cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.25182359.v1
title: An Experimental Study of Gong Meditation and Anxiety

description: This experimental study explored the possible correlation between gong meditation and trait anxiety. 26 Participants were randomly assigned to one of three groups: (Tx) treatment group listened to an 11-minute recorded gong meditation daily for 2 weeks, (WS) active control group listened to an 11-minute recording of water sounds in nature for 2 weeks, (C) true control group went about activities of daily living for 2 weeks. Trait anxiety was measured pre- and post-study using the State Trait Anxiety for Cognitive and Somatic Anxiety (STICSA, trait scale). EEG was measured pre- and post-study using an EEG headset. HRV was measured pre- and post-study using devices from the HeartMath Institute. Levels of Hypnotic Trance were measured post-study only using the Phenomenology of Consciousness Inventory (PCI).Trait anxiety in the Tx group showed a statistically significant reduction in STICSA trait values as compared to the WS group and both control groups combined. Hypnotic trance showed a statistically higher PCI HSS value as compared to WS group. Biological measures were inconsistent and not significant.The study was not sufficiently populated for the findings to be definitive. However, statistically significant reduction in trait anxiety in the Tx group compared to the WS group and all controls combined merits further study.
DOI: 10.6084/m9.figshare.25182359.v2
title: Data for an Experimental Study of Gong Meditation and Anxiety

description: This experimental study explored the possible correlation between gong meditation and trait anxiety. 26 Participants were randomly assigned to one of three groups: (Tx) treatment group listened to an 11-minute recorded gong meditation daily for 2 weeks, (WS) active control group listened to an 11-minute recording of water sounds in nature for 2 weeks, (C) true control group went about activities of daily living for 2 weeks. Trait anxiety was measured pre- and post-study using the State Trait Anxiety for Cognitive and Somatic Anxiety (STICSA, trait scale). EEG was measured pre- and post-study using an EEG headset. HRV was measured pre- and post-study using devices from the HeartMath Institute. Levels of Hypnotic Trance were measured post-study only using the Phenomenology of Consciousness Inventory (PCI).Trait anxiety in the Tx group showed a statistically significant reduction in STICSA trait values as compared to the WS group and both control groups combined. Hypnotic trance showed a statistically higher PCI HSS value as compared to WS group. Biological measures were inconsistent and not significant.The study was not sufficiently populated for the findings to be definitive. However, statistically significant reduction in trait anxiety in the Tx group compared to the WS group and all controls combined merits further study.
DOI: 10.18119/n96c8g
title: galFiltered
DOI: 10.25549/usctheses-ouc11277040
title: THESIS TEMPLATE
DOI: 10.25549/usctheses-c40-248250
title: etd-WongJaco-2-beati
DOI: 10.25549/usctheses-c40-248251
title: etd-WongJaco-3-charity
DOI: 10.34740/kaggle/dsv/7592074
title: WallStreetBets 2022
DOI: 10.25549/usctheses-ouc11277352
title: Dissertation_Geraldine Fitzgerald-Codd_Final_Copy_for upload to Digital Library_MAY 9, 2016
DOI: 10.25549/usctheses-ouc11292487
title: How Far Does Leadership Travel?
DOI: 10.5517/ccdc.csd.cc2gjgm3
title: CCDC 2279945: Experimental Crystal Structure Determination

description: Related Article: Rui Cao, Mengyu Zhang, Wen Tang, Jing Wu, Yang Luo, Yi Chen, Zhaodi Liu, Fuying Hao, Liangquan Sheng, Huajie Xu|2024|Spectrochim.Acta,Part A|310|123964|doi:10.1016/j.saa.2024.123964
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.cc2h0cxt
title: CCDC 2294276: Experimental Crystal Structure Determination

description: Related Article: Haohuan Yuan, Wei Yao, Xiaomin Zhang, Zhao Wei, Jiayue Xi, Yuanyuan Hao, Xian Liu, Ru Jiang, Huifang Nie|2024|J.Org.Chem.|89|1748|doi:10.1021/acs.joc.3c02446
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.10623317
title: Caffeoylquinic Acid Profiling: Comparative Analysis in Yerba Mate, Indian Camphorweed, and Stevia Extracts with Emphasis on the Influence of Brewing Conditions and Cold Storage in Yerba Mate Infusion
DOI: 10.5281/zenodo.10623318
title: Caffeoylquinic Acid Profiling: Comparative Analysis in Yerba Mate, Indian Camphorweed, and Stevia Extracts with Emphasis on the Influence of Brewing Conditions and Cold Storage in Yerba Mate Infusion
DOI: 10.5517/ccdc.csd.cc2h7597
title: CCDC 2300798: Experimental Crystal Structure Determination

description: Related Article: Yue Deng, Ying Tang, Jiamao Zhang, Xinxin Hang, Shentang Wang, Shanshan Hu, Jun Yang|2024|Polyhedron|251|116856|doi:10.1016/j.poly.2024.116856
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.cc2h9zng
title: CCDC 2303506: Experimental Crystal Structure Determination

description: Related Article: Georgios Malis, Anastasia S. Bakali, Antonios G. Hatzidimitriou, George Psomas|2024|J.Mol.Struct.|1303|137590|doi:10.1016/j.molstruc.2024.137590
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.cc2hfk0j
title: CCDC 2306927: Experimental Crystal Structure Determination

description: Related Article: Shivaiah Vaddypally, Alex N. Byrne, C. Franklin Goldsmith, Michael J. Zdilla, Vitaly G. Kiselev|2024|Inorg.Chem.|63|2322|doi:10.1021/acs.inorgchem.3c04338
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.cc2hfk1k
title: CCDC 2306928: Experimental Crystal Structure Determination

description: Related Article: Shivaiah Vaddypally, Alex N. Byrne, C. Franklin Goldsmith, Michael J. Zdilla, Vitaly G. Kiselev|2024|Inorg.Chem.|63|2322|doi:10.1021/acs.inorgchem.3c04338
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.cc2hgwf9
title: CCDC 2308211: Experimental Crystal Structure Determination

description: Related Article: Lihua Chen, Chenfei Li, Zheng-Fei Liu, Yoshiaki Kuboi, Enguang Fu, Lydia Sosa Vargas, Chihaya Adachi, Fabrice Mathevet, Shaodong Zhang|2024|Chem.Commun.|60|1758|doi:10.1039/D3CC05136F
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.cc2hhkj3
title: CCDC 2308865: Experimental Crystal Structure Determination

description: Related Article: Ryohei Akiyoshi, Akinori Saeki, Kazuyoshi Ogasawara, Daisuke Tanaka|2024|J.Mater.Chem.C|12|1958|doi:10.1039/D3TC04362B
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.cc2hhkk4
title: CCDC 2308866: Experimental Crystal Structure Determination

description: Related Article: Ryohei Akiyoshi, Akinori Saeki, Kazuyoshi Ogasawara, Daisuke Tanaka|2024|J.Mater.Chem.C|12|1958|doi:10.1039/D3TC04362B
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.cc2hhkl5
title: CCDC 2308867: Experimental Crystal Structure Determination

description: Related Article: Ryohei Akiyoshi, Akinori Saeki, Kazuyoshi Ogasawara, Daisuke Tanaka|2024|J.Mater.Chem.C|12|1958|doi:10.1039/D3TC04362B
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: 10.5519/qd.ip2rqwnq
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (5772043 records)
DOI: 10.25549/usctheses-c40-248253
title: etd-WongJaco-5-dao
DOI: 10.5281/zenodo.10620929
title: A Machine Learning Framework for Detecting and Adjusting for Learning Effects in the Evaluation of Medical Device Safety

description: Medical device failures have resulted in significant patient injury and represent an important preventable health risk in the United States. For example, over the past 10 years the replacement of seven types of faulty cardiovascular devices has cost the healthcare system ~$1.5 billion and impacted thousands of lives. Currently, assurance of post-approval device safety relies extensively on spontaneous reporting of adverse events by providers and device manufacturers; however, it is estimated that <0.5% of device failures are actually reported. In response, the United States Food and Drug Administration has signaled an interest in prospective active surveillance methodologies, which address several of the limitations of passive adverse event reporting and support direct estimation of event rates. Interpreting comparative safety and effectiveness of medical devices using real-world data is challenging and has important methodological gaps. Various patient and provider-level factors might affect adverse events rates of a device implantation procedure. For example, improvements in physician technical performance as a result of device familiarity, a “learning curve”, may influence adverse event rates following device implantation. Routine collection of clinical data during device placement and over the course of patient follow-up may support disentangling learning effects from intrinsic risk of medical devices.  Using observational data poses challenges because of complex patient characteristics resulting in non-linear relationships between risk factors and outcomes. In this work, we sought to develop a machine learning framework to separate learning effects from device signals that can be used in downstream surveillance activities.
DOI: 10.5281/zenodo.10597269
title: Morphological dataset of mammaliamorphs and phylogenetic analysis codes

description: The data matrix of 128 taxa and 583 characters for mammaliamorphs, the PAUP commands for parsimony-based analyses, the MrBayes commands for Bayesian analyses, the results of phylogenetic analyses, such as the apomorphic list from PAUP and ancestral state reconstruction from MrBayes.
DOI: 10.5281/zenodo.10637713
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Karl Franz Josef Malý, http://www.wikidata.org/entity/Q5958250. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q5958250
DOI: 10.5281/zenodo.10623247
title: Lidar observation of Ca+ in ionospheric E-F region at Mohe

description: The attached data is used for the paper.
DOI: 10.5281/zenodo.10623248
title: Lidar observation of Ca+ in ionospheric E-F region at Mohe

description: The attached data is used for the paper.
DOI: 10.5281/zenodo.10637335
title: How do Machine Learning Projects use Continuous Integration Practices? An Empirical Study on GitHub Actions

description: Reproduction Package for the Paper "How do Machine Learning Projects use Continuous Integration Practices? An Empirical Study on GitHub Actions"

This reproduction package contains the necessary materials to replicate the findings presented in the paper published at the Mining Software Repositories (MSR) conference in 2024.

Folder Structure:- datasets: Contains all datasets used in the analysis of the Research Questions (RQs) of the paper.

- plots: Contains plots generated to present the results of the investigated RQs of the study.

- r-script: Contains all R scripts used in the analysis of the RQs, as well as scripts used to compute metrics such as build duration, time to fix broken builds, and test coverage.

- RQ3-neovis-network-graph: Contains a README.txt file providing instructions to create the network graph used to present the results of RQ3 using the neovisjs library.

Please refer to the specific folders for detailed information on how to reproduce the analysis and results presented in the paper.

Furthermore, the code we used to retrieve data for the studied projects is available in the following GitHub repository: https://github.com/joaohelis/ml-ci-project-miner
DOI: 10.5281/zenodo.10637336
title: How do Machine Learning Projects use Continuous Integration Practices? An Empirical Study on GitHub Actions

description: Reproduction Package for the Paper "How do Machine Learning Projects use Continuous Integration Practices? An Empirical Study on GitHub Actions"

This reproduction package contains the necessary materials to replicate the findings presented in the paper published at the Mining Software Repositories (MSR) conference in 2024.

Folder Structure:- datasets: Contains all datasets used in the analysis of the Research Questions (RQs) of the paper.

- plots: Contains plots generated to present the results of the investigated RQs of the study.

- r-script: Contains all R scripts used in the analysis of the RQs, as well as scripts used to compute metrics such as build duration, time to fix broken builds, and test coverage.

- RQ3-neovis-network-graph: Contains a README.txt file providing instructions to create the network graph used to present the results of RQ3 using the neovisjs library.

Please refer to the specific folders for detailed information on how to reproduce the analysis and results presented in the paper.

Furthermore, the code we used to retrieve data for the studied projects is available in the following GitHub repository: https://github.com/joaohelis/ml-ci-project-miner
DOI: 10.5281/zenodo.10637762
title: Asymmetric influence of urban morphology changes on land surface temperature  between daytime and nighttime

description: This dataset provides data on urban morphology dynamics and land surface temperature in three major urban agglomerations in China.
DOI: 10.5281/zenodo.10637763
title: Asymmetric influence of urban morphology changes on land surface temperature  between daytime and nighttime

description: This dataset provides data on urban morphology dynamics and land surface temperature in three major urban agglomerations in China.
DOI: 10.25917/2zab-v083
title: Cancer Services Pharmacist Questionnaire Data
DOI: 10.5517/ccdc.csd.cc2hk5x5
title: CCDC 2310427: Experimental Crystal Structure Determination

description: Related Article: Takeru Inoue, Yuuka Matsuura, Koki Horii, Akihito Konishi, Jun-ichi Nishida, Makoto Yasuda, Takeshi Kawase|2024|Chem.Commun.|60|1735|doi:10.1039/D3CC05968E
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.10637631
title: Network traffic trace

description: https://github.com/EldhosePaul-2023/meshlab

 

Goal of the project is to measure and compare the performance of several forwarding techniques on different devices.

Compare the following four forwarding techniques/implementions regarding their performance:



eBPF (TC)

IP forwarding

IP forwarding with software offloading

IP forwarding with hardware offloading
DOI: 10.5281/zenodo.10637632
title: Network traffic trace

description: https://github.com/EldhosePaul-2023/meshlab

 

Goal of the project is to measure and compare the performance of several forwarding techniques on different devices.

Compare the following four forwarding techniques/implementions regarding their performance:



eBPF (TC or XDP)

IP forwarding

IP forwarding with software offloading

IP forwarding with hardware offloading
DOI: 10.5281/zenodo.10637773
title: Network traffic trace

description: https://github.com/EldhosePaul-2023/meshlab

 

Goal of the project is to measure and compare the performance of several forwarding techniques on different devices.

Compare the following four forwarding techniques/implementions regarding their performance:



eBPF (TC)

IP forwarding

IP forwarding with software offloading

IP forwarding with hardware offloading
DOI: 10.5517/ccdc.csd.cc2gq97r
title: CCDC 2285544: Experimental Crystal Structure Determination

description: Related Article: Yuichi Hirai, Anna Wrona-Piotrowicz, Janusz Zakrzewski, Magdalena Ciechańska, Takahito Ohmura, Takashi Takeda, Takayuki Nakanishi, Rémi Métivier, Clémence Allain|2024|J.Mater.Chem.C|12|1952|doi:10.1039/D3TC03968D
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.cc2gq95p
title: CCDC 2285542: Experimental Crystal Structure Determination

description: Related Article: Yuichi Hirai, Anna Wrona-Piotrowicz, Janusz Zakrzewski, Magdalena Ciechańska, Takahito Ohmura, Takashi Takeda, Takayuki Nakanishi, Rémi Métivier, Clémence Allain|2024|J.Mater.Chem.C|12|1952|doi:10.1039/D3TC03968D
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.cc2gq96q
title: CCDC 2285543: Experimental Crystal Structure Determination

description: Related Article: Yuichi Hirai, Anna Wrona-Piotrowicz, Janusz Zakrzewski, Magdalena Ciechańska, Takahito Ohmura, Takashi Takeda, Takayuki Nakanishi, Rémi Métivier, Clémence Allain|2024|J.Mater.Chem.C|12|1952|doi:10.1039/D3TC03968D
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.cc2gq94n
title: CCDC 2285541: Experimental Crystal Structure Determination

description: Related Article: Yuichi Hirai, Anna Wrona-Piotrowicz, Janusz Zakrzewski, Magdalena Ciechańska, Takahito Ohmura, Takashi Takeda, Takayuki Nakanishi, Rémi Métivier, Clémence Allain|2024|J.Mater.Chem.C|12|1952|doi:10.1039/D3TC03968D
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.cc2gq92l
title: CCDC 2285539: Experimental Crystal Structure Determination

description: Related Article: Yuichi Hirai, Anna Wrona-Piotrowicz, Janusz Zakrzewski, Magdalena Ciechańska, Takahito Ohmura, Takashi Takeda, Takayuki Nakanishi, Rémi Métivier, Clémence Allain|2024|J.Mater.Chem.C|12|1952|doi:10.1039/D3TC03968D
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.cc2gq93m
title: CCDC 2285540: Experimental Crystal Structure Determination

description: Related Article: Yuichi Hirai, Anna Wrona-Piotrowicz, Janusz Zakrzewski, Magdalena Ciechańska, Takahito Ohmura, Takashi Takeda, Takayuki Nakanishi, Rémi Métivier, Clémence Allain|2024|J.Mater.Chem.C|12|1952|doi:10.1039/D3TC03968D
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.cc2gq90j
title: CCDC 2285537: Experimental Crystal Structure Determination

description: Related Article: Yuichi Hirai, Anna Wrona-Piotrowicz, Janusz Zakrzewski, Magdalena Ciechańska, Takahito Ohmura, Takashi Takeda, Takayuki Nakanishi, Rémi Métivier, Clémence Allain|2024|J.Mater.Chem.C|12|1952|doi:10.1039/D3TC03968D
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.