Article
Environmental Sciences
Aoxuan Chen, Jin Yang, Yan He, Qiangqiang Yuan, Zhengqiang Li, Liye Zhu
Summary: In this study, an ensemble machine-learning approach was developed to obtain a high spatiotemporal resolution dataset of aerosol optical depth (AOD). By filling the data gaps and using interpolation models, a full-coverage AOD dataset of three highly urbanized areas in 2020 was obtained. Validation against in-situ AOD observations showed satisfactory accuracy (R = 0.80), particularly in spring and summer. Overall, this ensemble machine-learning model provides an effective scheme for reconstructing AOD with high resolution, which can advance the near-real-time monitoring of air quality in urban areas.
SCIENCE OF THE TOTAL ENVIRONMENT
(2023)
Article
Environmental Sciences
Hao Lin, Siwei Li, Jia Xing, Jie Yang, Qingxin Wang, Lechao Dong, Xiaoyue Zeng
Summary: Recent studies have shown that combining observations from multiple satellites can improve the temporal-spatial coverage of high-resolution AOD measurements. The developed fusing retrieval algorithm demonstrated high accuracy and spatial continuity in retrieving AOD over urban areas. Moreover, the algorithm significantly enhanced the temporal resolution of high-resolution AOD observations.
Article
Environmental Sciences
Khang Chau, Meredith Franklin, Huikyo Lee, Michael Garay, Olga Kalashnikova
Summary: Exposure to PM2.5 air pollution has detrimental health effects and satellite-retrieved AOD can supplement PM2.5 exposure modeling efforts. Regional differences in predictive performance and variable importance were observed in the study on the Persian Gulf area, indicating the need for further research on incorporating spatial and temporal autocorrelations in machine learning models.
Article
Green & Sustainable Science & Technology
Jiwei Liu, Yong Sun, Qun Li
Summary: Accurately measuring the individual exposure level of PM2.5 is crucial for studying health effects, but challenges arise from the lack of historical data and limited ground monitoring. Techniques utilizing NASA's aerosol optical depth along with ground monitoring and meteorological data has proven effective in estimating PM2.5 concentrations near the ground. However, existing models fail to consider complexities such as lag effects and correlations between features, leading to accuracy issues. Various machine learning models have been explored to address the challenges, with the deep neural network model showing promising performance. Efforts to enhance estimation accuracy and overcome data processing challenges are ongoing.
Article
Environmental Sciences
Saleem Ibrahim, Martin Landa, Ondrej Pesek, Karel Pavelka, Lena Halounova
Summary: This paper introduces a machine learning-based scheme to predict air quality, with trained models reaching up to 95% prediction accuracy. The study found that AOD levels decreased in most European countries in 2020, but increased in some eastern and western countries. Additionally, there was a positive correlation between AOD and relative humidity, and a negative correlation between AOD and wind speed.
Article
Environmental Sciences
Zhendong Sun, Jing Wei, Ning Zhang, Yulong He, Yu Sun, Xirong Liu, Huiyong Yu, Lin Sun
Summary: This study developed an AOD retrieval algorithm for the GF-4 satellite, showing good robustness in both bright urban areas and dark rural areas. The accuracy of GF-4 AOD was slightly higher in rural areas compared to urban areas, and higher than the MOD04 3 km and 10 km dark target AOD.
Article
Environmental Sciences
Lijuan Chen, Ying Fei, Ren Wang, Peng Fang, Jiamei Han, Yong Zha
Summary: High temporal resolution aerosol optical depth (AOD) products are crucial for atmospheric environment and climate change studies. The study utilized GOCI data for AOD retrieval in the Yangtze River Delta, showing consistent results with AERONET observations. Solar angle was found to impact AOD retrieval accuracy, with errors peaking at noon due to inaccurate surface reflectance estimation.
Article
Environmental Sciences
Lingbin Kong, Jinyuan Xin, Wenkang Gao, Guiqian Tang, Xuemei Wang, Yuesi Wang, Wenyu Zhang, Weihua Chen, Shiguo Jia
Summary: The study used an aerosol mass spectrometer to measure the chemical composition of non-refractory submicron particles (NR-PM1) in Beijing. It found that organics were the primary component, with higher concentrations during winter when influenced by air masses from the south. Traffic resources contributed more to PM pollution than stationary resources, with organics and ammonium sulfate contributing more in polluted days.
SCIENCE OF THE TOTAL ENVIRONMENT
(2021)
Article
Green & Sustainable Science & Technology
Suhaimee Buya, Sasiporn Usanavasin, Hideomi Gokon, Jessada Karnjana
Summary: This study develops a model using satellite data to estimate daily PM2.5 concentrations in small regions of Thailand due to limited ground station data. Multiple linear regression and three machine learning models are used, and the random forest model performs the best. The model incorporates various factors and shows high accuracy in estimating PM2.5.
Article
Environmental Sciences
Tianning Zhang, Weihuan He, Hui Zheng, Yaoping Cui, Hongquan Song, Shenglei Fu
Summary: The study proposed a model using satellite data to estimate PM2.5 concentrations in China in 2017, showing good performance in temporal and spatial variability. The GBDT model excelled in estimating PM2.5 concentrations, especially in summer.
Article
Environmental Sciences
Weihuan He, Huan Meng, Jie Han, Gaohui Zhou, Hui Zheng, Songlin Zhang
Summary: This study used the MAIAC aerosol products and GBDT algorithm to retrieve PM2.5 concentration across China from 2015 to 2020 at a resolution of 1 km, achieving excellent performance. Overall, PM2.5 pollution in China showed a downward trend during the study period, with the greatest decrease observed in the Beijing-Tianjin-Hebei region. The results indicate significant improvement in the atmospheric environment, with an increase in areas meeting the national air quality standard.
Article
Environmental Sciences
Lianfa Li
Summary: This study developed an adaptive method and utilized an advanced algorithm to fill in a significant amount of missing AOD data in mainland China. By improving the model testing accuracy and generating ground aerosol coefficients, it provides new insights for estimating aerosol air pollutants.
Article
Environmental Sciences
Jian Zhou, Yingjie Li, Qingmiao Ma, Qiaomiao Liu, Weiguo Li, Zilu Miao, Changming Zhu
Summary: A window-based AOD retrieval algorithm is proposed to ignore unreliable/non-Lambertian pixels and retrieve AOD from Sentinel-2 images in Beijing region. The algorithm shows good agreement with ground-based measured AOD and exhibits comparable spatial distributions to MAIAC algorithm AOD products. The very little noise and high spatial continuity of retrieval AOD suggest its potential for improving AOD quality.
Article
Meteorology & Atmospheric Sciences
Min Zhao, Tie Dai, Hao Wang, Qing Bao, Yimin Liu, Hua Zhang, Guangyu Shi
Summary: Current global climate models with coarse resolution cannot accurately simulate the complex topography over the Tibetan Plateau. This study shows that a high-resolution model performs better in reproducing the spatial distribution and seasonal variations of aerosol compared to a low-resolution model. The fine-scale topographic forcing, such as in the eastern marginal region of the Tibetan Plateau, cannot be accurately simulated by a low-resolution model. Increasing the 10-m wind speed in winter leads to increased dust emissions. The aerosol direct radiative effects at the top of the atmosphere and at the surface over the Tibetan Plateau are -0.76 W m(-2) and -8.72 W m(-2) respectively.
ADVANCES IN ATMOSPHERIC SCIENCES
(2022)
Article
Environmental Sciences
Xinyu Yu, Mengzhu Xi, Liyang Wu, Hui Zheng
Summary: This study constructed an STW-LightGBM model considering the spatiotemporal characteristics of air pollution and estimated the PM2.5 concentration of China's surface at 1 km resolution from 2015 to 2020. The model performed well with fitting accuracy above 0.85 at different time scales and an average regression slope of 0.9 annually. The results showed improvement in PM2.5 pollution from 2015 to 2020 with a decrease in average concentration and a consistent distribution of elevated PM2.5 levels in certain regions.
Article
Oncology
Ling-Fang Zhang, Jun-Liang Li, Yan-Hong Wang, Xiao-Hui Tai, Le Liu, Xu-Xia Zhang, Yi-Wei An, Hong-Ling Li
Summary: This study explored the application value of F-18-fluorodeoxyglucose-positron emission tomography/computed tomography (F-18-FDG PET/CT) SUVmax in gastric cancer, and found that it can predict the pathological differentiation, HER-2 status, and Ki-67 index of gastric cancer patients to some extent.
CANCER BIOTHERAPY AND RADIOPHARMACEUTICALS
(2023)
Article
Chemistry, Physical
Dongzheng Wu, Yichao Zhuang, Fei Wang, Yang Yang, Jing Zeng, Jinbao Zhao
Summary: This study proposes a dual-functional design of V2O5 electrode with a rational honeycomb-like structure and rich oxygen vacancies to enhance the kinetics synergistically. The results demonstrate that the oxygen vacancies can enhance both the intrinsic electronic conductivity of V2O5 and the Mg2+ diffusion kinetics inside the cathode, resulting in good high-rate performance.
Article
Computer Science, Interdisciplinary Applications
Guoxian Zhang, Shu Yang, Wen Cui, Zhi Huang, Xiaogang Zhang, Yali Zhang, Junyan Li, Zhongmin Jin
Summary: This study decomposed the complex three-dimensional micromotion at the head-neck junction of modular hip prostheses and revealed the main forms of micromotion and their relationship with motion state. The findings provide design considerations for further experimental testing and facilitate the understanding of fretting mechanisms in hip prostheses.
COMPUTER METHODS IN BIOMECHANICS AND BIOMEDICAL ENGINEERING
(2023)
Article
Chemistry, Multidisciplinary
Changcheng Sun, Ying Li, Yutian Zhang, Haoyan Huang, Huili Chen, Jiaqin Chen, Luyao Han, Xiang Chen, Xijing Chen, Yongjie Zhang
Summary: This study evaluated the subacute toxicity and toxicokinetics of a potential anti-cancer drug candidate, pterostilbene, in rats. The results showed that pterostilbene had minimal subacute toxicity, and its systemic exposure appeared to be linear within the tested dose range. These findings strongly support further development of pterostilbene as a novel anti-cancer agent.
DRUG AND CHEMICAL TOXICOLOGY
(2023)
Article
Clinical Neurology
Meng Wang, Ying Han, Chun-Juan Wang, Tao Xue, Hong-Qiu Gu, Kai-Xuan Yang, Heng-Yi Liu, Man Cao, Xia Meng, Yong Jiang, Xin Yang, Jing Zhang, Yun-Yun Xiong, Xing-Quan Zhao, Li-Ping Liu, Yi-Long Wang, Tian-Jia Guan, Zi-Xiao Li, Yong-Jun Wang
Summary: Short-term exposure to PM2.5 is significantly associated with hospital admission for stroke in individuals with pre-existing medical histories, especially in older or female patients with AF. Preventive measures to reduce PM2.5 concentrations are particularly important in individuals with other medical co-morbidities.
INTERNATIONAL JOURNAL OF STROKE
(2023)
Article
Agriculture, Multidisciplinary
Junhua Li, Jiali Zhai, Cuihua Chang, Yanjun Yang, Calum J. Drummond, Charlotte E. Conn
JOURNAL OF THE SCIENCE OF FOOD AND AGRICULTURE
(2023)
Article
Environmental Sciences
Bo Liu, Xin-Yu Fang, Yu-Lu Yan, Jun Wu, Xiao-Jie Lv, Jie Zhang, Liang-Wei Qi, Ting-Ting Qian, Yu-Yu Cai, Yin-Guang Fan, Dong-Qing Ye
Summary: There is an association between ambient temperature and outpatient visits for warts, where both low and high temperatures increase the risk while a large temperature drop is protective. Males and younger individuals are more sensitive to temperature, while the elderly are more susceptible to temperature changes.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2023)
Article
Surgery
Qi Li, Jingwei Zhang, Zhiqiang Cai, Pengbo Jia, Xintuan Wang, Xilin Geng, Yu Zhang, Da Lei, Junhui Li, Wenbin Yang, Rui Yang, Xiaodi Zhang, Chenglin Yang, Chunhe Yao, Qiwei Hao, Yimin Liu, Zhihua Guo, Shubin Si, Zhimin Geng, Dong Zhang
Summary: A Bayesian network prediction model was developed to predict gallbladder polyps (GPs) with malignant potential. The study identified factors such as age, number of polyps, and polyp size that were associated with the malignant potential of GPs. The model showed good performance on both training and testing sets and provided a grading system for patients based on preoperative ultrasound.
SURGICAL ENDOSCOPY AND OTHER INTERVENTIONAL TECHNIQUES
(2023)
Article
Chemistry, Physical
Jindi Feng, Kunpeng Li, Mingkun Zheng, Wancheng Zhang, Yong Liu, Dengjing Wang, Zhenhua Zhang, Chao Zuo, Rui Xiong, Zhihong Lu
Summary: Magnetic tunnel junctions (MTJs) with efficient spin-filtering effect and large tunneling magnetoresistance (TMR) ratio are highly desirable in spintronics. This study investigates the spin-dependent transport properties of van der Waals (vdW) MTJs comprising a 2H-WSe2 tunnel barrier and a 1T-CrSe2 or 1T-MoSe2/1T-CrSe2 electrode. The dual-electrode MTJ exhibits excellent spin-filtering effect and a giant TMR ratio, attributed to the half-metallicity of CrSe2 induced by charge transfer at the electrode interface.
APPLIED SURFACE SCIENCE
(2023)
Article
Public, Environmental & Occupational Health
Hang Liang, Zhang Yue, Yimin Liu, Ziju Yan, Boyu Wang, Nan Xiang, Erpeng Liu
Summary: This study examined the association between mild cognitive impairment (MCI) and the risk of falls among Chinese older adults, as well as the mediating roles of balance capacity and depressive symptoms in this association. The results showed a significant association between MCI and falls, with balance capacity and depressive symptoms mediating this relationship.
Article
Materials Science, Ceramics
Shuhao Wang, Xiang Li, Jiajia Wang, Xiaojun Wu, Ling Li, Ji Zhang, Yaojin Wang
Summary: This study reports the synergistic contribution of engineered defect and domain structure in MnCO3-modified ceramics, which leads to excellent piezoelectric properties and mechanical quality factor, as well as enhanced thermal stability.
JOURNAL OF THE AMERICAN CERAMIC SOCIETY
(2023)
Article
Horticulture
Yan Wang, Zhen-Shan Liu, Xiao-Qin Yang, Zhi-Yi Wang, Lan Ma, Hong-Xia Tu, Yan Ma, Jing-Ting Zhou, Jing Zhang, Hao Wang, Qing Chen, Wen He, Shao-Feng Yang, Meng-Yao Li, Yuan-Xiu Lin, Yun-Ting Zhang, Yong Zhang, Ya Luo, Hao-Ru Tang, Xiao-Rong Wang
Summary: Chinese cherry is an important stone fruit in China. The variation of fruit-related traits was investigated in an F-1 segregating population derived from 'Hongfei' x 'Pujianghonghua' of Chinese cherry. Different degrees of variation were observed in the main fruit traits, and transgressive heterosis and negative heterosis were found in certain traits. The optimal genetic models for fruit maturity date and fruit development period were identified, and the heritability of major genes was high. The best genetic models for fruit size and flavor traits were also determined.
SCIENTIA HORTICULTURAE
(2023)
Article
Plant Sciences
Hongwen Yan, Songrui Cai, Qiangsheng Li, Feng Tian, Sitong Kan, Meimeng Wang
Summary: This study selected an intelligent detection model based on YOLOv5s for achieving the intelligent picking operation of daylily. By optimizing the depth and width parameters of the network and using lightweight networks such as Ghost, Transformer, and MobileNetv3 to optimize the backbone network, the model's performance was continuously improved. The optimized YOLOv5s model achieved accurate and fast detection of daylily in complex field environments, with improved mean average precision and inference speed compared to other models.
Article
Geosciences, Multidisciplinary
Feng Tian, Hong-Li Ren, Minghong Liu, Baohuang Su, Run Wang
Summary: This study extends the ENSO PB diagnosis method to quantify the PB intensity and timing of global SST anomalies. The results show that strong PBs of global SST anomalies are mainly found in the regions of the tropical Pacific and southeastern tropical Indian Ocean. The timing of PB occurrence varies globally and evolves along the equatorial Pacific band. These findings could be useful for oceanic predictions.
GEOSCIENCE LETTERS
(2023)
Article
Agronomy
Yixiao Zhang, Tao He, Shunlin Liang, Zhongguo Zhao
Summary: In this study, a framework for estimating actual evapotranspiration (ET) through interactive detector for spatial associations (IDSA)-based machine learning (ML) approaches was proposed. Data from remote sensing and four flux towers were combined to explore the determinants of ET and simulate ET using ML models. The results showed that the spatial patterns of ET were difficult to explain by individual environmental variables, but improved interpretability was achieved through the interaction of air temperature and normalized different vegetation index. The framework had excellent performance and was superior to general ML models at different scales.
AGRICULTURAL WATER MANAGEMENT
(2023)