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5,371 results for “Flow”
Data from: Independently evolved and gene flow‐accelerated pesticide resistance in two‐spotted spider mites
<p>Pest species are often able to develop resistance to pesticides used to control them, depending on how rapidly resistance can emerge within a population or spread from another resistant population. We examined the evolution of bifenazate resistance in China in the two‐spotted spider mite (TSSM) <em>Tetranychus</em> <em>uticae</em> Koch (Acari: Tetranychidae), one of the most resistant arthropods, by using bioassays, detection of mutations in the target <em>cytb</em> gene, and population genetic structure analysis using microsatellite markers. Bioassays showed variable levels of resistance to bifenazate. The <em>cytb</em> mutation G126S, which confers medium resistance in TSSM to bifenazate, had previously been detected prior to the application of bifenazate and was now widespread, suggesting likely resistance evolution from standing genetic variation. G126S was detected in geographically distant populations across different genetic clusters, pointing to the independent origin of this mutation in different TSSM populations. A novel A269V mutation linked to a low‐level resistance was detected in two southern populations. Widespread resistance associated with a high frequency of the G126S allele was found in four populations from the Beijing area which were not genetically differentiated. In this case, a high level of gene flows likely accelerated the development of resistance within this local region, as well as into an outlying region distant from Beijing. These findings, therefore, suggest patterns consistent with both local evolution of pesticide resistance as well as an impact of migration, helping to inform resistance management strategies in TSSM.</p>
Diffusion in Temporal Networks: London Tube passenger flows
<p>This video shows the diffusion of visitation probabilities of a random walk in a temporal network that has been constructed based on time-stamped data on passenger flows in the London Tube network.</p> <p>The left panel shows a random walk based on the empirical temporal network. This temporal network exhibits non-Markovian characteristics as shown in [1]. The right panel shows a random walk based on a a shuffled version of the same network, in which all order correlations are destroyed. This corresponds to a Markovian temporal network in which all time-respecting path statistics correspond to what is expected based on the static, time-aggregated network.</p> <p>This video is an illustrative supporting animation for the following paper:</p> <p><em>[1] Ingo Scholtes, Nicolas Wider, René Pfitzner, Antonios Garas, Claudio Juan Tessone and Frank Schweitzer: </em><strong>Causality-driven</strong><strong> slow-down and speed-up of diffusion in non-Markovian temporal networks, </strong>Nature Communications, Vol. 5, Article 5024, September 24, 2014</p>
Supplementary Information S1 - Detailed results of the CAPRI N-LCA and S2 - Quantification of the main N budget flows in the EU25 agriculture sector of Leip, A., Billen, G., Garnier, J., Grizzetti, B., Lassaletta, L., Reis, S., Simpson, D., Sutton, M. a, de Vries, W., Weiss, F., Westhoek, H. (2015). Impacts of European livestock production: nitrogen, sulphur, phosphorus and greenhouse gas emissions, land-use, water eutrophication and biodiversity. Environ. Res. Lett. 10, 115004. doi:10.1088/1748-9326/10/11/115004
<p>Table S1-1 Quantification of GHG and Nr flow intensities [kg CO2eq (kg product)<sup>-1</sup> yr<sup>-1</sup>] or [g N (kg product)<sup>-1</sup> yr<sup>-1</sup>] with the CAPRI N-LCA model for six main livestock products (BEEF: beef, PORK: pork, EGGS: eggs, POUM: poultry meat; DAIR: milk and dairy products, SGMP: meat from sheep and goats) and six main vegetable food groups (POTA: potatoes, SUGB: sugar beet before processing, OILP: oil seeds before processing; CERR: cereals, LEGU: leguminous crops) as well as other crops (OCRP) and aggregated livestock (ANIMP) and vegetable (CROPP) food. </p> <p>Table S2-1 Quantification of the main N budget flows in the EU25 agriculture sector</p>
Flow cytometry data from human iPSC-derived macrophages
<p>Human induced pluripotent cells (iPSCs) were obtained from the HipSci project (http://www.hipsci.org) and differentiated into macrophages using an established protocol (van Wilgenburg, 2013). The genotype_id column of the flow_sample_metadata.txt file contains the canonical HipSci iPSC line name from which the macrophages were differentiated.</p> <p><strong>Data acquisition</strong></p> <p>We used flow cytometry to measure the cell surface expression of three canonical macrophage markers: CD14, CD16 (FCGR3A/FCGR3B) and CD206 (MRC1). Macrophages were cultured in 10 cm tissue-culture treated plates and detached from the plates by incubation in 6 mg/ml lidocaine-PBS solution (Sigma L5647) for 30 minutes followed by gentle scraping. From each cell line we harvested between 300,000-500,000 cells. Detached cells were washed in media, centrifuged at 1200 rpm for 5 minutes and resuspended in flow cytometry buffer (2% BSA, 0.001% EDTA in D-PBS) and split into two wells of a 96-well plate. Nonspecific antibody binding sites were blocked by incubating cells with Human TruStain FcX (Biolegend) for 45 minutes and washing with flow cytometry buffer. Half of the cells were stained for 1 hour with the PE-isotype control (BD 555749) antibody. The other half of the cells were co-stained for 1 hour with following three antibodies: CD14-Pacific Blue (BD 558121), CD16-PE (BD 555407), CD206-APC (BD 550889). After staining, the cells were washed three times. Resuspended cells were filtered through cell-strainer cap tubes (BD 352235) and measured on the BD LSRFortessa Cell Analyzer.</p>
Averaged results of blood flow simulations with discrete RBC tracking for microvascular networks
<p>The dataset contains the results for blood flow simulations in 3 cerebral micorvascular networks.The microvascular networks are from the mouse parietal cortex (Blinder et al., 2013) and embedded in a tissue volume of approximately 1 cubic mm. For the blood flow simulations we used a numercial model with discrete tracking of RBCs which is described in Schmid et al., 2017.</p> <p>For each network the following data are provided:<br> - Microvascular network with averaged flow and pressure field, as well as averaged values for the distribution and motion of red blood cells (RBCs).<br> - RBC trajectories describing the motion of individual RBCs through the microvascular networks.<br> - The data is stored as a graph, i.e. vertices connected by edges.<br> - Details regarding the simulation parameters can be found in Schmid et al., 2017.<br> - Data format (pickle - files containing python dictonairies).<br> <br> <strong>Microvascular networks:</strong><br> <strong>edgesDict.pkl:</strong> dictionary with edge related data (dictionary keys: flow [um^3/ms], diameter [um], tuple [-], httBC [-], nkind [-], length [um], htt [-], nRBC [-], diameters [um], points [um])<br> <strong>verticesDict.pkl:</strong> dictionary with vertex related data (dictionary keys: pressure [mmHg], coordinates [um], pBC [mmHg])</p> <p>Additional comments on dictionary keys:<br> - pBC: pressure boundary conditions. 'None' for internal nodes. Assigned based on the hierarchical boundary conditions approach (see Schmid et al. 2017 for details)<br> - tuple: connectivity of graph, tuple of vertices<br> - httBC: tube hematocrit boundary conditions. 'None' for internal nodes. Constant value assigned.<br> - nkind: integere to describe the vessel type. 0: pial artery, 1: pial venule, 2: descending arteriole, 3: ascending venule, 4: capillaries, 5: unknown<br> - htt: tube hematocrit<br> - nRBC: number of red blood cells<br> - points: list of tortuous vessel coordinates per edge<br> - diameters: local diameter measurements associated to the 'points' key.</p> <p><br> <strong>RBC trajectories:</strong><br> <strong>RBC_trajectories.pkl: </strong>dictonary for each RBC with relevant tracking data (dictionary key: RBC index). The relavant tracking data per RBC is stored in another dictionary with the following keys: edges, lengths, times, pressure, nkindsMod, RBCleft</p> <p>Additional comments on dictionary keys per RBC:<br> - RBCleft: bool to indicate that RBC left the computational domain<br> - edges: edge indices through which the RBC moves on its way through the vasculature<br> - pressure: pressure [mmHg] values at the nodes along the RBC trajectory<br> - times: time [ms] the RBC spends in the respective edge segment<br> - nkindsMod: nkind at the nodes along the RBC trajectory <br> - lengths: cummulative length travelled [um]</p>
Data and results for manuscript "Flow dynamics in hyper-saline aquifers: hydro-geophysical monitoring and modeling"
<p>The paper presents a general methodology that will help understand how freshwater and saltwater may interact in natural porous media, with a particular view at practical applications such as the storage of freshwater underground in critical areas such as semi-arid zones around the Mediterranean sea. The methodology is applied to a case study in Sardinia and shows how a mix of advanced monitoring and mathematical modeling tremendously advance our understanding of these systems.</p> <p>This package contains the raw cross-hole time-lapse ERT data, additional field data, the ERT inversion results of the field data as well as the modeling data in terms of the concentration distribution of the density-dependent flow and transport model and the inverted synthetic ERT monitoring results.</p>
Climate impact_River flow_Sweden
<p>Climate-impact ensemble of River flow (m<sup>3</sup> yr<sup>-1</sup>) for 12 selected hydropower plants in Swedish rivers, as well as the total river discharge to the Swedish coast. The dataset include modelled time-series from 18 ensemble members with daily values from 1981-2100, calculated with the HYPE model code (HYPE_version_4_8_0) in the S-HYPE model set-up (s-hype2012_version_2_0_0). Model code can be downloaded from: http://hypecode.smhi.se/ and climate projections from ESGF at https://www.cordex.org/. The data is in Excel format with one sheet per climate projection.</p>
hydropower impact_river flow_Sweden
<p>River flow (m<sup>3</sup> yr<sup>-1</sup>) for 12 selected hydropower plants in Swedish rivers as well as the total river discharge to the Swedish coast. The dataset include both Naturalised River Flow and Regulated River Flow, in daily time-series from 1981-2010, calculated with the HYPE model code (HYPE_version_4_3_1) in S-HYPE model set-ups (QR: s-hype2012_version_1_2_1 resp. QN: s-hype2012QN_version_1_2_1). Model code can be downloaded from: http://hypecode.smhi.se/ and model results with high spatial resolution can be downloaded from http://vattenwebb.smhi.se/. The results for the whole country of Sweden have been published in: Arheimer, B. and Lindström, G. 2014. Electricity vs Ecosystems – understanding and predicting hydropower impact on Swedish river flow. Evolving Water Resources Systems: Understanding, Predicting and Managing Water–Society Interactions. Proceedings of ICWRS2014, Bologna, Italy, June 2014; IAHS Publ. 364:313-319.</p>
Peak flow identified at selected GRDC stations and the corresponding hydrological and hydrometeorological state variables
Data set contains a list of peak flows at selected GRDC stations as well as the start, peak, and end dates of each selected event. Hydrometeorlogical variables and hydrological state variables simulated by a hydrological model E-HYPE corresponding to each selected event are also listed in the dataset. Further description and content of each data file is available in the included metadata.
Dataset for manuscript 'CeyeHao: AI-driven microfluidic flow programming with hierarchically assembled obstacles in microchannel and receptive-field-augmented neural network'
<p>This dataset contains:<br>1. The dataset used to train the models related to the manuscript 'CeyeHao: AI-driven microfluidic flow programming using hierarchically assembled obstacles in microchannel with receptive-field-augmented neural network'.<br>2. A checkpoint of trained 'CEyeNet' proposed in the manuscript.<br>3. Example microchannels designed in the manuscript to produce semantic flow profiles</p> <p>This dataset is intended for research and academic purpose.</p> <p>Detailed description please refer to the enclosed ReadMe.txt.</p>
Information flows around agricultural best management practices in central Pennsylvania
<p>This dataset was collected between February and April 2019, to assess the information network of agricultural Best-Management Practices (BMPs) in central Pennsylvania, a sub-region of the Chesapeake Bay watershed.</p> <p>It contains information flows (or "messages") relating to 16 specific BMPs, including:</p> <ul> <li>the BMP it relates to (e.g. riparian buffers, manure management planning, no-till, cover-cropping, etc.);</li> <li>the source and target of the information (actors);</li> <li>the kind of message (e.g. funding, regulation, technical assistance, etc.);</li> <li>the weight (strength) of messages (only for those received by farmers directly).</li> </ul> <p>Over 3900 messages/information flows were recorded, involving 57 actors.</p> <p>This data was used to conduct the study "Navigating agricultural nonpoint source pollution governance: A social network analysis of best management practices in central Pennsylvania".</p>
Twin test 1: Effect of vegetation on urban flows. PIV data from NTUA WT experiment and LDV from KIT WT experiment
<p>The first Twin Test (TW1) of the TWEET-IE project (<a href="http://www.tweet-ie.eu">www.tweet-ie.eu</a>) involved measurements of the flow past a surface mounted cube with openings, representing a building exposed to an atmospheric boundary layer. Tests were performed for smooth building walls but also with modelled vegetation covering the windward façade and the roof of the building. The measurements were performed both at Karlsruhe Institute of Technology (KIT) and the National Technical University of Athens (NTUA), in wind tunnels, at common locations around the building. Laser Doppler Anemometry (LDA) was used at KIT and Particle Image Velocimetry (2C-2D and 3C-2D PIV) at NTUA. In the present data set shows the effect of vegetation on the flow velocities and a comparison of the twin wind tunnel measurements. </p>
3D cell tracking dataset of bacterial biofilm deformation and recovery under shear flow
<p>This MAT file includes dataset in the scientific article "<i>In vivo</i> microrheology reveals elastic and plastic responses inside three-dimensional bacterial biofilms" by the following authors: Takuya Ohmura, Dominic Skinner, Konstantin Neuhaus, Gary Choi, Jörn Dunkel, Knut Drescher. This MAT file can be conveniently opened with Matlab. </p><p>When you open this file with Matlab, you will find 4 variables stored in the file "Data_v3_loop2_newRxy_bidx1_274.mat"</p><p><strong>Variable 1: name_parameter</strong></p><p>Names of 31 parameters for columns in 3 variables: 'deformation_all', 'recovery_all' , 'plasticity_all'. The parameters have cell displacements, orientations, coordinates, biofilm indexes and experimental conditions. When the parameters have units, they are shown in the names. </p><ul><li>'x_Frame1[um]'</li><li>'y_Frame1[um]'</li><li>'z_Frame1[um]'</li><li>'Normalized_x_Frame1'</li><li>'Normalized_y_Frame1'</li><li>'Normalized_z_Frame1'</li><li>'LocalDensity_Frame1(VolumeFractionAround30px)'</li><li>'LocalCellNumberDensity_Frame1(VolumeFractionAround30px)'</li><li>'NematicOrderParameter_Frame1'</li><li>'AlignmentFlow_Frame1[rad]'</li><li>'AlignmentRadial_Frame1[rad]'</li><li>'AlignmentZaxis_Frame1[rad]'</li><li>'d_x[um]'</li><li>'d_y[um]'</li><li>'d_z[um]'</li><li>'Normalized_d_x'</li><li>'Normalized_d_y'</li><li>'Normalized_d_z'</li><li>'d_LocalDensity'</li><li>'d_LocalNumberDensity[um^-3]'</li><li>'d_NematicOrderParameter'</li><li>'d_AlignmentFlow[rad]'</li><li>'d_AlignmentRadial[rad]'</li><li>'d_AlignmentZaxis[rad]'</li><li>'CrossProduct[um^2]'</li><li>'BiofilmIndexNumber'</li><li>'Biofilm_width[um]'</li><li>'Biofilm_height[um]'</li><li>'Biofilm_volume[um^3]'</li><li>'FlowRate[ul/min]'</li><li>'Duration[min]'</li></ul><p><strong>Variable 2: deformation_all</strong></p><p>The rows indicate 704198 single-cell trackings in deformations of 274 bacterial biofilms. Each of the 274 bacterial biofilms has a different 'BiofilmIndexNumber'. The columns indicate 31 parameters which names are shown in 'name_parameter'.</p><p><strong>Variable 3: recovery_all</strong></p><p>The rows indicate 685991 single-cell trackings in recoveries of 274 bacterial biofilms. Each of the 274 bacterial biofilms has a different 'BiofilmIndexNumber'. The columns indicate 31 parameters which names are shown in 'name_parameter'.</p><p><strong>Variable 4: plasticity_all</strong></p><p>The rows indicate 665749 single-cell trackings in plasticities of 274 bacterial biofilms. Each of the 274 bacterial biofilms has a different 'BiofilmIndexNumber'. The columns indicate 31 parameters which names are shown in 'name_parameter'.</p><p> </p><p>To plot the cell tracked data in the figures of the article, use our MATLAB code uploaded in our GitHub (https://github.com/knutdrescher/biofilm-rheology).</p>
Interspecific introgression and widespread intraspecific gene flow in a clade of tropical and subtropical seabirds
<p>The mechanisms that restrict gene flow between populations and facilitate population differentiation and speciation vary across the tree of life. In systems where physical barriers to gene flow are dynamic over time and space, such as many marine species, genetic introgression may be a major factor in the speciation process. In sympatric species of seabirds, hybridization has been frequently observed but few studies have investigated patterns of introgression. We used whole-genome sequence data to test for interspecific introgression between five pairs of tropical and subtropical seabird species and to test for gene flow within species across major land mass barriers and ocean basins. We found evidence for introgression between: blue-footed (<em>Sula</em> <em>nebouxii</em>) and Peruvian boobies (<em>S. variegata</em>); masked (<em>S. dactylatra</em>) and Nazca boobies (<em>S. granti</em>); and blue-footed and Nazca boobies. We found no evidence of introgression between blue-footed and brown boobies (<em>S. leucogaster</em>), or masked and brown boobies, despite observed hybridization between these species. We also found evidence for gene flow across several major land masses in three pantropical species: red-footed (<em>S. sula</em>), brown, and masked boobies. Finally, we report mixed evidence for ancient introgression between brown boobies and the ancestor of blue-footed, Peruvian, masked, and Nazca boobies. Our work indicates (1) that interspecific introgression has shaped contemporary booby diversity in the eastern Pacific, and (2) that contemporary physical barriers to gene flow between booby colonies are not absolute. Our findings contribute novel insights to the growing body of evidence that introgression is a widespread evolutionary process.</p>
Silica dissolution under a flow of pure water at pressure and temperature conditions relevant to geothermal energy extraction
<p>This dataset is a published product of the 'REFLECT' Project - a Horizon Europe project which aims to inform the processes of geothermal energy extraction by determining the effect of relevant fluid properties and reactions in order to enhance predictive geochemical modelling and thus the energy exploitation and life-time of geothermal power plants.</p><p>The dataset records the concentration of silica measured in water that had been passed through a packed column of quartz grains at temperatures from 200 to 450°C and pressures from 150 to 450 bar. Concentrations are reported as g/ml SiO2, measured photometrically. The reader is referred to the full report for deliverable 1.4 of the REFLECT project for details of the experimental set up and interpretation of the data.</p><p>Silica concentrations marked with (a) are believed to be artificially reduced compared to the rest of the dataset due to a reduction in the surface density of active sites during some of the highest dissolution experiments. The final column lists the chronological order in which the measurements were taken to assist with interpretation of this factor.</p><p>The density marked with (b) represents the density of water at 150 bar and 342°C, rather than the measured condition of 148 bar and 344°C. This is to reflect the fact that the solubility measurement suggests the presence of a liquid phase - the conditions chosen represent the closest point on the phase boundary to the measured conditions. The discrepancy may reflect a small shift in the phase envelope due to silica dissolution in addition to any uncertainty in the <i>pT</i> measurements.</p>
Dataset from : Detection and Analysis of an Alternate Flow Pattern in a Radial Vaned Diffuser
<p>This dataset pertains to the publication 'Detection and Analysis of an Alternate Flow Pattern in a Radial Vaned Diffuser', V. Moënne-Loccoz, I. Trébinjac, N. Poujol, P. Duquesne. International Journal of Turbomachinery, Propulsion and Power. MDPI (2020).</p><p>Where possible, each figure is provided in CSV format.</p>
FIGURE 2 in Speciation with gene flow in marine systems
FIGURE 2 Cladogram of the hypotheses of Animalia (after Dunn et al., 2014) and Chromista (after CavalierSmith, 2018) phylogenies. Animalia and Chromista clades in which marine species have been described, are marked blue, with clades in which potential cases of ecological speciation with gene flow Downloaded from Brill.com 12/12/2023 03:01:49PM have been identified in orangevia. Open LettersAccess refer.toThis examples is an of openspecies accessshown articlein fig. 1. distributed under the terms of the prevailing CC-BY license at the time of publication. http://creativecommons.org/licenses/by-nc/4.0
FIGURE 1 in Speciation with gene flow in marine systems
FIGURE 1 Examples of some species which potentially arose through ecological speciation with gene flow. The octocoral Eunicea flexuosa (a; photo by Y.W. Lau), the Caribbean hamlet Hypoplectrus unicolor (b; photo by O. Puebla), the intertidal gastropod Littorina saxatilis (c; photo by P. Larsson), the nudibranch Phestilla minor (d; photo by A. Fritts-Penniman), the Japanese greenling Hexagrammos otakii (e; photo by Z. Kanamoto), the corallivorous gastropod Coralliophila violacea (f; photo by S.E. Simmonds), the Downloaded from Brill.com 12/12/2023 03:01:49PM seahorse Hippocampus erectus (via g; Open photo by Access E.. RoseThis), the is an snapping open access shrimparticle Alpheus armatus distributed(h;under photothe terms by A. Anker), the undescribed, coral-associated of gobytheGobiodon prevailingsp. B (CC-BY i; photo licenseby P. at L. the Mundaytime),of and the publication. Caribbean sponge Chondrilla caribensis (j; photo by N.J. de Voogdhttp):. //creativecommons.org/licenses/by-nc/4.0
FIGURE 3 in Speciation with gene flow in marine systems
FIGURE 3 Genetic mechanisms of single traits driving divergence. Disruptive selection acting on a mating cue (e.g., colour pattern or body size) targeted by a preference locus elsewhere in the genome ('classic magic trait', after Servedio et al., 2011) results into assortative mating (a). In case of habitat or host differentiation and mating on the host species, disruptive selection may directly lead to assortative mating (b), without the need for a preference locus ('automatic magic trait'). Figures after Servedio et al. (2011). Downloaded from Brill.com 12/12/2023 03:01:49PM via Open Access. This is an open access article distributed under the terms of the prevailing CC-BY license at the time of publication. http://creativecommons.org/licenses/by-nc/4.0
Data for: Characterization of large-scale preferential flow across continental United States
<p>Understanding preferential flow (PF) at large scales is critical for improving land management and groundwater (GW) quality. However, limited knowledge of this process, due to soil surface heterogeneity and observational constraints, hampers progress. In this study, we propose estimating effective PF at remote sensing footprint scale (4 – 9 km) by examining its impact on soil moisture (SM) distribution and shallow GW (SGW) table fluctuations (depth 5 m). Effective PF encompasses macropore, funnel, and finger flow pathways influencing SGW table fluctuations. We compiled daily SGW observations (2019-2021) from 19 continental US (CONUS) sites through USGS. Using inverse modeling in HYDRUS-1D, SGW data, and CHIRPS precipitation data, we inversely estimated soil hydraulic parameters of the dual porosity model (DPM) simulating vertical flow from soil surface to subsurface. Effective PF presence was inferred using three criteria: (1) daily precipitation >= the site-specific average across multiple (calibration) years, (2) daily observed SGW table increase, and (3) daily difference between observed and DPM simulated SGW tables 50% of the site-specific RMSE. Leveraging optimized DPM parameters and associated soil texture, classified PF events, and Soil Moisture Active Passive (SMAP L3E) satellite-based SM, a Random Forest algorithm with 10-fold cross validation predicted large-scale effective PF events. Results indicate seasonal dependence, with spring having the highest occurrence of PF events. The Random Forest model achieved 98% accuracy in predicting large-scale PF events, with SMAP SM and saturated hydraulic conductivity (Ks) among the 4 most impactful variables. Our approach provides a soil hydraulic property, site characteristic, soil texture and remote sensing based generalized tool to analyze large-scale effective PF.</p>
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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.