cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.23791572
title: Raw data for "Comparison of the effects between catalase and superoxide dismutase on regulating macrophage inflammatory response and protecting osteogenic function of periodontal ligament cells"

description: Background: Reactive oxygen species (ROS) have been confirmed closely associated with the pathological process of periodontitis, but the specific roles played by different ROS types are still to be investigated. Catalase (CAT) and Superoxide dismutase (SOD) specifically eliminate hydrogen peroxide (H2O2) and superoxide anion (O2•-), respectively. We for the first time compare the effects and mechanisms of CAT and SOD in protecting periodontal ligament cells (PDLCs) against oxidative damage, reducing the expression of macrophage inflammatory factors, and preserving the osteogenic differentiation function of PDLCs by modulating the inflammatory environment.Methods: CAT or SOD in combination with lipopolysaccharide (LPS) were added to the culture medium of RAW 264.7 and PDLCs. The intracellular ROS level, lipid peroxidation and DNA damage were observed by confocal microscope. Inflammation levels were assessed by real-time quantitative polymerase chain reaction (RT-qPCR) and western blot. A co-culture system of macrophages and PDLCs was established, and the osteogenic differentiation of PDLCs was evaluated by alkaline phosphatase staining, alizarin red S staining, RT-qPCR and Western blot. Finally, differentially expressed genes (DEGs) in CAT and SOD were detected by RNA sequencing and the biological functions and signaling pathways involved were analyzed.Results: CAT or SOD can effectively inhibit intracellular ROS levels, lipid peroxidation and DNA damage, as well as increase the levels of antioxidative molecules and decrease the levels of inflammatory factors. SOD increased the levels of antioxidative molecules more strongly, while CAT reduced inflammatory factors more effectively. The RNA sequencing results indicate that CAT exhibits stronger inhibitory effects on inflammation-related signaling pathways, which could account for the above-mentioned differences.Conclusions: In this study, we observed differential antioxidant and anti-inflammatory effects between CAT and SOD, which may be associated with CAT's better inhibition of the activation of inflammatory pathways. Our study will provide scientific references for the future development of highly selective ROS- scavenging antioxidant drugs.
DOI: 10.6084/m9.figshare.23791572.v1
title: Raw data for "Comparison of the effects between catalase and superoxide dismutase on regulating macrophage inflammatory response and protecting osteogenic function of periodontal ligament cells"

description: Background: Reactive oxygen species (ROS) have been confirmed closely associated with the pathological process of periodontitis, but the specific roles played by different ROS types are still to be investigated. Catalase (CAT) and Superoxide dismutase (SOD) specifically eliminate hydrogen peroxide (H2O2) and superoxide anion (O2•-), respectively. We for the first time compare the effects and mechanisms of CAT and SOD in protecting periodontal ligament cells (PDLCs) against oxidative damage, reducing the expression of macrophage inflammatory factors, and preserving the osteogenic differentiation function of PDLCs by modulating the inflammatory environment.Methods: CAT or SOD in combination with lipopolysaccharide (LPS) were added to the culture medium of RAW 264.7 and PDLCs. The intracellular ROS level, lipid peroxidation and DNA damage were observed by confocal microscope. Inflammation levels were assessed by real-time quantitative polymerase chain reaction (RT-qPCR) and western blot. A co-culture system of macrophages and PDLCs was established, and the osteogenic differentiation of PDLCs was evaluated by alkaline phosphatase staining, alizarin red S staining, RT-qPCR and Western blot. Finally, differentially expressed genes (DEGs) in CAT and SOD were detected by RNA sequencing and the biological functions and signaling pathways involved were analyzed.Results: CAT or SOD can effectively inhibit intracellular ROS levels, lipid peroxidation and DNA damage, as well as increase the levels of antioxidative molecules and decrease the levels of inflammatory factors. SOD increased the levels of antioxidative molecules more strongly, while CAT reduced inflammatory factors more effectively. The RNA sequencing results indicate that CAT exhibits stronger inhibitory effects on inflammation-related signaling pathways, which could account for the above-mentioned differences.Conclusions: In this study, we observed differential antioxidant and anti-inflammatory effects between CAT and SOD, which may be associated with CAT's better inhibition of the activation of inflammatory pathways. Our study will provide scientific references for the future development of highly selective ROS- scavenging antioxidant drugs.
DOI: 10.5281/zenodo.8189608
title: GIS data for Hammarmossen, Sweden

description: GIS data in geopackage format for manuscript submitted to Ecosystems, entitled "Six decades of pool dynamics on a concentric-patterned raised bog". The file contains 8 layers with associated metadata and styling.
description: n/a
DOI: 10.5281/zenodo.8189607
title: GIS data for Hammarmossen, Sweden

description: GIS data in geopackage format for manuscript submitted to Ecosystems, entitled "Six decades of pool dynamics on a concentric-patterned raised bog". The file contains 8 layers with associated metadata and styling.
description: n/a
DOI: 10.5281/zenodo.8189601
title: Assessment of the quality of water for human consumption in the Laguna Verde area of Valparaiso in Central Chile (DATA)

description: Data set paper Assessment of the quality of water for human consumption in the Laguna Verde area of Valparaiso in Central Chile .
DOI: 10.5281/zenodo.8189600
title: Assessment of the quality of water for human consumption in the Laguna Verde area of Valparaiso in Central Chile (DATA)

description: Data set paper Assessment of the quality of water for human consumption in the Laguna Verde area of Valparaiso in Central Chile .
DOI: 10.5258/soton/d2562
title: Dataset to support the article: Assessing socket fit effects on pressure and shear at a transtibial residuum/socket interface

description: Article to be published in Applied Bionics and Biomechanics. This dataset contains results presented in the journal article 'Assessing socket fit effects on pressure and shear at a transtibial residuum/socket interface' submitted to 'Applied Bionics and Biomechanics' journal by Kirstie M. Devin, Jinghua Tang, David Moser and Liudi Jiang, in .xlsx format. The excel file contains all experimental data used for generating figure 3 to figure 5. Sheets have been named accordingly. Dataset is embargoed until 1/9/23 thereafter available upon request under a CC BY-NC-ND 4.0 licence. Please complete the request form attached
DOI: 10.5281/zenodo.8189626
title: Shyness and willingness to communicate: Levels, correlations, and perspectives of EFL learners

description: The file involves the quantitative data obtained after administering McCroskey and Richmond's (1991) shyness and WTC scales.
DOI: 10.5281/zenodo.8189627
title: Shyness and willingness to communicate: Levels, correlations, and perspectives of EFL learners

description: The file involves the quantitative data obtained after administering McCroskey and Richmond's (1991) shyness and WTC scales.
DOI: 10.6084/m9.figshare.23791710
title: X Chromosome White British_Database Macro v1.0.xlsm

description: X-STR database for White British population
DOI: 10.6084/m9.figshare.23791710.v1
title: X Chromosome White British_Database Macro v1.0.xlsm

description: X-STR database for White British population
DOI: 10.34740/kaggle/dsv/6204569
title: COVID Vaccination in World (updated daily)
DOI: 10.48420/21931770.v4
title: TPI UK ITL1 Scorecards

description: This dataset includes scorecards for all 12 ITL1 regions in the United Kingdom. These scorecards indicate for each ITL1 region how well the region is peforming as compared to the median of all ITL1 regions in the UK, for a broad set of indicators. These indicators are considered to be drivers of productivity and are classified according to five broad categories: Business performance & characteristics; Skills & training; Policy & institutions; Health & wellbeing; Investment, infrastructure & connectivity. The sources and methodology of the indicators, and their use in the scorecards is included, as well as a brief overview of this project.
DOI: 10.5281/zenodo.7944967
title: A metadata-based approach for research discipline prediction using machine learning techniques and distance metrics

description: The dataset is based on the paper: Hoang-Son Pham, Hanne Poelmans and Amr Ali-Eldin ‘’A metadata-based approach for research discipline prediction using machine learning techniques and distance metrics’’, IEEE Access (2023). The dataset includes: 1. a list of project metadata extracted from FRIS portal 2. a list of VODS disciplines 3. a distance matrix * Kindly refer to our paper for more details on the dataset. https://ieeexplore.ieee.org/document/10156853
DOI: 10.5281/zenodo.7944966
title: A metadata-based approach for research discipline prediction using machine learning techniques and distance metrics

description: The dataset is based on the paper: Hoang-Son Pham, Hanne Poelmans and Amr Ali-Eldin ‘’A metadata-based approach for research discipline prediction using machine learning techniques and distance metrics’’, IEEE Access (2023). The dataset includes: 1. a list of project metadata extracted from FRIS portal 2. a list of VODS disciplines 3. a distance matrix * Kindly refer to our paper for more details on the dataset. https://ieeexplore.ieee.org/document/10156853
DOI: 10.5281/zenodo.8188270
title: Data repository of the paper "Quantum-noise-limited optical neural networks operating at a few quanta per activation"

description: This data repository includes the requisite data and code for deriving the primary results from the paper, "Quantum-noise-limited optical neural networks operating at a few quanta per activation". The repository is structured to provide everything needed to reproduce the figures included in the main manuscript, along with the source code for training the neural network models and the collected experimental data mentioned in the paper. The code in this repository is primarily intended for reproducing the results discussed in the paper. Those interested in developing their own applications may refer to our Github repository: https://github.com/mcmahon-lab/Single-Photon-Detection-Neural-Networks. <strong>Where to Start</strong> The directory 'main_figures' includes Jupyter notebooks to generate each panel in Figure 3 and Figure 4 in the main text, using the data from the directory 'results', which can be generated by notebooks in the directory 'test'. The simulations, experiments, and figure generation were all conducted in Python. As certain parts of the code require specific versions of Python packages, the necessary packages are listed in the 'requirements.txt' file. For more information, please refer to 'README.txt'.
DOI: 10.5281/zenodo.8188269
title: Data repository of the paper "Quantum-noise-limited optical neural networks operating at a few quanta per activation"

description: This data repository includes the requisite data and code for deriving the primary results from the paper, "Quantum-noise-limited optical neural networks operating at a few quanta per activation". The repository is structured to provide everything needed to reproduce the figures included in the main manuscript, along with the source code for training the neural network models and the collected experimental data mentioned in the paper. The code in this repository is primarily intended for reproducing the results discussed in the paper. Those interested in developing their own applications may refer to our Github repository: https://github.com/mcmahon-lab/Single-Photon-Detection-Neural-Networks. <strong>Where to Start</strong> The directory 'main_figures' includes Jupyter notebooks to generate each panel in Figure 3 and Figure 4 in the main text, using the data from the directory 'results', which can be generated by notebooks in the directory 'test'. The simulations, experiments, and figure generation were all conducted in Python. As certain parts of the code require specific versions of Python packages, the necessary packages are listed in the 'requirements.txt' file. For more information, please refer to 'README.txt'.
DOI: 10.5258/soton/d2550
title: Dataset supporting the publication "High efficiency reflector-less dual-level silicon photonic grating coupler"

description: Dataset supporting the publication "Highly Efficient Reflector-Less Dual-Level Grating Couplers for Silicon Nitride Photonics" by V Vitali, C Lacava, T Domínguez Bucio, F Y. Gardes & P Petropoulos This dataset contains: data_figures.xlsx: this file is an excel file with different tabs. In each tab it is possible to find the data that have been used to generate each plot of the article, with the corresponding "X axis" data, "Y axis" data and, if present, "Z axis" data for contour plots. Each tab is named accordingly to the respective figure in the article.
DOI: 10.20393/ea1b5bdf-a6b1-48fe-b0f7-67a1777fea94
title: CoClime - Probability of phytoplankton (Dinophysis acuminata) presence, Southwest Ireland - present time prediction (1997 - 2016)

description: This is the output of GBM (Gradient Boosting Model) analyses of D. acuminata presence and absnece data done by MI OCIS and CoCliME project. This output dataset shows prediction of probability of D. acuminata presence in present time (1997 - 2016) in SW Ireland. The analyses was performed in R 3.6.3, with the packages tidyverse 1.3.0 for data handling and visualisation, and xgboost 1.2.0.1 for boosted regression analyses. The dataset used for analyses is available on MI data catalogue (http://data.marine.ie/geonetwork/srv/eng/catalog.search#/metadata/ie.marine.data:dataset.4445) and the dataset used for prediction is requested to be included in MI data catalogue ([20]. CDF-t Climate run (Climate_run_corr.rds) in CoCliME model SOP). This dataset is used to visualise the prediction on R Shiny application for present period (https://marine-institute-ireland.shinyapps.io/D_acuminata_probability/). This dataset is used for displaying present time prediction of D. acuminata probability of presence on the Shiny app.
DOI: 10.20393/8d380b4b-de9d-4783-9629-f3d75fe57c2e
title: CoClime - Abundance of phytoplankton (Karenia mikimotoi), Southwest Ireland - future prediction (2017 - 2035)

description: This is the output of GBM (Gradient Boosting Model) analyses of K. mikimotoi, abundance data done by MI OCIS and CoCliME project. This output dataset shows abundance of K. mikimotoi in present time (2017 - 2035) in SW Ireland. The analyses was performed in R 3.6.3, with the packages tidyverse 1.3.0 for data handling and visualisation, and xgboost 1.2.0.1 for boosted regression analyses. The dataset used for analyses is available on MI data catalogue (http://data.marine.ie/geonetwork/srv/eng/catalog.search#/metadata/ie.marine.data:dataset.4445) and the dataset used for prediction is requested to be included in MI data catalogue ([20]. CDF-t Climate run (Climate_run_corr.rds) in CoCliME model SOP). This dataset is used to visualise the prediction on R Shiny application for present period (https://marine-institute-ireland.shinyapps.io/K_mikimotoi_abundance/). This dataset is used for displaying present time prediction of K. mikimotoi abundance on the Shiny app.
DOI: 10.6073/pasta/b78161335e3edbd2393378b197735d85
title: Pre and post-fire composition, density, basal area, and biomass for 212 sites that burned between 2004 and 2015 in Interior Alaska

description: We collated data on pre-fire and post-fire stand composition from 212 sites across interior Alaska that burned between the years 2004 and 2014.
DOI: 10.20393/50cf4389-f5ec-4a97-96d5-abba7c4ef4d0
title: CoClime - Abundance of phytoplankton (“Pseudo-nitzschia seriata” complex), Southwest Ireland - future prediction (2017 - 2035)

description: This is the output of GBM (Gradient Boosting Model) analyses of P.seriata abundance data done by MI OCIS and CoCliME project. This output dataset shows abundance of P.seriata in the future (2017 - 2035) in SW Ireland. The analyses was performed in R 3.6.3, with the packages tidyverse 1.3.0 for data handling and visualisation, and xgboost 1.2.0.1 for boosted regression analyses. The dataset used for analyses is available on MI data catalogue (http://data.marine.ie/geonetwork/srv/eng/catalog.search#/metadata/ie.marine.data:dataset.4445) and the dataset used for prediction is requested to be included in MI data catalogue ([20]. CDF-t Climate run (Climate_run_corr.rds) in CoCliME model SOP). This dataset is used to visualise the prediction on R Shiny application for present period (https://marine-institute-ireland.shinyapps.io/P_seriata_abundance/). This dataset is used for displaying present time prediction of P.seriata abundance on the Shiny app.
DOI: 10.20393/3be19458-811a-4ac2-a5fb-671560488c42
title: CoClime - Abundance of phytoplankton (Dinophysis acuminata), Southwest Ireland - present time prediction (1997 - 2016)

description: This is the output of GBM (Gradient Boosting Model) analyses of D. acuminata abundance data done by MI OCIS and CoCliME project. This output dataset shows abundance of D. acuminata in present time (1997 - 2016) in SW Ireland. The analyses was performed in R 3.6.3, with the packages tidyverse 1.3.0 for data handling and visualisation, and xgboost 1.2.0.1 for boosted regression analyses. The dataset used for analyses is available on MI data catalogue (http://data.marine.ie/geonetwork/srv/eng/catalog.search#/metadata/ie.marine.data:dataset.4445) and the dataset used for prediction is requested to be included in MI data catalogue ([20]. CDF-t Climate run (Climate_run_corr.rds) in CoCliME model SOP). This dataset is used to visualise the prediction on R Shiny application for present period (https://marine-institute-ireland.shinyapps.io/D_acuminata_abundance/). This dataset is used for displaying present time prediction of D. acuminata abundance on the Shiny app.
DOI: 10.20393/b3bb07be-38a3-4524-918a-6c943629839e
title: CoClime - Abundance of phytoplankton (“Pseudo-nitzschia seriata” complex), Southwest Ireland - present time prediction (1997 - 2016)

description: This is the output of GBM (Gradient Boosting Model) analyses of P.seriata, abundance data done by MI OCIS and CoCliME project. This output dataset shows abundance of P.seriata in present time (1997 - 2016) in SW Ireland. The analyses was performed in R 3.6.3, with the packages tidyverse 1.3.0 for data handling and visualisation, and xgboost 1.2.0.1 for boosted regression analyses. The dataset used for analyses is available on MI data catalogue (http://data.marine.ie/geonetwork/srv/eng/catalog.search#/metadata/ie.marine.data:dataset.4445) and the dataset used for prediction is requested to be included in MI data catalogue ([20]. CDF-t Climate run (Climate_run_corr.rds) in CoCliME model SOP). This dataset is used to visualise the prediction on R Shiny application for present period (https://marine-institute-ireland.shinyapps.io/P_seriata_abundance/). This dataset is used for displaying present time prediction of P.seriata abundance on the Shiny app.
DOI: 10.20393/b8f137b5-31b1-4e69-b3da-77898762193b
title: CoClime - Probability of phytoplankton (Alexandrium species) presence, Southwest Ireland - present time prediction (1997 - 2016)

description: This is the output of GBM (Gradient Boosting Model) analyses of Alexandrium spp. presence and absnece data done by MI OCIS and CoCliME project. This output dataset shows prediction of probability of Alexandrium spp. presence in present time (1997 - 2016) in SW Ireland. The analyses was performed in R 3.6.3, with the packages tidyverse 1.3.0 for data handling and visualisation, and xgboost 1.2.0.1 for boosted regression analyses. The dataset used for analyses is available on MI data catalogue (http://data.marine.ie/geonetwork/srv/eng/catalog.search#/metadata/ie.marine.data:dataset.4445) and the dataset used for prediction is requested to be included in MI data catalogue ([20]. CDF-t Climate run (Climate_run_corr.rds) in CoCliME model SOP). This dataset is used to visualise the prediction on R Shiny application for present period (https://marine-institute-ireland.shinyapps.io/Alexandrium_probability/ ). This dataset is used for displaying present time prediction of Alexandrium spp. probability of presence on the Shiny app.
DOI: 10.5281/zenodo.7948227
title: PSR irradiance and AOD data aquired during MAPP project

description: Aerosol optical depth (AOD) and solar irradiance data acquired in the frame of the JRP project MAPP, Metrology for Aerosol Optical Properties 19ENV04 with the Precision SpectroRadiometer PSR-009 (Gröbner and Kouremeti 2019). The calibrations of the PSR-009 have been performed at PMOD/WRC while the straylight correction has been measured at PMOD/WRC and PTB. The Top-of-Atmosphere solar spectrum convolved with the slit functions of the PSR, used for the AOD retrieval is stated in the field <em>PSR.FN_ETS</em> · PSR_009_QASUMEFTS_env03_cosi_kittpeak_thullier_LSF_SLITextFillLSF.mat: QUASUMEFTS (Gröbner, Kröger et al. 2017) (300-450 nm) and ATLAS (Thuillier, Hersé et al. 2003)(450 nm -1030 nm) · PSR_009_QASUMEFTS_TSIS_HSRSall_LSF_SLITextFillLSF.mat: QUASUMEFTS (Gröbner, Kröger et al. 2017) (300-450 nm) and TSIS-1 (Coddington, Richard et al. 2021) (450 nm -1030 nm) · PSR_009_TSIS_HSRSall_LSF_SLITextFillLSF.mat: TSIS-1 (Coddington, Richard et al. 2021) <strong>References </strong> Coddington, O. M., E. C. Richard, D. Harber, P. Pilewskie, T. N. Woods, K. Chance, X. Liu and K. Sun (2021). "The TSIS-1 Hybrid Solar Reference Spectrum." Geophysical Research Letters <strong>48</strong>(12): e2020GL091709. Gröbner, J. and N. Kouremeti (2019). "The Precision Solar Spectroradiometer (PSR) for direct solar irradiance measurements." Solar Energy <strong>185</strong>: 199-210. Gröbner, J., I. Kröger, L. Egli, G. Hülsen, S. Riechelmann and P. Sperfeld (2017). "The high-resolution extraterrestrial solar spectrum (QASUMEFTS) determined from ground-based solar irradiance measurements." Atmos. Meas. Tech. <strong>10</strong>(9): 3375-3383. Thuillier, G., M. Hersé, D. Labs, T. Foujols, W. Peetermans, D. Gillotay, P. C. Simon and H. Mandel (2003). "The Solar Spectral Irradiance from 200 to 2400 nm as Measured by the SOLSPEC Spectrometer from the Atlas and Eureca Missions." Solar Physics <strong>214</strong>(1): 1-22. <strong>Acknowledgments</strong> This data was obtained within the joint research project EMPIR 19ENV04 MAPP “Metrology for aerosol optical properties” which has been supported by the European Metrology Program for Innovation and Research (EMPIR) . The EMPIR is jointly funded by the EMPIR participating countries within EURAMET and the European Union.
description: {"references": ["Gr\u00f6bner J and Kouremeti N 2019 The Precision Solar Spectroradiometer (PSR) for direct solar irradiance measurements Solar Energy 185 199-210 10.1016/j.solener.2019.04.060"]}