Antagonistic modulation of myosin conformational dynamics by sanshool and smoke-derived aldehydes: A molecular basis for heterocyclic amine control in thermal processing - Hongyu Deng; Jie Jia; Lihui Feng; Siwei Xiong; Hemei Yuan; Zhiyuan Fang; Qiulan Li; Shengjie Duan; Hongkang Zhu; Ya Wang; Jun Sheng; Yanping Huang; et al. (Food Chemistry, 2026)

A new method of consistency evaluation of brain drugs: a case study of edaravone - Liqiang Gu; Yanping Hu; Yinfang Lai; Sheng Zhang; Haoran Wang; Xiaozhen Xu; Lingfang Chen; Yuhua Shi; Jiechao Chen; Xiaochun Sun; Yuan Zhang; Lingzhi Hu (Regulatory Toxicology and Pharmacology, 2025)

Towards targeted heat resilience: A conceptual framework of urban heat-proof in Chengdu, China - Yutong Li; Sining Zhang; Xiaopeng Li; Shixian Luo; Qingling Liu; Yanping Zhong; Sheng Liu (Sustainable Cities and Society, 2025)

Multi-objective decision-making considering future demands helps to delineate key areas for ecological restoration in Changsha-Zhuzhou-Xiangtan urban agglomeration, China - Tao Li; Sheng Li; Yanping Zhao; Hua Zheng; Kuan Wang; Mi Yi (Journal of Environmental Management, 2025)

Mechanism and application of the Lagrangian flow network method to indicate practical material distribution patterns in the tide-dominated Bohai Sea with multi-frequency tides - Jinzhen Yu; Xueqing Zhang; Xiaoxuan Sheng; Fangjing Deng; Yanping Wang; Wensheng Jiang; Jihong Zhang (Ocean Modelling, 2025)

Review of utilization of bamboo fiber in asphalt modification: Insights into preparation, performance, reinforcement, and challenges - Haibin Li; Songjiang Liu; Fan Yang; Siyu He; Hongjun Jing; Xiaolong Zou; Zhigang Li; Yanping Sheng (Journal of Cleaner Production, 2024)

A highly sensitive SERS substrate of porous membrane-Ag NPs for kidney cancer detection - Sheng Chen; Jiamin Gao; Hongyi Zhang; Li Liu; Feng Lin; Zaijun Cheng; Yanping Chen; Dongyu Guo; Xingen Gao; Juqiang Lin (Analytica Chimica Acta, 2024)

Identification, characterisation and expression analysis of peanut sugar invertase genes reveal their vital roles in response to abiotic stress - Tingting Mao; Yaru Zhang; Wenwen Xue; Yu Jin; Hongfei Zhao; Yibo Wang; Shengnan Wang; Shengjie Zhuo; Feifei Gao; Yanping Su; Chunyan Yu; Xiaotong Guo; et al. (Plant Cell Reports, 2024)

Study on thermal properties of bio-char prepared by photo-thermal pyrolysis - Dexin Huang; Yankui Wang; Gongxiang Song; Song Hu; Hanjian Li; Yanping Zhang; Yi Wang; Sheng Su; Saad A. El-Sayed; Jun Xiang (Biomass and Bioenergy, 2023)

Sentinel supervised lung-on-a-chip: A new environmental toxicology platform for nanoplastic-induced lung injury - Sheng Yang; Tianyi Zhang; Yiling Ge; Yanping Cheng; Lihong Yin; Yuepu Pu; Zaozao Chen; Geyu Liang (Journal of Hazardous Materials, 2023)

Impact of waste of COVID-19 protective equipment on the environment, animals and human health: a review - Sheng Yang; Yanping Cheng; Tong Liu; Shaoping Huang; Lihong Yin; Yuepu Pu; Geyu Liang (Environmental Chemistry Letters, 2022)

An Improved Dueling Deep Double-Q Network Based on Prioritized Experience Replay for Path Planning of Unmanned Surface Vehicles - Zhengwei Zhu; Can Hu; Chenyang Zhu; Yanping Zhu; Yu Sheng (Journal of Marine Science and Engineering, 2021)
Unmanned Surface Vehicle (USV) has a broad application prospect and autonomous path planning as its crucial technology has developed into a hot research direction in the field of USV research. This paper proposes an Improved Dueling Deep Double-Q Network Based on Prioritized Experience Replay (IPD3QN) to address the slow and unstable convergence of traditional Deep Q Network (DQN) algorithms in autonomous path planning of USV. Firstly, we use the deep double Q-Network to decouple the selection and calculation of the target Q value action to eliminate overestimation. The prioritized experience replay method is adopted to extract experience samples from the experience replay unit, increase the utilization rate of actual samples, and accelerate the training speed of the neural network. Then, the neural network is optimized by introducing a dueling network structure. Finally, the soft update method is used to improve the stability of the algorithm, and the dynamic ϵ-greedy method is used to find the optimal strategy. The experiments are first conducted in the Open AI Gym test platform to pre-validate the algorithm for two classical control problems: the Cart pole and Mountain Car problems. The impact of algorithm hyperparameters on the model performance is analyzed in detail. The algorithm is then validated in the Maze environment. The comparative analysis of simulation experiments shows that IPD3QN has a significant improvement in learning performance regarding convergence speed and convergence stability compared with DQN, D3QN, PD2QN, PDQN, PD3QN. Also, USV can plan the optimal path according to the actual navigation environment with the IPD3QN algorithm.

Nucleotide diversity and molecular evolution of the PSY1 gene in Zea mays compared to some other grass species - Zhiyuan Fu; Jianbing Yan; Yanping Zheng; Marilyn L. Warburton; Jonathan H. Crouch; Jian-Sheng Li (Theoretical and Applied Genetics, 2010)

ABCC10, ABCC11, and ABCC12 - Gary D. Kruh; Yanping Guo; Elizabeth Hopper-Borge; Martin G. Belinsky; Zhe-Sheng Chen (Pflügers Archiv - European Journal of Physiology, 2007)