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.
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."
Top results from Data Repository sources. Show only results like these.
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: Yansheng Deng
... Abaqus input file of a thermal-mechanical-metallurgical directly coupling finite element model of grinding under grinding parameters, vw=10mm/s, ap=0.2mm (model_of_grinding.inp). The temperature history and evolution history of each phase of several elements IP:3( SDV1_IP3.xlsx for temperature, SDV4_IP3.xlsx for austenite, SDV24_IP3.xlsx for martensite, SDV25_IP3.xlsx for ferrite+pearlite, SDV42_IP3.xlsx for J2, SDV43_IP3.xlsx for A1, SDV66_IP3.xlsx for Hydrostatic Stress, SDV67_IP3.xlsx for Ms).
Contributors: Alex Waldron, Filippo Pecci, Ivan Stoianov
... This dataset is supplementary data to "Parameter Estimation for Water Distribution Networks with Multiple Head Loss Formulae" in ASCE Journal of Water Resources and Planning Management (under review). The files associated with this dataset are licensed under a Creative Commons Attribution 4.0 International licence. Any use of this dataset must credit the authors. BWFLnet is an operational network in Bristol, UK, operated by Bristol Water. The data provided is a the product of a long term research partnership between Bristol Water and Infrasense Labs at Imperial College London on dynamically adaptive networks. We acknowledge the financial support of EPSRC (EP/P004229/1, Dynamically Adaptive and Resilient Water Supply Networks for a Sustainable Future) for the acquisition of this data set. All data provided is recorded hydraulic data with locations and names anonymised. The authors hope that the publication of this dataset will facilitate the reproducibility of research in hydraulic model calibration as well as broader research in the water distribution sector.
Contributors: Ana Miller-ter Kuile, Devyn Orr, An Bui, Rodolfo Dirzo, Maggie K, Douglas McCauley, Carina Motta, Hillary Young
... Island ecosystems have experienced massive biodiversity loss, and invasive species, in particular rodents, are responsible for much of this loss (~15%). Rodent eradications have led to the recovery of over 100 island vertebrates and their ecological roles. While the focus of most eradication efforts has been vertebrate recovery, rodents are generalists that predominantly eat seeds and fruit. However, there has been limited work on the effects of rodent eradication on plant communities and plant-mediated ecological processes. In this study, we conducted repeated surveys of seed, juvenile, and adult tree abundance and survival in permanent vegetation plots across an islet network (Palmyra Atoll) in the Central Tropical Pacific, before and after the eradication of black rats (Rattus rattus). Our aim was to examine the role of seed predation on tree communities and biomass. We observed an 84% decrease in seed predation of an introduced foundational species (the coconut palm, Cocos nucifera), and a 14-fold increase in juvenile tree biomass in all species following eradication. Juvenile C. nucifera abundance increased 2-5 times more than other tree species, leading to a 10% increase in population growth rate and a 4-fold increase in adult tree biomass accumulation over the next tree generation. We conclude that rodents can have nuanced impacts on island ecosystems, including facilitation of other invasive species and alteration of ecosystem functions such as carbon and nutrient cycling and storage. Future eradication efforts need to incorporate plant responses, since plants can shape post-eradication recovery trajectories. These data include census data from permanent vegetation plots on Palmyra Atoll, data used to determine community biomass from these plots, maps of Palmyra Atoll and the vegetation plot locations, and statistical tests used to determine changes in stages and vital rates for tree species in the permanent vegetation plots.
Data for: Is green land cover associated with less health care spending? Promising findings from county-level Medicare spending in the continental United States
Contributors: Douglas Becker
... CSV master data file, R command file, and SHP files
Contributors: Elizabeth Dingle
... Grain size statistics (D50 and D84) for the Cagayan River (and tributaries), channel pattern analysis (sinuosity and braiding ratios) and digitised banklines generated for channel migration analysis. Digitised banklines are provided as ESRI shapefiles which should open in most GIS packages and GoogleEarth. Full details on grain size locations and sampling methods are provided in the manuscript "Decadal-scale morphological adjustment of a lowland tropical river".
Contributors: Jeffrey Richardson
... These data are used in the manuscript "Lidar-based modelling approaches for estimating solar insolation in heavily forested streams"