Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
5,371
datasets available to search
ShareScore release 0.9.0
Dataset results
5,371 results for “Flow”
Figure 5 from: Sampaio FAC, Rufino MS, Pompeu PS, Santos HA, Ferreira RL (2020) Hydraulic flow resistance of epigean and hypogean fish of the family Trichomycteridae (Ostariophysi, Siluriformes). Subterranean Biology 35: 97-110. https://doi.org/10.3897/subtbiol.35.55064
Figure 5 Relative critical speed (body length/s) of the tested epigean and hypogean species.
Data from: Imposed work of breathing for flow meters with in-line versus flow-through technique during simulated neonatal breathing
Background: The ability to determine airflow during nasal CPAP (NCPAP) treatment without adding dead space or resistance would be useful when investigating the physiologic effects of different NCPAP systems on breathing. The aim of this study was to investigate the effect on pressure stability of different flow measuring devices at the in-line and flow-through position, using simulated neonatal breathing. Methods: Six different flow measure devices were evaluated by recording pressure changes and imposed work of breathing for breaths with 16 and 32 ml tidal volumes. The tests were performed initially with the devices in an in line position and with 5 and 10 L/min using flow through technique, without CPAP. The flow meters were then subsequently tested with an Infant Flow CPAP system at 3, 5 and 8 cm H2O pressure using flow through technique. The quality of the recorded signals was compared graphically. Results: The resistance of the measuring devices generated pressure swings and imposed work of breathing. With bias flow, the resistance also generated CPAP pressure. Three of the devices had low resistance and generated no changes in pressure stability or CPAP pressure. The two devices intended for neonatal use had the highest measured resistance. Conclusion: The importance of pressure stability and increased work of breathing during non-invasive respiratory support are insufficiently studied. Clinical trials using flow-through technique have not focused on pressure stability. Our results indicate that a flow-through technique might be a way forward in obtaining a sufficiently high signal quality without the added effects of rebreathing and increased work of breathing. The results should stimulate further research and the development of equipment for dynamic flow measurements in neonates.
Data from: Transitions in the flow patterns and aerodynamic characteristics of the flow around staggered rows of cylinders
A two-dimensional numerical study of flow across rows of identical square cylinders arranged in staggered fashion is carried out. This study will unreveal complex flow physics depending upon the Reynolds number (Re) and gap spacing (g) between the cylinders. The combined effect of Reynolds number and gap spacing on the flow physics around staggered rows of cylinders are numerically studied for 20 ≤ Re ≤ 140 and 1 ≤ g ≤ 6. We use the lattice Boltzmann method for numerical computations. It is found that with increase in gap spacing between the cylinders the critical Reynolds number for the onset of vortex shedding also increases. We observed a strong effect of Reynolds number at g = 2 and 4. Secondary cylinder interaction frequency disappears for large Reynolds number at g = 6 and 5 and the flow around cylinders are fully dominated by the primary vortex shedding frequency. This ensures that at large gap spacing with an increase in the Reynolds number the wakes interaction between and behind the cylinders is weaken. Furthermore, it also ensures that the wake interaction behind the cylinders is strongly influenced by the jets in the gap spacing between the cylinders. We also found that g = 2 is the critical gap spacing for flow across rows of staggered square cylinders for the considered range of Reynolds number. Depending on the Reynolds number we observed; synchronous, quasi-periodic-I, quasi-periodic-II, and chaotic flow patterns. In synchronous flow pattern, an in-phase and anti-phase characteristics of consecutive cylinders has been observed. The important physical parameters are also analyzed and discussed in detail.
Data from: Continuum of vasodilator stress from rest to contrast medium to adenosine hyperemia for fractional flow reserve assessment
OBJECTIVES: We compared the diagnostic performance with adenosine-derived fractional flow reserve (FFR) #0.8 of contrast-based FFR (cFFR), resting distal pressure (Pd)/aortic pressure (Pa), and the instantaneous wave-free ratio (iFR). BACKGROUND: FFR objectively identifies lesions that benefit from medical therapy versus revascularization. However, FFR requires maximal vasodilation, usually achieved with adenosine. Radiographic contrast injection causes submaximal coronary hyperemia. Therefore, intracoronary contrast could provide an easy and inexpensive tool for predicting FFR. METHODS: We recruited patients undergoing routine FFR assessment and made paired, repeated measurements of all physiology metrics (Pd/Pa, iFR, cFFR, and FFR). Contrast medium and dose were per local practice, as was the dose of intracoronary adenosine. Operators were encouraged to perform both intracoronary and intravenous adenosine assessments and a final drift check to assess wire calibration. A central core lab analyzed blinded pressure tracings in a standardized fashion. RESULTS: A total of 763 subjects were enrolled from 12 international centers. Contrast volume was 8 +- 2 ml per measurement, and 8 different contrast media were used. Repeated measurements of each metric showed a bias <0.005, but a lower SD (less variability) for cFFR than resting indexes. Although Pd/Pa and iFR demonstrated equivalent performance against FFR #0.8 (78.5% vs. 79.9% accuracy, p ¼ 0.78; area under the receiver-operating characteristic curve: 0.875 vs. 0.881, p ¼ 0.35), cFFR improved both metrics (85.8% accuracy and 0.930 area, p < 0.001 for each) with an optimal binary threshold of 0.83. A hybrid decision-making strategy using cFFR required adenosine less often than when based on either Pd/Pa or iFR. CONCLUSIONS: cFFR provides diagnostic performance superior to that of Pd/Pa or iFR for predicting FFR. For clinical scenarios or health care systems in which adenosine is contraindicated or prohibitively expensive, cFFR offers a universal technique to simplify invasive coronary physiological assessments. Yet FFR remains the reference standard for diagnostic certainty as even cFFR reached only ~85% agreement.
Data from: Empirical phylogenies and species abundance distributions are consistent with pre-equilibrium dynamics of neutral community models with gene flow
Community characteristics reflect past ecological and evolutionary dynamics. Here, we investigate whether it is possible to obtain realistically shaped modelled communities – i.e., with phylogenetic trees and species abundance distributions shaped similarly to typical empirical bird and mammal communities – from neutral community models. To test the effect of gene flow, we contrasted two spatially explicit individual-based neutral models: one with protracted speciation, delayed by gene flow, and one with point mutation speciation, unaffected by gene flow. The former produced more realistic communities (shape of phylogenetic tree and species-abundance distribution), consistent with gene flow being a key process in macro-evolutionary dynamics. Earlier models struggled to capture the empirically observed branching tempo in phylogenetic trees, as measured by the gamma statistic. We show that the low gamma values typical of empirical trees can be obtained in models with protracted speciation, in pre-equilibrium communities developing from an initially abundant and widespread species. This was even more so in communities sampled incompletely, particularly if the unknown species are the youngest. Overall, our results demonstrate that the characteristics of empirical communities that we have studied can, to a large extent, be explained through a purely neutral model under pre-equilibrium conditions.
Data from: Measuring the biodiversity of microbial communities by flow cytometry
1. Measuring the microbial diversity in natural and engineered environments is important for ecosystem characterization, ecosystem monitoring and hypothesis testing. Although the conventional assessment through single marker gene surveys has resulted in major advances, the complete procedure remains slow (i.e., weeks to months), labour-intensive and susceptible to multiple sources of laboratory and data processing bias. Growing interest, in highly resolved, temporal surveys of microbial diversity, necessitates rapid, inexpensive and robust analytical platforms that require limited computational effort. 2. Here, we demonstrate that sensitive single-cell measurements of phenotypic attributes, obtained via flow cytometry, can provide fast (i.e., within minutes) first-line assessments of microbial diversity dynamics, without demanding extensive sample preparation and downstream data processing. We developed a data processing pipeline that fits bivariate kernel density functions to phenotypic parameter combinations of an entire microbial community, and concatenates them to a single one-dimensional phenotypic fingerprint. By calculating established diversity metrics from such phenotypic fingerprints, we construct an alternative interpretation of the microbial diversity that incorporates distinct phenotypic traits underlying cell-to-cell heterogeneity (i.e., morphology and nucleic acid content). 3. Based on a detailed longitudinal study of a highly dynamic microbial ecosystem, our approach delivered temporal alpha diversity profiles that strongly correlated with the reference diversity, as estimated by 16S rRNA amplicon sequencing. This strongly suggests that the distribution of a limited amount of phenotypic features within a microbial community already provides sufficient resolving power for the measurement of diversity dynamics at the species level. 4. We present a fast, robust analysis method for monitoring the microbial biodiversity of natural and engineered ecosystems that correlates well with the conventional marker gene surveys. Our work has both applied and fundamental implications that stretch from ecosystem monitoring and studies on microbial community dynamics, to supervised sampling strategies. Furthermore, our approach offers perspectives for the development of on-line and in situ monitoring systems for microbial ecosystems.
Data from: How mechanisms of habitat preference evolve and promote divergence with gene flow
Habitat preference may promote adaptive divergence and speciation, yet the conditions under which this is likely are insufficiently explored. We use individual-based simulations to study the evolution and consequence of habitat preference during divergence with gene flow, considering four different underlying genetically-based behavioral mechanisms: natal habitat imprinting, phenotype-dependent, competition-dependent, and direct genetic habitat preference. We find that the evolution of habitat preference generally requires initially high dispersal, is facilitated by asymmetry in population sizes between habitats, and is hindered by an increasing number of underlying genetic loci. Moreover, the probability of habitat preference to emerge and promote divergence differs greatly among the underlying mechanisms. Natal habitat imprinting evolves most easily and can allow full divergence in parameter ranges where no divergence is possible in the absence of habitat preference. The reason is that imprinting represents a one-allele mechanism of assortative mating linking dispersal behavior very effectively to local selection. At the other extreme, direct genetic habitat preference, a two-allele mechanism, evolves under restricted conditions only, and even then facilitates divergence weakly. Overall, our results indicate that habitat preference can be a strong reproductive barrier promoting divergence with gene flow, but that this is highly contingent on the underlying preference mechanism.
Data from: Sex-biased gene flow among elk in the greater Yellowstone ecosystem
We quantified patterns of population genetic structure to help understand gene flow among elk populations across the Greater Yellowstone Ecosystem. We sequenced 596 base pairs of the mitochondrial (mt)DNA control region of 380 elk from eight populations. Analysis revealed high mtDNA variation within populations, averaging 13.0 haplotypes with high mean gene diversity (0.85). The genetic differentiation among populations for mtDNA was relatively high (FST = 0.161; P = 0.001) compared to genetic differentiation for nuclear microsatellite data (FST = 0.002; P = 0.332), which suggested relatively low female gene flow among populations. The estimated ratio of male to female gene flow (m_m/m_f = 46) was among the highest we have seen reported for large mammals. Genetic distance (for mtDNA pair-wise FST) was not significantly correlated with geographic (Euclidean) distance between populations (Mantel's r = 0.274, P = 0.168). Large mtDNA genetic distances (e.g. FST > 0.2) between some of the geographically closest populations (<65 km) suggested behavioral factors and/or landscape features might shape female gene flow patterns. Given the strong sex-biased gene flow, future research and conservation efforts should consider the sexes separately when modeling corridors of gene flow or predicting spread of maternally transmitted diseases. The growing availability of genetic data to compare male versus female gene flow provides many exciting opportunities to explore the magnitude, causes, and implications of sex-biased gene flow likely to occur in many species.
Data from: Estimation of inhalation flow profile using audio-based methods to assess inhaler medication adherence
Asthma and chronic obstructive pulmonary disease (COPD) patients are required to inhale forcefully and deeply to receive medication when using a dry powder inhaler (DPI). There is a clinical need to objectively monitor the inhalation flow profile of DPIs in order to remotely monitor patient inhalation technique. Audio-based methods have been previously employed to accurately estimate flow parameters such as the peak inspiratory flow rate of inhalations, however, these methods required multiple calibration inhalation audio recordings. In this study, an audio-based method is presented that accurately estimates inhalation flow profile using only one calibration inhalation audio recording. Twenty healthy participants were asked to perform 15 inhalations through a placebo Ellipta™ DPI at a range of inspiratory flow rates. Inhalation flow signals were recorded using a pneumotachograph spirometer while inhalation audio signals were recorded simultaneously using the Inhaler Compliance Assessment device attached to the inhaler. The acoustic (amplitude) envelope was estimated from each inhalation audio signal. Using only one recording, linear and power law regression models were employed to determine which model best described the relationship between the inhalation acoustic envelope and flow signal. Each model was then employed to estimate the flow signals of the remaining 14 inhalation audio recordings. This process repeated until each of the 15 recordings were employed to calibrate single models while testing on the remaining 14 recordings. It was observed that power law models generated the highest average flow estimation accuracy across all participants (90.89±0.9% for power law models and 76.63±2.38% for linear models). The method also generated sufficient accuracy in estimating inhalation parameters such as peak inspiratory flow rate and inspiratory capacity within the presence of noise. Estimating inhaler inhalation flow profiles using audio based methods may be clinically beneficial for inhaler technique training and the remote monitoring of patient adherence.
Videos for: Modeling 2D gravity-driven flow in unsaturated porous media for different infiltration rates
<p>This dataset contains videos of transient flow simulations in unsaturated porous media flow related to the manuscript: Modeling 2D gravity-driven flow in unsaturated porous media for different infiltration rates.</p>
HOT Primary Production and Flow Cytometry v2022
<p>This dataset consists of measurements of photosynthetic primary production, chlorophyll a and phaeopigment concentrations, and flow cytometry-based determinations of the abundances of heterotrophic bacteria and the picophytoplankton - Prochlorococcus, Synechococcus and small eukaryotic phytoplankton. All samples were collected through the Hawaii Ocean Time-series (HOT) program, which began in 1988 with ~monthly cruises to Station ALOHA (A Long-term Oligotrophic Habitat Assessment; 22° 10 N, 158° 00 W). Photosynthetic production of organic matter was measured by the 14C tracer method. Details on the methods employed over the years are detailed in Karl et al., Progress in Oceanography (https://doi.org/10.1016/j.pocean.2021.102563). Flow cytometry-based determinations of microbial abundances were made using an EPICS 753 flow cytometer on HOT 22-173 (December 1980 – September 2005) and a B/D Influx flow cytometer beginning with HOT 174 . Details on the flow cytometry methods are provided at (https://hahana.soest.hawaii.edu/hot/methods/bact.html). Samples for chlorophyll a and phaeopigments were collected onto Whatman GF/F filters and extracted with 100% acetone and measured on a Turner Designs Model 10-AU fluorometer based on standard techniques described in Strickland and Parsons, 1972. Method details available at (https://hahana.soest.hawaii.edu/hot/methods/chl.html). Time is in a separate column from date. Dates and times are in local time (HST).</p>
Microscopy and flow cytometry raw data for: A genetically encoded biosensor to monitor dynamic changes of c-di-GMP with high temporal resolution
<p><br>This repository contains the microscopy and flow cytometry raw data for the following publication:</p> <p><strong>A genetically encoded biosensor to monitor dynamic changes of c-di-GMP with high temporal resolution</strong></p> <p>Andreas Kaczmarczyk, Simon van Vliet, Roman Peter Jakob, Raphael Dias Teixeira, Inga Scheidat, Alberto Reinders, Alexander Klotz, Timm Maier, Urs Jenal</p> <p>Biozentrum, University of Basel, 4056 Basel, Switzerland</p> <p>Correspondence to: urs.jenal[at]unibas.ch, andreas.kaczmarczyk[at]unibas.ch</p>
101 million cell case simulation of subsurface CO2 storage simulated with OPM Flow
<p>This dataset contains both the simulation description (DECK files) and the simulation output for a SPE11C derived test case with 101 million grid cells being simulated for 1000 years. The simulation was carried out on the Karolina cluster at IT4I using 32 CPU nodes on the project DD-23-66. The version of OPM Flow was a pre-2024.04 release version.<br><br>This upload is a preliminary upload as the current output is corrupt (the output needs to be read carefully in MRST/MATLAB). An updated upload is soon to follow. This upload is for perservation of historical data.</p>
PIV data of flow surrounding HEK-293 cell growth
<p>The dataset contains archived data from PIV measurements of flow in an organ-on-a-chip device presented as velocity fields in (yx), as well as cross sections of the data containing dimensions (z) needed to correctly display the data.</p>
High-resolution traffic flow data in Glasgow
<p><strong>Description of the dataset</strong></p> <p>This dataset offers a long-term traffic flow data at an intra-city scale with high spatio-temporal granularity. The dataset covers the Glasgow City Council area for four consecutive years spanning the COVID-19 pandemic, from October 2019 to September 2023, providing comprehensive temporal and spatial coverage. </p> <p>The code used to produce the indicators is available at: <a href="https://github.com/YueLi-0816/TrafficFlowData">https://github.com/YueLi-0816/TrafficFlowData</a>.</p> <p>This work is funded by the China Scholarship Council (CSC) from the Ministry of Education of P.R. China, the ESRC’s ongoing support for the Urban Big Data Centre (UBDC), and the Royal Society International Exchange Scheme.</p> <p><strong>Contents</strong></p> <p>Sensor status metadata - status.csv</p> <table> <tbody> <tr> <td> <p><span>Column name</span></p> </td> <td><span>Description</span></td> </tr> <tr> <td> <p><span>id</span></p> </td> <td><span>Unique ID for each sensor, e.g., GA0601_T.</span></td> </tr> <tr> <td> <p><span>latitude</span></p> </td> <td><span>The Latitude in decimal degrees of WGS84 coordinates, e.g., 55.86238129.</span></td> </tr> <tr> <td> <p><span>longitude</span></p> </td> <td><span>The Longitude in decimal degrees of WGS84 coordinates, e.g., -4.26570708.</span></td> </tr> <tr> <td> <p><span>step 1</span></p> </td> <td><span>The status of sensors at the current step is 1 if retained and 0 if removed.</span></td> </tr> <tr> <td> <p><span>step 2</span></p> </td> <td><span>The status of sensors at the current step is 1 if retained and 0 if removed.</span></td> </tr> <tr> <td> <p><span>step 3</span></p> </td> <td><span>The status of sensors at the current step is 1 if retained and 0 if removed.</span></td> </tr> <tr> <td> <p><span>step 4</span></p> </td> <td><span>The status of sensors at the current step is 1 if retained and 0 if removed.</span></td> </tr> <tr> <td> <p><span>step 5.1</span></p> </td> <td><span>The status of sensors at the current step is 1 if retained and 0 if removed.</span></td> </tr> <tr> <td> <p><span>step 5.2</span></p> </td> <td><span>The status of sensors at the current step is 1 if retained and 0 if removed.</span></td> </tr> </tbody> </table> <p>Sensor location metadata - locations.csv</p> <table> <tbody> <tr> <td>Column name</td> <td>Description</td> </tr> <tr> <td>id</td> <td>Unique ID for each sensor, e.g., GA0601_T.</td> </tr> <tr> <td>latitude</td> <td>The Latitude in decimal degrees of WGS84 coordinates, e.g., 55.86238129.</td> </tr> <tr> <td>longitude</td> <td>The Longitude in decimal degrees of WGS84 coordinates, e.g., -4.26570708.</td> </tr> </tbody> </table> <p> </p> <p>Traffic flows metadata</p> <table> <tbody> <tr> <td>File name</td> <td>Description</td> </tr> <tr> <td>[sensor_id].csv</td> <td>Traffic flows. [sensor_id] refers to the ‘id’ from the locations.csv</td> </tr> </tbody> </table> <p> </p> <table> <tbody> <tr> <td>Column name</td> <td>Description</td> </tr> <tr> <td>date</td> <td>The date the data is collected (YYYY-MM-DD), e.g., 2021-11-04.</td> </tr> <tr> <td>time</td> <td>The hours of the day the data is collected range from 0 to 23, 0 = [0,1), 23 = [23,24).</td> </tr> <tr> <td>flow</td> <td>Number of vehicles that pass the sensor location during the one-hour interval. </td> </tr> </tbody> </table>
Flow cytometry changes in murine XBP1 KO fed high fat diet
<p>Nonalcoholic fatty liver disease (NAFLD) is one of the most common causes of liver diseases in the United States and can progress to cirrhosis, end-stage liver disease and need for liver transplantation. There are limited therapies for NAFLD, in part, due to incomplete understanding of the disease pathogenesis, which involves different cell populations in the liver. Endoplasmic reticulum stress and its adaptative unfolded protein response (UPR) signaling pathway have been implicated in the progression from simple hepatic steatosis to nonalcoholic steatohepatitis (NASH). We have previously shown that mice lacking the UPR protein X-box binding protein 1 (XBP1) in the liver demonstrated enhanced liver injury and fibrosis in a high fat sugar (HFS) dietary model of NAFLD. In this study, to better understand the role of liver XBP1 in the pathobiology of NAFLD, we fed hepatocyte XBP1 deficient mice a HFS diet or chow and investigated UPR and other cell signaling pathways in hepatocytes, hepatic stellate cells and immune cells. We demonstrate that loss of XBP1 in hepatocytes increased inflammatory pathway expression and altered expression of the UPR signaling in hepatocytes and was associated with enhanced hepatic stellate cell activation after HFS feeding. We believe that a better understanding of liver cell-specific signaling in the pathogenesis of NASH may allow us to identify new therapeutic targets.</p>
In-operando visualization of redox flow battery in membrane-free microfluidic platform
<p>These data sheets are voltage-capacity characteristics of in-operando visualization in terms of mass-, and charge-transfer. </p> <p> </p>
Dataset: Daily Flows and Nutrients Loads in the Sprague River Basin, WY2002-2020
<p>Daily flows and nutrient (phosphorus, nitrogen, total suspended solids) loads were estimated for multiple locations in the Sprague River Basin (OR) over water year (WY) 2002-2020. These timeseries were computed using continuous and biweekly flow data in combination with biweekly nutrient measurements collect by Klamath Tribes at eight sampling stations across the basin. The estimated timeseries were then used as a basis to investigate the spatial and temporal dynamics of nutrient concentrations and loads, estimate relative amounts of background and anthropogenic loading, assess the potential impacts of the Klamath Tribes' water rights calls on instream flow and water quality in recent years, and evaluate long-term trends at each sampling station within the Sprague River basin.</p> <p>The data sources and methodologies used to generate this dataset are described in the following report:</p> <blockquote> <p>Walker, J.D. and J. Kann (2022). Spatial and Temporal Nutrient Loading Dynamics in the Sprague River Basin, OR, Water Years 2002 – 2020. Technical Report prepared for the Klamath Tribes Natural Resources Department. 114p. + appendices. <a href="https://doi.org/10.5281/zenodo.7377353">https://doi.org/10.5281/zenodo.7377353</a></p> </blockquote> <p>Source code available here: <a href="https://github.com/walkerjeffd/sprague-nutrient-dynamics">https://github.com/walkerjeffd/sprague-nutrient-dynamics</a></p> <p>See README.txt for details about each file including column descriptions.</p>
Flow estimates example for k = 50 - Information-Theoretic Sensor Placement for Large-Scale Sewer Networks
<p>This dataset is used to generate Figure 7 without running the simulations in the paper Information-Theoretic Sensor Placement for Large-Scale Sewer Networks.</p>
Flow channelling variability in transit times and tortuosity in a fractured rock model with small scale heterogeneity
<p>Description for file "simulation-particle-data-all-cases".</p> <p>First row is header information, as follows: </p> <p>Column 1, label "avf"<br> The variance of fracture aperture fields (m2)</p> <p>Column 2, label "sdx"<br> The correlation length factor of fracture aperture fields (-)</p> <p>Column 3, label "t"<br> Particle transit time (yr)</p> <p>Column 4, label "log_t"<br> Base-10 logarithm of transit time </p> <p>Column 5, label "l"<br> Particle trajectory length (m)</p> <p>Column 6, label "tort"<br> Particle trajectory tortuosity (-)</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.