期刊：
Expert Systems with Applications,2026年299:129968 ISSN：0957-4174
通讯作者：
Zhifeng Dai
作者机构：
[Huali Huang; Qinnan Jiang] College of Mathematics and Statistics, Changsha University of Science and Technology, Hunan, China;Beijing Huairou Laboratory, Bejing, 101499, Peoples R China;[Yaling Chen] School of Humanity and Management, Hunan University of Chinese Medicine, Changsha, Hunan, China;State Key Laboratory of Disaster Prevention & Reduction for Power Grid, Changsha University of Science & Technology, Changsha 410114, China;[Zhifeng Dai] College of Mathematics and Statistics, Changsha University of Science and Technology, Hunan, China<&wdkj&>Beijing Huairou Laboratory, Bejing, 101499, Peoples R China<&wdkj&>State Key Laboratory of Disaster Prevention & Reduction for Power Grid, Changsha University of Science & Technology, Changsha 410114, China
通讯机构：
[Zhifeng Dai] C;College of Mathematics and Statistics, Changsha University of Science and Technology, Hunan, China<&wdkj&>Beijing Huairou Laboratory, Bejing, 101499, Peoples R China<&wdkj&>State Key Laboratory of Disaster Prevention & Reduction for Power Grid, Changsha University of Science & Technology, Changsha 410114, China
摘要：
In order to better apply the advantages of deep learning models in crude oil price prediction, this paper proposes a novel deep learning combined model. It has a “decomposition and construction, dual-model parallel feature and extraction fully connected fusion” architecture, which combines the Transformer model with self-attention mechanism, the convolutional neural network (CNN) with local feature extraction in “parallel” and a fully connected neural network (FCN) to realize feature fusion. Firstly, the original price sequence is decomposed into multiple intrinsic mode functions through variational mode decomposition (VMD), and then the component with the highest Lempel-Ziv complexity (LZC) is processed by the empirical mode decomposition (EMD). Furthermore, model each component obtained from two decomposition using the Transformer-CNN model separately to obtain their predicted values. Finally, the final prediction results are derived from a linear combination of the predicted values of all components. Empirical analysis has demonstrated that the proposed model has better performance than benchmark models, and a series of tests have demonstrated its robustness. In conclusion, it represents a collaborative mechanism of decomposition as the foundation, dual models performing their respective duties, and fusion amplifying advantages. The application of this model in this paper significantly improves the forecasting accuracy of crude oil prices, which is helpful for investors and managers to grasp the trend of oil price changes and make response strategies.
In order to better apply the advantages of deep learning models in crude oil price prediction, this paper proposes a novel deep learning combined model. It has a “decomposition and construction, dual-model parallel feature and extraction fully connected fusion” architecture, which combines the Transformer model with self-attention mechanism, the convolutional neural network (CNN) with local feature extraction in “parallel” and a fully connected neural network (FCN) to realize feature fusion. Firstly, the original price sequence is decomposed into multiple intrinsic mode functions through variational mode decomposition (VMD), and then the component with the highest Lempel-Ziv complexity (LZC) is processed by the empirical mode decomposition (EMD). Furthermore, model each component obtained from two decomposition using the Transformer-CNN model separately to obtain their predicted values. Finally, the final prediction results are derived from a linear combination of the predicted values of all components. Empirical analysis has demonstrated that the proposed model has better performance than benchmark models, and a series of tests have demonstrated its robustness. In conclusion, it represents a collaborative mechanism of decomposition as the foundation, dual models performing their respective duties, and fusion amplifying advantages. The application of this model in this paper significantly improves the forecasting accuracy of crude oil prices, which is helpful for investors and managers to grasp the trend of oil price changes and make response strategies.
期刊：
Materials Science and Engineering B-Advanced Functional Solid-State Materials,2026年323:118759 ISSN：0921-5107
通讯作者：
Jincheng Fan
作者机构：
[Yifan Fang; Jincheng Fan; Risheng Hu; Haiou Liu; Bo Wu; Zhenqiang Tang; Wenbin Luo; Zisheng Chao] College of Materials Science and Engineering, Changsha University of Science and Technology, Changsha, Hunan 410114, China
通讯机构：
[Jincheng Fan] C;College of Materials Science and Engineering, Changsha University of Science and Technology, Changsha, Hunan 410114, China
摘要：
Supercapacitors are gaining prominence as energy storage devices due to their advantages such as fast charging and discharging, so there is an urgent need to develop higher performance devices. The electrode materials play a decisive role in the performance of supercapacitors. In this study, spinel CuNi 2 S 4 were synthesized by CuNi layered double hydroxides from Cu Metal-Organic Frameworks, which has a high specific capacitance of 7.1 F cm −2 (2784.3 F g −1 ). The capacitance retention rate of 79 % was retained after 5000 long cycles. A hybrid supercapacitor with CuNi 2 S 4 as cathode and activated carbon as anode was assembled with a specific capacitance of 423.6 mF cm −2 . The manufactured quasi-solid-state supercapacitor devices exhibit unique capacitance superposition properties in parallel configurations and voltage additive behavior in serial configurations. The fabricated solid-state supercapacitor-like devices show unique voltage stacking behavior in series configuration and capacitance stacking characteristics in parallel configuration.
Supercapacitors are gaining prominence as energy storage devices due to their advantages such as fast charging and discharging, so there is an urgent need to develop higher performance devices. The electrode materials play a decisive role in the performance of supercapacitors. In this study, spinel CuNi 2 S 4 were synthesized by CuNi layered double hydroxides from Cu Metal-Organic Frameworks, which has a high specific capacitance of 7.1 F cm −2 (2784.3 F g −1 ). The capacitance retention rate of 79 % was retained after 5000 long cycles. A hybrid supercapacitor with CuNi 2 S 4 as cathode and activated carbon as anode was assembled with a specific capacitance of 423.6 mF cm −2 . The manufactured quasi-solid-state supercapacitor devices exhibit unique capacitance superposition properties in parallel configurations and voltage additive behavior in serial configurations. The fabricated solid-state supercapacitor-like devices show unique voltage stacking behavior in series configuration and capacitance stacking characteristics in parallel configuration.
作者机构：
School of Hydraulic and Ocean Engineering, Changsha University of Science & Technology, Changsha 410114, China;Key Laboratory of Dongting Lake Aquatic Eco-Environmental Control and Restoration of Hunan Province, Changsha 410114, China;[Yanxiao Wei] RIKEN Center for Sustainable Resource Science, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan;[Jianhong Jiang; Qingchang Tang] China Machinery International Engineering Design & Research Institute Co., Ltd., Changsha 410007, China;[Xinying Kong] School of Chemistry and Chemical Engineering, University of South China, Hengyang, Hunan 421001, China
通讯机构：
[Hong Chen] S;School of Hydraulic and Ocean Engineering, Changsha University of Science & Technology, Changsha 410114, China<&wdkj&>Key Laboratory of Dongting Lake Aquatic Eco-Environmental Control and Restoration of Hunan Province, Changsha 410114, China
摘要：
To explore the adaptive mechanisms of the partial nitritation-anammox (PNA) process under high salinity stress during kitchen wastewater treatment, focusing on their physiological and molecular responses through metagenomic analysis. An airlift inner-circulation partition bioreactor (AIPBR) was developed, featuring an inner cylinder and a flow guide tube to create distinct oxygen gradients, facilitating the study of microbial adaptation under varying salt conditions. The AIPBR was operated with synthetic wastewater containing ammonium concentrations of 1800 ± 100 mg/L and salinity gradients ranging from 1 to 10 g/L, followed by a fixed salinity period at 6 g/L, with ammonium concentrations approximately 850 mg/L. High-throughput metagenomic analysis revealed shifts in functional genes and metabolic pathways in response to salinity stress. Anammox bacteria adapted by enriching genes involved in the synthesis of osmoprotective compounds and activating energy-producing pathways like the tricarboxylic acid cycle (TCA). These adaptations, along with modifications in membrane composition, were essential for sustaining system stability under elevated salinity. Under prolonged high salinity stress, anaerobic ammonium oxidizing (AnAOB) exhibited improved salt tolerance, maintaining a total nitrogen removal efficiency above 85 % and stabilizing after an adaptation phase. The metagenomic data revealed a marked enrichment of genes associated with ion transport, stress response mechanisms, and DNA repair pathways. Changes in microbial community composition favored salt-tolerant species, supporting system stability. These findings highlight the applicability of the developed bioreactor for scaling up the PNA process to handle high-salinity wastewater, providing a promising avenue for sustainable nitrogen removal in challenging environments.
To explore the adaptive mechanisms of the partial nitritation-anammox (PNA) process under high salinity stress during kitchen wastewater treatment, focusing on their physiological and molecular responses through metagenomic analysis. An airlift inner-circulation partition bioreactor (AIPBR) was developed, featuring an inner cylinder and a flow guide tube to create distinct oxygen gradients, facilitating the study of microbial adaptation under varying salt conditions. The AIPBR was operated with synthetic wastewater containing ammonium concentrations of 1800 ± 100 mg/L and salinity gradients ranging from 1 to 10 g/L, followed by a fixed salinity period at 6 g/L, with ammonium concentrations approximately 850 mg/L. High-throughput metagenomic analysis revealed shifts in functional genes and metabolic pathways in response to salinity stress. Anammox bacteria adapted by enriching genes involved in the synthesis of osmoprotective compounds and activating energy-producing pathways like the tricarboxylic acid cycle (TCA). These adaptations, along with modifications in membrane composition, were essential for sustaining system stability under elevated salinity. Under prolonged high salinity stress, anaerobic ammonium oxidizing (AnAOB) exhibited improved salt tolerance, maintaining a total nitrogen removal efficiency above 85 % and stabilizing after an adaptation phase. The metagenomic data revealed a marked enrichment of genes associated with ion transport, stress response mechanisms, and DNA repair pathways. Changes in microbial community composition favored salt-tolerant species, supporting system stability. These findings highlight the applicability of the developed bioreactor for scaling up the PNA process to handle high-salinity wastewater, providing a promising avenue for sustainable nitrogen removal in challenging environments.
作者机构：
School of Civil and Environmental Engineering, Changsha University of Science & Technology, Changsha 410114, China;Key Laboratory of Safety Control of Bridge Engineering of Ministry of Education, Changsha University of Science & Technology, Changsha 410114, China;[Chao-Huang Cai] College of Architecture and Civil Engineering, Beijing University of Technology, Beijing 100124, China;[Zhao-Hui Lu] Key Laboratory of Urban Security and Disaster Engineering of Ministry of Education, Beijing University of Technology, Beijing 100124, China;[Yu Leng] School of Civil and Environmental Engineering, Changsha University of Science & Technology, Changsha 410114, China<&wdkj&>Key Laboratory of Safety Control of Bridge Engineering of Ministry of Education, Changsha University of Science & Technology, Changsha 410114, China
通讯机构：
[Chao-Huang Cai] C;College of Architecture and Civil Engineering, Beijing University of Technology, Beijing 100124, China
摘要：
Failure probability of a structure is dominated by the importance domain whose extent is much smaller than the whole random variable space. Once the importance domain is identified, the failure probability can be evaluated efficiently through compressing the sampling space into the importance domain. Recently, ring simulation has attempted to identify the importance interval in one dimension (i.e., the radius). To obtain a complete importance domain in all dimensions, a new simulation method, called “partial ring simulation”, is proposed for the efficient estimation of the failure probability. In the proposed method, the importance domain, consisting of importance radius and importance direction, is adaptively identified by a stepwise strategy utilizing the information from prior steps. For generating samples located in the importance domain, a Markov chain Monte Carlo sampling is then constructed. The effectiveness of the proposed method is validated by four examples involving parallel, series, and nonlinear limit state functions, small failure probabilities, and high-dimensional problems. The results indicate that the proposed method greatly improves the computational efficiency of ring simulation.
Failure probability of a structure is dominated by the importance domain whose extent is much smaller than the whole random variable space. Once the importance domain is identified, the failure probability can be evaluated efficiently through compressing the sampling space into the importance domain. Recently, ring simulation has attempted to identify the importance interval in one dimension (i.e., the radius). To obtain a complete importance domain in all dimensions, a new simulation method, called “partial ring simulation”, is proposed for the efficient estimation of the failure probability. In the proposed method, the importance domain, consisting of importance radius and importance direction, is adaptively identified by a stepwise strategy utilizing the information from prior steps. For generating samples located in the importance domain, a Markov chain Monte Carlo sampling is then constructed. The effectiveness of the proposed method is validated by four examples involving parallel, series, and nonlinear limit state functions, small failure probabilities, and high-dimensional problems. The results indicate that the proposed method greatly improves the computational efficiency of ring simulation.
期刊：
Journal of Physics and Chemistry of Solids,2026年208:113148 ISSN：0022-3697
通讯作者：
Junfei Duan
作者机构：
[Jinyan Tang; Jingtian Tong; Hao He; Tianjian Xu; Jinzheng Yang; Dan Huang; Zhaoyong Chen; Junfei Duan] School of Materials Science and Engineering, Changsha University of Science and Technology, Changsha, 410114, China
通讯机构：
[Junfei Duan] S;School of Materials Science and Engineering, Changsha University of Science and Technology, Changsha, 410114, China
摘要：
Aqueous zinc-nickel batteries suffer from severe anode challenges including dendrite growth, self-corrosion, and hydrogen precipitation, which drastically limit their cycle life and performance. Herein, a novel chemical foaming strategy was proposed to scalably fabricate ZnO@Bi 2 O 3 heterostructures. ZnO nanocrystals (∼30–80 nm) intimately integrate with Bi 2 O 3 via chemically bonded heterointerfaces were prepared combined with thermal decomposition of zinc nitrate hexahydrate and the physical confinement of polyvinylpyrrolidone. Depth-profiling XPS analysis confirms that Bi 2 O 3 not only forms a permeable barrier against alkaline electrolyte penetration but also induces interfacial charge redistribution via Bi–O–Zn covalent bonding, which regulates Zn(OH) 4 2− migration pathways and suppresses dendrite formation and electrode corrosion. The optimized ZnO@Bi 2 O 3 -M electrode delivers a coulombic efficiency of over 80 % after 600 cycles at 25 mA cm −2 , accompanied by a specific capacity of 481.8 mAh g −1 , and maintains 167.7 mAh g −1 even at 60 mA cm −2 . This study proposes a novel design strategy for high-performance aqueous zinc-nickel battery anode materials via interfacial engineering, coupled with a scalable synthesis route paving the way for industrial implementation.
Aqueous zinc-nickel batteries suffer from severe anode challenges including dendrite growth, self-corrosion, and hydrogen precipitation, which drastically limit their cycle life and performance. Herein, a novel chemical foaming strategy was proposed to scalably fabricate ZnO@Bi 2 O 3 heterostructures. ZnO nanocrystals (∼30–80 nm) intimately integrate with Bi 2 O 3 via chemically bonded heterointerfaces were prepared combined with thermal decomposition of zinc nitrate hexahydrate and the physical confinement of polyvinylpyrrolidone. Depth-profiling XPS analysis confirms that Bi 2 O 3 not only forms a permeable barrier against alkaline electrolyte penetration but also induces interfacial charge redistribution via Bi–O–Zn covalent bonding, which regulates Zn(OH) 4 2− migration pathways and suppresses dendrite formation and electrode corrosion. The optimized ZnO@Bi 2 O 3 -M electrode delivers a coulombic efficiency of over 80 % after 600 cycles at 25 mA cm −2 , accompanied by a specific capacity of 481.8 mAh g −1 , and maintains 167.7 mAh g −1 even at 60 mA cm −2 . This study proposes a novel design strategy for high-performance aqueous zinc-nickel battery anode materials via interfacial engineering, coupled with a scalable synthesis route paving the way for industrial implementation.
期刊：
Materials Science in Semiconductor Processing,2026年201:110108 ISSN：1369-8001
通讯作者：
Chen, JL
作者机构：
[Peng, Zhuoyin; Pei, Caiyu; Zhang, Siyuan; Wang, Zixian; Wu, Zihan; Wang, Jiaqing; Chen, Jian; Chen, Jianlin; Li, Chi; Zhao, Siyuan; Huang, Jincheng; Chang, Di] Changsha Univ Sci & Technol, Sch Energy & Power Engn, Key Lab Renewable Energy Elect Technol Hunan Prov, Changsha 410114, Peoples R China.;[Shi, Yifei] Changsha Univ Sci & Technol, State Key Lab Disaster Prevent & Reduct Power Grid, Changsha 410114, Peoples R China.
通讯机构：
[Chen, JL ] C;Changsha Univ Sci & Technol, Sch Energy & Power Engn, Key Lab Renewable Energy Elect Technol Hunan Prov, Changsha 410114, Peoples R China.
关键词：
Inorganic perovskite solar cells;CsPbI2Br;Bulk modification;Cesium fluoride;Additives
摘要：
The inorganic perovskite solar cells (PSCs) exhibit superior thermal stability to the organic-inorganic hybrid PSCs. However, halide defects with low formation energy are often present at grain boundaries of the inorganic perovskite films. This results in many defects of Pb 2+ uncoordinated with halides, causing in non-radiative recombination in the films. In this work, cesium fluoride (CsF) was chosen as an additive in the CsPbI 2 Br precursor solution, in which Cs + can passivate the A-site vacancy defects in CsPbI 2 Br perovskite films; fluoride ion (F − ) has a smaller ionic radius and is more electronegative than chloride ion (Cl − ), iodide ion (I − ), and bromide ion (Br − ), which may allow it to fit in the smaller spaces in the host lattice, as well as weaken the lattice strain and improve the stability of the desired phase. Based on this strategy, CsF-treated carbon-based hole-transport-layer-free CsPbI 2 Br PSCs were obtained with a champion photovoltaic conversion efficiency of 13.45 %, short-circuit current density of 15.15 mA/cm 2 , open-circuit voltage of 1.18 V, and fill factor of 75 %. Meanwhile, the CsF-treated CsPbI 2 Br PSCs possessed better environmental stability compared to the un-treated counterpart due to the introduction of the more hydrophobic F − . This strategy provides a simple and feasible strategy for the development of efficient and stable inorganic PSCs.
The inorganic perovskite solar cells (PSCs) exhibit superior thermal stability to the organic-inorganic hybrid PSCs. However, halide defects with low formation energy are often present at grain boundaries of the inorganic perovskite films. This results in many defects of Pb 2+ uncoordinated with halides, causing in non-radiative recombination in the films. In this work, cesium fluoride (CsF) was chosen as an additive in the CsPbI 2 Br precursor solution, in which Cs + can passivate the A-site vacancy defects in CsPbI 2 Br perovskite films; fluoride ion (F − ) has a smaller ionic radius and is more electronegative than chloride ion (Cl − ), iodide ion (I − ), and bromide ion (Br − ), which may allow it to fit in the smaller spaces in the host lattice, as well as weaken the lattice strain and improve the stability of the desired phase. Based on this strategy, CsF-treated carbon-based hole-transport-layer-free CsPbI 2 Br PSCs were obtained with a champion photovoltaic conversion efficiency of 13.45 %, short-circuit current density of 15.15 mA/cm 2 , open-circuit voltage of 1.18 V, and fill factor of 75 %. Meanwhile, the CsF-treated CsPbI 2 Br PSCs possessed better environmental stability compared to the un-treated counterpart due to the introduction of the more hydrophobic F − . This strategy provides a simple and feasible strategy for the development of efficient and stable inorganic PSCs.
作者机构：
[Dian Zheng; Yameng Zhang; Jiaxin Liu; Yongqi Wang; Shiyu Chen; Sili Tan] School of Hydraulic and Ocean Engineering, Changsha University of Science & Technology, Changsha 410014, PR China;Key Laboratory of Dongting Lake Aquatic Eco-Environmental Control and Restoration of Hunan Province, Changsha, PR China;[Guanlong Yu] School of Hydraulic and Ocean Engineering, Changsha University of Science & Technology, Changsha 410014, PR China<&wdkj&>Key Laboratory of Dongting Lake Aquatic Eco-Environmental Control and Restoration of Hunan Province, Changsha, PR China
通讯机构：
[Guanlong Yu] S;School of Hydraulic and Ocean Engineering, Changsha University of Science & Technology, Changsha 410014, PR China<&wdkj&>Key Laboratory of Dongting Lake Aquatic Eco-Environmental Control and Restoration of Hunan Province, Changsha, PR China
摘要：
Excess nitrogen in water bodies can trigger eutrophication, posing a threat to the ecosystem. The treatment of nitrogenous wastewater and removal of nitrogen compounds from water bodies is essential to improve and maintain water quality. To address this issue, the immobilized heterotrophic nitrifying-aerobic denitrifying bacterium Alcaligenes faecalis ( A. faecalis ) was combined with ecological floating island (EFI) to improve nitrogen removal performance, and the optimal operating conditions were determined. EFI supplemented with immobilized A. faecalis exhibited excellent and stable nitrogen removal capacity, with average removal rates of 89.10 ± 3.65 %, 74.79 ± 8.81 % and 95.44 ± 4.93 % for TN, NH 4 + − N and NO 3 − − N respectively, when the HRT was 3 d and the C/N was 16. The addition of immobilized A. faecalis increased the relative abundance of dominant denitrifying bacteria, especially unclassified_p__Proteobacteria , thereby altering the microbial community structure, improving the denitrification efficiency of the EFI, and facilitating nitrogen removal. In addition, the immobilized A. faecalis could reduce the effects of the nitrogenous wastewater on plants, enabling the nitrogen removal of the EFI. The study suggests that immobilization of A. faecalis is an effective strategy to improve nitrogen removal through EFI-microbial integrated systems.
Excess nitrogen in water bodies can trigger eutrophication, posing a threat to the ecosystem. The treatment of nitrogenous wastewater and removal of nitrogen compounds from water bodies is essential to improve and maintain water quality. To address this issue, the immobilized heterotrophic nitrifying-aerobic denitrifying bacterium Alcaligenes faecalis ( A. faecalis ) was combined with ecological floating island (EFI) to improve nitrogen removal performance, and the optimal operating conditions were determined. EFI supplemented with immobilized A. faecalis exhibited excellent and stable nitrogen removal capacity, with average removal rates of 89.10 ± 3.65 %, 74.79 ± 8.81 % and 95.44 ± 4.93 % for TN, NH 4 + − N and NO 3 − − N respectively, when the HRT was 3 d and the C/N was 16. The addition of immobilized A. faecalis increased the relative abundance of dominant denitrifying bacteria, especially unclassified_p__Proteobacteria , thereby altering the microbial community structure, improving the denitrification efficiency of the EFI, and facilitating nitrogen removal. In addition, the immobilized A. faecalis could reduce the effects of the nitrogenous wastewater on plants, enabling the nitrogen removal of the EFI. The study suggests that immobilization of A. faecalis is an effective strategy to improve nitrogen removal through EFI-microbial integrated systems.
作者机构：
[Zelin Deng; Mingxuan Tang; Ke Nai] School of Computer, Changsha University of Science and Technology, Changsha, 410114, China;[Guiji Li] School of Computer Science and Engineering, Changsha University, Changsha, 410022, China;[Shaomiao Chen] School of Computer Science and Engineering, Hunan University of Science and Technology, Xiangtan, 411201, China;[Pei He] School of Computer Science and Cyber Engineering, Guangzhou University, Guangzhou, 510000, China
通讯机构：
[Ke Nai] S;School of Computer, Changsha University of Science and Technology, Changsha, 410114, China
摘要：
Person re-identification is a challenging task which aims to retrieve images of a target pedestrian across different cameras. Currently, existing models generally neglect the semantic relevance of local features, which may cause to limited identification performance. To address this issue, we propose a semantic-guided occlusion simulation based local feature semantic expansion network (FOSENet) to pursue satisfactory performance. Firstly, we propose a semantic-guided occlusion simulation (SGOS) method, which generates semantically relevant occlusion patches and further simulates the occlusion based on the semantic information of pedestrians to improve the diversity of the occluded pedestrian samples. Then, we propose a local feature semantic expansion (LFSE) method, which obtains several local areas around each key area and selects some useful local areas as additional cues of the key area to enhance the discrimination ability. Finally, we introduce a cross-center offset loss function, which enlarges the distance of a pair of nearest neighbor samples from two classes to optimize the model. Thus, the samples belonging to different identities are pushed further away. Extensive experiments are conducted on four challenging datasets, and the proposed method can achieve competitive results compared to multiple state-of-the-art works. The code is publicly available at https://github.com/xuanthan-art/code-with-paper-FOSENet.git
Person re-identification is a challenging task which aims to retrieve images of a target pedestrian across different cameras. Currently, existing models generally neglect the semantic relevance of local features, which may cause to limited identification performance. To address this issue, we propose a semantic-guided occlusion simulation based local feature semantic expansion network (FOSENet) to pursue satisfactory performance. Firstly, we propose a semantic-guided occlusion simulation (SGOS) method, which generates semantically relevant occlusion patches and further simulates the occlusion based on the semantic information of pedestrians to improve the diversity of the occluded pedestrian samples. Then, we propose a local feature semantic expansion (LFSE) method, which obtains several local areas around each key area and selects some useful local areas as additional cues of the key area to enhance the discrimination ability. Finally, we introduce a cross-center offset loss function, which enlarges the distance of a pair of nearest neighbor samples from two classes to optimize the model. Thus, the samples belonging to different identities are pushed further away. Extensive experiments are conducted on four challenging datasets, and the proposed method can achieve competitive results compared to multiple state-of-the-art works. The code is publicly available at https://github.com/xuanthan-art/code-with-paper-FOSENet.git
期刊：
International Journal of Thermal Sciences,2026年220:110367 ISSN：1290-0729
通讯作者：
Chuangang Fan
作者机构：
[Rongwei Bu] School of Transportation, Changsha University of Science and Technology, Changsha 410114, China;[Chuangang Fan; Zengguang Liang; Guanjie Rao] School of Civil Engineering, Central South University, Changsha 410075, China;[Zhenyu Gao] Center for Combinatorics, Nankai University, Tianjin 300071, China;[Wenlong Wang] National Institute of Natural Hazards, Ministry of Emergency Management of China, Beijing, 100085, China;[Tong Xu] School of Emergency Management and Safety Engineering, China University of Mining and Technology, Beijing 100083, China
通讯机构：
[Chuangang Fan] S;School of Civil Engineering, Central South University, Changsha 410075, China
摘要：
Polymethyl methacrylate (PMMA) is extensively utilized in the design of various architectural structures, including concave configurations. However, its inherent flammability poses a significant potential fire hazard. Investigation of upward flame spread over concave surfaces has been restricted to flame spread parameters, while the associated burning behaviors have not yet been addressed. In this study, 36 groups of fire experiments were performed on 3 mm thick PMMA with varying curvature (denoted by K , 0.52–2.00 m -1 ) and width ( W , 2.5–15.0 cm). The results reveal that the mass loss rate undergoes an eruptive growth when K ≥ 1.41 m -1 . By introducing a dimensionless parameter Γ , this burning behavior is quantitatively described using a piecewise power-law correlation between Γ and the Grashof number Gr x . The critical occurrence of eruptive burning behavior is identified at Gr x ≈ 3 × 10 7 . For Gr x < 3 × 10 7 , flame convection mode in the pyrolysis zone is governed by natural convection, whereas forced convection becomes gradually dominant when Gr x ≥ 3 × 10 7 . Subsequently, based on this critical threshold, the flame spread model before the occurrence of eruptive phenomenon is developed. This model reflects a power-law relationship between flame spread rate and pyrolysis length, with an average power exponent of 1.24.
Polymethyl methacrylate (PMMA) is extensively utilized in the design of various architectural structures, including concave configurations. However, its inherent flammability poses a significant potential fire hazard. Investigation of upward flame spread over concave surfaces has been restricted to flame spread parameters, while the associated burning behaviors have not yet been addressed. In this study, 36 groups of fire experiments were performed on 3 mm thick PMMA with varying curvature (denoted by K , 0.52–2.00 m -1 ) and width ( W , 2.5–15.0 cm). The results reveal that the mass loss rate undergoes an eruptive growth when K ≥ 1.41 m -1 . By introducing a dimensionless parameter Γ , this burning behavior is quantitatively described using a piecewise power-law correlation between Γ and the Grashof number Gr x . The critical occurrence of eruptive burning behavior is identified at Gr x ≈ 3 × 10 7 . For Gr x < 3 × 10 7 , flame convection mode in the pyrolysis zone is governed by natural convection, whereas forced convection becomes gradually dominant when Gr x ≥ 3 × 10 7 . Subsequently, based on this critical threshold, the flame spread model before the occurrence of eruptive phenomenon is developed. This model reflects a power-law relationship between flame spread rate and pyrolysis length, with an average power exponent of 1.24.
作者：
Runzhou Luo;Xudong Zha*;Hengwu Hu;Bingbing Lei
期刊：
Renewable & Sustainable Energy Reviews,2026年226:116332 ISSN：1364-0321
通讯作者：
Xudong Zha
作者机构：
[Runzhou Luo; Xudong Zha; Hengwu Hu; Bingbing Lei] School of Transportation, Changsha University of Science and Technology, Changsha, China
通讯机构：
[Xudong Zha] S;School of Transportation, Changsha University of Science and Technology, Changsha, China
摘要：
The growing prominence of energy shortages and environmental challenges has intensified global attention toward renewable energy utilization, with an urgent demand for energy transition in the transportation sector. Roads, as one of the important transportation infrastructures, contain a large amount of utilizable mechanical energy, and their energy harvesting technology is currently one of the hotspots in research.This study presents a comprehensive review of road mechanical energy harvesting technologies. First, three categories of road mechanical energy harvesting systems suitable for different application scenarios are summarized and analyzed, including speed bumps, flat-plate, embedded or integrated. Subsequently, from the four technical approaches of hydraulic/pneumatic, electromagnetic, piezoelectric, and TENGs, the principles, methodological frameworks, and research outcomes of various energy harvesting technologies are comprehensively reviewed. The key performance metric of energy output for these four technologies is compared and summarized, along with evaluations of their advantages and disadvantages. Furthermore, the integration and development of road mechanical energy harvesting technologies with smart road systems are introduced. Finally, the key challenges currently hindering the real-world implementations of road mechanical energy harvesting technologies are discussed, including energy harvesting efficiency, material performance, cost and return, regulatory issues, among others. Predictions and recommendations for future development are proposed, aiming to provide assistance for further research and large-scale applications.
The growing prominence of energy shortages and environmental challenges has intensified global attention toward renewable energy utilization, with an urgent demand for energy transition in the transportation sector. Roads, as one of the important transportation infrastructures, contain a large amount of utilizable mechanical energy, and their energy harvesting technology is currently one of the hotspots in research.This study presents a comprehensive review of road mechanical energy harvesting technologies. First, three categories of road mechanical energy harvesting systems suitable for different application scenarios are summarized and analyzed, including speed bumps, flat-plate, embedded or integrated. Subsequently, from the four technical approaches of hydraulic/pneumatic, electromagnetic, piezoelectric, and TENGs, the principles, methodological frameworks, and research outcomes of various energy harvesting technologies are comprehensively reviewed. The key performance metric of energy output for these four technologies is compared and summarized, along with evaluations of their advantages and disadvantages. Furthermore, the integration and development of road mechanical energy harvesting technologies with smart road systems are introduced. Finally, the key challenges currently hindering the real-world implementations of road mechanical energy harvesting technologies are discussed, including energy harvesting efficiency, material performance, cost and return, regulatory issues, among others. Predictions and recommendations for future development are proposed, aiming to provide assistance for further research and large-scale applications.
摘要：
To study the evolution of the rheological properties of warm mix asphalt (WMA) and its mastic viscoelastic drive prediction model, different dosages of Sasobit (S) and Evotherm 3G (G) WMA were prepared. The temperature sensitivity, high temperature deformation resistance, and low temperature viscoelastic properties of the two WMA were analyzed using a bonding material high and low temperature performance test. By combining the Refatus and Burgers models, the optimal dosage of the two warm mixes (S and G) was determined to be 4.0 % and 0.6 %, respectively. The prediction accuracy of three micromechanical models, including Hashin and Buttlar, for the high temperature performance of mastic was compared through the particle reinforcement theory system. The results showed that the warm mix additives significantly improved the high temperature stability performance of the asphalt, reduced the temperature sensitivity of the asphalt, and the Refatus model parameter a was decreased by 9.15 % and 1.0 % for B-S-4 and B-G-0.6 (denoting 4 % S and 0.6 % G added to the SBS modified asphalt, respectively). The creep deformation of WMA was smaller than that of the asphalt in the original samples, and the warm mix additives effectively improved the low temperature cracking resistance of asphalt. The Buttlar model optimally predicted the high temperature performance in the mastic (71 °C/29 °C correlation coefficient R 2 = 0.991/0.917), and the adsorption of mineral powders with SBS modified asphalt was superior to that of the base asphalt. At the same time, the warming agent had a detrimental effect on the asphalt adsorption. The results provide a theoretical basis for predicting WMA mastic’s multiscale performance and for designing sustainable pavement materials.
To study the evolution of the rheological properties of warm mix asphalt (WMA) and its mastic viscoelastic drive prediction model, different dosages of Sasobit (S) and Evotherm 3G (G) WMA were prepared. The temperature sensitivity, high temperature deformation resistance, and low temperature viscoelastic properties of the two WMA were analyzed using a bonding material high and low temperature performance test. By combining the Refatus and Burgers models, the optimal dosage of the two warm mixes (S and G) was determined to be 4.0 % and 0.6 %, respectively. The prediction accuracy of three micromechanical models, including Hashin and Buttlar, for the high temperature performance of mastic was compared through the particle reinforcement theory system. The results showed that the warm mix additives significantly improved the high temperature stability performance of the asphalt, reduced the temperature sensitivity of the asphalt, and the Refatus model parameter a was decreased by 9.15 % and 1.0 % for B-S-4 and B-G-0.6 (denoting 4 % S and 0.6 % G added to the SBS modified asphalt, respectively). The creep deformation of WMA was smaller than that of the asphalt in the original samples, and the warm mix additives effectively improved the low temperature cracking resistance of asphalt. The Buttlar model optimally predicted the high temperature performance in the mastic (71 °C/29 °C correlation coefficient R 2 = 0.991/0.917), and the adsorption of mineral powders with SBS modified asphalt was superior to that of the base asphalt. At the same time, the warming agent had a detrimental effect on the asphalt adsorption. The results provide a theoretical basis for predicting WMA mastic’s multiscale performance and for designing sustainable pavement materials.
作者：
Kang Chen;Mei Yi Lau;Xinyuan Luo;Jiani Huang;Liuzhang Ouyang;...
期刊：
材料科学技术(英文),2026年246:256-289 ISSN：1005-0302
通讯作者：
Liuzhang Ouyang<&wdkj&>Xu-Sheng Yang
作者机构：
[Mei Yi Lau; Jiani Huang; Xu-Sheng Yang] Department of Industrial and Systems Engineering, Research Institute for Advanced Manufacturing, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, China;[Xinyuan Luo] Key Laboratory of Energy Efficient & Clean Utilization, School of Energy and Power Engineering, Changsha University of Science and Technology, Changsha 410114, China;[Liuzhang Ouyang] School of Materials Science and Engineering, Guangdong Provincial Key Laboratory of Advanced Energy Storage Materials, South China University of Technology, Guangzhou 510641, China;[Kang Chen] Department of Industrial and Systems Engineering, Research Institute for Advanced Manufacturing, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, China<&wdkj&>Key Laboratory of Energy Efficient & Clean Utilization, School of Energy and Power Engineering, Changsha University of Science and Technology, Changsha 410114, China
通讯机构：
[Liuzhang Ouyang] S;[Xu-Sheng Yang] D;Department of Industrial and Systems Engineering, Research Institute for Advanced Manufacturing, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, China<&wdkj&>School of Materials Science and Engineering, Guangdong Provincial Key Laboratory of Advanced Energy Storage Materials, South China University of Technology, Guangzhou 510641, China
摘要：
Promoting the widespread utilization of hydrogen energy, supported by efficient storage and conversion technologies, represents a pivotal strategy for addressing global energy and environmental challenges. Among these technologies, the development of compact, safe, and economically viable hydrogen storage (abbreviated as H-storage) solutions is essential for advancing a hydrogen-based economy. Conventional technologies, such as compressed gaseous hydrogen and cryogenic liquid hydrogen, face limitations including safety concerns, high energy consumption, and significant evaporation losses. In comparison, metal hydride-based storage offers a promising alternative by enabling hydrogen to form stable compounds with metals under moderate conditions, thereby improving safety and hydrogen density (H-density). The review provides a comprehensive analysis of recent advances in the most appealing solid-state hydrogen storage alloys (HSAs), with a focus on their de-/hydrogenation properties and cycling stability. Key materials discussed include V-based body-centered cubic (BCC) HSAs, Mg-based crystalline and amorphous HSAs, and multi-component alloys—either employed as used as standalone H-storage materials or as multifunctional catalysts to improve hydrogen kinetics of Mg-based materials. The review begins by examining synthesis methods for HSAs. Afterwards, the review summarizes and discusses the H-storage properties of the above HSAs, with a particular emphasis on their de-/hydriding kinetics, thermodynamics, and cycling performance. In addition to highlighting the latest advancements of solid-state HSAs in the field of hydrogen energy, the remaining challenges and prospects of the emerging research are also discussed.
Promoting the widespread utilization of hydrogen energy, supported by efficient storage and conversion technologies, represents a pivotal strategy for addressing global energy and environmental challenges. Among these technologies, the development of compact, safe, and economically viable hydrogen storage (abbreviated as H-storage) solutions is essential for advancing a hydrogen-based economy. Conventional technologies, such as compressed gaseous hydrogen and cryogenic liquid hydrogen, face limitations including safety concerns, high energy consumption, and significant evaporation losses. In comparison, metal hydride-based storage offers a promising alternative by enabling hydrogen to form stable compounds with metals under moderate conditions, thereby improving safety and hydrogen density (H-density). The review provides a comprehensive analysis of recent advances in the most appealing solid-state hydrogen storage alloys (HSAs), with a focus on their de-/hydrogenation properties and cycling stability. Key materials discussed include V-based body-centered cubic (BCC) HSAs, Mg-based crystalline and amorphous HSAs, and multi-component alloys—either employed as used as standalone H-storage materials or as multifunctional catalysts to improve hydrogen kinetics of Mg-based materials. The review begins by examining synthesis methods for HSAs. Afterwards, the review summarizes and discusses the H-storage properties of the above HSAs, with a particular emphasis on their de-/hydriding kinetics, thermodynamics, and cycling performance. In addition to highlighting the latest advancements of solid-state HSAs in the field of hydrogen energy, the remaining challenges and prospects of the emerging research are also discussed.
摘要：
Concrete material will gradually lose its original structural strength over time and suffer from a variety of structural damages, such as cracks, potholes, etc. Diverse damage patterns and complex geometries of material make accurate multi-class material structural damage segmentation more difficult than the segmentation of a single type of damage. Integrating detection methods with other systems and applying them to engineering practice imposes demands on the efficiency of model inference. In response to these challenges, Real-Time concrete structural Damage Segmentation network (RTDSeg) was proposed. In this network, efficient feature extraction backbone was introduced to improve the perceptual capabilities of the model. In order to alleviate the problem of feature redundancy when fusing features from different scales, semantic enhancement module was designed to filter the encoding features. Furthermore, auxiliary prediction head and hard example sampling training method were introduced to optimize the training effectiveness of the model, which improved the model’s prediction accuracy without extra inference cost. A series of experiments demonstrated the superiority of RTDSeg and the effectiveness of several improvements. In the compared state-of-the-art networks, RTDSeg achieved 8.98% mIoU and 13.89% FPS lead on a bridge damage dataset, and 3.88% mIoU and 92.03% FPS lead on a reinforced concrete damage dataset compared to the ones with the highest accuracy.
Concrete material will gradually lose its original structural strength over time and suffer from a variety of structural damages, such as cracks, potholes, etc. Diverse damage patterns and complex geometries of material make accurate multi-class material structural damage segmentation more difficult than the segmentation of a single type of damage. Integrating detection methods with other systems and applying them to engineering practice imposes demands on the efficiency of model inference. In response to these challenges, Real-Time concrete structural Damage Segmentation network (RTDSeg) was proposed. In this network, efficient feature extraction backbone was introduced to improve the perceptual capabilities of the model. In order to alleviate the problem of feature redundancy when fusing features from different scales, semantic enhancement module was designed to filter the encoding features. Furthermore, auxiliary prediction head and hard example sampling training method were introduced to optimize the training effectiveness of the model, which improved the model’s prediction accuracy without extra inference cost. A series of experiments demonstrated the superiority of RTDSeg and the effectiveness of several improvements. In the compared state-of-the-art networks, RTDSeg achieved 8.98% mIoU and 13.89% FPS lead on a bridge damage dataset, and 3.88% mIoU and 92.03% FPS lead on a reinforced concrete damage dataset compared to the ones with the highest accuracy.
期刊：
Renewable & Sustainable Energy Reviews,2026年226:116230 ISSN：1364-0321
通讯作者：
Chuanchang Li
作者机构：
[Xinrui Yan; Baoshan Xie; Chuanchang Li] Key Laboratory of Renewable Energy Electric-Technology of Hunan Province, School of Energy and Power Engineering, Changsha University of Science and Technology, Changsha, 410114, China
通讯机构：
[Chuanchang Li] K;Key Laboratory of Renewable Energy Electric-Technology of Hunan Province, School of Energy and Power Engineering, Changsha University of Science and Technology, Changsha, 410114, China
摘要：
With the ongoing advancement of aerospace technology, the demand for high-performance materials is rising. Phase change materials (PCMs), known for their unique thermophysical properties and versatility, offer new opportunities for breakthroughs in aerospace applications. PCMs, characterized by their low density, high energy storage density, and robust cycle stability, are ideal for aircraft lightweighting and thermal management of electronic devices. This review provides an overview of PCMs, including their mechanism, classification, preparation methods, and performance optimization. It then outlines the selection criteria for aerospace applications, emphasizing attributes such as lightweight design, long-term cycle stability, high thermal conductivity, resistance to extreme temperatures and radiation, and compatibility with existing equipment. Finally, the review explores recent advancements in PCM applications in aerospace, addressing the associated challenges and future prospects.
With the ongoing advancement of aerospace technology, the demand for high-performance materials is rising. Phase change materials (PCMs), known for their unique thermophysical properties and versatility, offer new opportunities for breakthroughs in aerospace applications. PCMs, characterized by their low density, high energy storage density, and robust cycle stability, are ideal for aircraft lightweighting and thermal management of electronic devices. This review provides an overview of PCMs, including their mechanism, classification, preparation methods, and performance optimization. It then outlines the selection criteria for aerospace applications, emphasizing attributes such as lightweight design, long-term cycle stability, high thermal conductivity, resistance to extreme temperatures and radiation, and compatibility with existing equipment. Finally, the review explores recent advancements in PCM applications in aerospace, addressing the associated challenges and future prospects.
作者机构：
School of Computer Science and Engineering, Central South University, Changsha, 410083, Hunan, China;[Shichao Zhang] Guangxi Key Lab of Multi-Source Information Mining and Security, Guangxi Normal University, Guilin, 541004, Guangxi, China;School of Computer Science and Technology, Changsha University of Science & Technology, Changsha, 410114, Hunan, China;[Yuxuan Hu] School of Computer Science and Engineering, Central South University, Changsha, 410083, Hunan, China<&wdkj&>Guangxi Key Lab of Multi-Source Information Mining and Security, Guangxi Normal University, Guilin, 541004, Guangxi, China<&wdkj&>School of Computer Science and Technology, Changsha University of Science & Technology, Changsha, 410114, Hunan, China
通讯机构：
[Shichao Zhang] G;Guangxi Key Lab of Multi-Source Information Mining and Security, Guangxi Normal University, Guilin, 541004, Guangxi, China
摘要：
Image denoising plays a vital role in enhancing image quality for various downstream vision tasks by learning robust feature representations that distinguish clean signals from noise. Recent advances in deep learning have enabled data-driven feature extraction but frequently face challenges such as spatial-channel feature redundancy, suboptimal fusion of multi-level features, and over-smoothing due to pixel-wise loss functions. To address these interconnected issues, this paper proposes the Perceptual Feature Learning Network (PFLN), a lightweight architecture explicitly designed for efficient, discriminative feature learning. PFLN introduces a Redundancy Filtering Block (RFB) to suppress redundant information, a Selective Attention Fusion Block (SAFB) to adaptively integrate complementary features, and multi-level feature constraints combining pixel, perceptual, and spatial losses for holistic optimization. Experiments demonstrate that PFLN effectively learns compact, context-aware representations that improve denoising fidelity and texture preservation while maintaining computational efficiency, providing a balanced solution for real-world image denoising tasks.
Image denoising plays a vital role in enhancing image quality for various downstream vision tasks by learning robust feature representations that distinguish clean signals from noise. Recent advances in deep learning have enabled data-driven feature extraction but frequently face challenges such as spatial-channel feature redundancy, suboptimal fusion of multi-level features, and over-smoothing due to pixel-wise loss functions. To address these interconnected issues, this paper proposes the Perceptual Feature Learning Network (PFLN), a lightweight architecture explicitly designed for efficient, discriminative feature learning. PFLN introduces a Redundancy Filtering Block (RFB) to suppress redundant information, a Selective Attention Fusion Block (SAFB) to adaptively integrate complementary features, and multi-level feature constraints combining pixel, perceptual, and spatial losses for holistic optimization. Experiments demonstrate that PFLN effectively learns compact, context-aware representations that improve denoising fidelity and texture preservation while maintaining computational efficiency, providing a balanced solution for real-world image denoising tasks.
期刊：
Electric Power Systems Research,2026年251:112271 ISSN：0378-7796
通讯作者：
Yang, HY
作者机构：
[Jiang, Lingfeng; Guo, Chaocheng] Changsha Univ Sci & Technol, State Key Lab Disaster Prevent & Reduct Power Grid, Changsha, Peoples R China.;[Yang, Huanyu; Tao, Xingyu] Hunan Disaster Prevent Technol Co Ltd, State Key Lab Disaster Prevent C & Reduct Power Gr, Changsha, Peoples R China.;[Tang, Zhuang; Lu, Jiazheng; Ning, Kai] State Grid Hunan Elect Power Corp, State Key Lab Disaster Prevent & Reduct Power Grid, Disaster Prevent & Reduct Ctr, Changsha, Peoples R China.;[Huang, Xiaoqi] State Grid Hunan Elect Power Co Ltd, Hydropower Co, Changsha, Peoples R China.
通讯机构：
[Yang, HY ] H;Hunan Disaster Prevent Technol Co Ltd, State Key Lab Disaster Prevent C & Reduct Power Gr, Changsha, Peoples R China.
关键词：
Wind turbine blade;Ice accretion;Air-heating Deicing;Full-scale Experiment;Temperature Distribution Characteristics
摘要：
Wind turbine blades are prone to ice accretion in winter, which impair their aerodynamic performance and power output. The air-heating deicing device for blades is easy to construct and poses no risk of lightning strikes; however, it suffers from significant heat loss during the deicing process, and the temperature distribution characteristics of the blades and the influencing factors of the surface temperature rise remain unclear. In this study, we conducted a full-scale air-heating deicing experiment on a 42-meter-long blade under natural freezing rain conditions and developed a three-dimensional fluid-heat transfer model that considers the internal structure of the blade. We examined the influence of various parameters such as blower air flow, air pressure, blade rotation, ambient temperature, and cavity flow channel on the blade's temperature rise effect. The results indicate that the surface temperature distribution of the blade increases from the root to the tip, then decreases, and rises again. Under a -5 °C cold wave condition, the maximum surface temperature of the 42-meter-long blade reached approximately 40 °C, effectively removing surface ice. Reducing the blower air flow appropriately can enhance the steady-state temperature of the blade, while increasing air pressure can accelerate the temperature rise to reach a steady state faster. Additionally, an optimized air duct design incorporating a leading edge-to-upper web return air path was proposed, which significantly improves the air-heating efficiency of obstructed blades in operation. The findings provide theoretical guidance for optimizing the design of air-heating deicing systems.
Wind turbine blades are prone to ice accretion in winter, which impair their aerodynamic performance and power output. The air-heating deicing device for blades is easy to construct and poses no risk of lightning strikes; however, it suffers from significant heat loss during the deicing process, and the temperature distribution characteristics of the blades and the influencing factors of the surface temperature rise remain unclear. In this study, we conducted a full-scale air-heating deicing experiment on a 42-meter-long blade under natural freezing rain conditions and developed a three-dimensional fluid-heat transfer model that considers the internal structure of the blade. We examined the influence of various parameters such as blower air flow, air pressure, blade rotation, ambient temperature, and cavity flow channel on the blade's temperature rise effect. The results indicate that the surface temperature distribution of the blade increases from the root to the tip, then decreases, and rises again. Under a -5 °C cold wave condition, the maximum surface temperature of the 42-meter-long blade reached approximately 40 °C, effectively removing surface ice. Reducing the blower air flow appropriately can enhance the steady-state temperature of the blade, while increasing air pressure can accelerate the temperature rise to reach a steady state faster. Additionally, an optimized air duct design incorporating a leading edge-to-upper web return air path was proposed, which significantly improves the air-heating efficiency of obstructed blades in operation. The findings provide theoretical guidance for optimizing the design of air-heating deicing systems.
期刊：
Computers and Geotechnics,2026年189:107672 ISSN：0266-352X
通讯作者：
Fu Huang
作者机构：
[Fu Huang; Yongtao Wang; Min Zhang; Lu Chen] School of Civil and Environmental Engineering, Changsha University of Science and Technology, Changsha, Hunan, China
通讯机构：
[Fu Huang] S;School of Civil and Environmental Engineering, Changsha University of Science and Technology, Changsha, Hunan, China
摘要：
The collapse of stratum induced by subsurface excavation for a shallow tunnel in water-rich region is common in urban tunnel engineering. Although scholars have conducted numerous research on the stability of the soil mass above shallow-buried tunnel roof, the collapse characteristics of the soil mass induced by shallow-buried tunnel construction in water-rich strata have not been well investigated. In this work, a new three-dimensional collapse mechanism of the stratum above shallow-buried tunnel roof is generated “point by point” based on the spatial discretization technique for the first time. A scaled model test is designed to verify the validity of the constructed collapse mechanism. By introducing the pore water pressure which is obtained from numerical simulation as an external force into the virtual work equation, the safety factor of the stratum is derived from the upper bound theorem of limit analysis. Finally, a comparison between the theoretical solutions and numerical solutions have been conducted to prove the effectiveness of the proposed method
The collapse of stratum induced by subsurface excavation for a shallow tunnel in water-rich region is common in urban tunnel engineering. Although scholars have conducted numerous research on the stability of the soil mass above shallow-buried tunnel roof, the collapse characteristics of the soil mass induced by shallow-buried tunnel construction in water-rich strata have not been well investigated. In this work, a new three-dimensional collapse mechanism of the stratum above shallow-buried tunnel roof is generated “point by point” based on the spatial discretization technique for the first time. A scaled model test is designed to verify the validity of the constructed collapse mechanism. By introducing the pore water pressure which is obtained from numerical simulation as an external force into the virtual work equation, the safety factor of the stratum is derived from the upper bound theorem of limit analysis. Finally, a comparison between the theoretical solutions and numerical solutions have been conducted to prove the effectiveness of the proposed method
期刊：
SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY,2026年344(Pt 2):126733 ISSN：1386-1425
通讯作者：
Xia, Jiaoyun;Gong, Fuchun
作者机构：
[Zhou, Junxian; Qin, Xiaoling; Chen, Lusen; Zhang, Changshuo; Sun, Jing; Xu, Lujie] School of Chemistry and Pharmaceutical Engineering, Changsha University of Science and Technology, Changsha 410114, PR China;[Xia, Jiaoyun] School of Chemistry and Pharmaceutical Engineering, Changsha University of Science and Technology, Changsha 410114, PR China. Electronic address: xiajy625@163.com;[Gong, Fuchun] School of Chemistry and Pharmaceutical Engineering, Changsha University of Science and Technology, Changsha 410114, PR China. Electronic address: gongfc139@163.com
通讯机构：
[Xia, Jiaoyun; Gong, Fuchun] S;School of Chemistry and Pharmaceutical Engineering, Changsha University of Science and Technology, Changsha 410114, PR China. Electronic address:
摘要：
Currently, the mainstream strategy for NO 2 − sensing is the use of amino group as the recognition site and Griess reaction as signaling. However, this method suffers from the shortcomings of relying on strong acidic media and being susceptible to interference from amino species. Herein，we synthesized a novel fluorescent probe (OHQ) for NO 2 − . OHQ possesses a methylene activated by cyano group, enabling it to easily react with NO 2 − in a neutral medium. With the addition of NO 2 − , the fluorescence intensity of OHQ is significantly quenched in an acetonitrile-PBS solution (10 mM, pH 7.0). From this principle, a sensitive and selective method for detecting NO 2 − was developed, which offers a good linearity ranging from 0 to 55 μM and a lower limit detection of 2.5 nM (3σ). An OHQ-loaded test paper was also fabricated and applied to monitoring NO 2 − in food samples, indicating advantages of simple preparation and rapid response compared with traditional Griess reaction-based colorimetric reagents. Furthermore, OHQ was employed for fluorescence imaging and tracking NO 2 − in living cells, showing good cytopermeability, biocompatibility and fluorescence color rendering performance. Our proposed probe breaks through the bottleneck of relying on a strong acidic medium associated with traditional probes for NO₂ − , enabling it to provide a more practical method for the detection of NO 2 − and gives good application prospect.
Currently, the mainstream strategy for NO 2 − sensing is the use of amino group as the recognition site and Griess reaction as signaling. However, this method suffers from the shortcomings of relying on strong acidic media and being susceptible to interference from amino species. Herein，we synthesized a novel fluorescent probe (OHQ) for NO 2 − . OHQ possesses a methylene activated by cyano group, enabling it to easily react with NO 2 − in a neutral medium. With the addition of NO 2 − , the fluorescence intensity of OHQ is significantly quenched in an acetonitrile-PBS solution (10 mM, pH 7.0). From this principle, a sensitive and selective method for detecting NO 2 − was developed, which offers a good linearity ranging from 0 to 55 μM and a lower limit detection of 2.5 nM (3σ). An OHQ-loaded test paper was also fabricated and applied to monitoring NO 2 − in food samples, indicating advantages of simple preparation and rapid response compared with traditional Griess reaction-based colorimetric reagents. Furthermore, OHQ was employed for fluorescence imaging and tracking NO 2 − in living cells, showing good cytopermeability, biocompatibility and fluorescence color rendering performance. Our proposed probe breaks through the bottleneck of relying on a strong acidic medium associated with traditional probes for NO₂ − , enabling it to provide a more practical method for the detection of NO 2 − and gives good application prospect.
作者机构：
School of Civil Engineering, Changsha University, Changsha, 410022, PR China;Hunan Provincial Key Laboratory for Big Data Smart Application of Natural Disaster Risks Survey of Highway Engineering, Changsha University, Changsha, 410022, PR China;[Wu Gaoqiao] School of Traffic and Transportation Engineering, Changsha University of Science and Technology, Changsha, 410022, PR China;School of Civil Engineering and Architecture, Guangxi University, Nanning, 530004, PR China;State Key Laboratory of Featured Metal Materials and Life-cycle Safety for Composite Structures, Guangxi University, Nanning, 530004, PR China
通讯机构：
[Yao Xiao] S;School of Civil Engineering and Architecture, Guangxi University, Nanning, 530004, PR China<&wdkj&>State Key Laboratory of Featured Metal Materials and Life-cycle Safety for Composite Structures, Guangxi University, Nanning, 530004, PR China
摘要：
This research presents a novel approach to addressing plane strain stability problems in rock masses, obeying the generalized Hoek-Brown failure criterion. The methodology integrates upper bound (UB) finite element limit analysis (FELA) with power cone programming (PCP) techniques. To achieve significantly enhanced UB results, quadratic velocity elements are employed for the discretization of the kinematic theorem. Within the UB formulation, the generalized Hoek-Brown (GHB) yield criterion is represented through a series of linear constraints and two conic constraints—specifically, a quadratic cone and a power cone. This allows the GHB yield criterion to be articulated in its original form without the need for smoothing the yield surface. Three classic examples have been analyzed to verify the feasibility of the proposed method. Comprehensive comparisons between the newly obtained results and existing results from several related references demonstrate that the new method is highly efficient in terms of computation time and capable of generating highly accurate upper bounds when combined with an appropriate mesh adaptivity procedure.
This research presents a novel approach to addressing plane strain stability problems in rock masses, obeying the generalized Hoek-Brown failure criterion. The methodology integrates upper bound (UB) finite element limit analysis (FELA) with power cone programming (PCP) techniques. To achieve significantly enhanced UB results, quadratic velocity elements are employed for the discretization of the kinematic theorem. Within the UB formulation, the generalized Hoek-Brown (GHB) yield criterion is represented through a series of linear constraints and two conic constraints—specifically, a quadratic cone and a power cone. This allows the GHB yield criterion to be articulated in its original form without the need for smoothing the yield surface. Three classic examples have been analyzed to verify the feasibility of the proposed method. Comprehensive comparisons between the newly obtained results and existing results from several related references demonstrate that the new method is highly efficient in terms of computation time and capable of generating highly accurate upper bounds when combined with an appropriate mesh adaptivity procedure.
期刊：
Cold Regions Science and Technology,2026年241:104666 ISSN：0165-232X
通讯作者：
Wei Wen
作者机构：
[Rongkai Wen; Wei Wen; Pingbao Yin; Haibo Huang; Lijuan Bai] School of Civil and Environmental Engineering, Changsha University of Science & Technology, Changsha 410114, China;[Zhemin You] State Key Laboratory of Frozen Soil Engineering, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, Gansu 730000, China;[Qingguo Ma] State Key Laboratory of Subtropical Building and Urban Science, South China University of Technology, Guangzhou, Guangdong 510641, China
通讯机构：
[Wei Wen] S;School of Civil and Environmental Engineering, Changsha University of Science & Technology, Changsha 410114, China
摘要：
In negative temperature environments, the moisture and solutes within saline soils may crystallize into ice and salt, respectively, inducing recurrent frost heave and salt expansion phenomena, and occurring differential settlement under temperature fluctuations and dynamic loading. To elucidate the dynamic behavior of frozen subgrade under cyclic loading, a series of dynamic triaxial tests was conducted on unsaturated, sulfate-contaminated frozen red clay, with systematic variation in confining pressure, moisture content, and salinity. Experimental results reveal that a moderate amount of salt can enhance the structural stiffness of the soil-reflected by an 8 % increase in the dynamic elastic modulus ( E d ), reduce the area of the hysteresis loop (36.30 %) and effectively mitigates plastic deformation correspondingly. The dynamic modulus exhibited a non-linear “increase-decrease-increase” trend with rising confining pressure. With the increasing of water contents, more water will transform into ice. To comprehensively evaluate the dynamic response, parameters such as dynamic modulus, hysteresis loop area, and strain rate were analyzed by using the entropy weight method combined with the Rank Sum Ratio (RSR) approach, which indicated that confining pressure of 300 kPa, water content of 18 %, and salinity of 1 % were the optimal combination of test conditions based on the RSR value 0.844 and minimum strain rate 0.008 mm/s to yield maximum dynamic modulus (19GPa) and moderate energy dissipation(110 MPa).
In negative temperature environments, the moisture and solutes within saline soils may crystallize into ice and salt, respectively, inducing recurrent frost heave and salt expansion phenomena, and occurring differential settlement under temperature fluctuations and dynamic loading. To elucidate the dynamic behavior of frozen subgrade under cyclic loading, a series of dynamic triaxial tests was conducted on unsaturated, sulfate-contaminated frozen red clay, with systematic variation in confining pressure, moisture content, and salinity. Experimental results reveal that a moderate amount of salt can enhance the structural stiffness of the soil-reflected by an 8 % increase in the dynamic elastic modulus ( E d ), reduce the area of the hysteresis loop (36.30 %) and effectively mitigates plastic deformation correspondingly. The dynamic modulus exhibited a non-linear “increase-decrease-increase” trend with rising confining pressure. With the increasing of water contents, more water will transform into ice. To comprehensively evaluate the dynamic response, parameters such as dynamic modulus, hysteresis loop area, and strain rate were analyzed by using the entropy weight method combined with the Rank Sum Ratio (RSR) approach, which indicated that confining pressure of 300 kPa, water content of 18 %, and salinity of 1 % were the optimal combination of test conditions based on the RSR value 0.844 and minimum strain rate 0.008 mm/s to yield maximum dynamic modulus (19GPa) and moderate energy dissipation(110 MPa).
