cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.3886/e113756v1-130843
title: Replication data for: Dynamics of the Gender Gap for Young Professionals in the Financial and Corporate Sectors

description: The careers of MBAs from a top US business school are studied to understand how career dynamics differ by gender. Although male and female MBAs have nearly identical earnings at the outset of their careers, their earnings soon diverge, with the male earnings advantage reaching almost 60 log points a decade after MBA completion. Three proximate factors account for the large and rising gender gap in earnings: differences in training prior to MBA graduation, differences in career interruptions, and differences in weekly hours. The greater career discontinuity and shorter work hours for female MBAs are largely associated with motherhood. (JEL J16, J22, J31, J44)
DOI: 10.3886/e113756v1-130844
title: Replication data for: Dynamics of the Gender Gap for Young Professionals in the Financial and Corporate Sectors

description: The careers of MBAs from a top US business school are studied to understand how career dynamics differ by gender. Although male and female MBAs have nearly identical earnings at the outset of their careers, their earnings soon diverge, with the male earnings advantage reaching almost 60 log points a decade after MBA completion. Three proximate factors account for the large and rising gender gap in earnings: differences in training prior to MBA graduation, differences in career interruptions, and differences in weekly hours. The greater career discontinuity and shorter work hours for female MBAs are largely associated with motherhood. (JEL J16, J22, J31, J44)
DOI: 10.5517/ccdc.csd.cc2czqqt
title: CCDC 2204277: Experimental Crystal Structure Determination

description: Related Article: Teng Gao, Shaogang Shen, Yuanyuan Qin, Honglei Gao, Xiangyu Dong, Zhi Pang, Pengfei Wang, Ying Wang, Xiaoxiao Hu|2022|J.Mater.Chem.C|10|17053|doi:10.1039/D2TC04138C
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.cc2d01xd
title: CCDC 2204593: Experimental Crystal Structure Determination

description: Related Article: Liang-Yuan Pu, Yu-Jiao Zhang, Wei Liu, Fan Teng|2022|Chem.Commun.|58|13131|doi:10.1039/D2CC05172A
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.cc2d0d50
title: CCDC 2204911: Experimental Crystal Structure Determination

description: Related Article: Minju Lee, Kang Min Ok|2022|J.Mater.Chem.C|10|17127|doi:10.1039/D2TC04016F
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.cc2d0d61
title: CCDC 2204912: Experimental Crystal Structure Determination

description: Related Article: Minju Lee, Kang Min Ok|2022|J.Mater.Chem.C|10|17127|doi:10.1039/D2TC04016F
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.cc2d0d72
title: CCDC 2204913: Experimental Crystal Structure Determination

description: Related Article: Minju Lee, Kang Min Ok|2022|J.Mater.Chem.C|10|17127|doi:10.1039/D2TC04016F
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.cc2d41n8
title: CCDC 2208429: Experimental Crystal Structure Determination

description: Related Article: Bo Wang, Yiqing Lin|2022|Chem.Commun.|58|13071|doi:10.1039/D2CC05218K
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.cc2d424s
title: CCDC 2208444: Experimental Crystal Structure Determination

description: Related Article: Bo Wang, Yiqing Lin|2022|Chem.Commun.|58|13071|doi:10.1039/D2CC05218K
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: 10.5683/sp/vwcdkw
title: Anonymized Log Data from Drone-Video-Conferencing Study

description: This dataset contains anonymized log data (user-interface interaction logs and location/bearing data logs) from the drone-video-conferencing study that was part of my MSc thesis.
DOI: 10.13140/rg.2.2.33554.73925
title: 2%20Macovei[1].pdf
DOI: 10.13140/rg.2.2.11744.35849
title: 2%20Macovei[1].pdf
DOI: 10.5517/ccdc.csd.cc2cxl2z
title: CCDC 2202211: Experimental Crystal Structure Determination

description: Related Article: Peng-Hao Wang, Xiao-Yue Zhang, Jin-Ai Fan, Cai Sun|2022|Chem.Commun.|58|13099|doi:10.1039/D2CC04786A
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: 10.13140/rg.2.2.25166.13129
title: 2%20Macovei[1].pdf
DOI: 10.13140/rg.2.2.35232.46083
title: 2%20Macovei.Monica[1].pdf
DOI: 10.5287/bodleian:nrx68zxgw
title: Tool for Rapid Transient Transpiration Cooled Re-Entry Simulation - Dataset
DOI: 10.13140/rg.2.2.10905.49765
title: 2%20Macovei.Monica[1].pdf
DOI: 10.13140/rg.2.2.17616.38400
title: 2%20Macovei[1].pdf
DOI: 10.13140/rg.2.2.27682.71364
title: 3.%20Macovei%20Monica[1].pdf
DOI: 10.13140/rg.2.2.34393.60008
title: 16_Grigore[1].pdf
DOI: 10.26188/21618996
title: PhD Study 2 Access Database

description: Access Dataset for PhD Study 2. Contains detailed WAF accessment information to assess individual student Cambridge University English Vocabulary Profile ranking per question.
DOI: 10.26188/21618996.v1
title: PhD Study 2 Access Database

description: Access Dataset for PhD Study 2. Contains detailed WAF accessment information to assess individual student Cambridge University English Vocabulary Profile ranking per question.
DOI: 10.5281/zenodo.7359002
title: Emergent Solutions on Requirement Engineering for Agile Software Development: A tertiary study (Auxiliary Documentation in PDF)

description: <strong>[Context and motivation]</strong> Agile Software Development (ASD) is a new trend in software development and has become popular. Its advocates claim that ASD is well suited to solving traditional software development problems by valuing human factors over technical ones. However, one of the most critical phases in software development, Requirements Engineering (RE), can be overwhelming for ASD values.<br> <strong>[Question/problem]</strong> Trying to work with RE in a traditional way for ASD can limit ASD's potential. Therefore, it is necessary to investigate what academia and industry have done in RE to exploit all of the capabilities of ASD beyond traditional RE. <br> <strong>[Principal ideas/results]</strong> This work presents an overview of the state-of-the-art Requirement Engineering (RE) for Agile Software Development (ASD). We conducted a Tertiary Study in secondary studies published from 1st January 2015 to 30th June 2021, looking for solutions for RE-ASD using the Systematic Literature Review (SLR) protocol described by Kitchenham and Charters (2007). After executing the SLR protocol, we accepted 37 out of 169 studies and encountered 136 solutions used by academia and industry for RE-ASD. We considered only a few solutions that could be classified as emergent for RE-ASD, 24 out of 106. Furthermore, we cataloged the challenges presented by the emergent solutions (e.g., a steep learning curve due to the lack of experience, process, or culture) that should be addressed. Finally, we identified a possible gap between academia and industry regarding these emerging solutions that need further investigation. <br> <strong>[Contribution]</strong> By highlighting emerging Requirements Engineering (RE) solutions for Agile Software Development (ASD), we made our contribution to help researchers who need to propose new solutions to some of the problems that remain unsolved by pointing out the recent trends for RE for ASD. The repository contains the following: Auxiliary Documentation in PDF; Dataset from the Tertiary Study - compressed file (refsq2023Complement.zip): <strong>REFSQ2023-ALL-ARTICLES.csv:</strong> is a comma-separated file with all 198 (including the duplicates) found in our search in the digital libraries with their respective status (accepted, rejected, or duplicated). <strong>REFSQ2023-DISTINCT-SOLUTIONS.csv:</strong> is a comma-separated file with all the distinct solutions we found in our research. They are classified according to our classification method, explained in the article. <strong>REFSQ2023-GOOGLE-TRENDS-RESULTS.csv:</strong> is a comma-separated file with all results of our query in the Google Trends tool. It also brings the used search terms and the code and classification of each solution.
DOI: 10.13140/rg.2.2.12583.21923
title: Correlation between crystallography and beauty of symmetries In algerian carpets, jewels and achitectutral biuldings.
DOI: 10.5281/zenodo.7359001
title: Emergent Solutions on Requirement Engineering for Agile Software Development: A tertiary study (Auxiliary Documentation in PDF)

description: <strong>[Context and motivation]</strong> Agile Software Development (ASD) is a new trend in software development and has become popular. Its advocates claim that ASD is well suited to solving traditional software development problems by valuing human factors over technical ones. However, one of the most critical phases in software development, Requirements Engineering (RE), can be overwhelming for ASD values.<br> <strong>[Question/problem]</strong> Trying to work with RE in a traditional way for ASD can limit ASD's potential. Therefore, it is necessary to investigate what academia and industry have done in RE to exploit all of the capabilities of ASD beyond traditional RE. <br> <strong>[Principal ideas/results]</strong> This work presents an overview of the state-of-the-art Requirement Engineering (RE) for Agile Software Development (ASD). We conducted a Tertiary Study in secondary studies published from 1st January 2015 to 30th June 2021, looking for solutions for RE-ASD using the Systematic Literature Review (SLR) protocol described by Kitchenham and Charters (2007). After executing the SLR protocol, we accepted 37 out of 169 studies and encountered 136 solutions used by academia and industry for RE-ASD. We considered only a few solutions that could be classified as emergent for RE-ASD, 24 out of 106. Furthermore, we cataloged the challenges presented by the emergent solutions (e.g., a steep learning curve due to the lack of experience, process, or culture) that should be addressed. Finally, we identified a possible gap between academia and industry regarding these emerging solutions that need further investigation. <br> <strong>[Contribution]</strong> By highlighting emerging Requirements Engineering (RE) solutions for Agile Software Development (ASD), we made our contribution to help researchers who need to propose new solutions to some of the problems that remain unsolved by pointing out the recent trends for RE for ASD. The repository contains the following: Auxiliary Documentation in PDF; Dataset from the Tertiary Study - compressed file (refsq2023Complement.zip): <strong>REFSQ2023-ALL-ARTICLES.csv:</strong> is a comma-separated file with all 198 (including the duplicates) found in our search in the digital libraries with their respective status (accepted, rejected, or duplicated). <strong>REFSQ2023-DISTINCT-SOLUTIONS.csv:</strong> is a comma-separated file with all the distinct solutions we found in our research. They are classified according to our classification method, explained in the article. <strong>REFSQ2023-GOOGLE-TRENDS-RESULTS.csv:</strong> is a comma-separated file with all results of our query in the Google Trends tool. It also brings the used search terms and the code and classification of each solution.
DOI: 10.13140/rg.2.2.26004.99204
title: 3.%20Macovei%20Monica[1].pdf
DOI: 10.5517/ccdc.csd.cc2b87wr
title: CCDC 2152884: Experimental Crystal Structure Determination

description: Related Article: Ameneh Arabi, Marcus O. Cogley, Daniel Fabrizio, Shadrach Stitz, William A. Howard, Kraig A. Wheeler|2022|J.Mol.Struct.|1274|134551|doi:10.1016/j.molstruc.2022.134551
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.cc2c2jkk
title: CCDC 2177178: Experimental Crystal Structure Determination

description: Related Article: Ameneh Arabi, Marcus O. Cogley, Daniel Fabrizio, Shadrach Stitz, William A. Howard, Kraig A. Wheeler|2022|J.Mol.Struct.|1274|134551|doi:10.1016/j.molstruc.2022.134551
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.7359039
title: tropidonophis_doriae_decontaminated_gx.fasta.gz

description: .
DOI: 10.5517/ccdc.csd.cc2b87xs
title: CCDC 2152885: Experimental Crystal Structure Determination

description: Related Article: Ameneh Arabi, Marcus O. Cogley, Daniel Fabrizio, Shadrach Stitz, William A. Howard, Kraig A. Wheeler|2022|J.Mol.Struct.|1274|134551|doi:10.1016/j.molstruc.2022.134551
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.7359038
title: tropidonophis_doriae_decontaminated_gx.fasta.gz

description: .
DOI: 10.5281/zenodo.6659434
title: MargNet: Photometric identification of compact galaxies, stars and quasars

description: This page contains the accompanying deep learning models, dataset and code for the paper on MargNet, titled "Photometric identification of compact galaxies, stars and quasars using multiple neural networks". <strong>Deep Learning Models</strong>: MargNet is a deep learning-based classifier for identifying stars, quasars and compact galaxies using photometric parameters and images from the Sloan Digital Sky Survey. MargNet consists of a combination of Convolutional Neural Network (CNN) and Artificial Neural Network (ANN) architectures. The deep learning Keras model for each experiment was saved as an h5 file after training. All saved models (organised by different experiments, as described in the paper) are available in SavedModels.zip. <strong>Dataset</strong>: Our dataset consists of 240,000 compact objects and an additional 150,000 faint objects consisting of an equal number of stars, galaxies and quasars. This data is available as NumPy arrays and CSV files, as described below: SDSS ObjID of each object (objlist.npy) SDSS 5-band images of each object cropped to 32*32 pixels (X.npy) The set of 24 photometric features for each object (dnnx.npy) The classification label for each object (y.npy) SDSS spreadsheet containing all the features from dnnx, labels from y, ObjIDs from objlist and a couple of more SDSS specific parameters (photofeatures.csv) The complete dataset (organised by different experiments, as described in the paper) is available in Dataset.zip.<br> (Note: objlist, X, dnnx and y are in the same order. So, objlist[0], X[0], dnnx[0] and y[0] correspond to the same object.) <strong>Code</strong>: All our code was written in Python in the form of Jupyter Notebooks. A copy of our code has also been made available on GitHub, but not all files could be included on GitHub due to the storage limit. So a complete copy of the repository has also been mirrored here on Zenodo and is contained in MargNet_RepositoryMirror.tgz
DOI: 10.6084/m9.figshare.21441306.v1
title: cases statistics_2022_11_01.xls

description: Autosomal short tandem repeats (STRs) are routinely used for forensic parentage testing and individual identification. Abnormal allelic genotypes of autosomal STRs, X-STRs, and Y-STRs may affect the interpretation of forensic results. However, the extent of the effect on forensic results is not known. Therefore, we assessed the influence of abnormal chromosomes on forensic analysis results. The two autosomal STR kits used were not sensitive enough to produce accurate results for the two chimeric Turner syndrome patients studied; for one of the patients, the amelogenin genotype could lead to the wrong interpretation of sex. The blood sample from an allogenic bone marrow transplantation patient was not suitable for forensic analysis. Finally, different azoospermia factor microdeletions of the Y chromosome resulted in different Y-STR dropout patterns. Therefore, regarding individuals with abnormal chromosome karyotypes, forensic conclusions were affected.
DOI: 10.34740/kaggle/dsv/4580368
title: BBC News
DOI: 10.6084/m9.figshare.21619068
title: ESC_retinal organoid_ATAC_seq

description: embryonic stem cell normal ATAC-seq
DOI: 10.5517/ccdc.csd.cc29c8dc
title: CCDC 2125992: Experimental Crystal Structure Determination

description: Related Article: Taeil Shin, Taehoon Jang, Hyunwoo Kim|2022|Organometallics|41|3032|doi:10.1021/acs.organomet.2c00442
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.cc2bdhkt
title: CCDC 2156966: Experimental Crystal Structure Determination

description: Related Article: Levi S. Warring, Jacob E. Walley, Diane A. Dickie, William Tiznado, Sudip Pan, Robert J. Gilliard, Jr.|2022|Inorg.Chem.|61|18640|doi:10.1021/acs.inorgchem.2c03135
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.cc2bdhlv
title: CCDC 2156967: Experimental Crystal Structure Determination

description: Related Article: Levi S. Warring, Jacob E. Walley, Diane A. Dickie, William Tiznado, Sudip Pan, Robert J. Gilliard, Jr.|2022|Inorg.Chem.|61|18640|doi:10.1021/acs.inorgchem.2c03135
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.7359143
title: Japanese International Student-Athletes' Adjustment Experience at the National Collegiate Athletic Association

description: This data is the interview guide that was conducted in this article. The purpose of this study is to clarify the challenges for ISAs from Japan in adjusting to the United States’ universities. Situating in the ISA adjustment model and using a unique case study design, 13 Japanese ISAs at the NCAA Division I universities were interviewed, and data were coded by a continuous comparative analysis method. The results revealed that Japanese ISAs who participated in this study faced academic, social, athletic, personal-emotional, and institutional adjustment challenges. Particularly, Japanese ISAs differed from ISAs from other countries in several points; cultural differences, differences in communication styles, and systemic differences in academia and athletics between Japan and the US.<br> All datasets underlying the results cannot be sufficiently de-identified by redaction for uploading to a general data repository due to the sample size and nature of the conversations. Thus, the datasets are not available to share for ethical and privacy considerations as well as the guarantee given to the interviewees to maintain the anonymity of the interview. A reader or reviewer may apply for access to the datasets by contacting the corresponding author (matsuo. hirokazu.ga@u.tsukuba.ac.jp) directly. The access will be available upon considering the request and permission<br> received from the interviewees. The row datasets are in Japanese.