Find research datasets worth reusing

Dataset used in "Deep learning with multisite data reveals the lasting effects of soil type, tillage and vegetation history on biopore genesis"

Please see the paper "Deep learning with multisite data reveals the lasting effects of soil type, tillage and vegetation history on biopore genesis" how the images were captured, manual counting was performed, training datasets were prepared and models were trained.

Characterization of the material behavior and identification of effective elastic moduli based on molecular dynamics simulations of coarse-grained silica: dataset

Abstract: (from [1]) <blockquote> The addition of fillers can significantly improve the mechanical behavior of polymers. The responsible mechanisms at the molecular level can be well assessed by particle-based simulation techniques, such as molecular dynamics. However, the high computational cost of these simulations prevents the study of macroscopic samples. Continuum-based approaches, particularly micromechanics, offer a more efficient alternative but require precise constitutive models for all constituents, which are usually unavailable at these small length scales. In this contribution, we derive a molecular-dynamics-informed constitutive law by employing a characterization strategy introduced in a previous publication. We choose silicon dioxide (silica) as an exemplary filler material used in polymer composites and perform uniaxial and shear deformation tests with molecular dynamics. The material exhibits elastoplastic behavior with a pronounced anisotropy. Based on the pseudo-experimental data, we calibrate an anisotropic elastic constitutive law and reproduce the material response for small strains accurately.   The study validates the characterization strategy that facilitates the calibration of constitutive laws from molecular dynamics simulations. Furthermore, the obtained material model for coarse-grained silica forms the basis for future continuum-based investigations of polymer nanocomposites. In general, the presented transition from a fine-scale particle model to a coarse and  computationally efficient continuum description adds to the body of knowledge of molecular science as well as the engineering community.   </blockquote> Contact: Maximilian Ries Institute of Applied Mechanics Friedrich-Alexander-Universität Erlangen-Nürnberg Egerlandstr. 5 91058 Erlangen Software: All simulations were performed with LAMMPS [3], version: 29 Oct 2020 / 20201029 Compiled with Compiler: GNU C++ 4.8.5 20150623 (Red Hat 4.8.5-39) with OpenMP not enabled C++ standard: C++11 Active compile time flags: -DLAMMPS_GZIP -DLAMMPS_SMALLBIG Installed packages: CLASS2, KSPACE, MANYBODY, MC, MOLECULE, MPIIO, OPT, VORONOI, USER-INTEL, USER-MISC, USER-MOLFILE, USER-NETCD License: Creative Commons Attribution 4.0 International   Context: Data set supplementing  journal paper: [1] Ries, M.; Bauer, C.; Weber, F.; Steinmann, P. & Pfaller, S., "Characterization of the material behavior and identification of effective elastic moduli based on molecular dynamics simulations of coarse-grained silica", Mathematics and Mechanics of Solids, 2022, 108128652211080. This dataset contains the results presented in [1] and the necessary data to obtain those. Content: The files to reproduce our simulations and their results are structured as follows: <ul> <li>01_potentials tabulated potentials calibrated via iterative Boltzmann inversion in [2] kindly provided by the Müller-Plathe group at Technische Universität Darmstadt <ul> <li>Angle_table angular interactions</li> <li>Bond_table bond interactions</li> <li>Nonbond_table pair interactions</li> </ul> </li> <li>02_sample Lammps data file (molecular style) of the investigated silica sample</li> <li>03_simulations The condensed simulation directories with the naming convention given below are organized in the following subfolders: <ul> <li>01_time-proportional time-proportional simulation data</li> <li>02_time-periodic time-periodic simulation data</li> </ul> </li> </ul> Each simulation directory contains: <ul> <li>lammps input file (*.in) of the specific simulation</li> <li>input.prm: input parameters of the specific simulation (read by the input file)</li> <li>meta.info: meta data of the specific simulation run</li> <li>LAMMPS_out: simulation results (lammps thermo_out) in tabulated form, an overview of columns is given below <ul> <li>thermo_out.Dat: raw output</li> <li>thermo_out_SG.Dat: smoothed output (Savitzky-Golay filter)</li> <li>thermo_out_STD.Dat: standard deviation of raw output</li> </ul> </li> </ul> Naming convention: Silica-[deformation]-[direction]_[deformation function]-[deformation magnitude]_[deformation rate] ●    [deformation]: uniaxial tension (UT), simple shear (SS) ●    [direction]: deformation carried out in X/Y/Z (UT) or XY/XZ/YZ (SS) ●    [deformation function]: time-proportional (strain), time-periodic (strain_ampl) ●    [deformation magnitude]: maximum strain (time-proportional), strain amplitude (time-periodic); unitless ●    [deformation rate]: rate-[strain rate] (only time-proportional): 0.001/ns-0.1/ns Output quantities (columns of *.Dat files): ●    Step: time step ●    Time: time in fs ●    TotEng: total energy in kcal/mol ●    PotEng: potential energy in kcal/mol ●    KinEng: kinetic energy in kcal/mol ●    E_pair: pair energy in kcal/mol ●    E_bond: bond energy in kcal/mol ●    E_angle: angle energy in kcal/mol ●    E_dihed: dihedral energy in kcal/mol ●    Temp: temperature in K ●    Press: hydrostatic pressure in atm ●    Pxx: xx component of pressure tensor in atm ●    Pyy: yy component of pressure tensor in atm ●    Pzz: zz component of pressure tensor in atm ●    Pxy: xy component of pressure tensor in atm ●    Pxz: xz component of pressure tensor in atm ●    Pyz: yz component of pressure tensor in atm ●    Volume: volume of simulation box in (Angstroms)^3 ●    Lx: box length in x direction in Angstroms ●    Ly: box length in y direction in Angstroms ●    Lz: box length in z direction in Angstroms ●    Density: density in g/(cm^3) ●    c_RG: radius of gyration in Angstroms ●    c_RG[1]: squared radius of gyration tensor (xx component) in (Angstroms)^2 ●    c_RG[2]: squared radius of gyration tensor (yy component) in (Angstroms)^2 ●    c_RG[3]: squared radius of gyration tensor (zz component) in (Angstroms)^2 ●    c_RG[4]: squared radius of gyration tensor (xy component) in (Angstroms)^2 ●    c_RG[5]: squared radius of gyration tensor (xz component) in (Angstroms)^2 ●    c_RG[6]: squared radius of gyration tensor (yz component) in (Angstroms)^2 ●    c_bondave[1]: bond energy averaged over all atoms in kcal/mol ●    c_bondave[2]: bond distance averaged over all atoms in  Angstroms ●    c_bondave[3]: squared bond distance averaged over all atoms in (Angstroms)^2 ●    c_angleave[1]: angle energy averaged over all atoms in kcal/mol ●    c_angleave[2]: angle averaged over all atoms degree ●    c_angleave[3]: cosine of angle (unitless) ●    c_angleave[4]: squared cosine of angle (unitless) ●    c_MSD[1]: mean squared displacement x-direction in (Angstroms)^2 ●    c_MSD[2]: mean squared displacement y-direction in (Angstroms)^2 ●    c_MSD[3]: mean squared displacement z-direction in (Angstroms)^2 ●    c_MSD[4]: total mean squared displacement in (Angstroms)^2 ●    c_COM[1]: x coordinate of center of mass in Angstroms ●    c_COM[2]: y coordinate of center of mass in Angstroms ●    c_COM[3]: z coordinate of center of mass in Angstroms ●    v_strain_xx: xx component of engineering strain tensor (unitless)   ●    v_strain_yy: yy component of engineering strain tensor (unitless)    ●    v_strain_zz: zz component of engineering strain tensor (unitless)    ●    v_vMisesequivstress: von Mises equivalent stress in MPa ●    v_Cauchy_xx: xx component of stress tensor in MPa   ●    v_Cauchy_yy: yy component of stress tensor in MPa ●    v_Cauchy_zz: zz component of stress tensor in MPa ●    v_Cauchy_xy: xy component of stress tensor in MPa ●    v_Cauchy_xz: xz component of stress tensor in MPa ●    v_Cauchy_yz: yz component of stress tensor in MPa ●    v_strain_xy: xy component of engineering strain tensor (unitless)   ●    v_strain_xz: xz component of engineering strain tensor (unitless)   ●    v_strain_yz: yz component of engineering strain tensor (unitless)   References: [1] Ries, M.; Bauer, C.; Weber, F.; Steinmann, P. & Pfaller, S., "Characterization of the material behavior and identification of effective elastic moduli based on molecular dynamics simulations of coarse-grained silica", Mathematics and Mechanics of Solids, 2022, 108128652211080. [2] Ghanbari, A.; Ndoro, T. V. M.; Leroy, F.; Rahimi, M.; Böhm, M. C. & Müller-Plathe, F., “Interphase Structure in Silica-Polystyrene Nanocomposites: A Coarse-Grained Molecular Dynamics Study”, Macromolecules, 2012, 45, 572-584. [3] Plimpton, S., “Fast parallel algorithms for short-range molecular dynamics,” Journal of computational physics, 1995, 117, 1-19.

opencc-by-nc-4.0Oct 2021View details →

Dataset for: Effectiveness of rectal artesunate as pre-referral treatment for severe malaria in children under 5 years of age: a multi-country observational study

Dataset underlying the publication "Effectiveness of rectal artesunate as pre-referral treatment for severe malaria in children under 5 years of age: a multi-country observational study" (BMC Medicine) Data originating from the Community Access to Rectal Artesunate for Malaria (CARAMAL) Project, 2018-2021. Analysis of the health effect of the roll-out and administration of pre-referral rectal artesunate (RAS) in the Democratic Republic of the Congo, Nigeria and Uganda. Details provided in the publication.

Supporting Information for "From Hofmeister to hydrotrope: Effect of anion hydrocarbon chain length on a polymer brush"

This deposition contains the data and analysis (Jupyter notebooks) detailed in “From Hofmeister to hydrotrope: Effect of anion hydrocarbon chain length on a polymer brush”. All Jupyter notebooks have also been converted into PDF files for ease of viewing. All data and code (notebooks) required to reproduce the analysis can be found within the “supporting_data_analysis.zip” archive. This archive contains four sub-directories: <ul> <li>Computional_data <ul> <li>Optimised geometry files (.xyz) for all short chain fatty acid (SCFA) anion-solvent and anion-NIPAM fragment structures.</li> <li>Summary of analysed data (“SAPT_computational_data.xlsx”) describing the different interaction energies between a SCFA anion-NIPAM fragment and anion-solvent: electrostatic, exchange, induction, dispersion and total interaction energy contributions.</li> </ul> </li> <li>Ellipsometry <ul> <li>Data directory containing all raw ellipsometry data.</li> <li>“refellips_Dry.ipynb” and “refellips_Spectroscopic_SL.ipynb” notebooks to reproduce the analysis of a dry (solid-air) and hydrated (solid-liquid) polymer brush, respectively. </li> <li>A spatial map of the polymer brush used for spectroscopic ellipsometry data analysis: “PNIPAM_brush_spatial_map.png”.</li> <li>“Ellipsometry_sigmoid_fitting.ipynb” notebook and “Water_data.csv” file for the demonstration of the extraction of a thermotransition temperature from an ellipsometry dataset. Relevant plotting tools can be found in the <a href="https://github.com/refnx/refellips">refellips repo</a>.</li> </ul> </li> <li>Neutron_reflectometry <ul> <li>Data directory containing all relevant reduced reflectivity profiles from the Platypus reflectometry at ANSTO.</li> <li>“refnx_dry.ipynb”, “refnx_D2O.ipynb” and “refnx_SCFA_electrolytes.ipynb notebooks required to reproduce the analysis pertaining to a dry, polymer brush and a brush exposed to pure D2O and various SCFA electrolytes, respectively.</li> <li>Additional code required to model the hydrated polymer brush and various plotting tools can be in the <a href="https://github.com/igresh/refnxtoolbox">refnxtoolbox repo</a>.</li> </ul> </li> <li>QCMD_data <ul> <li>Data directory containing all processed QCM-D data (.csv)</li> </ul> </li> </ul>

Dataset: Complex effects of chytrid parasites on the growth of the cyanobacterium Planktothrix rubescens across interacting temperature and light gradients

This dataset contains the raw and processed data used in the manuscript "Complex effects of chytrid parasites on the growth of the cyanobacterium Planktothrix rubescens across interacting temperature and light gradients", by Wierenga et al. (preprint: https://doi.org/10.1101/2022.02.24.481659). An explanation of the experiment and measurements is found in the manuscript, and detailed descriptions of the data files are available in the "_file_description.txt" files inside each folder of the dataset.

openother-openAug 2022View details →

Fangxi-Xu/Succinate_Periodontitis: Targeting Succinate Receptor Effectively Inhibits Periodontitis

Periodontal disease (PD) is one of the most common inflammatory diseases in humans and is initiated by an oral microbial dysbiosis that stimulates inflammation and bone loss. Here, we report an abnormal elevation of succinate in the subgingival plaque of subjects with severe PD. Succinate activates the succinate receptor-1 (SUCNR1) and stimulates inflammation. We detected SUCNR1 expression in the human and mouse periodontium and hypothesize that succinate activates SUCNR1 to accelerate periodontitis through the inflammatory response. Administration of exogenous succinate enhanced periodontal disease, whereas SUCNR1 knockout mice were protected from inflammation, oral dysbiosis, and subsequent periodontal bone loss in two different models of periodontitis. Therapeutic studies demonstrated that a novel SUCNR1 antagonist inhibited inflammatory events and osteoclastogenesis in vitro and reduced periodontal bone loss in vivo. Our study reveals a previously unknown action of succinate in promoting periodontitis and provides a novel topical treatment for this disease. Any microbiome data and r code used for downstream analysis in the manuscript were deposited to this repository. Full Changelog: <a href="https://github.com/Fangxi-Xu/Succinate_Periodontitis/commits/microbiome">https://github.com/Fangxi-Xu/Succinate_Periodontitis/commits/microbiome</a>

The hydro-mechanical properties of fracture intersections: pressure dependant permeability and effective stress law

The present repository includes the raw permeability data presented in the manuscript submitted for publication in Journal of Geophysical Research: Solid Earth entitled The hydro-mechanical properties of fracture intersections: pressure-dependant permeability and effective stress law. The repository is presented as compressed folders named after the Figures of the manuscript where the data is presented.

opencc-zeroAug 2022View details →

dryad40/100

Quantifying the ecological impacts of alien aquatic macrophytes: A global meta‐analysis of effects on fish, macroinvertebrate and macrophyte assemblages

Biological invasions constitute a pervasive and growing threat to the biodiversity and functioning of freshwater ecosystems. Macrophytes are key primary producers and ecosystem engineers in freshwaters, meaning that alien macrophyte invasions have the capacity to alter the structure and function of recipient aquatic ecosystems profoundly. Although prevailing wisdom holds that alien macrophyte invasions tend to compromise freshwater ecosystem structure and function, the ecological impacts of alien macrophyte invasion have not been quantitatively reviewed to date. Here we present a global meta-analysis of 202 cases from 53 research articles, exploring the impacts of alien macrophyte invasion on the abundance and diversity of three ubiquitous and ecologically important focal groups, which together comprise the bulk of non-microbial freshwater biodiversity: resident macrophytes, macroinvertebrates and fish. Our synthesis includes data from all continents except Antarctica and Asia, covering 25 alien macrophyte species, but reveals considerable taxonomic and geographical biases in knowledge. Meta-analysis results reveal that invasion by alien macrophytes has an overall negative impact on taxonomic diversity of the three focal groups, but no consistent effect on abundance. At a finer resolution, we detect a strong negative effect of alien macrophyte invasion on resident macrophyte abundance and diversity, and a significant but smaller positive effect of submerged alien macrophyte invasion on macroinvertebrates. Effects on fish appear inconsistent. Our findings emphasise the importance of context- and taxon-specific ecological research in informing appropriate and proportionate management of alien macrophyte invasions, since alien macrophyte impacts are not consistently negative. We also identify significant geographical and taxonomic limitations in existing studies, quantitative data being lacking for many alien taxa.

A quantitative interphase model for polymer nanocomposites: Verification, validation, and consequences regarding size effects: dataset

Abstract: (from [1]) <blockquote> The enhanced mechanical behavior of polymer nanocomposites with spherical filler particles is attributed to the formation of matrix-filler interphases. The nano-scale leads to particularly high interphase volume fractions while rendering experimental investigations extremely difficult. Previously, we introduced a molecular dynamics-based interphase model capturing the crucial spatial profiles of elastic and inelastic properties inside the interphase. This contribution demonstrates that our model captures polymer nanocomposites’ essential characteristics reported from experiments. To this end, we thoroughly verify and validate the model before discussing the resulting local plastic strain distribution. Furthermore, we obtain a reinforcement in terms of the overall stiffness for smaller particles and higher filler contents, while the influence of particle spacing seems negligible, matching experimental observations in the literature. This paper proposes a methodology to unravel the underlying complex mechanical behavior of polymer nanocomposites and to translate the findings into engineering quantities accessible to a broader audience and technical applications. </blockquote>   Contact: Maximilian Ries Institute of Applied Mechanics Friedrich-Alexander-Universität Erlangen-Nürnberg Egerlandstr. 5 91058 Erlangen Software: Abaqus version R2018 License: Creative Commons Attribution 4.0 International   Context: Data set supplementing  journal paper: [1] Ries, M.; Weber, F.; Possart, G.; Steinmann, P. & Pfaller, S., “A quantitative interphase model for polymer nanocomposites: Verification, validation, and consequences regarding size effects”, Composites Part A: Applied Science and Manufacturing, 2022, 107094. This dataset contains the results presented in [1] and the necessary data to obtain those. Content: simulation folder denotation (“-” used instead of decimal points): distance_particles _ radius_particle _ thickness_ip _ num_ip _ length_box _ factor_el_length _ fraction_box_length _ switch_mat_ip with <ul> <li>    distance_particles: center distance of the nanoparticles in nm</li> <li>    radius_particle: radius of the nanoparticles in nm</li> <li>    thickness_ip: thickness of the interphase layers in nm</li> <li>    num_ip: number of interphase layers</li> <li>    length_box: box edge length in nm</li> <li>    factor_el_length: factor scaling the element length on the arcs of the interphase layers (element length = factor_el_length * thickness_ip)</li> <li>    fraction_box_length: matrix element length = length_box / fraction_box_length</li> <li>    switch_mat_ip: if = 0: interphases are assigned their actual material properties, if = 1: interphases are assigned the material properties of the bulk</li> </ul>                                                           each simulation folder contains the following file types: <ul> <li>    .cae: Abaqus model database, containing parts, meshes, loads, etc.</li> <li>    .dat: Printed output from the analysis input file processor, as well as printed output of selected results written during the analysis</li> <li>    .inp: Analysis input file</li> <li>    .log: Log file, which contains start and end times for modules run by the current execution procedure</li> <li>    .msg: Diagnostic or informative messages about the progress of the solution</li> <li>    .odb: Output database containing all results data from an Abaqus analysis</li> <li>    .sta: Status file with increment summaries</li> </ul> folder structure: <ul> <li>Standard_case: simulation folders of the standard close (particle center distance: 5.1776 nm) and distant (particle center distance: 7.9481 nm) cases (particle radius: 2 nm, filler content 0.054 vol.%, number of interphase layers: 4, factor_el_length: 1.0) and further particle center distances</li> <li>Layers: simulation folders with different numbers of interphase layers, i.e., different values for num_ip,  based on the standard close and distant cases <ul> <li>Close_case</li> <li>Distant_case</li> </ul> </li> <li>Mesh: simulation folders with different mesh qualities, i.e., different values for factor_el_length, based on the standard close and distant cases <ul> <li>Close_case</li> <li>Distant_case</li> </ul> </li> <li>Particle_size: simulation folders with different particle sizes <ul> <li>2_nm: simulation folders with particle surface distance 2 nm <ul> <li>vol_ratio_0-00054: simulation folders with filler content 0.054 vol.%</li> <li>vol_ratio_0-0075: simulation folders with filler content 0.75 vol.%</li> </ul> </li> <li>4_nm: simulation folders with particle surface distance 4 nm <ul> <li>vol_ratio_0-00054: simulation folders with filler content 0.054 vol.%</li> <li>vol_ratio_0-0075: simulation folders with filler content 0.75 vol.%</li> </ul> </li> <li>8_nm: simulation folders with particle surface distance 8 nm <ul> <li>vol_ratio_0-00054: simulation folders with filler content 0.054 vol.%</li> <li>vol_ratio_0-0075: simulation folders with filler content 0.75 vol.%</li> </ul> </li> </ul> </li> </ul>

Cross-boundary effects of human impacts on animal assemblages

Data describing the abundance of coastal vertebrates and fish across 100 sites surveyed twice over two years on the Sunshine coast in eastern Australia.

opencc-by-4.0Dec 2021View details →

16S Phyloseq R object accompanying the paper: Effects of storage methods on total bacterial count and microbial composition of bovine colostrum

This ready to load phyloseq R S4 object contains the ASV table, taxonomy table and sample metadata (16S V3-V4). This data was build using the DaDa2 (version 1.12.1) and phyloseq (version 1.32) R packages using our raw Illumina MiSeq PE300 sequencing data deposited at NCBI-SRA under BioProject: PRJNA872909. The accompanying (peer-reviewed) scientific article can be found here:  <ul> <li>https://www.todo</li> <li>DOI: todo</li> </ul>   Study/draft abstract: Lisa Robbers, Hannes Bijkerk,  Lars Ravesloot, Alex Bossers, Mirjam Nielen, Ruurd Jorritsma, Ad Koets, Lindert Benedictus Neonatal calves need to acquire passive immunity through maternal colostrum, as they are immunologically naïve and the structure of the bovine placenta does not allow passage of maternal antibodies during pregnancy. Milked colostrum is not initially sterile and may even contain high bacterial counts. Minimizing total bacterial counts in colostrum is generally advised, however bacterial quality of colostrum comprises more than just bacterial quantities, but also depends on the specific bacteria present. While duration and temperature of colostrum storage are known to affect total plate counts (TPC), less is known about the effects of storage on the actual bacterial composition of the TPC. We speculated that, depending on the storage conditions, colostrum is a substrate in which certain bacterial species can thrive affecting the quality of colostrum. We therefore aimed to characterize the effects of different colostrum storage methods on the composition of the viable, aerobic, microbial community. Colostrum samples were stored at different temperatures and for different durations. Next, bacterial growth was assessed using the aerobe plate count culture method, followed by 16S rRNA gene amplicon sequencing. Differences in the TPC bacterial compositions of the stored colostrum samples, as determined by 16S rRNA gene amplicon sequencing, were mostly explained by the variation in bacterial composition of the colostrum sample directly after milking. In line with earlier studies, the results from our study show that the TPC increased when colostrum was stored for 24 hours at room temperature, but not when stored in a refrigerator for the same duration. Community structure of the TPC of colostrum stored at room temperature for 24 hours and stored in a refrigerator for a week was significantly different from the baseline samples. The 16S rRNA sequencing results indicate this is because of increased numbers of Enterobacteriaceae. Enterobacteriaceae abundance in refrigerated samples seemed to remain stable for the first 24 hours, but increased drastically after one week. The results indicate that microbial composition of stored colostrum is mostly influenced by the composition of the colostrum sample directly after milking, which is most probably the result of contamination or other environmental influences during the milking process. This study provides a deeper insight in the changes in the microbial composition of colostrum TPC during practical storage conditions and provides a primer for more detailed research into the determinants of bacterial composition of colostrum and the linked health effects.

Data depository - "Quantifying the effect of wind on volcanic plumes: implications for plume modelling"

This depository contains all data to understand, evaluate, and build upon the research reported in the manuscript: "Quantifying the effect of wind on volcanic plumes: implications for plume modelling", submitted to Journal of Geophysical Research. Abstract The considerable effects that wind can have on estimates of mass eruption rates (MERs) in explosive eruptions based on volcanic plume height are well known but difficult to quantify rigorously. Many explicitly wind-affected plume models have the additional difficulty that they require the use of centerline heights of bent-over plumes, a parameter not easily obtained directly from observational data. We tested two such models by using the time series of varying plume heights and wind speeds of the 2010 Eyjafjallajökull eruption. The mapped fallout and photos taken during this eruption allow us to estimate the plume geometry and to empirically constrain input parameters for the two models tested. Two strategies are presented to correct the difference in maximum plume height and centerline height: (i) based on plume radius, and (ii) by using the plume type parameter ∏, which quantifies the relative influence of buoyancy and cross-wind on the plume dynamics, to discriminate weak, intermediate and strong plumes. The results indicate that it may be more appropriate to classify plumes as either wind-dominated, intermediate or buoyancy-dominated, where the relative effects of both wind and MER define the type. The analysis of the Eyjafjallajökull data shows that the MER estimates from both models are considerably improved when a plume-type dependent centreline-correction is applied and the wind entrainment coefficient β is refined. For this particular eruption, we find that the best value for β lies between 0.22 and 0.34, unlike previous suggestions that set this parameter to 0.50.

opencc-by-4.0Oct 2020View details →

The cost of self-promotion: Ecological and demographic implications of the mentor effect in natural Taraxacum populations

This data accompanies the pending publication "The cost of self-promotion: Ecological and demographic implications of the mentor effect in natural Taraxacum populations" by Lynn et al. The work is also published under Austin Lynn's PhD Dissertation, which is under embargo until 2022.

Supplementary audio files: Propagation effects in the synthesis of wind turbine noise

The audio files are supplementary files required for the audio article titled: "Propagation effects in the synthesis of wind turbine noise". Each audio file refers to a signal of a test obtained from the wind turbine noise model which is described in the article.  The audio files can be read as:      NNx-x-TETIN-eeeeeee.mp3 NNx-x refers to the Test case and case number for the syntheisized trailing edge and turbulent inflow noise, eeeeeee is the description of the specific case. (tauTT- angle of the receiver, ff - for free field, GPE for ground and propagation effects included, GPE_Turb for ground and propagation effects included with turbulence scattering) eg: C2-2-TETIN_tau80_GPE_Turb.mp3 is the synthesized sound for Test case C2-2 in the article which includes the ground and propagation effects and also scattering due to turbulence. The receiver is at an angle of 80° with respect to the wind direction.

Tracking the photomineralization mechanism in irradiated lab-generated and field-collected brown carbon samples and its effect on cloud condensation nuclei abilities

Data set of the data presented in figures and tables in our manuscript on the photomineralization of brown carbon samples: ammonium sulfate-methylglyoxal solutions, Suwannee River fulvic acid isolates, firewood smoke and ambient aerosols from Padua, Italy.

Model output data for Smith et al., "Effects of increasing the category resolution of the sea ice thickness distribution in a coupled climate model on Arctic and Antarctic sea ice"

Model output data for Smith et al., "Effects of increasing the category resolution of the sea ice thickness distribution in a coupled climate model on Arctic and Antarctic sea ice", in review in Journal of Geophysical Research-Oceans, 2022. Details on CESM model settings and run setups can be found within the manuscript.

Raw Datasets of: "Evaluating the Cost-Effectiveness of Plastic Surgery Based on the Satisfaction with Quality of Life and Nasolabial Appearance in Thai Preteens with Cleft Lip and Palate"

A cross-sectional study with 30 Thai preteen CLP patients aged between 8 to 12-year-old was undertaken between 2017 and 2019 at Tawanchai center. Their satisfaction with QoL was reflected through an interview and a questionnaire with the cooperation of their parents as their caregivers while satisfaction with their nasolabial appearance was from the evaluation of five experts who compared their photos with those of normal faces to determine correlation values of the nasolabial appearance from 5-rating scales using Fleiss’s kappa coefficient scores.

Dataset for "Air-sea interactions on Titan: effect of radiative transfer on the lake evaporation and atmospheric circulation"

These documents are supplements to the "Air-sea interactions on Titan: effect of radiative transfer on the lake evaporation and atmospheric circulation" paper published by the same authors in The Planetary Science Journal in 2022. Are made available: -the Supporting Information document on the performed sensitivity study, "paper_mtWRF_lake_RT_220825_SI.pdf" -the Fortran source code of the radiative transfer module developed for this work, "module_ra_gray.F" -all the netCDF simulation outputs and a list describing their parameters, "run-##.nc.gz" "list_simulations_2D_paper2022_RT_zenodo.pdf" -the Python codes to plot figures from the netCDF output files, "mtwrf_analysis_#D_#.py"

opencc-zeroSep 2022View details →

dryad40/100

Data associated with: Emergence of the physiological effects of elevated CO2 on land-atmosphere exchange of carbon and water

Elevated atmospheric CO2 (eCO2) influences the carbon assimilation rate and stomatal conductance of plants and thereby can affect the global cycles of carbon and water. Yet, the detection of these physiological effects of eCO2 in observational data remains challenging, because natural variations and confounding factors (e.g., warming) can overshadow the eCO2 effects in observational data of real-world ecosystems. In this study, we aim at developing a method to detect the emergence of the physiological CO2 effects on various variables related to carbon and water fluxes. We mimic the observational setting in ecosystems using a comprehensive process-based land surface model QUINCY to simulate the leaf-level effects of increasing atmospheric CO2 concentrations and their century-long propagation through the terrestrial carbon and water cycles across different climate regimes and biomes. We then develop a statistical method based on the signal-to-noise ratio to detect the emergence of the eCO2 effects. The signal in gross primary production (GPP) emerges at relatively low CO2 increase (Δ[CO2] ~ 20 ppm) where the leaf area index is relatively high. Compared to GPP, the eCO2 effect causing reduced transpiration water flux (normalized to leaf area) emerges only at relatively high CO2 increase (Δ[CO2] >> 40 ppm), due to the high sensitivity to climate variability and thus lower signal-to-noise ratio. In general, the response to eCO2 is detectable earlier for variables of the carbon cycle than the water cycle, when plant productivity is not limited by climatic constraints, and stronger in forest-dominated rather than in grass-dominated ecosystems. Our results provide a step toward when and where we expect to detect physiological CO2 effects in in-situ flux measurements, how to detect them and encourage future efforts to improve the understanding and quantification of these effects in observations of terrestrial carbon and water dynamics.

Reproduction package for the paper "The effects of surface fossil magnetic fields on massive star evolution: IV. Grids of models at Solar, LMC, and SMC metallicities"

This is a reproduction package for the paper "The effects of surface fossil magnetic fields on massive star evolution - IV. Grids of models at Solar, LMC, and SMC metallicities" by <a href="https://doi.org/10.1093/mnras/stac2598">Keszthelyi et al. (2022).</a>