Contributors: Jacqueline Zadelaar
... Are Individual Differences Quantitative Or Qualitative? An Integrated Behavioral And Fmri Mimic Approach. Authors: Jacqueline N. Zadelaar, Wouter D. Weeda, Lourens J. Waldorp, Anna C. K. Van Duijvenvoordee, N. E. Blankenstein, Hilde M. Huizenga In cognitive neuroscience there is a growing interest in individual differences. We propose the Multiple Indicators Multiple Causes (MIMIC) model of combined behavioral and fMRI data to determine whether such differences are quantitative or qualitative in nature. A simulation study revealed the MIMIC model to have adequate power for this goal, and parameter recovery to be satisfactory. The MIMIC model was illustrated with a re-analysis of Van Duijvenvoorde et al. (2016) and Blankenstein et al. (2018) decision making data. This showed individual differences in Van Duijvenvoorde et al. (2016) to originate in qualitative differences in decision strategies. Parameters indicated some individuals to use an expected value decision strategy, while others used a loss minimizing strategy, distinguished by individual differences in vmPFC activity. Individual differences in Blankenstein et al. (2018) were explained by quantitative differences in risk aversion. Parameters showed that more risk averse individuals preferred safe over risky choices, as predicted by heightened vmPFC activity. We advocate using the MIMIC model to empirically determine, rather than assume, the nature of individual differences in combined behavioral and fMRI datasets.
Contributors: Lukas Graf, Levente Papp
... This dataset provides sample data demonstrating the capacities of the OBIA4RTM tool. OBIA4RTM combines radiative transfer modelling (RTM) of vegetation with object-based image analysis (OBIA). Its main purpose is to provide vegetation parameters such as Leaf Area Index (LAI) or leaf Chlorophyll a+b content (CAB) on a per-object rather than per pixel base. In this dataset, the OBIA4RTM tool was applied to two Sentinel-2 scenes covering an agricultural area in Southern Germany. Field parcels were used as image objects that were delineated from high-resolution ortho-photography and classified into vegetated and non-vegetated parcels using a Support Vector Machine trained on manually selected samples. For each of the two scenes - dating back on the 6th and 18th of July 2017 - the canopy RTM ProSAIL was run in forward mode and the synthetic spectra stored in a Lookup-Table (LUT). For parameter retrieval, the 5 closest matches between spectra in the LUT and a given observed satellite spectrum averaged per parcel were used. Matches were found in terms of the lowest Root Mean Squared Error (RMSE). The utilized vegetation parameterisation is provided additionally. The results include the Leaf Area Index (LAI), the Chlorophyll a+b content (CAB) of leaves and the fraction of brown leaves (Cbrown). In addition, the retrieval error in terms of RMSE is provided together with the average of the 5 best matching synthetic spectra in the LUT to a given object-based spectrum. This allows for evaluating the quality of the inversion results and enables user to further improve the results by applying a more appropiate vegetation parameterisation. The structure of the dataset (see below) is straightforward: - The "Field Parcels" folder contains an ESRI shapefile with the field parcels as well as the classification results for the two image acquisition dates - The "ProSAIL Parametersisation" directory provides the vegetation parameters used to run the ProSAIL model. - The actual results are stored as ESRI-shapefiles in "Retrieved Vegetation Parameters" folder containing the LAI, CAB, Fraction of brown leaves and the RMSE as well as inverted Sentinel-2 spectra - "Sentinel-2 data" contains the utilized Sentinel-2 data as GeoTiff clipped to the study area in Level-2A This information should allow for reproducing the results using the freely available base version of OBIA4RTM (for research and education) or within other software packages. All geodata is projected in UTM-Zone 32N, WGS-84.
Common genetic variations associated with the persistence of immunity following childhood immunisation
Contributors: Daniel O'Connor
... Genotyping data of common genetic variations associated with the persistence of immunity following childhood immunisation
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Data for: Legacy of a Pleistocene bacterial community: Patterns in community dynamics through changing ecosystems.
Contributors: Senthil Kumar Sadasivam, Anbarasu Kumaresan, Sivakumar Krishnan, Bhavatharini Shanmuganathan, Manoj Kumar Jaiswal, SHAN P THOMAS
... The dataset contains supplementary data files for the manuscript titled "Legacy of a Pleistocene bacterial community: Patterns in community dynamics through changing ecosystems."
Contributors: Szilárd Szabó, Boglárka Balázs, Zoltán Kovács, Balázs Deák, Ádám Kertész
... The dataset is derived from the Hungarian part of the CarpatClim database (https://doi.org/10.1002/joc.4059) and the MODIS MOD13Q1 16 days 250 m (https://doi.org/10.5067/MODIS/MOD13Q1.006) between 2000-2010, using bivariate linear regression on monthly data. The 1038 points represent 1038 R-squared (R2) values of the regressions. R2 values reflect the strength of relationship between aridity, precipitation, potential evapotranspiration, maximum temperature and the normalized vegetation index (NDVI). For spatial analysis, we provided the codes of Hungarian macro regions, land cover and topography data (terrain height, slope and aspect). Column name Description CC_ID: CarpatClim identifier Country: Country code of CarpatClim /1=Hungary/ UTM_X: X UTM Coordinate UTM_Y: Y UTM Coordinate ARIvsNDVI_R2: R2 of Aridification Index and NDVI 2000–2010 PRECvsNDVI_R2: R2 of Precipitation and NDVI 2000–2010 PETvsNDVI_R2: R2 of Potential Evapotranspiration and NDVI 2000–2010 TMAXvsNDVI_R2: R2 of Maximum Temperature and NDVI 2000–2010 DEM_slope: SRTM slope value (degree) DEM_aspect: SRTM aspect value (azimuth) DEM: SRTM elevation (m) CLC_code: CORINE Land Cover code /arable lands (211, 213,221,222, 242,243), grasslands (231, 321), forests (311, 312, 313, 324), wetlands (411, 412), water bodies (511, 512) and artificial surfaces (112, 121, 122, 131, 142) Macro_reg_code: Hunrarian Macro Region code /Great Hungarian Plain=1, Kisalföld=2, Alpokalja=3, Transdanubian Hills=4, Transdanubian Mountains=5, North-Hungarian Mountains=6/ Microregion_code: Hungarian Micro Region code (Dövényi, Z. 2010) Dövényi, Z. ed. 2010. Inventory of Natural Micro-regions of Hungary, Hungarian Academy of Sciences Geographical Institute, Budapest
Contributors: Tanika Chakraborty, Rajshri Jayaraman
... 1. Data Use: Data were obtained and used by request from ASER. You are kindly requested to respect this and also obtain the authorization from ASER before using these data for a different purpose. Contact details are available here: http://www.asercentre.org/ 2. Software: The analysis was conducted in STATA, v14.2 3. Data files: Following are raw data files: a. Cross-sectional household surveys for the years 2005-2012: aser_2005_hh.dta aser_2006_hh.dta aser_2006_hh.dta aser_2007_hh.dta aser_2008_hh.dta aser_2009_hh.dta aser_2010_hh.dta aser_2011_hh.dta aser_2012_hh.dta b. Cross-section school surveys for the years 2007, and 2009-12: sch_2007.dta sch_2009.dta sch_2010.dta sch_2011.dta sch_2012.dta c. State-level data for the state-level regression results: states.dta d. Geographic data base of Indian administrative boundaries, obtained from http://www.gadm.org: IND*.* The .shp files could not be uploaded to Mendeley Data. Hence we have provides 2 .shp files along with the manuscript under program files.
Abaqus Code for a Residual Control Staggered Solution Scheme for the Phase-Field Modeling of Brittle Fracture
Contributors: Karlo Seleš
... Abaqus UEL and UMAT subroutines for the phase-field modeling of brittle fracture. The code consists of the 3-layered system of user elements and user material subroutine producing a staggered algorithm with a residual norm based stopping criterion. The elements are 4-node full integration 2D and 8-node full integration 3D linear elements. The implementation files (source code and input files) for some examples published in the associated journal article are given. The files contain detailed explanations and instructions for users. This is an updated version of the dataset. See more info in Version_3-ChangeLog.txt For additional information, suggestions or comments, please contacts us at email@example.com
Contributors: Emily Schworer, Lisa A. Daunhauer, Mark Prince, Amy Needham, Elizabeth A. Will, Deborah J. Fidler
... This dataset represents one timepoint of data collection for a sample of infants with Down syndrome. Complete Bayley-III information is provided, as well as demographic information and child medical/health history information. In addition, infants were administered a short exploration task that involved presenting the infant with a teether in their line of vision, and then placing it on the table before them. Exploration trials were coded for the percentage of time the infant spent visually, manually, and orally exploring the object.
Contributors: Sly Wongchuig, Rodrigo Paiva
... We make available the daily discharge dataset of the Hydrological Reanalysis across the 20th Century for the Amazon Basin in its v1.0 version, which correspond to the HRXX_Amz.nc file. The matrix of daily discharge contains 36890 columns (one per day, starting at 01Jan/1910) and 12466 rows (one per catchment). Authors: Sly Wongchuig Correa Rodrigo Cauduro Dias de Paiva Vinícius Siqueira Walter Collischonn Institute of Hydraulic Research - (IPH/UFRGS) Brazil - November 2018 Citation: When using these data, please refer to the following paper: Wongchuig, C.S.; Paiva, R.C.D.; Siqueira, V.; Collischonn, W. 2019. Hydrological Reanalysis Across the 20th Century: A Case Study of the Amazon Basin. Journal of Hydrology, vol. 570, p. 755-773. https://doi.org/10.1016/j.jhydrol.2019.01.025
Data for: The role of chemical disorder and structural freedom in radiation-induced amorphization of silicon carbide deduced from electron spectroscopy and ab initio simulations
Contributors: Alexander Leide, Ju Li, Lin Shao, Di Chen, Ziqiang Wang, Linn Hobbs
... Atomic position files of relaxed structures after atomic disordering, and melt-quenching. Example input files for stages of VASP molecular dynamics, Conjugate Gradient Approximation relaxation, and FEFF ELNES simulations. This data is associated with the article submission to Journal of Nuclear Materials: "The role of chemical disorder and structural freedom in radiation-induced amorphization of silicon carbide deduced from electron spectroscopy and ab initio simulations"