cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.57760/sciencedb.08942
title: Data from: Designing a Multi-epitope Subunit Vaccine against Orf Virus Using Molecular Docking and Molecular Dynamics
title: Data from: Designing a Multi-epitope Subunit Vaccine against Orf Virus Using Molecular Docking and Molecular Dynamics

description: Supplementary Table 1. Codon-optimized DNA sequence of the constructed multi-epitope subunit vaccine ORFV-S.
description: Supplementary Table 1. Codon-optimized DNA sequence of the constructed multi-epitope subunit vaccine ORFV-S.
DOI: 10.57760/sciencedb.08515
title: Model constraints on infiltration of surface-derived fluid deep into the brittle crust: numerical results
title: Model constraints on infiltration of surface-derived fluid deep into the brittle crust: numerical results

description: Numerical simulations were performed to investigate the downward infiltration of surface derived water along faults with imposed transient variations in permeability arising from fracturing and healing over earthquakes cycles. Fluid is driven downward along a fault either due to gradients in hydraulic head arising from topography or due to dilation on the fault during earthquakes (seismic pumping).   Results show that both forcing scenarios are equally capable of driving surface-derived fluid to the base of faults at 10 km depth in several tens of thousands of years. Downward flow of cold fluid occurs almost exclusively during and shortly after earthquakes, while during the remaining portion of the seismic cycle fluids remain relatively stationary while they undergo thermal relaxation (i.e., heating). Rapid downward flow is favoured by a large coseismic permeability, long permeability healing time scale, and large coseismic dilatancy or high topographic relief above the fault at the surface. However, downward fluid flow may be completely inhibited if the fluid pressure exceeds the hydrostatic gradient, even by modest amounts, which suggests that deep fluid infiltration is unlikely to occur in every region.Results of the models are presented and discussed in a paper submitted to Geophysical Journal International by Guy Simpson in 2024.
description: Numerical simulations were performed to investigate the downward infiltration of surface derived water along faults with imposed transient variations in permeability arising from fracturing and healing over earthquakes cycles. Fluid is driven downward along a fault either due to gradients in hydraulic head arising from topography or due to dilation on the fault during earthquakes (seismic pumping).   Results show that both forcing scenarios are equally capable of driving surface-derived fluid to the base of faults at 10 km depth in several tens of thousands of years. Downward flow of cold fluid occurs almost exclusively during and shortly after earthquakes, while during the remaining portion of the seismic cycle fluids remain relatively stationary while they undergo thermal relaxation (i.e., heating). Rapid downward flow is favoured by a large coseismic permeability, long permeability healing time scale, and large coseismic dilatancy or high topographic relief above the fault at the surface. However, downward fluid flow may be completely inhibited if the fluid pressure exceeds the hydrostatic gradient, even by modest amounts, which suggests that deep fluid infiltration is unlikely to occur in every region.Results of the models are presented and discussed in a paper submitted to Geophysical Journal International by Guy Simpson in 2024.
DOI: 10.57760/sciencedb.xbyxb.00005
title: Supplementary Figures and table(Specific dendritic-cell subset devotes to the chaos of programmed cell-death patterns from systemic lupus erythematosus circulation to lupus nephritis)
title: Supplementary Figures and table(Specific dendritic-cell subset devotes to the chaos of programmed cell-death patterns from systemic lupus erythematosus circulation to lupus nephritis)

description: This is supplementary material to the article. A detailed description of the supplementary materials is available in the article (Specific dendritic-cell subset devotes to the chaos of programmed cell-death patterns from systemic lupus erythematosus circulation to lupus nephritis)
description: This is supplementary material to the article. A detailed description of the supplementary materials is available in the article (Specific dendritic-cell subset devotes to the chaos of programmed cell-death patterns from systemic lupus erythematosus circulation to lupus nephritis)
DOI: 10.57760/sciencedb.08928
title: Data for Responses of non-native and native plant species to fluctuations of water availability in a greenhouse experiment
title: Data for Responses of non-native and native plant species to fluctuations of water availability in a greenhouse experiment

description: Plant biomass and VWC of each pot are given in the data.
description: Plant biomass and VWC of each pot are given in the data.
DOI: 10.57760/sciencedb.xbyxb.00001
title: Supplementary Figures and table (Imbalance of programmed cell death patterns mediated by dendritic cell subsets in systemic lupus erythematosus and lupus nephritis)
title: Supplementary Figures and table (Imbalance of programmed cell death patterns mediated by dendritic cell subsets in systemic lupus erythematosus and lupus nephritis)

description: This is supplementary material to the article. A detailed description of the supplementary materials is available in the article (Imbalance of programmed cell death patterns mediated by dendritic cell subsets in systemic lupus erythematosus and lupus nephritis)
description: This is supplementary material to the article. A detailed description of the supplementary materials is available in the article (Imbalance of programmed cell death patterns mediated by dendritic cell subsets in systemic lupus erythematosus and lupus nephritis)
DOI: 10.57760/sciencedb.08059
title: Marmosets population genetic Data
title: Marmosets population genetic Data

description: We characterize the genetic relationships and risk variants for epilepsy in 41 samples from two epileptic marmosets’ pedigrees with whole-genome sequencing. 
description: We characterize the genetic relationships and risk variants for epilepsy in 41 samples from two epileptic marmosets’ pedigrees with whole-genome sequencing.
DOI: 10.57760/sciencedb.07989
title: A dataset for suggesting variable orderings for cylindrical algebraic decompositions
title: A dataset for suggesting variable orderings for cylindrical algebraic decompositions

description: This dataset contains the running time and the number of cells of the CylindricalAlgebraicDecompose command in the RegularChains library of Maple under all possible variable orderings for more than 20K number of randomly generated polynomial systems of three variables (12141 examples) and four variables (11800 examples). For each example, the running time of the worst ordering is at least twice that of the best variable ordering. It can be used for benchmarking and designing heuristic methods and machine learning models for suggesting variable orderings for CADs. Please refer readme.txt for more detailed information of the dataset and the tiny difference between v1, v2 and v3. 
description: This dataset contains the running time and the number of cells of the CylindricalAlgebraicDecompose command in the RegularChains library of Maple under all possible variable orderings for more than 20K number of randomly generated polynomial systems of three variables (12141 examples) and four variables (11800 examples). For each example, the running time of the worst ordering is at least twice that of the best variable ordering. It can be used for benchmarking and designing heuristic methods and machine learning models for suggesting variable orderings for CADs. Please refer readme.txt for more detailed information of the dataset and the tiny difference between v1, v2 and v3.
DOI: 10.57760/sciencedb.15393
title: " Representational Similarity Analysis"
title: " Representational Similarity Analysis"

description: The dataset includes raw EEG data
description: The dataset includes raw EEG data
DOI: 10.57760/sciencedb.17721
title: Rich Data Variables: Integration of Ten Years of Daily Weather, Traffic, and Air Pollution Data Across Six Largest Norwegian Cities
title: Rich Data Variables: Integration of Ten Years of Daily Weather, Traffic, and Air Pollution Data Across Six Largest Norwegian Cities

description: This study combines a decade of daily weather, traffic, and air quality data from Norway's six largest cities. The data is sourced from the Norwegian Public Roads Administration, the Norwegian Institute of Air Research, and the Norwegian Meteorological Institute. Careful selection and verification of monitoring stations were conducted to ensure accuracy and consistency. Initially focusing on the top ten populous cities, monitoring sites for traffic and air pollution were scrutinized. Weather variables were then aligned with selected sites, resulting in a dataset spanning 2009 to 2018. It includes key pollutants like NO, NO2, NOx, PM2.5, and PM10. This dataset has significant potential for further analysis and informing policy decisions, making it valuable for researchers and policymakers studying the connections between weather, traffic, and air quality in urban areas.
description: This study combines a decade of daily weather, traffic, and air quality data from Norway's six largest cities. The data is sourced from the Norwegian Public Roads Administration, the Norwegian Institute of Air Research, and the Norwegian Meteorological Institute. Careful selection and verification of monitoring stations were conducted to ensure accuracy and consistency. Initially focusing on the top ten populous cities, monitoring sites for traffic and air pollution were scrutinized. Weather variables were then aligned with selected sites, resulting in a dataset spanning 2009 to 2018. It includes key pollutants like NO, NO2, NOx, PM2.5, and PM10. This dataset has significant potential for further analysis and informing policy decisions, making it valuable for researchers and policymakers studying the connections between weather, traffic, and air quality in urban areas.
DOI: 10.57760/sciencedb.18091
title: Changes in Chinese People's Social Concern and Attitudes towards Persons with Disabilities since the Reform and Opening-Up
title: 改革开放以来中国人对残疾人的关注度和态度的变迁

description: This dataset is the original data used for the paper Care Advances with the Times: Changes in Chinese People's Social Concern and Attitudes towards Persons with Disabilities since the Reform and Opening-Up" submitted to the Acta Psychologica Sinica.
description: This dataset is the original data used for the paper Care Advances with the Times: Changes in Chinese People's Social Concern and Attitudes towards Persons with Disabilities since the Reform and Opening-Up" submitted to the Acta Psychologica Sinica.
DOI: 10.57760/sciencedb.15208
title: Land use/land cover fusion dataset in Guangxi, China, 2000, 2010 and 2020
title: 2000、2010和2020年中国广西土地利用/土地覆盖融合数据集

description: This study selected six widely used remote sensing-based data products for land use/land cover, including the ESA GlobCover (ESAGC), ESRI Land Use/Land Cover (ESRI-LULC), Finer Resolution Observation and Monitoring of Global Land Cover (FROM-GLC), China Land Cover Dataset (CLCD), Global Land Cover product with Fine Classification System at 30 m (GLC_FCS30) and GlobeLand30 (GLC30). By reclassifying multiple data products and proposing data fusion methods based on spatial consistency analysis, a new high-precision and consistent land use/land cover data product for Guangxi in 2020 was synthesized, with a correlation coefficient greater than 0.94 with local statistical yearbook data. In this study, CLCD, GLC_FCS30, and GLC30 were further selected to form three-phase land use/land cover fused data for Guangxi in 2000, 2010, and 2020. This study can provide a methodological basis for the integration and application of regional-scale land use/land cover data products, as well as provide basic data for carrying out research on regional land cover changes and supporting rational management and sustainable development of regional land resources.
description: This study selected six widely used remote sensing-based data products for land use/land cover, including the ESA GlobCover (ESAGC), ESRI Land Use/Land Cover (ESRI-LULC), Finer Resolution Observation and Monitoring of Global Land Cover (FROM-GLC), China Land Cover Dataset (CLCD), Global Land Cover product with Fine Classification System at 30 m (GLC_FCS30) and GlobeLand30 (GLC30). By reclassifying multiple data products and proposing data fusion methods based on spatial consistency analysis, a new high-precision and consistent land use/land cover data product for Guangxi in 2020 was synthesized, with a correlation coefficient greater than 0.94 with local statistical yearbook data. In this study, CLCD, GLC_FCS30, and GLC30 were further selected to form three-phase land use/land cover fused data for Guangxi in 2000, 2010, and 2020. This study can provide a methodological basis for the integration and application of regional-scale land use/land cover data products, as well as provide basic data for carrying out research on regional land cover changes and supporting rational management and sustainable development of regional land resources.
DOI: 10.57760/sciencedb.01749
title: The Role of Magnetic Fields in Triggered Star Formation of RCW 120
title: The Role of Magnetic Fields in Triggered Star Formation of RCW 120

description: This version was submitted to the collection of Research in Astronomy and Astrophysics hosted by ScienceDB. The JHK-band starlight polarization of background stars behind the Galactic HII region RCW 120. Each ascii file contains the starlight polarization in one passband (J, H, K).
description: This version was submitted to the collection of Research in Astronomy and Astrophysics hosted by ScienceDB. The JHK-band starlight polarization of background stars behind the Galactic HII region RCW 120. Each ascii file contains the starlight polarization in one passband (J, H, K).
DOI: 10.57760/sciencedb.space.00745
title: Space Science in China
title: Space Science in China

description: This video recording is an episode of the UA 2024 lecture series (Universe Adventure: China Space Satellite Data Analysis School 2024).
description: This video recording is an episode of the UA 2024 lecture series (Universe Adventure: China Space Satellite Data Analysis School 2024).
DOI: 10.57760/sciencedb.space.00747
title: NSSDC: Data Governance and application practices
title: NSSDC: Data Governance and application practices

description: This video recording is an episode of the UA 2024 lecture series (Universe Adventure: China Space Satellite Data Analysis School 2024).
description: This video recording is an episode of the UA 2024 lecture series (Universe Adventure: China Space Satellite Data Analysis School 2024).
DOI: 10.57760/sciencedb.space.00751
title: GECAM Data Analysis Tutorial
title: GECAM Data Analysis Tutorial

description: This video recording is an episode of the UA 2024 lecture series (Universe Adventure: China Space Satellite Data Analysis School 2024).
description: This video recording is an episode of the UA 2024 lecture series (Universe Adventure: China Space Satellite Data Analysis School 2024).
DOI: 10.57760/sciencedb.space.00752
title: Exploring the dynamic X-ray universe with the Einstein Probe mission
title: Exploring the dynamic X-ray universe with the Einstein Probe mission

description: This video recording is an episode of the UA 2024 lecture series (Universe Adventure: China Space Satellite Data Analysis School 2024).
description: This video recording is an episode of the UA 2024 lecture series (Universe Adventure: China Space Satellite Data Analysis School 2024).
DOI: 10.57760/sciencedb.space.00761
title: Introduction to the DAMPE instrument and scientific objectives
title: Introduction to the DAMPE instrument and scientific objectives

description: This video recording is an episode of the UA 2024 lecture series (Universe Adventure: China Space Satellite Data Analysis School 2024).
description: This video recording is an episode of the UA 2024 lecture series (Universe Adventure: China Space Satellite Data Analysis School 2024).
DOI: 10.57760/sciencedb.space.00758
title: Status of Dark Matter Indirect Detection
title: Status of Dark Matter Indirect Detection

description: This video recording is an episode of the UA 2024 lecture series (Universe Adventure: China Space Satellite Data Analysis School 2024).
description: This video recording is an episode of the UA 2024 lecture series (Universe Adventure: China Space Satellite Data Analysis School 2024).
DOI: 10.57760/sciencedb.16286
title: Arctic Ocean dynamical downscaling data (ssp245) for understanding past and future climate change
title: Arctic Ocean dynamical downscaling data (ssp245) for understanding past and future climate change

description: The Arctic is one of Earth’s regions most susceptible to climate change. However, the in-situ long-term observations used for climate research are relatively sparse in the Arctic Ocean, and the simulations from current climate models exhibit remarkable biases in the Arctic. Here we present an Arctic Ocean dynamical downscaling dataset based on a high-resolution ice-ocean coupled model FESOM and a climate model FIO-ESM. The dataset includes 115-year (1900–2014) historical simulations and two 86-year future scenario simulations (2015–2100) under scenarios SSP245 and SSP585. The historical results demonstrate that the root mean square errors of temperature and salinity in the dynamical downscaling dataset are much smaller than those from CMIP6 (the Coupled Model Intercomparison Project phase 6) climate models. The common biases, such as the too deep and too thick Atlantic layer in climate models, are reduced significantly by dynamical downscaling. This dataset serves as a crucial long-term data source for climate change assessments and scientific research in the Arctic Ocean, providing valuable information for the scientific community.
description: The Arctic is one of Earth’s regions most susceptible to climate change. However, the in-situ long-term observations used for climate research are relatively sparse in the Arctic Ocean, and the simulations from current climate models exhibit remarkable biases in the Arctic. Here we present an Arctic Ocean dynamical downscaling dataset based on a high-resolution ice-ocean coupled model FESOM and a climate model FIO-ESM. The dataset includes 115-year (1900–2014) historical simulations and two 86-year future scenario simulations (2015–2100) under scenarios SSP245 and SSP585. The historical results demonstrate that the root mean square errors of temperature and salinity in the dynamical downscaling dataset are much smaller than those from CMIP6 (the Coupled Model Intercomparison Project phase 6) climate models. The common biases, such as the too deep and too thick Atlantic layer in climate models, are reduced significantly by dynamical downscaling. This dataset serves as a crucial long-term data source for climate change assessments and scientific research in the Arctic Ocean, providing valuable information for the scientific community.
DOI: 10.57760/sciencedb.16206
title: Arctic Ocean dynamical downscaling data (historical) for understanding past and future climate change
title: Arctic Ocean dynamical downscaling data (historical) for understanding past and future climate change

description: The Arctic is one of Earth’s regions most susceptible to climate change. However, the in-situ long-term observations used for climate research are relatively sparse in the Arctic Ocean, and the simulations from current climate models exhibit remarkable biases in the Arctic. Here we present an Arctic Ocean dynamical downscaling dataset based on a high-resolution ice-ocean coupled model FESOM and a climate model FIO-ESM. The dataset includes 115-year (1900–2014) historical simulations and two 86-year future scenario simulations (2015–2100) under scenarios SSP245 and SSP585. The historical results demonstrate that the root mean square errors of temperature and salinity in the dynamical downscaling dataset are much smaller than those from CMIP6 (the Coupled Model Intercomparison Project phase 6) climate models. The common biases, such as the too deep and too thick Atlantic layer in climate models, are reduced significantly by dynamical downscaling. This dataset serves as a crucial long-term data source for climate change assessments and scientific research in the Arctic Ocean, providing valuable information for the scientific community.
description: The Arctic is one of Earth’s regions most susceptible to climate change. However, the in-situ long-term observations used for climate research are relatively sparse in the Arctic Ocean, and the simulations from current climate models exhibit remarkable biases in the Arctic. Here we present an Arctic Ocean dynamical downscaling dataset based on a high-resolution ice-ocean coupled model FESOM and a climate model FIO-ESM. The dataset includes 115-year (1900–2014) historical simulations and two 86-year future scenario simulations (2015–2100) under scenarios SSP245 and SSP585. The historical results demonstrate that the root mean square errors of temperature and salinity in the dynamical downscaling dataset are much smaller than those from CMIP6 (the Coupled Model Intercomparison Project phase 6) climate models. The common biases, such as the too deep and too thick Atlantic layer in climate models, are reduced significantly by dynamical downscaling. This dataset serves as a crucial long-term data source for climate change assessments and scientific research in the Arctic Ocean, providing valuable information for the scientific community.