Find research datasets worth reusing

Dataset for the paper "Electrochemical and Spectroscopic Characterisation of Organic Molecules with High Positive Redox Potentials for Energy Storage in Aqueous Flow Cells", DOI:10.1039/d4ya00366g

<table> <tbody> <tr> <td>The data in this spreadsheet was used to produce the figures in the paper</td> </tr> <tr> <td>Authors:</td> <td>Christopher G. Cannon, Peter A. A. Klusener, Nigel P. Brandon, and Anthony R. J. Kucernak</td> </tr> <tr> <td>Title:</td> <td>Electrochemical and Spectroscopic Characterisation of Organic Molecules with High Positive Redox Potentials for Energy Storage in Aqueous Flow Cells</td> </tr> <tr> <td>Journal:</td> <td>Energy Advances</td> </tr> <tr> <td>DOI:</td> <td>DOI:10.1039/d4ya00366g</td> </tr> <tr> <td>Please cite the above reference if you wish to use this data</td> </tr> <tr> <td> </td> <td> </td> </tr> <tr> <td>DOI of data:</td> <td>10.5281/zenodo.13712672</td> </tr> </tbody> </table>

Data for Transparent Porous Medium for Optical Fluid Flow Measurement using Refractive Index Matching

This data repository contains shadowgraph images acquired during the design of three transparent porous media using refractive index matching. The images were captured through various liquid mixtures, including toluene/1-hexanol, potassium thiocyanate (KSCN), and cyclohexanol/toluene, both with (PM) and without glass beads (FM). The images were processed and analysed using ImageJ, an open-source software tool.

Hydrograph and Recession Flows Predictions Simulations using Deep Learning: Watershed Uniqueness and Objective Functions

This resource contains the results presented in the paper titled 'Hydrograph and Recession Flows Simulations using Deep Learning: Watershed Uniqueness and Objective Functions' by Abhinav Gupta and Sean McKenna. '

Climate change has no apparent effect on debris flows in a supply-limited torrent

<h3>This file contains all tree-ring data, growth disturbance data, final debris-flow chronology data and map background data used in the paper "A supply-limited torrent that does not feel the heat of climate change"</h3> Multetta-tree-ring raw data.rwl: Contains the raw measurement data from 761 tree-ring cores from 478 P. mugo trees. Growth Disturbances-Original data.xlsx: Contains detailed information on tree-ring cores, growth disturbances and their intensity. Zone area refers to the zonation (1-4 corresponds to SI-SIV) of the sampled trees in the study area. Tree ID refers to the name of the tree-ring core or cross section/wedge. The third and fourth columns refer to Y/latitude and X/longitude. Last ring refers to the year of the outermost ring and is mostly 2020, which is the year when the fieldwrok was carried out. In some cases, tree-ring cores were broken or they were taken from dead trees, so the year of the outermost ring is not 2020. Oldest ring refers to the year of the innermost available ring. In the age incomplete column, a value of 1 indicates that the oldest ring measured is not the innermost ring of the tree center. Age refers to the age of the trees, which is equals to the value of the last ring minus the value of the oldest ring. The Comments column indicates the wedge and the cross section. From the tenth column, the numbers 2020, 2019, 2018...... refer to different years corresponding to tree rings. Here, all values including 0, 1, 2, 3 and 4 indicate that there is a measured annual ring in the corresponding year. Blank indicates no data. GS refers to growth suppression. CW refers to compression wood. I refers to injury and CT refers to callus tissue. The number 0 means no growth disturbance. Numbers 1-4 mean intensity from weak to strong. For example, in the 2016 column, any core with '2GS' means the tree-ring showed growth suppression in 2016 and the corresponding intensity is 2. The growth disturbance (GDs) statistic is shown at the bottom, including all 1427 GDs, but GDs with intensity 1 were excluded from the analysis. Note: Samples mub74 and mul105 have data from both section and core, so 480 tree-ring series exist.  Events-Final definition.xlsx: Contains all tree-ring based reconstructed debris-flow events for each zone (1-4 corresponds to SI-SIV) after careful examination of the spatial distribution of damaged trees. In the process of defining events, years were excluded from the analysis that (1) showed incoherent patterns of damaged trees (e.g. GDs evenly distributed on the cone, probably due to climatic extremes or insect pests), (2) were recorded in historical chronicles as snow avalanche years, or (3) were characterized by high mortality of P. mugo trees, as indicated by low tree-ring index (<1.5 average value) in the event cataster of the Canton of Grisons and the Swiss National Park (Bigler and Rigling, 2013). Figures and the data used in figures are shown as below: Information on tree location and age in fig.1D, GDs and sample depth (At) in fig.3A, reconstructed XXL events in fig.4A, GDs for affected regions (total of 16 regions) in fig.4B, GDs in different years for different zones in fig.S3 and GDs for different affected regions in fig.S4 is from the file: Growth Disturbances-Original data.xlsx. Information on the 56 defined events in fig.3B and the reconstructed debris-flow events in fig.5A, 5B is from the file: Events-Final definition.xlsx. Here, 75 events occurred in 4 zones, but actually all events occurred in 56 different years. The LiDAR DEM background in fig.1B, 1C and the hillshade view of the 2023 LiDAR DEM background in fig.S1, S2 are from Swisstopo (https://map.geo.admin.ch/). The R code used for the repose time pattern analysis in fig.5A, 5B is originally from the previously published paper (Heiser, M. et al., 2023) and is available on GitLab at https://gitlab.com/Rexthor/repose-time-patterns.

openSep 2024View details →

Continuous Flow Synthesis and Simulation-Supported Investigation of Tunable Plasmonic Gold Patchy Nanoparticles

This is the dataset for the following manuscript "Continuous Flow Synthesis and Simulation-Supported Investigation of Tunable Plasmonic Gold Patchy Nanoparticles". Abstract Plasmonic nanoparticles have intriguing optical properties which make them suitable candidates for sensing or theranostic applications. Anisotropic patchy particles, where metal is locally deposited on the surface of a core particle, exhibit plasmon resonances that can be specifically adjusted for these applications. However, many existing synthesis routes are complex, yield too little material, or provide particles with limited optical tunability. In this work, we present a simple and scalable continuous flow synthesis of gold-on-polystyrene patchy particles with widely adjustable optical properties. By increasing the chloride concentration in the electroless deposition of gold, we slow down the redox reduction kinetics and obtain a dense patch morphology as well as a reduced nucleation rate. The latter is counteracted by introducing a low-level seeding approach where a small number of gold nanocrystals heterocoagulate with the core particles prior to patch growth. Seeding and patch growth are performed in a continuous flow set-up with two T-shaped milli-mixers. The resulting patchy particle samples exhibit a tunable dipolar plasmon peak between 600 nm and 1100 nm. We also investigate the structure-property relationship for our gold patchy particles using Finite Element Method simulations. After identifying a suitable patch shape model, we elucidate the influence of individual geometric parameters on the optical properties and show that the relationship holds true for a large range of patch coverages. Finally, we apply the relationship to explain the time-dependent change in the optical properties of as-synthesized patches by correlating it with the patch shape transformation revealed by electron microscopy.   The uploaded data are sorted by figure.

Supplementary Data for Bayesian material flow analysis of the construction aggregate cycle in England (2019)

Supplementary Data for Bayesian material flow analysis of the construction aggregate cycle in England (2019) by  Adam R. Mason 1,a, Tom Bide 2,b, Junyang Wang 3,c, John Morley 4,d, Mohit Arora 5,e, Alperen Yayla1,f, Julia A. Stegemann 5,g, Rupert J. Myers 1,h,*   1 Department of Civil and Environmental Engineering, Imperial College London, UK 2 British Geological Survey, UK 3 Department of Mathematics, Imperial College London, UK 4 Department of Earth Science and Engineering, Imperial College London, UK 5 School of Engineering, King’s College London, UK 6 Department of Civil, Environmental and Geomatic Engineering, University College London, UK   Author e-mails: a <a href="mailto:a.mason19@imperial.ac.uk">a.mason19@imperial.ac.uk</a>, b <a href="mailto:tode@bgs.ac.uk">tode@bgs.ac.uk</a>, c <a href="mailto:junyang.wang21@imperial.ac.uk">junyang.wang21@imperial.ac.uk</a>, d <a href="mailto:john.morley18@imperial.ac.uk">john.morley18@imperial.ac.uk</a>, e <a href="mailto:mohit.arora@kcl.ac.uk">mohit.arora@kcl.ac.uk</a>, f <a href="mailto:a.yayla22@imperial.ac.uk">a.yayla22@imperial.ac.uk</a>, g <a href="mailto:j.stegemann@ucl.ac.uk">j.stegemann@ucl.ac.uk</a>; *corresponding author: h <a href="mailto:r.myers@imperial.ac.uk">r.myers@imperial.ac.uk</a>

Supplemental materials for "Boosting Barlow Twins reduced order modeling for machine learning-based surrogate models in multiphase flow problems"

Supplemental materials for "Boosting Barlow Twins reduced order modeling for machine learning-based surrogate models in multiphase flow problems" in Water Resources Research. Detailed information is available in readme.md.

restrictedcc-by-4.0May 2024View details →

Memory of shear flow in soft jammed materials

Dataset contains flow curve, stress relaxation and residual stress of experimental system (2w% Carbopol (974p (Lubrizol)) in propylene glycol). Simulation dataset contains flow curves, stress relaxation, residual stress, nematic order parameter, mean squared displacement, spatial correlations of displacement fluctuation, fraction of icosahedrons for different shear rates.  Data description is in "Memory of shear flow in soft jammed materials" arXiv preprint arXiv:2312.00251 (2023)

Numerical experiments on granulation-generated two-fluid waves and flows in a solar magnetic carpet

An animation showing log(Ti) overlaid by magnetic field lines which correspond to a magnetic carpet. The jets shown on the movie are generated by the solar granulation, which leads to reconnection of magnetic field lines and thermal energy release in the photosphere and the chromosphere.

Dataset for the plots in paper: 'A Kronecker product accelerated efficient sparse Gaussian Process (E-SGP) for flow emulation' in 'Journal of Computational Physics'

The .xlsx file contains the data used for the plots Fig. 3, 4, 7, 8 and 9 in the paper 'Kronecker product accelerated efficient sparse Gaussian Process (E-SGP) for flow emulation'.

Animations depicting 2D prescribed-flow particle-based simulations described in arxiv.org:2308.05015

File names contain the follwing information: <ul> <li>singular=True or singular=False - setting controlling the type of immersion freezing parameterization</li> <li>seed=0 - value of the random seed used</li> <li>rhod_w_max=value - value of the amplitude of the prescribed-flow eddy stream function (dimension of density times velocity in SI units)</li> <li>"cld" or "ice" - set of variables plotted (either those pertinent to cloud water or ice water) </li> </ul>

opencc-by-nc-nd-4.0Sep 2024View details →

Core competencies of a scholarly journal editor. Database and citation search report and PRISMA_flow_diagram

Report on Database and Citation search and PRISMA_flow_diagram

Supplementary Material for "Integrating Security-Enriched Data Flow Diagrams Into Architecture-Based Confidentiality Analysis"

Supplementary material for the paper "Integrating Security-Enriched Data Flow Diagrams Into Architecture-Based Confidentiality Analysis". For more information, please see the README.md. For even more information please visit https://dataflowanalysis.org

opencc-by-4.0Oct 2014View details →

Debris Flow Dataset for Debris Flow Velocity Inversion based on Farneback Optical Flow

A velocity inventory of large-scale debris flow flume experimental data, published by USGS (Logan, 2018), was generated using the Debris Flow Velocity Inversion Method based on optical flow model (Farnebäck, 2003). This dataset includes raw data from three debris flow experiments conducted in 2007, 2015, and 2017. Each dataset corresponds to three relevant results: perspective transformation, optical flow analysis, and front position detection.

Data for Pure Shift NMR in Continuous Flow

Open the record for dataset details and reuse information.

Input Files and Processed Results for FreeMHD: validation and verification of the open-source, multi-domain, multi-phase solver for electrically conductive flows

Input Files (StartingFiles.zip) and Processed Results (FreeMHDPaperAllFigures.zip) used to make paper figures.    FreeMHD: validation and verification of the open-source, multi-domain, multi-phase solver for electrically conductive flows The extreme heat fluxes in the divertor region of tokamaks may require an alternative to solid plasma-facing components, for the extraction of heat and the protection of the surrounding walls. Flowing liquid metals are proposed as an alternative, but raise additional challenges that require investigation and numerical simulations. Free surface designs are desirable for plasma-facing components (PFCs), but steady flow profiles and surface stability must be ensured to limit undesirable interactions with the plasma. Previous studies have mainly used steady-state, 2D, or simplified models for internal flows and have not been able to adequately model free-surface liquid metal (LM) experiments. Therefore, FreeMHD has been recently developed as an open-source magnetohydrodynamics (MHD) solver for free-surface electrically conductive flows subject to a strong external magnetic field. The FreeMHD solver computes incompressible free-surface flows with multi-region coupling for the investigation of MHD phenomena involving fluid and solid domains. The model utilizes the finite-volume OpenFOAM framework under the low magnetic Reynolds number approximation. FreeMHD is validated using analytical solutions for the velocity profiles of closed channel flows with various Hartmann numbers and wall conductance ratios. Next, experimental measurements are then used to verify FreeMHD, through a series of cases involving dam breaking, 3D magnetic fields, and free-surface LM flows. These results demonstrate that FreeMHD is a reliable tool for the design of LM systems under free surface conditions at the reactor scale. Furthermore, it is flexible, computationally inexpensive, and can be used to solve fully 3D transient MHD flows.

Raw flow cytometry data files (fcs files) part 8

These FCS files are raw data for Figure 6A_2 of the following manuscript: Caerin 1.1/1.9-mediated antitumor immunity depends on IFNAR-Stat1 signalling of tumour infiltrating macrophage by autocrine IFNα and is enhanced by CD47 blockade Junjie Li#1,6, Yuandong Luo3, Quanlan Fu3, Shuxian Tang2, Pingping Zhang2, Ian H. Frazer5, Xiaosong Liu#1, 2, Tianfang Wang#4*, Guoying Ni#1, 2* 1.     Key Laboratory of Cancer Immunotherapy of Guangdong tertiary education, Guangdong CAR-T Treatment-Related Adverse Reaction Key Laboratory, The First Affiliated Hospital, Clinical Medical School, Guangdong Pharmaceutical University, Guangzhou 510080, China 2.     Cancer Research Institute, Foshan First People’s Hospital, Foshan, Guangdong 528000, China 3.     Medical School of Guizhou University, Guiyang, Guizhou 550000, China 4.     Centre for Bioinnovation, University of the Sunshine Coast, Maroochydore BC, QLD 4558, Australia 5.     Diamantia Institute, Translational Research Institute, University of Queensland, Woolloongabba, Brisbane, QLD 4002, Australia 6.     Zhongao Biopharmaceutical Technology (Guangdong) Co., Ltd, Zhongshan, Guangdong 528403, China * Corresponding author: twang@usc.edu.au, ngy2003@gmail.com

Raw flow cytometry data files (fcs files) part 7

These FCS files are raw data for Figure 6A_1 the following manuscript: Caerin 1.1/1.9-mediated antitumor immunity depends on IFNAR-Stat1 signalling of tumour infiltrating macrophage by autocrine IFNα and is enhanced by CD47 blockade Junjie Li#1,6, Yuandong Luo3, Quanlan Fu3, Shuxian Tang2, Pingping Zhang2, Ian H. Frazer5, Xiaosong Liu#1, 2, Tianfang Wang#4*, Guoying Ni#1, 2* 1.     Key Laboratory of Cancer Immunotherapy of Guangdong tertiary education, Guangdong CAR-T Treatment-Related Adverse Reaction Key Laboratory, The First Affiliated Hospital, Clinical Medical School, Guangdong Pharmaceutical University, Guangzhou 510080, China 2.     Cancer Research Institute, Foshan First People’s Hospital, Foshan, Guangdong 528000, China 3.     Medical School of Guizhou University, Guiyang, Guizhou 550000, China 4.     Centre for Bioinnovation, University of the Sunshine Coast, Maroochydore BC, QLD 4558, Australia 5.     Diamantia Institute, Translational Research Institute, University of Queensland, Woolloongabba, Brisbane, QLD 4002, Australia 6.     Zhongao Biopharmaceutical Technology (Guangdong) Co., Ltd, Zhongshan, Guangdong 528403, China * Corresponding author: twang@usc.edu.au, ngy2003@gmail.com

Raw flow cytometry data files (fcs files) part 3

These FCS files are raw data for Figure 3C, 4A and S2D of the following manuscript: Caerin 1.1/1.9-mediated antitumor immunity depends on IFNAR-Stat1 signalling of tumour infiltrating macrophage by autocrine IFNα and is enhanced by CD47 blockade Junjie Li#1,6, Yuandong Luo3, Quanlan Fu3, Shuxian Tang2, Pingping Zhang2, Ian H. Frazer5, Xiaosong Liu#1, 2, Tianfang Wang#4*, Guoying Ni#1, 2* 1.     Key Laboratory of Cancer Immunotherapy of Guangdong tertiary education, Guangdong CAR-T Treatment-Related Adverse Reaction Key Laboratory, The First Affiliated Hospital, Clinical Medical School, Guangdong Pharmaceutical University, Guangzhou 510080, China 2.     Cancer Research Institute, Foshan First People’s Hospital, Foshan, Guangdong 528000, China 3.     Medical School of Guizhou University, Guiyang, Guizhou 550000, China 4.     Centre for Bioinnovation, University of the Sunshine Coast, Maroochydore BC, QLD 4558, Australia 5.     Diamantia Institute, Translational Research Institute, University of Queensland, Woolloongabba, Brisbane, QLD 4002, Australia 6.     Zhongao Biopharmaceutical Technology (Guangdong) Co., Ltd, Zhongshan, Guangdong 528403, China * Corresponding author: twang@usc.edu.au, ngy2003@gmail.com

Raw flow cytometry data files (fcs files) part 6

These FCS files are raw data for Figure 5J-L of the following manuscript: Caerin 1.1/1.9-mediated antitumor immunity depends on IFNAR-Stat1 signalling of tumour infiltrating macrophage by autocrine IFNα and is enhanced by CD47 blockade Junjie Li#1,6, Yuandong Luo3, Quanlan Fu3, Shuxian Tang2, Pingping Zhang2, Ian H. Frazer5, Xiaosong Liu#1, 2, Tianfang Wang#4*, Guoying Ni#1, 2* 1.     Key Laboratory of Cancer Immunotherapy of Guangdong tertiary education, Guangdong CAR-T Treatment-Related Adverse Reaction Key Laboratory, The First Affiliated Hospital, Clinical Medical School, Guangdong Pharmaceutical University, Guangzhou 510080, China 2.     Cancer Research Institute, Foshan First People’s Hospital, Foshan, Guangdong 528000, China 3.     Medical School of Guizhou University, Guiyang, Guizhou 550000, China 4.     Centre for Bioinnovation, University of the Sunshine Coast, Maroochydore BC, QLD 4558, Australia 5.     Diamantia Institute, Translational Research Institute, University of Queensland, Woolloongabba, Brisbane, QLD 4002, Australia 6.     Zhongao Biopharmaceutical Technology (Guangdong) Co., Ltd, Zhongshan, Guangdong 528403, China * Corresponding author: twang@usc.edu.au, ngy2003@gmail.com