cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc2fj9s2
title: CCDC 2250004: Experimental Crystal Structure Determination

description: Related Article: Thomas Mies, Andrew J. P. White, Henry S. Rzepa, Luciano Barluzzi, Mohit Devgan, Richard A. Layfield, Anthony G. M. Barrett|2023|Inorg.Chem.|62|13253|doi:10.1021/acs.inorgchem.3c01506
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: 10.5517/ccdc.csd.cc2gx7vh
title: CCDC 2291267: Experimental Crystal Structure Determination

description: Related Article: Li Jinyu|2023|CSD Communication|||
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: 10.5281/zenodo.8290208
title: Porous Subvolume - Planar Specimen - Fine Mesh

description: Geometry of specimen: Planar ROI, with cylindrical ends Pores: Contains a subvolume of pores (1/9th the volume of ROI) Meshing: Fine (~240k elements) Additional info: These pores were segmented from a tomography and remeshed via GMSH
DOI: 10.5281/zenodo.8290207
title: Porous Subvolume - Planar Specimen - Fine Mesh

description: Geometry of specimen: Planar ROI, with cylindrical ends Pores: Contains a subvolume of pores (1/9th the volume of ROI) Meshing: Fine (~395k elements) Additional info: These pores were segmented from a tomography and remeshed via GMSH
DOI: 10.5281/zenodo.8290345
title: Porous Subvolume - Planar Specimen - Fine Mesh

description: Geometry of specimen: Planar ROI, with cylindrical ends Pores: Contains a subvolume of pores (1/9th the volume of ROI) Meshing: Fine (~395k elements) Additional info: These pores were segmented from a tomography and remeshed via GMSH
DOI: 10.5281/zenodo.8290343
title: Porous Subvolume - Planar Specimen - Coarse Mesh

description: Geometry of specimen: Planar ROI, with cylindrical ends Pores: Contains a subvolume of pores (1/9th the volume of ROI) Meshing: Coarse (~12k elements) Additional info: These pores were segmented from a tomography and remeshed via GMSH
DOI: 10.5281/zenodo.8290344
title: Porous Subvolume - Planar Specimen - Coarse Mesh

description: Geometry of specimen: Planar ROI, with cylindrical ends Pores: Contains a subvolume of pores (1/9th the volume of ROI) Meshing: Coarse (~12k elements) Additional info: These pores were segmented from a tomography and remeshed via GMSH
DOI: 10.5281/zenodo.8290366
title: Porous Subvolume - Planar Specimen - Coarse Mesh

description: Geometry of specimen: Planar ROI, with cylindrical ends Pores: Contains a subvolume of pores (1/9th the volume of ROI) Meshing: Coarse (~12k elements) Additional info: These pores were segmented from a tomography and remeshed via GMSH
DOI: 10.26207/j1gm-5x58
title: Data for: Online community photo-sharing in entomology: a large-scale review with suggestions on best practices
DOI: 10.5519/qd.dawn2tii
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (46 records)
DOI: 10.34740/kaggle/dsv/5998526
title: CRS Visual Dataset
DOI: 10.5281/zenodo.6853515
title: Example input dataset for thoracic CT-based body composition assessment

description: The uploaded archive file (tar.gz) contains an example dataset to demonstrate the input data arrangement for the thoracic CT-based body composition assessment pipeline described at https://github.com/MASILab/S-EFOV. The dataset consists of four chest CT scans selected from the TCIA COVID-19-AR dataset. The CT scans were converted from DICOM format to NIfTI format using https://github.com/rordenlab/dcm2niix. The original TCIA dataset were published under Creative Commons Attribution 4.0 International License and the TCIA Data Usage Policy. The usage of this derived subset should follow the same guidelines.
DOI: 10.5281/zenodo.6853516
title: Example input dataset for thoracic CT-based body composition assessment

description: The uploaded archive file (tar.gz) contains an example dataset to demonstrate the input data arrangement for the thoracic CT-based body composition assessment pipeline described at https://github.com/MASILab/S-EFOV. The dataset consists of four chest CT scans selected from the TCIA COVID-19-AR dataset. The CT scans were converted from DICOM format to NIfTI format using https://github.com/rordenlab/dcm2niix. The original TCIA dataset were published under Creative Commons Attribution 4.0 International License and the TCIA Data Usage Policy. The usage of this derived subset should follow the same guidelines.
DOI: 10.5281/zenodo.8290372
title: Example input dataset for thoracic CT-based body composition assessment

description: The uploaded archive file (tar.gz) contains an example dataset to demonstrate the input data arrangement for the thoracic CT-based body composition assessment pipeline described at https://github.com/MASILab/S-EFOV. The dataset consists of four chest CT scans selected from the TCIA COVID-19-AR dataset. The CT scans were converted from DICOM format to NIfTI format using https://github.com/rordenlab/dcm2niix. The original TCIA dataset were published under Creative Commons Attribution 4.0 International License and the TCIA Data Usage Policy. The usage of this derived subset should follow the same guidelines.
DOI: 10.5066/p9109fw1
title: Coastwide Reference Monitoring System (CRMS) 2021 land-water classification data, Eastern Louisiana

description: Wetland restoration efforts conducted by the Coastal Wetlands Planning, Protection and Restoration Act (CWPPRA) in Louisiana rely on monitoring efforts to determine the efficacy of these efforts. The Coastwide Reference Monitoring System (CRMS) was developed to assist in a multiple-reference approach that uses aspects of hydrogeomorphic functional assessments and probabilistic sampling for monitoring. The CRMS program includes a suite of approximately 398 sites that encompass the range of hydrological and ecological conditions for each stratum. As part of CRMS, land and water classifications are created from Digital Orthophoto Quarter Quadrangles (DOQQs) approximately every three years at all CRMS sites. A DOQQ is a raster image in which displacement in the image caused by sensor orientation and terrain relief has been removed and combines the image characteristics of a photo with geometric qualities of a map. The DOQQs generated for this project consist of 2021 Color Infrared (CIR) Digital Imagery. These images were classified into land and water categories using a threshold of the near infrared (NIR) band, followed by supervised and unsupervised classification. Initial classification results are then reviewed by multiple image analysts to identify and manually recode errors. The final land-water classifications are intended to serve as both geographic and quantitative assessments of landscape composition on the date of acquisition. Five previous assessments have been conducted (2005, 2008, 2012, 2015/2016, and 2018). Once the program creates enough data points for statistical analyses, these data will be used for land area change rate calculation.
DOI: 10.5281/zenodo.8290569
title: Lichens as bioindicators of monitoring of the selective air pollution, Zabrze (Poland) - XRF analysis results.

description: XRF analyses were performed by the BRUKER S8 TIGER series 2 WD-XRF spectrometer with a 1kW Rh X-ray tube. The system is equipped with five analyzing crystals (LiF200, PET, XS–55, LIF-220 & Ge) and two detectors (flow and scintillation counter). The samples were measured by best detection mode (18min analysis time), and the results were evaluated in Quant-Express (fundamental parameters) and SPECTRAplus Software.<br> Dr Ewa Szram, employed at the Institute of Earth Sciences, Faculty of Natural Sciences, Silesian University in Katowice, carried out the project. This research was funded by the National Science Centre, Poland MINIATURA-6 2022/06/X/ST10/00338 “Lichens as bioindicators of monitoring of the selective air pollution”
DOI: 10.5281/zenodo.8290568
title: Lichens as bioindicators of monitoring of the selective air pollution, Zabrze (Poland) - XRF analysis results.

description: XRF analyses were performed by the BRUKER S8 TIGER series 2 WD-XRF spectrometer with a 1kW Rh X-ray tube. The system is equipped with five analyzing crystals (LiF200, PET, XS–55, LIF-220 & Ge) and two detectors (flow and scintillation counter). The samples were measured by best detection mode (18min analysis time), and the results were evaluated in Quant-Express (fundamental parameters) and SPECTRAplus Software.<br> Dr Ewa Szram, employed at the Institute of Earth Sciences, Faculty of Natural Sciences, Silesian University in Katowice, carried out the project. This research was funded by the National Science Centre, Poland MINIATURA-6 2022/06/X/ST10/00338 “Lichens as bioindicators of monitoring of the selective air pollution”
DOI: 10.5066/p9rwo4kt
title: Drilling, construction, geophysical data, and lithologic log for borehole USGS 144

description: In 2016, the U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Energy (DOE), drilled and constructed borehole USGS 144 (433021112552501) for stratigraphic framework analyses and water quality monitoring at the Idaho National Laboratory (INL), located in southeastern Idaho. Borehole USGS 144 was continuously cored from approximately 4 to 639 ft below land surface (BLS). The final construction depth, after reaming out cored section of the well, is 620 ft BLS. The USGS INL Project Office drilling team performed the core drilling operations and well construction between August 22, 2016, to December 7, 2016. The USGS collected geophysical data, daily drilling notes, and prepared detailed core descriptions for core collected to 639 ft BLS, which are included as part of this data release. The USGS INL Project Office collected geophysical logs on November 16, 28 and 30, 2016. Geophysical data include natural gamma, temperature, specific conductance, acoustic televiewer (ATV), neutron, neutron porosity, and gamma-gamma density logs which were examined synergistically with available core material to identify contacts between basalt flows, location and thickness of sediment layers, relative changes in porosity, vertical changes in specific conductivity and temperature, and changes in fracture density. Additionally, a gyroscopic deviation survey was performed and analyzed to reflect the projected well bore path. Geophysical data were collected using Century™ multi-parameter logging probes and select logs are displayed in well log figures. Geophysical data shown in figure displays include the natural gamma and neutron probe (9057A), gamma-gamma density probe (0024A), and gyroscopic deviation probe (9095C), and acoustic televiewer (9804A). With the exception of the 9804A and 9042A logs run inside the open borehole after drill rod was removed geophysical data were collected through the drill rod after reaching total cored depth. All logs were run from the bottom-up after reaching total unobstructed depth. Geophysical log data not represented in figure displays can be obtained by downloading attached LAS files, which are bundled in a single compressed ZIP file, or by visiting USGS - GeoLog Locator. Drill core was taken to the USGS Lithologic Core Storage Library for storage and permanent archive located at Central Facilities Area on the INL. Drill core was photographed and described using standardized methods and procedures developed by the USGS INL Project Office which maximizes the description of the core and minimizes any interpretation.
DOI: 10.5281/zenodo.7954637
title: Dataset and Python Scripts used in the manuscript "Global-MHD Simulations using MagPIE : Impact of Flux Transfer Events on the Ionosphere"

description: Dataset and Python Scripts used in the manuscript "Global-MHD Simulations using MagPIE : Impact of Flux1 Transfer Events on the Ionosphere" Author: Arghyadeep Paul, Antoine Strugarek and Bhargav Vaidya<br> Date: 21 May, 2023 <br> Figure 1 has been plotted from two data files named C0_320.vtk and c1_320.vtk using the visualisation toolkit VisIt. Visit can be freely downloaded from https://wci.llnl.gov/simulation/computer-codes/visit Figure 2 has been plotted using the ipython notebook named "figure_2.ipynb" <br> Figure 3 has been plotted using the data file named "t_4964.vtk" and the visualisation toolkit VisIt. <br> Figure 4 has been plotted using the ipython notebook named "figure_4.ipynb" <br> Figure 5 has been plotted using the ipython notebook named "figure_5.ipynb" <br> Figure 6 has been plotted using the ipython notebook named "figure_6.ipynb" <br> Figure 7 has been plotted using the ipython notebook named "figure_7.ipynb" <br> Figure 8 has been plotted using the ipython notebook named "figure_8.ipynb" <br> Figure 9 has been plotted using the ipython notebook named "figure_9.ipynb" <br> All the associated data files are uploaded with the ipython notebooks
DOI: 10.5281/zenodo.7954636
title: Dataset and Python Scripts used in the manuscript "Global-MHD Simulations using MagPIE : Impact of Flux Transfer Events on the Ionosphere"

description: Dataset and Python Scripts used in the manuscript "Global-MHD Simulations using MagPIE : Impact of Flux1 Transfer Events on the Ionosphere" Author: Arghyadeep Paul, Antoine Strugarek and Bhargav Vaidya<br> Date: 21 May, 2023 <br> Figure 1 has been plotted from two data files named C0_320.vtk and c1_320.vtk using the visualisation toolkit VisIt. Visit can be freely downloaded from https://wci.llnl.gov/simulation/computer-codes/visit Figure 2 has been plotted using the ipython notebook named "figure_2.ipynb" <br> Figure 3 has been plotted using the data file named "t_4964.vtk" and the visualisation toolkit VisIt. <br> Figure 4 has been plotted using the ipython notebook named "figure_4.ipynb" <br> Figure 5 has been plotted using the ipython notebook named "figure_5.ipynb" <br> Figure 6 has been plotted using the ipython notebook named "figure_6.ipynb" <br> Figure 7 has been plotted using the ipython notebook named "figure_7.ipynb" <br> Figure 8 has been plotted using the ipython notebook named "figure_8.ipynb" <br> Figure 9 has been plotted using the ipython notebook named "figure_9.ipynb" <br> All the associated data files are uploaded with the ipython notebooks
DOI: 10.5281/zenodo.8290704
title: Lichens as bioindicators of monitoring of the selective air pollution, Zabrze (Poland) - total carbon (TC) and total sulfur (TS) results.

description: Total carbon (TC) and total sulfur (TS) contents were measured using an Eltra CS-500 IR-analyzer with a TIC module. TC was determined using an infrared cell detector on CO2 gas, which was evolved by combustion under an oxygen atmosphere. Calibration was made by means of the Eltra standards 2.27 % S and 45.14 % C. <br> Dr Ewa Szram, employed at the Institute of Earth Sciences, Faculty of Natural Sciences, Silesian University in Katowice, carried out the project. This research was funded by the National Science Centre, Poland MINIATURA-6 2022/06/X/ST10/00338 “Lichens as bioindicators of monitoring of the selective air pollution”
DOI: 10.5281/zenodo.8290703
title: Lichens as bioindicators of monitoring of the selective air pollution, Zabrze (Poland) - total carbon (TC) and total sulfur (TS) results.

description: Total carbon (TC) and total sulfur (TS) contents were measured using an Eltra CS-500 IR-analyzer with a TIC module. TC was determined using an infrared cell detector on CO2 gas, which was evolved by combustion under an oxygen atmosphere. Calibration was made by means of the Eltra standards 2.27 % S and 45.14 % C. <br> Dr Ewa Szram, employed at the Institute of Earth Sciences, Faculty of Natural Sciences, Silesian University in Katowice, carried out the project. This research was funded by the National Science Centre, Poland MINIATURA-6 2022/06/X/ST10/00338 “Lichens as bioindicators of monitoring of the selective air pollution”
DOI: 10.34770/67tb-0988
title: Density Limits as Disruption Forecasters for Spherical Tokamaks

description: Fusion power output from spherical tokamaks would benefit from increased confined plasma density, but there exists a limit on the density before confinement is lost and the plasma current is disrupted. This density limit has long been characterized by a simple, global Greenwald limit proportional to the plasma current and inversely proportional to the cross sectional area of the plasma. It is shown that in the database of discharges from the NSTX and MAST spherical tokamaks, the likelihood of disruption does increase above the Greenwald limit, and especially in the plasma current rampdown phase. The physics of the density limit has been recently theoretically explored through local criteria. Several of these are tested using the disruption event characterization and forecasting (DECAFTM) code for their potential effectiveness as disruption warning signals. For a limited set of NSTX discharges, a local island power balance criteria was found to be less reliable, presently, than the Greenwald limit. An empirical critical edge line density and a boundary turbulent transport limit were both tested for MAST-U, which has an electron density profile measurement with high spatial resolution in the outer part of the plasma. Both were found to have similar dependencies on key plasma parameters. In a limited set of MAST-U discharges that appear to disrupt due to rising density at values under the Greenwald limit, crossing of the boundary turbulent transport limit occurred close to the time of disruption. Finally, these limits were evaluated for their potential use in real-time, and it was found that with the necessary real-time inputs and with refinement through further testing, these limits could be implemented in a real-time disruption forecasting system.
DOI: 10.5519/qd.xv5kn76n
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1 records)
DOI: 10.6084/m9.figshare.24045147
title: Figures for function uploaded.pzfx

description: Raw data in Graphpad prizm format
DOI: 10.6084/m9.figshare.24045147.v1
title: Figures for function uploaded.pzfx

description: Raw data in Graphpad prizm format
DOI: 10.5517/ccdc.csd.cc2fkpwl
title: CCDC 2251340: Experimental Crystal Structure Determination

description: Related Article: Haiting Wu, Yiting He, Huiying Deng, Yunshi Liang, Lingling Xiang, Xueping Tang, Xueying Li, Zhijun Yuan, Bohong Lin, Song Chen, Jing Zhang|2023|J.Org.Chem.|88|11504|doi:10.1021/acs.joc.3c00660
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: 10.5517/ccdc.csd.cc2fkpyn
title: CCDC 2251342: Experimental Crystal Structure Determination

description: Related Article: Haiting Wu, Yiting He, Huiying Deng, Yunshi Liang, Lingling Xiang, Xueping Tang, Xueying Li, Zhijun Yuan, Bohong Lin, Song Chen, Jing Zhang|2023|J.Org.Chem.|88|11504|doi:10.1021/acs.joc.3c00660
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: 10.5517/ccdc.csd.cc2fqpf9
title: CCDC 2256131: Experimental Crystal Structure Determination

description: Related Article: Tanzilya S. Rizbayeva, Andrey V. Smolobochkin, Almir S. Gazizov, Julia K. Voronina, Victor V. Syakaev, Daria P. Gerasimova, Olga A. Lodochnikova, Sergey V. Efimov, Vladimir V. Klochkov, Alexander R. Burilov, Michail A. Pudovik|2023|J.Org.Chem.|88|11855|doi:10.1021/acs.joc.3c01138
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: 10.5517/ccdc.csd.cc2fqphc
title: CCDC 2256133: Experimental Crystal Structure Determination

description: Related Article: Tanzilya S. Rizbayeva, Andrey V. Smolobochkin, Almir S. Gazizov, Julia K. Voronina, Victor V. Syakaev, Daria P. Gerasimova, Olga A. Lodochnikova, Sergey V. Efimov, Vladimir V. Klochkov, Alexander R. Burilov, Michail A. Pudovik|2023|J.Org.Chem.|88|11855|doi:10.1021/acs.joc.3c01138
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: 10.5517/ccdc.csd.cc2fqpkf
title: CCDC 2256135: Experimental Crystal Structure Determination

description: Related Article: Tanzilya S. Rizbayeva, Andrey V. Smolobochkin, Almir S. Gazizov, Julia K. Voronina, Victor V. Syakaev, Daria P. Gerasimova, Olga A. Lodochnikova, Sergey V. Efimov, Vladimir V. Klochkov, Alexander R. Burilov, Michail A. Pudovik|2023|J.Org.Chem.|88|11855|doi:10.1021/acs.joc.3c01138
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: 10.5517/ccdc.csd.cc2frhrg
title: CCDC 2256916: Experimental Crystal Structure Determination

description: Related Article: Tanzilya S. Rizbayeva, Andrey V. Smolobochkin, Almir S. Gazizov, Julia K. Voronina, Victor V. Syakaev, Daria P. Gerasimova, Olga A. Lodochnikova, Sergey V. Efimov, Vladimir V. Klochkov, Alexander R. Burilov, Michail A. Pudovik|2023|J.Org.Chem.|88|11855|doi:10.1021/acs.joc.3c01138
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: 10.5517/ccdc.csd.cc2frhsh
title: CCDC 2256917: Experimental Crystal Structure Determination

description: Related Article: Tanzilya S. Rizbayeva, Andrey V. Smolobochkin, Almir S. Gazizov, Julia K. Voronina, Victor V. Syakaev, Daria P. Gerasimova, Olga A. Lodochnikova, Sergey V. Efimov, Vladimir V. Klochkov, Alexander R. Burilov, Michail A. Pudovik|2023|J.Org.Chem.|88|11855|doi:10.1021/acs.joc.3c01138
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.