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5,371 results for “Flow”
Picophytoplankton and bacteria total carbon estimates from cell counts analyzed with flow cytometry (FCM) from CCE LTER process cruises in the California Current region, 2006 - 2017.
Picophytoplankton populations and non-pigmented prokaryotes are sampled within the California Current Ecosystem (CCE) for abundances from various depths. Seawater is collected from Niskin bottles and cells are fixed in the field aboard the survey cruises (since 2004, ongoing) with paraformaldehyde, and stained with a DNA-specific dye back in the laboratory. The cells are enumerated by an Altra flow cytometer (with a syringe pump for volumetric sample delivery) simultaniously with argon ion lasers, to distinguish three major populations of photoautotrophs (Prochlorococcus, Synechococcus, and pico-eukaryotes) and the assemblage of heterotrophic prokaryotes collectively referred to as H-Bact. FCM abundance estimates for each are converted to carbon biomass equivalents using mixed-layer estimates.
Measurement of Absolute Retinal Blood Flow Using a Laser Doppler Velocimeter Combined with Adaptive Optics
<p><strong>Data set of measurements related to the following:</strong></p> <p><strong>Purpose: </strong>Development and validation of an absolute laser Doppler velocimeter (LDV) based on an adaptive optical fundus camera which provides simultaneously high definition images of the fundus vessels and absolute maximal red blood cells (RBCs) velocity in order to calculate the absolute retinal blood flow.</p> <p><strong>Methods: </strong>This new absolute laser Doppler velocimeter is combined with the adaptive optics fundus camera (rtx1, Imagine Eyes©,Orsay, France) outside its optical wavefront correction path. A 4 seconds recording includes 40 images, each synchronized with two Doppler shift power spectra. Image analysis provides the vessel diameter close to the probing beam and the velocity of the RBCs in the vessels are extracted from the Doppler spectral analysis. Combination of those values gives an average of the absolute retinal blood flow. An in vitro experiment consisting of latex microspheres flowing in water through a glass-capillary to simulate a blood vessel and in vivo measurements on six healthy human retinal venous junctions were done to assess the device.</p> <p><strong>Results: </strong>In the in vitro experiment, the calculated flow varied between 1.75 μl/min and 25.9 μl/min and was highly correlated (r2 = 0.995) with the imposed flow by a syringe pump. In the in vivo experiment, the error between the flow in the parent vessel and the sum of the flow in the daughter vessels was between −25% and 17% (mean±sd −2 ± 17%). Retinal blood flow in the main temporal retinal veins of healthy subjects varied between 1.3 μL/min and 28.7 μL/min</p> <p><strong>Conclusion: </strong>This adaptive optics LDV prototype (aoLDV) allows the measurement of absolute retinal blood flow derived from the retinal vessel diameter and the maximum RBCs velocity in that vessel.</p>
Dataset for: Reorganization of complex ciliary flows around regenerating Stentor coeruleus
<p><strong>We upload additional video files accompanying the article </strong><em>Reorganization of complex ciliary flows around rege</em><em>nerating Stentor coeruleus</em><strong>. </strong></p> <p>The first three videos are available as part of the journal ESM. (see https://dx.doi.org/10.6084/m9.figshare.c.4745069.) Files are in .mp4 format.</p> <p>suppvid1 - DIC imaging of flow fields around a regenerating <em>Stentor</em> (5.5 hrs post sucrose shock)<br> suppvid2 - High-speed video of linear membranellar band (6.5 hrs post sucrose shock)<br> suppvid3 - High-speed video of fully-regenerated membranellar band (8.5 hrs post sucrose shock)</p> <p>Example DIC videos showing regeneration dynamics. Videos are in raw .nd2 (Nikon NIS Elements) format (including embedded metadata). Note: very large files!</p> <p><strong>SDIC 1-6:</strong> DIC imaging of flow fields induced by the membranellar band cilia over the course of oral regeneration. </p> <p>Example high-speed videos showing regeneration dynamics.</p> <p><strong>SH1-5: </strong>high-speed imaging of membranellar band cilia dynamics over the course of oral regeneration, including sample from a control Stentor. </p> <p>Please contact the authors directly if you have any other questions about this data or the associated publication.</p>
Supporting dataset for manuscript "Age as a Diagnosis of Steady-state Flows in Shallow Rectangular Reservoirs"
<p>Supporting dataset for manuscript "Age as a Diagnosis of Steady-state Flows in Shallow Rectangular Reservoirs"</p>
Upscaling capillary pressure curves for numerical modeling of gravity-capillary driven flow
<p>This work investigates upscaling of capillary pressure curves for modeling gravity segregation under the influence of capillary heterogeneity. We consider two flowing phases driven by gravity and capillary forces and seek the saturation spatial and temporal variation until equilibrium is reached. Existing upscaling methods, found in the literature, are applied to a number of cases. Resulting saturation solutions are compared to fine-scale simulations and the different methods are evaluated, showing in general that the popular capillary limit method produces the best results. However, a large number of cases are found to have significant errors. This leads to the conclusion that existing methods are often inadequate. We therefore propose a new optimization-based upscaling method. Using this approach it is shown that capillary pressure can be upscaled to Brooks-Corey type functions and produce accurate upscaled simulations matching the fine-scale solutions. Optimization upscaling is computationally demanding and requires the fine-scale simulations for minimizing an objective function. However, it is shown that the upscaled curves are robust, i.e., they can be applied to different permeability realizations to calculate ensemble average saturation solutions.<br> </p>
Fig. 4 in Flowing into the unknown: inferred paleodrainages for studying the ichthyofauna of Brazilian coastal rivers
Fig. 4. Results of correlation tests: a. between the paleodrainage total area with contemporary land area encompassed by each paleodrainage (r2 = 0.99; P <0.0001); b. the number of contemporary basins encompassed by each paleodrainage (r2 = 0.17; P <0.0001); and c. between the contemporary land area and the area of the continental shelf exposed during the drop in sea level (r2 = 0.04; P = 0.01). Individual values per paleodrainages are given in Tab. 1.
Fig. 3 in Flowing into the unknown: inferred paleodrainages for studying the ichthyofauna of Brazilian coastal rivers
Fig. 3. Map of the 145 palaeodrainages inferred for a sea level retreat of -125 m during glacial periods of the Pleistocene; the black line marks the current coastline of Brazil. Both the area that includes the contemporary exposed land area, as well as the area of the continental shelf exposed when sea levels dropped (marked with stippling) is shown for each paleodrainage, with each paleodrainage shown in a different colour. Numbers along the coast indicate the paleodrainage ID on Tab. 1.
Fig. 1 in Flowing into the unknown: inferred paleodrainages for studying the ichthyofauna of Brazilian coastal rivers
Fig. 1. Map of the Brazilian coast showing main river drainages, bays, lagoons and mountain chains. Elevation and bathymetric profile for the area highlight the isolation of the coastal basins from inland rivers by mountains, including the Serra do Mar and the Chapada Diamantina in the west. Continental shelf exposed during the Pleistocene is marked with the stippled yellow shading.
Fig. 2 in Flowing into the unknown: inferred paleodrainages for studying the ichthyofauna of Brazilian coastal rivers
Fig. 2. Samples of some of the freshwater fish species of the Brazilian coastal drainages: a. Microglanis cottoides ((Boulenger, 1891) UFRGS 20930; 43.2 mm SL, standard length), b. Heptapterus sp. (UFRGS 20970; 89.2 mm SL), c. Phalloceros sp. (UFRGS 18596; 22 mm SL), d. Deuterodon singularis Lucena & Lucena, 1992 (UFRGS 20728; 59.6 mm SL), e. Scleromystax barbatus ((Quoy & Gaimard, 1824) UFRGS 18832; 65 mm SL), f. Pareiorhaphis splendens ((Bizerril, 1995) UFRGS 20971; 57.4 mm SL), g. Spintherobolus ankoseion Weitzman & Malabarba, 1999 (UFRGS 20923; 23.7 mm SL), h. Cyphocharax santacatarinae ((Fernández-Yépez, 1948) UFRGS 20918; 46.9 mm SL), i. Corydoras ehrhardti Steindachner, 1910 (UFRGS 20938; 50 mm SL), j. Mimagoniates lateralis ((Nichols, 1913) UFRGS 20488; 30.5 mm SL), k. Trichomycterus cf. cubataonis Bizerril, 1994 (UFRGS 20937; 30 mm SL), l. Parotocinclus maculicauda ((Steindachner, 1877) UFRGS 20932; 44.1 mmSL), m. Probolodus oyakawai Santos & Castro, 2014 (UFRGS 18752; 45 mm SL), n. Mimagoniates rheocharis Menezes & Weitzman, 1990 (UFRGS 20808; 54.2 mm SL), o. Geophagus brasiliensis ((Quoy & Gaimard, 1824)UFRGS 20919; 72.5 mm SL), p. Characidium pterostictum Gomes, 1947 (UFRGS 18563; 55 mm SL), q. Oligosarcus hepsetus ((Cuvier, 1829) UFRGS 18571; 65 mm SL), r. Atlantirivulus cf. luelingi ((Seegers, 1984) UFRGS 21033; 31.5 mm SL), s. Gymnotus pantherinus ((Steindachner, 1908) UFRGS 20928; 186 mm SL), and t. Pseudotothyris ignota Martins, Britski & Langeani, 2014 (UFRGS 20934; 33.2 mm SL). Photo credits: Tiago P. Carvalho.
Link to dataset related to article "Development, application and computational analysis of high-dimensional fluorescent antibody panels for single-cell flow cytometry"
<p>The interrogation of single cells is revolutionizing biology, especially our understanding of the immune system. Flow cytometry is still one of the most versatile and high-throughput approaches for single-cell analysis, and its capability has been recently extended to detect up to 28 colors, thus approaching the utility of cytometry by time of flight (CyTOF). However, flow cytometry suffers from autofluorescence and spreading error (SE) generated by errors in the measurement of photons mainly at red and far-red wavelengths, which limit barcoding and the detection of dim markers. Consequently, development of 28-color fluorescent antibody panels for flow cytometry is laborious and time consuming. Here, we describe the steps that are required to successfully achieve 28-color measurement capability. To do this, we provide a reference map of the fluorescence spreading errors in the 28-color space to simplify panel design and predict the success of fluorescent antibody combinations. Finally, we provide detailed instructions for the computational analysis of such complex data by existing, popular algorithms (PhenoGraph and FlowSOM). We exemplify our approach by designing a high-dimensional panel to characterize the immune system, but we anticipate that our approach can be used to design any high-dimensional flow cytometry panel of choice. The full protocol takes a few days to complete, depending on the time spent on panel design and data analysis.</p> <p> </p> <p> </p> <p>link related to dataset: https://flowrepository.org/id/FR-FCM-ZYV3</p>
Dataset for the article entitled "Macroalgal metabolism and lateral carbon flows can create significant carbon sinks"
<p>The dataset for the article entitled “Macroalgal metabolism and lateral carbon flows can create significant carbon sinks” by Watanabe et al., 2020</p>
Non-local Impacts of Gaps on Submerged Canopy Flow
<p>The folders include all the Vectrino measurements/records used for the paper, "Non-local Impacts of Gaps on Submerged Canopy Flow". Each folder has the the filtered data with the naming convention, '[gapsize]_[dist downstream]_[z(height from bed].mat'. There are separate folders for Set A and Set B experiments, which separate into the medium and fast flow speeds. There are homogenous measurements as well.</p>
COVID-19 Personal Protective Equipment by Patient Flow
<p>This process flow map outlines the Personal Protective Equipment usage rates per provider, per patient, and per procedure for all patients presenting for medical care.</p>
State estimation of surface and deep flows from sparse SSH observations of geostrophic ocean turbulence using Deep Learning
<p>This is a data repository in support of the publication "State estimation of surface and deep flows from sparse SSH observations of geostrophic ocean turbulence using Deep Learning" by Manucharyan et al. (2020), Journal of Advances in Modeling Earth Systems. The zipped file contains 10-day-separated snapshots of surface and deep ocean streamfunctions from the two-layer quasigeostrophic model of ocean turbulence. The included Python scripts demonstrate the efficacy of Deep Learning in temporal interpolation and state estimation given partial observations of the surface ocean turbulence.</p> <p> </p>
Clustering and kernel density estimation for assessment of measurable residual disease by flow cytometry
<p>Flow cytometry raw data and supplementary table S1.</p>
Experimental data and linear model for "Asymmetric internal tide generation in the presence of a steady flow"
<p>This dataset contain the experimental data, analyses, and linear model that are described in the manuscript</p> <p>"Asymmetric internal tide generation in the presence of a steady flow". submitted to Journal of Geophysical Research - Oceans.</p> <p>The folder data_density_fields_fluxes contains the experimental density fields (itXX/results/densityfields) and energy fluxes (itXX/results/fluxes) for the five experiments described in the manuscript: exp I (it17), exp II (it16), exp III (it15), exp IV (it13) and exp (V) (it 18).</p> <p>The Dossmannetal_wavesolution.m file is the linear model described in the manuscript for internal wave generation over a ridge.</p>
Experimental flows through an array of emerged or slightly submerged square cylinders over a rough bed
<p>The experimental dataset was collected in an 18 m long and1 m wide laboratory flume.<br> An urbanised floodplain is modelled. The bed is rough, modelled with dense artificial grass. An array of square cylinders, representing housemodels, was set on the rough bed. The cylinder immersion rate was varied: cylinders are emerged for three flow cases<br> H/k = 42%, 93% and 98% (H water depth and k obstacle height) and slightly submerged for H/k = 148%.<br> This dataset comprises water, velocities across the channel and between y/(L/2) = 5 to 7 (L = 14.3 cm) measured using an Acoustic Doppler Velocimetry with a side looking probe, and velocities in longitudinal-vertical planes measured using Particle Image Velocimetry.</p> <p>This data set is explained in detail the following article :<br> Oukacine, M., Proust, S., Larrarte, F. <em>et al.</em> Experimental flows through an array of emerged or slightly submerged square cylinders over a rough bed. <em>Sci Data</em> <strong>8, </strong>6 (2021). <a href="https://doi.org/10.1038/s41597-020-00791-w">https://doi.org/10.1038/s41597-020-00791-w</a></p>
Lagrangian particle dataset (2 years) for Agulhas region surface flow
<p>This is a .npz file containing the longitudes and latitudes of approximately 24,000 virtual Lagrangian particles (0.2 degree in longitude and latitude initial spacing) released on January 5, 2000 in the eastern South Atlantic Ocean and advected for 2 years. The data was used for the detection of finite-time coherent sets (Agulhas rings), see this <a href="https://github.com/OceanParcels/coherent_vortices_OPTICS">github repository</a> for the usage and this <a href="https://github.com/OceanParcels/near_surface_microplastic">github repository</a> for simulation details. Trajectories were simulated using OceanParcels (https://oceanparcels.org/), with surface currents derived from a NEMO-ORCA 006 run, available at http://opendap4gws.jasmin.ac.uk/thredds/nemo/root/catalog.html.</p>
Codes and datasets associated with the paper "Parameterizing the Energy Dissipation Rate in Stably Stratified Flows"
<p>Here, you will find some of the codes and datasets utilized in the article: "Parameterizing the Energy Dissipation Rate in Stably Stratified Flows". (<a href="https://arxiv.org/abs/2001.02255">https://arxiv.org/abs/2001.02255</a>)</p> <p>The direct numerical simulations were performed using the HERCULES code (<a href="https://github.com/friedenhe/HERCULES">https://github.com/friedenhe/HERCULES</a>). For all the simulations, the bulk Reynolds number is kept at 20,000. The bulk Richardson number is varied from 0.1 to 0.5. The zip files Re20000RiXX.zip contains the various turbulence statistics. </p> <p>Re20000Ri10: Ri_b = 0.1</p> <p>Re20000Ri20: Ri_b = 0.2</p> <p>Re20000Ri30: Ri_b = 0.3</p> <p>Re20000Ri40: Ri_b = 0.4</p> <p>Re20000Ri50: Ri_b = 0.5</p> <p>Every dat file (within the zip archives) is in ascii format and has 10 rows and 286 columns. Each row corresponds to normalized time (ranging from 1 to 10). Each column represents vertical model levels. </p> <p> </p>
Liquefied Natural Gas Phase III: Export Competition in a Well Supplied, Flow-Shifting Global Economy
<p>With trillions of cubic feet of shale reserves, the United States’ (US) abundance of natural gas has prompted an increase in production of Liquefied Natural Gas (LNG) as an export commodity. While the Trump administration has taken strides to loosen policy set by the Federal Energy Regulatory Commission (FERC) in order to streamline US LNG export facility permitting, UNOTI has reasoned that policies focused too heavily on LNG as an export is misguided. A more robust energy policy acknowledges the higher value of natural gas to the petrochemical manufacturing industries as well as the development and commercialization of new LNG technologies in the maritime industry, particularly as a marine fuel. Furthermore, US energy independence fueled by shale mining will alter how the US acts in the global market place, thereby destabilizing the system in place since the Bretton Woods Agreement in 1944. However, competing natural gas rich nations like Australia, Qatar, and Russia have similar goals to expand production indicating US LNG export growth will not be without competition. In addition to potential increases in US LNG exports and what this implies for global markets, this paper discusses current transportation developments in LNG powered marine vessel refueling technology allowing for waterside refueling as an alternative to shore side bunkering, as well as an overview of what increased US shale frac’ing and LNG export implies for US roadway infrastructure and how short sea shipping may provide an alternative to trucking and rail movements.</p>
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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.