Dynamic characteristics and accumulated plastic deformation prediction of lithium slag filler for road applications based on interpretable machine learning - Hai Shi; Zhenghao Yu; Xiangjin Ji; Kun Yu; Mingzhou Bai; Daming Lin; Yin Cheng (Soil Dynamics and Earthquake Engineering, 2026)

The emerging high entropy materials for energy storage and conversion: Recent advances and future perspectives - Fangfei Lin; Runzhe Yao; Liyi Liu; Mengli Zhao; Junheng Wang; Fei Kang; De Li; Daming Chen; Panpan Zhang; Xing Lu; Yong Chen; Yaqing Wei (Chemical Engineering Journal, 2026)

The characteristics of wind-blown snow hazards and an in-situ wind tunnel experiment study on snow disaster prevention along railway - Shumao Qiu; Guoce Liu; Hai Shi; Daming Lin; Mingzhou Bai; Jun Hou (Natural Hazards, 2026)

Rational design of high entropy metal phosphide anode for highly reversible lithium storage - Liyi Liu; Xuhao Liu; Jianqiu Zhu; Zhihui Huo; Bin Chen; Wei Liang; Mingeng Li; Fangfei Lin; Mengli Zhao; De Li; Daming Chen; Zhen Wang; et al. (Chemical Engineering Journal, 2026)

Efficient preparation of large-area anisotropic graphite films with high thermal conductivity and excellent electromagnetic shielding performance - Zhihong Han; Mingyi Tan; Daming Chen; Wenzheng Zhang; Zhipeng Lin; Jiahui Zhou; Yuhao Fang; Shengze Zhang; Qihong Wei; Xinghong Zhang; Wenbo Han (Chemical Engineering Journal, 2025)

Rapid and accurate detection of total nitrogen in the different types for soil using laser-induced breakdown spectroscopy combined with transfer learning - Peng Lin; Changbo Song; Chongshan Yang; Mengjie Zhang; Shixiang Ma; Jiangtao Wen; Daming Dong; Yuxing Han (Computers and Electronics in Agriculture, 2024)

Long-range infrared absorption spectroscopy and fast mass spectrometry for rapid online measurements of volatile organic compounds from black tea fermentation - Chongshan Yang; Leizi Jiao; Chunwang Dong; Xuelin Wen; Peng Lin; Dandan Duan; Guanglin Li; Chunjiang Zhao; Xinglan Fu; Daming Dong (Food Chemistry, 2024)

Thermally managed and fireproof composite aerogels for safer and year-round energy saving - Wei Cai; Zhaoxin Li; Heng Xie; Wei Wang; Tianyang Cui; Bicheng Lin; Liangyuan Qi; Xin Hu; Yu Du; Yang Ming; Shuo Shi; Daming Chen; et al. (Chemical Engineering Journal, 2024)

Major genomic mutations driving hepatocellular carcinoma - Ran Chen; Moubin Lin; Daming Gao (Genome Instability & Disease, 2023)

Variable response of particles and inorganic carbon of two different soils during splash erosion - Chenjia Yuan; Junqiu Lin; Bing Wang; Daming Yang; Nufang Fang; Lingshan Ni; Zhihua Shi (CATENA, 2023)

Underwater Target Detection Based on Improved YOLOv7 - Kaiyue Liu; Qi Sun; Daming Sun; Lin Peng; Mengduo Yang; Nizhuan Wang (Journal of Marine Science and Engineering, 2023)
Underwater target detection is a crucial aspect of ocean exploration. However, conventional underwater target detection methods face several challenges such as inaccurate feature extraction, slow detection speed, and lack of robustness in complex underwater environments. To address these limitations, this study proposes an improved YOLOv7 network (YOLOv7-AC) for underwater target detection. The proposed network utilizes an ACmixBlock module to replace the 3 × 3 convolution block in the E-ELAN structure, and incorporates jump connections and 1 × 1 convolution architecture between ACmixBlock modules to improve feature extraction and network reasoning speed. Additionally, a ResNet-ACmix module is designed to avoid feature information loss and reduce computation, while a Global Attention Mechanism (GAM) is inserted in the backbone and head parts of the model to improve feature extraction. Furthermore, the K-means++ algorithm is used instead of K-means to obtain anchor boxes and enhance model accuracy. Experimental results show that the improved YOLOv7 network outperforms the original YOLOv7 model and other popular underwater target detection methods. The proposed network achieved a mean average precision (mAP) value of 89.6% and 97.4% on the URPC dataset and Brackish dataset, respectively, and demonstrated a higher frame per second (FPS) compared to the original YOLOv7 model. In conclusion, the improved YOLOv7 network proposed in this study represents a promising solution for underwater target detection and holds great potential for practical applications in various underwater tasks.

Hydrate-based adsorption-hydration hybrid approach enhances methane storage density in ZIF-8@AC - Guodong Zhang; Zhe Liu; Daming Liu; Yan Lin; Fei Wang (Chemical Engineering Journal, 2023)

Dynamics of soil organic carbon in different-sized aggregates under splash erosion - Junqiu Lin; Nufang Fang; Yan Zhang; Yi Zeng; Daming Yang; Wei Dai; Ling Wang; Zhihua Shi (Journal of Soils and Sediments, 2022)

Remote Detection of Hydrocarbon Microseepage in a Loess Covered Area - Liang Zhao; Daming Wang; Shengbo Chen; Lin Li; Tianyu Zhang (Journal of Earth Science, 2020)

Assessment of slope construction risk uncertainty based on index importance ranking - Daming Lin; Ping Chen; Jilei Ma; Yun Zhao; Tao Xie; Renmao Yuan; Lin Li (Bulletin of Engineering Geology and the Environment, 2019)

An engineering site suitability index (ESSI) for the evaluation of geological situations based on a multi-factor interaction matrix - Kun Li; Yanjun Shang; Wantong He; Daming Lin; Muhammad Hasan; Kaiyang Wang (Bulletin of Engineering Geology and the Environment, 2019)

Spatial relationship between climatic diversity and biodiversity conservation value - Junjun Wang; Ruidong Wu; Daming He; Feiling Yang; Peijun Hu; Shiwei Lin; Wei Wu; Yixin Diao; Yang Guo (Conservation Biology, 2018)
Capturing the full range of climatic diversity in a reserve network is expected to improve the resilience of biodiversity to climate change. Therefore, a study on systematic conservation planning for climatic diversity that explicitly or implicitly hypothesizes that regions with higher climatic diversity support greater biodiversity is needed. However, little is known about the extent and generality of this hypothesis. We used the case of Yunnan, southwest China, to quantitatively classify climatic units and modeled 4 climatic diversity indicators, including the variety (VCU), rarity (RCU), endemism (ECU) of climatic units, and a composite index of climatic diversity (CICD). We used 5 schemes that reliably identify priority conservation areas (PCAs) to identify areas with high biodiversity conservation value. We then investigated the spatial relationships between the 4 climatic diversity indicators and the results of the 5 PCA schemes and assessed the representation of climatic diversity within the existing nature reserves. The CICD was the best indicator of areas with high conservation value, followed by ECU and RCU. Contrary to conventional knowledge, VCU was not positively associated with biodiversity conservation value. The rarer or more endemic climatic units tended to have higher reserve coverage than the more common units. However, only 28 units, covering 10.5% of the land in Yunnan, had >17% of their areas protected. In addition to climatic factors, topography and human disturbances also significantly affected the relationship between climatic diversity and biodiversity conservation value. Our results suggest that climatic diversity can be an effective surrogate for establishing a more robust reserve network under climate change in Yunnan. Our study improves understanding of the relationship between climatic diversity and biodiversity and helps build an evidence‐based foundation for systematic conservation planning that targets climatic diversity in response to climate change.

Intelligent feeding control methods in aquaculture with an emphasis on fish: a review - Chao Zhou; Daming Xu; Kai Lin; Chuanheng Sun; Xinting Yang (Reviews in Aquaculture, 2018)
In aquaculture, feeding is the primary factor determining efficiency and cost, so it is important to know when to stop feeding to maximize efficiency. Until now, fish feeding has been mostly based on artificial discrimination, which is usually time‐consuming and laborious. In recent years, intelligent feeding control according to changes in behaviour and growth status has gained increasing attention. This approach involves many methods as well as monitoring and feedback equipment and can automatically determine the feeding demands of fish. This review summarizes the development of intelligent feeding control methods, such as mathematical models, acoustic methods and computer vision, in aquaculture over the past three decades. All methods have unique application scenarios and models for the culture to which they are most suitable, and the advantages and disadvantages of each method in the laboratory as well as in pond, cage and recirculating aquaculture systems are analysed. Studies show that improvements in sensor accuracy and hardware and software processing speed have promoted the development of new technologies and methods, providing effective or potential support for intelligent feeding control. However, its accuracy and intelligent are still need to be improved to meet the needs of actual feeding scenarios. Through close collaborations between engineers and fish behaviourists, the feeding machine and system will be more elaborate and precise on the basis of the above methods, and the level of intelligence will be further improved.

Correction to: Three dimensional characteristics of biopores and non-biopores in the subsoil respond differently to land use and fertilization - Zhongbin Zhang; Kailou Liu; Hu Zhou; Henry Lin; Daming Li; Xinhua Peng (Plant and Soil, 2018)

Three dimensional characteristics of biopores and non-biopores in the subsoil respond differently to land use and fertilization - Zhongbin Zhang; Kailou Liu; Hu Zhou; Henry Lin; Daming Li; Xinhua Peng (Plant and Soil, 2018)

Modification of rock mass strength assessment methods and their application in geotechnical engineering - Daming Lin; Kaiyang Wang; Kun Li; Wantong He; Weixing Bao; Renmao Yuan; Yanjun Shang (Bulletin of Engineering Geology and the Environment, 2017)

Deformation and failure of a tunnel in the restraining bend of a strike–slip fault zone: an example from Hengshan Mountain, Shanxi Province, China - Daming Lin; Renmao Yuan; Yanjun Shang; Weixing Bao; Kaiyang Wang; Zhongjian Zhang; Kun Li; Wantong He (Bulletin of Engineering Geology and the Environment, 2017)

Modifications to the GSI for granite in drilling - Daming Lin; Yan Sun; Wei Zhang; Renmao Yuan; Wantong He; Bo Wang; Yanjun Shang (Bulletin of Engineering Geology and the Environment, 2014)

Deposition rate and interaction of human-riverine from height increase and permanent function of an 1180 years weir in Southeast China - YanJun Shang; Hyeong-Dong Park; ZhiFa Yang; SiGuang Chen; DaMing Lin (Science China Earth Sciences, 2014)