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  • Data set for 'SPACE SYNTAX AND THE HISTORIC URBAN CORE OF ŁÓDŹ' article Author: Mariusz Lamprecht, PhD, Institute of the Built Environment and Spatial Policy, Faculty of Geographical Sciences, University of Łódź mariusz.lamprecht@geo.uni.lodz.pl
    Data Types:
    • Other
    • Software/Code
    • Geospatial Data
    • Tabular Data
    • Dataset
    • Document
    • File Set
  • Title of article: Hidden properties of city plans. A case study of Łódź Author: Mariusz Lamprecht, PhD, Institute of the Built Environment and Spatial Policy, Faculty of Geographical Sciences, University of Łódź mariusz.lamprecht@geo.uni.lodz.pl The set of data presented in the article in figures 3-12 (shp files).
    Data Types:
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    • Software/Code
    • Geospatial Data
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  • Non-marginal (average) AWARE CFs and WSI CFs: We provide a shapefile, CSV file and KML file of the average AWARE characterization factors (CFs) based on the marginal AWARE CFs from Boulay et al. (2018). We also provide it together with average WSI factors from Pfister and Bayer (2014), since based on the UNEP SETAC recommendation, AWARE should be used together with an alternative scarcity method to test sensitivities (Jolliet et al. 2018). The XLS version of the average AWARE CFs is available from the original publication: Pfister S, Scherer L, Buxmann K (2020) Water scarcity footprint of hydropower based on a seasonal approach - Global assessment with sensitivities of model assumptions tested on specific cases. Science of The Total Environment. https://doi.org/10.1016/j.scitotenv.2020.138188 DATA structure: The CSV files lists CFs for each month (01 to 12) and each methods: AWARE_01 stands for original marginal AWARE CFs of January, AWARE_a_01 represents the newly calculated average AWARE CFs for January, WSI_01 are the marginal WSI CFs for January and WSI_AVG_01 the average WSI CFs for January. The CSV file can be linked to WaterGAP watersheds based on the "BAS34S_ID" . The WaterGAP shapefile is e.g. available at http://www.wulca-waterlca.org/aware.html. The Shapefile and KML file follows the same order but are already linked to the watershed shapefile.
    Data Types:
    • Geospatial Data
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  • The present study The evidence reported above supports the notion that social support both directly affects the relapse tendency of women experiencing heroin addiction, but also may have an indirect impact through the active coping strategies. In addition, the role of social support may also be moderated by openness to experience. Further, previous studies of heroin addiction found that the age of addict and their parents' level of education level were significantly correlated with their rates of heroin abuse (Aggarwal et al., 2015; Kolodny et al., 2015). Therefore, it is necessary to control for these factors in the present study. Based on the above analysis, this study proposes the hypotheses listed here and summarized in the model in Fig. 1. (1) Active coping strategies would mediate the relationship between social support and the relapse tendency. (2) Openness to experience would moderate the relationships between social support and active coping strategies, and between social support and the relapse tendency. (3) Openness to experience would moderate the mediating effect of active coping strategies in the relationship between social support and the relapse tendency. Statistical analyses Descriptive analyses and Pearson’s correlations were used by SPSS 22.0 for all variables. To test the moderated mediation model, we have adopted Stride's advice, and constructs are measured by latent variables as opposed to observed variables (Stride, Gardner, Catley, & Thomas, 2015). The analysis process of the entire model corresponds to the SPSS macro PROCESS (http://www.afhayes.com) suggested by Hayes (2018) but applying Mplus 7.4. The mediating (indirect) effect with 5000 bootstrap samples. In order to better reveal the relationship between latent variables, we used the item parceling strategy (Hall, Snell, & Foust, 1999; Little, Cunningham, Shahar, & Widaman, 2002). The critical value of the statistical test includes p value under the standard 0.05 level, and 95% bias-correction bootstrap confidence interval.
    Data Types:
    • Software/Code
    • Geospatial Data
    • Dataset
  • We simulated the surface evolution for a pre-Nectarian surface unit and found that relative to their size, large complex craters are less destructive to the surrounding terrain than small simple craters. The data is structured as follows: 01_CTEM_Outputs - .dat files in which the craters from the simulations are stored - Python script to convert the .dat files to shapefiles 02_Shapefiles_From_CTEM_Outputs - Shapefiles in which the craters from the simulations are stored - Shapefile of the surrounding area (created manually) 03_CSFD_Measurements - A modified version of CSFD Tools to conduct Cartesian crater size-frequency distribution measurements - .scc files which contain the results from the Traditional Crater Counting and Non-sparseness Correction techniques (for further analysis in Craterstats) 04_Crater_Statistics - .stat files which contain crater size-frequency distribution statistics (obtained from the Craterstats software) 05_Crater_Equilibrium - simplified .stat files which contain cumulative number density information - Python script to fit a power law function to the simplified .stat files 06_Geometric_Saturation_Levels - .stat files which contain crater size-frequency distribution statistics (obtained from the Craterstats software) - Python script to calculate geometric saturation levels from .stat files - .txt files containing geometric satration levels Data by Orgel et al. (2018) are availiable here: http://www.planet.geo.fu-berlin.de/Orgel_etal_2017_Lunar_basins.zip
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  • The database, version 26 (first version was available in 2002), contains now 13239 site forms, (most of them with their geographical coordinates), comprising 16695 radiometric data: Conv. 14C and AMS 14C (12922 items), TL (10143 items), OSL (6510 items), ESR, Th/U and AAR (2093 items) from the European (Russian Siberia included) Lower, Middle and Upper Palaeolithic. All 14C dates are conventional dates BP. This improved version 26 replaces the older version 25. 170 new sites are incorporated and 267 sites have a corrected or an updated content.
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  • We examined the role of employee justice perceptions in explaining the distinct effects of two forms of pay transparency– process versus outcome pay transparency– on counterproductive workplace behavior (CWB). Study 1, a field study of 321 employees, revealed that process pay transparency is inversely related to CWB-O, with this effect mediated by greater procedural justice perceptions. In contrast, among employees perceiving their pay position as being lower than that of referent others, outcome pay transparency is positively associated with both CWB-O and CWB-I, with this effect mediated by reduced distributive justice perceptions. Study 2, using an online simulation-based experiment conducted on 394 employees and assessing actual deception behaviors, replicated and extended these findings. Specifically, when pay allocations were transparent (vs. secretive) and participant's pay was manipulated to be lower than that of teammates, participants reported lower distributive justice perceptions leading to heightened deception behaviors, with this effect mediated by a more negative emotional state. Analyses were done using MPlus 8.4. Files (.dat , and .inp , files are attached) for both CFA (Study 1) and path analyses (Studies 1 and 2). *-alt* files were used for testing alternative models reported in the papaer. R file and .csv file (Study 1) were used to compute alpha and omega values for ordinal indicators. Finally, *-omega* files (Study 2) were used to compute omegas in Study 2.
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    • Software/Code
    • Geospatial Data
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  • The dataset contains the Shu-Talas Transboundary Basin shapefiles. The shapefiles are produced using the data from HydroSHEDS project that provides watershed delineations at a global scale. Shu-Talas Basin has two major rivers, Shu and Talas. Their boundary shapefiles are included separately. Very small sub-basins within the Shu-Talas Basin are merged and dissolved.
    Data Types:
    • Software/Code
    • Geospatial Data
    • Dataset
  • The dataset contain ground rainfall data, radar rainfall grid data, and polarimetric data. These data are taken as an example for analyses of quantitative precipitation estimates by X-band polarimetric weather radar in Yogyakrta Region.
    Data Types:
    • Other
    • Software/Code
    • Geospatial Data
    • Tabular Data
    • Dataset
    • Document
    • File Set
  • In this folder are stored the data used in the Data in Brief article "Hydro-stratigraphic datasets for the reconstruction of a large scale 3D FEM numerical model in the Milan metropolitan area (northern Italy)" (Previati A., et al., 2020). 1. "SHP" folder contains the side boundaries of the model (Model_Domain.shp), the top and bottom boundaries (Ground_Surface_Elevation.shp, Model_Bottom.shp), the limit surface (Phreatic_Aquifer_Bottom.shp) between the shallow phreatic and the lower semi-confined aquifers and the hydraulic head isolines as on 2016 (Hydraulic_head_Isolines.shp). 2. "3DFEM_Mesh_Parameters.txt" contains the location (X, Y, Z Coordinate system EPSG:3003) of the mesh nodes and the associated parameters (hydraulic conductivity and porosity) as well as the grain size class, the aquifer system and the depositional system (see the associated article for a detailed description).
    Data Types:
    • Software/Code
    • Geospatial Data
    • Dataset
    • Document
    • File Set
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