cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6073/pasta/043fe51a8f71c376b86402c57f57133b
title: Abundance and Size of Seagrass-Associated Fishes in the Virginia Coastal Lagoons, 2019-2023

description: These data comprise annual summer estimates of the abundance (counts) and size (length) of fishes across restored seagrass meadows of the Virginia coastal lagoons. Fish were collected using a 25-ft (7.62-m) wide beach seine hauled by hand over a 25 m linear swath of the seafloor. Seine hauls were collected in June at 31 sites (1 haul per site). All fish caught in the seine were identified to lowest practical taxonomic level, counted, measured (total length), and released. Data collection began in June 2019 and continues annually (sampling was not carried out in 2020 due to logistical interruptions associated with the COVID-19 pandemic). Data on water temperature, salinity, and conductivity were collected while sampling occurred using a YSI 30 probe. Dissolved oxygen measurements were collected using a YSI ProODO probe. In 2019, these data were collected on the top and bottom of the water column, but in 2021 and subsequent sampling only one observation (mid-water column) was made. To reconcile this difference for the combined data set, top and bottom environmental measurements from 2019 were averaged. Each fish collection site is co-located with a nearby synoptic site where long-term measurements of seagrass, sediments, and fauna are made. The relationship between site names and coordinates are given in Synoptic_fish_sites.csv. The sites where fish sampling occurred are different and are given by the "fish_sites" column, with coordinates for these sites under the "fish_longitude" and "fish_latitude" columns. Importantly, the coordinates of where sampling occurred will differ slightly between years without a change to the name of the site. Site geographic coordinates for individual years are in the PhysicalSamples.csv file. In 2023, three new sites were added to represent unvegetated areas outside of but near the seagrass meadows. These sites are HI29, SPDR-bare, and SS-bare, and are designed to serve as references for seagrass sites in Hog Island Bay, Spider Crab Bay / Cobb Bay, and South Bay / Ship Shoal, respectively.
DOI: 10.6084/m9.figshare.24241159.v3
title: data

description: These data are presented in the article titled "Dopamine neuron activity evoked by food and food predictive cues is augmented by peripheral and central manipulations of glucose availability." These data have been processed as follows:Raw 405nm was subtracted from raw 465nm and then normalized by z-scoring each session.The data have then been downsampled from ~1kHz to 10HzThe data have then been stored in a .csv as long format with pertinent information (event onsets/offsets, treatments, etc.)
DOI: 10.6073/pasta/93e28b956f19095f87c34b899469c53a
title: DEPRECATED: Hubbard Brook Experimental Forest (USDA Forest Service): Daily Mean Temperature Data, 1955 - present

description: This data package has been DEPRECATED. The full timeline of these data can be found in: USDA Forest Service, Northern Research Station. 2023. Hubbard Brook Experimental Forest: Daily Temperature Record, 1955 - present ver 12. Environmental Data Initiative. https://doi.org/10.6073/pasta/44d122ddf3b108473d8e9e13c6b2ddb0. Air temperature is measured at seven locations within the rain gage clearings throughout Hubbard Brook. The oldest air temperature record dates back to October 20, 1955 at Station 1. Since that time, temperature measurements have been made continuously using hygrothermographs housed in standard shelters. These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station.
DOI: 10.5281/zenodo.8436178
title: Targeted social immunity is associated with a pathogen-specific erosion of individual immune function in ants - dataset

description: Complete dataset of quantitative data and R scripts used to generate the figures and statistics of the publication, sorted by figure panel number. Information about data structure are including in the scripts.
DOI: 10.5281/zenodo.8436177
title: Targeted social immunity is associated with a pathogen-specific erosion of individual immune function in ants - dataset

description: Complete dataset of quantitative data and R scripts used to generate the figures and statistics of the publication, sorted by figure panel number. Information about data structure are including in the scripts.
DOI: 10.6084/m9.figshare.24298951
title: EVC 2022 closed codes

description: Closed codes applying the Neglected, Acknowledged, Targeted (NAT) taxonomy to the interviews described in:https://figshare.com/articles/online_resource/EVC_Interview_Guide/23552844https://figshare.com/articles/presentation/EVC_Interview_Slides/23552808
DOI: 10.6084/m9.figshare.24298951.v1
title: EVC 2022 closed codes

description: Closed codes applying the Neglected, Acknowledged, Targeted (NAT) taxonomy to the interviews described in:https://figshare.com/articles/online_resource/EVC_Interview_Guide/23552844https://figshare.com/articles/presentation/EVC_Interview_Slides/23552808
DOI: 10.5281/zenodo.7897564
title: Regression Datasets: Strength as a Function of Liquid Water Content in Different Snow Types

description: This repository contains two datasets used for determining the shear strength of different snow types as a function of liquid water content. It also contains one dataset with additional information pertaining to our experiment, including site and condition details. <strong>Please read the 'Read me.txt' file before using these datasets.</strong>
DOI: 10.5281/zenodo.7897565
title: Regression Datasets: Strength as a Function of Liquid Water Content in Different Snow Types

description: This repository contains two datasets used for determining the shear strength of different snow types as a function of liquid water content: <strong>1. Wet Snow Strength - All Data</strong>: This dataset contains 349 paired measurements of blade hardness (N) and volumetric liquid water content (LWC, %) taken within 19 different snow layers. Blade hardness is measured using a blade hardness gauge and LWC is measured using an SLF snow sensor. Properties of the snow layer where each measurement was taken are also listed. <strong>2. Blade Hardness Gauge Shear Frame Comparison - All Data: </strong>This dataset contains 216 measurements of blade hardness (N) and shear strength (kPa) taken within 18 different snow layers. Blade hardness is measured using a blade hardness gauge and shear strength is measured using a 250 cm<sup>2</sup> shear frame. 12 measurements from each instrument are taken for each snow layer within a 100 x 150 cm plot. Shear frame measurements listed have already been adjusted for frame size effects (using a multiplier of 0.65 for the 250 cm<sup>2</sup> shear frame). Properties of the snow layer where each measurement was taken are also listed.
DOI: 10.5281/zenodo.7949501
title: Regression Datasets: Strength as a Function of Liquid Water Content in Different Snow Types

description: This repository contains two datasets used for determining the shear strength of different snow types as a function of liquid water content. It also contains one dataset with additional information pertaining to our experiment, including site and condition details. <strong>Please read the 'Read me.txt' file before using these datasets.</strong>
DOI: 10.5281/zenodo.8436295
title: Regression Datasets: Strength as a Function of Liquid Water Content in Different Snow Types

description: This repository contains two datasets used for determining the shear strength of different snow types as a function of liquid water content. It also contains one dataset with additional information pertaining to our experiment, including site and condition details. <strong>Please read the 'Read me.txt' file before using these datasets.</strong>
DOI: 10.5281/zenodo.8436315
title: Machine Learning Applications in Marketing: Literature Review and Research Agenda

description: Currently, machine learning applications in marketing allow to optimize strategies, personalize experiences and improve decision making. However, there are still several research gaps, so the objective is to examine the research trends in the use of machine learning in marketing. A bibliometric analysis is proposed to assess the current scientific activity, following the parameters established by PRISMA-2020. Machine learning applications in marketing have experienced steady growth and increased attention in the academic community. Key references, such as Miklosik and Evans, and prominent journals, such as IEEE Access and Journal of Business Research, have been identified. A thematic evolution towards big data and digital marketing is observed, and thematic clusters such as "digital marketing", "interpretation", "prediction", and "healthcare" stand out. These findings demonstrate the continued importance and research potential of this evolving field.
DOI: 10.5281/zenodo.8436314
title: Machine Learning Applications in Marketing: Literature Review and Research Agenda

description: Currently, machine learning applications in marketing allow to optimize strategies, personalize experiences and improve decision making. However, there are still several research gaps, so the objective is to examine the research trends in the use of machine learning in marketing. A bibliometric analysis is proposed to assess the current scientific activity, following the parameters established by PRISMA-2020. Machine learning applications in marketing have experienced steady growth and increased attention in the academic community. Key references, such as Miklosik and Evans, and prominent journals, such as IEEE Access and Journal of Business Research, have been identified. A thematic evolution towards big data and digital marketing is observed, and thematic clusters such as "digital marketing", "interpretation", "prediction", and "healthcare" stand out. These findings demonstrate the continued importance and research potential of this evolving field.
DOI: 10.5517/ccdc.csd.cc2fl2lq
title: CCDC 2251703: Experimental Crystal Structure Determination

description: Related Article: Santosh J. Gharpure, Sanyog Kumari, Mahadev S. Sherikar|2023|Chem.Asian J.|18|e202300626|doi:10.1002/asia.202300626
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.cc2fl2ns
title: CCDC 2251705: Experimental Crystal Structure Determination

description: Related Article: Santosh J. Gharpure, Sanyog Kumari, Mahadev S. Sherikar|2023|Chem.Asian J.|18|e202300626|doi:10.1002/asia.202300626
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.cc2fl2ty
title: CCDC 2251710: Experimental Crystal Structure Determination

description: Related Article: Santosh J. Gharpure, Sanyog Kumari, Mahadev S. Sherikar|2023|Chem.Asian J.|18|e202300626|doi:10.1002/asia.202300626
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.cc2fl2vz
title: CCDC 2251711: Experimental Crystal Structure Determination

description: Related Article: Santosh J. Gharpure, Sanyog Kumari, Mahadev S. Sherikar|2023|Chem.Asian J.|18|e202300626|doi:10.1002/asia.202300626
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.cc2fzp7c
title: CCDC 2263813: Experimental Crystal Structure Determination

description: Related Article: Sohan Singh, Vikki N. Shinde, Sunil Kumar, Neha Meena, Nattamai Bhuvanesh, Krishnan Rangan, Anil Kumar, Hemant Joshi|2023|Chem.Asian J.|18|e202300628|doi:10.1002/asia.202300628
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.cc2fzp9f
title: CCDC 2263815: Experimental Crystal Structure Determination

description: Related Article: Sohan Singh, Vikki N. Shinde, Sunil Kumar, Neha Meena, Nattamai Bhuvanesh, Krishnan Rangan, Anil Kumar, Hemant Joshi|2023|Chem.Asian J.|18|e202300628|doi:10.1002/asia.202300628
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.cc2g5886
title: CCDC 2269177: Experimental Crystal Structure Determination

description: Related Article: Santosh J. Gharpure, Sanyog Kumari, Mahadev S. Sherikar|2023|Chem.Asian J.|18|e202300626|doi:10.1002/asia.202300626
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: 10.6084/m9.figshare.24299464
title: Supplemental Materials

description: Supplemental materials from Martin et al., 2023
DOI: 10.6084/m9.figshare.24299464.v1
title: Supplemental Materials

description: Supplemental materials from Martin et al., 2023
DOI: 10.5517/ccdc.csd.cc2flwmk
title: CCDC 2252479: Experimental Crystal Structure Determination

description: Related Article: Marvin Sindlinger, Markus Ströbele, Jörg Grunenberg, Holger F. Bettinger|2023|Chemical Science|14|10478|doi:10.1039/D3SC03433J
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.cc2gfwvn
title: CCDC 2277472: Experimental Crystal Structure Determination

description: Related Article: Jonathan B. F. Vandenwijngaerden, Jianjun Huang, Charlotte Cresens, Wim Dehaen, Luc Van Meervelt, Susana Rocha, Mark Van der Auweraer, Eduard Fron|2023|Mat.Advs.|4|4571|doi:10.1039/D3MA00511A
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.cc2gfwwp
title: CCDC 2277473: Experimental Crystal Structure Determination

description: Related Article: Jonathan B. F. Vandenwijngaerden, Jianjun Huang, Charlotte Cresens, Wim Dehaen, Luc Van Meervelt, Susana Rocha, Mark Van der Auweraer, Eduard Fron|2023|Mat.Advs.|4|4571|doi:10.1039/D3MA00511A
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.8436282
title: Dataset for article: Hofmann and Keller. "XXXX". XXXX

description: This is a dataset related to documentation considered for analysis associated with the following publication: Hofmann and Keller. "XXXX". <em>Journal of XXXX.</em> The archive savedrecs.xlsx are the records from Web of Science Core Collection. The archive scopus.xlsx are the records from Scopus. The archive source_not_considered.xlsx are the journals not considered for this research.
DOI: 10.5281/zenodo.8436281
title: Dataset for article: Hofmann and Keller. "XXXX". XXXX

description: This is a dataset related to documentation considered for analysis associated with the following publication: Hofmann and Keller. "XXXX". <em>Journal of XXXX.</em> The archive savedrecs.xlsx are the records from Web of Science Core Collection. The archive scopus.xlsx are the records from Scopus. The archive source_not_considered.xlsx are the journals not considered for this research.
DOI: 10.6084/m9.figshare.24293662
title: Assembled transcriptomes, individual gene alignments, concatenated and trimmed alignments, tree files for the phylogenomic dataset including eleftherids, Ichthyodinida and psammosids.

description: The dataset contains the concatenated and trimmed alignment and corresponding Maximum-likelihood (ML) multi-protein tree for phylogenomic analysis of eleftherids, Ichthyodinida (MALV-I) and psammosids. Transcriptomes assembled from raw reads are provided in the "transcriptomes" folder. The individual proteins concatenated for phylogenomic analysis are in the "individual_proteins" folder. Individual proteins and the corresponding phylogenomic files with additional SAG data from Delmont <i>et al.</i> 2022 are included in "wDelmont2022SAGs" Transcriptomes were assembled with Trinity (eleftherids) or rnaSPAdes (Ichthyodinida, psammosids) and protein coding regions were predicted using TransDecoder. Homologues to the 263 genes described in Burki <i>et al. </i>2016 were identified using BLAST, aligned with MAFFT L-ins-i and trimmed with trimAL (gap threshold of 80%). Single-protein ML phylogenies were reconstructed and manually cleaned to remove paralogues/contamination. Cleaned proteins were then aligned and trimmed as above and concatenated with SCaFOs. ML trees of the final concatenated alignment were generated with IQ-TREE using the LG+C60+F+G4 model.
DOI: 10.6084/m9.figshare.23148029
title: Supplementary data: Contrasting genes for short and long-term biofilm adaptation in <em>Listeria </em>

description: <em>Listeria monocytogenes</em> is a dangerous bacterium found in food that can cause severe illness and even death in humans. It has different types, some of which are more likely to infect people. Biofilms, crucial for survival and infection, hold the key to understanding transmission. To unravel the genetic basis of biofilm formation, we undertook a study employing genome-wide association studies and gene transcription profiling. We identified 273 genes associated with robust biofilm formation through GWAS and discovered differential expression in 220 genes through RNAseq. Statistical analysis revealed fewer overlapping genes than expected by chance, supporting an evolutionary scenario where initial adaptation relies on gene expression variation, followed by slower adaptation through genetic changes within the core genome.
DOI: 10.6084/m9.figshare.23148029.v1
title: Supplementary data: Contrasting genes for short and long-term biofilm adaptation in <em>Listeria </em>

description: <em>Listeria monocytogenes</em> is a dangerous bacterium found in food that can cause severe illness and even death in humans. It has different types, some of which are more likely to infect people. Biofilms, crucial for survival and infection, hold the key to understanding transmission. To unravel the genetic basis of biofilm formation, we undertook a study employing genome-wide association studies and gene transcription profiling. We identified 273 genes associated with robust biofilm formation through GWAS and discovered differential expression in 220 genes through RNAseq. Statistical analysis revealed fewer overlapping genes than expected by chance, supporting an evolutionary scenario where initial adaptation relies on gene expression variation, followed by slower adaptation through genetic changes within the core genome.
DOI: 10.5517/ccdc.csd.cc2gfwxq
title: CCDC 2277474: Experimental Crystal Structure Determination

description: Related Article: Jonathan B. F. Vandenwijngaerden, Jianjun Huang, Charlotte Cresens, Wim Dehaen, Luc Van Meervelt, Susana Rocha, Mark Van der Auweraer, Eduard Fron|2023|Mat.Advs.|4|4571|doi:10.1039/D3MA00511A
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: 10.6084/m9.figshare.21587088.v1
title: An Empirical Analysis of Issue Templates Usage in Large-Scale Projects on GitHub

description: GitHub Issues is a widely used issue tracking tool in open-source software projects. Originally designed with broad flexibility, its lack of standardization led to incomplete issue reports, impeding software development and maintenance efficiency. To counteract this, GitHub introduced issue templates in 2016, which rapidly became popular. Our study assesses the current use and evolution of these templates in large-scale projects, and their impact on issue tracking metrics, including resolution time, number of reopens, and comments. Employing a comprehensive analysis of 350 templates and their past versions from 100 significant open-source projects, we also evaluated over 1.9 million issues for template conformity and impact. Additionally, we solicited insights from open-source software maintainers through a survey. Our findings highlight issue templates' extensive usage in 99 of the 100 surveyed large-scale projects, with a growing preference for issue forms, a more structured template variant. Projects with a template exhibited markedly reduced resolution time (374.56 days to 103.46 days) and reduced comment count (4.90 to 4.34) compared to those without. Use of issue forms further significantly decreased resolution time, the number of reopenings, and discussion extent. Thus, our research underscores issue templates' positive impact in large-scale projects, offering recommendations for improved effectiveness.
DOI: 10.5281/zenodo.8111150
title: Distribution System Environmental and Sequencing Datasets for Assessing the Impacts of Lead Corrosion Control on the Microbial Ecology and Abundance of Drinking Water Associated Pathogens in a Full-Scale Drinking Water Distribution System

description: The dataset of environmental parameters and sequence fastqs used to create figures and do analysis in the paper <strong>Assessing the Impacts of Lead Corrosion Control on the Microbial Ecology and Abundance of Drinking Water Associated Pathogens in a Full-Scale Drinking Water Distribution System </strong>submitted to Environmental Science & Technology