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5,371 results for “Flow”
Merging Flow Synthesis and Enzymatic Maturation to Expand the Chemical Space of Lasso Peptides
<p>LC-MS, UHPLC, and LC-IM-MS data of the corresponding publication</p>
A method to determine local aerodynamic force coefficients from fiber-resolved 3D flow simulations around a staple fiber yarn: simulation data
<p>This data set contains all set-up files and necessary scripts to run the simulations performed in the publication <a href="https://doi.org/10.1007/s11044-024-09992-2" target="_blank" rel="noopener">"A method to determine local aerodynamic force coefficients from fiber-resolved 3D flow simulations around a staple fiber yarn"</a>, published in Multibody System Dynamics.</p>
High-pressure flow digestion system
<p><span>Buildup of the presented high-pressure flow-through microwave-assisted digestion system. The gray shaded components including the digestion vessel indicate the pressurized part. The counter-current nitrogen stream enters the digestion system at the nitrog</span>en inlet port/ sample exit port and leaves the system at the pressure interface. (A, H) nitric acid 5% (v/v) rinsing solution, (B) sample (1% (w/w) wine), (C) waste (D) digested sample, (E) precision dispenser, (F) six-port high performance valve, (G) sample loop, (I) Knauer HPLC pump, (J) pressure interface including the nitrogen exit port, (K) cooling unit, (L) high pressure vessel, (M) magnetron, (N) nitrogen inlet port/ sample exit port, (O) pressure restriction loop</p>
Data from: A geometric VOF method for interface flow simulations
<p>This set is the original data used in the article titled "A Geometric VOF Method for Interface Flow Simulations". In this paper, a novel numerical technique designed for interface flow simulations using the Volume of Fluid (VOF) method on arbitrary unstructured meshes has been introduced. The method is called SimPLIC, which seamlessly integrates Piecewise Linear Interface Calculation (PLIC) and Simpson's rule. The main focus of the proposed method is to compute the volume of the primary phase that moves across a mesh face within a single time step. This is achieved by reconstructing the interface and assessing how the submerged face area evolves over time. Simpson's rule is employed to integrate the time evolution of this submerged face area, ensuring an accurate estimation of the volume of the transported primary phase. The method's robustness was validated by solving a spherical interface advection problem in a non-uniform three-dimensional flow across unstructured meshes with diverse cell types and dimensions. Key metrics such as volume conservation, shape retention, friction boundedness and solving efficiency were meticulously monitored and juxtaposed. Numerical outcomes underscored the precision and adequacy of the PLIC-VOF technique when complemented with Simpson's rule in advecting the interface. Furthermore, the SimPLIC method has been integrated into OpenFOAM v2312 as an unofficial extension and is now accessible to the community.</p>
Fig. 3 in Transportation of microplastic during high-flow and low-flow seasons in southeastern Black Sea: A modelling approach
Fig. 3 — Snapshots of microplastic distribution on southeastern Black Sea in high-flow (S1, S2, and S3) and low-flow (S4, S5, and S6)
TIGAR experiments with background flow and Rossby wave forcing
<p>A barotropic version of the TIGAR (Transient Inertia-Gravity And Rossby wave dynamics) model has been run at T42 resolution to simulate the effects of subtropical Rossby waves on equatorial waves in the presence of a zonal background flow. TIGAR solves the rotating shallow water equations by applying Hough harmonics as spectral basis functions thereby enabling the analysis of Rossby and Inertia-gravity wave dynamics. More details of the model are available at: <a href="https://doi.org/10.1002/qj.4006">https://doi.org/10.1002/qj.4006</a> .</p>
Dataset: Amplify Cash Flow High Income ETF (HCOW) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Dataset: Amplify Cash Flow Dividend Leaders ETF (COWS) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Dataset: Victoryshares Free Cash Flow ETF (VFLO) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Dataset: Themes US Cash Flow Champions ETF (USCF) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Dataset: Themes US Small Cap Cash Flow Champions ETF (SMCF) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Dataset: Victoryshares Small Cap Free Cash Flow ETF (SFLO) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Dataset: Invesco Nasdaq Free Cash Flow Achievers ETF (QOWZ) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Drag, lift, and torque correlations for axi-symmetric rod-like non-spherical particles in linear wall-bounded shear flow
<p><strong>Data linked to the manuscript: </strong><br><em>Drag, lift, and torque coefficients of fixed axi-symmetric rod-like particles in linear wall-bounded shear flow</em></p> <p><strong>Authors:</strong><br>Victor Cheron, Berend van Wachem</p> <p>Corresponding author:<br>Berend.van.Wachem@gmail.com</p> <p><strong>Files</strong><br>Temporally averaged drag, lift and torque coefficients are written in .txt files stored in the folder ResultsCoefficients.<br>Python scripts used to plot the correlations are stored in the folder PythonScript.<br>Two simulation results are provided in the folder SimulationResults.</p> <p><strong>Results and Coefficients</strong></p> <p>The .txt files are split per coefficient, aspect ratio and shear rate, which can be identified by the name of the .txt file.<br>The results obtained for the torque coefficient of the particle of aspect ratio 2.5 for a uniform flow configuration are given in the file:<br><em>Uniform-Torque-Angles-Size2-5.txt</em></p> <p>The results obtained for the lift coefficient of the particle of aspect <br>ratio 10 for a shear rate 0.2 configuration are given in the file:<br><em>Shear02-Lift-Angles-Size10.txt</em></p> <p>In the files, the results are ordered per orientation angle and particle Reynolds number. </p> <p><strong>PythonScripts</strong></p> <p>The python scripts are split among three files:<br>- Getter.py: this script reads the .txt files storing the coefficients.<br>- ManuscriptCorrelations.py : this script returns the functions to read plot the correlations for the drag, lift and torque coefficients.<br>- generalmain.py : calls the functions</p> <p>The scripts Getter.py and ManuscriptCorrelations.py are called from the script generalmain.py file. <br>This will return a 1D column vector ordering the variables used to derive the<br>correlations:<br>- Coefficients<br>- Reynolds number<br>- Orientation Angle<br>- Dimensionless distance to the wall<br>- Aspect ratio</p> <p><strong>Simulation Results</strong></p> <p>A simulation result is provided:<br>- Aspect ratio 5, particle Reynolds number 100, orientation angles 30 and 150,<br> dimensionless distance 1.</p> <p>The data of all fields (pressure, velocity, source terms from the particles) are stored in .h-files.</p> <p>A .xmf reader is provided to read the simulation results in Paraview.</p> <p>Data for one converged simulation time are provided due to storage limits.</p> <p> </p> <p><strong>Acknowledgments</strong><br>This research was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) - Project-ID 448292913 and by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) - Project-ID 422037413 - TRR 287.</p>
Discrete Flow Cytometry of Underway Samples From TN428 Using a BD Influx Cell Sorter
<p>The dataset consists of BD Influx-based analysis of phytoplankton populations from discrete flow cytometry data collected underway during a transit cruise (TN428) from American Samoa to Australia. The data consists of cell abundance, cell size (equivalent spherical diameter), carbon quota, and carbon biomass for picophytoplankton populations, namely the cyanobacteria Prochlorococcus, Synechococcus and Crocosphaera, and small eukaryotic phytoplankton (<5 μm ESD). Time is in UTC format, latitude and longitude are in decimal degrees, and depth is in meters. Further information can be found here: [https://github.com/fribalet/FCSplankton](https://github.com/fribalet/FCSplankton)</p>
FIGURE S4. The production flow for a in The challenge of hard-to-reach spaces in mechanical fossil preparation: Development of the Wada air scribe, a novel short-bodied air scribe with an adjustable handle
FIGURE S4. The production flow for a bushing. Schematic diagrams in lateral (upper row) and front (middle row) views and cross-sections (lower row) are shown.
FIGURE S3. The production flow for a in The challenge of hard-to-reach spaces in mechanical fossil preparation: Development of the Wada air scribe, a novel short-bodied air scribe with an adjustable handle
FIGURE S3. The production flow for a cylinder. Schematic diagrams in lateral (upper row) and front (lower row) views are shown.
FIGURE S2. The production flow for a in The challenge of hard-to-reach spaces in mechanical fossil preparation: Development of the Wada air scribe, a novel short-bodied air scribe with an adjustable handle
FIGURE S2. The production flow for a junction. Schematic diagrams in lateral view (upper row) and crosssections (lower row) are shown.
Replication data for: Bilateral flows and rates of international migration of scholars for 210 countries and areas for the period 1998-2020
<h3>Data and code for performing analyses and plotting figures for "Bilateral flows and rates of international migration of scholars for 210 countries and areas for the period 1998-2020"</h3> <p>The code and data can also be found at https://github.com/MPIDR/Global-flows-and-rates-of-international-migration-of-scholars/</p> <p><strong>Abstract</strong>: A lack of comprehensive migration data is a major barrier for understanding the causes and consequences of migration processes, including for specific groups like high-skilled migrants. We leverage large-scale bibliometric data from Scopus and OpenAlex to trace the global movements of scholars. Based on our empirical validations, we develop pre-processing steps and offer best practices for the measurement and identification of migration events. We have prepared a publicly accessible dataset that shows a high level of correlation between the counts of scholars in Scopus and OpenAlex for most countries. Although OpenAlex has more extensive coverage of non-Western countries, the highest correlations with Scopus are observed in Western countries. We share aggregated yearly estimates of international migration rates and of bilateral flows for 210 countries and areas worldwide for the period 1998-2020 and describe the data structure and usage notes. We expect that the publicly shared dataset will enable researchers to further study the causes and the consequences of migration of scholars to forecast the future mobility of global academic talent.</p>
Fig. 5 in Application of the physical habitat simulation for fish species to assess environmental flows in an Atlantic Forest Stream in South-eastern Brazil
Fig. 5. Average habitat suitability index –HSI– in the upper and lower reach of the riacho São Pedro, for the three fish species.
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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.