cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25318/2710040101-fra
title: Montant dépensé pour la formation en lien avec l'adoption de technologies de pointe, selon l'industrie et la taille de l'entreprise

description: Enquête sur les technologies de pointe, montant dépensé pour la formation en lien avec l'adoption de technologies de pointe, selon le système de classification des industries de l'Amérique du Nord (SCIAN) et la taille de l'entreprise pour le Canada et certaines provinces, en 2022.
DOI: 10.34740/kaggle/dsv/6430569
title: COVID Vaccination in World (updated daily)
DOI: 10.6084/m9.figshare.24081417
title: Raw data from the manuscript 'Morning exercise and pre-breakfast metformin interact to reduce glycaemia in people with Type 2 Diabetes: a randomized crossover trial' Pena Carrillo et al. 2023

description: In this study, nine male and nine females with type 2 diabetes undergoing metformin monotherapy (age 61±2 year, mean±SEM) completed a 16-week crossover trial including 2-week baseline recording, six weeks randomly assigned to a morning exercise (7-10am) or evening exercise (4-7pm), and a two-week wash-out period. Exercise arms consisted of 30 minutes of walking at 70% of estimated max-HR every other day. Glucose levels were measured with continuous glucose monitors and activity measured by wrist-worn monitors. Food-intake was recorded by 4-day food diaries during baseline, first and last 2 weeks of each exercise arm.There was no difference in exercise intensity, total caloric intake, or total physical activity between morning and evening arms. Acute glucose area under the curve, was lower (<i>p</i>=0.02) after acute morning exercise (180.6±16.1 mmol/L) compared to baseline (210.3±18.0 mmol/L). Acute AUC glucose was significantly lower (<i>p</i>=0.01) in participants taking metformin before breakfast (152.5±10.59 mmol/L) compared with participants taking metformin after breakfast (227.2±27.51 mmol/L) only during the morning exercise arm. During weeks 5-6 of the exercise protocol, AUC glucose was significantly lower (p=0.04) for participants taking metformin before breakfast (168.8±5.6), rather than after breakfast (224.5±21.2) only during morning exercise.
DOI: 10.6084/m9.figshare.24081417.v1
title: Raw data from the manuscript 'Morning exercise and pre-breakfast metformin interact to reduce glycaemia in people with Type 2 Diabetes: a randomized crossover trial' Pena Carrillo et al. 2023

description: In this study, nine male and nine females with type 2 diabetes undergoing metformin monotherapy (age 61±2 year, mean±SEM) completed a 16-week crossover trial including 2-week baseline recording, six weeks randomly assigned to a morning exercise (7-10am) or evening exercise (4-7pm), and a two-week wash-out period. Exercise arms consisted of 30 minutes of walking at 70% of estimated max-HR every other day. Glucose levels were measured with continuous glucose monitors and activity measured by wrist-worn monitors. Food-intake was recorded by 4-day food diaries during baseline, first and last 2 weeks of each exercise arm.There was no difference in exercise intensity, total caloric intake, or total physical activity between morning and evening arms. Acute glucose area under the curve, was lower (<i>p</i>=0.02) after acute morning exercise (180.6±16.1 mmol/L) compared to baseline (210.3±18.0 mmol/L). Acute AUC glucose was significantly lower (<i>p</i>=0.01) in participants taking metformin before breakfast (152.5±10.59 mmol/L) compared with participants taking metformin after breakfast (227.2±27.51 mmol/L) only during the morning exercise arm. During weeks 5-6 of the exercise protocol, AUC glucose was significantly lower (p=0.04) for participants taking metformin before breakfast (168.8±5.6), rather than after breakfast (224.5±21.2) only during morning exercise.
DOI: 10.5281/zenodo.7872534
title: Kingfisher genomes

description: Genomes associated with Communications Biology paper.
DOI: 10.5281/zenodo.7872533
title: Kingfisher genomes

description: Genomes associated with Communications Biology paper.
DOI: 10.57745/9iw3pu
title: Review_Host Plants of Popillia japonica.tab

description: :unav
DOI: 10.57745/5zpgys
title: Host plants_Popillia japonica_RDG_2023_V2.tab

description: :unav
DOI: 10.57745/8us8hj
title: Host Plants of Popillia japonica_RDG_2023_V2.docx

description: :unav
DOI: 10.57745/ik5m6w
title: Host Plants of Popillia japonica.docx

description: :unav
DOI: 10.25345/c52z13088
title: MassIVE MSV000092831 - Pseudomonas savastanoi pv. phaseolicola R5 treated with genistein (metabolomics)
title: P. savastanoi pv. phaseolicola isolate R5 was cultured in 10 mL Luria broth with 400 uM genistein or without (but with 50 uL DMSO) at 28 C at 200 rpm on a shaking platform. Replicate R5 cultures of each treatment were centrifuged at 5,000 x g for 10 min., washed once in 1 mL phosphate buffered saline, centrifuged at 5,000 x g for 10 min., resuspended in 1 mL of 1:1:1:1 acetone/acetonitrile/methanol/water and 1,2500 pmol prednisone, and pulverized in the bead mill as before. Two matrix blank samples were prepared the same way starting with 10 mL Luria broth (without R5 and without genistein). The milled extracts were centrifuged for 20 minutes at 12,000 x g. The supernatants were transferred to fresh tubes and centrifuged again. The supernatants were transferred to glass vials and dried under vacuum. The residues were resuspended in 115 uL 50% methanol/0.1% formic acid. Fifteen uL of each sample was pooled to create a quality control (QC) sample. Five uL of the samples were separated on a 150 x 2.1 mm Hypersil GOLD VANQUISH HPLC column with 1.9 um particles (Thermo Fisher Scientific) coupled to a Vanquish HPLC pump (Thermo Fisher Scientific) controlling a 10-minute linear gradient from 0% to 95% acetonitrile and 0.1% formic acid at a flow rate of 0.2 mL per minute. Eluent was electrosprayed at 3.5 kV positive polarity into an Exploris 240 mass spectrometer (Thermo Fisher Scientific) using an internal mass calibrant. Sheath gas was 35, auxiliary gas was 7, and sweep gas was 1 (arbitrary units). The ion transfer tube temperature was 325 C and the vaporizer temperature was 275 C. Advanced peak determination, mild trapping, and internal mass calibration was enabled. Default charge state was 1 and the expected peak width was 6 sec. AcquireX software was used to create a background ion exclusion list from the matrix blank sample and an inclusion ion list from the QC sample. Three subsequent injections of the QC were performed to generate MS2 spectra. After each QC injection, the resolved ions were appended to the exclusion list. Survey scans were recorded in the Orbitrap at 60,000 resolution over a mass range of 70-800 m/z. The RF lens was 70%. Monoisotopic precursor selection was enabled, the minimum intensity was 5,000, and charge states were filtered to 1. Precursors selected within a 1.0 Da isolation window were fragmented by high energy collision-induced dissociation (30%, 50%, 70% normalized stepped collision energy), and fragment ions were resolved in the Orbitrap at 30,000 resolution. Subsequently, all test samples were analyzed alongside QC and matrix blank samples in the following order: Matrix blank 1, QC 1, sample replicate set 1, Blank 2, QC 2, sample replicate set 2, etc. Survey scans were recorded in the Orbitrap at 120,000 resolution over a mass range of 70-800 m/z. The RF lens was 70%. The samples also were analyzed in negative ion mode at -2,500 V but with the same other settings.
DOI: 10.5281/zenodo.7086419
title: Annual Article Processing Charges (APCs) and number of gold and hybrid open access articles in Web of Science indexed journals published by Elsevier, Sage, Springer-Nature, Taylor & Francis and Wiley 2015-2018

description: <strong>Dataset of annual Article Processing Charges (APCs) for 6,252 journals from 2015 to 2018. </strong>The dataset contains annual APCs for journals indexed in the Web of Science (WoS) and published by the oligopoly of academic publishers (Elsevier, Sage, Springer-Nature, Taylor & Francis, Wiley). It also includes an estimate of the total APCs paid by the academic community based on the number of gold and hybrid articles published between 2015 and 2018. The dataset was created using publication data from WoS, OA status from Unpaywall and annual APC prices from open datasets (Matthias, 2020; Morrison, 2021) and historical fees retrieved via the Internet Archive Wayback Machine. Detailed methods and findings are reported in the following journal article Butler, L.-A., Matthias, L., Simard, M.-A., Mongeon, P., & Haustein, S. (2023). The Oligopoly's Shift to Open Access. How the Big Five Academic Publishers Profit from Article Processing Charges. <em>Quantitative Science Studies</em>. Preprint: https://doi.org/10.5281/zenodo.8322555 <strong>Description of included files (v1):</strong> <em>APCs.csv: </em>contains the annual APCs for gold and hybrid OA journals indexed in Web of Science published by the oligopoly of academic publishers (Elsevier, Sage, Springer-Nature, Taylor & Francis, Wiley) between 2015 and 2018 including the total estimate of APCs paid per journal per year. It contains APC data for 18,846 journal-year-OA status combinations. <em>countries.csv</em>: contains the fractionalized number of annual gold and hybrid OA articles by oligopoly publishers between 2015 and 2018 and the total estimate of fractionalized APCs paid per country per journal per year. <em>oecd.csv</em>: contains the fractionalized number of annual gold and hybrid OA articles by oligopoly publishers between 2015 and 2018 and the total estimate of fractionalized APCs per discipline per journal per year. <em>ReadMe.csv</em>: contains a description of the variables used in <em>APCs.csv</em>, <em>countries.csv</em> and <em>oecd.csv</em>.
DOI: 10.5519/qd.mize9z0j
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (75 records)
DOI: 10.5281/zenodo.8252477
title: NO2, O3, PM10 and PM2.5 concentrations - Daily geographical aggregates at NUTS3 level from CAMS European Air Quality Re-analyses.

description: This dataset offers daily aggregated measurements of air pollutants – NO2, O3, PM10, and PM2.5 – across distinct NUTS3 regions in continetal Europe. The temporal coverage spans from January 1, 2013, to December 31, 2022, providing a comprehensive temporal context for analyzing long-term air quality dynamics. Each daily entry comprises key statistical descriptors, encompassing mean, maximum, minimum, and standard deviation values of pollutant concentrations specific to each NUTS3 area. Additionally, for O3, the dataset includes an eight-hour rolling mean daily maximum. Spatial reference is established via shapefiles (EPSG:4326) sourced from Eurostat's official repository (https://ec.europa.eu/eurostat/web/gisco/geodata/reference-data/administrative-units-statistical-units/nuts). These shapefiles link the air quality data to precise NUTS3 regions through unique identifiers. The concentration data spanning from 2018 to 2022 originate from the European Air Quality Reanalyses dataset of the Atmosphere Data Store (ADS), an initiative by the Copernicus Atmosphere Monitoring Service (CAMS). Accessible via https://ads.atmosphere.copernicus.eu/cdsapp#!/dataset/cams-europe-air-quality-reanalyses?tab=doc, this dataset offers a robust foundation for assessing air quality. For the years 2013 to 2017, data were previously obtained from a former download platform for the same dataset. Important: in future all data will be migrated to the Atmosphere Data Store (ADS) platform. The native resolution of the CAMS data is 0.1° x 0.1° spatially and hourly temporally. To enhance spatial accuracy, the spatial resolution was virtually increased by a factor of 5 using bilinear interpolation, resulting in a refined grid. The daily mean concentrations were subsequently computed for this augmented grid. Aggregated statistics were derived for each NUTS3 polygon, employing all grid cells intersecting with the polygons. The computation was based on the proportion of cell area included within the respective polygons. This dataset constitutes a valuable resource for conducting ecologically designed epidemiological studies, as it facilitates the exploration of potential associations between air quality and health trends across broad geographical areas.
description: Generated using Copernicus Atmosphere Monitoring Service Information 2013-2022
description: {"references": ["Marecal, V., et al. (2015). \"A regional air quality forecasting system over Europe: the MACC-II daily ensemble production.\" Geoscientific Model Development 8(9): 2777-2813."]}
DOI: 10.5281/zenodo.8252476
title: NO2, O3, PM10 and PM2.5 concentrations - Daily geographical aggregates at NUTS3 level from CAMS European Air Quality Re-analyses.

description: This dataset offers daily aggregated measurements of air pollutants – NO2, O3, PM10, and PM2.5 – across distinct NUTS3 regions in continetal Europe. The temporal coverage spans from January 1, 2013, to December 31, 2022, providing a comprehensive temporal context for analyzing long-term air quality dynamics. Each daily entry comprises key statistical descriptors, encompassing mean, maximum, minimum, and standard deviation values of pollutant concentrations specific to each NUTS3 area. Additionally, for O3, the dataset includes an eight-hour rolling mean daily maximum. Spatial reference is established via shapefiles (EPSG:4326) sourced from Eurostat's official repository (https://ec.europa.eu/eurostat/web/gisco/geodata/reference-data/administrative-units-statistical-units/nuts). These shapefiles link the air quality data to precise NUTS3 regions through unique identifiers. The concentration data spanning from 2018 to 2022 originate from the European Air Quality Reanalyses dataset of the Atmosphere Data Store (ADS), an initiative by the Copernicus Atmosphere Monitoring Service (CAMS). Accessible via https://ads.atmosphere.copernicus.eu/cdsapp#!/dataset/cams-europe-air-quality-reanalyses?tab=doc, this dataset offers a robust foundation for assessing air quality. For the years 2013 to 2017, data were previously obtained from a former download platform for the same dataset. Important: in future all data will be migrated to the Atmosphere Data Store (ADS) platform. The native resolution of the CAMS data is 0.1° x 0.1° spatially and hourly temporally. To enhance spatial accuracy, the spatial resolution was virtually increased by a factor of 5 using bilinear interpolation, resulting in a refined grid. The daily mean concentrations were subsequently computed for this augmented grid. Aggregated statistics were derived for each NUTS3 polygon, employing all grid cells intersecting with the polygons. The computation was based on the proportion of cell area included within the respective polygons. This dataset constitutes a valuable resource for conducting ecologically designed epidemiological studies, as it facilitates the exploration of potential associations between air quality and health trends across broad geographical areas.
description: Generated using Copernicus Atmosphere Monitoring Service Information 2013-2022
description: {"references": ["Marecal, V., et al. (2015). \"A regional air quality forecasting system over Europe: the MACC-II daily ensemble production.\" Geoscientific Model Development 8(9): 2777-2813."]}
DOI: 10.6084/m9.figshare.24093636
title: Gene expression data from treadmill training study in aged mice

description: Here we characterized the impact of exercise training on skeletal muscle inflammatory and metabolic profiles, cellular remodeling and function, together with femoral artery reactivity prior to (baseline) and 4 days following recovery (Reload 4) from hindlimb unloading in aged male mice. We hypothesized that 12-weeks of treadmill training in aged male mice would improve skeletal muscle cellular remodeling at baseline and during recovery from disuse resulting in improved muscle regrowth. Physical performance, ex vivo muscle and vascular function, tissue and organ mass, hindlimb muscle cellular remodeling (macrophage, satellite cell, capillary, myofiber size, fibrosis) and proteolytic, inflammatory and metabolic muscle transcripts were evaluated in aged exercise trained and untrained mice. Data within this excel sheet contains the gene expression data (fold change) identified in from Figure 8.
DOI: 10.6084/m9.figshare.24093636.v1
title: Gene expression data from treadmill training study in aged mice

description: Here we characterized the impact of exercise training on skeletal muscle inflammatory and metabolic profiles, cellular remodeling and function, together with femoral artery reactivity prior to (baseline) and 4 days following recovery (Reload 4) from hindlimb unloading in aged male mice. We hypothesized that 12-weeks of treadmill training in aged male mice would improve skeletal muscle cellular remodeling at baseline and during recovery from disuse resulting in improved muscle regrowth. Physical performance, ex vivo muscle and vascular function, tissue and organ mass, hindlimb muscle cellular remodeling (macrophage, satellite cell, capillary, myofiber size, fibrosis) and proteolytic, inflammatory and metabolic muscle transcripts were evaluated in aged exercise trained and untrained mice. Data within this excel sheet contains the gene expression data (fold change) identified in from Figure 8.
DOI: 10.5281/zenodo.8195625
title: Data file: (Non-)disclosure of lifetime sexual violence in maternity care: Disclosure rate, associated characteristics and reasons for non-disclosure

description: This dataset contains the data used for the study: (Non-)disclosure of lifetime sexual violence in maternity care: Disclosure rate, associated characteristics and reasons for non-disclosure.
DOI: 10.5281/zenodo.8195624
title: Data file: (Non-)disclosure of lifetime sexual violence in maternity care: Disclosure rate, associated characteristics and reasons for non-disclosure

description: This dataset contains the data used for the study: (Non-)disclosure of lifetime sexual violence in maternity care: Disclosure rate, associated characteristics and reasons for non-disclosure.
DOI: 10.34740/kaggle/dsv/6430626
title: USA_S&P500_Fundamentals_2004_2023
DOI: 10.5281/zenodo.8325537
title: Datasets from 'Phonon Signatures in Photon Correlations'

description: Datasets associated with the PRL publication 'Phonon Signatures in Photon Correlations'. The data for figures 1-4 and 4-7 of the supplemental material are also supplied. The data is a table of times (t and tau for respective figures) and correlation functions. This data was used for plotting the figures which are in the manuscript.
DOI: 10.5281/zenodo.8325580
title: Table for original data on clinical characteristics of the two cohorts.

description: This table includes original data on clinical characteristics of the two cohorts.
DOI: 10.5281/zenodo.8325579
title: Table for original data on clinical characteristics of the two cohorts.

description: This table includes original data on clinical characteristics of the two cohorts.
DOI: 10.5281/zenodo.8325592
title: ggCaller benchmarking simulation results

description: Results from ggCaller, Panaroo, PEPPAN and Roary analysis of simulated datasets described in Chapter 3 of the PhD Thesis "Graph-based and alignment-free analysis of bacterial pangenomes."
DOI: 10.5281/zenodo.8325591
title: ggCaller benchmarking simulation results

description: Results from ggCaller, Panaroo, PEPPAN and Roary analysis of simulated datasets described in Chapter 3 of the PhD Thesis "Graph-based and alignment-free analysis of bacterial pangenomes."
DOI: 10.5517/ccdc.csd.cc2cxrnq
title: CCDC 2202384: Experimental Crystal Structure Determination

description: Related Article: Qi Li, Simin Shen, Lijuan Liang, Kun Huang, Dasheng Zheng, Dabin Qin, Bin Zhao|2023|Dyes Pigm.|219|111639|doi:10.1016/j.dyepig.2023.111639
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.cc2cxrpr
title: CCDC 2202385: Experimental Crystal Structure Determination

description: Related Article: Qi Li, Simin Shen, Lijuan Liang, Kun Huang, Dasheng Zheng, Dabin Qin, Bin Zhao|2023|Dyes Pigm.|219|111639|doi:10.1016/j.dyepig.2023.111639
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.cc2gfmzj
title: CCDC 2277228: Experimental Crystal Structure Determination

description: Related Article: Ling-Qi Du, Zhao-Xu Chen, Qiao-Chang Wei, Zhi-Lin Chen, Yan Yang|2023|Inorg.Chem.Commun.|156|111238|doi:10.1016/j.inoche.2023.111238
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.cc2gfn0l
title: CCDC 2277229: Experimental Crystal Structure Determination

description: Related Article: Ling-Qi Du, Zhao-Xu Chen, Qiao-Chang Wei, Zhi-Lin Chen, Yan Yang|2023|Inorg.Chem.Commun.|156|111238|doi:10.1016/j.inoche.2023.111238
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.cc2gfn1m
title: CCDC 2277230: Experimental Crystal Structure Determination

description: Related Article: Ling-Qi Du, Zhao-Xu Chen, Qiao-Chang Wei, Zhi-Lin Chen, Yan Yang|2023|Inorg.Chem.Commun.|156|111238|doi:10.1016/j.inoche.2023.111238
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.cc2gfn2n
title: CCDC 2277231: Experimental Crystal Structure Determination

description: Related Article: Ling-Qi Du, Zhao-Xu Chen, Qiao-Chang Wei, Zhi-Lin Chen, Yan Yang|2023|Inorg.Chem.Commun.|156|111238|doi:10.1016/j.inoche.2023.111238
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.cc2gfn3p
title: CCDC 2277232: Experimental Crystal Structure Determination

description: Related Article: Ling-Qi Du, Zhao-Xu Chen, Qiao-Chang Wei, Zhi-Lin Chen, Yan Yang|2023|Inorg.Chem.Commun.|156|111238|doi:10.1016/j.inoche.2023.111238
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.