Modulating d-d orbital coupling in bifunctional NiMo alloy for enhanced overall water splitting - Bo Zhao; Mingpeng Chen; Jin Zhang; Huachuan Sun; Boran Zhao; Dequan Li; Yuewen Wu; Tong Zhou; Feng Liu; Hao Cui; Qingju Liu (Chemical Engineering Journal, 2026)

Environmental PET-microplastic exposure and risk of non-alcoholic fatty liver disease: An integrated computational toxicology and multi-omics study - Yu Yuan; Chunli Lin; Tianyu Zhang; Chao Song; Yuewen Sun; Hongzhen Tang (Naunyn-Schmiedeberg's Archives of Pharmacology, 2026)

Enterobacteriaceae-targeting tungsten nanoclusters for precision IBD therapy: A quadruple-action strategy integrating targeted delivery, ROS scavenging, microbiome reprogramming and anti-inflammation - Guangfu Feng; Minhui Xu; Huangbang Liang; Jiasheng Peng; Tao Sun; Yuanchun Du; Yuewen Huang; Jun Fang (Chemical Engineering Journal, 2026)

Co-activation of PET and willow impacts pore development via influencing occurrence of cracking and condensation reactions - Chengsen Song; Yuewen Shao; Yuchen Jiang; Kai Sun; Linghui Kong; Shu Zhang; Xun Hu (Fuel, 2026)

Preclinical Safety Assessment of the Oral Administration of Lactobacillus plantarum GUANKE in Animal Models - Yuewen Yang; Yanlin Zhang; Ruixiang Sun; Wenjuan Du; Yangyang Liu; Lijun Zheng; Zhihong Ren; Ming ding Li; Jianguo Xu (Probiotics and Antimicrobial Proteins, 2025)

Mathematical modeling and connectivity-enhanced segmentation of void fraction in two-phase flow CT images - Zirou Jiang; Shuo Xu; Jiahao Chang; Jichen Miao; Yuewen Sun (Annals of Nuclear Energy, 2025)

Chitin nanocrystal/carboxymethyl cellulose bilayer emulsion with rigid inner layer and flexible outer shell for ultra-stable encapsulation of fish oil - Yufei Sun; Qianxi Deng; Simeng Ji; Yuewen Li; Kao Wu; Ying Kuang; Fatang Jiang; Pengpeng Deng (Carbohydrate Polymers, 2025)

Nanofiltration membranes with ion-induced swelling for elevated water permeance in water treatment - Chenyi Fang; Muhammad Avicenna Naradipa; Yuewen Jia; Junyu Mi; Haoze Zeng; Joseph Imbrogno; Tim M. Swenson; Chenhao Yi; Shipeng Sun; Andrivo Rusydi; Sui Zhang (Water Research, 2025)

Carbon distribution and metabolism mechanism of a novel mixotrophic Chlorella in municipal wastewater - Xiaoyan Wang; Yu Hong; Yuewen Zhang; Dezhi Sun (Bioresource Technology, 2025)

Ni- and Co-based catalysts via alloying Ni and Co with Sn species for selective conversion of vanillin through tailoring hydrogenation and deoxygenation activity - Yuewen Shao; Mingzhu Guo; Linghui Kong; Mengjiao Fan; Kai Sun; Chao Li; Lijun Zhang; Shu Zhang; Tao Wei; Xun Hu (Fuel, 2025)

RC parameter identification and load aggregation analysis of air-conditioning systems: A multi-strategy improved black-winged kite algorithm - Mengran Zhou; Chunchen Shi; Feng Hu; Ziwei Zhu; Kun Wang; Xiangnan Sun; Yu Zhang; Mengcheng Zhou; Lehan Zhang; Yuewen Zhang (Energy and Buildings, 2025)

Corrigendum to “Multifunctional sodium alginate-based self-healing edible cross-linked coating for banana preservation” [Food Hydrocolloids 151 (2024) 109753] - Pengpeng Deng; Yunxin Zhang; Qianxi Deng; Yufei Sun; Yuewen Li; Zihao Wang; Fatang Jiang (Food Hydrocolloids, 2025)

Insights into selective chlorination volatilization behavior and process optimization of Cu in FexOy-Cu2O-CaCl2-SiO2 system - Hongyan Sun; Liquan Zhu; Xiaojun Hu; Zhongzi Chen; Yuewen Fan; Kuochih Chou (Journal of Environmental Chemical Engineering, 2025)

Reaction kinetics of H2O and CO2 with molten slag containing FeO for H2-CO gas production - Yuewen Fan; Yukang Zhou; Jiahe Sun; Xiaojun Hu (Fuel, 2025)

High strength, gas barrier and hydrophobic konjac glucomannan/glutenin films with semi-interpenetrating network for cherry tomato preservation - Pengpeng Deng; Zihao Wang; Yuewen Li; Simeng Ji; Yufei Sun; Qianxi Deng; Juanjuan Chen; Fatang Jiang (Food Hydrocolloids, 2025)

Identification and functional analysis of a novel L-type lectin (NdLTL1) from Neocaridina denticulata sinensis - Yuewen Jia; Yijie Liu; Wenli Zhang; Rongxiao Wang; Yuying Sun; Jiquan Zhang (Fish & Shellfish Immunology, 2025)

Importance of balanced distribution of metallic sites and acidic sites in Co/Ni-based catalysts for selective conversion of polycarbonate plastic into valuable chemicals - Yuewen Shao; Chengsen Song; Mengjiao Fan; Kai Sun; Guoming Gao; Chao Li; Lijun Zhang; Shu Zhang; Tao Wei; Xun Hu (Chemical Engineering Journal, 2025)

An advanced machine vision-based method for abnormal detection of transverse vibrations in ship propulsion shafting - Yongjiu Zou; Kexin Zhang; Fangyang Dong; Peng Zhang; Lele Cao; Si Luo; Xingjia Jiang; Taili Du; Shitao Peng; Yuewen Zhang; Peiting Sun; Minyi Xu (Ocean Engineering, 2024)

Preparation of activated carbon with recycled ZnCl2 for maximizing utilization efficiency of the activating agent and minimizing generation of liquid waste - Mengjiao Fan; Yuewen Shao; Yongqin Wang; Jing Sun; Huiru He; Yuchen Jiang; Shu Zhang; Yi Wang; Xun Hu (Chemical Engineering Journal, 2024)

Activation of poplar sawdust and anthracite coal: Distinct involvement of aliphatic and aromatic structures in pore development - Chao Li; Yifan Sun; Yuchen Jiang; Yuewen Shao; Guoming Gao; Shu Zhang; Yonggui Tang; Dong Wang; Xun Hu (Biomass and Bioenergy, 2024)

Optimization of process parameters for selective chlorination and volatilization in FeO-Cu2O-CaCl2 system - Hongyan Sun; Xiaojun Hu; Yuewen Fan; Shiming Guo; Kuochih Chou (Process Safety and Environmental Protection, 2024)

Prognostic Significance of Methyl-CpG Binding Domain4 Polymorphism rs140693 and Clinical Characteristics in Chinese Lung Cancer Patients - Zhengxing Li; Yuewen Hu; Chang Xu; Zixiu Zou; Zhenyu Sun; Zhunyi Gao; Man Xiao; Shicheng Guo; Yi Wang; Haijian Wang; Zhiping Wang; Qiang Li; et al. (Phenomics, 2024)

Alloying nickel with phosphorus to switch the selective conversion of furfural from furans to cyclopentanones or 1,4-pentanediol - Guoming Gao; Xun Hu; Yuewen Shao; Kai Sun; Chao Li; Qifeng Chen; Shu Zhang (Fuel, 2024)

Transcriptomic analyses of Pinctada fucata martensii responses under stress of titanium dioxide nanoparticles - Fengfeng Li; Jiaen Liu; Zixin Gao; Chuangye Yang; Liwei Sun; Yongshan Liao; Yuewen Deng (Frontiers in Marine Science, 2024)
Titanium dioxide nanoparticles (TiO 2 -NPs) released into the environment is becoming more prevalent due to their increased usage, marine TiO 2 -NPs contamination is escalating concerns in coastal areas. To understand the potential impact of TiO 2 -NPs on transcript changes in pearl oyster ( Pinctada fucata martensii ), transcriptome analysis on the gill tissues of pearl oysters was conducted after 14-day TiO 2 -NPs exposure and 7-day brief recovery. A total of 911 differentially expressed genes (DEGs) were identified between the control group (TC) and the experimental group (TE) exposed to 14-day TiO 2 -NPs. Gene ontology (GO) analyses of the DEGs demonstrated their substantial enrichments in functions related to “hydrolase activity”, “oxidoreductase activity”, and “DNA integration”. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways analyses of the DEGs indicated enrichment in several pathways, including “ubiquitin-mediated protein hydrolysis”, “ECM-receptor interactions”, “NOD-like receptor signaling pathway”, “Toll-like receptor”, and “FOXO signaling pathway”. This suggests that exposure to TiO 2 -NPs intensifies oxidative stress and apoptosis in pearls oysters, leading to negative effects such as disrupted protein homeostasis, decreased biomineralization activity, reduced neuronal excitability, weakened immune response, and reduced cellular metabolism. Transcriptome analysis identified 844 DEGs between the TE and recovery group (TR), which underwent a 7-day brief recovery period. GO analyses of the DEGs demonstrated their substantial enrichments in functions related to “DNA integration”, “obsolete oxidation-reduction process”, and “proteolysis”. KEGG pathways analyses of the DEGs indicated enrichment in several pathways, including “lysine degradation”, “glycine, serine, and threonine metabolism”, and “NOD-like receptor signaling pathway”. The findings indicated that although pearl oysters showed only slight relief after 7 days of brief recovery, they continued to experience negative effects from TiO 2 -NP exposure. Our findings shed light on the complex responses of pearl oysters to TiO 2 -NPs stress and offer valuable theoretical insights into the toxicological impact of TiO 2 -NPs on pearl oysters.

Bi-AAE: A binary adversarial autoencoder deep neural network model for anomaly detection in system-levels marine diesel engines - Peng Zhang; Chaozhe Li; Huanyun Xu; Yongjiu Zou; Kai Wang; Yuewen Zhang; Peiting Sun (Ocean Engineering, 2024)

Activation of spring jasmine wood impregnated with homologous bio-oil: Influence of organics in bio-oil on pore development - Linghui Kong; Yuewen Shao; Runxing Sun; Shu Zhang; Yi Wang; Jun Xiang; Song Hu; Dong Wang; Chuanjun Leng; Xun Hu (Fuel, 2024)

Multifunctional sodium alginate-based self-healing edible cross-linked coating for banana preservation - Pengpeng Deng; Yunxin Zhang; Qianxi Deng; Yufei Sun; Yuewen Li; Zihao Wang; Fatang Jiang (Food Hydrocolloids, 2024)

A Study of Adaptive Threshold Based on the Reconstruction Model for Marine Systems and Their Equipment Failure Warning - Xuxu Duan; Zeyu Gao; Zhenxing Qiao; Taili Du; Yongjiu Zou; Peng Zhang; Yuewen Zhang; Peiting Sun (Journal of Marine Science and Engineering, 2024)
To achieve the failure warning of marine systems and their equipment (MSAE), the threshold is one of the most prominent issues that should be solved first. In this study, a fusion model based on sparse Bayes and probabilistic statistical methods is applied to determine a new and more accurate adaptive alarm threshold. A multistep relevance vector machine (RVM) model is established to realize the parameter reconstruction in which the internal uncertainties caused by the degradation process and the external uncertainty caused by the loading, environment, and disturbances were considered. Then, a varying moving window (VMW) method is employed to determine the window size and achieve continuous data reconstruction. Further, the model based on Johnson distribution systems is utilized to complete the transformation of the residual parameters and calculate the adaptive threshold. Finally, the proposed adaptive decision threshold is successfully involved in the actual examples of the peak pressure and exhaust temperature of marine diesel engines. The results show that the proposed method can realize the continuous health condition monitoring of MSAE, successfully detect abnormal conditions in advance, achieve an early warning of failure, and reserve sufficient time for decision-making to prevent the occurrence of catastrophic disasters.

High yield of carbonaceous material from biomass via pyrolysis-condensation - Kai Sun; Yi Wang; Lijun Zhang; Yuewen Shao; Chao Li; Shu Zhang; Xun Hu (Chemical Engineering Journal, 2024)

Sustainable production of porous carbon from biomass: Influence of pre-carbonization on pore evolution and environment impact - Chao Li; Kai Sun; Yifan Sun; Yuewen Shao; Guoming Gao; Lijun Zhang; Shu Zhang; Xun Hu (Chemical Engineering Journal, 2024)

A precise method to calibrate a vessel's dynamic draft based on a single GNSS antenna - Yuewen Sun; Wenyi Duan; Fanlin Yang; Xianhai Bu; Miao Fan; Dongyue Tang; Yong Ma (Ocean Engineering, 2023)

Smoke Detection of Marine Engine Room Based on a Machine Vision Model (CWC-Yolov5s) - Yongjiu Zou; Jinqiu Zhang; Taili Du; Xingjia Jiang; Hao Wang; Peng Zhang; Yuewen Zhang; Peiting Sun (Journal of Marine Science and Engineering, 2023)
According to statistics, about 70% of ship fire accidents occur in the engine room, due to the complex internal structure and various combustible materials. Once a fire occurs, it is difficult to extinguish and significantly impacts the crew’s life and property. Therefore, it is urgent to design a method to detect the fire phenomenon in the engine room in real time. To address this problem, a machine vision model (CWC-YOLOv5s) is proposed, which can identify early fires through smoke detection methods. Firstly, a coordinate attention mechanism is added to the backbone of the baseline model (YOLOv5s) to enhance the perception of image feature information. The loss function of the baseline model is optimized by wise intersection over union, which speeds up the convergence and improves the effect of model checking. Then, the coordconv coordinate convolution layer replaces the standard convolution layer of the baseline model, which enhances the boundary information and improves the model regression accuracy. Finally, the proposed machine vision model is verified by using the ship video system and the laboratory smoke simulation bench. The results show that the proposed model has a detection precision of 91.8% and a recall rate of 88.1%, which are 2.2% and 4.6% higher than those of the baseline model.

Study of a Machine Vision Approach to Leak Monitoring of a Marine System - Xingjia Jiang; Yingwei Dai; Peng Zhang; Yucheng Wang; Taili Du; Yongjiu Zou; Yuewen Zhang; Peiting Sun (Journal of Marine Science and Engineering, 2023)
Leak monitoring is essential for the intelligent operation and maintenance of marine systems, and can effectively prevent catastrophic accidents on ships. In response to this challenge, a machine vision-based leak model is proposed in this study and applied to leak detection in different types of marine system in complex engine room environments. Firstly, an image-based leak database is established, and image enhancement and expansion methods are applied to the images. Then, Standard Convolution and Fast Spatial Pyramid Pooling modules are added to the YOLOv5 backbone network to reduce the floating-point operations involved in the leak feature channel fusion process, thereby improving the detection speed. Additionally, Bottleneck Transformer and Shuffle Attention modules are introduced to the backbone and neck networks, respectively, to enhance the feature representation performance, select critical information for the leak detection task, and suppress non-critical information to improve detection accuracy. Finally, the proposed model’s effectiveness is verified using leak images collected by the ship’s video system. The test results demonstrate that the proposed model exhibits excellent recognition performance for various types of leak, especially for drop-type leaks (for which the accuracy reaches 0.97).

Growth performance and biochemical composition of juvenile pearl oyster Pinctada martensii fed on artificial diets - Qingheng Wang; Chuangye Yang; Xiaodong Du; Xingwang Liu; Ruijiao Sun; Yuewen Deng (Aquaculture International, 2016)

Cloning and promoter activity of rat Smad1 5′-flanking region in rat hepatic stellate cells - Yu Sun; Jianghong Fan; Hong Shen; Ping Li; Peter Cattini; Yuewen Gong (Molecular and Cellular Biochemistry, 2007)