cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.7284/117544
title: Multibeam Echosounder data collected during research cruise WEST15MV using a SeaBeam 2000 instrument system onboard the platform RV Melville

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.14459/2023mp1709953
title: Generation and Scan Data for Publication "Target Acquired? Evaluating Target Generation Algorithms for IPv6" at TMA'23

description: This dataset describes and reproduces the findings presented in the paper "Target Acquired? Evaluating Target Generation Algorithms for IPv6", published at TMA'23. It contains the scripts for setting up the used Target Generation Algorithms, their inputs and generated candidate sets, their active subsets discovered by our sets and scripts for reproducing our visualizations and results. The data is published in CSV format, the scripts can be found in a Jupyter notebook. Additional data can be found at the IPv6 Hitlist service
DOI: 10.12751/g-node.dhwj4v
title: Evaluation of oculomotor functions in the diagnosis of mTBI: a pilot study with healthy controls using eye-tracking and fMRI

description: fMRI data was obtained on 31 healthy adults using oculomotor tasks developed by Neuroflex(c) Each run included a set of 4 tasks - Smooth Pursuit, Saccades, Anti-Saccades, and Optokinetic Nystagmus repeated twice.
DOI: 10.17037/data.00003491
title: Therapy codelist - CPRD Gold - Antihypertensive medications read codes

description: Read codes for Antihypertensive medications extracted from the Clinical Practice Research Datalink (CPRD).
DOI: 10.17037/data.00003492
title: Clinical codelist - CPRD Gold - Chronic kidney disease read codes

description: Read codes for Chronic kidney disease extracted from the Clinical Practice Research Datalink (CPRD).
DOI: 10.6084/m9.figshare.23499195
title: Figure 1 - Data and Code

description: Data and code to reproduce Figures 1a, b, and c.
DOI: 10.6084/m9.figshare.23499195.v1
title: Figure 1 - Data and Code

description: Data and code to reproduce Figures 1a, b, and c.
DOI: 10.7284/149358
title: CTD (Conductivity, Temperature, Depth) data collected during research cruise AE2111 using a SeaBird SBE-911+ instrument system onboard the platform RV Atlantic Explorer

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.17037/data.00003493
title: Clinical codelist - CPRD Gold - Coronary heart disease read codes

description: Read codes for Coronary heart disease extracted from the Clinical Practice Research Datalink (CPRD).
DOI: 10.6084/m9.figshare.23499198
title: Figure 2 - Data and code

description: Data and code to reproduce Figure 2 a and c, both created with Excel. Figure 2b is based on the data of Figure 2a.
DOI: 10.6084/m9.figshare.23499198.v1
title: Figure 2 - Data and code

description: Data and code to reproduce Figure 2 a and c, both created with Excel. Figure 2b is based on the data of Figure 2a.
DOI: 10.17037/data.00003494
title: Therapy codelist - CPRD Gold - Diabetes medications

description: Read codes for Diabetes medications extracted from the Clinical Practice Research Datalink (CPRD).
DOI: 10.5281/zenodo.7213667
title: supplementary files of IFD

description: 补充文件
DOI: 10.5281/zenodo.7213668
title: supplementary files of IFD

description: 补充文件
DOI: 10.5281/zenodo.8028469
title: supplementary files of IFD

description: 补充文件
DOI: 10.17037/data.00003495
title: Clinical codelist - CPRD Gold - Diabetes read codes

description: Read codes for Diabetes extracted from the Clinical Practice Research Datalink (CPRD).
DOI: 10.17037/data.00003496
title: Clinical codelist - CPRD Gold - Diabetic retinopathy read codes

description: Read codes for Diabetic retinopathy extracted from the Clinical Practice Research Datalink (CPRD).
DOI: 10.17037/data.00003497
title: Clinical codelist - CPRD Gold - Heart failure read codes

description: Read codes for heart failure extracted from the Clinical Practice Research Datalink (CPRD).
DOI: 10.17037/data.00003498
title: Clinical codelist - CPRD Gold - Hypertension

description: Read codes for hypertension extracted from the Clinical Practice Research Datalink (CPRD).
DOI: 10.17034/95462975-ee19-4864-9120-557946d1c293
title: Supplementary files for "Identification and characterisation of antimicrobial peptides in parasitic helminths"

description: PhD thesis supplementary Excel files. Files provided in xlsx and CSV formats. Please contact airvine16@qub.ac.uk for any issues regarding access to files. Supplementary File 1: SF1, Table 1: AMP query sequences used for construction of AMP group HMMs. SF1, Table 2: Genomic and transcriptomic datasets used in the study. All files were retrieved from Wormbase Parasite version 14. SF1, Table 3: AMP gene IDs identified from 134 nematode predicted protein datasets. SF1, Table 4: Number and relative abundance of putative AMP genes identified in this study. Supplementary File 2: SF2, Table 1: Lophotrochozoan-derived AMPs identified in literature search SF2, Table 2: Genomic and transcriptomic datasets utilised in the study. All files were retrieved from Wormbase Parasite version 14. SF2, Table 3: HMM query sequences used to build antimicrobial saposin profile SF2, Table 4: Flatworm Gene ID for Histone, Ubiquitin, B-Thymosin, Troponin and Filamin protein homologs. All gene IDs are from Wormbase Parasite version 14 SF2, Table 5: Identified putative antimicrobial SAPosin-Like Protein (SAPLIP) genes from flatworms Supplementary File 3: SF3, Table 1: Genomic datasets utilised in the study. All files were retrieved from Wormbase Parasite version 12. SF3, Table 2: Nematode AMP-LPs SF3, Table 3: Flatworm AMP-LPs Supplementary File 4: SF4, Table 1: Cecropin gene complement in eight Ascarididoidea species. Supplementary File 5: SF5, Table 1: Genomic and transcriptomic datasets utilised in the study. SF5, Table 2: Macin gene complement in 28 nematode species. Dataset files are embargoed until 31 July 2024 in line with thesis embargo.
DOI: 10.57745/yqdu24
title: Lisez_moi.pdf

description: Fichier lisez-moi associé au jeu de données Nomenclature Hérelles.
DOI: 10.57745/h6dhvl
title: Synopsis_Nomenclature.tab

description: Tableau comparatif des différentes nomenclatures "candidates".
DOI: 10.57745/iyxmrx
title: Dictionnaire_Concepts.pdf

description: Définition des concepts de la hiérarchie Hérelles.
DOI: 10.57745/wd309q
title: Caractéristiques_Classes_Concept.pdf

description: Synthèse des caractéristiques principales des concepts de la hiérarchie Hérelles.
DOI: 10.57745/nckonj
title: Organigramme_Hierarchie_Concepts.pdf

description: Représentation schématique de la hiérarchie de concept.
DOI: 10.57745/7wbjgd
title: Sémantique_Herelles_Nomenclature.pdf

description: Tableau associant certains concepts de la hiérarchie à des termes similaires ou sémantiquement proches.
DOI: 10.17037/data.00003499
title: Clinical codelist - CPRD Gold - Ischemic stroke

description: Read codes for Ischemic stroke extracted from the Clinical Practice Research Datalink (CPRD).
DOI: 10.6084/m9.figshare.23402816
title: 7,690 SNP markers for genomic selection of quantitative traits in chile peppers

description: Genotype data (numeric) of the 204 chile pepper genotypes for 7,690 single nucleotide polymorphism (SNP) markers used for genomic prediction.
DOI: 10.6084/m9.figshare.23502000
title: <strong>Practices for Managing Machine Learning Products: a Multivocal Literature</strong>

description: The data available is the replication package as supplementary material of the paper "Practices for Managing Machine Learning Products: a Multivocal Literature Review , providing a detailed chain of evidence so that any researcher can verify all codes and the most relevant excerpts. <br> Abstract: Machine Learning (ML) has grown in popularity in the software industry due to its ability to solve complex problems. Developing ML Systems involves more uncertainty and risk because it requires identifying a business opportunity and managing source code, data, and trained models. Our research aims to identify the existing practices used in the industry for building ML applications, comprehending the organizational complexity of adopting ML Systems. We conducted a Multivocal Literature Review and, then, created a taxonomy of the practices applied to the ML System lifecycle discussed among practitioners and researchers. The core of the study emerged from 41 selected posts from the grey literature and 37 selected scientific papers. Applying Initial Coding and Focused Coding techniques into these data, we mapped 91 practices into six core categories related to designing, developing, testing, and deploying ML Systems. The results, including a taxonomy of practices, provide organizations with valuable insights to identify gaps in their current ML processes and practices and a roadmap for improving, optimizing, and managing ML systems.
DOI: 10.6084/m9.figshare.23502000.v1
title: <strong>Practices for Managing Machine Learning Products: a Multivocal Literature</strong>

description: The data available is the replication package as supplementary material of the paper "Practices for Managing Machine Learning Products: a Multivocal Literature Review , providing a detailed chain of evidence so that any researcher can verify all codes and the most relevant excerpts. <br> Abstract: Machine Learning (ML) has grown in popularity in the software industry due to its ability to solve complex problems. Developing ML Systems involves more uncertainty and risk because it requires identifying a business opportunity and managing source code, data, and trained models. Our research aims to identify the existing practices used in the industry for building ML applications, comprehending the organizational complexity of adopting ML Systems. We conducted a Multivocal Literature Review and, then, created a taxonomy of the practices applied to the ML System lifecycle discussed among practitioners and researchers. The core of the study emerged from 41 selected posts from the grey literature and 37 selected scientific papers. Applying Initial Coding and Focused Coding techniques into these data, we mapped 91 practices into six core categories related to designing, developing, testing, and deploying ML Systems. The results, including a taxonomy of practices, provide organizations with valuable insights to identify gaps in their current ML processes and practices and a roadmap for improving, optimizing, and managing ML systems.
DOI: 10.17037/data.00003500
title: Clinical codelist - CPRD Gold - Mild cognitive impairment

description: Read codes for mild cognitive impairment extracted from the Clinical Practice Research Datalink (CPRD).
DOI: 10.7284/149360
title: CTD (Conductivity, Temperature, Depth) data collected during research cruise AE2112 using a SeaBird SBE-911+ instrument system onboard the platform RV Atlantic Explorer

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.5525/gla.researchdata.1441
title: Male Suicide Risk and Recovery Factors: A 20-year Systematic Review and Qualitative Meta-analysis

description: Data is from a qualitative meta-synthesis article looking at male suicide risk and recovery factors.
DOI: 10.17037/data.00003501
title: Clinical codelist - CPRD Gold - Neuropathy

description: Read codes for neuropathy extracted from the Clinical Practice Research Datalink (CPRD).
DOI: 10.7284/149363
title: CTD (Conductivity, Temperature, Depth) data collected during research cruise AE2114 using a SeaBird SBE-911+ instrument system onboard the platform RV Atlantic Explorer

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.17037/data.00003502
title: Clinical codelist - CPRD Gold - Peripheral vascular disease

description: Read codes for peripheral vascular disease extracted from the Clinical Practice Research Datalink (CPRD).
DOI: 10.7284/149364
title: CTD (Conductivity, Temperature, Depth) data collected during research cruise AE2115 using a SeaBird SBE-911+ instrument system onboard the platform RV Atlantic Explorer

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.57745/dpmfiq
title: EstimationProductionSedimentaireTorrents_HydroDemoV1.tab

description: Feuile de calcul MS Excel pour l'estimation de la production sédimentaire des torrents
DOI: 10.5281/zenodo.8024907
title: Top-down determinants of the numerosity-time interaction

description: This is the dataset related to the article:"Top-down determinants of the numerosity-time interaction" The file contains subjects data for the four experiments sub_ID is the participant's identification number PSE indicates the Point of Subjective Equality for the Specified Condition SD indicates the Standard Deviation of the PSE in the adjacent column
DOI: 10.17037/data.00003503
title: Clinical codelist - CPRD Gold - Smoking

description: Read codes for smoking extracted from the Clinical Practice Research Datalink (CPRD).
DOI: 10.7284/149365
title: CTD (Conductivity, Temperature, Depth) data collected during research cruise AE2116 using a SeaBird SBE-911+ instrument system onboard the platform RV Atlantic Explorer

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.5281/zenodo.8028584
title: Single-pulsar search for eccentric SMBHBs using NANOGrav 12.5-year data of PSR J1909--3744: Posterior samples

description: This repository contains posterior samples for a Bayesian single-pulsar search for nanohertz gravitational waves originating from eccentric supermassive binaries, done using the NANOGrav 12.5-year dataset for PSR J1909-3744. The analysis is presented in Susobhanan 2023 [https://arxiv.org/abs/2210.11454].
DOI: 10.5281/zenodo.8028583
title: Single-pulsar search for eccentric SMBHBs using NANOGrav 12.5-year data of PSR J1909--3744: Posterior samples

description: This repository contains posterior samples for a Bayesian single-pulsar search for nanohertz gravitational waves originating from eccentric supermassive binaries, done using the NANOGrav 12.5-year dataset for PSR J1909-3744. The analysis is presented in Susobhanan 2023 [https://arxiv.org/abs/2210.11454].
DOI: 10.5281/zenodo.7938743
title: Investigating the fast spectral diffusion of a quantum emitter in hBN using resonant excitation and photon correlations

description: Data from the article "Investigating the fast spectral diffusion of a quantum emitter in hBN using resonant excitation and photon correlations" (Phys. Rev. B <strong>107</strong>, 195304 (2023) – [arXiv])
DOI: 10.17037/data.00003504
title: Therapy codelist - CPRD Gold - Statins

description: Read codes for Statins extracted from the Clinical Practice Research Datalink (CPRD).
DOI: 10.7284/149367
title: CTD (Conductivity, Temperature, Depth) data collected during research cruise AE2120 using a SeaBird SBE-911+ instrument system onboard the platform RV Atlantic Explorer

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/149368
title: CTD (Conductivity, Temperature, Depth) data collected during research cruise AE2121 using a SeaBird SBE-911+ instrument system onboard the platform RV Atlantic Explorer

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/149370
title: CTD (Conductivity, Temperature, Depth) data collected during research cruise AE2123 using a SeaBird SBE-911+ instrument system onboard the platform RV Atlantic Explorer

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/149371
title: CTD (Conductivity, Temperature, Depth) data collected during research cruise AE2124 using a SeaBird SBE-911+ instrument system onboard the platform RV Atlantic Explorer

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.5281/zenodo.8028614
title: [Data S10] Microbiota dictate T cell clonal selection to promote graft-vs-host disease after stem cell transplantation

description: Data S10. 10x genomics sequencing data files for Figure 5. Matrix file "sample_filtered_feature_bc_matrix.h5" and V(D)J annotations "filtered_contig_annotations.csv" are included below. Accompanying code can be found at https://github.com/acyeh-lab/2023/tree/main/scseq.
DOI: 10.5281/zenodo.8028613
title: [Data S10] Microbiota dictate T cell clonal selection to promote graft-vs-host disease after stem cell transplantation

description: Data S10. 10x genomics sequencing data files for Figure 5. Matrix file "sample_filtered_feature_bc_matrix.h5" and V(D)J annotations "filtered_contig_annotations.csv" are included below. Accompanying code can be found at https://github.com/acyeh-lab/2023/tree/main/scseq.
DOI: 10.5281/zenodo.8028508
title: Microscopy-based assessment of H3K27-acetylation at RNA polymerase II clusters during early stages of zebrafish embryo development (additional data)

description: Additional data for the the following main repository: https://doi.org/10.5281/zenodo.8019735
DOI: 10.5281/zenodo.8028507
title: Microscopy-based assessment of H3K27-acetylation at RNA polymerase II clusters during early stages of zebrafish embryo development (additional data)

description: Additional data for the the following main repository: https://doi.org/10.5281/zenodo.8019735
DOI: 10.5281/zenodo.8019735
title: Microscopy-based assessment of H3K27-acetylation at RNA polymerase II clusters during early stages of zebrafish embryo development

description: This repository contains the data and MatLab analysis scripts of the analysis of histone 3 lysine 27 acetylation (H3K27ac) at RNA polymerase II clusters over the course of zygotic genome activation and gastrulation of zebrafish embryos. Samples were prepared and images were recorded by Marcel Sobucki in Lennart Hilbert's laboratory, images were analyzed by Lennart Hilbert. To analyse date data, the raw image data are first extracted into MatLab-native files using the MultiPosition_extraction_nd2.m script. The actual analysis is then carried out using the ClusterAnalysis.m script. Example microscopy images were produced using the ExampleImages.m script. The extracted data can be reviewed using the ReviewExtractedStacks.m script. Additional data needed to be stored in an extra repository due to size limitations: https://doi.org/10.5281/zenodo.8028508
DOI: 10.5281/zenodo.7966359
title: Effect of stochastic deformation on the vibration characteristics of a tube bundle in axial flow: code and data

description: These files accompany the following publication: Dolfen, H., Vandewalle, S., & Degroote, J. (2023). Effect of stochastic deformation on the vibration characteristics of a tube bundle in axial flow. Nuclear Engineering and Design, 411, 112412. doi:10.1016/j.nucengdes.2023.112412. In this publication the effect of a stochastic bow deformation on the vibration characteristics of a tube bundle was investigated. The Monte Carlo and generalized Polynomial Chaos (gPC) method were used. For the latter method, the chaospy Python-package was used. Further dependencies include the numpy, scipy and matplotlib Python packages. The gPC was benchmarked with the Monte Carlo method on a steady CFD case. The the gPC was used on an FSI case used to extract the output quantity of interest, the vibration characteristics. This FSI case was run in the open-source code CoCoNuT. This code developed at Ghent University is Python-based and has the capability to couple existing solvers, both open-source and commercial solvers. The archive includes scripts to set-up the steady CFD case as well as the FSI case, the used version of CoCoNuT and some post-processing scripts. ReadMe files are provided to explain the files, and what adjustments are likely needed to make it work on a different system. For CoCoNuT to work, the 'coconut' folder should be added to the PYTHONPATH environment variable. For requirements to run CoCoNuT, refer to the documentation.
DOI: 10.5281/zenodo.7966358
title: Effect of stochastic deformation on the vibration characteristics of a tube bundle in axial flow: code and data

description: These files accompany the following publication: Dolfen, H., Vandewalle, S., & Degroote, J. (2023). Effect of stochastic deformation on the vibration characteristics of a tube bundle in axial flow. Nuclear Engineering and Design, 411, 112412. doi:10.1016/j.nucengdes.2023.112412. In this publication the effect of a stochastic bow deformation on the vibration characteristics of a tube bundle was investigated. The Monte Carlo and generalized Polynomial Chaos (gPC) method were used. For the latter method, the chaospy Python-package was used. Further dependencies include the numpy, scipy and matplotlib Python packages. The gPC was benchmarked with the Monte Carlo method on a steady CFD case. The the gPC was used on an FSI case used to extract the output quantity of interest, the vibration characteristics. This FSI case was run in the open-source code CoCoNuT. This code developed at Ghent University is Python-based and has the capability to couple existing solvers, both open-source and commercial solvers. The archive includes scripts to set-up the steady CFD case as well as the FSI case, the used version of CoCoNuT and some post-processing scripts. ReadMe files are provided to explain the files, and what adjustments are likely needed to make it work on a different system. For CoCoNuT to work, the 'coconut' folder should be added to the PYTHONPATH environment variable. For requirements to run CoCoNuT, refer to the documentation.
DOI: 10.57967/hf/0751
title: headlines-semantic-similarity
DOI: 10.5517/ccdc.csd.ccsm04j
title: CCDC 733247: Experimental Crystal Structure Determination

description: Related Article: N. Srinivasan, P. Valarmathi, S. Thirumaran, Samuele Ciattini|2023|J.Mol.Struct.|1289|135800|doi:10.1016/j.molstruc.2023.135800
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.cc2cwdm9
title: CCDC 2201081: Experimental Crystal Structure Determination

description: Related Article: Yoshimi Ichimaru, Koichi Kato, Kirara Sugiura, Risa Isomura, Haruto Fujioka, Tohru Koike, Sayuri Fujii-Kishida, Masaaki Kurihara, Yoshihiro Yamaguchi, Wanchun Jin, Masanori Imai, Hiromasa Kurosaki|2023|Inorg.Chem.Commun.|153|110782|doi:10.1016/j.inoche.2023.110782
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.cc2drtxx
title: CCDC 2227440: Experimental Crystal Structure Determination

description: Related Article: N. Broftová, T. Landovský, H. Dvořáková, V. Eigner, M. Krupička, P. Lhoták|2023|Org.Biomol.Chem.|21|4620|doi:10.1039/D3OB00530E
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.cc2drtyy
title: CCDC 2227441: Experimental Crystal Structure Determination

description: Related Article: N. Broftová, T. Landovský, H. Dvořáková, V. Eigner, M. Krupička, P. Lhoták|2023|Org.Biomol.Chem.|21|4620|doi:10.1039/D3OB00530E
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.