cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.13145/bacdive104581.20251217.10
title: Nocardioides sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.15156/bio/sh0096640.10fu
title: SH0096640.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.13145/bacdive104582.20230509.8.1
title: Nocardioides sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive104582.20251217.10
title: Nocardioides sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive104583.20230509.8.1
title: Nocardioides sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.15156/bio/sh0096641.10fu
title: SH0096641.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.5517/ccdc.csd.cc2l31vm
title: CCDC 2386220: Experimental Crystal Structure Determination

description: Related Article: Felix Kracht, Christoph Stuhl, Cäcilia Maichle-Mössmer, Reiner Anwander|2024|Dalton Trans.|53|19280|doi:10.1039/D4DT02722A
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.cc2l31wn
title: CCDC 2386221: Experimental Crystal Structure Determination

description: Related Article: Felix Kracht, Christoph Stuhl, Cäcilia Maichle-Mössmer, Reiner Anwander|2024|Dalton Trans.|53|19280|doi:10.1039/D4DT02722A
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.cc2l31xp
title: CCDC 2386222: Experimental Crystal Structure Determination

description: Related Article: Felix Kracht, Christoph Stuhl, Cäcilia Maichle-Mössmer, Reiner Anwander|2024|Dalton Trans.|53|19280|doi:10.1039/D4DT02722A
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: 10.6084/m9.figshare.27124374
title: Mapping research landscape of emerging technology in the accounting field: a bibliometric analysis

description: This study aims to trace the evolution of research on emerging technologies in the accounting field, map the clustering of this research and identify gaps that require further investigation. Data were collected from Scopus and filtered based on specific criteria, resulting in a final dataset of 324 articles analyzed bibliometrically over the past twenty-eight years. The research method was conducted in two stages: bibliometric analysis and analysis discussion of relevant articles. This study successfully maps emerging technologies in the accounting field into four main clusters, focusing on five key technologies: automation and robotic process automation, artificial intelligence, big data, blockchain and cloud computing. The basic theory or reasoning used by the author to divide the accounting field into four clusters is based on the technology acceptance model. Cluster 1 is technology acceptance and use in the accounting field. Cluster 2 is leveraging technology in the transformation of accounting education. Cluster 3 is implementing technology and innovation in the accounting Profession. Cluster 4 is research and methodology in technology-related accounting studies. This research provides valuable insights for future research agendas. Additionally, the results highlight gaps in the study of emerging technologies within the accounting field, identifying areas that require further exploration.
DOI: 10.6084/m9.figshare.27124374.v1
title: Mapping research landscape of emerging technology in the accounting field: a bibliometric analysis

description: This study aims to trace the evolution of research on emerging technologies in the accounting field, map the clustering of this research and identify gaps that require further investigation. Data were collected from Scopus and filtered based on specific criteria, resulting in a final dataset of 324 articles analyzed bibliometrically over the past twenty-eight years. The research method was conducted in two stages: bibliometric analysis and analysis discussion of relevant articles. This study successfully maps emerging technologies in the accounting field into four main clusters, focusing on five key technologies: automation and robotic process automation, artificial intelligence, big data, blockchain and cloud computing. The basic theory or reasoning used by the author to divide the accounting field into four clusters is based on the technology acceptance model. Cluster 1 is technology acceptance and use in the accounting field. Cluster 2 is leveraging technology in the transformation of accounting education. Cluster 3 is implementing technology and innovation in the accounting Profession. Cluster 4 is research and methodology in technology-related accounting studies. This research provides valuable insights for future research agendas. Additionally, the results highlight gaps in the study of emerging technologies within the accounting field, identifying areas that require further exploration.
DOI: 10.5517/ccdc.csd.cc2l31yq
title: CCDC 2386223: Experimental Crystal Structure Determination

description: Related Article: Felix Kracht, Christoph Stuhl, Cäcilia Maichle-Mössmer, Reiner Anwander|2024|Dalton Trans.|53|19280|doi:10.1039/D4DT02722A
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.cc2l31zr
title: CCDC 2386224: Experimental Crystal Structure Determination

description: Related Article: Felix Kracht, Christoph Stuhl, Cäcilia Maichle-Mössmer, Reiner Anwander|2024|Dalton Trans.|53|19280|doi:10.1039/D4DT02722A
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: 10.6084/m9.figshare.26326268
title: An empirical assessment of online shopping behavior among Saudi college students: applying SEM

description: In such a volatile environment, it is difficult to understand customer behavior, especially in online market scenarios, and understanding this area is critical for developing online retailers’ strategies. In the Kingdom of Saudi Arabia (KSA), the number of online users is growing very rapidly, before covid-19 online shopping is at a nascent stage, but now it is entering a growth stage with indefinite lockdowns and restrictions growing worldwide. In this scenario, the lack of knowledge regarding online shopping behavior makes it very difficult to measure it. Therefore, this research is designed to understand online shopping behavior and at the same time develop empirical measures for the assessment of online shopping behavior. This study utilizes the extended Technology Acceptance Model (TAM) to examine the factors that influence Saudi college students’ online shopping behavior for the assessment and testing of hypotheses. Structural equation Modeling (SEM) was used. The outcomes of this research are as follows: Perceived enjoyment, perceived ease of use, social norms, and perceived risk tend to have significant influences on online shopping behavior among college students in the Kingdom of Saudi Arabia (KSA). As stated above that before covid-19, online shopping is at a nascent stage in the Kingdom of Saudi Arabia and is now growing rapidly. To address this research gap, this study analyzes the factors influencing customers’ decisions to shop online through a sample of students from Saudi universities. This research makes a unique contribution to understanding, developing, and empirically testing these measures. This study also contributes to the empirical application of the technology acceptance model (TAM) to Saudi consumers.
DOI: 10.6084/m9.figshare.26326268.v1
title: An empirical assessment of online shopping behavior among Saudi college students: applying SEM

description: In such a volatile environment, it is difficult to understand customer behavior, especially in online market scenarios, and understanding this area is critical for developing online retailers’ strategies. In the Kingdom of Saudi Arabia (KSA), the number of online users is growing very rapidly, before covid-19 online shopping is at a nascent stage, but now it is entering a growth stage with indefinite lockdowns and restrictions growing worldwide. In this scenario, the lack of knowledge regarding online shopping behavior makes it very difficult to measure it. Therefore, this research is designed to understand online shopping behavior and at the same time develop empirical measures for the assessment of online shopping behavior. This study utilizes the extended Technology Acceptance Model (TAM) to examine the factors that influence Saudi college students’ online shopping behavior for the assessment and testing of hypotheses. Structural equation Modeling (SEM) was used. The outcomes of this research are as follows: Perceived enjoyment, perceived ease of use, social norms, and perceived risk tend to have significant influences on online shopping behavior among college students in the Kingdom of Saudi Arabia (KSA). As stated above that before covid-19, online shopping is at a nascent stage in the Kingdom of Saudi Arabia and is now growing rapidly. To address this research gap, this study analyzes the factors influencing customers’ decisions to shop online through a sample of students from Saudi universities. This research makes a unique contribution to understanding, developing, and empirically testing these measures. This study also contributes to the empirical application of the technology acceptance model (TAM) to Saudi consumers.
DOI: 10.5517/ccdc.csd.cc2l320t
title: CCDC 2386225: Experimental Crystal Structure Determination

description: Related Article: Felix Kracht, Christoph Stuhl, Cäcilia Maichle-Mössmer, Reiner Anwander|2024|Dalton Trans.|53|19280|doi:10.1039/D4DT02722A
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.cc2l322w
title: CCDC 2386227: Experimental Crystal Structure Determination

description: Related Article: Felix Kracht, Christoph Stuhl, Cäcilia Maichle-Mössmer, Reiner Anwander|2024|Dalton Trans.|53|19280|doi:10.1039/D4DT02722A
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: 10.6084/m9.figshare.26311258
title: Environmental performance reclaimed: unleashing the power of green transformational leadership and dynamic capability

description: This study examines the mediating role of green innovation in the relationship between green transformational leadership and environmental performance and simultaneously posits green dynamic capability as a pivotal boundary condition. A survey questionnaire was administered to 306 firms. The collected data were analyzed using Amos, and structural equation modelling was employed to test the hypotheses. The findings reveal a significant positive relationship between green transformational leadership and environmental performance. This study also demonstrates that green transformational leadership has an indirect impact on environmental performance through green innovation, and this relationship is anchored by a high level of green dynamic capability. This study demonstrates that green dynamic capability serves as a holistic catalyst that amplifies the impact of green transformational leadership on green innovation and simultaneously catalyzes the translation of green innovation into better environmental performance, ultimately offering fresh insight into environmental management puzzles.
DOI: 10.6084/m9.figshare.26311258.v1
title: Environmental performance reclaimed: unleashing the power of green transformational leadership and dynamic capability

description: This study examines the mediating role of green innovation in the relationship between green transformational leadership and environmental performance and simultaneously posits green dynamic capability as a pivotal boundary condition. A survey questionnaire was administered to 306 firms. The collected data were analyzed using Amos, and structural equation modelling was employed to test the hypotheses. The findings reveal a significant positive relationship between green transformational leadership and environmental performance. This study also demonstrates that green transformational leadership has an indirect impact on environmental performance through green innovation, and this relationship is anchored by a high level of green dynamic capability. This study demonstrates that green dynamic capability serves as a holistic catalyst that amplifies the impact of green transformational leadership on green innovation and simultaneously catalyzes the translation of green innovation into better environmental performance, ultimately offering fresh insight into environmental management puzzles.
DOI: 10.5517/ccdc.csd.cc2l321v
title: CCDC 2386226: Experimental Crystal Structure Determination

description: Related Article: Felix Kracht, Christoph Stuhl, Cäcilia Maichle-Mössmer, Reiner Anwander|2024|Dalton Trans.|53|19280|doi:10.1039/D4DT02722A
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.cc2l324y
title: CCDC 2386229: Experimental Crystal Structure Determination

description: Related Article: Felix Kracht, Christoph Stuhl, Cäcilia Maichle-Mössmer, Reiner Anwander|2024|Dalton Trans.|53|19280|doi:10.1039/D4DT02722A
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: 10.6084/m9.figshare.24782754
title: Self management and entrepreneurial mindset to support the MSMEs owner’s financial well-being

description: The purpose of this research is to determine the moderating function of self-management and entrepreneurial mindset in enhancing the effect of money attitude on FWB among owners of MSMEs (MSMEs) in Riau, Indonesia. This study used a quantitative method, utilizing primary data sources with 150 owners of MSMEs as respondents. The results of the study show that money attitude has a positive effect on financial well-being. While other results show that Self-Management and Entrepreneurial Mindset can strengthen the influence of money attitude on the financial well-being of MSME owners. The implication of this study are first, self-management encourages and strengthens MSME owners, in a positive money attitude to increase MSME owners’ FWB. Second, MSME owners with an entrepreneurial mindset are willing to accept risks and uncertainty to profit by spotting substantial opportunities, integrating existing resources, and being able to incorporate their new ideas into their enterprises so that they can continue to sustain and build their businesses, hence improving the owners’ FWB.
DOI: 10.6084/m9.figshare.24782754.v1
title: Self management and entrepreneurial mindset to support the MSMEs owner’s financial well-being

description: The purpose of this research is to determine the moderating function of self-management and entrepreneurial mindset in enhancing the effect of money attitude on FWB among owners of MSMEs (MSMEs) in Riau, Indonesia. This study used a quantitative method, utilizing primary data sources with 150 owners of MSMEs as respondents. The results of the study show that money attitude has a positive effect on financial well-being. While other results show that Self-Management and Entrepreneurial Mindset can strengthen the influence of money attitude on the financial well-being of MSME owners. The implication of this study are first, self-management encourages and strengthens MSME owners, in a positive money attitude to increase MSME owners’ FWB. Second, MSME owners with an entrepreneurial mindset are willing to accept risks and uncertainty to profit by spotting substantial opportunities, integrating existing resources, and being able to incorporate their new ideas into their enterprises so that they can continue to sustain and build their businesses, hence improving the owners’ FWB.
DOI: 10.5517/ccdc.csd.cc2l7mdw
title: CCDC 2390608: Experimental Crystal Structure Determination

description: Related Article: Alexey N. Bilyachenko, Victor N. Khrustalev, Zhibin Huang, Lidia S. Shul'pina, Pavel V. Dorovatovskii, Elena S. Shubina, Nikolay S. Ikonnikov, Nikolai N. Lobanov, Karim Ragimov, Di Sun|2024|Dalton Trans.|53|19102|doi:10.1039/D4DT02690J
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.cc2jrylv
title: CCDC 2346718: Experimental Crystal Structure Determination

description: Related Article: Aoi Nakagawa, Wataru Ota, Takumi Ehara, Yusuke Matsuo, Kiyoshi Miyata, Ken Onda, Tohru Sato, Shu Seki, Takayuki Tanaka|2024|Chem.Commun.|60|14770|doi:10.1039/D4CC05539J
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.cc2jrymw
title: CCDC 2346719: Experimental Crystal Structure Determination

description: Related Article: Aoi Nakagawa, Wataru Ota, Takumi Ehara, Yusuke Matsuo, Kiyoshi Miyata, Ken Onda, Tohru Sato, Shu Seki, Takayuki Tanaka|2024|Chem.Commun.|60|14770|doi:10.1039/D4CC05539J
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.