cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.57760/sciencedb.16380
title: Three-dimensional motion dataset of Dunhuang dance
title: 敦煌舞三维动作数据集

description: Dunhuang dance is an artistic treasure of traditional Chinese culture, with a long history and an important component of Dunhuang culture. Its digital preservation, display, and research are of great significance. To promote the digitalization process and development of Dunhuang dance, this study proposes to combine Dunhuang dance with 3D human pose estimation technology to construct a Dunhuang dance 3D action database. This database divides Dunhuang dance into 7 themes, 83 basic movements, and 16 long movements. Good results have been achieved in quantitative, qualitative, and manual evaluations, laying the foundation for the preservation, application, and development of Dunhuang dance; This provides new ideas for the research, promotion, and inheritance of Dunhuang culture. The future use of this database can be applied to generative artificial intelligence, digital exhibitions and performances of Dunhuang dance culture, education and research of Dunhuang dance, digital media and entertainment of Dunhuang dance, etc. 
description: Dunhuang dance is an artistic treasure of traditional Chinese culture, with a long history and an important component of Dunhuang culture. Its digital preservation, display, and research are of great significance. To promote the digitalization process and development of Dunhuang dance, this study proposes to combine Dunhuang dance with 3D human pose estimation technology to construct a Dunhuang dance 3D action database. This database divides Dunhuang dance into 7 themes, 83 basic movements, and 16 long movements. Good results have been achieved in quantitative, qualitative, and manual evaluations, laying the foundation for the preservation, application, and development of Dunhuang dance; This provides new ideas for the research, promotion, and inheritance of Dunhuang culture. The future use of this database can be applied to generative artificial intelligence, digital exhibitions and performances of Dunhuang dance culture, education and research of Dunhuang dance, digital media and entertainment of Dunhuang dance, etc.
DOI: 10.57760/sciencedb.psych.00152
title: Does happiness come from wealth? A 11-year panel data analysis on socio-economic and social media
title: Does happiness come from wealth? A 11-year panel data analysis on socio-economic and social media

description: The data set and code of paper "Does Wealth Equate to Happiness? An 11-Year Panel Data Analysis Exploring Socio-Economic Indicators and Social Media Metrics"
description: The data set and code of paper "Does Wealth Equate to Happiness? An 11-Year Panel Data Analysis Exploring Socio-Economic Indicators and Social Media Metrics"
DOI: 10.57760/sciencedb.09217
title: High-precision Chinese forest cover dataset based on multi-source land cover products
title: 基于多源土地覆盖产品整合的高精度中国森林覆盖数据集

description: This dataset is a set of high-precision national forest cover data products based on the consistency and complementarity of multi-source land cover products, cloud-free composite images, random forest classification model and multi-level voting strategy.This approach enhances the accuracy of forest resource monitoring, forest management, and forest carbon quantification and evaluation in China. The dataset serves as a fundamental resources for precise forest monitoring information, facilitating informed decision-making in forest management and contributing to the effectiveness of forest management strategies.
description: This dataset is a set of high-precision national forest cover data products based on the consistency and complementarity of multi-source land cover products, cloud-free composite images, random forest classification model and multi-level voting strategy.This approach enhances the accuracy of forest resource monitoring, forest management, and forest carbon quantification and evaluation in China. The dataset serves as a fundamental resources for precise forest monitoring information, facilitating informed decision-making in forest management and contributing to the effectiveness of forest management strategies.
DOI: 10.57760/sciencedb.16322
title: Cluster Counting Algorithm for Drift Chamber using LSTM and DGCNN
title: Cluster Counting Algorithm for Drift Chamber using LSTM and DGCNN

description: Particle identification (PID) of hadrons plays a crucial role in particle physics experiments, especially for flavor physics and jet tagging. The cluster counting method, which measures the number of primary ionizations in gaseous detectors, represents a promising breakthrough in PID. However, developing an effective reconstruction algorithm for cluster counting remains a major challenge. In this study, we address this challenge by proposing a cluster counting algorithm based on long short-term memory and dynamic graph convolutional neural networks. Leveraging Monte Carlo simulated samples, our machine learning-based algorithm surpasses traditional methods. Specifically, it achieves a remarkable 10% improvement in K/π separation for PID performance.cluster_counting_ml_codes:Python codes to train and test machine learning model for cluster counting. Including LSTM for peak finding and DGCNN for clusterization.samplesCERN ROOT files of simulation samples of waveforms of the signal in drift chamber cells.
description: Particle identification (PID) of hadrons plays a crucial role in particle physics experiments, especially for flavor physics and jet tagging. The cluster counting method, which measures the number of primary ionizations in gaseous detectors, represents a promising breakthrough in PID. However, developing an effective reconstruction algorithm for cluster counting remains a major challenge. In this study, we address this challenge by proposing a cluster counting algorithm based on long short-term memory and dynamic graph convolutional neural networks. Leveraging Monte Carlo simulated samples, our machine learning-based algorithm surpasses traditional methods. Specifically, it achieves a remarkable 10% improvement in K/π separation for PID performance.cluster_counting_ml_codes:Python codes to train and test machine learning model for cluster counting. Including LSTM for peak finding and DGCNN for clusterization.samplesCERN ROOT files of simulation samples of waveforms of the signal in drift chamber cells.
DOI: 10.57760/sciencedb.16493
title: RAS Dataset
title: RAS Dataset

description: The current challenge in effectively treating atrial fibrillation (AF) stems from a limited understanding of the intricate structure of the human atria. The objective and quantitative interpretation of the right atrium (RA) in late gadolinium-enhanced magnetic resonance imaging (LGE-MRI) scans relies heavily on its precise segmentation. Leveraging the potential of artificial intelligence (AI) - based approaches for RA segmentation presents a promising solution. However, the successful implementation of AI in this context necessitates access to a substantial volume of annotated LGE-MRI images for model training. In this paper, we present a comprehensive 3D cardiac dataset comprising 50 high-resolution LGE-MRI scans, each meticulously annotated at the pixel level. The annotation process underwent rigorous standardization through crowdsourcing among a panel of medical experts, ensuring the accuracy and consistency of the annotations. Our dataset represents a significant contribution to the field, providing a valuable resource for advancing AI-based RA segmentation methods.
description: The current challenge in effectively treating atrial fibrillation (AF) stems from a limited understanding of the intricate structure of the human atria. The objective and quantitative interpretation of the right atrium (RA) in late gadolinium-enhanced magnetic resonance imaging (LGE-MRI) scans relies heavily on its precise segmentation. Leveraging the potential of artificial intelligence (AI) - based approaches for RA segmentation presents a promising solution. However, the successful implementation of AI in this context necessitates access to a substantial volume of annotated LGE-MRI images for model training. In this paper, we present a comprehensive 3D cardiac dataset comprising 50 high-resolution LGE-MRI scans, each meticulously annotated at the pixel level. The annotation process underwent rigorous standardization through crowdsourcing among a panel of medical experts, ensuring the accuracy and consistency of the annotations. Our dataset represents a significant contribution to the field, providing a valuable resource for advancing AI-based RA segmentation methods.
DOI: 10.57760/sciencedb.16314
title: AllocationStatisticsR2024
title: AllocationStatisticsR2024

description: R language code for data analysis of three allocation methods
description: R language code for data analysis of three allocation methods
DOI: 10.15468/dl.r3zw4z
title: Occurrence Download

description: A dataset containing 206073 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Masaryk University - Herbarium BRNU"
 ]
}

 The dataset includes 206073 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001332-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57760/sciencedb.15307
title: PB-GPT
title: PB-GPT

description: Here we showcase the dataset and original code used in the article "PB-GPT: an Innovative GPT-Based Model for Protein Backbone Generation."For specific instructions on the usage of the data and code, please refer to the following link: https://github.com/XMUCXx/PB-GPT.
description: Here we showcase the dataset and original code used in the article "PB-GPT: an Innovative GPT-Based Model for Protein Backbone Generation."For specific instructions on the usage of the data and code, please refer to the following link: https://github.com/XMUCXx/PB-GPT.
DOI: 10.57760/sciencedb.13771
title: Spectroscopic properties of Pr:PbF2 crystal with different doping concentration
title: Spectroscopic properties of Pr:PbF2 crystal with different doping concentration

description: The dataset of paper entitled "Spectroscopic properties of Pr:PbF2 crystal with different doping concentration"
description: The dataset of paper entitled "Spectroscopic properties of Pr:PbF2 crystal with different doping concentration"
DOI: 10.57760/sciencedb.16042
title: Semi-supervised learning for explainable few-shot battery lifetime prediction
title: Semi-supervised learning for explainable few-shot battery lifetime prediction

description: Source code for Semi-supervised learning for explainable few-shot battery lifetime prediction. Details can be found in README.md
description: Source code for Semi-supervised learning for explainable few-shot battery lifetime prediction. Details can be found in README.md
DOI: 10.57760/sciencedb.16603
title: Sensible and latent heat fluxes on the Qinghai-Tibet Plateau based on the Noah-MP land surface model
title: 基于Noah-MP陆面模式的青藏高原感热和潜热通量

description: This data is a simulation of the Noah-MP land surface model. Time period: January 1981 to December 2018；Temporal resolution: 6h; Spatial resolution: 0.1 °.The atmospheric forcing field data used for the experiment is CMFD (He et al, 2020).
description: This data is a simulation of the Noah-MP land surface model. Time period: January 1981 to December 2018；Temporal resolution: 6h; Spatial resolution: 0.1 °.The atmospheric forcing field data used for the experiment is CMFD (He et al, 2020).
DOI: 10.57760/sciencedb.15154
title: A dataset of air-sea fluxes at Hainan Xisha Marine Environmental National Observation and Research Station from 2016 to 2020
title: 2016-2020年海南西沙海洋环境国家野外科学观测研究站海气通量数据集

description: The exchange of air-sea flux is a key observation and monitoring object for conducting scientific researches on ocean and the atmosphere coupling systems and ensuring marine environmental safety. This paper collects and processes observational data of 2016 to 2020 obtained from the comprehensive meteorological observation tower of the Hainan Xisha Marine Environmental National Observation and Research Station, located on the edge of Yongxing Island in Xisha. The tower is equipped with advanced observation equipment and sensors, achieving long-term stable measurement and real-time transmission and archiving of air-sea flux data. The dataset mainly includes air-sea flux components such as shortwave radiation, longwave radiation, latent heat flux, sensible heat flux, momentum flux, and carbon dioxide flux, and provides corresponding hydrological and meteorological variables such as wind speed, wind direction, temperature, relative humidity, atmospheric pressure, precipitation, and sea surface temperature. This dataset can provide important basic data support for improving air-sea flux parameterization schemes, developing related data products, conducting regional air-sea interaction and climate change studies, as well as monitoring deep-sea marine environments and warning of disasters.
description: The exchange of air-sea flux is a key observation and monitoring object for conducting scientific researches on ocean and the atmosphere coupling systems and ensuring marine environmental safety. This paper collects and processes observational data of 2016 to 2020 obtained from the comprehensive meteorological observation tower of the Hainan Xisha Marine Environmental National Observation and Research Station, located on the edge of Yongxing Island in Xisha. The tower is equipped with advanced observation equipment and sensors, achieving long-term stable measurement and real-time transmission and archiving of air-sea flux data. The dataset mainly includes air-sea flux components such as shortwave radiation, longwave radiation, latent heat flux, sensible heat flux, momentum flux, and carbon dioxide flux, and provides corresponding hydrological and meteorological variables such as wind speed, wind direction, temperature, relative humidity, atmospheric pressure, precipitation, and sea surface temperature. This dataset can provide important basic data support for improving air-sea flux parameterization schemes, developing related data products, conducting regional air-sea interaction and climate change studies, as well as monitoring deep-sea marine environments and warning of disasters.
DOI: 10.57760/sciencedb.space.00618
title: CSES satellite-based observations of industrial frequency radiation
title: 基于CSES卫星的工频辐射观测结果

description: Results of observing month-to-month variations in the incidence of 60 Hz IF radiation over the United States using CSES satellite electric field data.
description: Results of observing month-to-month variations in the incidence of 60 Hz IF radiation over the United States using CSES satellite electric field data.
DOI: 10.57760/sciencedb.space.01783
title: VLF signal dataset radiated by NWC transmitter
title: NWC台站辐射的甚低频信号数据集

description: VLF signal sources include lightning and some submarine communication systems. There are many artificial very low frequency communication stations worldwide, with operating frequencies ranging from 1kHz to 50kHz. The VLF electromagnetic waves emitted by ground based very low frequency artificial sources can be reflected back and forth between the ground and the ionosphere, and propagated to a distance using the Earth ionosphere Waveguide (EIWG). During the propagation process, some energy can also penetrate upwards into the ionosphere and propagate in the form of right-handed polarized whistler waves towards the top of the ionosphere and the magnetosphere, ultimately being received by satellites. Numerous studies have shown that the main energy attenuation of VLF electromagnetic waves propagating upwards occurs in the low ionosphere region, and after passing through the low ionosphere, their energy almost no longer decays. Therefore, the VLF signals received by satellites can effectively reflect low ionospheric information. The dataset used in this study is sourced from the electric field instrument data of the domestically launched Zhangheng-1 satellite, which can be downloaded and obtained from public websites. By processing the raw data, the dataset used in this study was obtained. 
description: VLF signal sources include lightning and some submarine communication systems. There are many artificial very low frequency communication stations worldwide, with operating frequencies ranging from 1kHz to 50kHz. The VLF electromagnetic waves emitted by ground based very low frequency artificial sources can be reflected back and forth between the ground and the ionosphere, and propagated to a distance using the Earth ionosphere Waveguide (EIWG). During the propagation process, some energy can also penetrate upwards into the ionosphere and propagate in the form of right-handed polarized whistler waves towards the top of the ionosphere and the magnetosphere, ultimately being received by satellites. Numerous studies have shown that the main energy attenuation of VLF electromagnetic waves propagating upwards occurs in the low ionosphere region, and after passing through the low ionosphere, their energy almost no longer decays. Therefore, the VLF signals received by satellites can effectively reflect low ionospheric information. The dataset used in this study is sourced from the electric field instrument data of the domestically launched Zhangheng-1 satellite, which can be downloaded and obtained from public websites. By processing the raw data, the dataset used in this study was obtained.
DOI: 10.57760/sciencedb.16716
title: A MWISP dataset of 12CO/13CO emissions toward the Cygnus region
title: A MWISP dataset of 12CO/13CO emissions toward the Cygnus region

description: The Milky Way Imaging Scroll Painting (Su et al. 2019) project is an ongoing CO survey by using the PMO-13.7 m millimeter-wavelength telescope at Delingha, China. The survey observes 12CO, 13CO and C18O simultaneously toward the northern Galactic plane. The data cube to Cygnus is clipped in the range, l : 72º ~ 87º, b : -5.1º ~ 5.1º. We resampled the velocity channels of all three lines to 0.2 km•s-1 (the corresponding RMS level is 0.42 K for 12CO, 0.22 K for 13CO and C18O) to reduce the bias in data processing. The resultant data are in -45 ~ 40 km•s-1, covering the major emission of Cygnus. The uploaded data is reduced using a moment masking method: pixels with three consecutive channels larger than 3 times the noise RMS for 12CO, and all fitted pixels based on Gaussian decomposition in this work for 13CO, respectively.All data cubes are presented in standard FITS format, which can be read by SAO DS9, IDL, and astropy module in Python, etc.
description: The Milky Way Imaging Scroll Painting (Su et al. 2019) project is an ongoing CO survey by using the PMO-13.7 m millimeter-wavelength telescope at Delingha, China. The survey observes 12CO, 13CO and C18O simultaneously toward the northern Galactic plane. The data cube to Cygnus is clipped in the range, l : 72º ~ 87º, b : -5.1º ~ 5.1º. We resampled the velocity channels of all three lines to 0.2 km•s-1 (the corresponding RMS level is 0.42 K for 12CO, 0.22 K for 13CO and C18O) to reduce the bias in data processing. The resultant data are in -45 ~ 40 km•s-1, covering the major emission of Cygnus. The uploaded data is reduced using a moment masking method: pixels with three consecutive channels larger than 3 times the noise RMS for 12CO, and all fitted pixels based on Gaussian decomposition in this work for 13CO, respectively.All data cubes are presented in standard FITS format, which can be read by SAO DS9, IDL, and astropy module in Python, etc.
DOI: 10.57760/sciencedb.j00139.00119
title: Haplotype-resolved and chromosome-scale genome of Amur leopard
title: 东北豹染色体单倍型基因组

description: By collecting blood samples from a rescued Amur leopard in the wild, we successfully assembled a high-quality genome for this species, with a genome size of 2.42 Gb and a scaffold N50 value of 146.59 Mb. More than 2.40 Gb scaffolds (~99.34%) were anchored to 19 chromosome-scale pseudomolecules with a complete X chromosome identified
description: By collecting blood samples from a rescued Amur leopard in the wild, we successfully assembled a high-quality genome for this species, with a genome size of 2.42 Gb and a scaffold N50 value of 146.59 Mb. More than 2.40 Gb scaffolds (~99.34%) were anchored to 19 chromosome-scale pseudomolecules with a complete X chromosome identified
DOI: 10.57760/sciencedb.09463
title: AirCore at northern Tibetan Plateau during Asian Summer Monsoon
title: AirCore at northern Tibetan Plateau during Asian Summer Monsoon

description: The dataset including CO, CH4 (from AirCore), O3 (ozone sonde) and particles (POPS) from surface to 25 km over northern Tibetan Plateau during summer 2020. The backward trajectory are calculated along each measurement point of AirCore using CLaMS driven by ERA5.
description: The dataset including CO, CH4 (from AirCore), O3 (ozone sonde) and particles (POPS) from surface to 25 km over northern Tibetan Plateau during summer 2020. The backward trajectory are calculated along each measurement point of AirCore using CLaMS driven by ERA5.
DOI: 10.57760/sciencedb.j00186.00396
title: NRIs-IQA dataset
title: NRIs-IQA dataset

description: The uploaded data set contains 20000 multi-degraded neutron-radiographic-Image quality data sets with image quality labels and 30 high-quality neutron radiographic Images generated by high-flux equipments such as reactors and accelerators. The neutron-radiographic-Image quality data set and the corresponding image quality labels are generated by the proposed method.
description: The uploaded data set contains 20000 multi-degraded neutron-radiographic-Image quality data sets with image quality labels and 30 high-quality neutron radiographic Images generated by high-flux equipments such as reactors and accelerators. The neutron-radiographic-Image quality data set and the corresponding image quality labels are generated by the proposed method.
DOI: 10.57760/sciencedb.16788
title: Punishment fMRI project
title: Punishment fMRI project

description: Behavioral and fMRI data2024.03.08 updated (please use the updated version)
description: Behavioral and fMRI data2024.03.08 updated (please use the updated version)
DOI: 10.57760/sciencedb.ecodb.00199
title: The canopy structure and topography dataset of Zhejiang Gutianshan 24-ha forest dynamics plot in a subtropical evergreen broadleaf forest in 2018
title: 2018年浙江古田山24公顷亚热带常绿阔叶林动态监测样地林冠结构和地形数据集

description: This study selected a 24-ha subtropical evergreen broadleaf forest dynamic plot located in the core conservation area of Qianjiangyuan National Park as the research subject. The point cloud data obtained in 2018 based on near-surface remote sensing technology for this area was analyzed and quality-controlled to acquire canopy structure and topography data. This dataset comprises three files: canopy structure data, topography data and quality report. the spatial resolution of the dataset is 20m.
description: This study selected a 24-ha subtropical evergreen broadleaf forest dynamic plot located in the core conservation area of Qianjiangyuan National Park as the research subject. The point cloud data obtained in 2018 based on near-surface remote sensing technology for this area was analyzed and quality-controlled to acquire canopy structure and topography data. This dataset comprises three files: canopy structure data, topography data and quality report. the spatial resolution of the dataset is 20m.