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2,194 results for “Diffusers”
Data to reproduce: Cultural diffusion dynamics depend on behavioral production rules
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Response of Lake Baikal periphyton to nutrient enrichment at 10 sites across a land use gradient: Results from a nutrient diffusing substrata (NDS) experiment
This data set contains results of a study on the response of benthic algae to experimental nutrient enrichment in the nearshore of Lake Baikal, Russia. Nutrient diffusing substrata (NDS) were deployed at 10 sites across a land-use gradient (from town to forested) during August to September of 2015 . Four NDS treatments were used at each site: 'control', 'added phosphorus', 'added nitrogen' and 'added nitrogen and phosphorus'. NDS tiles were left in the lake for 32-33 days. After retrieval, benthic chlorophyll a levels from all sites were analyzed as an index of periphyton biomass (data in file periphyton_chl_a.csv). Taxonomic identification of algae was done at 4 of the 10 sites (2 developed, 2 undeveloped); cell counts are presented in file 'periphyton_abundance.csv'; biovolumes were determined for the most common taxa and are presented in file 'periphyton_biovolume.csv'.
Mapping of nanoparticles diffusion in cells
<p>We mapped the diffusion of particles in the cytoplasm. To do so, we electroporated QDs-SB particles in cells as shown in Debayle et al 2019. Here we were using RPE1 cells. We present the recording of three cells and the scripts that we used to generate some maps of diffusion in the cell.</p> <p>The scripts were made to use the output tracks from Slimfast 1.103e but can be adapted by changeing the beginning of the script.</p> <p>Some functions were found in Matlab Central and their corresponding license is in their respective folders.</p>
Diffusion of nanoparticles in the cell cytoplasm
<p>In Etoc 2018, we presented the diffusive behavior inside the cytosol of living cells for different kind of nanometric sized nanoparticles. We showed that the passivation of the particles is the main parameter that regulate the diffusion properties of particles smaller than 70nm not only in Hela cells but also in RPE1 and MSC cells.</p> <p>Here we open the data for the MSC cells.</p> <p>Experiments consists in the recording of small subregions of the cytoplasm located at the periphery of the cell.</p> <p>A README file is included in the archive with the recording parameters.</p> <p>DATA were recorded by Elie BALLOUL</p> <p>Scripts were written by Mathieu COPPEY, Fred ETOC and modified by Elie BALLOUL.(to use polyfit instead of ezyfit)</p> <p>We also make available the scripts that we used to generate the maps.</p> <p>Some functions were found in Matlab Central and their corresponding license is in their respective folders.</p>
The Plasma Distribution in Saturn's Inner Magnetosphere from 2.4 to 10 Rs: A Diffusive Equilibrium Model
<p>This is the supporting data set for the paper by the same title published in AGU JGR Space Physics, <a href="https://doi.org/10.1029/2019JA027545">10.1029/2019JA027545</a></p> <p>Abstract:</p> <p>Electron density measurements have been obtained by the Cassini Radio and Plasma Wave Science (RPWS) instrument covering the period from 30 June, 2004 to 19 April, 2017, spanning latitudes up to ~30<sup>o </sup>and <em>L</em> values from 2.4 to 10. Near the F ring, electron densities are derived from RPWS measurements of electron plasma oscillations at high latitudes and from the Langmuir Probe (RPWS/LP) sweep data at low latitudes. The electron density measurements from the ring-grazing orbits, beginning in December 2016, have made it possible to extend the work of a previous diffusive equilibrium model to include the distribution of the ring plasma. Beyond the ring-grazing orbits, the densities are derived from RPWS measurements of the upper hybrid resonance frequency. These density measurements are used to anchor the fit of an expanded diffusive equilibrium density model for a two-species plasma consisting of water group and hydrogen ions in Saturn’s inner magnetosphere. Density contour plots for the two ion species and the electrons are presented. The distribution of the derived plasma densities is consistent with two primary sources, the Enceladus plumes and the extended ring atmosphere. There is also an indication of a weaker plasma source at Dione. In the region just outside the A Ring and in the region including the Enceladus orbit, the diffusive equilibrium model also clearly shows the expansion of lighter ions and electrons to higher latitudes along the magnetic field lines with evidence of a weaker plasma expansion between the orbits of Tethys and Dione.</p>
Data base for Re(VII) diffusion in compated montmorillonite, Na-bentonite and illite/smectite mixed layer
<p>The diffusion behavior of Re(VII) in compacted montmorillonite, Na-bentonite and illite/smectite mixed layer was investigated by a through-diffusion method and a pore-scale modeling. Donnan and a multi-porosity modeling were employed to compare with the pore-scale modeling, which can capture the overlapped electrical double layer. This dataset contains a through-diffusion experimental data and simulations data, which is calculated byincluding a pore-scale modeling, Donnan theory and a multi-porosity modeling.</p>
Data Files for PyGDSM: Python interface to the Global Diffuse Sky Model
<p>HDF5 data files for PyGDSM: Python interface to Global Diffuse Sky Models</p> <p>PyGDSM is a Python interface for the Global Diffuse Sky Models (GDSM ascl:1011.010). GDSM are models of diffuse galactic radio emission, constructed from a variety of all-sky surveys spanning the radio band (e.g. Haslam and WMAP). PyGDSM uses the Global Sky Model (GSM2008) of <a href="http://onlinelibrary.wiley.com/doi/10.1111/j.1365-2966.2008.13376.x/abstract">Oliveira-Costa et. al., (2008)</a>, <a href="http://arxiv.org/abs/1605.04920">Zheng et. al., (2016)</a> model GSM2016, and <a href="https://lda10g.alliance.unm.edu/LWA1LowFrequencySkySurvey/">LWA1 Low Frequency Sky Model</a> (LFSM). The PyGDSM module provides visualization utilities, file output in FITS format, and the ability to generate observed skies for a given location and date. PyGDSM requires <a href="https://healpy.readthedocs.org/en/latest/">Healpy</a>, PyEphem (ascl:1112.014), and AstroPy (ascl:1304.002).</p>
Hampering Effect of Wave-Driven Turbulence on Advection Speed and Diffusion Rate of Pollutants: A Large Eddy Simulation Study
<p>The source codes and namelist files are prepared to reproduce the results of the study entitled 'Hampering Effect of Wave-Driven Turbulence on Advection Speed and Diffusion Rate of Pollutants: A Large Eddy Simulation Study'. Download the originial source codes for the Parallelized LES model (PALM) at <a href="https://palm.muk.uni-hannover.de">https://palm.muk.uni-hannover.de</a> and use the source codes provided here as 'user-defined code' in PALM.</p> <p>The data can be used to reproduce the figures of the scientific article named after the study.</p>
The Effects of Upper-Hybrid Waves on Energy Conversion in the Electron Diffusion Region
<p>The data from the simulations of upper-hybrid waves near the electron diffusion region. </p> <p>Read 'note.txt' for the description about the data. </p>
Data from: Effects of fluorescent glutamate indicators on neurotransmitter diffusion and uptake
Genetically encoded fluorescent glutamate indicators (iGluSnFRs) enable neurotransmitter release and diffusion to be visualized in intact tissue. Synaptic iGluSnFR signal time courses vary widely depending on experimental conditions, often lasting 10-100 times longer than the extracellular lifetime of synaptically released glutamate estimated with uptake measurements. iGluSnFR signals typically also decay much more slowly than the unbinding kinetics of the indicator. To resolve these discrepancies, here we have modeled synaptic glutamate diffusion, uptake and iGluSnFR activation to identify factors influencing iGluSnFR signal waveforms. Simulations suggested that iGluSnFR competes with transporters to bind synaptically released glutamate, delaying glutamate uptake. Accordingly, synaptic transporter currents recorded from iGluSnFR-expressing astrocytes in mouse cortex were slower than those in control astrocytes. Simulations also suggested that iGluSnFR reduces free glutamate levels in extrasynaptic spaces, likely limiting extrasynaptic receptor activation. iGluSnFR and lower-affinity variants nonetheless provide linear indications of vesicle release, underscoring their value for optical quantal analysis.
Noninvasive quantification of axon radii using diffusion MRI
<p>Axon size plays a crucial role in determining conductance velocity and, consequently, in the the timing and synchronization of neural activation. Noninvasive measurement of axon radii could have significant impact on the understanding of healthy and diseased neural processes. However, until now, accurate axon radius mapping has eluded in vivo neuroimaging, mainly due to a lack of sensitivity of the MRI signal to micron-sized axons. Here, we show how -- when confounding factors such as extra-axonal water and axonal orientation dispersion are eliminated -- heavily diffusion-weighted MRI signals becomes sensitive to axon radii. However, diffusion MRI is only capable of estimating a single metric representing the entire axon radius distribution within a voxel that emphasizes the largest axons. Our findings, both in rodents and humans, enable noninvasive mapping of critical information on axon radii, as well as resolve the long-standing debate on whether axon radii can be quantified.</p>
Data for "A Generalized Mixing Length Closure for Eddy-Diffusivity Mass-Flux Schemes of Turbulence and Convection"
<p>This folder contains the data used in the publication: </p> <p>Lopez-Gomez, I., Cohen, Y., He, J., Jaruga, A., Schneider, T., 2020: A Generalized Mixing Length Closure for Eddy-Diffusivity Mass-Flux Schemes of Turbulence and Convection, Journal of Advances in Modeling Earth Systems.</p> <p>If you make use of this data in your work, please cite our paper when doing so.</p>
Data from: Detecting and quantifying social transmission using network-based diffusion analysis
<p>1. Although social learning capabilities are taxonomically widespread, demonstrating that freely interacting animals (whether wild or captive) rely on social learning has proved remarkably challenging.</p> <p>2. Network-based diffusion analysis (NBDA) offers a means for detecting social learning using observational data on freely interacting groups. Its core assumption is that if a target behaviour is socially transmitted, then its spread should follow the connections in a social network that reflects social learning opportunities.</p> <p>3. Here, we provide a comprehensive guide for using NBDA. We first introduce its underlying mathematical framework and present the types of questions that NBDA can address. We then guide researchers through the process of: selecting an appropriate social network for their research question; determining which NBDA variant should be used; and incorporating other variables that may impact asocial and social learning. Finally, we discuss how to interpret an NBDA model's output and provide practical recommendations for model selection.</p> <p>4. Throughout, we highlight extensions to the basic NBDA framework, including incorporation of dynamic networks to capture changes in social relationships during a diffusion and using a multi-network NBDA to estimate information flow across multiple types of social relationship.</p> <p>5. Alongside this information, we provide worked examples and tutorials demonstrating how to perform analyses using the newly developed NBDA package written in the R programming language.</p>
Transition from Light Diffusion to Localization in Three-Dimensional Amorphous Dielectric Networks near the Band Edge
<p>Data files and codes to generate all data considered in "Transition from Light Diffusion to Localization in Three-Dimensional Amorphous Dielectric Networks near the Band Edge", J. Haberko, L.S. Froufe-Perez, and F. Scheffold, Nature Communications 2020. DOI: 10.1038/s41467-020-18571-w</p>
Data from: Sleep, inflammation, and cognitive behavior of aged wild-type mice subjected to diffuse brain injury and aged 3xTg-AD mice as a model of Alzheimer's disease
<p>Identifying differential responses between sexes following traumatic brain injury (TBI) can elucidate the mechanisms behind disease pathology. Peripheral and central inflammation in the pathophysiology of TBI can increase sleep in male rodents, but this remains untested in females. We hypothesized that diffuse TBI would increase inflammation and sleep in males more so than in females. Diffuse TBI was induced in C57BL/6J mice and serial blood samples were collected (baseline, 1, 5, 7 days post‐injury [DPI]) to quantify peripheral immune cell populations and sleep regulatory cytokines. Brains and spleens were harvested at 7DPI to quantify central and peripheral immune cells, respectively. Mixed‐effects regression models were used for data analysis. Female TBI mice had 77%–124% higher IL‐6 levels than male TBI mice at 1 and 5DPI, whereas IL‐1β and TNF‐α levels were similar between sexes at all timepoints. Despite baseline sex differences in blood‐measured Ly6Chigh monocytes (females had 40% more than males), TBI reduced monocytes by 67% in TBI mice at 1DPI. Male TBI mice had 31%–33% more blood‐measured and 31% more spleen‐measured Ly6G+ neutrophils than female TBI mice at 1 and 5DPI, and 7DPI, respectively. Compared with sham, TBI increased sleep in both sexes during the first light and dark cycles. Male TBI mice slept 11%–17% more than female TBI mice, depending on the cycle. Thus, sex and TBI interactions may alter the peripheral inflammation profile and sleep patterns, which might explain discrepancies in disease progression based on sex.</p>
Figures and datasets of paper titled "Phosphorous diffusion gettering of trapping centers in upgraded metallurgical-grade solar silicon"
<p>Datasets and figures of paper titled "Phosphorous Diffusion Gettering of Trapping Centers in Upgraded Metallurgical-Grade Solar Silicon" published in arXiv (<a href="http://arxiv.org/abs/2101.07145">http://arxiv.org/abs/2101.07145</a>)</p>
Data for the article "Commensurability between element symmetry and the number of skyrmions governing skyrmion diffusion in confined geometries"
<p>Data for the article "Commensurability between element symmetry and the number of skyrmions governing skyrmion diffusion in confined geometries" (<a href="https://arxiv.org/abs/2009.03995">[2009.03995] Commensurability governing skyrmion diffusion in confined geometries (arxiv.org)</a>)</p>
Impact of Clean Energy on CO2 Emissions and Economic Growth within the Phases of Renewables Diffusion in Selected European Countries
<p>This study explores the impact of clean energy and non-renewable energy consumption on CO<sub>2</sub> emissions and economic growth within two phases (formative and expansion) of renewable energy diffusion for three selected countries (France, Spain, and Sweden). The vector autoregression (VAR) model is estimated on the basis of annual data disaggregated into quarterly data. The Granger causality results reveal distinctive differences in the causality patterns across countries and two phases of renewables diffusion. Clean energy consumption contributes to a decline of emissions more clearly in the expansion phase in France and Spain. However, this effect seems to be counteracted by the increases in emissions due to economic growth and non-renewable energy consumption. Therefore, clean energy consumption has not yet led to a decoupling of economic growth from emissions in France and Spain; in contrast, the findings for Sweden evidence such a decoupling due to the neutrality between economic growth and emissions. Generally, the findings show that despite the enormous growth of renewables and active mitigation policies, CO<sub>2</sub> emissions have not substantially decreased in selected countries or globally. Focused and coordinated policy action, not only at the EU level but also globally, is urgently needed to overhaul existing fossil-fuel economies into low-carbon economies and ultimately meet the relevant climate targets.</p>
Dataset for "Verifying Monte Carlo simulations of diffusion tensor cardiovascular magnetic resonance using a finite volume method"
<p>This dataset contains the results of random walk and finite volume simulations of diffusion in cardiac tissue. The data was used for the work presented at the 8th World Congress of Biomechanics in 2018.</p>
Elemental vacancy diffusion database from high-throughput first-principles calculations for fcc and hcp structures
<p><br /> This work demonstrates how databases of diffusion-related properties can be developed from high-throughput ab initio calculations. The formation and migration energies for vacancies of all adequately stable pure elements in both the face-centered cubic (fcc) and hexagonal close packing (hcp) crystal structures were determined using ab initio calculations. For hcp migration, both the basal plane and z-direction nearest-neighbor vacancy hops were considered. Energy barriers were successfully calculated for 49 elements in the fcc structure and 44 elements in the hcp structure. These data were plotted against various elemental properties in order to discover significant correlations. The calculated data show smooth and continuous trends when plotted against Mendeleev numbers. The vacancy formation energies were plotted against cohesive energies to produce linear trends with regressed slopes of 0.317 and 0.323 for the fcc and hcp structures respectively. This result shows the expected increase in vacancy formation energy with stronger bonding. The slope of approximately 0.3, being well below that predicted by a simple fixed bond strength model, is consistent with a reduction in the vacancy formation energy due to many-body effects and relaxation. Vacancy migration barriers are found to increase nearly linearly with increasing stiffness, consistent with the local expansion required to migrate an atom. A simple semi-empirical expression is created to predict the vacancy migration energy from the lattice constant and bulk modulus for fcc systems, yielding estimates with errors of approximately 30%.</p> <p>Files:</p> <p>figure_excel_files.zip:</p> <p>Excel files for figures in the publication, and excel files of main data tables for FCC and HCP vacancy formation energies and vacancy migration energies.</p> <p>fcc_hvf_hvm.tar.gz and hcp_hvf_hvm.tar.gz:</p> <p>Raw VASP files corresponding to FCC and HCP vacancy formation energies and vacancy migration energies.<br /> <br /> bulk_modulus.tar.gz:</p> <p>Raw VASP files corresponding to FCC bulk modulus calculations.<br /> </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.