cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.22008/fk2/iw73uu/kqzejd
title: AWS_one-boom_readme.pdf

description: Uploaded with pyDataverse 2023-05-01 00:22
DOI: 10.6084/m9.figshare.19149510.v1
title: Two-point correlation function coefficients and characteristic statistics, and comparison of results between lithium and RbI from Finite-element and semi-analytical study of elastic wave propagation in strongly scattering polycrystals

description: (For Editorial Office) This ESM contains multiple tables and figures, with detailed captions included.
DOI: 10.22008/fk2/iw73uu/iwdac1
title: AWS_changelog_one-boom.txt

description: Uploaded with pyDataverse 2023-05-01 00:22
DOI: 10.22008/fk2/iw73uu/vdlgfj
title: CEN1_day.csv

description: Uploaded with pyDataverse 2023-05-16 10:35
DOI: 10.15156/bio/sh1397015.10fu
title: SH1397015.10FU

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: 10.15156/bio/sh1397017.10fu
title: SH1397017.10FU

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: 10.15156/bio/sh1397018.10fu
title: SH1397018.10FU

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: 10.15156/bio/sh1397019.10fu
title: SH1397019.10FU

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: 10.15156/bio/sh1397022.10fu
title: SH1397022.10FU

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: 10.15156/bio/sh1397023.10fu
title: SH1397023.10FU

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: 10.15156/bio/sh1397025.10fu
title: SH1397025.10FU

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: 10.15156/bio/sh1397026.10fu
title: SH1397026.10FU

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: 10.15156/bio/sh1397028.10fu
title: SH1397028.10FU

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: 10.18130/v3/f5kuci
title: Supplemental Materials
title: Osmolarity controls oscillatory calcium signaling to reduce autonomous aldosterone production in zona glomerulosa cells

description: Supplemental data and methods for Endocrinology article "Osmolarity controls oscillatory calcium signaling to reduce autonomous aldosterone production in zona glomerulosa cells"
DOI: 10.5281/zenodo.18670695
title: OPTIMIZING QUALITY AND EFFICIENCY OF AI-GENERATED SCIENTIFIC AND TECHNICAL TRANSLATIONS THROUGH POST-EDITING

description: This article examines methods for optimizing the quality and efficiency of AI-generated scientific and technical translations with a particular focus on post-editing. As artificial intelligence increasingly supports professional translation workflows, post-editing has become a critical stage for ensuring accuracy, terminological consistency, and contextual adequacy in specialized texts.

The study analyzes approaches to automating post-editing processes through the integration of intelligent tools designed to reduce manual effort and streamline editorial tasks. It further explores optimization technologies based on machine learning and neural network models, demonstrating their role in decreasing translation errors and minimizing post-editing time. These advancements are shown to significantly improve productivity when processing complex scientific and technical materials.

In addition, the article discusses current trends in AI-assisted translation, including scalability and processing speed in large-scale projects. Post-editing is positioned as an essential quality assurance mechanism that enables AI systems to meet growing demands without compromising reliability. Ethical and contextual considerations are also addressed, emphasizing the importance of post-editing in preserving scientific meaning and terminological precision across languages.

Overall, the findings highlight post-editing as a key factor in enhancing the effectiveness of AI-driven scientific and technical translation and provide practical insights for researchers and translation professionals.
DOI: 10.5281/zenodo.18670696
title: OPTIMIZING QUALITY AND EFFICIENCY OF AI-GENERATED SCIENTIFIC AND TECHNICAL TRANSLATIONS THROUGH POST-EDITING

description: This article examines methods for optimizing the quality and efficiency of AI-generated scientific and technical translations with a particular focus on post-editing. As artificial intelligence increasingly supports professional translation workflows, post-editing has become a critical stage for ensuring accuracy, terminological consistency, and contextual adequacy in specialized texts.

The study analyzes approaches to automating post-editing processes through the integration of intelligent tools designed to reduce manual effort and streamline editorial tasks. It further explores optimization technologies based on machine learning and neural network models, demonstrating their role in decreasing translation errors and minimizing post-editing time. These advancements are shown to significantly improve productivity when processing complex scientific and technical materials.

In addition, the article discusses current trends in AI-assisted translation, including scalability and processing speed in large-scale projects. Post-editing is positioned as an essential quality assurance mechanism that enables AI systems to meet growing demands without compromising reliability. Ethical and contextual considerations are also addressed, emphasizing the importance of post-editing in preserving scientific meaning and terminological precision across languages.

Overall, the findings highlight post-editing as a key factor in enhancing the effectiveness of AI-driven scientific and technical translation and provide practical insights for researchers and translation professionals.
DOI: 10.5517/cc42msl
title: CCDC 121699: Experimental Crystal Structure Determination

description: Related Article: W.Grochala, A.Jagielska, K.Wozniak, A.Wieckowska, R.Bilewicz, B.Korybut-Daszkiewicz, J.Bukowska, L.Piela|2001|J.Phys.Org.Chem.|14|63|doi:10.1002/1099-1395(200102)14:2<63::AID-POC328>3.0.CO;2-W
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/cc6dvhx
title: CCDC 191099: Experimental Crystal Structure Determination

description: Related Article: F.C.Krebs, T.Jensen|2003|J.Fluorine Chem.|120|77|doi:10.1016/S0022-1139(02)00289-0
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/cc42mtm
title: CCDC 121700: Experimental Crystal Structure Determination

description: Related Article: W.Grochala, A.Jagielska, K.Wozniak, A.Wieckowska, R.Bilewicz, B.Korybut-Daszkiewicz, J.Bukowska, L.Piela|2001|J.Phys.Org.Chem.|14|63|doi:10.1002/1099-1395(200102)14:2<63::AID-POC328>3.0.CO;2-W
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: 10.25346/s6eecgix/h0cbsh
title: vc_redist.x64-1.exe
DOI: 10.5517/cc42mvn
title: CCDC 121701: Experimental Crystal Structure Determination

description: Related Article: W.Grochala, A.Jagielska, K.Wozniak, A.Wieckowska, R.Bilewicz, B.Korybut-Daszkiewicz, J.Bukowska, L.Piela|2001|J.Phys.Org.Chem.|14|63|doi:10.1002/1099-1395(200102)14:2<63::AID-POC328>3.0.CO;2-W
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/cc709bv
title: CCDC 208826: Experimental Crystal Structure Determination

description: Related Article: A.B.Smith III, Haifeng Cui|2003|Org.Lett.|5|587|doi:10.1021/ol027575g
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/cc709dx
title: CCDC 208828: Experimental Crystal Structure Determination

description: Related Article: Y.Topcu, O.Andac, V.T.Yilmaz, W.T.A.Harrison|2002|Cryst.Res.Technol.|37|509|doi:10.1002/1521-4079(200205)37:5<509::AID-CRAT509>3.0.CO;2-Q
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/cc70ccy
title: CCDC 208889: Experimental Crystal Structure Determination

description: Related Article: T.Hattori, Y.Shimazumi, H.Goto, O.Yamabe, N.Morohashi, W.Kawai, S.Miyano|2003|J.Org.Chem.|68|2099|doi:10.1021/jo026747k
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: 10.25346/s6eecgix/bxdn0f
title: qt_ja-1.qm
DOI: 10.5517/cc5y4fn
title: CCDC 176961: Experimental Crystal Structure Determination

description: Related Article: Jin-Hua Yang, Shao-Liang Zheng, Jun Tao, Gao-Feng Liu, Xiao-Ming Chen|2002|Aust.J.Chem.|55|741|doi:10.1071/CH02126
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: 10.25346/s6eecgix/xtxtxk
title: qjpeg-1.dll
DOI: 10.5517/cc5y4gp
title: CCDC 176962: Experimental Crystal Structure Determination

description: Related Article: Jin-Hua Yang, Shao-Liang Zheng, Jun Tao, Gao-Feng Liu, Xiao-Ming Chen|2002|Aust.J.Chem.|55|741|doi:10.1071/CH02126
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/cc70krj
title: CCDC 209087: Experimental Crystal Structure Determination

description: Related Article: S.Thyagarajan, C.D.Incarvito, A.L.Rheingold, K.H.Theopold|2003|Inorg.Chim.Acta|345|333|doi:10.1016/S0020-1693(02)01275-6
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/cc70ksk
title: CCDC 209088: Experimental Crystal Structure Determination

description: Related Article: S.Thyagarajan, C.D.Incarvito, A.L.Rheingold, K.H.Theopold|2003|Inorg.Chim.Acta|345|333|doi:10.1016/S0020-1693(02)01275-6
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: 10.25346/s6eecgix/ahmgza
title: qt_he-1.qm
DOI: 10.5517/cc70kyq
title: CCDC 209093: Experimental Crystal Structure Determination

description: Related Article: Ke-Qing Ling, Y.Lee, D.Macikenas, J.D.Protasiewicz, L.M.Sayre|2003|J.Org.Chem.|68|1358|doi:10.1021/jo020582y
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/cc70lf7
title: CCDC 209108: Experimental Crystal Structure Determination

description: Related Article: Zhengbo Han, Enbo Wang, Wansheng You, Shuxia Liu, Changwen Hu, Yan Xing, Hengqing Jia, Yonghua Lin|2001|J.Mol.Struct.|595|7|doi:10.1016/S0022-2860(01)00476-8
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/cc5tyyv
title: CCDC 173908: Experimental Crystal Structure Determination

description: Related Article: Deyuan Kong, J.Reibenspies, Jianggao Mao, A.Clearfield, A.E.Martell|2003|Inorg.Chim.Acta|342|158|doi:10.1016/S0020-1693(02)01018-6
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.