cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.7910/dvn/fegpuj
title: ACTG ART Interruption Studies: Viral Rebound after Treatment Interruption
title: SAS transport files and associated documentation
title: ACTG ART Interruption Studies: Viral Rebound after Treatment Interruption Final Analysis Datasets

description: These datasets contain data for the N = 235 participants from 6 ACTG studies with Analytic Treatment Interruption (ATI), who were on suppressive antiretroviral treatment (ART), received no immunologic interventions, and had HIV-1 RNA level &lt; 50 copies/mL at time of ATI. As described in the primary paper (Li 2016), the 6 source studies are: ACTG 371, ACTG 5024, ACTG 5068, ACTG 5170, ACTG 5187, ACTG 5197. Note that HIV-1 RNA levels during ATI were measured less frequently in ACTG 5170 (every 4 weeks) than in the other studies. If ACTG 5170 is excluded, the remaining N = 139 participants were in studies where HIV-1 RNA levels were to be measured every 1-2 weeks initially during ATI.&lt;br&gt;&lt;br&gt;
N = 124 participants (of the 235) had HIV-persistence data measured prior to ART interruption. These data were examined in Li 2016 and also in multiple statistical methods and modeling papers (Conway 2019, Wang 2020, Lok 2021, Chernofsky 2024, Chernofsky 2025), including causal mediation analysis for the effects of pre-ATI HIV-persistence measures on ATI outcomes.&lt;br&gt;&lt;br&gt;
Note that currently conducted ATI studies typically do not include participants taking Non-Nucleoside Reverse Transcriptase Inhibitors (NNRTIs) (see Li et al. 2022), so for use of these data as historical controls for ATI outcomes, recommend exclude those taking NNRTIs at the time of ATI.
description: USING THE SAS FILES: The SAS transport file (.trn) contains the datasets for this study. To use the unpacking program provided (unpack.sas), place the program and the SAS transport (.trn) file in the same directory, then run unpack.sas using SAS. The files will unpack into that directory. Please note that the unpacking program must be used because of the way SAS handles transferring datasets from one computer system to another. 

NOTES ABOUT THE DE-IDENTIFIED FILES: The data are de-identified so that no original identifiers are included in the data files. In order to de-identify data for public use, all dates (if included) have been converted to the number of days from a reference date. The SAS labels specify the start day for the calculation of the number of days in the variable. All site and institution information has been removed. Also, any other variable that has been deemed inappropriate to include in these public use datasets has been removed. This might limit how the files can be used. The de-identification process has been done in response to current regulatory requirements. 

RAW DATA FILES: The file Study_Data_CSV_ATI_LI_2016.zip contains comma separated value (.csv) files for this study. 

ADDITIONAL INFORMATION: Additional information concerning the data can be found in the file documentation files and metadata.csv.
DOI: 10.6073/pasta/c975b778462c176741ca186bf9c63ad8
title: AET01 Konza prairie grass reference evapotranspiration

description: Estimated evapotranspiration from a hypothetical short grass with a height of 0.12 m, a surface resistance of 70 s m-1, and an albedo of 0.23 (no water stress). Dataset contains daily total estimated evapotranspiration.
DOI: 10.5683/sp3/o9muzj
title: Replication Data for: D Lim, W Pei, JW Lee, KE Musselman, K Masani. Feasibility of a Depth Camera-Based Center of Mass Feedback System for Closed-Loop Functional Electrical Stimulation Therapy and Visual Feedback Balance Training

description: Center of mass and functional electrical stimulation amplitude time series during visual feedback balance training for 10 able-bodied participants.
description: Added ORCID
DOI: 10.17026/ar/qwq4xv
title: Archeologisch Bureauonderzoek (BO) Enschede, Iepstraat Gemeente Enschede (OV)

description: &lt;p&gt;Aantreffen van archeologische resten binnen het plangebied vastgesteld.&lt;/p&gt;
&lt;p&gt;Deze verwachting is gebaseerd op de KLIC-analyse waaruit blijkt dat een
aanzienlijk deel van het plangebied diep vergraven is bij de aanleg van
riolering, water- en gasleidingen. Geadviseerd wordt dan ook om binnen
het plangebied geen vervolgonderzoek uit te voeren.&lt;/p&gt;

&lt;p&gt;Selectiebesluit bevoegde overheid (1-12-2025, regioarcheoloog E. Kaptijn)
Bovenstaande conclusies worden door de regioarcheoloog onderschreven.&lt;/p&gt;&lt;p&gt;
Geadviseerd wordt om het plangebied wat betreft archeologie vrij te geven.&lt;/p&gt;
DOI: 10.5517/ccdc.csd.cc29zzbm
title: CCDC 2144931: Experimental Crystal Structure Determination

description: Related Article: Hitomi Ohmagari, Nicolas Marets, Jun Kamata, Mayo Yoneyama, Takumi Miyauchi, Yuta Takahashi, Yukina Yamamoto, Yuto Ogihara, Daisuke Saito, Kenta Goto, Ayumi Ishii, Masako Kato and Miki Hasegawa|2022|CSD Communication|||
description: Related Article: Hitomi Ohmagari, Nicolas Marets, Jun Kamata, Mayo Yoneyama, Takumi Miyauchi, Yuta Takahashi, Yukina Yamamoto, Yuto Ogihara, Daisuke Saito, Kenta Goto, Ayumi Ishii, Masako Kato and Miki Hasegawa|2022|Frontiers in Chemistry|10|1047960|doi:10.3389/fchem.2022.1047960
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.cc29zzcn
title: CCDC 2144932: Experimental Crystal Structure Determination

description: Related Article: Hitomi Ohmagari, Nicolas Marets, Jun Kamata, Mayo Yoneyama, Takumi Miyauchi, Yuta Takahashi, Yukina Yamamoto, Yuto Ogihara, Daisuke Saito, Kenta Goto, Ayumi Ishii, Masako Kato and Miki Hasegawa|2022|CSD Communication|||
description: Related Article: Hitomi Ohmagari, Nicolas Marets, Jun Kamata, Mayo Yoneyama, Takumi Miyauchi, Yuta Takahashi, Yukina Yamamoto, Yuto Ogihara, Daisuke Saito, Kenta Goto, Ayumi Ishii, Masako Kato and Miki Hasegawa|2022|Frontiers in Chemistry|10|1047960|doi:10.3389/fchem.2022.1047960
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.cc29zzfq
title: CCDC 2144934: Experimental Crystal Structure Determination

description: Related Article: Hitomi Ohmagari, Nicolas Marets, Jun Kamata, Mayo Yoneyama, Takumi Miyauchi, Yuta Takahashi, Yukina Yamamoto, Yuto Ogihara, Daisuke Saito, Kenta Goto, Ayumi Ishii, Masako Kato and Miki Hasegawa|2022|CSD Communication|||
description: Related Article: Hitomi Ohmagari, Nicolas Marets, Jun Kamata, Mayo Yoneyama, Takumi Miyauchi, Yuta Takahashi, Yukina Yamamoto, Yuto Ogihara, Daisuke Saito, Kenta Goto, Ayumi Ishii, Masako Kato and Miki Hasegawa|2022|Frontiers in Chemistry|10|1047960|doi:10.3389/fchem.2022.1047960
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.cc29zzgr
title: CCDC 2144935: Experimental Crystal Structure Determination

description: Related Article: Hitomi Ohmagari, Nicolas Marets, Jun Kamata, Mayo Yoneyama, Takumi Miyauchi, Yuta Takahashi, Yukina Yamamoto, Yuto Ogihara, Daisuke Saito, Kenta Goto, Ayumi Ishii, Masako Kato and Miki Hasegawa|2022|CSD Communication|||
description: Related Article: Hitomi Ohmagari, Nicolas Marets, Jun Kamata, Mayo Yoneyama, Takumi Miyauchi, Yuta Takahashi, Yukina Yamamoto, Yuto Ogihara, Daisuke Saito, Kenta Goto, Ayumi Ishii, Masako Kato and Miki Hasegawa|2022|Frontiers in Chemistry|10|1047960|doi:10.3389/fchem.2022.1047960
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.cc29zzhs
title: CCDC 2144936: Experimental Crystal Structure Determination

description: Related Article: Hitomi Ohmagari, Nicolas Marets, Jun Kamata, Mayo Yoneyama, Takumi Miyauchi, Yuta Takahashi, Yukina Yamamoto, Yuto Ogihara, Daisuke Saito, Kenta Goto, Ayumi Ishii, Masako Kato and Miki Hasegawa|2022|CSD Communication|||
description: Related Article: Hitomi Ohmagari, Nicolas Marets, Jun Kamata, Mayo Yoneyama, Takumi Miyauchi, Yuta Takahashi, Yukina Yamamoto, Yuto Ogihara, Daisuke Saito, Kenta Goto, Ayumi Ishii, Masako Kato and Miki Hasegawa|2022|Frontiers in Chemistry|10|1047960|doi:10.3389/fchem.2022.1047960
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.cc29zzjt
title: CCDC 2144937: Experimental Crystal Structure Determination

description: Related Article: Hitomi Ohmagari, Nicolas Marets, Jun Kamata, Mayo Yoneyama, Takumi Miyauchi, Yuta Takahashi, Yukina Yamamoto, Yuto Ogihara, Daisuke Saito, Kenta Goto, Ayumi Ishii, Masako Kato and Miki Hasegawa|2022|CSD Communication|||
description: Related Article: Hitomi Ohmagari, Nicolas Marets, Jun Kamata, Mayo Yoneyama, Takumi Miyauchi, Yuta Takahashi, Yukina Yamamoto, Yuto Ogihara, Daisuke Saito, Kenta Goto, Ayumi Ishii, Masako Kato and Miki Hasegawa|2022|Frontiers in Chemistry|10|1047960|doi:10.3389/fchem.2022.1047960
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.cc2jtpqs
title: CCDC 2348396: Experimental Crystal Structure Determination

description: Related Article: Duy Tuan Doan,  Thi Linh Giang Hoang,  Thi Thom Nguyen,  Thierry Maris,  Phuong Nguyen-Tri |2026|J.Mol.Struct.|1352|144349|doi:10.1016/j.molstruc.2025.144349
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5281/zenodo.18340134
title: Hyperautomation Architectures for Financial Workflow Transformation: Integrating Generative Artificial Intelligence, Process Mining, and Socio-Technical Systems Theory

description: The accelerating convergence of hyperautomation, generative artificial intelligence, and process mining is reshaping contemporary financial workflows, redefining how organizations conceptualize efficiency, control, and strategic intelligencein digitally mediated environments. Financial operations, traditionally characterized by high volumes of rule-based transactions, regulatory intensity, and legacy system dependence, now represent a critical frontier for advanced automation paradigms that extend beyond conventional robotic process automation toward self-learning, adaptive, and context-aware systems (Panetta, 2021). This research develops an extensive theoretical and analytical examination of hyperautomation frameworks in financial workflows, grounded explicitly in the generative artificial intelligence and process mining framework articulated by Krishnan and Bhat (2025), while situating their contribution within broader debates spanning Industry 4.0, digital twins, neural analytics, and socio-technical transformation.The study adopts a qualitative, theory-building research design that synthesizes multidisciplinary literature across information systems, artificial intelligence, operations management, and organizational theory, enabling an interpretive analysis of how hyperautomation reconfigures financial process intelligence, governance mechanisms, and human-machine collaboration (Haleem et al., 2021). Rather than offering empirical measurement or computational modeling, the article emphasizes deep conceptual elaboration, tracing the historical evolution of automation from deterministic systems toward generative, probabilistic architectures capable of autonomous decision support (Park, 2018). The abstracted findings reveal that hyperautomationin financial workflows operates not merely as a technological enhancement but as an institutional re-alignment mechanism that alters accountability structures, knowledge flows, and strategic foresight capabilities (Krishnan & Bhat, 2025).Results from theinterpretive analysis indicate that the integration of generative AI with process mining enables continuous process discovery, anomaly interpretation, and scenario simulation, thereby expanding financial organizations’ capacity for anticipatory governanceand adaptive compliance (Jacoby & Usländer, 2020). However, the discussion also highlights persistent challenges, including algorithmic opacity, cognitive displacement of human expertise, and uneven diffusion across organizational clusters and labor markets (Goher et al., 2021). By critically engaging with these tensions, the article contributes an original, publication-ready synthesis that advances hyperautomation theory in financial contexts and delineates future research trajectories at the intersectionof intelligent systems, organizational resilience, and digital ethics.
DOI: 10.5517/ccdc.csd.cc2jtprt
title: CCDC 2348397: Experimental Crystal Structure Determination

description: Related Article: Duy Tuan Doan,  Thi Linh Giang Hoang,  Thi Thom Nguyen,  Thierry Maris,  Phuong Nguyen-Tri |2026|J.Mol.Struct.|1352|144349|doi:10.1016/j.molstruc.2025.144349
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5281/zenodo.18340133
title: Hyperautomation Architectures for Financial Workflow Transformation: Integrating Generative Artificial Intelligence, Process Mining, and Socio-Technical Systems Theory

description: The accelerating convergence of hyperautomation, generative artificial intelligence, and process mining is reshaping contemporary financial workflows, redefining how organizations conceptualize efficiency, control, and strategic intelligencein digitally mediated environments. Financial operations, traditionally characterized by high volumes of rule-based transactions, regulatory intensity, and legacy system dependence, now represent a critical frontier for advanced automation paradigms that extend beyond conventional robotic process automation toward self-learning, adaptive, and context-aware systems (Panetta, 2021). This research develops an extensive theoretical and analytical examination of hyperautomation frameworks in financial workflows, grounded explicitly in the generative artificial intelligence and process mining framework articulated by Krishnan and Bhat (2025), while situating their contribution within broader debates spanning Industry 4.0, digital twins, neural analytics, and socio-technical transformation.The study adopts a qualitative, theory-building research design that synthesizes multidisciplinary literature across information systems, artificial intelligence, operations management, and organizational theory, enabling an interpretive analysis of how hyperautomation reconfigures financial process intelligence, governance mechanisms, and human-machine collaboration (Haleem et al., 2021). Rather than offering empirical measurement or computational modeling, the article emphasizes deep conceptual elaboration, tracing the historical evolution of automation from deterministic systems toward generative, probabilistic architectures capable of autonomous decision support (Park, 2018). The abstracted findings reveal that hyperautomationin financial workflows operates not merely as a technological enhancement but as an institutional re-alignment mechanism that alters accountability structures, knowledge flows, and strategic foresight capabilities (Krishnan & Bhat, 2025).Results from theinterpretive analysis indicate that the integration of generative AI with process mining enables continuous process discovery, anomaly interpretation, and scenario simulation, thereby expanding financial organizations’ capacity for anticipatory governanceand adaptive compliance (Jacoby & Usländer, 2020). However, the discussion also highlights persistent challenges, including algorithmic opacity, cognitive displacement of human expertise, and uneven diffusion across organizational clusters and labor markets (Goher et al., 2021). By critically engaging with these tensions, the article contributes an original, publication-ready synthesis that advances hyperautomation theory in financial contexts and delineates future research trajectories at the intersectionof intelligent systems, organizational resilience, and digital ethics.
DOI: 10.5517/ccdc.csd.cc2jtpsv
title: CCDC 2348398: Experimental Crystal Structure Determination

description: Related Article: Duy Tuan Doan,  Thi Linh Giang Hoang,  Thi Thom Nguyen,  Thierry Maris,  Phuong Nguyen-Tri |2026|J.Mol.Struct.|1352|144349|doi:10.1016/j.molstruc.2025.144349
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.cc2jtptw
title: CCDC 2348399: Experimental Crystal Structure Determination

description: Related Article: Duy Tuan Doan,  Thi Linh Giang Hoang,  Thi Thom Nguyen,  Thierry Maris,  Phuong Nguyen-Tri |2026|J.Mol.Struct.|1352|144349|doi:10.1016/j.molstruc.2025.144349
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5281/zenodo.18339742
title: LINF_310035200

description: Protein of unknown function - conserved; Leishmania infantum (strain JPCM5)
DOI: 10.5517/ccdc.csd.cc2jtpvx
title: CCDC 2348400: Experimental Crystal Structure Determination

description: Related Article: Duy Tuan Doan,  Thi Linh Giang Hoang,  Thi Thom Nguyen,  Thierry Maris,  Phuong Nguyen-Tri |2026|J.Mol.Struct.|1352|144349|doi:10.1016/j.molstruc.2025.144349
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.cc2km6br
title: CCDC 2371944: Experimental Crystal Structure Determination

description: Related Article: Duy Tuan Doan,  Thi Linh Giang Hoang,  Thi Thom Nguyen,  Thierry Maris,  Phuong Nguyen-Tri |2026|J.Mol.Struct.|1352|144349|doi:10.1016/j.molstruc.2025.144349
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5281/zenodo.18339741
title: LINF_310035200

description: Protein of unknown function - conserved; Leishmania infantum (strain JPCM5)
DOI: 10.5517/ccdc.csd.cc2llz6d
title: CCDC 2401514: Experimental Crystal Structure Determination

description: Related Article: N. Archana, M. Vijayasri, K. Dayanidhi, S. Parthiban
|2026|J.Mol.Struct.|1351|144270|doi:10.1016/j.molstruc.2025.144270
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.cc2lvqpw
title: CCDC 2408969: Experimental Crystal Structure Determination

description: Related Article: Ning Li, Wen-Jing Li, Xin-Yi Chen, Hai-Xia Wang, Ming-Sheng Xie, Hai-Ming Guo|2025|Adv.Synth.Catal.|367|e202500089|doi:10.1002/adsc.202500089
description: Related Article: Ning Li, Jun-Hao Zhang, Wei-Jing Yang, Ming-Sheng Xie, Hai-Ming Guo|2025|Org.Chem.Front.|12|3271|doi:10.1039/D5QO00237K
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.cc2pcj5s
title: CCDC 2483725: Experimental Crystal Structure Determination

description: Related Article: Tsholofelo S. Nthehang, Ibrahim Waziri, Tunde L. Yusuf, Samson O. Oselusi, Alfred J. Muller|2026|J.Mol.Struct.|1352||doi:10.1016/j.molstruc.2025.144508
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.cc2pcj6t
title: CCDC 2483726: Experimental Crystal Structure Determination

description: Related Article: Tsholofelo S. Nthehang, Ibrahim Waziri, Tunde L. Yusuf, Samson O. Oselusi, Alfred J. Muller|2026|J.Mol.Struct.|1352||doi:10.1016/j.molstruc.2025.144508
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.