Find research datasets worth reusing

Data of hybrid vesicles fusion for Nano Letters' journal article

Dataset to accompany the manuscript "Thermoplasmonic induced vesicle fusion for investigating membrane protein phase affinity"

Simulation Data for the article 'The Influence of Cloud Condensation Nucleus (CCN) Coagulation on the Venus Cloud Structure'

This dataset contains the NetCDF output files from simulations using PlanetCARMA in support of the work published in the manuscript, "The Influence of Cloud Condensation Nucleus (CCN) Coagulation on the Venus Cloud Structure."  A summary of the included NetCDF data is found in the README file that is part of the data object.  The submission version of this dataset contains only those simulations that provided data that were discussed in the accepted final manuscript.  However, additional simulations were carried out in the course of the work, and are described in the manuscript.  Upon request, the authors will revise this data repository by adding such data products from among that list as may be requested by others.

opencc-by-4.0Feb 2023View details →

Data related to the article "Frequency-dependent impedance of nanocapacitors from electrode charge fluctuations as a probe of electrolyte dynamics"

Contains input files and data used to generate the figures of the article: Frequency-dependent impedance of nanocapacitors from electrode charge fluctuations as a probe of electrolyte dynamics (Giovanni Pireddu and Benjamin Rotenberg) arXiv: https://arxiv.org/abs/2206.13322 The folder EXAMPLE_INPUT_FILES contains typical <a href="https://doi.org/10.21105/joss.02373">MetalWalls</a> (<a href="https://gitlab.com/ampere2/metalwalls">repository</a>) input files used to perform the simulations. The folder DATA_FIGURES contains the processed data used to plot all the figures of the paper (see below).   The 'd*' labels are used in the directory or file names to refer to the following interelectrode distances considered: - 'd1' corresponds to 2.51 nm; - 'd2' corresponds to 4.94 nm; - 'd3' corresponds to 9.76 nm; - 'd4' corresponds to 19.42 nm; Figure 1: - 'Fig1_Continuum.dat':         -  Capacitance calculated considering a continuum approximation - 'Fig1_DDS.dat':     -  Capacitance calculated considering the DDS model (three capacitors in series) - 'Fig1_MD.dat':     -  Capacitance calculated from MD simulations. Includes the capacitance of the empty capacitor. Figure 2: Panel A - 'Fig2_QACFd*.dat':     - Time autocorrelation function of the electrode charge fluctuations Panel B - 'Fig2_Qrampd*.dat':     - Charge profile upon a step in voltage (0 to 1 V) - 'Fig2_Vramp.dat':     - Voltage ramp related to the charging profiles Panel C - 'Fig2_QACFNormd*.dat':     - Normalized charge autocorrelation function -'Fig2_QrampNormd*.dat'     - Normalized charge profile Figure 3: - 'Fig3_MDd*.dat':     - Real and imaginary parts of impedance as estimated from MD simulations - 'Fig3_ECd*.dat'     - Real and imaginary parts of impedance as calculated from the equivalent circuit models Figure 4: - 'Fig4_MDd*.dat':     - Magnitude of admittance as estimated from MD simulations - 'Fig4_Debyed*.dat':     - Magnitude of admittance as calculated from the Debye relaxation model Inset - 'Fig4_MDTau.dat':     - Relaxation time estimated from MD simulations - 'Fig4_TauFit.dat':     - Fit of the relaxation time

opencc-by-4.0Nov 2022View details →

Datasets supplementing journal article "Probing dynamic covalent chemistry in a 2D boroxine framework by in-situ near-ambient pressure X-ray photoelectron spectroscopy" in Nanoscale 2022

Datasets supporting the Nanoscale journal article "Probing dynamic covalent chemistry in a 2D boroxine framework by in-situ near-ambient pressure X-ray photoelectron spectroscopy". NAP-XPS.zip: Near-ambient pressure X-ray photoelectron spectroscopy, Figures 2, 3. (NEP 101007417) STM.zip: Scanning tunneling microscopy, Figure 5a, inset. (NEP 101007417) TPD.zip: Temperature programmed desorption, Figure 1a. UHV-XPS.zip: X-ray photoelectron spectroscopy, Figure 1b,c. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 101007417, having benefited from the access provided by by ALBA in Barcelona (Spain) and CNR-IOM in Trieste (Italy) within the framework of the NFFA-Europe Pilot Transnational Access Activity, proposal ID075.

X-ray tomographic datasets associated with the article "Pore space of in-situ semi-dense asphalt: A characterization by X-ray tomography" (DOI: 10.1016/j.conbuildmat.2024.139091)

This Zenodo repository provides two sets of 3D images, which constitute part of the dataset base for the article titled "Pore space of in-situ semi-dense asphalt: A characterization by X-ray tomography", written by the same authors cited here, together with other co-authors. The article is published in the journal "Construction and Building Materials". It can be reached via the following URL: <a href="https://doi.org/10.1016/j.conbuildmat.2024.139091" target="_blank" rel="noopener">https://doi.org/10.1016/j.conbuildmat.2024.139091</a>. The core specimens were obtained in 2019 from semi-dense asphalt (SDA) pavement sections located in the Swiss Canton of Zürich. For each of three pavement sections, labelled in the following as SDA4-1yr, SD4-5yr and SDA8, 100 mm diameter cores were extracted, both inside (I) and outside (O) of the wheel path, in order to see the effect of the traffic load on the pore space characteristics. Out of the original cores for the SDA4 pavements, 5 30 mm diameter sub-cores were drilled out of their centers, both in- and out-of the wheel path, and investigated with X-ray tomography. Only 1 30 mm core was analyzed for SDA8, both in- and out- of the wheel path. The asphalt in that pavement type has lower porosity, making it less interesting from the sound absorption viewpoint. The whole dataset consists of .7z archive files. Such files have the following designations: SDA_J_K_L_Tomogram.7z or SDA_J_K_L_PoreSpaceBinTomogram.7z, where J = 1,2, K = I,O and L = 1,2,3,4,5. When referring to the specimen naming within the corresponding article, the first index, J, refers to the specimen "age": J = 1 indicates the 1-year old specimens (called SDA4-1yr within the article); J = 2 refers to the 5-year old ones (SDA4-5yr). The second index, K, refers to the location of the specimen within the pavement section course ("I" for in-wheel path and "O" for out-of-wheel path). The final index L just enumerates the distinct specimens of the same group. There are two additional groups of archive files: LNA_I_Tomogram.7z/LNA_I_PoreSpaceBinTomogram.7z refers to the single in-wheel-path, 7-year old specimen (called SDA8 within the article); LNA_O_Tomogram.7z/LNA_O_PoreSpaceBinTomogram.7z refers to the single out-of-wheel path, 7-year old specimen. The two sets/types of 3D images can be recognized by the different file naming. The first set includes the raw X-ray tomograms of the 22 specimens analyzed. Each tomogram is stored in the form of a "stack" (or series) of 16-bit unsigned integer 2D TIFF image file, being one 2D cross-section (also called "slice", in tomographic jargon) from the "tomographed" volume. Such slices are contained in a folder. The folder was then archived in a .7z archive file. The second set of 3D images is characterized by the filename pattern SDA_J_K_L_PoreSpaceBinTomogram.7z. Each zipped folder contains the slices of the binary tomogram of the whole pore space of the respective specimen, segmented according with the 3d image analysis workflow described within the article. Each slice of such tomogram was stored as a 8-bit unsigned integer 2D TIFF image file, whose pixels can have only two possible values: 255, if the pixel is inside the segmented pore space; 0 if the pixel is outside it. Almost all of the acquired tomograms have an isotropic voxel size of 0.0214 mm, meaning that each slice is separated in space from the next one by such distance. The samples SDA_2_O_1 and SDA_2_I_1 have a voxel size of 0.0220 mm, while the sample LNA_I has a voxel size of 0.0223 mm.

Data, code and software to reproduce the article entitled "Modeling soil-plant functioning of intercrops using comprehensive and generic formalisms implemented in the STICS model"

This is the data, code and software to reproduce the article entitled " Modeling soil-plant functioning of intercrops using comprehensive and generic formalisms implemented in the STICS model". Here is a summary of the paper: The growing demand for sustainable agriculture is raising interest in intercropping for its multiple potential benefits to avoid or limit the use of chemical inputs or increase the production per surface unit. Predicting the existence and magnitude of those benefits remains a challenge given the numerous interactions between interspecific plant-plant relationships, their environment and the agricultural practices. Soil-crop models are critical in understanding these interactions in dynamics during the whole growing season, but few models are capable of accurately simulating intercropping systems. In this study, we propose a set of simple and generic formalisms for simulating key interactions in intercropping systems that can be readily included into existing dynamic crop models. This requires simulating important processes such as development, light interception, plant growth, N and water balance, and yield formation in response to management practices, soil conditions, and climate. These formalisms were integrated into the STICS soil-crop model and evaluated using observed data of intercropping systems of cereal and legumes mixtures, including Faba bean-Wheat, Pea-Barley, Sunflower-Soybean, and Wheat-Pea mixtures. We demonstrate that the proposed formalisms provide a comprehensive simulation of soil-plant interactions in various types of bispecific intercrops. The model was found consistent and generic under a range of spring and winter intercrops (nRMSE = 25% for maximum leaf area index, 23% for shoot biomass at harvest, and 18% for yield). This is the first time a complete set of formalisms has been developed and published for simulating intercropping systems and integrated into a soil-crop model. With its emphasis on being generic, sufficiently accurate, simple, and easy to parameterize, STICS is well-suited to help researchers designing in silico the agroecological transition by virtually pre-screening sustainable, manageable intercrop systems adapted to local conditions.

Lithium-Ion Batteries in Automated Guided Vehicles (AGVs) dataset for article "Automated Battery Power Fade Estimation for Fast Charge and Discharge Operations"

Dataset of aggregated information related to discharge-only cycles of lithium-ion battery packs employed in Automated Guided Vehicle systems. The dataset supports the study in conference article "Automated Battery Power Fade Estimation for Fast Charge and Discharge Operations"

Dataset for article "From X-rays to physical parameters: a comprehensive analysis of thermal tidal disruption event X-ray spectra"

This repository contains the data used in the modeling of TDE X-ray emission within the article: Mummery et al. 2023, " From X-rays to physical parameters: a comprehensive analysis of thermal tidal disruption event X-ray spectra" published as Mummery et al. 2023, MNRAS, 519, 5828

Model outputs for the article "Modelling the evolution of Arctic multiyear sea ice over 2000–2018"

icemod_monthly.tar.gz contains the gridded monthly averaged quantities used in the manuscript "Modelling the evolution of Arctic multiyear sea ice over 2000-2018" for each year between 2000 and 2018. Multiyear ice variables are conc_myi (concentration of multiyear ice in a grid cell) and thick_myi (cell average thickness of multiyear ice in a grid cell, in metres), along with source and sink terms (units per day) for multiyear concentration (dci_mlt_myi, dci_ridge_myi and dci_rplnt_myi, for melt, ridging and replenishment) and volume (dvi_mlt_myi and dvi_rplnt_myi, for melt and replenishment). transports_monthly_sections.zip contains the transports of multiyear ice through the sections defining each region in Figure 8 of the paper. MYIsiaXport indicates multiyear ice area transport, while myiXport indicates multiyear ice volume transport. In case information is missing, do not hesitate to contact heather.regan@nersc.no, guillaume.boutin@nersc.no, or einar.olason@nersc.no.

Data, scripts, and figures of the article: The effect of oregano essential oils on Feed Passage Syndrome in broilers: 2. Assessment under a challenge model

This data set contains the data, JMP scripts, and figures of the article titled "The effect of oregano essential oil on Feed Passage Syndrome in broilers: 2. Assessment under a challenge model" to be published in the journal Animal - Open Space.

Data, scripts, and figures of the article: The effect of oregano essential oils on Feed Passage Syndrome in broilers: 1. Assessment under field conditions

This data set contains the data, JMP scripts, and figures of the article titled "The effect of oregano essential oils on Feed Passage Syndrome in broilers: 1. Assessment under field conditions" to be published in the journal Animal - Open Space.

opencc-by-4.0Apr 2023View details →

Dataset for the article "Development of an integrated socio-hydrological modeling framework for assessing the impacts of shelter location arrangement and human behaviors on flood evacuation processes"

This dataset include the data needed to create the socio-hydrological model to simulate human evacuation processes via a transportation network before a flood hits the residential area. Source code, in JAVA, for generating households in the agent-based model are also provided.

opencc-by-4.0Apr 2023View details →

data for journal article 'Nernst-Ettingshausen effect in thin Pt and W films at low temperatures'

This dataset contains the supporting information for the journal article 'Nernst-Ettingshausen effect in thin Pt and W films at low temperatures'.

opencc-by-4.0Dec 2022View details →

Data associated with the article "Evolution and phylogenetic distribution of endo-α-mannosidase"

Data associated with the article "Evolution and phylogenetic distribution of endo-α-mannosidase" Changelog: version 1.1 <ul> <li>added Tunicaraptor motif analysis alignment</li> </ul> version 1.0 <ul> <li>Initial release</li> </ul>   Funding statement: National Science Centre of Poland is acknowledged for funding of the project 2020/36/C/NZ8/00081, "The role of glycosylation in the emergence of animal multicellularity", which enabled the creation of this research output.

opencc-by-4.0May 2023View details →

Dataset of the article "A new and almost perfectly accurate approximation of the eigenvalue effective population size of a dioecious population: comparisons with other estimates and detailed proofs"

Dataset of the article "A new and almost perfectly accurate approximation of the eigenvalue effective population size of a dioecious population: comparisons with other estimates and detailed proofs"  (https://doi.org/10.5281/zenodo.7927968), recommended by PCI Evol Biol (https://evolbiol.peercommunityin.org/articles/rec?id=651)

opencc-by-4.0May 2023View details →

Original data for "Imaging and quantifying the chemical communication between single particles in metal alloy" article

This upload contains original data and supplementary data for the publication titled "Imaging and Quantifying the Chemical Communication Between Single Particles in Metal Alloy" by L. Godeffroy, A. Makogon, S. G. Derouich, F. Kanoufi, V. Shkirskiy in the ACS Analytical Chemistry journal. The preprint of the paper is included in this upload and is also available on ChemRxiv (<a href="https://doi.org/10.26434/chemrxiv-2022-rn77b-v2">https://doi.org/10.26434/chemrxiv-2022-rn77b-v2</a>).  The file "OpticalData.zip" contains the original optical images. Each pixel in the images has a size of 180 nm, and the time interval between frames is 1.87 seconds. The file "sem_identical.png" contains a scanning electron microscopy (SEM) image of the same surface area as the optical images, captured using secondary electrons. The file "WorkingWithData.ipynbb" is a Jupyter Lab file that demonstrates a few examples of how data can be loaded and processed in a Python environment. Python 3 was used for this purpose. There are also two supplementary movies: Movie S1: This movie provides an enlarged view (marked with a square in Movie S2) of the surface film transformation on Al6061 during immersion in 10 mM H2SO4. It includes snapshots at 17 s, 28 s, 37 s, and 84 s, along with a related SEM image of the same location. Movie S2: This movie presents a wide-field view of the surface film transformation on Al6061 during immersion in 10 mM H2SO4, along with a related SEM image of the same location. The square highlights the area around which the narrative in the manuscript is focused.

Supplementary data for the journal article "Quantifying the impact of 3D pore space morphology on diffusive mass transport in loam and sand"

Binarized cutouts (black=pore, white=soil) of 3D CT images of soil samples from loam and sand together with geometrical descriptors and diffusive properties computed on these cutouts. The geometrical descriptors include, among others, porosity, specific surface area, geodesic tortuosity, geometric tortuosity, constrictivity, mean chord length and mean of spherical contact distribution. Diffusion is quantified by the so-called M-factor which equals the ratio of the effective and intrinsic diffusivity. This data supplements the journal article "Quantifying the impact of 3D pore space morphology on diffusive mass transport in loam and sand". Additional information can be found there.

opencc-by-4.0Jun 2023View details →

Supplementary material for the article "High-resolution projections of ambient heat for major European cities using different heat metrics"

This dataset contains the data displayed in the figures or the article "High-resolution projections of ambient heat for major European cities using different heat metrics". The different files contain: <ul> <li>Data_Fig1_DeltaTXx_EURO-CORDEX_1981-2010_to_3K-European-warming_RCP85.nc: Change of yearly maximum temperature in Europe between 1981-2010 and 3 °C European warming relative to 1981-2010.</li> <li>Data_Fig2_timeseries-GSAT-ESAT_EURO-CORDEX_CMIP5_CMIP6_1971-2100_RCP85_SSP585.xlsx: Time series of global mean surface air temperature (GSAT) for CMIP5 and CMIP6 models, and for European mean surface air temperature (ESAT) for EURO-CORDEX, CMIP5, and CMIP6 models for the period 1971-2100.</li> <li>Data_Fig3_TX-distribution_distance-from-city-centre_E-OBS_1981-2010.xlsx: Distribution of average daily maximum temperature in summer (June, July, August) in 1981-2010 for E-OBS for all investigated cities. Temperature data are indicated as a function of the distance to the city centre.</li> <li>Data_Fig3_TX-distribution_distance-from-city-centre_ERA5-Land_1981-2010.xlsx: Distribution of average daily maximum temperature in summer (June, July, August) in 1981-2010 for ERA5-Land for all investigated cities. Temperature data are indicated as a function of the distance to the city centre.</li> <li>Data_Fig3_TX-distribution_distance-from-city-centre_EURO-CORDEX_1981-2010.xlsx: Distribution of average daily maximum temperature in summer (June, July, August) in 1981-2010 for the EURO-CORDEX models for all investigated cities. Temperature data are indicated as a function of the distance to the city centre.</li> <li>Data_Fig3_TX-distribution_distance-from-city-centre_weather-stations_1981-2010.xlsx: Distribution of average daily maximum temperature in summer (June, July, August) in 1981-2010 for GSOD and ECA&D stations for all investigated cities. Temperature data are indicated as a function of the distance to the city centre.</li> <li>Data_Fig4_TX-ambient-heat_EURO-CORDEX_3K-European-warming.xlsx: Daytime heat metrics for the investigated cities: HWMId-TX at 3 °C European warming relative to 1981-2010, TX exceedances above 30 °C at 3 °C European warming relative to 1981-2010, and TXx change between 1981-2010 and 3 °C European warming relative to 1981-2010 for EURO-CORDEX models.</li> <li>Data_Fig5_Contribution-of-explanatory-variables-to-total-explained-variance.xlsx: Contribution of different explanatory variables (climate and location factors) to the total explained variance of spatial patterns of heat metrics.</li> <li>Data_Fig6_TN-ambient-heat_EURO-CORDEX_3K-European-warming.xlsx: Nighttime heat metrics for the investigated cities: HWMId-TN at 3 °C European warming relative to 1981-2010, TN exceedances above 20 °C at 3 °C European warming relative to 1981-2010, and TNx change between 1981-2010 and 3 °C European warming relative to 1981-2010 for EURO-CORDEX models.</li> <li>Data_Fig7_TX-ambient-heat_CMIP5_3K-European-warming.xlsx: Daytime heat metrics for the investigated cities: HWMId-TX at 3 °C European warming relative to 1981-2010, TX exceedances above 30 °C at 3 °C European warming relative to 1981-2010, and TXx change between 1981-2010 and 3 °C European warming relative to 1981-2010 for CMIP5 models.</li> <li>Data_Fig7_TX-ambient-heat_CMIP6_3K-European-warming.xlsx: Daytime heat metrics for the investigated cities: HWMId-TX at 3 °C European warming relative to 1981-2010, TX exceedances above 30 °C at 3 °C European warming relative to 1981-2010, and TXx change between 1981-2010 and 3 °C European warming relative to 1981-2010 for CMIP6 models.</li> <li>Data_Fig8_GCM-RCM-matrix_ambient-heat_3K-European-warming.xlsx: GCM-RCM matrices for the three heat metrics.</li> </ul>

opencc-by-4.0Aug 2022View details →

Raw data for the Article "Cyclopentadienone Iron Complex-Catalyzed Hydrogenation of Ketones: An Operando Spectrometric Study Using Pressurized Sample Infusion-Electrospray Ionization-Mass Spectrometry"

This data set contains the raw data (NMR, LC-MS, ESI-MS, HRMS, Elemental Analysis) for the article "Cyclopentadienone Iron Complex-Catalyzed Hydrogenation of Ketones: An Operando Spectrometric Study Using Pressurized Sample Infusion-Electrospray Ionization-Mass Spectrometry" published in Organometallics, DOI: <a href="https://doi.org/10.1021/acs.organomet.2c00341">https://doi.org/10.1021/acs.organomet.2c00341</a> The compound names correspond to the ones used in the article and its supporting information.