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25 results for “particle transport”
Dataset accompanying the publication "Transport and retention of micro-Polystyrene in coarse riverbed sediments: Effects of flow velocity, particle and sediment sizes"
<p>The dataset in this repository is accompanying the publication "Transport and retention of micro-Polystyrene in coarse riverbed sediments: Effects of flow velocity, particle and sediment sizes" (in Microplastics and Nanoplastics, 2023, submitted 09.06.2023)</p> <p>The repository contains the raw image files of all sample filters which were scanned using the fluorescence imaging system ChemiDoc and used to analyse the infiltration behaviour of microplastic polystyrene in the manuscript. In addition, we provide the resulting data from the particle identification and geometric analysis which were derived from the raw data using ImageJ in tabular excel format. The data is structured in folders following the naming of the columns from the manuscript.</p>
MC particle transport simulations for the 2022 LET-measurements at DCPT: v1.0.0
Open the record for dataset details and reuse information.
FESOM model data and particle tracking data used in publication 'Cross-shelf transport of Barents Sea dense water as a sink for CO2 in the Arctic Ocean'
<p>FESOM model data and particle tracking data used in the paper 'Cross-shelf transport of Barents Sea dense water as a sink for CO2 in the Arctic Ocean" by Andreas Rogge at al.</p> <p>1) FESOM velocity fields averaged over the top 200 m water depth, averaged over the time period 2015-2018.</p> <p>2) FESOM transect at 95°E in the Arctic Ocean (temperature, salinity and velocity), averaged over the time period 2015-2018.</p> <p>3a) Particle back-tracking data based on daily FESOM velocity fields in netcdf format. Particles were released at 95°E every 14 days during the year 2018 and tracked until they reached the surface. Three different constant sinking velocities were used, representative for small and large non-ballasted particles and small ballasted particles.</p> <p>3b) Distribution of particles at the surface for the experiments with three different sinking velocities as mat files. </p>
Data from: Effects of soil particles and convective transport on dispersion and aggregation of nanoplastics via small-angle neutron scattering (SANS) and ultra SANS (USANS)
Terrestrial nanoplastics (NPs) pose a serious threat to agricultural food production systems due to the potential harm of soil-born micro- and macroorganisms that promote soil fertility and ability of NPs to adsorb onto and penetrate into vegetables and other crops. Very little is known about the dispersion, fate and transport of NPs in soils. This is because of the challenges of analyzing terrestrial NPs by conventional microscopic techniques due to the low concentrations of NPs and absence of optical transparency in these systems. Herein, we investigate the potential utility of small-angle neutron scattering (SANS) and Ultra SANS (USANS) to probe the agglomeration behavior of NPs prepared from polybutyrate adipate terephthalate, a prominent biodegradable plastic used in agricultural mulching, in the presence of vermiculite, an artificial soil. SANS with the contrast matching technique was used to study the aggregation of NPs co-dispersed with vermiculite in aqueous media. We determined the contrast match point for vermiculite was 66% D 2 O / 33% H 2 O. At this condition, the signal for vermiculite was ~50-100%-fold lower that obtained using neat H 2 O or D 2 O as solvent. According to SANS and USANS, smaller-sized NPs (50 nm) remained dispersed in water and did not undergo size reduction or self-agglomeration, nor form agglomerates with vermiculite. Larger-sized NPs (300-1000 nm) formed self-agglomerates and agglomerates with vermiculite, demonstrating their significant adhesion with soil. However, employment of convective transport (simulated by ex situ stirring of the slurries prior to SANS and USANS analyses) reduced the self-agglomeration, demonstrating weak NP-NP interactions. Convective transport also led to size reduction of the larger-sized NPs. Therefore, this study demonstrates the potential utility of SANS and USANS with contrast matching technique for investigating behavior of terrestrial NPs in complex soil systems.
Data of event list of cold and hot patches for manuscript "The Dependence of Cold and Hot Patches on Local Plasma Transport and Particle Precipitation in Northern Hemisphere Winter"
<p>A database of 4,634 cold patches (high density and low electron temperature) and 4,700 hot patches (high density and high electron temperature) from Defense Meteorological Satellite Program F16 in 2005-2018 winter months.</p>
Experiments on a single large particle segregating in bedload transport
<p>This depository contains all the data presented in "Experiments on a single large particle segregating in bedload transport" from H. Rousseau, J. Chauchat and P. Frey in Physical Review Fluids, as well as the code to read these data.</p> <p>There are 10 folders that each correspond to a configuration (i.e. size ratio and Shields number). These folders contain subfolders that correspond to the different repetitions we made for each configuration. In a subfolder, one can find:<br>- The first image of the experiment (t=0s).<br>- An hdf5 file called "bedAndWaterLines.h5" which contains the data for the waterline positions and the bedline positions with time.<br>- An hdf5 file called "frame_0_to_3000_with_step_1_and_shift_1.hdf5" which contains the granular bed velocity fields Ux and Uy interpolated over the time. These velocities have been obtained using the OpyFlow toolbox (https://github.com/groussea/opyflow.git).<br>- An hdf5 file called "DataTracked.h5" which contains the results from the detection of the intruder. Inside "DataTracked.h5", one can find one folder by timestep that includes the coordinates of the intruder. The total number of frame, the acquisition rate and the scale are also saved as datasets in "DataTracked.h5".</p> <p>The code "plotData.py" has been coded in python3 and allows one to read the data from the hdf5 files (make sure you installed the h5py package for python before). "plotData.py" is annotated and thus, it contains all the instructions to plot the data of a given repetition. It is based on the following classes:<br>- "LoadResult" that reads "DataTracked.h5"<br>- "loadWaterAndBed" that reads "bedAndWaterLines.h5"<br>- "readOpyf" that reads "frame_0_to_3000_with_step_1_and_shift_1.hdf5"</p> <p> </p> <p>The file "listRepetitions.ods" is also provided. It allows one to match a given experiment in the paper to its name in this depository.</p> <p>Do not hesitate to contact us if you need more info.</p>
Particle trajectories generated by the eDNA fate and transport model for the Atlantic bottlenose dolphin (Tursiops truncatus) -- Part I
<ul> <li>"release" includes particle trajectories generated by the eDNA fate and transport model, which was driven by the hydrodynamics simulated with the realistic wind and tidal forcings.</li> <li>The python codes used to read the particle trajectories and get the particle counts in each model grid cell can be found in https://github.com/Jilian0717/eDNA_fate_transport_model/tree/main/particle_density</li> </ul>
Particle trajectories generated by the eDNA fate and transport model for the Atlantic bottlenose dolphin (Tursiops truncatus) -- Part II
<ul> <li>"release_no_wind" includes particle trajectories generated by the eDNA fate and transport model, which was driven by the hydrodynamics simulated without wind forcing. The purpose is to diagnose the influence of wind on particle distributions.</li> <li>The python codes used to read the particle trajectories and get the particle counts in each model grid cell can be found in https://github.com/Jilian0717/eDNA_fate_transport_model/tree/main/particle_density</li> </ul>
Snow particle number, aerosol concentration and 10 meter windspeed data from MOSAiC, N-ICE, Weddel Sea expeditions and chemistry transport model data (p-TOMCAT) .
<p>The folder contains data for the MOSAiC, N-ICE and Weddell sea expedition for Snow particle counter measurements. Coarse aerosol measurements from the MOSAiC expedition are also included. Simulation data from a chemistry transport model (p-TOMCAT) is also available. This version includes both .mat and .nc files</p>
Data From: Active sinking particles: Flow and transport dynamics due to sessile suspension feeders on sinking aggregates
<p>Sinking or sedimentation of biological aggregates plays a critical role in carbon sequestration in the ocean and in vertical material fluxes in waste-water treatment plants. In both these contexts, the sinking aggregates are "active," since they are biological hot-spots and are densely colonized by microorganisms including bacteria and sessile protists, some of which generate feeding currents. However, the effect of these feeding currents on the sinking rates, trajectories, and mass transfer to these "active sinking particles," has not previously been studied. Here we use a novel scale-free vertical-tracking microscope (a.k.a. Gravity Machine, Krishnamurthy et al. "Scale-free vertical tracking microscopy." Nature Methods (2020)) to follow model sinking aggregates (agar spheres) with attached protists (<em>Vorticella convallaria</em>), sinking over long distances while simultaneously measuring local flows. We find that activity due to attached \vortc causes significant changes to the flow around aggregates in a dynamic manner and reshapes mass transport boundary layers. Furthermore, we find that activity-mediated local flows along with sinking modify the encounter and plume cross-sections of the aggregate and induce sustained aggregate rotations. Overall our work shows the important role of biological activity in shaping the near-field flows around aggregates with potentially important effects on aggregate fate and material fluxes.</p>
The Effects of Dapagliflozin on HDL Particles Subtypes and Reverse Cholesterol Transport in Type 2 Diabetic Patients
ClinicalTrials.gov study NCT02327039. IPD Sharing: Not stated. Countries: 1. Publications: 2.
Data From: Active sinking particles: Flow and transport dynamics due to sessile suspension feeders on sinking aggregates
Open the record for dataset details and reuse information.
Data from: Effects of soil particles and convective transport on dispersion and aggregation of nanoplastics via small-angle neutron scattering (SANS) and ultra SANS (USANS)
Open the record for dataset details and reuse information.
Research data supporting article on "Language and Design Evolution of the OpenMC Monte Carlo Particle Transport Code"
<p>This file contains an archive of all research data that supports the article on "Language and Design Evolution of the OpenMC Monte Carlo Particle Transport Code".</p>
Controls over particle motion and resting times of coarse bed load transport in a glacier-fed mountain stream
<p>Field data bedload monitorning in the Estero Morales</p>
Breakthrough curves under variable saturation conditions to explore the effects of particle size and charge density on the transport of nanoplastic particles through sand
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Wind Energetic Particle Acceleration, Composition and Transport (EPACT)/LEMT 1-Hr Omnidirectional Fluxes
This dataset contains hourly-averaged omnidirectional fluxes for He, C, O, Ne, Si, and Fe in particles/cm2-sr-s-MeV/nuc in seven energy bins (six for Ne) in the general range of 2-10 MeV/nucleon. The error bars are statistical only, that is, corresponding to sqrt(N), where N is the number of collected ions. For intervals in which zero ions were observed, the error bar corresponds to one ion. ASCII listing generated from this link provide the start-time of the averaging interval as YYYY DD HH, followed by pairs of numbers giving the flux and its uncertainty from the selected intervals. The available energy ranges for bins bby species are:+----------------------------------------------------------------------------------------------+| Species | Band 1 | Band 2 | Band 3 | Band 4 | Band 5 | Band 6 | Band 7 ||----------------------------------------------------------------------------------------------|| He | 2.00-2.40 | 2.40-3.00 | 3.00-3.70 | 3.70-4.53 | 4.53-6.00 | 6.00-7.40 | 7.40-9.64 || C | 2.57-3.19 | 3.19-3.85 | 3.85-4.80 | 4.80-5.80 | 5.80-7.20 | 7.20-9.10 | 9.10-13.70 || O | 2.56-3.17 | 3.17-3.88 | 3.88-4.68 | 4.68-6.00 | 6.00-7.40 | 7.40-9.20 | 9.20-13.40 || Ne | 3.27-3.98 | 3.98-4.72 | 4.72-5.92 | 5.92-7.87 | 7.87-9.96 | 9.96-12.7 | || Si | 2.50-3.20 | 3.20-4.00 | 4.00-4.90 | 4.90-6.00 | 6.00-7.90 | 7.90-9.70 | 9.70-13.60 || Fe | 2.40-3.00 | 3.00-3.95 | 3.95-4.80 | 4.80-5.90 | 5.90-7.80 | 7.80-9.30 | 9.30-12.50 |+----------------------------------------------------------------------------------------------+
Wind Energetic Particle Acceleration, Composition and Transport (EPACT)/LEMT 5-min Omnidirectional Fluxes
This dataset contains 5-min omnidirectional fluxes for He, C, O, Ne, Si, and Fe in particles/cm2-sr-s-MeV/nuc in seven energy bins (six for Ne) in the general range of 2-10 MeV/nucleon. The error bars are statistical only, that is, corresponding to sqrt(N), where N is the number of collected ions. For intervals in which zero ions were observed, the error bar corresponds to one ion. ASCII listing generated from this link provide the start-time of the averaging interval as YYYY DD HH, followed by pairs of numbers giving the flux and its uncertainty from the selected intervals. The available energy bins for the species are:+----------------------------------------------------------------------------------------------+| Species | Band 1 | Band 2 | Band 3 | Band 4 | Band 5 | Band 6 | Band 7 ||----------------------------------------------------------------------------------------------|| He | 2.00-2.40 | 2.40-3.00 | 3.00-3.70 | 3.70-4.53 | 4.53-6.00 | 6.00-7.40 | 7.40-9.64 || C | 2.57-3.19 | 3.19-3.85 | 3.85-4.80 | 4.80-5.80 | 5.80-7.20 | 7.20-9.10 | 9.10-13.70 || O | 2.56-3.17 | 3.17-3.88 | 3.88-4.68 | 4.68-6.00 | 6.00-7.40 | 7.40-9.20 | 9.20-13.40 || Ne | 3.27-3.98 | 3.98-4.72 | 4.72-5.92 | 5.92-7.87 | 7.87-9.96 | 9.96-12.7 | || Si | 2.50-3.20 | 3.20-4.00 | 4.00-4.90 | 4.90-6.00 | 6.00-7.90 | 7.90-9.70 | 9.70-13.60 || Fe | 2.40-3.00 | 3.00-3.95 | 3.95-4.80 | 4.80-5.90 | 5.90-7.80 | 7.80-9.30 | 9.30-12.50 |+----------------------------------------------------------------------------------------------+
Wind Energetic Particle Acceleration Composition Transport (EPACT) SupraThermal Energetic Particle Telescope (STEP) Differential, Directional Hydrogen Fluxes, 10 min Data
The EPACT Instrument on Wind STEP - SupraThermal Energetic Particle Telescope measures Ion Fluxes of Protons (H) in 0.12.5 MeV Energy Range and He-Fe Nuclei in the ~0.032 MeV/nucleon Energy Ranges in two identical Telescopes, each with a Geometrical Factor of 0.4 cm^2 sr and a rectangular Field of View with an Angular Acceptance of 44° in Azimuth and 17° in Polar Angle.
Wind Energetic Particle Acceleration Composition Transport (EPACT) SupraThermal Energetic Particle Telescope (STEP) Differential, Directional Iron Fluxes, 10 min Data
The EPACT Instrument on Wind STEP - SupraThermal Energetic Particle Telescope measures Ion Fluxes of Protons (H) in 0.12.5 MeV Energy Range and He-Fe Nuclei in the ~0.032 MeV/nucleon Energy Ranges in two identical Telescopes, each with a Geometrical Factor of 0.4 cm^2 sr and a rectangular Field of View with an Angular Acceptance of 44° in Azimuth and 17° in Polar Angle.
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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.