Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
91,407
datasets available to search
ShareScore release 0.9.0
Dataset results
91,407 results for “Effects With / Effects Of”
Supplementary Material of the Manuscript: "The effects of blank size and knapping strategy on the estimation of core's reduction intensity"
<p>This repository hosts the R-markdown and dataset that allow reproducibility and replicability of the statistical analyses implemented in the paper: Lombao, D., Cueva-Temprana, A., Rabuñal, J.R., Morales, J.I., Mosquera, M. The effects of blank size and knapping strategy on the estimation of core’s reduction intensity. <em>Archaeol Anthropol Sci</em> <strong>11</strong>, 5445–5461 (2019). https://doi.org/10.1007/s12520-019-00879-4<br> For further information, please open first the readme.txt. document.</p>
The effects of visual distractors on serial dependence
<p>Datasets and analysis script for two experiments on behavioral serial dependence, using discrimination & orientation adjustment tasks.<br> The datasets are used and described in:<br> Title: "The effects of visual distractors on serial dependence"<br> Authors: Christian Houborg, David Pascucci, Ömer Daglar Tanrikulu & Árni Kristjánsson<br> Year: 2023<br> Journal: Journal of Vision<br> The link and DOI to the related paper will be available soon.</p>
Direct and indirect effects of climate and land use change on food webs in lakes and streams
<p>Here, we provide the data and code necessary to reproduce the workflow and analysis in: Barbosa and Siqueira. Direct and indirect effects of climate and land use change on food webs in lakes and streams. A preprint is available at https://doi.org/10.1101/2022.04.18.488700</p> <p>We compiled multicontinental data to investigate how climate and land use change are related to the structure of freshwater food webs, considering the inherent differences in lentic and lotic ecosystems. We analyzed the direct and indirect relationships between land use intensity, and temperature and precipitation changes, and food webs using multi-group structural equation modeling. Freshwater food webs were obtained from three sources: the Mangal interaction database, using the rmangal package in R, the GlobAl databasE of traits and food Web Architecture (GATEWAY) version 1.0, and the Interaction Web Data Base (IWDB). We also included food webs acquired from a search in the Web of Science Core Collection. Land use data was compiled from the global ESA CCI database, an annually generated land cover product at 300 m resolution for the period 1992 – 2015. Climate data was compiled from the TerraClimate database, a monthly generated product for climate and climatic water balance for global terrestrial surfaces at ~ 4 km for the period 1958 – 2015. </p>
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"
<p>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)</p>
Compton y-parameter map of thermal SZ effect from Planck PR4 data
<p>This dataset hosts the results and processing data from the paper "An improved Compton parameter map of thermal Sunyaev-Zeldovich effect from Planck PR4 data", <a href="https://doi.org/10.1093/mnras/stad3156">https://doi.org/10.1093/mnras/stad3156</a>. Please cite this paper, should you use this data.</p> <p>Contact: <a href="mailto:chandran@ifca.unican.es">chandran@ifca.unican.es</a></p> <p>UPDATED FITS HEADER.</p>
Effects of life stage on the sensitivity of Folsomia candida to four pesticides
<p>This submission provides R-code and data files for our peer-reviewed work.</p><p>The R-notebook "Analysis_likelihood_ratio_test" contains the code used to estimate the parameters of concentration-response curves (EC10, EC50, LC10, LC50, and slopes) and perform likelihood ratio tests to compare curves from different tested life stages.</p><p>The R-notebook "Figures_Concentration_response_curves" showcases the code used to generate the figures presented in the manuscript.</p><p>The dataset files are provided in CSV format with Comma Separated Values:</p><ul><li>Cyproconazole_FolsomiaCandida_10days_20days_RawData_New.csv</li><li>Imidacloprid_FolsomiaCandida_10days_20days_RawData_New.csv</li><li>Teflubenzuron_FolsomiaCandida_10days_20days_RawData_New.csv</li><li>Thiacloprid_FolsomiaCandida_10days_20days_RawData_New.csv</li></ul><p>The submission includes the following:</p><ul><li>R files: R notebooks described above.</li><li>CSV files: Count data of springtail juveniles and adults.</li></ul><p> </p><p>This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 859891.</p><p>This publication reflects only the authors' view and the European Commission is not responsible for any use that may be made of the information it contains.</p>
Non-identical moire twins in bilayer graphene revealed by valley Hall effect measurements
<p>The superlattice obtained by aligning a monolayer graphene and boron nitride (BN) inherits from the hexagonal lattice a sixty degrees periodicity with the layer alignment. It implies that, in principle, the properties of the heterostructure must be identical for 0$^{\circ}$ and 60$^{\circ}$ of layer alignment. Here, we demonstrate, using dynamically rotatable van der Waals heterostructures, that the moir\'e superlattice formed in a bilayer graphene/BN has different electronic properties at 0$^{\circ}$ and 60$^{\circ}$ of alignment. Although the existence of these non-identical moir\'e twins is explained by different relaxation of the atomic structures for each alignment, the origin of the observed valley Hall effect remains to be explained. A simple Berry curvature argument do not hold to explain the hundred and twenty degrees periodicity of this observation. Our results highlight the complexity of the interplay between mechanical and electronic properties on moir\'e structure and the importance of taking into account atomic structure relaxation to understand its electronic properties.</p>
Dataset: Green light during incubation: effects on hatching characteristics in brown and white laying hens
<p>Dataset used for the paper "Green light during incubation: effects on hatching characteristics in brown and white laying hens".<br> <br> Abstract:</p> <p>Providing light during incubation is being investigated as a method to improve welfare in later life in poultry. This incubation method would more closely approximate chicken natural environment compared to the current incubation in darkness. Previous studies showed promising results of light during incubation on broiler welfare, but little is known about effects of light during incubation on laying hens. Especially, information about its effects on hatching characteristics (hatch time, hatchability, chick quality, body weight and embryonic age of death) is scarce and requires investigation in both white and brown egg layers. In the current study, Dekalb White (DW) and ISA Brown (ISA) eggs were incubated in complete darkness (dark) or in a light:dark cycle of 12L:12D throughout incubation (light), resulting in four treatment groups: DW-dark, DW-light, ISA-dark, and ISA-light. In the light treatments, green LEDs of 520nm wavelength were used, at an intensity of 400 lux. First, light transmission through the eggshell was measured through 27 eggs. Then, an analysis of the effects of light during incubation on hatching characteristics was performed on 711 chicks in two consecutive experimental rounds. Light transmission was higher through white eggshells than through brown eggshells (N = 27, p < 0.001). Light during incubation had no effects on hatching characteristics (N = 711, p ≥ 0.1). Despite the difference of light transmission through eggshell between hybrids, there was no interaction between incubation treatment and hybrid on hatching characteristics (N = 471, p ≥ 0.06). Hatch time was longer and navel quality was better in DW than in ISA, while body weight and embryonic age of death were lower in DW than in ISA (all p < 0.001). Males and females had similar chick quality scores except for the beak quality, which was better for males (N = 486, p = 0.003). To conclude, green light during incubation did not negatively affect hatching characteristics in either DW nor ISA laying hen hybrids. Future research should therefore focus on its potential benefits for laying hen welfare.</p>
Datasets for "Placebo effects of transcranial direct current stimulation on motor skill acquisition"
<p>The following two .csv files contain the participant level data for the primary analyses conducted within the research study:</p> <p>"Placebo effects of transcranial direct current stimulation on motor skill acquisition"</p> <p>Data are formatted in long format for ease of analysis</p> <p>Dataset used in first analysis - Estimation of TDCS effect and Placebo effect including a NO TDCS control group</p> <p>ALLGROUPS.csv</p> <p>subid = Participant specific identifier<br> Age = Participant age in years<br> Sex = Participant sex (M/F)<br> RASex = Sex of research assistant that conducted the study for the participant<br> TrialNum = Trial number for the reaching task<br> Performance = Total trial time of the trial in seconds<br> AssignGrp = Group participant was assigned: Active = Active TDCS, Sham = Sham TDCS, Ctrl = No TDCS</p> <p>Dataset used in second analysis - Estimation of expectancy effects on Performance among TDCS groups ONLY</p> <p>TDCSGroupsONLY.csv</p> <p>subid = Participant specific identifier<br> Age = Participant age in years<br> Sex = Participant sex (M/F)<br> RASex = Sex of research assistant that conducted the study for the participant<br> TrialNum = Trial number for the reaching task<br> Performance = Total trial time of the trial in seconds<br> AssignGrp = Group participant was assigned: Active = Active TDCS, Sham = Sham TDCS, Ctrl = No TDCS<br> PostExp = Expectancy score post practice<br> PreExp = Expectancy score pre practice<br> Suggestibility = Suggestibility score<br> Prior Know = Prior knowledge of TDCS (Yes/No)<br> Prior Study = Participation in a study using TDCS (Yes/No)</p>
Seasonal controls override forest harvesting effects on the composition of dissolved organic matter mobilized from boreal forest soil organic horizons
<p>Dataset comprised of nutrient fluxes (DOC, TDN, NH4, TDN and SRP), optical parameters related to DOM composition (SUVA, spectral slopes and slope ratio), pH, and other nutrient and elemental ratios for passive pan lysimeters installed across terrestrial sites in Pynn's Brook, Newfoundland.</p>
Three-component modelling of O-rich AGB star winds I. Effects of drift using forsterite – dataset
<p>The data provided here include all parameter files, log files, and a set of the<br> binary output files that are the basis for the publication in A&A.</p> <p>The file 'file_listing.txt' contains a complete list of files and directories<br> in all gzipped tar files. Each individual gzipped tar file is formatted as<br> follows:</p> <p> Mm.m_Ll.ll_Ttttt.tar.gz</p> <p>where<br> m.m :: the assumed mass of the model, in solar masses<br> l.ll :: The assumed luminosity, in log10(solar luminosities)<br> tttt :: The effective temperature of the star, in Kelvin.</p> <p><br> The contents of the tar files vary according to the model, but here is the<br> general directory structure:</p> <p> nodr/ :: non-drift / PC models<br> drift/ :: drift models</p> <p> nodr/init<br> drift/init :: Initial model files created using John Connor.</p> <p><br> File suffixes are the following:</p> <p> .par :: Plain-text parameter file that contains all parameters that are<br> different from the respective default value in the model.<br> Consequently, to see what parameters were actually used, it is<br> necessary to look in the log file (see below).</p> <p> .bin :: Binary file that contains output of converged models. Each model is<br> stored in two versions, first the previous time step and then the<br> current time step (having access to the model code T-800, data of both<br> time steps are needed to restart model calculations at that time<br> step).</p> <p> The initial model file only contains one model; where the previous<br> time step data are the same as the current time step data.</p> <p> We provide a tool to read this file, see below.</p> <p> Note! These files can get pretty large and are therefore only<br> available for a smaller number of the models in the Zenodo dataset.<br> Please ask the corresponding author for the missing files is the<br> need should appear.</p> <p> .log :: Plain-text log file that shows the used model parameters and a number<br> of key properties for each converged model.<br> The encoding of this file is UTF-8.</p> <p> .inf :: Plain-text secondary log file that contains the header of the<br> [primary] log file as well as timing information.<br> The encoding of this file is UTF-8.</p> <p> .tpb :: Secondary binary file that contains a number of properties specified<br> at the outer boundary, typically for each consecutive time step.</p> <p> We provide a tool to read this file, see below.</p> <p> .lis :: Plain-text file with the iteration history. Unavailable here.</p> <p> .liv :: Plain-text file with values specified for a number of properties at<br> each gridpoint. Unavailable here.</p> <p> .inp :: Plain-text file that is used to launch a model; some are present.<br> This file is automatically generated by the tool that launches T-800<br> and is typically removed when T-800 launches. Unavailable here.</p> <p> .eps :: Encapsulated PostScript file created by John Connor when calculating<br> the initial model.</p> <p><br> Model evolution structure - file endings before the suffix:</p> <p> _rlx :: Files related to relaxing the T-800 calculations on the initial model<br> created by John Connor.</p> <p> _exp :: Files related to expanding the initially compact model to using the<br> full radial domain.</p> <p> _fix :: Files related to the intermediate stage where calculations are changed<br> from expansion to outflow.<br> <br> _out :: Files related to the outflow stage of the calculations; this is what<br> you want to look at to see the wind evolution. Results in the paper<br> are calculated using these data.</p> <p> Note! Some outflow stage calculations continue the evolution of the previous<br> set of files. The underlying reason for continued calculations is typically<br> that the calculated time interval is too short. Such files are typically<br> given the extension '_cont.lin_out', '_cont2.lin_out', etc.</p> <p><br> Stored data in the binary files:</p> <p> The binary files (suffix '.bin') contain the full radial structure in the<br> following 10 (PC models) or 11 (drift models) primary variables:</p> <p> mr: radius<br> mm: integrated [gas] mass<br> md: gas density<br> mu: gas velocity<br> me: internal energy<br> mj: radiative energy<br> mh: radiative flux<br> n0: dust moment, forsterite (Fo)<br> nm: number density of magnesium atoms<br> ns: number density of silicon atoms<br> v0: dust velocity, forsterite (only drift models)</p> <p> Other properties are derived from these primary variables using auxiliary code<br> that isn't part of this dataset.</p> <p><br> Load files:</p> <p> Two tools are provided here that can load the binary data files using the<br> Interactive Data Language (IDL):</p> <p> sc_load_bin (for files with the suffix '.bin'):</p> <p> Loads the full content of a T-800 binary file and returns a structure<br> with the data.</p> <p><br> sc_load_tpb (for files with the suffix '.tpb'):</p> <p> Loads the full content of a T-800 'tpb' binary file and returns a<br> structure with the data.</p> <p> Note! Due to the way models run on clusters, this file is sometimes<br> incomplete; this happens when the model code T-800 is stopped as the<br> cluster-specific walltime is reached. If this is the case, it is<br> necessary to use the binary file instead, where data are saved<br> typically every 20:th time step.</p> <p> Alternative tools for use with Python and Julia could be considered for<br> writing, but where not yet available when this dataset was made public.<br> Please contact the corresponding author for a current status on this issue.</p> <p> </p>
Data for the publication "Future warming exacerbated by aged soot effect on cloud formation"
<p>This repository contains the data for the paper:</p> <p>"Ulrike Lohmann, Franz Friebel, Zamin A. Kanji, Fabian Mahrt, Amewu A. Mensah and David Neubauer: Future warming exacerbated by aged soot effect on cloud formation. <em>Nat. Geosci.</em> <strong>13, </strong>674–680 (2020). https://doi.org/10.1038/s41561-020-0631-0"</p> <p>Each tar-file contains the data (or instructions how to obtain the data) to reproduce a figure or table in our paper.</p> <p>Note that the scripts to plot this data are to be found in the accompanying package (http://dx.doi.org/10.5281/zenodo.3457878)</p> <p>Also note that Extended Data Fig. 1 is identical to Supplementary Fig. S4 as well as that Extended Data Table 1 is identical to Supplementary Table S2.</p>
Dataset for Automatic Refactoring Candidate Identification Leveraging Effective Code Representation
<p>The dataset consists of positive and negative case methods for Extract Method refactoring for selected GitHub repositories.<br> <br> <em>Each sample format - </em></p> <pre><code class="language-json">{ "repo_name": "...", "repo_url": "...", "positive_case_methods": ["...", "...", ...], "negative_case_methods": ["...", "...", ...] }</code></pre> <p> </p>
The effect of a political crisis on performance of community- and state-managed forests in Madagascar
<p>Data associated with paper: "The effect of a political crisis on performance of community forests and protected areas in Madagascar"</p> <p>For code and selected tabular data outputs, also see: https://github.com/raenb0/madagascar</p> <p>Includes a number of files with raster (tif) data. All data is for Madagascar:</p> <p>⦁ for2000.tif is forest cover in the year 2000<br>⦁ for2000_0.tif is the same as above but contains 0 values instead of NA values (better for analysis)<br>⦁ defor_year_90m is annual deforestation as a proportion of each 90 m pixel that is deforested, values range from 0-1.</p> <p>data on all time-invariant covariates used for matching, including:<br>⦁ dist_cart (distance from cart tracks, meters)<br>⦁ dist_road (distance from roads, meters)<br>⦁ dist_urb (distance from villages, meters)<br>⦁ dist_urb (distance from urban centers, meters)<br>⦁ dist_vil (distance from villages, meters)<br>⦁ edge_05 (distance from forest edge in 2005, meters)<br>⦁ elev (elevation, meters)<br>⦁ q1_materials (index of self-reported development level, based on material assets)<br>⦁ rain (average precipitation 1970-2000, mm)<br>⦁ rice (rice suitability, 0 for unsuitable or 1 for suitable)<br>⦁ slope (slope, meters)<br>⦁ v7_security (self-reported indicator of security and risk of theft)<br>⦁ veg_type (vegetation type, 1= eastern humid forest, 2= western deciduous forest, 3 = southern dry spiny forest)</p> <p>time-variant covariates include (for years 2005-2020):<br>⦁ distance_year (distance from forest edge of each forest pixel, in meters, in each year)<br>⦁ drght_year (drought severity, Palmer Index Score)<br>⦁ pop_year (human population density, people per sq km)<br>⦁ precip_year (maximum accumulated precipitation, mm)<br>⦁ rice_av_year (annual average rice prices, in USD)<br>⦁ rice_sd_year (standard deviation of rice price, in USD)<br>⦁ temp_year (maximum annual temperature, degrees C)<br>⦁ wind_year (maximum annual windspeed, meters/sec)</p> <p>Shapefile polygons for Community Forest Managed areas (CFM) and protected areas administered by Madagascar National Parks can be requested from the corresponding author: ran63 (at) cornell (dot) edu</p> <p>Shapefile polygons for protected areas in Madagascar are available from the World Database of Protected Areas: https://www.protectedplanet.net/country/MDG</p>
Needle Langmuir Probe - guard and boom effects
<p>The dataset includes two distinct simulation setups named "LG_experiment" and "RG_RP_experiment". A detailed explanation of the datasets is given in the article "Effects of Guard and Boom on Needle Langmuir Probes Studied With Particle in Cell Simulations"</p> <p> </p> <p>The naming convention of the included folders is a description of the simulation contained within with the convention following the order: probe length (Lp) probe radius (Rp) length of guard (Lg) guard radius (Rg) probe voltage (Vp) boom voltage (Vb). Each descriptor has a numeric value with three numbers where the last is the first decimal, eg 010 corresponds to 1.0. All lengths are given in Debye Lengths.</p> <p> </p> <p>The LG_experiment is a simulation setup where all parameters are fixed except the guard length, to investigate the effects of the guard length on the cylindrical Langmuir probe.</p> <p> </p> <p>The RG_RP_experiment is a simulation setup where all parameters are fixed except the guard radius, to investigate the effects of the guard radius on the cylindrical Langmuir probe. Two guard radii are included.</p> <p> </p> <p>Each simulation folder contains three data files. The pictetra.hst file which is the history of the probe-guard-boom system. The index values 0,1,2 correspond to the probe,guard and boom respectively. (see the included plot.py). The scc*.vtk files contain surface values on the probe-guard-boom system, and the pictetra*.vtk files contain plasma values through the simulated domain.</p> <p> </p> <p>A minimal python example for plotting the currents is included in the file "plot.py".</p>
Elevated temperature effects on animal personality: hormonal stress response underlying behavioural differences in the American bullfrog
<p>Dataset for research paper submitted to Animal Behaviour</p> <p>Behavioural_data.csv: raw data for how individual bullfrogs performed in six different trials on an 8-arm maze before and after they were submitted to thermal stress. Behaviours analyzed: movements against the wall of the maze, posture changes, total ambulatory distance (m), and time on the centre of the arena (s).</p> <p>Hormone_data.csv: raw hormone (corticosterone and testosterone) data collected from individual bullfrogs in four different time points: baseline, 12 hours after stress, 24 days after stress, and 47 days after stress.</p> <p>Mass_data.csv: raw mass data collected from individual bullfrogs at the beginning and end of the experiment. SVL = snout-vent length. Body index is calculated as the residuals of a linear regression between mass as dependent variable and SVL as independent variable.</p>
Dataset for "Joint optimization of land carbon uptake and albedo can help achieve moderate instantaneous and long-term cooling effects"
<p>Data and Code for 'Joint optimization of land carbon uptake and albedo can help achieve moderate instantaneous and long-term cooling effects' by Graf et al. (Communications Earth and Environment)</p>
The effect of dietary bioactive on gut microbiome diversity (DIME) – a pilot study
<p>The DIME study consists of a randomised 2x2 cross-over human intervention where healthy participants (n = 20) are subjected to a diet high in bioactive-rich food for two weeks and a diet low in bioactive-rich food. There is a four-week washout between the two interventions. </p> <p>The continuous glucose monitoring was achieved using the Abbott freesylte libre flash glucose device. The baseline of the participants were determined 7 days before the start of the intervention, followed by the first arm and second arm. The period between the two arms (washout) was not recorded.</p> <p>We also included sleep data which consists of the amount of time spent in bed and during that time the amount of time spent in light, deep and rem in all 20 participants during the course of the dietary intervention, both the high and low bioactive diet. that was captured using Fitbit wearables during both stages of the dietary intervention,</p>
Database generated to analyze the effects of a nonadiabatic wall on hypersonic shock/boundary-layer interactions
<p>This dataset was generated to analyze the effects of a nonadiabatic wall on hypersonic shock/boundary-layer interactions and is related to the following publication:</p> <p>Volpiani, P. S., Bernardini, M., & Larsson, J. (2020). Effects of a nonadiabatic wall on hypersonic shock/boundary-layer interactions. <em>Physical Review Fluids</em>, <em>5</em>(1), 014602.</p> <p>The database contains instantaneous and statistical fields of hypersonic boundary layers and shock/boundary-layer interactions at free-stream Mach number 5. We considered different wall thermal conditions and a wide range of deflection angles. Python scripts are also provided to analyze the data.</p>
Database generated to analyze the effects of a nonadiabatic wall on supersonic shock/boundary-layer interactions
<p>This dataset was generated to analyze the effects of a nonadiabatic wall on supersonic shock/boundary-layer interactions and is related to the following publication:</p> <p>Volpiani, P. S., Bernardini, M., & Larsson, J. (2018). Effects of a nonadiabatic wall on supersonic shock/boundary-layer interactions. <em>Physical Review Fluids</em>, <em>3</em>(8), 083401.</p> <p>The database contains instantaneous and statistical fields of supersonic boundary layers and shock/boundary-layer interactions at free-stream Mach number 2.28. We considered different wall thermal conditions and a wide range of deflection angles. Python scripts are also provided to analyze the data.</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.