cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.6362298
title: MASS2ANT Snowfall Dataset (Downscaling @5.5km over Dronning Maud Land, Antarctica, 1850 - 2014): Daily fields (Part 3)

description: We provide in this dataset maps at 5.5 km resolution of the daily and yearly accumulated snowfall over emerged land (Ice Sheet) of Dronning Maud Land (Antarctica) from 1850 to 2014. We used a statistical method to derive fine resolution maps from GCM runs (CESM2, 10 runs). In the method, we searched for analogs in a database we constructed from the association between re-analyses large-scale meteorological fields (ERA5 and ERA-Interim) and RCM daily accumulated snowfall (RACMO2.3p5.5). RACMO2.3p5.5 data are available freely on request (https://www.projects.science.uu.nl/iceclimate/models/antarctica.php). CESM2 CMIP6 runs are also freely available (https://esgf-node.llnl.gov/search/cmip6/). The complete description of the algorithm and performance is described in: <strong><em>Ghilain </em><em>N.,</em><em> Vannitsem </em><em>S.,</em><em> Dalaiden </em><em>Q.,</em><em> Goosse </em><em>H.,</em><em> De Cruz </em><em>L.,</em><em> </em><em>Wei</em><em> </em><em>W., </em><em>Reconstruction</em><em> of d</em><em>aily snowfall accumulation at 5.</em><em>5</em><em>km resolution over Dronning Maud Land, Antarctica, from 1850 to 2014 </em><em>using an analog-based downscaling technique</em></strong>, submitted to Earth System Science Data (ESSD). The MASS2ANT Snowfall dataset is composed of the annual estimations of snowfall over Dronning Maud Land, the daily time series for the total period for all the emerged grid points of the domain, the principal components time series and Empirical Orthogonal Functions (EOF) offering the possibility to analyze the synoptic weather patterns associated to snowfall over the ice sheet and the Principal Component weights (PCs) time series from the re-analysis in case one wants to extend or improve the database. Realistic weather patterns can be recomposed in associating (product of matrices) the PCs with the EOFs. Here (Daily fields - Part 3), we provide the daily snowfall time series resulting from the downscaling of the 3 last members of CESM2, using ERA-Interim (or ERA5) and RACMO2.3p5.5 for training.
description: The study was funded in the framework of the MASS2ANT project (\url{https://www.elic.ucl.ac.be/users/klein/Mass2Ant/index.html}, contract No BR/165/A2) by the Belgian Science Policy.
DOI: 10.5281/zenodo.6379053
title: Database of Indian Social Media Influencers on Twitter

description: Databases of highly networked individuals have been indispensable in studying narratives and influence on social media. To support studies on Twitter in India, we present a systematically categorised database of accounts of influence on Twitter in India, identified and annotated through an iterative process of friends, networks, and self-described profile information, verified manually. We built an initial set of accounts based on the friend network of a seed set of accounts based on real-world renown in various fields, and then snowballed “friends of friends” multiple times, and rank ordered individuals based on the number of in-group connections, and overall followers. We then manually classified identified accounts under the categories of entertainment, sports, business, government, institutions, journalism, civil society accounts that have independent standing outside of social media, as well as a category of “digital first” referring to accounts that de- rive their primary influence from online activity. Overall, we annotated 11580 unique accounts across all categories. The database is useful studying various questions related to the role of influencers in polarisation, misinformation, extreme speech, political discourse etc.
DOI: 10.5281/zenodo.6379052
title: Database of Indian Social Media Influencers on Twitter

description: Databases of highly networked individuals have been indispensable in studying narratives and influence on social media. To support studies on Twitter in India, we present a systematically categorised database of accounts of influence on Twitter in India, identified and annotated through an iterative process of friends, networks, and self-described profile information, verified manually. We built an initial set of accounts based on the friend network of a seed set of accounts based on real-world renown in various fields, and then snowballed “friends of friends” multiple times, and rank ordered individuals based on the number of in-group connections, and overall followers. We then manually classified identified accounts under the categories of entertainment, sports, business, government, institutions, journalism, civil society accounts that have independent standing outside of social media, as well as a category of “digital first” referring to accounts that de- rive their primary influence from online activity. Overall, we annotated 11580 unique accounts across all categories. The database is useful studying various questions related to the role of influencers in polarisation, misinformation, extreme speech, political discourse etc.
DOI: 10.34740/kaggle/dsv/3345725
title: Russian Invasion of Ukraine
DOI: 10.5281/zenodo.6378971
title: Linguistic-symbolic classification of occupations

description: As a result, it has been considered the following occupational categories, based on the degree of symbolic analysis and language intensity: (A) high symbolic analysts, (B) low symbolic analysts, (C) high intensity oral interaction with public (high public service), (D) low intensity oral interaction with public (low public service), and (E) manual labor occupations with limited symbolic and oral demands. Further, and within (B) category -low symbolic analysts-, it is distinguished between (B1) those whose work is generally inside the organization (such as file clerks) and (B2) those whose work includes interacting with the public (such as receptionists). In a similar way, (C) category is also divided into (C1) category of nurses and (C2-C5) which group the remainder of the high public service occupations. The result of the categorization of occupations by language use is summarized in the table below: Major occupational classification Linguistic characteristics of occupation Sub classification Example of occupation A: High symbolic analysts Produce/consume long or complex written communications, with variable but often important oral communication A1. Upper management Chief executive, human resource executive A2. Professionals Lawyer, doctor A3. Lower management First line manager/supervisor A4. High symbolic analysts, not managers Public relations specialists, computer systems specialists B: Low symbolic analysts Produce/consume short or simple written communications, with variable but often important oral communication B1. Low symbolic analysts with low likelihood of public interaction File clerks B2. Low symbolic analysts with high likelihood of public interaction Receptionists, billing/appointment clerks C: In-person service workers with high communicative demands Important oral communication, limited but present written skills, and high public interaction C1. Nurses Nurses C2. Assistants and technicians in public service settings Medical technicians C3. Police, etc. Police, detectives, investigators C4. Firefighters, emergency medical technicians Firefighters, emergency medical technicians C5. Miscellaneous Counselors, dispatchers D. In-person service workers with low communicative demands Simple oral communication and public interaction, very limited or no writing (no subcategories in our study) home health care aides, security guards E. Manual work Limited oral and written consumption and production E1. Skilled manual work Plumber E2. Unskilled manual work Janitor
description: Source: Alarcon, A. et al. (2014). The Occupational Location of Spanish-English Bilinguals in the New Information Economy. In R. M. Callahan & P. C. Gandara (Eds.), The Bilingual Advantage (pp. 120-139). Clevedon, Bristol. Multilingual Matters Editorial.
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DOI: 10.5281/zenodo.6378970
title: Linguistic-symbolic classification of occupations

description: As a result, it has been considered the following occupational categories, based on the degree of symbolic analysis and language intensity: (A) high symbolic analysts, (B) low symbolic analysts, (C) high intensity oral interaction with public (high public service), (D) low intensity oral interaction with public (low public service), and (E) manual labor occupations with limited symbolic and oral demands. Further, and within (B) category -low symbolic analysts-, it is distinguished between (B1) those whose work is generally inside the organization (such as file clerks) and (B2) those whose work includes interacting with the public (such as receptionists). In a similar way, (C) category is also divided into (C1) category of nurses and (C2-C5) which group the remainder of the high public service occupations. The result of the categorization of occupations by language use is summarized in the table below: Major occupational classification Linguistic characteristics of occupation Sub classification Example of occupation A: High symbolic analysts Produce/consume long or complex written communications, with variable but often important oral communication A1. Upper management Chief executive, human resource executive A2. Professionals Lawyer, doctor A3. Lower management First line manager/supervisor A4. High symbolic analysts, not managers Public relations specialists, computer systems specialists B: Low symbolic analysts Produce/consume short or simple written communications, with variable but often important oral communication B1. Low symbolic analysts with low likelihood of public interaction File clerks B2. Low symbolic analysts with high likelihood of public interaction Receptionists, billing/appointment clerks C: In-person service workers with high communicative demands Important oral communication, limited but present written skills, and high public interaction C1. Nurses Nurses C2. Assistants and technicians in public service settings Medical technicians C3. Police, etc. Police, detectives, investigators C4. Firefighters, emergency medical technicians Firefighters, emergency medical technicians C5. Miscellaneous Counselors, dispatchers D. In-person service workers with low communicative demands Simple oral communication and public interaction, very limited or no writing (no subcategories in our study) home health care aides, security guards E. Manual work Limited oral and written consumption and production E1. Skilled manual work Plumber E2. Unskilled manual work Janitor
description: Source: Alarcon, A. et al. (2014). The Occupational Location of Spanish-English Bilinguals in the New Information Economy. In R. M. Callahan & P. C. Gandara (Eds.), The Bilingual Advantage (pp. 120-139). Clevedon, Bristol. Multilingual Matters Editorial.
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DOI: 10.34740/kaggle/dsv/3345806
title: Russian Invasion of Ukraine
DOI: 10.5281/zenodo.6379098
title: SciExpeM - 10.5281/zenodo.6379098

description: Black, G.; Curran, H.J.; Pichon, S.; Simmie, J.M.; Zhukov, V. - Combustion And Flame, 2010, (157), 363-373
DOI: 10.5281/zenodo.6379097
title: SciExpeM - 10.5281/zenodo.6379098

description: Black, G.; Curran, H.J.; Pichon, S.; Simmie, J.M.; Zhukov, V. - Combustion And Flame, 2010, (157), 363-373
DOI: 10.5281/zenodo.6351581
title: Language intensity scale

description: This is an index comprised by 3 subindexs and a global index (which is the result of a combination of the other three). These are:<br> LC Index: Linguistic Competences<br> CA Index: Communication Skills<br> IA Index: Information-processing Abilities<br> ILT/LIO Index: Linguistic Intensity of Occupations<br> To elaborate the different indexes, the information contained in the O*Net database (corresponding to the USA of the year 2015) has been used, from which those variables (taken as items) directly related to each one have been considered of the first three indices (CL, HTI, HSC) considered as reflective constructs. In contrast, the ILT index has been constructed as a second order construct, of a formative nature, based on the factorial scores of the first three indices. For the validation of the measurement scales and the obtaining of the factorial scores of the different indexes, a statistical model of structural equations has been used, specifically based on the technique of the variances (PLS). The factorial scores obtained for each dimension, both first order (CL, HTI, HSC) and second order (ILT), have been transformed into a range of variation in the 0-100 range, to obtain the values For each occupation of the different indexes.
description: For more detail about the development of these scales and indexes and their application: Vidal A. and Lopez-Panisello, MB. (2021). Construcción y validación de una escala de medida del concepto Intensidad Lingüística del Trabajo (ILT) y su impacto sobre los salarios. In: Vidal and Alarcón (eds.) Lenguaje y Ocupaciones. Editorial URV
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DOI: 10.5281/zenodo.6351580
title: Language intensity scale

description: This is an index comprised by 3 subindexs and a global index (which is the result of a combination of the other three). These are:<br> LC Index: Linguistic Competences<br> CA Index: Communication Skills<br> IA Index: Information-processing Abilities<br> ILT/LIO Index: Linguistic Intensity of Occupations<br> To elaborate the different indexes, the information contained in the O*Net database (corresponding to the USA of the year 2015) has been used, from which those variables (taken as items) directly related to each one have been considered of the first three indices (CL, HTI, HSC) considered as reflective constructs. In contrast, the ILT index has been constructed as a second order construct, of a formative nature, based on the factorial scores of the first three indices. For the validation of the measurement scales and the obtaining of the factorial scores of the different indexes, a statistical model of structural equations has been used, specifically based on the technique of the variances (PLS). The factorial scores obtained for each dimension, both first order (CL, HTI, HSC) and second order (ILT), have been transformed into a range of variation in the 0-100 range, to obtain the values For each occupation of the different indexes.
description: For more detail about the development of these scales and indexes and their application: Vidal A. and Lopez-Panisello, MB. (2021). Construcción y validación de una escala de medida del concepto Intensidad Lingüística del Trabajo (ILT) y su impacto sobre los salarios. In: Vidal and Alarcón (eds.) Lenguaje y Ocupaciones. Editorial URV
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DOI: 10.5281/zenodo.4287517
title: MASS2ANT Snowfall Dataset (Downscaling @5.5km over Dronning Maud Land, Antarctica, 1850 - 2014)

description: <strong>MASS2ANT Snowfall Dataset: Information for users</strong> November 2020 N. Ghilain<sup>1</sup>, S. Vannitsem<sup>1</sup>, Q. Dalaiden<sup>2</sup>, H. Goosse<sup>2</sup>, L. De Cruz<sup>1</sup> <sup>1</sup>Royal Meteorological Institute, Uccle, Belgium <sup>2</sup>UCLouvain, Earth and Life Institute, Louvain-la-Neuve, Belgium contacts RMI: stephane.vannitsem@meteo.be, nicolas.ghilain@meteo.be, lesley.decruz@meteo.be contacts UCLouvain: hugues.goosse@uclouvain.be, quentin.dalaiden@uclouvain.be We provide in this dataset maps at 5.5 km resolution of the daily and yearly accumulated snowfall over emerged land (Ice Sheet) of Dronning Maud Land (Antarctica) from 1850 to 2014. We used a statistical method to derive fine resolution maps from GCM runs (CESM2, 10 runs). In the method, we searched for analogs in a database we constructed from the association between re-analyses large-scale meteorological fields (ERA5 and ERA-Interim) and RCM daily accumulated snowfall (RACMO2.3p5.5). RACMO2.3p5.5 data are available freely on request (https://www.projects.science.uu.nl/iceclimate/models/antarctica.php). CESM2 CMIP6 runs are also freely available (https://esgf-node.llnl.gov/search/cmip6/). The complete description of the algorithm and performance is described in: <em>Ghilain </em><em>N.,</em><em> Vannitsem </em><em>S.,</em><em> Dalaiden </em><em>Q.,</em><em> Goosse </em><em>H.,</em><em> De Cruz </em><em>L.,</em><em> </em><em>Wei</em><em> </em><em>W., </em><em>Reconstruction</em><em> of d</em><em>aily snowfall accumulation at 5.</em><em>5</em><em>km resolution over Dronning Maud Land, Antarctica, from 1850 to 2014 </em><em>using an analog-based downscaling technique</em>, submitted to Earth System Science Data (ESSD). The MASS2ANT Snowfall dataset is composed of the annual estimations of snowfall over Dronning Maud Land, the daily time series for the total period for all the emerged grid points of the domain (2 files are given in example, the all set is available on zenodo: 10.5281/zenodo.6355455, 10.5281/zenodo.6359385, 10.5281/zenodo.6362299), the principal components time series and Empirical Orthogonal Functions (EOF) offering the possibility to analyze the synoptic weather patterns associated to snowfall over the ice sheet and the Principal Component weights (PCs) time series from the re-analysis in case one wants to extend or improve the database. Realistic weather patterns can be recomposed in associating (product of matrices) the PCs with the EOFs The method could be easily expanded to other sources (other GCM, other reference RCM or other reanalysis), and potentially for other parts of Antarctica. Samples of the programs used to generate this database are therefore also provided here. Refer to MASS2ANT_Snowfall_Dataset_InfoUsers.pdf
description: The study was funded in the framework of the MASS2ANT project (\url{https://www.elic.ucl.ac.be/users/klein/Mass2Ant/index.html}, contract No BR/165/A2) by the Belgian Science Policy.
DOI: 10.5281/zenodo.4287516
title: MASS2ANT Snowfall Dataset (Downscaling @5.5km over Dronning Maud Land, Antarctica, 1850 - 2014)

description: <strong>MASS2ANT Snowfall Dataset: Information for users</strong> November 2020 N. Ghilain<sup>1</sup>, S. Vannitsem<sup>1</sup>, Q. Dalaiden<sup>2</sup>, H. Goosse<sup>2</sup>, L. De Cruz<sup>1</sup> <sup>1</sup>Royal Meteorological Institute, Uccle, Belgium <sup>2</sup>UCLouvain, Earth and Life Institute, Louvain-la-Neuve, Belgium contacts RMI: stephane.vannitsem@meteo.be, nicolas.ghilain@meteo.be, lesley.decruz@meteo.be contacts UCLouvain: hugues.goosse@uclouvain.be, quentin.dalaiden@uclouvain.be We provide in this dataset maps at 5.5 km resolution of the daily and yearly accumulated snowfall over emerged land (Ice Sheet) of Dronning Maud Land (Antarctica) from 1850 to 2014. We used a statistical method to derive fine resolution maps from GCM runs (CESM2, 10 runs). In the method, we searched for analogs in a database we constructed from the association between re-analyses large-scale meteorological fields (ERA5 and ERA-Interim) and RCM daily accumulated snowfall (RACMO2.3p5.5). RACMO2.3p5.5 data are available freely on request (https://www.projects.science.uu.nl/iceclimate/models/antarctica.php). CESM2 CMIP6 runs are also freely available (https://esgf-node.llnl.gov/search/cmip6/). The complete description of the algorithm and performance is described in: <em>Ghilain </em><em>N.,</em><em> Vannitsem </em><em>S.,</em><em> Dalaiden </em><em>Q.,</em><em> Goosse </em><em>H.,</em><em> De Cruz </em><em>L.,</em><em> </em><em>Wei</em><em> </em><em>W., </em><em>Reconstruction</em><em> of d</em><em>aily snowfall accumulation at 5.</em><em>5</em><em>km resolution over Dronning Maud Land, Antarctica, from 1850 to 2014 </em><em>using an analog-based downscaling technique</em>, submitted to Earth System Science Data (ESSD). The MASS2ANT Snowfall dataset is composed of the annual estimations of snowfall over Dronning Maud Land, the daily time series for the total period for all the emerged grid points of the domain (2 files are given in example, the all set is available on zenodo: 10.5281/zenodo.6355455, 10.5281/zenodo.6359385, 10.5281/zenodo.6362299), the principal components time series and Empirical Orthogonal Functions (EOF) offering the possibility to analyze the synoptic weather patterns associated to snowfall over the ice sheet and the Principal Component weights (PCs) time series from the re-analysis in case one wants to extend or improve the database. Realistic weather patterns can be recomposed in associating (product of matrices) the PCs with the EOFs The method could be easily expanded to other sources (other GCM, other reference RCM or other reanalysis), and potentially for other parts of Antarctica. Samples of the programs used to generate this database are therefore also provided here. Refer to MASS2ANT_Snowfall_Dataset_InfoUsers.pdf
description: The study was funded in the framework of the MASS2ANT project (\url{https://www.elic.ucl.ac.be/users/klein/Mass2Ant/index.html}, contract No BR/165/A2) by the Belgian Science Policy.
DOI: 10.34740/kaggle/dsv/3345850
title: Russian Invasion of Ukraine
DOI: 10.6084/m9.figshare.19403597
title: Supplementary Material for: Die deutsche Version der Interpersonal Hopelessness Scale (IHS)

description: <b><i>Hintergrund:</i></b> Angesichts des angenommenen Einflusses interpersonaler Hoffnungslosigkeit für die Entstehung aktiver Suizidgedanken, wie von der Interpersonalen Theorie Suizidalen Verhaltens [Joiner. Why people die by suicide. 2005] postuliert, zielt diese Studie darauf ab, erstmals eine deutsche Version der Interpersonalen Hoffnungslosigkeitsskala [IHS; Tucker et al. Psychiatry Res. 2018;259:427–32], die IHS-d, vorzustellen und psychometrisch zu überprüfen. <b><i>Material und Methoden:</i></b> <i>N</i> = 437 Teilnehmende (75.1% weiblich) zwischen 18 und 71 Jahren (M = 29.75, SD = 11.25) nahmen an einer querschnittlichen Online-Studie teil. Die Faktorstruktur der IHS-d wurde mittels konfirmatorischer Faktorenanalyse überprüft. Zusätzlich wurden Konstruktvalidität und Reliabilität evaluiert. <b><i>Ergebnis:</i></b> Es ergab sich eine signifikant bessere Datenpassung für ein 2-Faktor-Modell als für das 1-Faktor-Modell. Die identifizierten Subskalen (Interpersonale Hoffnungslosigkeit hinsichtlich perceived burdensomeness und hinsichtlich thwarted belongingness) erzielten hohe Faktorladungen ≥0.75; Inter-Item-Korrelationen, <i>r</i> ≥ 0.60, Item-Skala-Korrelationen, <i>r</i><sub><i>it</i></sub> ≥ 0.71 und interne Konsistenzen, <i>α</i><sub><i>PB</i></sub> = 0.93; <i>α</i><sub><i>TB</i></sub> = 0.92. <b><i>Diskussion:</i></b> Die postulierte einfaktorielle Struktur der englischen Version konnte für die IHS-d nicht reproduziert werden. Die beiden identifizierten Subskalen zeigten jedoch gute psychometrische Eigenschaften. <b><i>Schlussfolgerung:</i></b> Der Einsatz der IHS-d erweitert die Möglichkeiten der Messung des wichtigen Konstrukts Hoffnungslosigkeit und kann daher die Suizidrisikoabschätzung sinnvoll ergänzen.