptic Pressure Forcing
<p>{Mg (m/s): 0, 0.4, 1.2, 2 and α: 0°, and 180°}</p> <p>Consult the details in Allouche et al. (2023): https://doi.org/10.1002/qj.4552. The latter corresponds to the steady state simulations of these transient ones here.<br>All of these simulations have a domain extent (L_x, L_y, L_z=z_i) of (80 km, 5 km, 1.6 km). The numerical mesh (Nx, Ny, Nz) is (384, 24, 64). For plotting, the vertical levels vary for each variable. A variable at 'c_s nodes' is plotted at dz/2, dz, 2*dz, 3*dz, and so forth up to z_i. A variable on 'w nodes' is plotted at 0, dz, 2*dz, 3*dz, and so forth up to z_i. This information is given in the variable table below.</p> <p>These simulations are given in a netcdf format (.nc). One is able to download and reshape these matrices.</p>
FORCe step-down-and-pivot biomechanical dataset
<p>Copyright (c) 2023 by La Trobe University </p> <p>This work is licensed under CC BY 4.0.</p> <p>----------------------------------------</p> <p>Correspondence: Prasanna Sritharan, p.sritharan@latrobe.edu.au</p> <p>Biomechanical data for the step-down-and-pivot task underaken as part of the FORCe project at the La Trobe Sports & Exercise Medicine Research Centre, La Trobe University, Victoria, Australia.</p> <ul> <li>Experimental joint angles and joint moment data for the step-down-and-pivot task. </li> <li>Relevant participant demographic data is provided.</li> <li>All valid participants and trials provided.</li> <li>All participants are fully de-identified.</li> <li>Joint angles are provided in degrees, and joint moments normalised to % of body weight * height.</li> <li>All trials resamples to 101 time steps, with a time vector provided.</li> </ul> <p>Any use of this data must cite the following published work:</p> <p>Crossley K, Pandy MG, Majumdar S, Smith AJ, Semciw AI, Kemp JL, Heerey JJ, King MG, Lawrenson PR, Lin YC, Souza RB. Femoroacetabular impingement and hip OsteoaRthritis Cohort (FORCe): protocol for a prospective study. Journal of Physiotherapy. 2017 Jan 1. <a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.jphys.2017.10.004" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.jphys.2017.10.004</a></p>
Data and code for figures: Design, fabrication and characterization of kinetic-inductive force sensors for scanning probe applications
<p>This directory contains the datasets, code (if applicable) for measurement libraries, data processing and figure generation for the research article "Design, fabrication and characterization of kinetic-inductive force sensors for scanning probe applications", Beilstein J. Nanotechnol. 2024, 15, 242-255.</p>
Supplementary data to "Radiative forcing and equivalent effective chlorine due to hydrochlorofluorocarbons peaked in 2021"
<p><span>README for Supplementary data to “</span><span>Radiative forcing and equivalent effective chlorine due to hydrochlorofluorocarbons peaked in 2021”</span></p> <p> </p> <p><span>This repository contains 4 folders:</span></p> <p><span>1) agage: contains the inputs to the 12-box model and the derived monthly and annual mole fractions (global and semi-hemispheric) using measurements from the AGAGE network.</span></p> <p><span>2) noaa: contains the inputs to the 12-box model and the derived monthly and annual mole fractions (global and semi-hemispheric) using measurements from the NOAA network.</span></p> <p><span>3) vollmer: contains the inputs to the 12-box model and the derived monthly and annual mole fractions (global and semi-hemispheric) using measurements from the measurements published in Vollmer et al. (2021).</span></p> <p><span>4) Projections: contains a csv file with the merged mole fractions (i.e., mean) from the various networks and the projected quantities.</span></p> <p> </p> <p><span>The 12-box model and the method used to quantify global mean mole fractions are available via GitHub (https://github.com/mrghg/py12box (last accessed 5 March 2024) and https://github.com/mrghg/py12box_invert (last accessed 5 March 2024)) and Zenodo (https://doi.org/10.5281/zenodo.6857447 and https://doi.org/10.5281/zenodo.6857794).</span></p> <p> </p> <p><span>AGAGE data are also available at http://agage.mit.edu/data/agage-data (last accessed 5 March 2024) and https://data.ess-dive.lbl.gov/ (current dataset <a href="https://doi.org/10.15485/1998580"><span>https://doi.org/10.15485/1998580</span></a>) and newer data can be made available upon request. The most recent NOAA atmospheric observations are available at https://gml.noaa.gov/aftp/data/hats/hcfcs/ (last accessed 5 March 2023). </span></p> <p> </p> <p><span>References:</span></p> <p><span>Vollmer, M. K. et al. Unexpected nascent atmospheric emissions of three ozone-depleting hydrochlorofluorocarbons. Proc Natl Acad Sci USA 118, e2010914118 (2021).</span></p>
Spatiotemporally distinct responses to mechanical forces shape the developing seed of Arabidopsis
<p><span>Source Data File related to the manuscript:</span></p> <p><a name="_Hlk141697088"></a><span> </span></p> <p><span>Spatiotemporally distinct responses to mechanical forces</span></p> <p><span>shape the developing seed of Arabidopsis</span></p> <p> </p> <p><span>See Description Dataset file for full description</span></p> <p><span> </span></p>
MD Simulation of AtALMT9 TMD Using Martini3 and charmm36 Force Field
<p>This dataset contains the MD simulation data associated with the article:</p> <p>"Structural basis for malate-driven, pore lipid-regulated activation of the Arabidopsis vacuolar anion channel ALMT9"</p> <p><em>(Not published yet)</em></p> <p> </p> <p>Folder</p> <p>AA : All-atom simulation files.</p> <p>CG : Coarse-grained simulation files.</p> <p>toppar : parameter files.</p> <p> </p> <p>File Description</p> <p>conf.pdb : Initial structure of the simulation.</p> <p>all.fit.10ns.now.zen.xtc : trajectory file without water. </p> <p>now.pdb : coordinate file of corresponding trajectory.</p> <p>topol.top : GROMACS topology file.</p> <p> </p> <p> </p>
Photo-thermal expansion of a PMMA nanosphere using mid-IR photo-induced force microscopy (PiF-IR)
<p>This dataset contains the raw data associated with our manuscript, <em>'Photo-thermal expansion of nanostructures in photo-induced force microscopy</em><strong>'</strong></p> <p>by Shohely Tasnim Anindo,1,2 Daniela Täuber,3,4 and Christin David*1,5</p> <div> <div> <div> <p>1 Institute of Condensed Matter Theory and Optics, Friedrich-Schiller-Universität Jena, Max-Wien-Platz 1, 07743 Jena, Germany<br>2 Abbe Center of Photonics, Albert-Einstein-Straße 6, 07745 Jena, Germany<br>3 Institute of Physical Chemistry, Friedrich-Schiller-Universität Jena, Helmholtzweg 4, 07743 Jena, Germany <br>4 Leibniz Institute of Photonic Technology, Albert-Einstein-Straße 9, 07745 Jena, Germany <br>5 University of Applied Sciences Landshut, Am Lurzenhof 1, 84036 Landshut, Germany</p> </div> </div> </div> <p>The raw data were acquired using a VistaScope (Molecular Vista, US) operated in the side-band mode of mid-infrared photo-induced force microscopy (PiF-IR). These data are associated with the experimental part in this manuscript. Details of the data acquisition and processing are described in the Methods section of the manuscript.</p> <p>The dataset is structured in the following:</p> <ul> <li>PiF-IR scans of a spherical PMMA nanoparticle with radius R = 50 nm (PMMA NP) at varied illumination power in the resonant condition using the illumination frequency: 1150 cm^-1</li> <li>PiF-IR scans of the same PMMA NP at varied illumination power in the non-resonant condition using the illumination frequency: 1300 cm^-1</li> <li>PiF-IR hyperspectral scan of the same PMMA NP over the spectral range 989 - 1349 cm^-1</li> </ul>
Demonstrations for imitation learning for the paper "Fitting parameters of linear dynamical systems to regularize forcing terms in Dynamical Movement Primitives"
<p>Demonstrations for the coathanger experiment in the paper "Fitting parameters of linear dynamical systems to regularize forcing terms in Dynamical Movement Primitives". https://elib.dlr.de/205110/</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.