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Open data and R analysis scripts for the paper as submitted for publication: "Poppelaars, E. S., Klackl, J., Pletzer, B., & Jonas, E. (2020). Delta-beta cross-frequency coupling as an index of stress regulation during social-evaluative threat." Hypotheses and analyses were preregistered: Poppelaars, E. S., Klackl, J., Pletzer, B., & Jonas, E. (2018). Delta-beta cross-frequency coupling as an index of stress regulation during social-evaluative threat. Open Science Framework. https://osf.io/8gchf/register/565fb3678c5e4a66b5582f67. Description of the dataset: A dataset of 37 men and 30 women (tested in the luteal phase of their menstrual cycle) participated in a public speaking task to induce social-evaluative threat. Responses of multiple stress systems were measured (sympathetic and parasympathetic nervous system activity, self-reported affect, and hypothalamic–pituitary–adrenal axis activity), as well as personality traits (e.g. trait social anxiety), and EEG delta-beta cross-frequency coupling (e.g., frontal and parietal amplitude-amplitude correlation and phase-amplitude coupling). Description of analyses files: - File 'README.txt' contains the description of the files (metadata). - File 'SET_CFC_MatlabOutput.xlsx' contains the delta-beta coupling data, calculated using MATLAB scripts from https://github.com/ESPoppelaars/Cross-frequency-coupling. - File 'SETData.sav' contains the raw stress and personality data, taken from https://doi.org/10.17632/7vj8r76s6f. - Files 'SET_CFC.outl.del.RData' contains the complete dataset with missing values and outliers deleted. - File 'Codebook_SET_CFC.outl.del.csv' contains a description of all variables in the 'SET_CFC.outl.del.RData' file (metadata). - Files 'SET_CFC.outl.del.imp.RData' and 'SET_CFC.outl.del.imp.extra.RData' contain multiple imputed datasets (without missing values) that can be used to reproduce results from the paper. - File 'LSA_HSA_brief.RData' contains data to use as informed priors for the Bayesian analyses, calculated from data published at https://doi.org/10.3758/s13415-018-0603-7. - File 'Codebook_LSA_HSA_brief.csv' contains a description of all variables in the 'LSA_HSA_brief.RData' file (metadata). - File '01_CalculationOfData.R' is an R analysis script that imports the raw data, calculates new variables, and imputes missing data via multiple imputation using the 'predictorMatrixAdj.xlsx' file. - File '02_AnalysisOfImputedData.R' is an R analysis script that calculates descriptive statistics, creates plots, and tests hypotheses using t-tests, Bayesian statistics, and multiple lineair regressions. Also uses the custom functions: 'BF.evidence.R', 'cohen.d.magnitude.R' and 'p.value.sig.R', as well as the 'BF_t.R' file as taken from https://doi.org/10.17045/sthlmuni.4981154.v3.
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Replication files and data for De Visscher, Eberhardt and Everaert, "Estimating and Testing the Multicountry Endogenous Growth Model," Journal of International Economics.
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Model outputs used for the paper entitled: "Quantifying the Impact of Excess Moisture from Transpiration from Crops on an Extreme Heat Wave Event in the Midwestern U.S.: A Top-down Constraint from MODIS Water Vapor Retrieval."
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Selected World Ocean Datasets of the CTD profiles with vertical resolution greater than 1 meter.
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This data set contains properties of the chromatin fiber sampled from molecular biosystems simulations and is created to support a manuscript "Submolecular-resolution 3D Simulations of the Oct4 Promoter Region Predict Structural Mechanism of Heterochromatin Formation". The included properties are radius of gyration (Rg_Mean), number of HP1-mediated inter-nucleosome bridges (nBridges_Mean), average size of HP1-mediated loops (mBRIDGE_loop_Mean). Each value is a mean over 100 simulation snapshots.
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The raw data and the experimentally obtained images captured in this study. The raw data can be opened by Origin software.
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Termites are present in different environments, they perform the functions of cycling organic compounds in the soil and decomposing organic matter. Through this behavior, some species can generate great economic losses in the agricultural environment for some cultures. Such insects can communicate through semi-chemical and vibroacystic signals. These signals transmit different types of messages. The vibroacoustic signals occur when there is interaction between the generated vibrating waves, which can, consequently, generate understandable optical interference phenomena when light is applied, one of these phenomena that can be understood is the dynamic biospeckle. It is proposed in this research, to evaluate the bioactivity of the termite Nasutitermes corniger (Insecta: Isoptera) during the walk using the optical phenomenon of interference Biospeckle. Termites were collected in colonies present on the University campus of the Federal University of Sergipe-UFS. 25 individuals were randomly selected, distributed in 5 groups. Such individuals will be submitted to the simulation activity of walking in arenas created using Petri dishes (14 x 1.5 cm) which were exposed to laser light, during the movement of the insect videos were captured which were later processed using the Generalized Differences Method and the Moment of Inertia. It was possible to detect the areas of walking and of greater activities caused naturally by the groups of Nasutitermes corniger present in the arenas, as well as the method of MI showed to be significantly different when analyzed before and during the walking. Thus, it is possible to analyze the walking activity of Nasutitermes corniger by means of dynamic biospeckle in different types of light, which can be applied as a possible tool to evaluate the termite's bioactivity.
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These data correspond to that presented in the manuscript "Local evaporation controlled by regional atmospheric circulation in the Altiplano of the Atacama Desert" by Lobos et al. These data were collected in the E-DATA field campaign, performed in the Salar del Huasco, Chile, on November 2018.
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The research was conducted on the premise that natural forest contributes to the provision of ecosystem services, but they are dwindling at an alarming rate. Periodic monitoring is needed to provide information on the status of the forest to assist in management planning. This research, therefore, presents a spatiotemporal change detection analysis of the Nkandla Forest reserve in South Africa. The research looks into the decadal changes that took place between 1989 and 2019. Four forest cover types which are closed canopy, open canopy, grasslands and bare sites were mapped and assessed. There were consistent gains and losses among each of the cover types at each decade with the prominent changes occurring between the closed and open canopy forest. These changes were as a result of ecological and chronic anthropogenic factors. The prediction of the future forest cover distribution was done for 2029 and 2039. The prediction shows a decline in the closed-canopy forest, a moderate increase in the grassland and a marginal increse in the open canopy forest.
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This is a novel multi-fidelity data assimilation method that provides an alternative to EnKF.
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