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1,582 results for “Manuscripts”
Dataset to Manuscript: Schiedung et al. (2023; SBB) Enhanced loss but limited mobility of pyrogenic and organic matter in continuous permafrost-affected forest soils.
<p>Dataset to Schiedung et al. (2023; SBB) Enhanced loss but limited mobility of pyrogenic and organic matter in continuous permafrost-affected forest soils.</p> <p>All published data is provided in the files "<strong>dd_</strong>". This includes:</p> <ul> <li>dd_cores: All data of soil cores and with depth</li> <li>dd_fractions: All data obtained from fractionation of the 0-3cm core layers</li> <li>dd_teabag: All data and mass losses of incubated teabags</li> <li>dd_temperature: All data and recorded soil temperatures</li> </ul> <p>All parameters and names are described in the corresponding file starting with "<strong>Var_names_</strong>". Details on methods and calculations are given in the manuscript and supporting information.</p> <p>NanoSIMS data is provided in the folder "<strong>dd_NanoSIMS.zip</strong>". This contains a file with descriptions of the provided tif-files "<strong>dd_NanoSIMS</strong>". Descriptions of the variables and parameters as well as further instructions are given in the file "<strong>Var_names_description_dd_NanoSIMS</strong>". Images and additional data can be requested by the corresponding author (marcusschiedung@gmail.com).</p> <p> </p> <p> </p>
Experimental data for the manuscript titled Rotating quantum wave turbulence
<p>This submission contains the minimal dataset required to reproduce the experimental findings related to the manuscript titled <em>Rotating quantum wave turbulence</em>, associated with the DOI 10.1038/s41567-023-01966-z.</p>
Dataset for manuscript "Thermal infrared dust optical depth and coarse-mode effective diameter over oceans retrieved from collocated MODIS and CALIOP observations"
<p>This is the long-term satellite retrieval dataset of dust aerosol optical depth at 10 μm (DAOD<sub>10μm</sub>) and dust coarse mode effective diameter (D<sub>eff</sub>) based on collocated MODIS and CALIOP observations from July 2006 to August 2018. The full description is in the manuscript "<strong>Thermal infrared dust optical depth and coarse-mode effective diameter over oceans retrieved from collocated MODIS and CALIOP observations" </strong>by Zheng, Jianyu, et al. The readme file for the data is in "readme_dust_aod_size_product.txt". The variable list of Level-2 data is in "variable_list_L2.txt". The variable list of Level-3 data is in "variable_list_L3.txt".</p>
Datasets and R source code of manuscript "Parasites make hosts more profitable but less available to predators"
<p>Data about experimentations of DIV-1 (virus) infection on Daphnia magna.</p> <p>Linked article: Parasites make hosts more profitable but less available to predators</p>
Model output used in the manuscript "The evolution of a non-autonomous chaotic system under non-periodic forcing: a climate change example"
<p>This *.zip file contains the model output from ensemble simulations for the Lorenz 84-Stommel 61 model (<a href="https://doi.org/10.1034/j.1600-0870.2001.00241.x" target="_blank" rel="noopener">Van Veen et al, 2001</a>; <a href="https://dx.doi.org/10.1088/1748-9326/8/3/034021" target="_blank" rel="noopener">Daron and Stainforth, 2013</a>). To run these simulations, we used the Low-EFFourth ensemble generator (<a href="https://doi.org/10.48550/arXiv.2506.03313" target="_blank" rel="noopener">de Melo Viríssimo, 2025a</a>; <a href="https://doi.org/10.5281/zenodo.15566109" target="_blank" rel="noopener">de Melo Viríssimo, 2025b</a>), which is a MATLAB-based framework that allows for large ensembles of low-dimensional dynamical systems to be run and studied in a systematic way (<a href="https://doi.org/10.5194/egusphere-egu23-14755" target="_blank" rel="noopener">de Melo Viríssimo and Stainforth, 2023</a>).</p> <p>These model outputs are presented and discussed in the article "<em>The evolution of a non-autonomouys chaotic system under non-periodic forcing: a climate change example</em>", published by Chaos (<a href="https://doi.org/10.1063/5.0180870" target="_blank" rel="noopener">de Melo Viríssimo et al., 2024</a>). The manuscript describes the experiments performed, the parameter values used and the modifications done to the original L84-S61 model. For this matter, we also refer you to <a href="https://dx.doi.org/10.1088/1748-9326/8/3/034021" target="_blank" rel="noopener">Daron and Stainforth (2013)</a>.</p> <p>All files uploaded were generated from simulations run by the authors.</p> <p>For specific information about each file uploaded, please refer to the README file. If you have any questions, please feel free to contact me.</p> <p><strong>Note:</strong> This version (v1.1) is the same version as v1.0 but with the correct README file.</p>
Plot-level field data and model simulation results, archived to accompany Turner et al. manuscript; reports data from summer 2017 sampling of short-interval fires that burned during summer 2016 in Greater Yellowstone.
Subalpine forests in the northern Rocky Mountains have been resilient to stand-replacing fires that historically burned at 100–300-yr intervals. Fire intervals are projected to decline drastically as climate warms, and forests that reburn before recovering from previous fire may lose their ability to rebound. We studied recent fires in Greater Yellowstone (Wyoming, USA) and asked whether short-interval (less than 30 yrs) stand-replacing fires can erode lodgepole pine (Pinus contorta var. latifolia) forest resilience via increased burn severity, reduced early postfire tree regeneration, reduced carbon stocks, and slower carbon recovery. During 2016, fires reburned young lodgepole pine forests that regenerated after wildfires in 1988 and 2000. During 2017, we sampled 0.25-ha plots in stand-replacing reburns (n=18) and nearby young forests that did not reburn (n=9). We also simulated stand development with and without reburns to assess carbon recovery trajectories. Nearly all prefire biomass was combusted ("crown fire plus") in some reburns in which prefire trees were dense and small (≤ 4 cm basal diameter). Postfire tree seedling density was reduced six-fold relative to the previous (long-interval) fire, and high-density stands (greater than 40,000 stems ha-1) were converted to sparse stands (less than 1,000 stems ha-1). In reburns, coarse wood biomass and aboveground carbon stocks were reduced by 65% and 62%, respectively, relative to areas that did not reburn. Increased carbon loss plus sparse tree regeneration delayed simulated carbon recovery by greater than 150 yrs. Forests did not transition to nonforest, but extreme burn severity and reduced tree recovery foreshadow an erosion of forest resilience.
Project files provided as supporting information to the manuscript "Ligand-protein interactions in lysozyme investigated through a dual-resolution model"
<p><strong>README file for the project files provided as supporting information to the manuscript "Ligand-protein interactions in lysozyme investigated through a dual-resolution model"</strong></p> <p>February 12, 2020</p> <p>Authors: Raffaele Fiorentini, Kurt Kremer and Raffaello Potestio</p> <p>================================</p> <p>Overview</p> <p>The dataset is organised in three (compressed) subfolders (see the tree diagrams in each section):</p> <p>- annihilation<br> - decoupling<br> - density</p> <p>The figure deltaG_binding_ann_dec_comparison.png shows the results of binding free energy calculations comparing the values obtained both for annihilation and decoupling.</p> <p>The figure deltaG_binding_annih_gromacs_espp.png displays the results for Binding FE, comparing the values obtained in GROMACS and ESPResSo++.</p> <p>The README.pdf file contains detailed information about these folders and their content.</p> <p>================================</p> <p>The "annihilation" folder contains all results concerning the calculation of binding free energy in case of annihilation and it is divided in two parts: </p> <p>- complex<br> - ligand</p> <p>In "complex" are reported the results of Ligand-Protein FE both in ESPResSo++ and GROMACS. All simulations are fully-atomistic. </p> <p>In "ligand" are reported the results of ligand solvation free energy both in ESPResSo++ and GROMACS. All simulations are fully-atomistic. </p> <p>====</p> <p>The "decoupling" folder contains all results concerning the calculation of binding free energy in case of decoupling and it is divided in three parts: </p> <p>- complex-DualRes<br> - complex-FullyAT<br> - ligand</p> <p>In "complex-DualRes" are reported the results of Ligand-Protein FE only in ESPResSo++ (GROMACS cannot do decoupling). The system is simulated in Dual-Resolution. It is possible to find the trajectory files in the sub-directories "lambdaindex-0" and "lambdaindex-30".</p> <p>In "complex-fullyAT" are reported the results of Ligand-Protein FE only in ESPResSo++. The system simulated is fully-atomistic. It is possible to find the trajectory file in the sub-directories "lambdaindex-0" and "lambdaindex-30".</p> <p>In "ligand" are reported the results of ligand solvation free energy only in ESPResSo++. All simulations are fully-atomistic. It is possible to find the trajectory file in the sub-directories "lambdaindex-0" and "lambdaindex-20".</p> <p>====</p> <p>The "density" folder contains the data for the tuning of the c parameter of the steric repulsion among residues. This parameter is tuned so that the water density attains the value computed in all-atom simulations.</p>
Datasets for manuscript: Global River Discharge and Floods in the Warmer Climate of the Last Interglacial
<p>This datasets contains results of the global hydrological and hydrodynamic modeling presented in the paper referenced in the title (doi: 10.1029/2020GL089375). The dataset comprises results for one set of simulations, based on Global Climate Model CESM1.2, out of the eight sets of simulations for eight GCMs included in the paper. The corresponding results for the other seven sets of simulations (based on GCMs CESM2, EC‐EARTH3.2, HadGEM3‐GC3.1, IPSL‐CM6‐LR, MPI‐ESM 1.2.01p1‐LR, NorESM1‐F, and NUIST‐CSM) can be obtained by writing to the corresponding author at paolo.scussolini@vu.nl.</p> <p>Files description:</p> <p>fldare_yearmean_timmean_CEM1.2_LIG.nc : Annual average flood area for the Last Interglacial simulation with GCM CESM1.2, hydrological model PCR-GLOBWB and hydrodynamic model CaMa-Flood.<br> <br> fldare_yearmean_timmean_CESM1.2_PI.nc 4 Mb : Annual average flood area for the Pre-Industrial simulation with GCM CESM1.2, hydrological model PCR-GLOBWB and hydrodynamic model CaMa-Flood.<br> <br> fldsto_yearmean_timmean_CESM1.2_LIG.nc 4 Mb : Annual average flood volume for the Last Interglacial simulation with GCM CESM1.2, hydrological model PCR-GLOBWB and hydrodynamic model CaMa-Flood.<br> <br> fldsto_yearmean_timmean_CESM1.2_PI.nc 4 Mb : Annual average flood volume for the Pre-Industrial simulation with GCM CESM1.2, hydrological model PCR-GLOBWB and hydrodynamic model CaMa-Flood.<br> <br> outflw_yearmean_timmean_CESM1.2_LIG.nc 4 Mb : Annual average river discharge for the Last Interglacial simulation with GCM CESM1.2, hydrological model PCR-GLOBWB and hydrodynamic model CaMa-Flood.<br> <br> outflw_yearmean_timmean_CESM1.2_PI.nc 4 Mb : Annual average river discharge for the Pre-Industrial simulation with GCM CESM1.2, hydrological model PCR-GLOBWB and hydrodynamic model CaMa-Flood.<br> <br> runoff_annuaTot_output_mergetime_timmean_CESM1.2_LIG.nc : Annual average runoff for the Last Interglacial simulation with GCM CESM1.2 and hydrological model PCR-GLOBWB.<br> <br> runoff_annuaTot_output_mergetime_timmean_CESM1.2_PI.nc : Annual average runoff for the Pre-Industrial simulation with GCM CESM1.2 and hydrological model PCR-GLOBWB.</p> <p> </p>
Raw SNR data for Manuscript "GPS Interferometric Reflectometry : Using a Low Cost Antenna to Measure Water Levels"
<p>Raw GPS L1 SNR (and ancillary) data for an experiment to use a low-cost GPS antenna/receiver to measure water levels using the GNSS - Interferometric Reflectometry technique.</p> <p>The data were recorded at the RNLI lifeboat station in Sligo, Ireland (N 54<sup>o </sup>18' 17.8'', W 8<sup>o</sup> 34' 5.4'' ) using a Globalsat BU353S4 USB puck that uses a SirfStar IV receiver with patch antenna (2018 data) and a Maestro A2200A SirfStar IV module (2019 data). Both systems were mounted to a radio mast at around 16m above sea level.</p> <p>The data are stored in daily files with the naming convention sligDDD0.YY.TNR.gz where DDD is the Day of Year and YY is the year in short format (18,19). Each file is gzipped. </p> <p>The files are flat text files with fixed width columns in the following order</p> <p>1) PRN GPS satellite code</p> <p>2) Elevation (degrees)</p> <p>3) Azimuth (degrees)</p> <p>4) Seconds of Day</p> <p>5) change in elevation angle with time (degrees/second) : needed for reflector height change corrections</p> <p>6) Blank</p> <p>7) S1 SNR signal (dB-Hz)</p> <p>8) Blank reserved for S2 SNR signal</p> <p>9) Blank reserved for S5 SNR signal</p>
Supplementary data for the manuscript "Technical note: Estimating aqueous solubilities and activity coefficients of mono- and α,ω-dicarboxylic acids using COSMO-RS-DARE"
<p>.cosmo files (BP-TZVPD-FINE) of dicarboxylic acids (C2-C8), dimers and monohydrates of mono- (C1-C6) and dicarboxylic acids, and water dimer.</p>
The datasets used in the manuscript named "Dynamical Seasonal Prediction of Tropical Cyclone Activity Using a Global Ensemble Prediction System FGOALS-f2 V1.0"
<p>The hindcast and real-time prediction output of FGOALS-f2 V1.0 used in the study named "Dynamical Seasonal Prediction of Tropical Cyclone Activity Using a Global Ensemble Prediction System FGOALS-f2 V1.0"</p>
Raw and analyzed data for manuscript: "Wood surface ablation and nanostructuring using a femtosecond laser"
<p><strong>Abstract</strong></p> <p>The processing of Norway spruce and European beech wood specimens by means of femtosecond laser pulses was investigated on conditioned natural samples as well as on samples coated with beeswax or a water-borne stain. Depending on laser pulse energies and processing times, this allowed for different modes of surface modification. At low laser intensities, an etching almost without thermal impact was detected, whereas higher laser intensities led to the generation of hierarchical micro and nanostructures. The usage of argon or atmospheric air as cover gases during the laser processing had only minor effects on the surface structures. Observed differences in the etching or functionalization of the wooden surfaces mostly originated in the chemical structure of the surface finish and the physical properties of the wood substrates, such as the density or moisture content.</p>
Mechanical data of rotary shear experiments and temperature measurements for the manuscript: "Fast and localized temperature measurements during simulated earthquakes in carbonate rocks"
<p>Mechanical data of rotary shear experiments and temperature measurements</p> <p>Each experiment is presented in a file with the experiment name (mechanical data of rotary shear experiment) and a file with the experiment name and _Temp (temperature measurement with the optical fiber).</p> <p>Mechanical data are presented in a tab-delimited file with calibrated measurements of:</p> <ul> <li>Time (milliseconds)</li> <li>Normal stress: Normal (MPa) </li> <li>Fault displacement: Slip (mm)</li> <li>Fault velocity: Velocity (mm/s)</li> <li>Shear stress: Shearstress (MPa)</li> <li>Axial shortening: Shortening (mm).</li> </ul> <p> In a separate file, temperature data are presented as tab-delimited file with calibrated measurements of:</p> <ul> <li>Time (milliseconds)</li> <li>Temperature from optical fiber in the channel at 1.5 µm : Temperature_1,5 (°C) </li> </ul>
Raw and processed GO term data to support running GCEA analyses using ensemble-based nulls, as described in the manuscript, 'Overcoming bias in gene category enrichment analyses of brain-wide transcriptomic data'.
<p>Data to support a toolbox for performing gene category enrichment analyses, including against ensembles of null phenotypes.</p> <p>Descriptions of how these data files can be used for this purpose are in the documentation for the toolbox, at https://github.com/benfulcher/GCEA_FalsePositives</p>
Raw and analyzed data for manuscript: "An open-source surface barrier discharge plasma pretreatment for reduced cracking of outdoor wood coatings"
<p><strong>Highlights:</strong></p> <ul> <li>Surface barrier discharges are an affordable and available plasma technology for industrial, laboratory and home-workshop applications.</li> <li>Plasma pretreatments had no impact on the appearance of different protective wood coating for outdoor usage.</li> <li>The weathering performance of outdoor wood coatings improved by plasma, showing less cracks and less biotic factors.</li> </ul>
Supplementary data files for manuscript titled "From spreadsheet lab data templates to knowledge graphs: A FAIR data journey in the domain of AMR research"
<div>This data repository contains all the necessary supplementary files for the manuscript titled "<strong>From spreadsheet lab data templates to knowledge graphs: A FAIR data journey in the domain of AMR research.</strong>"</div> <div> </div> <div>The repository is a copy of the <a href="https://github.com/IMI-COMBINE/template2graphs">GitHub page</a> with the source code used to generate the graph and additional files required for the Lab Data Template.</div> <div> </div> <div>Below we provide a brief overview of the data files in the `additional folder` and their underlying purpose:</div> <div> <ul> <li>The <strong>Data Survey</strong> collects relevant project and data set information to set up a Data Management Plan. It can serve as an input for Lab Data Template development.</li> <li>The <strong>Lab Data Templates</strong> facilitate the collection of AMR research data (in vivo and in vitro) in several sub-tables. The Excel format is compatible with upload procedures into the data repository 'grit' and serves as input for a knowledge graph workflow.</li> <li>The <strong>Data dictionary</strong> is connected to the Lab Data Templates and ensures harmonized data entries. In addition, the dictionaries collect metadata beyond the content of the Lab Data Template (e.g. bacterial strain information or compound information) and link to ontologies where possible.</li> <li>The <strong>FAIR assessments</strong> have been used as a primer for improving the template. This report is generated using the FAIR-DSM model.</li> </ul> </div> <div>The templates have been used during the IMI2 GNA NOW project to collect information and have been improved according to FAIR standards in collaboration with the IMI FAIRplus project ("post FAIRification").</div>
A Corpus of Biblical Names in the Greek New Testament to Study the Additions, Omissions, and Variations across Different Manuscripts
<p>The analysis of textual variants of verses in the Ancient Greek New Testament across different manuscripts has mainly been done by close reading with manual effort. With the increasing number of transcriptions of the different manuscripts, quantitative analyses (so-called distant reading) can be used to search for patterns of omission, addition, or other variations, to formulate novel hypotheses to be investigated by close reading. In this work, we present a corpus of biblical names including spelling variation and inflections and their mentions in the transcriptions of the Ancient Greek New Testament.</p>
Citation analysis of Brown 1988 and Charnov 1976, for Figure 1 of manuscript "Halloween Charnov", Calcagno et al. 2023
<p>This contains the R script (bibliom.txt) and the ciatation data files (three .csv files) needed to generate Figure 1 in manuscript "Taking fear back into the Marginal Value Theorem: the risk-MVT and optimal boldness", by Calcagno, Gorgnard, Hamelin and Mailleret, 2023.</p>
Data accompanying the manuscript "Assessing the Probability of Extremely Low Wind Energy Production in Europe at Sub-seasonal to Seasonal Time Scales"
<p>This dataset contains time series of wind energy production aggregated over France and Europe, obtained from a 1000-year climate simulation from the CESM model (version 1.2.2, Hurrel et al. 2013), coupled to a simple energy model to compute grid-point capacity factor from surface wind. Wind power is then computed by multiplying the capacity factor by the installed capacity, taken from 5 e-Highway scenarios (X5, X7, X10, X13 and X16), and integrated over the regions of interest. More details about the climate simulation, wind energy model and installed capacity scenarios can be found in the associated manuscript, "Assessing the Probability of Extremely Low Wind Energy Production in Europe at Sub-seasonal to Seasonal Time Scales" (Cozian et al. 2023).</p><p>The data is organized into 10 files for France and 10 files for Europe. In each case, the 10 files correspond to 10 batches of 100 years each, with 3-hourly output. Each file contains 5 time series corresponding to the 5 installed capacity scenarios.</p><h4>References</h4><ul><li>Hurrell J W, Holland M M, Gent P R, Ghan S, Kay J E, Kushner P J, Lamarque J F, Large W G, Lawrence D, Lindsay K, Lipscomb W H, Long M C, Mahowald N, Marsh D R, Neale R B, Rasch P, Vavrus S, Vertenstein M, Bader D, Collins W D, Hack J J, Kiehl J and Marshall S (2013). The community earth system model: A framework for collaborative research. Bulletin of the American Meteorological Society, 94, 1339–1360. <a href="https://doi.org/10.1175/BAMS-D-12-00121.1">https://doi.org/10.1175/BAMS-D-12-00121.1</a></li><li>e-Highway 2050 (2015). Europe's future secure and sustainable electricity infrastructure. <a href="https://docs.entsoe.eu/baltic-conf/bites/www.e-highway2050.eu/results">https://docs.entsoe.eu/baltic-conf/bites/www.e-highway2050.eu/results</a></li><li>Cozian B, Herbert C and Bouchet F (2023). Assessing the Probability of Extremely Low Wind Energy Production in Europe at Sub-seasonal to Seasonal Time Scales. <a href="https://doi.org/10.48550/arXiv.2311.13526">https://doi.org/10.48550/arXiv.2311.13526</a></li></ul>
Dataset for manuscript titled "Exploring SureChEMBL from a drug discovery perspective".
<p>This is the data directory for running the code available on the GitHub repository for the manuscript titled "Exploring SureChEMBL from a drug discovery perspective<strong></strong>". The GitHub repository is available at <a href="https://github.com/Fraunhofer-ITMP/patent-clinical-candidate-characteristics">https://github.com/Fraunhofer-ITMP/patent-clinical-candidate-characteristics.</a></p>
ScienceDex guides
Understand access before you commit
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.