cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.10521913
title: Quantifying Security Issues in Reusable JavaScript Actions in GitHub Workflows

description: Quantifying Security Issues in Reusable JavaScript Actions in GitHub Workflows

Overview

This replication package contains all the material required to replicate the analyses we made for our paper entitled Quantifying Security Issues in Reusable JavaScript Actions in GitHub Workflows, which has been accepted for publication at the MSR 2024 (the 21st International Conference on Mining Software Repositories). The materials provided here will guide you through the process of replicating our research findings.

This research is supported by the Fonds de la Recherche Scientifique - FNRS under grant numbers T.0149.22, F.4515.23, and J.0147.24.

Requirements

Before you proceed with replicating our analysis, ensure that you have the following prerequisites installed on your system:



Python 3.8 or higher

Dependencies listed in the requirements.txt file


Getting Started

To begin replicating our analysis, follow these steps:





Clone this repository to your local machine:




Navigate to the cloned directory:




Set up a Jupyter Lab environment to execute the provided notebooks.




Install the required dependencies using the requirements.txt file:



pip install -r requirements.txt


Data Replication

The data-raw folder contains all the data required to replicate the analysis. These data were obtained by running various notebooks. Here is a list of the notebooks and their resulting CSV files:



Extract Actions - actions.csv

Extract Releases - releases.csv

Extract Actions Type - types.csv

Check Manifests and Extract Dependencies - lock_dependencies.csv

Check Vulnerabilities - vulnerabilities.csv

Extract JS Entry Points and CodeQL Results - codeql_results_raw.csv, codeql_queries.csv

Extract Dependents - dependents.csv


Research Questions and Analysis

The data folder contains all the data required to replicate the paper-story notebook and the research questions. The research and analysis presented in the paper are based on two final datasets created from the data-raw files as follows:



Vulnerabilities in Dependency Network of Actions - actions_dependencies_vulnerabilities.parquet

Security Weaknesses in JavaScript Code of Actions - actions_code_vulnerabilities.parque
DOI: 10.5281/zenodo.10521914
title: Quantifying Security Issues in Reusable JavaScript Actions in GitHub Workflows

description: Quantifying Security Issues in Reusable JavaScript Actions in GitHub Workflows

Overview

This replication package contains all the material required to replicate the analyses we made for our paper entitled Quantifying Security Issues in Reusable JavaScript Actions in GitHub Workflows, which has been accepted for publication at the MSR 2024 (the 21st International Conference on Mining Software Repositories). The materials provided here will guide you through the process of replicating our research findings.

This research is supported by the Fonds de la Recherche Scientifique - FNRS under grant numbers T.0149.22, F.4515.23, and J.0147.24.

Requirements

Before you proceed with replicating our analysis, ensure that you have the following prerequisites installed on your system:



Python 3.8 or higher

Dependencies listed in the requirements.txt file


Getting Started

To begin replicating our analysis, follow these steps:





Clone this repository to your local machine:




Navigate to the cloned directory:




Set up a Jupyter Lab environment to execute the provided notebooks.




Install the required dependencies using the requirements.txt file:



pip install -r requirements.txt


Data Replication

The data-raw folder contains all the data required to replicate the analysis. These data were obtained by running various notebooks. Here is a list of the notebooks and their resulting CSV files:



Extract Actions - actions.csv

Extract Releases - releases.csv

Extract Actions Type - types.csv

Check Manifests and Extract Dependencies - lock_dependencies.csv

Check Vulnerabilities - vulnerabilities.csv

Extract JS Entry Points and CodeQL Results - codeql_results_raw.csv, codeql_queries.csv

Extract Dependents - dependents.csv


Research Questions and Analysis

The data folder contains all the data required to replicate the paper-story notebook and the research questions. The research and analysis presented in the paper are based on two final datasets created from the data-raw files as follows:



Vulnerabilities in Dependency Network of Actions - actions_dependencies_vulnerabilities.parquet

Security Weaknesses in JavaScript Code of Actions - actions_code_vulnerabilities.parque
DOI: 10.5281/zenodo.10525721
title: Clinical Bacteria DataSet

description: We have updated the latest Dataset in Version V3.
DOI: 10.5281/zenodo.10474234
title: Clinical Bacteria Dataset

description: We have updated the latest Dataset in Version V3.
DOI: 10.5281/zenodo.10474233
title: Clinical Bacteria DataSet

description: This dataset comprises Gram-stained bacteria images obtained using M-ROSE from lower respiratory tract specimens of patients with lung infection from 2018 to 2022 at the Chinese PLA General Hospital. 1705 images (4,912 × 3,684 pixels) were desensitized and constituted RawImageDataSet. A total of 4,833 cocci and 6,991 bacilli were manually labeled and differentiated into negative and positive categories. 

Additionally, we have also employed a cascade detection and semantic segmentation network for bacteria identification that achieved over 85% accuracy. DeepDataSet was constructed to verify the dataset quality, which includes 640DataSet, DetectionDataSet, and SegmentationDataSet applied to train deep learning networks directly. The data and benchmark algorithms we provide may contribute to the study of automated bacterial identification in clinical specimens.



RawImageDataSet: 1705 original images obtained from clinical specimens using the micro-optical system. 

DeepDataSet: partial image selected randomly from RawImageDataSet, used to verify the quality of the dataset.



640DataSet: partially extracted from corresponding raw images in a random manner and cropped into 640×640 pixels, then labeled them manually with detection box and segmentation boxes

DetectionDataSet: converted from 640DataSet to detection DataSet applied for YOLOv5 networks

SegmentationDataSet: converted from 640DataSet to Segmentation DataSet applied for Unet networks




Accumulated annotation a total of 3371 Gram-negative cocci (G-cocci), 1462 Gram-positive cocci (G+cocci), 5799 Gram-negative bacilli (G-bacilli), and 1192 Gram-positive bacilli (G+bacilli ).
DOI: 10.5281/zenodo.10526360
title: Clinical Bacteria DataSet

description: This dataset comprises Gram-stained bacteria images obtained using M-ROSE from lower respiratory tract specimens of patients with lung infection from 2018 to 2022 at the Chinese PLA General Hospital. 1705 images (4,912 × 3,684 pixels) were desensitized and constituted RawImageDataSet. A total of 4,833 cocci and 6,991 bacilli were manually labeled and differentiated into negative and positive categories. 

Additionally, we have also employed a cascade detection and semantic segmentation network for bacteria identification that achieved over 85% accuracy. DeepDataSet was constructed to verify the dataset quality, which includes 640DataSet, DetectionDataSet, and SegmentationDataSet applied to train deep learning networks directly. The data and benchmark algorithms we provide may contribute to the study of automated bacterial identification in clinical specimens.



RawImageDataSet: 1705 original images obtained from clinical specimens using the micro-optical system. 

DeepDataSet: partial image selected randomly from RawImageDataSet, used to verify the quality of the dataset.



640DataSet: partially extracted from corresponding raw images in a random manner and cropped into 640×640 pixels, then labeled them manually with detection box and segmentation boxes

DetectionDataSet: converted from 640DataSet to detection DataSet applied for YOLOv5 networks

SegmentationDataSet: converted from 640DataSet to Segmentation DataSet applied for Unet networks




Accumulated annotation a total of 3371 Gram-negative cocci (G-cocci), 1462 Gram-positive cocci (G+cocci), 5799 Gram-negative bacilli (G-bacilli), and 1192 Gram-positive bacilli (G+bacilli ).
DOI: 10.5281/zenodo.10419535
title: Livestock increasingly drove global agricultural emissions in 1910-2015

description: supplementary material
DOI: 10.5281/zenodo.8362532
title: Livestock increasingly drove global agricultural emissions in 1910-2015

description: supplementary material
DOI: 10.5281/zenodo.8362533
title: Livestock increasingly drove global agricultural emissions in 1910-2015

description: supplementary material
DOI: 10.5281/zenodo.10467296
title: Broadband transient reflectivity data for Pr0.5Ca1.5MnO4

description: Broadband transient reflectivity data for determining the chirp in a pump probe measurement based on principal component analysis . Ipython notebooks are given to reproduce the data in the Optics Express publication.
DOI: 10.5281/zenodo.10467297
title: Broadband transient reflectivity data for Pr0.5Ca1.5MnO4

description: Broadband transient reflectivity data for determining the chirp in a pump probe measurement based on principal component analysis . Ipython notebooks are given to reproduce the data in the Optics Express publication.
DOI: 10.34740/kaggle/dsv/7426318
title: AutoXGB
DOI: 10.34740/kaggle/dsv/7426319
title: OnlineFree
DOI: 10.34740/kaggle/dsv/7426340
title: Egypt Gold Prices | Daily Updated
DOI: 10.5281/zenodo.8116003
title: DiscFine_Subvolumes_Healthy_Fatigue_Viet_Tomo

description: Contains, for 60 subvolumes (camemberts without any defects), nominal stress ranging from 100 to 140 MPa:


a) stresses,


b) volumes


Mesh type: Fine mesh


Note: Summed volume of 20 subvolumes correctly equals the volume of experimental fatigue specimens used by Viet Duc Le.
DOI: 10.5281/zenodo.8089346
title: DiscFine_Subvolumes_Healthy_Fatigue_Viet_Tomo

description: Contains, for 60 subvolumes (camemberts without any defects), nominal stress ranging from 100 to 140 MPa:


a) stresses,


b) volumes


Mesh type: Fine mesh


Note: Summed volume of 20 subvolumes correctly equals the volume of experimental fatigue specimens used by Viet Duc Le.
DOI: 10.34740/kaggle/dsv/7426309
title: LUFlow Network Intrusion Detection Data Set
DOI: 10.11588/data/nuixmg
title: Designing Sustainable Polymers: Lactate Esters for 3D Printing and Upcycling [data]

description: The search for sustainable polymer systems is key to tackling the current climate crisis. However, the use of bio-based polymers does not suffice to achieve this goal. Additionally, new chemical approaches enabling the re- or upcycling of polymer materials need to be explored. Herein, we exploit lactate esters with different substituents as readily available bio-based molecules for the synthesis of printable monomers. The synthesis of these lactate ester-based monomers follows green chemistry principles by establishing a solvent-free, one-pot approach, relying on a reusable catalyst, and achieving high conversions (84 – 100%) at mild conditions. Further, these monomers are utilized in 3D printable ink formulations for digital light processing (DLP) for the first time in combination with a recycled crosslinker. The resulting 3D printed structures display complex geometries with high resolution. A key attribute of the presented system is that the 3D printed polymer material can be upcycled via aminolysis affording a pre-cursor of the crosslinker, which is in turn incorporated into the further ink formulations, introducing a material circularity into the system. These results demonstrate a powerful approach by combining bio-based monomers and chemical upcycling with sustainable 3D printing techniques.
DOI: 10.6084/m9.figshare.24998822
title: Data base.savInjuries database

description: Muscle and Hamstring strain injuries in LaLiga
DOI: 10.5517/ccdc.csd.cc2fx6sc
title: CCDC 2261443: Experimental Crystal Structure Determination

description: Related Article: Shuo-En Tsai, Cheng-Yen Chung, Sin-Min Li, Wei-Zheng Zeng, Jia- Yu Chou, Wen-Ping Jiang, Guan-Jhong Huang, Der-Yen Lee, Fung Fuh Wong|2024|J.Mol.Struct.|1298|137023|doi:10.1016/j.molstruc.2023.137023
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.cc2fx90p
title: CCDC 2261512: Experimental Crystal Structure Determination

description: Related Article: Yingui Gao, Zhihuang Xu, Liwang Ye, Yuanjie Wang, Xinxin Zhuang|2024|Phys.Chem.Chem.Phys.(PCCP)|26|2472|doi:10.1039/D3CP05140D
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.cc2fy87x
title: CCDC 2262449: Experimental Crystal Structure Determination

description: Related Article: Stephanie García-Zavala, Ramón Guzmán-Mejía, J. Carlos Jiménez-Cruz, Rafael Herrera-Bucio, Hugo A. García-Gutiérrez, Pedro Navarro-Santos, Judit A. Aviña-Verduzco|2024|J.Mol.Struct.|1301|137358|doi:10.1016/j.molstruc.2023.137358
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.cc2fyc6z
title: CCDC 2262541: Experimental Crystal Structure Determination

description: Related Article: Shumin Chen, Kangting Zheng, Yanfang Zhu, Pengtao Ma|2024|J.Mol.Struct.|1297|136965|doi:10.1016/j.molstruc.2023.136965
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.cc2fyc70
title: CCDC 2262542: Experimental Crystal Structure Determination

description: Related Article: Shumin Chen, Kangting Zheng, Yanfang Zhu, Pengtao Ma|2024|J.Mol.Struct.|1297|136965|doi:10.1016/j.molstruc.2023.136965
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.cc2fynnq
title: CCDC 2262834: Experimental Crystal Structure Determination

description: Related Article: Nanhao Jin, Yuqi Liu, Xiaoming Liu, Yue Zhao, Han Chen, Xinying Wang, Yuebin Feng, Huilong Luo, Wei Li|2024|J.Mol.Struct.|1299|137147|doi:10.1016/j.molstruc.2023.137147
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.cc2fynpr
title: CCDC 2262835: Experimental Crystal Structure Determination

description: Related Article: Nanhao Jin, Yuqi Liu, Xiaoming Liu, Yue Zhao, Han Chen, Xinying Wang, Yuebin Feng, Huilong Luo, Wei Li|2024|J.Mol.Struct.|1299|137147|doi:10.1016/j.molstruc.2023.137147
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.cc2fz4g1
title: CCDC 2263293: Experimental Crystal Structure Determination

description: Related Article: Provash Joarddar, Pinku Saha, Sirajuddin Sarkar, Atish Dipankar Jana|2024|J.Mol.Struct.|1301|137310|doi:10.1016/j.molstruc.2023.137310
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.cc2fznps
title: CCDC 2263796: Experimental Crystal Structure Determination

description: Related Article: Jie Wang, Wei-Feng Zheng, Xue Zhang, Hui Qian, Shengming Ma |2023|Nat.Commun.|14|7399|doi:10.1038/s41467-023-42660-1
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.cc2fzphm
title: CCDC 2263821: Experimental Crystal Structure Determination

description: Related Article: Michaela Harmošová, Mária Vilková, Martin Kello, Dominika Šebová, Erika Samoľová, Miroslava Litecká, Ivan Potočňák|2024|Polyhedron|249|116794|doi:10.1016/j.poly.2023.116794
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.cc2fzpjn
title: CCDC 2263822: Experimental Crystal Structure Determination

description: Related Article: Michaela Harmošová, Mária Vilková, Martin Kello, Dominika Šebová, Erika Samoľová, Miroslava Litecká, Ivan Potočňák|2024|Polyhedron|249|116794|doi:10.1016/j.poly.2023.116794
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.cc2fzpkp
title: CCDC 2263823: Experimental Crystal Structure Determination

description: Related Article: Michaela Harmošová, Mária Vilková, Martin Kello, Dominika Šebová, Erika Samoľová, Miroslava Litecká, Ivan Potočňák|2024|Polyhedron|249|116794|doi:10.1016/j.poly.2023.116794
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.cc2fzplq
title: CCDC 2263824: Experimental Crystal Structure Determination

description: Related Article: Michaela Harmošová, Mária Vilková, Martin Kello, Dominika Šebová, Erika Samoľová, Miroslava Litecká, Ivan Potočňák|2024|Polyhedron|249|116794|doi:10.1016/j.poly.2023.116794
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.cc2fzpmr
title: CCDC 2263825: Experimental Crystal Structure Determination

description: Related Article: Michaela Harmošová, Mária Vilková, Martin Kello, Dominika Šebová, Erika Samoľová, Miroslava Litecká, Ivan Potočňák|2024|Polyhedron|249|116794|doi:10.1016/j.poly.2023.116794
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.cc2fzpns
title: CCDC 2263826: Experimental Crystal Structure Determination

description: Related Article: Michaela Harmošová, Mária Vilková, Martin Kello, Dominika Šebová, Erika Samoľová, Miroslava Litecká, Ivan Potočňák|2024|Polyhedron|249|116794|doi:10.1016/j.poly.2023.116794
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.cc2fzppt
title: CCDC 2263827: Experimental Crystal Structure Determination

description: Related Article: Michaela Harmošová, Mária Vilková, Martin Kello, Dominika Šebová, Erika Samoľová, Miroslava Litecká, Ivan Potočňák|2024|Polyhedron|249|116794|doi:10.1016/j.poly.2023.116794
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.cc2fzpqv
title: CCDC 2263828: Experimental Crystal Structure Determination

description: Related Article: Michaela Harmošová, Mária Vilková, Martin Kello, Dominika Šebová, Erika Samoľová, Miroslava Litecká, Ivan Potočňák|2024|Polyhedron|249|116794|doi:10.1016/j.poly.2023.116794
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.cc2g04f2
title: CCDC 2264253: Experimental Crystal Structure Determination

description: Related Article: Shumin Chen, Kangting Zheng, Yanfang Zhu, Pengtao Ma|2024|J.Mol.Struct.|1297|136965|doi:10.1016/j.molstruc.2023.136965
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.