cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.7319129
title: Correcting for probe wandering by precession path segmentation

description: Scanning precession electron diffraction datasets and processing scripts used in the journal publication "<strong>Correcting for probe wandering by precession path segmentation</strong>". DOI link to publication: https://doi.org/10.1016/j.ultramic.2023.113715 <strong>Prerequisites</strong> To run the scripts necessary to process the data, the open source packages JupyterLab and HyperSpy need to be installed. These notebooks were created with these package versions: hyperspy 1.6.4 jupyterlab 3.2.0 <strong>Data files</strong> There are three data types: Scanning precession electron diffraction (SPED) datasets contain the .hspy extension. There are two SPED datasets acquired by precession path segmentation, and one regular dataset: <em>SPED_256x256_22x22_10186nm_NBD_a5_spot1nm_CL20cm_125msExp_3000msFB_subframing_x8_pivotoff_01.hspy</em> is a precession path segmentation dataset presented in figure 2 in the article. <em>SPED_zoom1_256x256_12x12_5556nm_NBD_a5_spot1nm_CL20cm_10msExp_3000msFB_subframing_x8.hspy</em> is a precession path segmentation dataset presented in figures 1 and 3 in the article. <em>SPED_zoom1_256x256_12x12_5556nm_NBD_a5_spot1nm_CL20cm_10msExp_300msFB.hspy</em> is a regular SPED dataset of the same region as the dataset just above (also containing "zoom1" in its name). A series of diffraction patterns with de-rocking switched off can be found in the <em>eight_segments.npy</em> file. This dataset was recorded by Dr. Tina Bergh at Department of Chemical Engineering, Norwegian University of Science and Technology, and is meant to be used as an illustration of the precession segments used in figure 1 in the article. Virtual bright field images of the precession path segmented scans, before and after rigid correction in SmartAlign, can be found with the .png extension. The files starting with "pivot01..." are images from the precession path segmentation scan with an intentional pivot point misalignment, while the files starting with "small..." are from the well aligned scan. The files ending with "_reg" are regular, i.e., non-corrected compound VBF images, while the files ending with "_cor" are SmartAlign rigidly corrected VBF images. <strong>Processing scripts</strong> There are two processing scripts: <em>p01_slicing_segments.ipynb</em> is used to process the precession path segmentation datasets, from slicing of the raw data to constructing virtual bright field images. <em>p02_image_processing.ipynb</em> is used to create the images found in the article and for image analysis. The latter includes blur quantification and measuring edge sharpness.
DOI: 10.5281/zenodo.7713090
title: Dataset Digital Competence

description: The dataset contains data on demographics (gender, age), education (type of study program, enrolled year, affiliation of studies to a scientific field, daily use of computer) and data on the self-assessed level of digital competence of the respondents.
DOI: 10.6084/m9.figshare.22242277
title: Supplemental online material.docx

description: Full description of the influence of students’ general characteristics on the comparison of their objective PA, perceived PA, and flow state beween the creative and reproductive sessions.
DOI: 10.6084/m9.figshare.22242277.v1
title: Supplemental online material.docx

description: Full description of the influence of students’ general characteristics on the comparison of their objective PA, perceived PA, and flow state beween the creative and reproductive sessions.
DOI: 10.48420/22219564
title: Processed simulation outputs for "Modelling the impact of non-pharmaceutical interventions on workplace transmission of SARS-CoV-2 in the home-delivery sector"

description: The same data as stored in the "raw data" dataset is reformatted in "pickle" format for use in python plotting. README.txt contains descriptions of the data in each column of the table.
DOI: 10.48420/22219564.v1
title: Processed simulation outputs for "Modelling the impact of non-pharmaceutical interventions on workplace transmission of SARS-CoV-2 in the home-delivery sector"

description: The same data as stored in the "raw data" dataset is reformatted in "pickle" format for use in python plotting. README.txt contains descriptions of the data in each column of the table.
DOI: 10.17028/rd.lboro.22242334
title: Supplementary information files for A family of bis-naphthyl C2-symmetric and asymmetric clefts: Synthesis, solid state structure and calculation of the interplanar angle

description: Supplementary files for article A family of bis-naphthyl C2-symmetric and asymmetric clefts: Synthesis, solid state structure and calculation of the interplanar angle <br> The synthesis of a new family of naphthalenoid C2-symmetric clefts has been realized through a four-step synthetic sequence giving three C2-symmetric clefts and a rare nonsymmetric example. Subsequently, stereoselective reduction of the carbonyl groups at C-8 and C-16 then provides cleft molecules with hydrogen bonding potential. Using single-crystal X-ray and computational analysis, the cleft angle of the dione has been determined.
DOI: 10.17028/rd.lboro.22242334.v1
title: Supplementary information files for A family of bis-naphthyl C2-symmetric and asymmetric clefts: Synthesis, solid state structure and calculation of the interplanar angle

description: Supplementary files for article A family of bis-naphthyl C2-symmetric and asymmetric clefts: Synthesis, solid state structure and calculation of the interplanar angle <br> The synthesis of a new family of naphthalenoid C2-symmetric clefts has been realized through a four-step synthetic sequence giving three C2-symmetric clefts and a rare nonsymmetric example. Subsequently, stereoselective reduction of the carbonyl groups at C-8 and C-16 then provides cleft molecules with hydrogen bonding potential. Using single-crystal X-ray and computational analysis, the cleft angle of the dione has been determined.
DOI: 10.5519/qd.ohzljalt
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1 records)
DOI: 10.5281/zenodo.7416204
title: Dataset for "Narrow range of early habitable Venus scenarios permitted by modelling of oxygen loss and radiogenic argon degassing"

description: Code and datasets required to reproduce figures in main text of Warren & Kite 2023 "Narrow range of early habitable Venus scenarios permitted by modelling of oxygen loss and radiogenic argon degassing." https://www.pnas.org/doi/full/10.1073/pnas.2209751120 Code and usage instructions are also available at: github.com/aowarren/Venus_O2 After downloading, code will need to be modified to find files in chosen directories for running the full model (also requires installation of VolcGases from github.com/Nicholaswogan/VolcGases) and files for re-creating plots. All .zip files contain data used to create figures in paper. Instructions to reproduce figures below: <strong>1. To reproduce full dataset</strong>, download all files excluding .zip files and install VolcGases. Modify "modular_functions_clean_redox.py" to match VolcGases installation. <em>For runaway greenhouse runs:</em> Ensure "modular_functions_clean_redox.py" line 512 is commented out. Run "adding_dissolution_clean.py" followed by "ext1line.py" to pre-run runaway greenhouse model and save output to read into full model (this speeds up running the entire suite of "melting" models, but is not strictly necessary). Next, use "gridsearch_all_redox.csv" to set model parameters, then run "input_clean_redox.py" to initiate model. <em>For runs without runaway greenhouse melting:</em> uncomment "modular_functions_clean_redox.py" line 512. Use "gridsearch_all_redox.csv" to set model parameters, then run "input_clean_redox.py" to initiate model. <strong>2. To reproduce Figures 2, 3, S1, and S2</strong>, either download all zip files beginning with "Fig2_" and "Fig3_", extract all files to single location, or save all new model output into a single directory and use "plot_together.py" to generate figures (instructions contained within script). Use same script to reproduce Figures S9 and S10 with data in "t_atm_sensitivity.zip" and "bH_sensitivity.zip". <strong>3. To reproduce Figures 4 and 5</strong>, If using new model runs to generate plots, first run "gen_data_forplots.py". Alternatively, download: e_statistics_nomelt_CO_FMQ0.npz e_wd_statistics_melt_CO_FMQ0.npz 40_Ar_hab_dlith_KU_mix_52522.csv 40_Ar_hab_dlith_KU_nomix_52522.csv Then, run maintext_plotting_new.py. <strong>4. To reproduce Figures S5 to S8</strong>, run "Ar_plots.py". Requires: "serpent_dehyd2.csv" and "eclogite_transition.csv".
DOI: 10.5281/zenodo.7416203
title: Dataset for "Narrow range of early habitable Venus scenarios permitted by modelling of oxygen loss and radiogenic argon degassing"

description: Code and datasets required to reproduce figures in main text of Warren & Kite 2023 "Narrow range of early habitable Venus scenarios permitted by modelling of oxygen loss and radiogenic argon degassing." https://www.pnas.org/doi/full/10.1073/pnas.2209751120 Code and usage instructions are also available at: github.com/aowarren/Venus_O2 After downloading, code will need to be modified to find files in chosen directories for running the full model (also requires installation of VolcGases from github.com/Nicholaswogan/VolcGases) and files for re-creating plots. All .zip files contain data used to create figures in paper. Instructions to reproduce figures below: <strong>1. To reproduce full dataset</strong>, download all files excluding .zip files and install VolcGases. Modify "modular_functions_clean_redox.py" to match VolcGases installation. <em>For runaway greenhouse runs:</em> Ensure "modular_functions_clean_redox.py" line 512 is commented out. Run "adding_dissolution_clean.py" followed by "ext1line.py" to pre-run runaway greenhouse model and save output to read into full model (this speeds up running the entire suite of "melting" models, but is not strictly necessary). Next, use "gridsearch_all_redox.csv" to set model parameters, then run "input_clean_redox.py" to initiate model. <em>For runs without runaway greenhouse melting:</em> uncomment "modular_functions_clean_redox.py" line 512. Use "gridsearch_all_redox.csv" to set model parameters, then run "input_clean_redox.py" to initiate model. <strong>2. To reproduce Figures 2, 3, S1, and S2</strong>, either download all zip files beginning with "Fig2_" and "Fig3_", extract all files to single location, or save all new model output into a single directory and use "plot_together.py" to generate figures (instructions contained within script). Use same script to reproduce Figures S9 and S10 with data in "t_atm_sensitivity.zip" and "bH_sensitivity.zip". <strong>3. To reproduce Figures 4 and 5</strong>, If using new model runs to generate plots, first run "gen_data_forplots.py". Alternatively, download: e_statistics_nomelt_CO_FMQ0.npz e_wd_statistics_melt_CO_FMQ0.npz 40_Ar_hab_dlith_KU_mix_52522.csv 40_Ar_hab_dlith_KU_nomix_52522.csv Then, run maintext_plotting_new.py. <strong>4. To reproduce Figures S5 to S8</strong>, run "Ar_plots.py". Requires: "serpent_dehyd2.csv" and "eclogite_transition.csv".
DOI: 10.5517/ccdc.csd.cc23xswq
title: CCDC 1964094: Experimental Crystal Structure Determination

description: Related Article: Orhi Esarte Palomero, Richard A. Jones|2023|Polyhedron|234|116340|doi:10.1016/j.poly.2023.116340
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.cc23xsxr
title: CCDC 1964095: Experimental Crystal Structure Determination

description: Related Article: Orhi Esarte Palomero, Richard A. Jones|2023|Polyhedron|234|116340|doi:10.1016/j.poly.2023.116340
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.cc23xsys
title: CCDC 1964096: Experimental Crystal Structure Determination

description: Related Article: Orhi Esarte Palomero, Richard A. Jones|2023|Polyhedron|234|116340|doi:10.1016/j.poly.2023.116340
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.cc23xszt
title: CCDC 1964097: Experimental Crystal Structure Determination

description: Related Article: Orhi Esarte Palomero, Richard A. Jones|2023|Polyhedron|234|116340|doi:10.1016/j.poly.2023.116340
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.cc23xt0w
title: CCDC 1964098: Experimental Crystal Structure Determination

description: Related Article: Orhi Esarte Palomero, Richard A. Jones|2023|Polyhedron|234|116340|doi:10.1016/j.poly.2023.116340
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.cc23xt1x
title: CCDC 1964099: Experimental Crystal Structure Determination

description: Related Article: Orhi Esarte Palomero, Richard A. Jones|2023|Polyhedron|234|116340|doi:10.1016/j.poly.2023.116340
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.cc23xt2y
title: CCDC 1964100: Experimental Crystal Structure Determination

description: Related Article: Orhi Esarte Palomero, Richard A. Jones|2023|Polyhedron|234|116340|doi:10.1016/j.poly.2023.116340
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.cc23xt3z
title: CCDC 1964101: Experimental Crystal Structure Determination

description: Related Article: Orhi Esarte Palomero, Richard A. Jones|2023|Polyhedron|234|116340|doi:10.1016/j.poly.2023.116340
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.7713098
title: Pre Computed LCF FE Simulations - TP Athens

description: Pre computed LCF FE simulations at different levels of loadings.
DOI: 10.5281/zenodo.7713097
title: Pre Computed LCF FE Simulations - TP Athens

description: Pre computed LCF FE simulations at different levels of loadings.
DOI: 10.48420/22232833
title: Input data for "Modelling the impact of non-pharmaceutical interventions on workplace transmission of SARS-CoV-2 in the home-delivery sector"

description: Data used as input for some simulations in "Modelling the impact of non-pharmaceutical interventions on workplace transmission of SARS-CoV-2 in the home-delivery sector". "LIDD_demand_norm.csv": normalised demand used to simulate LIDD setting. Need to be multiplied by absolute number of deliveries per day to be used. "SPDD_demand_norm.csv": normalised demand used to simulate SPDD setting. Need to be multiplied by absolute number of deliveries per day to be used. "inc_prev.csv": Community incidence and prevalence values assumed for simulation scenarios. <br>
DOI: 10.48420/22232833.v1
title: Input data for "Modelling the impact of non-pharmaceutical interventions on workplace transmission of SARS-CoV-2 in the home-delivery sector"

description: Data used as input for some simulations in "Modelling the impact of non-pharmaceutical interventions on workplace transmission of SARS-CoV-2 in the home-delivery sector". "LIDD_demand_norm.csv": normalised demand used to simulate LIDD setting. Need to be multiplied by absolute number of deliveries per day to be used. "SPDD_demand_norm.csv": normalised demand used to simulate SPDD setting. Need to be multiplied by absolute number of deliveries per day to be used. "inc_prev.csv": Community incidence and prevalence values assumed for simulation scenarios. <br>
DOI: 10.5281/zenodo.7704542
title: Supplementary Material for 'Leveraging the GIDAS Database for the Criticality Analysis of Automated Driving Systems'

description: This repository contains the supplementary material for the publication 'Leveraging the GIDAS Database for the Criticality Analysis of Automated Driving Systems'.<br> It consists of four files: Criticality-Phenomena-Catalog.CSV: The catalog of criticality phenomena (CP) Criticality-Phenomena-Phi-Coefficient.CSV: The calculation of the Phi coefficient between all pairs of CP Criticality-Phenomena-Risk-Calculation.CSV: The case-phenomenon relation matrix, including the calculated values for the risk of each CP for all three severity levels Criticality-Phenomena-Sorted-By-Risk.CSV: A list of the CP from the CP catalog sorted by risk for all three severity classes
DOI: 10.5281/zenodo.7704541
title: Supplementary Material for 'Leveraging the GIDAS Database for the Criticality Analysis of Automated Driving Systems'

description: This repository contains the supplementary material for the publication 'Leveraging the GIDAS Database for the Criticality Analysis of Automated Driving Systems'.<br> It consists of four files: Criticality-Phenomena-Catalog.CSV: The catalog of criticality phenomena (CP) Criticality-Phenomena-Phi-Coefficient.CSV: The calculation of the Phi coefficient between all pairs of CP Criticality-Phenomena-Risk-Calculation.CSV: The case-phenomenon relation matrix, including the calculated values for the risk of each CP for all three severity levels Criticality-Phenomena-Sorted-By-Risk.CSV: A list of the CP from the CP catalog sorted by risk for all three severity classes
DOI: 10.5281/zenodo.7685452
title: Checkpoints for Morphological Classification of Radio Galaxies with wGAN-supported Augmentation

description: Checkpoint for the Generator Model described in https://github.com/floriangriese/wGAN-supported-augmentation
DOI: 10.5281/zenodo.7685453
title: Checkpoints for Morphological Classification of Radio Galaxies with wGAN-supported Augmentation

description: Checkpoint for the Generator Model described in https://github.com/floriangriese/wGAN-supported-augmentation
DOI: 10.5281/zenodo.7689127
title: Checkpoints for Morphological Classification of Radio Galaxies with wGAN-supported Augmentation

description: Checkpoint for the Generator Model described in https://github.com/floriangriese/wGAN-supported-augmentation
DOI: 10.5281/zenodo.7713168
title: Checkpoints for Morphological Classification of Radio Galaxies with wGAN-supported Augmentation

description: Checkpoint for the Generator Model described in https://github.com/floriangriese/wGAN-supported-augmentation
DOI: 10.35078/qmkoaw
title: Replication Data for: Ficha epidemiológica de localidade: Distrito: Teófilo Otoni| Município: Itinga

description: Levantamento Triatomínico com operações de campo ocorridas em Minas Gerais pela Superintendência de Campanhas de Saúde Pública (SUCAM) e FUNASA (Fundação Nacional de Saúde), no período de 1979 a 1999, objetivando a busca da presença de vetores da doença de Chagas ou de vestígios dessa presença. A partir dela são orientadas as operações com inseticida (pt) Triatomine survey with field operations carried out in Minas Gerais by the Public Health Campaigns Superintendence (SUCAM) and FUNASA (National Health Foundation), from 1979 to 1999, aiming to search for the presence of Chagas disease vectors or traces of that presence. From it, operations with insecticide are guided (en) Encuesta de triatominos con operaciones de campo realizada en Minas Gerais por la Superintendencia de Campañas de Salud Pública (SUCAM) y FUNASA (Fundación Nacional de Salud), de 1979 a 1999, con el objetivo de buscar la presencia de vectores de la enfermedad de Chagas o rastros de esa presencia. Desde ella se orientan las operaciones con insecticida (es)
DOI: 10.20375/0000-000f-8244-1
title: Codebook_KIIS_Social Protest_2009-2021.xlsx
DOI: 10.20375/0000-000f-8245-0
title: Data_converted_KIIS_Social Protest_2009-2021_eng.xlsx
DOI: 10.20375/0000-000f-8246-f
title: Data Documentation KIIS Social Protest 2009-2021.pdf
DOI: 10.20375/0000-000f-8247-e
title: Data_KIIS_Social Protest_2009-2021_eng.sav
DOI: 10.20375/0000-000f-8248-d
title: Data_KIIS_Social Protest_2009-2021_ukr.sav
DOI: 10.20375/0000-000f-824a-b
title: Codebook_KIIS_Social Protest_2009-2021.xlsx
DOI: 10.20375/0000-000f-824b-a
title: Data_converted_KIIS_Social Protest_2009-2021_eng.xlsx
DOI: 10.20375/0000-000f-824c-9
title: Data Documentation KIIS Social Protest 2009-2021.pdf
DOI: 10.20375/0000-000f-824d-8
title: Data_KIIS_Social Protest_2009-2021_eng.sav
DOI: 10.20375/0000-000f-824e-7
title: Data_KIIS_Social Protest_2009-2021_ukr.sav
DOI: 10.6084/m9.figshare.22242298
title: Assessing the Benefits and Costs of the Hydrogen Cyanide Antiherbivore Defense in Trifolium repens

description: These are the raw data files associated with our manuscript " Assessing the Benefits and Costs of the Hydrogen Cyanide Antiherbivore Defense in <em>Trifolium repens</em>" <sub> </sub> Authors: Hind Emad Fadoul; Lucas J. Albano; Matthew E. Bergman; Michael A. Phillips and Marc T. J. Johnson Journal: Plants.
DOI: 10.6084/m9.figshare.22242298.v1
title: Assessing the Benefits and Costs of the Hydrogen Cyanide Antiherbivore Defense in Trifolium repens

description: These are the raw data files associated with our manuscript " Assessing the Benefits and Costs of the Hydrogen Cyanide Antiherbivore Defense in <em>Trifolium repens</em>" <sub> </sub> Authors: Hind Emad Fadoul; Lucas J. Albano; Matthew E. Bergman; Michael A. Phillips and Marc T. J. Johnson Journal: Plants.
DOI: 10.6084/m9.figshare.22242445
title: Temporal dominance of sensations (TDS) of Mopane fortified porridge

description: Dataset of Temporal dominance of sensations (TDS) of Mopane fortified porridge developed by Abertay University using UK and Zimbabwean assessors
DOI: 10.6084/m9.figshare.22242445.v1
title: Temporal dominance of sensations (TDS) of Mopane fortified porridge

description: Dataset of Temporal dominance of sensations (TDS) of Mopane fortified porridge developed by Abertay University using UK and Zimbabwean assessors