Heterogeneous responses of the East Asian summer monsoon and hydroclimate in southwest China to Bond events during the Late Holocene - Bin Zhao; Tianxiang Fu; Zhigang Zhang; Kan Zhao; Zhenqiu Zhang; Qingfeng Shao; Yijia Liang; Yongjin Wang (Global and Planetary Change, 2026)

The long-term environmental evolution of an urban lake in the highly developed Yangtze River Delta - Zhenglan Fu; Longjuan Cheng; Qingfeng Jiang; Jiali Zhang; Xinyue Chen; Shuyi Yang; Xinyuan Gao; Xiang Kuai; Dejun Wan; Dongliang Ning; Bin Xue (Journal of Geographical Sciences, 2025)

Decrypting gene-spliced like and fast kinetic energy storage modes of Na/Mg dual doped manganese oxides cathode for high-performance aqueous zinc-ion batteries - Xiaosha Cui; Yaxiong Zhang; Qingfeng Wu; Sida Deng; Shengyuan Wang; Jiuzhou Wang; Yupeng Liu; Junli Zhang; Erqing Xie; Jiecai Fu (Chemical Engineering Journal, 2025)

Efficient As(III) removal from acidic wastewater by polymorphism control of FeS - Jing Chen; Qingfeng Dong; Jing Li; Chaobo Zhang; Guang Fu; Zhanqing Lu (Journal of Water Process Engineering, 2025)

Estimation of the Relative Chlorophyll Content of Carya illinoensis Leaves Using Fractional Order Derivative of Leaf and Canopy Scale Hyperspectral Data - Jiajia Xu; Genshen Fu; Lipeng Yan; Lei Yu; Fan Kuang; Qingfeng Huang; Xuehai Tang (Journal of Soil Science and Plant Nutrition, 2024)
Chlorophyll is a crucial physiological and biochemical indicator that impacts plant photosynthesis, accumulation of photosynthetic products, and final yield. The measurement and analysis of chlorophyll content in plants can provide valuable insights into their nutritional status and overall health. The non-destructive and efficient estimation of relevant plant physiological and biochemical indicators using hyperspectral technology can provide a reliable method for collecting data on nutrient levels and health status during plant growth and development. Fifty-three Carya illinoensis plants of Jiande and Changlin series known for their exceptional qualities and significant economic benefits were used as the research object for collecting their leaf and canopy hyperspectral data. Firstly, fractional order derivative (FOD) was used for spectral preprocessing. Secondly, the spectral response relationship between spectrum and relative chlorophyll content (soil and plant analyzer development, SPAD) was explored by combining single-band and two-band spectral index (normalized difference spectral index, NDSI). The correlation coefficient of Pearson correlation analysis was used to estimate the linear correlation between variables. Finally, the correlation between the spectral feature variables and SPAD was analyzed and calculated. Top 10 absolute values of the correlation coefficients were screened out as modeling variables. eXtreme gradient boosting (XGBoost) machine learning algorithm was used to construct the optimal estimation model of SPAD of Carya illinoensis leaves. Results showed that the correlation between leaf and canopy spectrum after FOD pretreatment and SPAD was substantially improved, compared with raw spectrum. FOD combined with leaf and canopy NDSI was more effective than single band in improving the correlation between spectral characteristics and target components, which was increased by 0.166 and 0.338, respectively. The leaf spectrum could estimate SPAD more accurately than that of canopy spectrum. The optimal SPAD model was the 0.5th-order derivative transformation combined with two-band leaf spectral index (NDSI) model. The R 2 P was 0.788, and the RMSEP was 0.842 in prediction set. On one hand, this study confirms the feasibility of rapid and non-destructive estimation of SPAD of Carya illinoensis leaves using hyperspectral technology. On the other hand, FOD combined with two-band spectral indices can significantly improve the response relationship between spectral characteristics and target variables, enrich hyperspectral data processing methods, and propose a novel approach for the detection of plant nutrient level and health.

Correction to: Clinical Significance and Influencing Factors of Microvascular Tissue Reperfusion After Macrovascular Recanalization - Xuesong Bai; Fan Yu; Qiuyue Tian; Wei Li; Arman Sha; Wenbo Cao; Yao Feng; Bin Yang; Yanfei Chen; Peng Gao; Yabing Wang; Jian Chen; et al. (Translational Stroke Research, 2023)

Low-dose graphene oxide promotes tumor cells proliferation by activating PI3K-AKT-mTOR signaling via cellular membrane protein integrin αV - Zhiwen Zheng; Abuduliaizezi Halifu; Juan Ma; Leyi Liu; Qingfeng Fu; Bocun Yi; E. Du; Dawei Tian; Yong Xu; Zhihong Zhang; Jianqiang Zhu (Environmental Pollution, 2023)

Clinical Significance and Influencing Factors of Microvascular Tissue Reperfusion After Macrovascular Recanalization - Xuesong Bai; Fan Yu; Qiuyue Tian; Wei Li; Araman Sha; Wenbo Cao; Yao Feng; Bin Yang; Yanfei Chen; Peng Gao; Yabing Wang; Jian Chen; et al. (Translational Stroke Research, 2023)

AIFM1 variants associated with auditory neuropathy spectrum disorder cause apoptosis due to impaired apoptosis-inducing factor dimerization - Yue Qiu; Hongyang Wang; Huaye Pan; Jing Guan; Lei Yan; Mingjie Fan; Hui Zhou; Xuanhao Zhou; Kaiwen Wu; Zexiao Jia; Qianqian Zhuang; Zhaoying Lei; et al. (Journal of Zhejiang University-SCIENCE B, 2023)

An intelligent model for early kick detection based on cost-sensitive learning - Peng Chi; Li Qingfeng; Fu Jianhong; Yang Yun; Zhang Xiaomin; Su Yu; Xu Zhaoyang; Zhong Chengxu; Wu Pengcheng (Process Safety and Environmental Protection, 2023)

The combined effect of titanium dioxide nanoparticles and cypermethrin on male reproductive toxicity in rats - Yuxin Li; Mingqing Zhong; Xianzhi He; Ruoyu Zhang; Yu Fu; Ruolan You; Feiyan Tao; Lei Fang; Yuanyuan Li; Qingfeng Zhai (Environmental Science and Pollution Research, 2022)