cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25625/2nqnr1/cyoa6g
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DOI: 10.25625/wezknl/guz7no
title: NO2 angular distribution.zip

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description: :unav
DOI: 10.25625/hyargo/gu3ryk
title: 0117_0054.img

description: :unav
DOI: 10.25625/wezknl
title: Angular distribution of desorbing NO2 from Ag(111)

description: VMI-TPD measurements used to deduce the angular distribution of desorbing NO2 from Ag(111). A 1:9-mixture of NO2/He was used for dosage onto the surface via a molecular beam at a surface temperature of 350 K.
DOI: 10.25625/2nqnr1/qpqd7i
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DOI: 10.25625/2nqnr1/nishep
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DOI: 10.25625/2nqnr1/8ovuws
title: metadata_0124_021_350K.dat

description: #1: Index #2: t/ s #3: T / K #4: UHV pressure / mbar #5-7: Intensities of ROIs in LabView program. Not used for data analysis
DOI: 10.25625/hyargo/fb7woe
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DOI: 10.25625/hyargo/qr1zns
title: metadata_0117_003_490K.dat

description: #1: Index #2: t / s #3: T / K #4: UHV p / mbar #5-7: Intensities of preliminary ROIs in LabView program. Not used for data analysis
DOI: 10.25625/hyargo/rfhkpe
title: 0117_0058.img

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DOI: 10.25625/2nqnr1/eudvte
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description: :unav
DOI: 10.25625/hyargo
title: Velocity distribution of recombinatively-desorbing oxygen from Ag(111)

description: Velocity-map images taken during a TPD experiment. These images were used to deduce the velocity distribution of recombinatively-desorbing oxygen from Ag(111) after exposure to NO2 at a surface temperature of 510 K.
DOI: 10.25625/hyargo/xlfz3p
title: 0117_0065.img

description: :unav
DOI: 10.25625/2nqnr1/uddhlg
title: 0124_0089.img

description: :unav
DOI: 10.25625/2nqnr1/xt4nko
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DOI: 10.25625/2nqnr1/7jaqco
title: 0124_0042.img

description: :unav
DOI: 10.25625/2nqnr1
title: Velocity distribution of desorbing NO2 from Ag(111)

description: VMI-TPD data used to deduce the velocity distribution of desorbing NO2 from Ag(111).
DOI: 10.5519/qd.05qdxb7b
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (273527 records)
DOI: 10.5517/ccdc.csd.cc23yfr8
title: CCDC 1964710: Experimental Crystal Structure Determination

description: Related Article: Ping Shang, Yao Wu, Zi-Hao Jiang, Hui-Zhen He, Qing Huang, Xiao-Qian Pu, Yu-Qing Xiao, Xuan-Feng Jiang|2022|Inorg.Chem.|61|14267|doi:10.1021/acs.inorgchem.2c01489
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.21227/4eyw-n176
title: TSN-FlexTest Traffic Streams for Spot Robot, Tactile Internet, and Generic Data

description: In this dataset, we provide detailed traffic stream data for the Spot robot, including both the Spot robot control traffic stream and the Spot video stream. The Spot robot traffic streams provide realistic traffic data for communication network evaluations, e.g., for measurements with the TSN FlexText testbed. Furthermore, we share data for the tactile internet including audio, video, and robotic communication. Finally, the dataset includes generic data streams for three different intervals (0.2ms, 0.3ms, and 0.5ms) with two different Ethernet frame sizes. The data is provided as .*pcap which can be replayed with various tools or be analyzed, e.g., with Wireshark. The Spot data streams are split into two directions and are based on Spot API calls.
DOI: 10.6084/m9.figshare.23703672
title: Childhood nature experiences and adult nature connection in Greek adults

description: These are data collected from 401 Greek adults on their current nature connection and its associations with their childhood experiences.
DOI: 10.5281/zenodo.7941460
title: Map of the global wildland-urban interface

description: The wildland-urban interface (WUI) is where buildings and wildland vegetation meet or intermingle. It is where human-environmental conflicts and risks are concentrated, including the loss of houses and lives to wildfire, habitat loss and fragmentation, and the spread of zoonotic diseases. However, a global analysis of the WUI has been lacking. This dataset features a global, 10 m resolution map of the wildland-urban interface that was developed in a recent study by the authors of this dataset (see corresponding publication). <strong>Temporal extent</strong> The data contains data representative for ca. 2020. <strong>Data format and units</strong> The data are organized in tiles of 100 km x 100 km and follow the EQUI7 tiling grid and projection system. The images are compressed GeoTiff files (*.tif). There is a mosaic in GDAL Virtual format (*.vrt), which can readily be opened in most Geographic Information Systems. Please consider the generation of image pyramids before using *.vrt files. The raster dataset contains Wildland-urban interface (WUI) data (one layer), 10 m spatial resolution, 8 discrete classes: 1 - Forest/Shrubland/Wetland-dominated Intermix WU 2 - Forest/Shrubland/Wetland-dominated Interface WUI 3 - Grassland-dominated Intermix WUI 4 - Grassland -dominated Interface WUI 5 - Non-WUI: Forest/Shrub/Wetland-dominated 6 - Non-WUI: Grassland-dominated 7 - Non-WUI: Urban 8 - Non-WUI: Other In addition, the data contain tabular data on WUI area, population and biomass in the WUI, as well as wildfire area and people affected by wildfire in the WUI per world region, country, subnational administrative unit and biome. The data also contain the key algorithm for WUI mapping (also accessible here: https://github.com/franzschug/global_wildland_urban_interface). <strong>Further information</strong> For further information, please see the publication or contact Franz Schug (fschug@wisc.edu). Visit the website of SILVIS lab, University of Wisconsin-Madison (http://silvis.forest.wisc.edu/globalwui) to learn more about the Wildland-Urban Interface. The data can be interactively visualizes in a web viewer here. <strong>Corresponding publication</strong> Schug, Franz<sup>*</sup>; Bar-Massada, Avi; Carlson, Amanda R.; Cox, Heather; Hawbaker, Todd J.; Helmers, David; Hostert, Patrick; Kaim, Dominik; Kasraee, Neda K.; Martinuzzi, Sebastián; Mockrin, Miranda H.; Pfoch, Kira A.; Radeloff, Volker C. The global wildland-urban interface, DOI: 10.1038/s41586-023-06320-0 <strong>Funding</strong> This research was funded by the NASA Land Cover and Land Use Change Program under agreement 80NSSC21K0310.
DOI: 10.5281/zenodo.7791979
title: Map of the global wildland-urban interface

description: The wildland-urban interface (WUI) is where buildings and wildland vegetation meet or intermingle. It is where human-environmental conflicts and risks are concentrated, including the loss of houses and lives to wildfire, habitat loss and fragmentation, and the spread of zoonotic diseases. However, a global analysis of the WUI has been lacking. This dataset features a global, 10 m resolution map of the wildland-urban interface that was developed in a recent study by the authors of this dataset (see corresponding publication). <strong>Temporal extent</strong> The data contains data representative for ca. 2020. <strong>Data format and units</strong> The data are organized in tiles of 100 km x 100 km and follow the EQUI7 tiling grid and projection system. The images are compressed GeoTiff files (*.tif). There is a mosaic in GDAL Virtual format (*.vrt), which can readily be opened in most Geographic Information Systems. Please consider the generation of image pyramids before using *.vrt files. The raster dataset contains Wildland-urban interface (WUI) data (one layer), 10 m spatial resolution, 8 discrete classes: 1 - Forest/Shrubland/Wetland-dominated Intermix WU 2 - Forest/Shrubland/Wetland-dominated Interface WUI 3 - Grassland-dominated Intermix WUI 4 - Grassland -dominated Interface WUI 5 - Non-WUI: Forest/Shrub/Wetland-dominated 6 - Non-WUI: Grassland-dominated 7 - Non-WUI: Urban 8 - Non-WUI: Other In addition, the data contain tabular data on WUI area, population and biomass in the WUI, as well as wildfire area and people affected by wildfire in the WUI per world region, country, subnational administrative unit and biome. The data also contain the key algorithm for WUI mapping (also accessible here: https://github.com/franzschug/global_wildland_urban_interface). <strong>Further information</strong> For further information, please see the publication or contact Franz Schug (fschug@wisc.edu). Visit the website of SILVIS lab, University of Wisconsin-Madison (http://silvis.forest.wisc.edu/globalwui) to learn more about the Wildland-Urban Interface. The data can be interactively visualizes in a web viewer here. <strong>Corresponding publication</strong> Schug, Franz<sup>*</sup>; Bar-Massada, Avi; Carlson, Amanda R.; Cox, Heather; Hawbaker, Todd J.; Helmers, David; Hostert, Patrick; Kaim, Dominik; Kasraee, Neda K.; Martinuzzi, Sebastián; Mockrin, Miranda H.; Pfoch, Kira A.; Radeloff, Volker C. The global wildland-urban interface, DOI: 10.1038/s41586-023-06320-0 <strong>Funding</strong> This research was funded by the NASA Land Cover and Land Use Change Program under agreement 80NSSC21K0310.
DOI: 10.3886/e184161
title: Data and Code for: Does Identity Affect Labor Supply?

description: How does identity influence economic behavior in the labor market? I investigate this question in rural India, focusing on the effect of caste identity on job-specific labor supply. In a field experiment, laborers choose whether to take up various job offers, which differ in associations with specific castes. Workers are less willing to accept offers that are linked to castes other than their own, especially when those castes rank lower in the social hierarchy. Workers forego large payments to avoid job offers that conflict with their caste identity, even when these decisions are made in private.
description: Male casual daily-wage laborers living in Odisha, India.
description: Data were collected via in-person surveys using paper instruments. The data was double entered using the Cylon software (https://github.com/cylondata/cylon), by two different data entry officers, to reduce errors.
DOI: 10.6084/m9.figshare.23676582
title: loadest input data for carbon

description: Input carbon data for loadest
DOI: 10.6084/m9.figshare.23676582.v5
title: loadest input data for carbon

description: Input carbon data for loadest
DOI: 10.6084/m9.figshare.23676582.v4
title: loadest input data for carbon

description: Input carbon data for loadest
DOI: 10.3886/e188611
title: Data and code for: "The Reversal Interest Rate"

description: The reversal interest rate is the rate at which accommodative monetary policy reverses and becomes contractionary for lending. We theoretically demonstrate its existence in a macroeconomic model featuring imperfectly competitive banks that face financial frictions. When interest rates are cut too low, further monetary stimulus cuts into banks’ profit margins, depressing their net worth and curtailing their credit supply. Similarly, when interest rates are low for too long, the persistent drag on bank profitability eventually outweighs banks’ initial capital gains, also stifling credit supply. We quantify the importance of this mechanism within a calibrated New Keynesian model.
DOI: 10.3886/e188611v1
title: Data and code for: "The Reversal Interest Rate"

description: The reversal interest rate is the rate at which accommodative monetary policy reverses and becomes contractionary for lending. We theoretically demonstrate its existence in a macroeconomic model featuring imperfectly competitive banks that face financial frictions. When interest rates are cut too low, further monetary stimulus cuts into banks’ profit margins, depressing their net worth and curtailing their credit supply. Similarly, when interest rates are low for too long, the persistent drag on bank profitability eventually outweighs banks’ initial capital gains, also stifling credit supply. We quantify the importance of this mechanism within a calibrated New Keynesian model.