cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc2fyxr2
title: CCDC 2263085: Experimental Crystal Structure Determination

description: Related Article: Josina L. Bohlen, Lukas Endres, Regina Drescher, Krzysztof Radacki, Maximilian Dietz, Ivo Krummenacher, Holger Braunschweig|2023|Chemical Science|14|9010|doi:10.1039/D3SC02668J
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.cc2fzr5c
title: CCDC 2263873: Experimental Crystal Structure Determination

description: Related Article: Gu lijie|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.8314701
title: Camera Dataset - Solomatov and Akkaynak (2023)

description: <strong>Source URL</strong>: https://color-lab-eilat.github.io/Spectral-sensitivity-estimation-web/#camera-dataset-section<br> <br> <strong>Abstract</strong><br> A number of problems in computer vision and related fields would be mitigated if camera spectral sensitivities were known. As consumer cameras are not designed for high-precision visual tasks, manufacturers do not disclose spectral sensitivities. Their estimation requires a costly optical setup, which triggered researchers to come up with numerous indirect methods that aim to lower cost and complexity by using color targets. However, the use of color targets gives rise to new complications that make the estimation more difficult, and consequently, there currently exists no simple, low-cost, robust go-to method for spectral sensitivity estimation that non-specialized research labs can adopt. Furthermore, even if not limited by hardware or cost, researchers frequently work with imagery from multiple cameras that they do not have in their possession. To provide a practical solution to this problem, we propose a framework for spectral sensitivity estimation that not only does not require any hardware (including a color target), but also does not require physical access to the camera itself. Similar to other work, we formulate an optimization problem that minimizes a two-term objective function: a camera-specific term from a system of equations, and a universal term that bounds the solution space. Different than other work, we utilize publicly available high-quality calibration data to construct both terms. We use the colorimetric mapping matrices provided by the Adobe DNG Converter to formulate the camera-specific system of equations, and constrain the solutions using an autoencoder trained on a database of ground-truth curves. On average, we achieve reconstruction errors as low as those that can arise due to manufacturing imperfections between two copies of the same camera. We provide predicted sensitivities for more than 1,000 cameras that the Adobe DNG Converter currently supports, and discuss which tasks can become trivial when camera responses are available.
DOI: 10.5281/zenodo.8314702
title: Camera Dataset - Solomatov and Akkaynak (2023)

description: <strong>Source URL</strong>: https://color-lab-eilat.github.io/Spectral-sensitivity-estimation-web/#camera-dataset-section<br> <br> <strong>Abstract</strong><br> A number of problems in computer vision and related fields would be mitigated if camera spectral sensitivities were known. As consumer cameras are not designed for high-precision visual tasks, manufacturers do not disclose spectral sensitivities. Their estimation requires a costly optical setup, which triggered researchers to come up with numerous indirect methods that aim to lower cost and complexity by using color targets. However, the use of color targets gives rise to new complications that make the estimation more difficult, and consequently, there currently exists no simple, low-cost, robust go-to method for spectral sensitivity estimation that non-specialized research labs can adopt. Furthermore, even if not limited by hardware or cost, researchers frequently work with imagery from multiple cameras that they do not have in their possession. To provide a practical solution to this problem, we propose a framework for spectral sensitivity estimation that not only does not require any hardware (including a color target), but also does not require physical access to the camera itself. Similar to other work, we formulate an optimization problem that minimizes a two-term objective function: a camera-specific term from a system of equations, and a universal term that bounds the solution space. Different than other work, we utilize publicly available high-quality calibration data to construct both terms. We use the colorimetric mapping matrices provided by the Adobe DNG Converter to formulate the camera-specific system of equations, and constrain the solutions using an autoencoder trained on a database of ground-truth curves. On average, we achieve reconstruction errors as low as those that can arise due to manufacturing imperfections between two copies of the same camera. We provide predicted sensitivities for more than 1,000 cameras that the Adobe DNG Converter currently supports, and discuss which tasks can become trivial when camera responses are available.
DOI: 10.6084/m9.figshare.24082182
title: Data and code for the paper <b><i>Exploring the Impact of Short Daily Hemodialysis on Muscle Strength and Bone Health in End-Stage Kidney Disease Patients: A Cross-Sectional Study</i></b>

description: All data and code used for the study <b><i>Exploring the Impact of Short Daily Hemodialysis on Muscle Strength and Bone Health in End-Stage Kidney Disease Patients: A Cross-Sectional Study</i></b>
DOI: 10.6084/m9.figshare.24082182.v1
title: Data and code for the paper <b><i>Exploring the Impact of Short Daily Hemodialysis on Muscle Strength and Bone Health in End-Stage Kidney Disease Patients: A Cross-Sectional Study</i></b>

description: All data and code used for the study <b><i>Exploring the Impact of Short Daily Hemodialysis on Muscle Strength and Bone Health in End-Stage Kidney Disease Patients: A Cross-Sectional Study</i></b>
DOI: 10.6084/m9.figshare.24082113
title: Psychological Flexibility, Coping, and Attachment Style in Predicting Secondary Traumatic Stress and Burnout In Forensic Inpatient Staff

description: 102 healthcare professionals working forensic inpatient settings completed the measures assessing: burnout, secondary traumatic stress, psychological flexibility, coping style, attachment style and a demographic questionnaire recording length of service and the sex of staff.
DOI: 10.6084/m9.figshare.24082128.v1
title: Population weighted average Travel Distance to nearest 24-hr ED by CSD (csv)

description: Contains the CSD identifier (CSDUID) and the spaces population weighted average travel time to closest 24-hr Emergency department
DOI: 10.6084/m9.figshare.24082119.v2
title: Population weighted average Travel Distance to nearest 24-hr ED by CSD (csv)

description: Contains the CSD identifier (CSDUID) and the spaces population weighted average travel distance to closest 24-hr Emergency department
DOI: 10.6084/m9.figshare.24082233
title: Canadian Road Network File for 2021 (shp)

description: This shape file was used to develop the network analysis necessary to perform this analysis in ArcGIS Pro v 3.0.3
DOI: 10.6084/m9.figshare.24082221
title: antsxnetWmh.h5

description: unetweightssmh<br>
DOI: 10.6084/m9.figshare.24082221.v1
title: antsxnetWmh.h5

description: unetweightssmh<br>
DOI: 10.5281/zenodo.8316785
title: Dataset for "Optical Performance of Commercial Liquid Lenses in Microgravity"

description: Dataset for microgravity investigation of Corning Varioptic A-39N0 and Optotune EL-16-40-TC-VIS lenses
DOI: 10.5281/zenodo.8316784
title: Dataset for "Optical Performance of Commercial Liquid Lenses in Microgravity"

description: Dataset for microgravity investigation of Corning Varioptic A-39N0 and Optotune EL-16-40-TC-VIS lenses
DOI: 10.5281/zenodo.8316793
title: Red de drenaje de la cuenca alta y media del río Luján

description: Se delimitó la red de drenaje de la cuenca alta y cuenca media del río Luján a través del uso de un modelo digital de terreno (MDT) de 5 m de resolución elaborado a partir de un relevamiento aéreo durante el 2018 (Instituto Geográfico Nacional, 2020) y fue corregida en base a imágenes de imágenes satelitales de alta resolución para los años 2021 y 2022 provistas por Google Earth de la costelación de satélites de la companía Maxar Technologies. Todas las capas generadas fueron georreferenciadas según el sistema WGS84 con proyección POSGAR 2007 - FAJA 5.
description: Shapefiles de la red de drenaje de la cuenca alta y media del río Luján. Todas las capas generadas fueron georreferenciadas según el sistema WGS84 con proyección POSGAR 2007 - FAJA 5.
description: {"references": ["Instituto Geogr\u00e1fico Nacional. (2020). Modelo Digital de Terreno de la Cuenca R\u00edo Luj\u00e1n \u2013 Buenos Aires. Disponible en: https://mapa.ign.gob.ar", "Maxar Technologies Inc. (2022). CONSTELLATION. The world's most advanced Earth observation satellites. https://www.maxar.com/constellation"]}
DOI: 10.5281/zenodo.8316792
title: Red de drenaje de la cuenca alta y media del río Luján

description: Se delimitó la red de drenaje de la cuenca alta y cuenca media del río Luján a través del uso de un modelo digital de terreno (MDT) de 5 m de resolución elaborado a partir de un relevamiento aéreo durante el 2018 (Instituto Geográfico Nacional, 2020) y fue corregida en base a imágenes de imágenes satelitales de alta resolución para los años 2021 y 2022 provistas por Google Earth de la costelación de satélites de la companía Maxar Technologies. Todas las capas generadas fueron georreferenciadas según el sistema WGS84 con proyección POSGAR 2007 - FAJA 5.
description: Shapefiles de la red de drenaje de la cuenca alta y media del río Luján. Todas las capas generadas fueron georreferenciadas según el sistema WGS84 con proyección POSGAR 2007 - FAJA 5.
description: {"references": ["Instituto Geogr\u00e1fico Nacional. (2020). Modelo Digital de Terreno de la Cuenca R\u00edo Luj\u00e1n \u2013 Buenos Aires. Disponible en: https://mapa.ign.gob.ar", "Maxar Technologies Inc. (2022). CONSTELLATION. The world's most advanced Earth observation satellites. https://www.maxar.com/constellation"]}
DOI: 10.5281/zenodo.8316995
title: Red de drenaje de la cuenca alta y media del río Luján

description: Se delimitó la red de drenaje de la cuenca alta y cuenca media del río Luján a través del uso de un modelo digital de terreno (MDT) de 5 m de resolución elaborado a partir de un relevamiento aéreo durante el 2018 (Instituto Geográfico Nacional, 2020) y fue corregida en base a imágenes de imágenes satelitales de alta resolución para los años 2021 y 2022 provistas por Google Earth de la costelación de satélites de la companía Maxar Technologies. Todas las capas generadas fueron georreferenciadas según el sistema WGS84 con proyección POSGAR 2007 - FAJA 5.
description: Shapefiles de la red de drenaje de la cuenca alta y media del río Luján. Todas las capas generadas fueron georreferenciadas según el sistema WGS84 con proyección POSGAR 2007 - FAJA 5.
description: {"references": ["Instituto Geogr\u00e1fico Nacional. (2020). Modelo Digital de Terreno de la Cuenca R\u00edo Luj\u00e1n \u2013 Buenos Aires. Disponible en: https://mapa.ign.gob.ar", "Maxar Technologies Inc. (2022). CONSTELLATION. The world's most advanced Earth observation satellites. https://www.maxar.com/constellation"]}
DOI: 10.5281/zenodo.7992529
title: Supplementary CIF files for "Shedding Light on the Enigmatic TcO2 ⋅ xH2O Structure with Density Functional Theory and EXAFS Spectroscopy"

description: Optimized geometries from the paper "Shedding Light on the Enigmatic TcO2 ⋅ <em>x</em>H2O Structure with Density Functional Theory and EXAFS Spectroscopy" (https://doi.org/10.1002/chem.202202235), provided in CIF format. All structures were fully optimized (lattice vectors and atomic coordinates) using AMS/BAND (https://www.scm.com/) with the PBE density functional, scalar relativistic effects (ZORA), and numerical atomic orbitals (NAOs) augmented with a triple-zeta polarized (TZP) set of Slater-type basis functions. For the chains, D3 dispersion corrections were also included.
description: The research was funded by the European Commission (EC) through the EURAD FUTURE T3 project (H2020-847593) and by the German Federal Ministry of Education and Research (BMBF) through the KRIMI project (02NUK056C).
description: {"references": ["A. F. Oliveira, A. Kuc, T. Heine, U. Abram, A. C. Scheinost, Chem. Eur. J. 2022, 28, e202202235."]}
DOI: 10.5281/zenodo.7992528
title: Supplementary CIF files for "Shedding Light on the Enigmatic TcO2 ⋅ xH2O Structure with Density Functional Theory and EXAFS Spectroscopy"

description: Optimized geometries from the paper "Shedding Light on the Enigmatic TcO2 ⋅ <em>x</em>H2O Structure with Density Functional Theory and EXAFS Spectroscopy" (https://doi.org/10.1002/chem.202202235), provided in CIF format. All structures were fully optimized (lattice vectors and atomic coordinates) using AMS/BAND (https://www.scm.com/) with the PBE density functional, scalar relativistic effects (ZORA), and numerical atomic orbitals (NAOs) augmented with a triple-zeta polarized (TZP) set of Slater-type basis functions. For the chains, D3 dispersion corrections were also included.
description: The research was funded by the European Commission (EC) through the EURAD FUTURE T3 project (H2020-847593) and by the German Federal Ministry of Education and Research (BMBF) through the KRIMI project (02NUK056C).
description: {"references": ["A. F. Oliveira, A. Kuc, T. Heine, U. Abram, A. C. Scheinost, Chem. Eur. J. 2022, 28, e202202235."]}
DOI: 10.5519/qd.hpjp3tkd
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (300 records)
DOI: 10.5281/zenodo.8226867
title: Supplement data for : Intratumoral drug-releasing microdevices allow in situ high throughput pharmaco phenotyping in patients with gliomas

description: Transcriptomic and metabolomic data associated with the manuscript: Intratumoral drug-releasing microdevices allow in situ high throughput pharmaco phenotyping in patients with gliomas.
DOI: 10.5281/zenodo.8226866
title: Supplement data for : Intratumoral drug-releasing microdevices allow in situ high throughput pharmaco phenotyping in patients with gliomas

description: Transcriptomic and metabolomic data associated with the manuscript: Intratumoral drug-releasing microdevices allow in situ high throughput pharmaco phenotyping in patients with gliomas.
DOI: 10.5281/zenodo.7906798
title: Satellite-driven back trajectories from the CAFE-Brazil flights

description: Satellite-driven back trajectories from the locations of the CAFE-Brazil flights.
description: Acknowledgments: I am grateful to Anna Possner for her insightful discussions and valuable suggestions, as her original idea served as the driving force behind these calculations. The implementation of the Python algorithm used for calculating the trajectories drew inspiration from Tom Gowa's code, which can be found at https://github.com/tomgowan/trajectories. I appreciate the assistance provided by Rogerio Batista in retrieving the data from the CPTEC ftp database. This work was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – TRR 301 – Project-ID 428312742.
description: {"references": ["NOAA Geostationary Operational Environmental Satellites (GOES) 16 was accessed on April 30th, 2023, from https://registry.opendata.aws/noaa-goes and http://ftp.cptec.inpe.br/goes/goes16/retangular/ch13/."]}
DOI: 10.5281/zenodo.7906799
title: Satellite-driven back trajectories from the CAFE-Brazil flights

description: Satellite-driven back trajectories from the locations of the CAFE-Brazil flights.
description: Acknowledgments: I am grateful to Anna Possner for her insightful discussions and valuable suggestions, as her original idea served as the driving force behind these calculations. The implementation of the Python algorithm used for calculating the trajectories drew inspiration from Tom Gowa's code, which can be found at https://github.com/tomgowan/trajectories. I appreciate the assistance provided by Rogerio Batista in retrieving the data from the CPTEC ftp database. This work was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – TRR 301 – Project-ID 428312742.
description: {"references": ["NOAA Geostationary Operational Environmental Satellites (GOES) 16 was accessed on April 30th, 2023, from https://registry.opendata.aws/noaa-goes and http://ftp.cptec.inpe.br/goes/goes16/retangular/ch13/."]}
DOI: 10.5281/zenodo.8316742
title: Satellite-driven back trajectories from the CAFE-Brazil flights

description: Satellite-driven back trajectories from the locations of the CAFE-Brazil flights.
description: Acknowledgments: I am grateful to Anna Possner for her insightful discussions and valuable suggestions, as her original idea served as the driving force behind these calculations. The implementation of the Python algorithm used for calculating the trajectories drew inspiration from Tom Gowa's code, which can be found at https://github.com/tomgowan/trajectories. I appreciate the assistance provided by Rogerio Batista in retrieving the data from the CPTEC ftp database. This work was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – TRR 301 – Project-ID 428312742.
description: {"references": ["NOAA Geostationary Operational Environmental Satellites (GOES) 16 was accessed on April 30th, 2023, from https://registry.opendata.aws/noaa-goes and http://ftp.cptec.inpe.br/goes/goes16/retangular/ch13/."]}
DOI: 10.6084/m9.figshare.24082299
title: Putin's war axiology (February - September 2022)

description: A detailed list of identified values and axiological terms, accompanied by corresponding excerpts from Putin’s utterances during the first stage of the war against Ukraine (February - September 2022)
DOI: 10.6084/m9.figshare.24082299.v1
title: Putin's war axiology (February - September 2022)

description: A detailed list of identified values and axiological terms, accompanied by corresponding excerpts from Putin’s utterances during the first stage of the war against Ukraine (February - September 2022)
DOI: 10.5281/zenodo.8317025
title: Cloud-CCI+ SEVIRI CRE case study dataset

description: A dataset of tracked DCC cores and anvils over sub-Saharan Africa (approximately 18°W-46°E, 31°S-15°N) for four months (May 2016 to August 2016). The dataset tracks the cloud properties and their cloud radiative effect over the lifetime of each DCC. The files contained within <em>seviri_labels_* </em>contain daily data of tracked DCCs on the SEVIRI grid with spatial masks corresponding to each detected anvil and core at each time step. The files contained within <em>seviri_statistics</em> contain the properties of each DCC core and anvil at each timestep along their lifetime. Each file contains all DCCs tracked within one month. This dataset accompanies the article <em>"A Lagrangian Perspective on the Lifecycle and Cloud Radiative Effect of Deep Convective Clouds Over Africa" </em>by William k. Jones, Martin Stengel and Philip Stier, which is to be submitted to ACP
DOI: 10.5281/zenodo.8317024
title: Cloud-CCI+ SEVIRI CRE case study dataset

description: A dataset of tracked DCC cores and anvils over sub-Saharan Africa (approximately 18°W-46°E, 31°S-15°N) for four months (May 2016 to August 2016). The dataset tracks the cloud properties and their cloud radiative effect over the lifetime of each DCC. The files contained within <em>seviri_labels_* </em>contain daily data of tracked DCCs on the SEVIRI grid with spatial masks corresponding to each detected anvil and core at each time step. The files contained within <em>seviri_statistics</em> contain the properties of each DCC core and anvil at each timestep along their lifetime. Each file contains all DCCs tracked within one month. This dataset accompanies the article <em>"A Lagrangian Perspective on the Lifecycle and Cloud Radiative Effect of Deep Convective Clouds Over Africa" </em>by William k. Jones, Martin Stengel and Philip Stier, which is to be submitted to ACP
DOI: 10.5281/zenodo.7552550
title: Data of publication Carbon Dioxide Release from Retrogressive Thaw Slumps in Siberia

description: This is the publication of data for the publication Beer et al., Carbon Dioxide Release from Retrogressive Thaw Slumps in Siberia, submitted to the Journal Environmental Research Letters in 2023. There are three variables included in the file results_thawslump_extrapolation_23092022.xlsx file: area of all thaw slumps, 0-100 cm carbon stocks of all thaw slumps, and annual CO2 release from all thaw slumps. In the mat-file there is even more information on soil temperature and CO2 production and emissions for a complete uncertainty assessment.
DOI: 10.5281/zenodo.7552549
title: Data of publication Carbon Dioxide Release from Retrogressive Thaw Slumps in Siberia

description: This is the publication of data for the publication Beer et al., Carbon Dioxide Release from Retrogressive Thaw Slumps in Siberia, submitted to the Journal Environmental Research Letters in 2023. There are three variables included in the file results_thawslump_extrapolation_23092022.xlsx file: area of all thaw slumps, 0-100 cm carbon stocks of all thaw slumps, and annual CO2 release from all thaw slumps. In the mat-file there is even more information on soil temperature and CO2 production and emissions for a complete uncertainty assessment.
DOI: 10.6084/m9.figshare.24082305
title: Values attributed to Russian in Putin's speeches on the 'special military operation' against Ukraine during its first phase (February - September 2022)

description: A detailed list of the values attributed by Putin to Russia in his statements about the Russian-Ukrainian war (February - September 2022)
DOI: 10.6084/m9.figshare.24082305.v1
title: Values attributed to Russian in Putin's speeches on the 'special military operation' against Ukraine during its first phase (February - September 2022)

description: A detailed list of the values attributed by Putin to Russia in his statements about the Russian-Ukrainian war (February - September 2022)
DOI: 10.5281/zenodo.8310978
title: Supplementary datasets for "Thermal evolution of the lithosphere-asthenosphere boundary beneath arc and its geodynamic implications: depth variation of thermal histories of mantle xenoliths from Ichinomegata, Northeast Japan"

description: Supplementary datasets for Sato and Ozawa (2023, JGR:SE) "Thermal evolution of the lithosphere-asthenosphere boundary beneath arc and its geodynamic implications: depth variation of thermal histories of mantle xenoliths from Ichinomegata, Northeast Japan" <strong>Data Set S1.</strong> Original chemical zoning profile data of olivine and pyroxene and raw results of the diffusion modelling applied to them. <strong>Data Set S2.</strong> Original X-ray mapping data of olivine and pyroxene. <strong>Data Set S3.</strong> Composite images of microphotographs showing the entire thin section of the examined xenolith samples.