cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.4121/19934783.v2
title: Acceptance of a Virtual Coach for Quitting Smoking and Becoming Physically Active: Dataset

description: <strong>Study</strong>The data was gathered during a longitudinal study on the online crowdsourcing platform Prolific between 20 May 2021 and 30 June 2021. The Human Research Ethics Committee of Delft University of Technology granted ethical approval for the research (Letter of Approval number: 1523). In this study, smokers who were contemplating or preparing to quit smoking interacted with the text-based virtual coach Sam in up to five conversational sessions. In each session, participants were assigned a new preparatory activity for quitting smoking, such as thinking of and writing down reasons for quitting smoking. After the five sessions, participants filled in a post-questionnaire in which they were asked about their acceptance of Sam. Participants answered six acceptance questions, and provided a rating and a free-text response for each of them.The study was pre-registered in the Open Science Framework (OSF): https://osf.io/k2uac. This pre-registration describes the study design, measures, etc. Note that this dataset contains only part of the collected data, namely, the data related to studying the acceptance of the virtual coach.The implementation of the virtual coach Sam can be found here: https://doi.org/10.5281/zenodo.6319356. There you can also find a list of the 24 preparatory activities used in the study (Activities.xlsx).<br><strong>Data</strong>This dataset contains four types of data:<strong>Data from participants' Prolific profiles</strong>. This includes data on demographics (e.g., age range, household size) as well as smoking and physical activity behavior (e.g., weekly exercise amount).<strong>Data from a pre-screening questionnaire</strong>. This includes, for example, the responses to informed consent questions.<strong>Data from a pre-questionnaire</strong>. This includes data on smoking and physical activity behavior, as well as personality and need for cognition.<strong>Data from a post-questionnaire</strong>. This includes data on the acceptance of the virtual coach as well as doing the preparatory activities.There is a separate data file for each type of data.<br><strong>Analysis</strong>Parts of the dataset have been used to study the acceptance of the virtual coach. Examples include: Examining people's relationship and willingness to continue working with a virtual smoking cessation coach (see this peer-reviewed paper: https://doi.org/10.1007/978-3-031-30933-5_17), andInvestigating the acceptance of a virtual coach as a guided intervention for quitting smoking (see the bachelor's thesis by Jaap Dechering: http://resolver.tudelft.nl/uuid:71038d25-9a5a-4068-b22f-fa37b0be23aa).
DOI: 10.6084/m9.figshare.21952973
title: Hirai_et_al_Rapid_dissolution_of_organic_aerosols_in_liquid_methane_on_Titan_database

description: These are the research data used in the study on Hirai et al. <br> data.xlsx contains processed data used in each figures in the main text and supplementary informations in the secondary revised manuscript. raw_data.zip contains each primary data in the secondary revised manuscript. <br>
DOI: 10.6084/m9.figshare.21952973.v1
title: Hirai_et_al_Rapid_dissolution_of_organic_aerosols_in_liquid_methane_on_Titan_database

description: These are the research data used in the study on Hirai et al. <br> data.xlsx contains processed data used in each figures in the main text and supplementary informations in the secondary revised manuscript. raw_data.zip contains each primary data in the secondary revised manuscript. <br>
DOI: 10.34740/kaggle/dsv/5572554
title: AutoXGB
DOI: 10.17632/gtzwwbh9kx.1
title: Data for 'On the pursuit of energy security: evidence from the nexus between clean energy stock price and energy security elements'

description: The data-set contains data on Nasdaq clean energy stock price index, Nasdaq clean energy efficiency index, BRENT oil price, WTI oil price, carbon futures, Henry Hub natural gas price, composite natural gas price index and volume of Nasdaq clean energy stock.
The data is for a paper entitled "On the pursuit of energy security: evidence from the nexus between clean energy stock price and energy security elements" currently under consideration for publication.
DOI: 10.17632/wgcb89ck6g.1
title: Headway data SWAL

description: Headway data of the special width approach lanes
DOI: 10.17632/g8vjh2x7hj.1
title: Cryptocurrency Acquisition Preferences of Romanian Cryptocurrency Users With and Without the Influence of Energy Labels

description: The "Energy Labelling and Sustainable Cryptocurrency Choices" online survey is a non-probability sampling survey of Romanian smartphone users, 18 and over, that have expressed an interest in holding cryptocurrencies in future. On 10 November 2022, participants were subjected to a control treatment test with two different user interfaces.

This data set contains raw response data (cryptocurrency-energy-labelling-data.sav) and the questionnaire design (cryptocurrency-energy-labelling-design.pdf) which also serves as a key for columns of the response data file.

Participant Recruitment: Pollfish

Universe: Persons 18 and over that are present in Romania at the time of participation and have self-declared to be considering holding cryptocurrencies in future.

Units of Analysis: Individual

Method of Data Collection: Online Survey
DOI: 10.17632/4gn7tk33ph.1
title: Dataset to the publication: Close coupling of plant functional types with soil microbial community composition drives soil carbon and nutrient cycling in tundra heath

description: Aims 
This study aimed at elucidating divergent effects of two dominant plant functional types (PFTs) in tundra heath, dwarf shrubs and mosses, on microbial decomposition processes and soil carbon (C) and nutrient cycling, and thereby to enhance our understanding of the complex interactions between PFTs, soil microbes and soil functioning.
Methods
Samples of organic soil were collected under three dwarf shrub species (of distinct mycorrhizal association and life form) and three moss species in early and late growing season and analysed for soil C and nutrient pools, extracellular enzyme activities and phospholipid fatty acid profiles, together with a range of plant traits, soil and abiotic site characteristics. 
Results
Shrub soils were characterised by high microbial biomass C and phosphorus and phosphatase activity, which was linked with a fungal-dominated microbial community, while moss soils were characterised by high soil nitrogen availability, peptidase and peroxidase activity associated with a bacterial-dominated microbial community. The variation in soil microbial community structure was explained by mycorrhizal association, root morphology, litter and soil organic matter quality and soil pH-value. Furthermore, we found that the seasonal variation in microbial biomass and enzyme activities over the growing season, likely driven by plant belowground C allocation, was most pronounced under the tallest shrub Betula nana. 
Conclusion
Our study demonstrates a close coupling of PFTs with soil microbial communities, microbial decomposition processes and soil nutrient availability in tundra heath, which suggests potential strong impacts of global change-induced shifts in plant community composition on carbon and nutrient cycling in high-latitude ecosystems.
DOI: 10.6084/m9.figshare.22258975
title: Diversity and Teamwork in Student Software Teams

description: Diversity is becoming an increasingly relevant topic in computer science, especially software development. Since software develop- ment is concerned with human and social processes, there is an agreement that a higher diversity rate in professional software teams positively influences communication, innovation, and per- formance. However, there is a lack of understanding of the impact of diversity in software development teams at an educational level to identify potential challenges and opportunities that might affect later professional stages. In this paper, we investigate the impact of diversity on key teamwork skills such as communication, collab- oration, and productivity in student software development teams. Therefore, we conducted several surveys on project work progress in an introductory software engineering course with students and their tutors regarding these teamwork metrics. We link these self- assessments and the project outcome to seven aspects of diversity. Our results show correlations between teamwork satisfaction and team diversity. Considering the changes in teamwork over the project timeline, we identified deteriorations in certain teamwork metrics—independent of the team diversity. These findings serve to enhance understanding and improvement of students’ team- work for students and educators. In particular, it is essential in software development courses at an undergraduate level to support our future software engineers to keep them motivated and decrease possible frustrations regarding teamwork.
DOI: 10.21227/5wyy-ef39
title: arxiv_algorithms_math_cs_03-12-2022

description: There is a growing trend towards combining mathematics and computer science education. Although there are surely synergies between the two disciplines, has sufficient thought been given to the benefit of fostering independently the unique skillsets they offer in order to best harness these synergies? By comparing and contrasting quantitative evidencerelating to skillsets demonstrated through choice of words in describing research contributions to a field common to both mathematics and computer science, algorithms, this research aims to provide a better understanding of what are the unique differences in skillsets offered by the two disciplines. Through the use of natural language processing and  machine learning techniques, applied in quantitative experimentation, it was found that phrases used by mathematicians to describe their research contributions to the field of algorithms showed a clear emphasis on (developing algorithms as a) method to finding a solution by (developing) functions and/ or convergent numerical methods (and validating them through) numerical examples. While phrases used by computer scientists showed an emphasis on (using algorithms as an) approach to solve a problem with data (to train a) model (typically via) optimisation methods or numerical experiments, (and typically being a) machine learning (algorithm) such as a deep neural network or other neural network, reinforcement learning or deep learning, and on (the algorithm’s) performance and time to solve. This research fills a gap in the literature by providing quantitative experiment-based evidence of some of the unique differences in skillsets of mathematicians and computer scientists (on a high level, the skillsets required to develop effective algorithms to solveproblems versus the skillsets to use (and experiment with) algorithms using a computer on data to solve problems in an optimal way). It is expected that this research would be of interest to educators and hiring managers who require to cultivate and leverage these skillsets to the benefit of society.
DOI: 10.6084/m9.figshare.22666360
title: Supplementary materials for "Dialect differences and linguistic divergence: A cross-linguistic survey of grammatical variation" by John Mansfield, Henry Leslie-O’Neill and Haoyi Li, published in LDC, 2023

description: These are the supplementary materials for an article published in Language Dynamics and Change, entitled "Dialect differences and linguistic divergence: A crosslinguistic survey of grammatical variation", by John Mansfield, Henry Leslie-O'Neill and Haoyi Li with DOI: 10.1163/22105832-bja10026. This article presents a new type of comparative linguistic survey, analyzing (socio)linguistic variation in a database of 1,155 grammatical constructions drawn from 42 diverse languages. We focus in particular on variation in the expression of grammatical meanings, and the extent to which grammatical variation differentiates geographic dialects. This is the first study we know of to present a systematic, crosslinguistic survey of dialect differentiation. We identify three main structural types of grammatical variation— <em>form</em>, <em>order</em>, and <em>omission</em>—and find that in situations of close contact between dialects, where signaling of distinct group identities is more relevant, form variables are more likely to differentiate dialects than the other two types. Order and omission variables usually only differentiate dialects that have minimal contact. Our survey suggests that social signaling may have a substantial role in the divergence of grammars, and provides systematic support for previous proposals regarding convergence and divergence under contact. In the supplementary materials, we include further information on the selection of reference grammars and their bibliographic details. We also describe the process for identifying grammatical variables and how they were categorised into structural types, and provide more information about the coding of social distance, and our tests for inter-coder reliability. Finally, we present an alternative regression model without random slopes for language family by structural type, which provides very similar results to the model presented in the main paper.
DOI: 10.6084/m9.figshare.22666360.v1
title: Supplementary materials for "Dialect differences and linguistic divergence: A cross-linguistic survey of grammatical variation" by John Mansfield, Henry Leslie-O’Neill and Haoyi Li, published in LDC, 2023

description: These are the supplementary materials for an article published in Language Dynamics and Change, entitled "Dialect differences and linguistic divergence: A crosslinguistic survey of grammatical variation", by John Mansfield, Henry Leslie-O'Neill and Haoyi Li with DOI: 10.1163/22105832-bja10026. This article presents a new type of comparative linguistic survey, analyzing (socio)linguistic variation in a database of 1,155 grammatical constructions drawn from 42 diverse languages. We focus in particular on variation in the expression of grammatical meanings, and the extent to which grammatical variation differentiates geographic dialects. This is the first study we know of to present a systematic, crosslinguistic survey of dialect differentiation. We identify three main structural types of grammatical variation— <em>form</em>, <em>order</em>, and <em>omission</em>—and find that in situations of close contact between dialects, where signaling of distinct group identities is more relevant, form variables are more likely to differentiate dialects than the other two types. Order and omission variables usually only differentiate dialects that have minimal contact. Our survey suggests that social signaling may have a substantial role in the divergence of grammars, and provides systematic support for previous proposals regarding convergence and divergence under contact. In the supplementary materials, we include further information on the selection of reference grammars and their bibliographic details. We also describe the process for identifying grammatical variables and how they were categorised into structural types, and provide more information about the coding of social distance, and our tests for inter-coder reliability. Finally, we present an alternative regression model without random slopes for language family by structural type, which provides very similar results to the model presented in the main paper.
DOI: 10.5519/qd.voauz48h
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1 records)
DOI: 10.5281/zenodo.7882908
title: Cardea

description: Dataset for Cardea Research Manager Survey 2022
DOI: 10.5281/zenodo.7882907
title: Cardea

description: Dataset for Cardea Research Manager Survey 2022
DOI: 10.5281/zenodo.7882891
title: Predicting the Future of AI with AI

description: This dataset augments the paper "Predicting the Future of AI with AI: High-quality link prediction in an exponentially growing knowledge network" by Mario Krenn, Lorenzo Buffoni, Bruno Coutinho, Sagi Eppel, Jacob Gates Foster, Andrew Gritsevskiy, Harlin Lee, Yichao Lu, Joao P. Moutinho, Nima Sanjabi, Rishi Sonthalia, Ngoc Mai Tran, Francisco Valente, Yangxinyu Xie, Rose Yu, Michael Kopp. GitHub: https://github.com/artificial-scientist-lab/FutureOfAIviaAI
DOI: 10.5281/zenodo.7516667
title: Data for: Quantum Monte Carlo study of the role of p-wave interactions in ultracold Fermi gases

description: Dataset to reproduce the figures of the article G. Bertaina, M.G. Tarallo, S. Pilati, "Quantum Monte Carlo study of the role of p-wave interactions in ultracold Fermi gases" https://arxiv.org/abs/2212.09150
DOI: 10.5281/zenodo.7852523
title: Data for: Quantum Monte Carlo study of the role of p-wave interactions in ultracold Fermi gases

description: Dataset to reproduce the figures of the article G. Bertaina, M.G. Tarallo, S. Pilati, "Quantum Monte Carlo study of the role of p-wave interactions in ultracold Fermi gases" https://arxiv.org/abs/2212.09150
DOI: 10.5281/zenodo.7882958
title: Project TARA Survey data

description: The survey questionnaire and survey response data (anonymized) for Project TARA study on responsible metrics and U.S. academia.
DOI: 10.5281/zenodo.7882959
title: Project TARA Survey Questionnaire

description: The survey questionnaire for Project TARA study on responsible metrics and U.S. academia.
DOI: 10.5281/zenodo.7882974
title: Project TARA Survey data

description: The survey questionnaire and survey response data (anonymized) for Project TARA study on responsible metrics and U.S. academia.
DOI: 10.25625/8hq1dn
title: Workshop Dataset version 2

description: workshop test
DOI: 10.25625/8hq1dn/nvfklz
title: AI_story4.jpeg

description: :unav
DOI: 10.7488/ds/3847
title: Historical textile dye analysis using DESI-MS

description: Desorption electrospray ionization mass spectrometry (DESI-MS) is an ambient mass spectrometry technique that shows great potential for the analysis of fragile heritage objects in situ. This article focuses on the application of a recently built DESI source to characterize natural dyestuffs in historical textiles and a presentation of initial imaging experiments. Optimization of the instrumental settings, geometrical parameters, and solvent system of the DESI-MS analysis were conducted on rhodamine B samples. Some variables, including an increased flow rate, a narrower range of optimized geometrical variables and a solvent system without additives, were applicable to both early synthetic and natural dyes. Direct dye turmeric (Curcuma longa L.) could be reliably analyzed on both silk and wool, as could anthraquinone standards without mordanting. These preliminary results suggest that the dye application process (direct, mordant, vat) has a large impact on the ionization efficiency of DESI-MS. Imaging trials highlighted the future suitability of DESI-MS for the analysis of patterned textiles that are difficult to sample, such as calico fabrics, or other currently inaccessible objects. The dataset is related to the paper Sandström, E., Vettorazzo, C., Logan Mackay, C., Troalen, L.G. and Hulme, A.N. (2023). "Historical Textile Dye Analysis Using DESI-MS", Heritage 6(5), 4042-4053; https://doi.org/10.3390/heritage6050212 .
DOI: 10.5281/zenodo.7883072
title: Emotions Iliad Dataset

description: a CSV file with four columns: "chap", "text", "label", "annotator_code", and "label_code". The first row of the file contains the headers for each column. Each subsequent row contains data for a particular text. The "chap" column represents the chapter number of the text. The "text" column contains a quote from the text. The "label" column is a classification label assigned to the quote by an annotator. The "annotator_code" column is an identifier for the annotator who assigned the label. The "label_code" column is a numeric code assigned to the label. it is related to the labeling or classification of quotes from a text based on the emotional tone conveyed by the text.
DOI: 10.5281/zenodo.7883071
title: Emotions Iliad Dataset

description: a CSV file with four columns: "chap", "text", "label", "annotator_code", and "label_code". The first row of the file contains the headers for each column. Each subsequent row contains data for a particular text. The "chap" column represents the chapter number of the text. The "text" column contains a quote from the text. The "label" column is a classification label assigned to the quote by an annotator. The "annotator_code" column is an identifier for the annotator who assigned the label. The "label_code" column is a numeric code assigned to the label. it is related to the labeling or classification of quotes from a text based on the emotional tone conveyed by the text.
DOI: 10.5281/zenodo.7883031
title: Processed MEG data used for revealing dynamic brain reconfiguration using MAPPER

description: This is MEG data used for topological data analysis for revealing dynamic brain reconfiguration.
DOI: 10.5281/zenodo.7883030
title: Processed MEG data used for revealing dynamic brain reconfiguration using MAPPER

description: This is MEG data used for topological data analysis for revealing dynamic brain reconfiguration.
DOI: 10.6084/m9.figshare.22725686
title: Score_EKG integration into ACLS

description: Dataset used in the <strong>Reliability for Simulation-based Assessment for Integration of Basic EKG Interpretation into ACLS Station: Generalizability Theory Analysis</strong>
DOI: 10.6084/m9.figshare.22725686.v1
title: Score_EKG integration into ACLS

description: Dataset used in the <strong>Reliability for Simulation-based Assessment for Integration of Basic EKG Interpretation into ACLS Station: Generalizability Theory Analysis</strong>
DOI: 10.5517/ccdc.csd.cc2fkbs4
title: CCDC 2250996: Experimental Crystal Structure Determination

description: Related Article: Arnold L. Rheingold|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: 10.5517/ccdc.csd.cc2fkbzb
title: CCDC 2251002: Experimental Crystal Structure Determination

description: Related Article: Arnold L. Rheingold|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: 10.5517/ccdc.csd.cc2fkxmk
title: CCDC 2251549: Experimental Crystal Structure Determination

description: Related Article: Arnold L. Rheingold|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: 10.5517/ccdc.csd.cc2fkxtr
title: CCDC 2251555: Experimental Crystal Structure Determination

description: Related Article: Arnold L. Rheingold|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.