cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.57760/sciencedb.09456
title: Development Progress of the Neutronics Calculation Module of Neutronics and Thermal Hydraulic Calculation Program NECP-Panda for Pebble-bed High Temperature Gas-cooled Reactor
title: 球床式高温气冷堆物理热工计算程序 NECP-Panda中子学计算模块研发进展

description: [背景] 球床高温气冷堆（PB-HTGR）在几何结构、中子特性和运行方式方面与其他类型的反应堆有很大不同。因此，必须为PB-HTGR开发专门的分析和计算代码。【目的】为了进一步提高PB-HTGR核心物理计算精度，习安交通大学核工程计算物理实验室自主研发了适用于PB-HTGR的中子学和热力计算程序NECP-Panda中子计算模块。[方法]在中子学计算中，NECP-Panda采用了两步法。第一步是基于蒙特卡罗方法计算组分均质群常数 。第二步，利用碰撞概率方程对卵石床进行均质化，随后利用三维圆柱几何节点膨胀法（NEM）完成全芯扩散计算。为了准确说明中子泄漏效应对模型区域群常数的影响，对扩散计算和中子泄漏校正进行迭代，直至该区域的群常数收敛。此外，在迭代中对多孔结构的中子流效应进行了校正，在扩散计算中对卵石床顶部的空腔进行了特殊处理。【结果】NECP-Panda已经通过了两种模型的验证，一种是简化的混合球床反应器，另一种是高温反应器球床模块（HTR-PM）。数值结果表明，NECP-Panda计算的简化混合球床反应器的特征值计算接近蒙特卡罗连续能量结果。HTR-PM计算出的HTR-PM临界载荷高度与蒙特卡罗连续能量计算结果高度吻合，吸波器值也吻合较好。 【结论】结果表明，NECP-Panda在PB-HTGR的中子学计算中具有较强的计算能力和精度，为后续模块的开发奠定了坚实的基础。
description: [背景] 球床高温气冷堆（PB-HTGR）在几何结构、中子特性和运行方式方面与其他类型的反应堆有很大不同。因此，必须为PB-HTGR开发专门的分析和计算代码。【目的】为了进一步提高PB-HTGR核心物理计算精度，习安交通大学核工程计算物理实验室自主研发了适用于PB-HTGR的中子学和热力计算程序NECP-Panda中子计算模块。[方法]在中子学计算中，NECP-Panda采用了两步法。第一步是基于蒙特卡罗方法计算组分均质群常数 。第二步，利用碰撞概率方程对卵石床进行均质化，随后利用三维圆柱几何节点膨胀法（NEM）完成全芯扩散计算。为了准确说明中子泄漏效应对模型区域群常数的影响，对扩散计算和中子泄漏校正进行迭代，直至该区域的群常数收敛。此外，在迭代中对多孔结构的中子流效应进行了校正，在扩散计算中对卵石床顶部的空腔进行了特殊处理。【结果】NECP-Panda已经通过了两种模型的验证，一种是简化的混合球床反应器，另一种是高温反应器球床模块（HTR-PM）。数值结果表明，NECP-Panda计算的简化混合球床反应器的特征值计算接近蒙特卡罗连续能量结果。HTR-PM计算出的HTR-PM临界载荷高度与蒙特卡罗连续能量计算结果高度吻合，吸波器值也吻合较好。 【结论】结果表明，NECP-Panda在PB-HTGR的中子学计算中具有较强的计算能力和精度，为后续模块的开发奠定了坚实的基础。
DOI: 10.57760/sciencedb.09669
title: Main and Supplementary data to the article
title: Main and Supplementary data to the article

description: This database including the main figures and tables of “Effects of lower limb training on lower limb muscle dysfunction in middle-aged and elderly patients with COPD: a systematic review and meta-analysis”.
description: This database including the main figures and tables of “Effects of lower limb training on lower limb muscle dysfunction in middle-aged and elderly patients with COPD: a systematic review and meta-analysis”.
DOI: 10.57760/sciencedb.09364
title: Dataset for "Observations of negative sprites and halos over a coastal thunderstorm in South China Sea "
title: Dataset for "Observations of negative sprites and halos over a coastal thunderstorm in South China Sea "

description: This dataset pertains to observations of a thunderstorm in the coastal region of Guangdong on August 28, 2021. It primarily supports the article "Observations of Negative Sprites and Halos Over a Coastal Thunderstorm in the South China Sea". The dataset includes images of mid- and high-level discharge events captured over the thunderstorm that night, TLE parent lightning electric field signals observed by Guangdong Station and Zengcheng Station, TBB data from the Himawari-8 satellite, the S-band Doppler weather radar data from the China Meteorological Administration, as well as the figures ploted and related code used.
description: This dataset pertains to observations of a thunderstorm in the coastal region of Guangdong on August 28, 2021. It primarily supports the article "Observations of Negative Sprites and Halos Over a Coastal Thunderstorm in the South China Sea". The dataset includes images of mid- and high-level discharge events captured over the thunderstorm that night, TLE parent lightning electric field signals observed by Guangdong Station and Zengcheng Station, TBB data from the Himawari-8 satellite, the S-band Doppler weather radar data from the China Meteorological Administration, as well as the figures ploted and related code used.
DOI: 10.15468/dl.ty9vuk
title: Occurrence Download

description: A dataset containing 202122 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is National Benthic Inventory"
 ]
}

 The dataset includes 202122 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001342-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57760/sciencedb.space.00774
title: The Best Practices of Research Data Sharing Associated with Publication
title: The Best Practices of Research Data Sharing Associated with Publication

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.00753
title: Detectors and In-orbit Results of GRID: a Student NanoSat Mission for Gamma-Ray Burst Observation
title: Detectors and In-orbit Results of GRID: a Student NanoSat Mission for Gamma-Ray Burst Observation

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: 10.15468/dl.e3362a
title: Occurrence Download

description: A dataset containing 202812 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Vulnerable marine ecosystems in the South Pacific Ocean region"
 ]
}

 The dataset includes 202812 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001340-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34965/i53381
title: 20244079
DOI: 10.57760/sciencedb.16344
title: Surface forcing (ssp585) for Arctic Ocean dynamical downscaling data establishment
title: Surface forcing (ssp585) for Arctic Ocean dynamical downscaling data establishment

description: The surface forcing to drive FESOM2 to establish the Arctic Ocean dynamical downscaling data is from the output of FIO-ESM v2.1. The surface forcing includes the eastward and northward components of near-surface wind, near-surface air temperature, near-surface specific humidity, surface downwelling shortwave radiation, surface downwelling longwave radiation, rainfall flux, snowfall flux, total (liquid and solid) runoff. To reduce the simulated errors from the surface forcing bias, the climatological biases of near-surface wind and near-surface air temperature relative to those from the surface-atmospheric dataset for driving ocean–sea-ice models based on Japanese 55-year atmospheric reanalysis (JRA55-do) during 1960–2009 are removed.
description: The surface forcing to drive FESOM2 to establish the Arctic Ocean dynamical downscaling data is from the output of FIO-ESM v2.1. The surface forcing includes the eastward and northward components of near-surface wind, near-surface air temperature, near-surface specific humidity, surface downwelling shortwave radiation, surface downwelling longwave radiation, rainfall flux, snowfall flux, total (liquid and solid) runoff. To reduce the simulated errors from the surface forcing bias, the climatological biases of near-surface wind and near-surface air temperature relative to those from the surface-atmospheric dataset for driving ocean–sea-ice models based on Japanese 55-year atmospheric reanalysis (JRA55-do) during 1960–2009 are removed.
DOI: 10.57760/sciencedb.16341
title: Surface forcing (historical) for Arctic Ocean dynamical downscaling data establishment
title: Surface forcing (historical) for Arctic Ocean dynamical downscaling data establishment

description: The surface forcing to drive FESOM2 to establish the Arctic Ocean dynamical downscaling data is from the output of FIO-ESM v2.1. The surface forcing includes the eastward and northward components of near-surface wind, near-surface air temperature, near-surface specific humidity, surface downwelling shortwave radiation, surface downwelling longwave radiation, rainfall flux, snowfall flux, total (liquid and solid) runoff. To reduce the simulated errors from the surface forcing bias, the climatological biases of near-surface wind and near-surface air temperature relative to those from the surface-atmospheric dataset for driving ocean–sea-ice models based on Japanese 55-year atmospheric reanalysis (JRA55-do) during 1960–2009 are removed.
description: The surface forcing to drive FESOM2 to establish the Arctic Ocean dynamical downscaling data is from the output of FIO-ESM v2.1. The surface forcing includes the eastward and northward components of near-surface wind, near-surface air temperature, near-surface specific humidity, surface downwelling shortwave radiation, surface downwelling longwave radiation, rainfall flux, snowfall flux, total (liquid and solid) runoff. To reduce the simulated errors from the surface forcing bias, the climatological biases of near-surface wind and near-surface air temperature relative to those from the surface-atmospheric dataset for driving ocean–sea-ice models based on Japanese 55-year atmospheric reanalysis (JRA55-do) during 1960–2009 are removed.
DOI: 10.57760/sciencedb.16342
title: Surface forcing (ssp245) for Arctic Ocean dynamical downscaling data establishment
title: Surface forcing (ssp245) for Arctic Ocean dynamical downscaling data establishment

description: The surface forcing to drive FESOM2 to establish the Arctic Ocean dynamical downscaling data is from the output of FIO-ESM v2.1. The surface forcing includes the eastward and northward components of near-surface wind, near-surface air temperature, near-surface specific humidity, surface downwelling shortwave radiation, surface downwelling longwave radiation, rainfall flux, snowfall flux, total (liquid and solid) runoff. To reduce the simulated errors from the surface forcing bias, the climatological biases of near-surface wind and near-surface air temperature relative to those from the surface-atmospheric dataset for driving ocean–sea-ice models based on Japanese 55-year atmospheric reanalysis (JRA55-do) during 1960–2009 are removed.
description: The surface forcing to drive FESOM2 to establish the Arctic Ocean dynamical downscaling data is from the output of FIO-ESM v2.1. The surface forcing includes the eastward and northward components of near-surface wind, near-surface air temperature, near-surface specific humidity, surface downwelling shortwave radiation, surface downwelling longwave radiation, rainfall flux, snowfall flux, total (liquid and solid) runoff. To reduce the simulated errors from the surface forcing bias, the climatological biases of near-surface wind and near-surface air temperature relative to those from the surface-atmospheric dataset for driving ocean–sea-ice models based on Japanese 55-year atmospheric reanalysis (JRA55-do) during 1960–2009 are removed.
DOI: 10.15468/dl.tb2gt7
title: Occurrence Download

description: A dataset containing 204830 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Vascular Plant Herbarium, UiB"
 ]
}

 The dataset includes 204830 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001341-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57760/sciencedb.09599
title: China 0.1° Extreme Climate Index Dataset from 1979 to 2018
title: 1979–2018年中国0.1°极端气候指标数据集

description: The CECID (China Extreme Climate Index Dataset), a 0.1° extreme climate index dataset for China from 1979-2018, was calculated based on the China Surface Meteorological Element Driven Dataset (CMFD) and the China Near Surface Air Temperature Dataset (CDAT) using the R language program package climdex.pcic , the dataset covers 27 extreme climate indices. The correlation coefficients of most of the indicators (e.g., FD, TR, R10mm, PRCPTOT) are above 0.7 compared with the public extreme climate index datasets. The CECID can be used for studying the characteristics of extreme climate events in China and their impacts on ecosystems. It holds practical value and significance in disaster prevention, climate change assessment, and related fields.
description: The CECID (China Extreme Climate Index Dataset), a 0.1° extreme climate index dataset for China from 1979-2018, was calculated based on the China Surface Meteorological Element Driven Dataset (CMFD) and the China Near Surface Air Temperature Dataset (CDAT) using the R language program package climdex.pcic , the dataset covers 27 extreme climate indices. The correlation coefficients of most of the indicators (e.g., FD, TR, R10mm, PRCPTOT) are above 0.7 compared with the public extreme climate index datasets. The CECID can be used for studying the characteristics of extreme climate events in China and their impacts on ecosystems. It holds practical value and significance in disaster prevention, climate change assessment, and related fields.
DOI: 10.57760/sciencedb.10436
title: ESDC: An Earth Science Data Corpus to Support Literature Information Extraction
title: ESDC: An Earth Science Data Corpus to Support Literature Information Extraction

description: Large amounts of original research data related to earth system science have increased rapidly over the past ten years, making it easy to help researchers understand the human-earth system from different fields. A substantial amount of these earth science data products is published as open source by geographers in authoritative journals. Extracting information from the literature of these authoritative journals holds significant potential in constructing a domain knowledge base. However, this potential remains largely unfulfilled in geoscience. This is because there is almost no publicly available related corpus and baselines, which is one of the biggest obstacles. Therefore, we present the Earth Science Data Corpus (ESDC), an academic text corpus of 500 abstracts from the authoritative journal. To the best of our knowledge, it is the first corpus of earth science data to provide such detail, which provides a professional training dataset for knowledge extraction and construction of domain-specific knowledge graphs from massive literature. In the production process of ESDC, we considered the contextual features of spatiotemporal entities and the linguistic characteristics of academic literature and formulated annotation guidelines and procedures tailored for earth science data to ensure the reliability of the ESDC.
description: Large amounts of original research data related to earth system science have increased rapidly over the past ten years, making it easy to help researchers understand the human-earth system from different fields. A substantial amount of these earth science data products is published as open source by geographers in authoritative journals. Extracting information from the literature of these authoritative journals holds significant potential in constructing a domain knowledge base. However, this potential remains largely unfulfilled in geoscience. This is because there is almost no publicly available related corpus and baselines, which is one of the biggest obstacles. Therefore, we present the Earth Science Data Corpus (ESDC), an academic text corpus of 500 abstracts from the authoritative journal. To the best of our knowledge, it is the first corpus of earth science data to provide such detail, which provides a professional training dataset for knowledge extraction and construction of domain-specific knowledge graphs from massive literature. In the production process of ESDC, we considered the contextual features of spatiotemporal entities and the linguistic characteristics of academic literature and formulated annotation guidelines and procedures tailored for earth science data to ensure the reliability of the ESDC.
DOI: 10.57760/sciencedb.space.00755
title: To Understand the Densest Cosmic Matter in the era of Multi-Messenger Astronomy
title: To Understand the Densest Cosmic Matter in the era of Multi-Messenger Astronomy

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.00764
title: Fundamentals of statistics and principles of data analysis
title: Fundamentals of statistics and principles of data analysis

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.00781
title: Fundamentals of statistics and principles of data analysis (2)
title: Fundamentals of statistics and principles of data analysis (2)

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.00771
title: Enabling Open Science Through Trusted Connections: Best Practices and Case Studies of Persistent Identifiers
title: Enabling Open Science Through Trusted Connections: Best Practices and Case Studies of Persistent Identifiers

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.00769
title: The Concept and Practice of Open Science
title: The Concept and Practice of Open Science

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: 10.15468/dl.w4hp9g
title: Occurrence Download

description: A dataset containing 14210 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Unio pictorum (Linnaeus, 1758)"
 ]
}

 The dataset includes 14210 records from 256 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001338-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57760/sciencedb.j00186.00140
title: Data from gamma-ray imaging systems
title: Data from gamma-ray imaging systems

description: In this database, we have uploaded real radiation images from gamma-ray imaging systems. Additionally, we performed single-image super-resolution to reconstruct the acquired images and have uploaded the reconstruction results.
description: In this database, we have uploaded real radiation images from gamma-ray imaging systems. Additionally, we performed single-image super-resolution to reconstruct the acquired images and have uploaded the reconstruction results.
DOI: 10.57760/sciencedb.18320
title: Data for the TSYS-021-0378
title: Data for the TSYS-021-0378

description: The figures of the corresponding article.
description: The figures of the corresponding article.
DOI: 10.57760/sciencedb.10128
title: Low-oxygen environments suppressed metazoan diversification during the Terreneuvian
title: Low-oxygen environments suppressed metazoan diversification during the Terreneuvian

description: Organic carbon isotope and nitrogen isotope data for the Meishucun and Zhujiaqing sections from South China are includes, whose geochronlogical ages span from late Ediacaran to early Cambrian.
description: Organic carbon isotope and nitrogen isotope data for the Meishucun and Zhujiaqing sections from South China are includes, whose geochronlogical ages span from late Ediacaran to early Cambrian.
DOI: 10.57760/sciencedb.j00001.00980
title: Meteorological observation data from the Great Wall station and Zhongshan station in Antarctica during the past 35 years
title: 近35年南极长城站和中山站气象观测数据集

description: The Great Wall Station and Zhongshan Station are Chinese permanent scientific research stations in Antarctica, located on the King George Island and in the Larsemann Hills. These two stations are representative observation stations for the study of climate change in the coastal areas of the West Antarctica and the East Antarctica respectively. After the completion of the two stations, surface meteorological observation is carried out according to the specifications of the China Meteorological Administration. This dataset collected the surface meteorological observation data of the Great Wall Station and Zhongshan Station from 1985 to 2022. The data has been quality controlled according to the "Specifications for surface meteorological observation". Nowadays long-term continuous surface meteorological observation data has been obtained including surface air temperature, relative humidity, air pressure, wind speed, wind direction and cloud amount. This dataset can be used for the research of weather processes, climate change and numerical weather forecast in the Antarctic.
description: The Great Wall Station and Zhongshan Station are Chinese permanent scientific research stations in Antarctica, located on the King George Island and in the Larsemann Hills. These two stations are representative observation stations for the study of climate change in the coastal areas of the West Antarctica and the East Antarctica respectively. After the completion of the two stations, surface meteorological observation is carried out according to the specifications of the China Meteorological Administration. This dataset collected the surface meteorological observation data of the Great Wall Station and Zhongshan Station from 1985 to 2022. The data has been quality controlled according to the "Specifications for surface meteorological observation". Nowadays long-term continuous surface meteorological observation data has been obtained including surface air temperature, relative humidity, air pressure, wind speed, wind direction and cloud amount. This dataset can be used for the research of weather processes, climate change and numerical weather forecast in the Antarctic.
DOI: 10.57760/sciencedb.12208
title: Genome assembly of Musa ornata and M. velutina
title: Genome assembly of Musa ornata and M. velutina

description: Here we present the genome assemblies of M. ornata and M. velutina. Besides, the DNA and Amino Acid sequences of protein-coding genes, annotation files (gff3 format) are also uploaded here.
description: Here we present the genome assemblies of M. ornata and M. velutina. Besides, the DNA and Amino Acid sequences of protein-coding genes, annotation files (gff3 format) are also uploaded here.