作者机构：
[Jiwen Zhang; Jinke Cheng; Yuhui Liu; Yi Wang; Peng Chen] Provincial Guizhou Key Laboratory of Green Chemical and Clean Energy Technology, School of Chemistry and Chemical Engineering, Guizhou University, Guiyang 550025, China;College of Chemistry and Chemical Engineering, Central South University of Forestry and Technology, Changsha 410004, PR China;Advanced Catalytic Engineering Research Center of the Ministry of Education, State Key Laboratory of Chemo/Biosensing and Chemometrics, College of Chemistry and Chemical Engineering, Hunan University, Changsha 410082, PR China;[Kailong Lv] Fuquan Fupeng Chemical Co., Ltd, Qianna Buyi National Minority Miao National Minority Autonomous, 550500, China;[Shuang-Feng Yin] College of Chemistry and Chemical Engineering, Central South University of Forestry and Technology, Changsha 410004, PR China<&wdkj&>Advanced Catalytic Engineering Research Center of the Ministry of Education, State Key Laboratory of Chemo/Biosensing and Chemometrics, College of Chemistry and Chemical Engineering, Hunan University, Changsha 410082, PR China
通讯机构：
[Jinke Cheng; Peng Chen] P;Provincial Guizhou Key Laboratory of Green Chemical and Clean Energy Technology, School of Chemistry and Chemical Engineering, Guizhou University, Guiyang 550025, China
作者机构：
[Luosong Zheng; Heping Luo; Yuxin Zhong; Wanqian Li; Han Xu; Fuquan Xiong; Jiahao Pi; Yan Qing; Yiqiang Wu] College of Materials Science and Engineering, Central South University of Forestry and Technology, Changsha 410004, PR China
通讯机构：
[Han Xu; Yan Qing] C;College of Materials Science and Engineering, Central South University of Forestry and Technology, Changsha 410004, PR China
关键词：
Electrocatalyst;Built-in electric field;Hierarchical porous structure;Wood;Oxygen evolution reaction
作者：
Chengwei Zhao;Ruihuan Liu*;Xuanhua Xu;Jishan He
期刊：
Expert Systems with Applications,2025年261:125532 ISSN：0957-4174
通讯作者：
Ruihuan Liu
作者机构：
[Chengwei Zhao] School of Business, Central South University of Forestry and Technology, Changsha, China;[Ruihuan Liu] School of Logistics, Central South University of Forestry and Technology, Changsha, China;[Xuanhua Xu; Jishan He] School of Business, Central South University, Changsha, China
通讯机构：
[Ruihuan Liu] S;School of Logistics, Central South University of Forestry and Technology, Changsha, China
通讯机构：
[Gong, ZL ] C;Cent South Univ Forestry & Technol, Coll Mech & Intelligent Mfg, Changsha 410004, Peoples R China.
关键词：
CFD;DEM;Rotary kilns;Design load;Flights
摘要：
The rotary kilns are widely used in chemical, food and metallurgical industries, and the design load of the internal flights has a significant effect on the drying efficiency of the rotary kilns. The motion of granular flow and heat absorption process inside the rotary kilns were simulated by establishing a coupled CFD and DEM model. The average heat absorption rate of granules was proposed to simulate the "L" type and three segments flights, and the results showed that the average heat absorption rate of granules was in accordance with the conclusions of previous scholars. We used the average heat absorption method of granules to optimize the structural parameters of the "J" type flights design load, the best parameter was obtained, and then compared with the "L" type and three segments of the flights, we found that the drying efficiency of "J" type flights is the best, followed by three segments and "L" type is found to be the worst. At the same time, the active region was divided to explore the relationship between the area occupied by the granules in different regions and the average heat absorption rate of granules, and it was found that under the same shape of the flights, the larger the area occupied by the granules in region 2, the larger the corresponding average heat absorption rate of granules.
作者机构：
[Yu Ren; Jiaohua Qin; Xuyu Xiang; Yun Tan] Central South University of Forestry and Technology, School of Electronic Information and Physics, Changsha, China
通讯机构：
[Jiaohua Qin] C;Central South University of Forestry and Technology, School of Electronic Information and Physics, Changsha, China
关键词：
Reversible data hiding;Encrypted images;Lasso regression predictor;Dynamic secret sharing
摘要：
Reversible data hiding in encrypted images (RDH-EI) integrates encryption with information hiding, enabling the embedding of additional data while ensuring full recovery of the original image, widely used in multimedia data protection and forensics. However, with the increasingly serious problem of data islands, the existing RDH-EI schemes for end-to-end communication scenarios can no longer meet the application requirements for multi-party data sharing. For solving this problem, this paper proposes an RDH-EI method based on Lasso regression predictor and dynamic secret sharing. First, Lasso regression predictor is proposed, which avoids the problem of over-fitting by regularizing the loss function. Then, to reserve more embeddable room, we map the prediction error and use arithmetic coding for compression. Next, the original image and auxiliary information are shared through dynamic secret sharing algorithm, and they can be transmitted to the corresponding data hiders respectively. According to the reserved room, each data hider allows for the discrete implantation of the secret bits into the corresponding encrypted image. The receiver can successfully extract the secret bits and recreate the cover image without distortion by gathering a specific percentage of marked images. Experimental results demonstrate that the suggested Lasso regression predictor has a greater prediction accuracy, outperforming contemporary methods for embedding rate. Additionally, it has great security and strong key sensitivity.
通讯机构：
[Yin, SF ] H;Hunan Univ, Coll Chem & Chem Engn, State Key Lab Chemo Biosensing & Chemometr, Adv Catalyt Engn Res Ctr,Minist Educ, Changsha 410082, Peoples R China.
关键词：
Photocatalytic oxidation;Reactive oxygen species;Mixed metal oxide photocatalyst;Cu species;Hydroxyl radical
摘要：
Photocatalytic selective benzene hydroxylation via activation of C(sp2)-H under visible light remains a challenging reaction. Copper-incorporated mixed metal oxide photocatalysts have shown promise in addressing this difficulty by enabling visible light harvesting, controlled reactive oxygen species (ROS) generation, effective ROS utilization, and reactant adsorption. However, copper incorporated metal oxide catalysts were suffered from poor catalytic activity and selectivity due to leaching of Cu species. To solve this problem, herein, a novel stable mixed metal oxide (CuZnSbO) was prepared for the first time by applying a facile method. Copper introduction brought about the suitable band gap energy for a wide range of visible light harvesting of the CuZnSbO catalyst. The copper species play a key role in activating H2O2 to produce hydroxyl radicals (center dot OH) for benzene oxidation by controlling charge recombination. The mixed metal oxide of zinc and antimony supports the included copper strongly enabling copper stability. The CuZnSbO not only generates available hydroxyl radicals but also facilitates efficient hydroxyl radical consumption to initiate C(sp2)-H activation, forming benzene radical intermediates en route to phenol. That is ever reported. CuZnSbO delivered 31.51 % benzene conversion and 100 % phenol selectivity. This work demonstrates the promise of engineered mixed metal oxide that boosts Cu species utilization for H2O2 and benzene activation. The photocatalyst showed good activity in selective oxidative hydroxylation reactions through harnessing visible light and controlled ROS generation. Importantly, Cu cations govern the photocatalytic center dot OH generation mechanisms as shown by XPS and active site deactivation analysis.
关键词：
Circadian lighting;Multi-channel spectral sensors;Spectral power distribution;Machine learning
摘要：
Light has an undeniable impact on the human body, as it can to some extent affect hormone secretion and emotional changes. Spectral power distribution (SPD) is the main indicator for evaluating the quality of light sources, but traditional spectral measurement equipment is bulky and expensive, and cannot be widely used in our daily life. In order to fill this gap, this article designs a low-cost and small lighting measurement device for measuring the circadian lighting, which obtains spectral data from 8 channels in the visible light range through multi-channel spectral sensors. Machine learning methods are used to reconstruct the SPD of 81 wavelength data points, thereby improving the accuracy of designed measurement device. This device can simultaneously achieve real-time measurement of SPD and real-time monitoring of circadian related parameters, and return circadian related parameters (such as circadian action factor, melanopic efficacy of luminous radiation, equivalent melanopic lux, etc.). Results have found that the error of circadian parameters measured by this equipment is less than 5%.
作者机构：
[Yiting Luo] Hunan First Normal University, Changsha 410114, PR China;[Jiayi Gong; Ziyi Yang; Yonghua Chen; Shunhong Huang; Xiancheng Ma; Wende Yan] College of Life and Environmental Science, Central South University of Forestry and Technology, Changsha 410004, PR China;[Zhao Liu] Radiation Environmental Supervision Station of Xinjiang Uygur Autonomous Region, Urumqi, Xinjiang 830010, PR China;Power China Zhongnan Engineering Corporation Limited, Changsha 410004, PR China;[Rongkui Su] College of Life and Environmental Science, Central South University of Forestry and Technology, Changsha 410004, PR China<&wdkj&>Power China Zhongnan Engineering Corporation Limited, Changsha 410004, PR China
通讯机构：
[Rongkui Su] C;College of Life and Environmental Science, Central South University of Forestry and Technology, Changsha 410004, PR China<&wdkj&>Power China Zhongnan Engineering Corporation Limited, Changsha 410004, PR China
作者机构：
[Lixin Wang; Jie Ouyang; Yi Tian; Liangliang Zhou; Mengting Cheng; Yuzhu Wang; Xi Ren; Zhuoshi Wu; Wei Yin; Qingquan Sheng; Jianhua Luo; Liaoyuan Xia; Yongfeng Luo] Hunan Province Key Laboratory of Materials Surface & Interface Science and Technology, School of Materials Science and Engineering, Central South University of Forestry and Technology, Changsha, Hunan 410004, PR China
通讯机构：
[Yongfeng Luo] H;Hunan Province Key Laboratory of Materials Surface & Interface Science and Technology, School of Materials Science and Engineering, Central South University of Forestry and Technology, Changsha, Hunan 410004, PR China
期刊：
Separation and Purification Technology,2025年356:129867 ISSN：1383-5866
通讯作者：
Wenlei Wang
作者机构：
[Qianfeng Wu] College of Life and Environmental Sciences, South Central University of Forestry Science and Technology, Changsha 410004, China;[Binbin Tan; Jiang Wang; Junlong Liu; Yao Deng] College of Chemistry and Chemical Engineering, Central South University of Forestry and Technology, Changsha 410004, China;[Zhihao Zhang; Jing Wang; Huidi Zhang] College of Materials Science and Engineering, Central South University of Forestry and Technology, Changsha 410004, China;Institute of Chemical Disposal and Resource Utilization of Hazardous Wastes, Central South University of Forestry and Technology, Changsha 410004, China;[Ting Yang; Wenlei Wang] College of Chemistry and Chemical Engineering, Central South University of Forestry and Technology, Changsha 410004, China<&wdkj&>Institute of Chemical Disposal and Resource Utilization of Hazardous Wastes, Central South University of Forestry and Technology, Changsha 410004, China
通讯机构：
[Wenlei Wang] C;College of Chemistry and Chemical Engineering, Central South University of Forestry and Technology, Changsha 410004, China<&wdkj&>Institute of Chemical Disposal and Resource Utilization of Hazardous Wastes, Central South University of Forestry and Technology, Changsha 410004, China
摘要：
Human immunoglobulin (HIgG) has gained recognition as a crucial biomarker diagnosing and treating various diseases, particularly in identifying elevated serum levels in conditions like measles and pneumococcal disease. Traditional detection methods, however, are often hindered by inefficiencies, high costs, and potential inaccuracies, underscoring the urgent need for more sensitive, efficient, accurate, and self-calibration methods for HIgG. Here, a novel ZnIn2S4/SnO2 composites was synthesized, featuring uniformly dispersed SnO2 nanoparticles on the flower-like ZnIn2S4 structure, resulting in a type II heterojunction that promotes the separation and transfer of photogenerated carriers. Under optimized conditions, this composite demonstrated remarkable photocurrent enhancements 52 and 195 times greater than that of the individual ZnIn2S4 or SnO2, respectively. A novel dual-mode biosensing platform was subsequently developed, employing the ZnIn2S4/SnO2 composites as both as the photoelectrochemical (PEC) signal generator and antibody carrier. This system utilizes multifunctional CuO NPs with ascorbic acid oxidase-like properties, serving as a secondary antibody label. Upon specific binding to HIgG, a notable decrease in the PEC response occurs due to the catalytic activity of CuO NPs and the antigen-antibody interactions. The introduction of o-phenylenediamine (OPD) further enhances detection by facilitating the formation of a fluorescent substance DHAA. This dual-signal approach yielded excellent linear correlations between both PEC and fluorescence signals and HIgG concentration, achieving low detection limits of 22.5 pg/mL or 8.6 pg/mL. These two signals originated from the same PEC electrode with continuous detection in the absence and presence of OPD, simplifying experimental procedures and enhancing the reliability of detection. The non-toxic, chemically stable ZnIn2S4/SnO2 composites ensures reliable and sensitive detection through photocurrent output after incubation with biomolecules. The integration of nanozyme catalysis, biospecific reactions, and in situ fluorescent products generation promise high selectivity across diverse immunosensing applications.
通讯机构：
[Jiang, F ] C;Cent South Univ Forestry & Technol, Changsha, Peoples R China.
关键词：
Multitasking;driverless;Environment awareness;Traffic target and lane line detection
摘要：
Implementing environmental perception in intelligent vehicles is a crucial application, but the parallel processing of numerous algorithms on the vehicle side is complex, and their integration remains a critical challenge. To address this problem, this paper proposes a multitask detection algorithm Multitask Detection Network (MDNet) based on Cross Stage Partial Networks with Darknet53 Backbone (CSP-DarkNet53) with high feature extraction capability, which can simultaneously detect vehicles, pedestrians, traffic lights, traffic signs, and bicycles as well as lane lines. MDNet obtains exceptional results in multitask scenarios by employing innovative architectural designs consisting of a Feature Extraction Module, Target-level Branches, and Pixel-level Branches. The feature extraction module proposes an improved CSPPF structure to extract features more efficiently for three tasks, facilitating MDNet's capacity. The target-level branch suggests PFPN, which combines features from the backbone network, and the pixel-level branch utilizes a primary feature fusion network and an enhanced C2F_Faster method to spot lane lines more precisely. By incorporating these designs, MDNet's performance in complex environments is enhanced significantly. The algorithm underwent testing on the Berkeley DeepDrive 100K (BDD100K) and Cityscapes datasets, in which it could identify traffic targets and lane lines in numerous challenging settings, resulting in a 9.8 % measure of improvement in detection accuracy map for all three tasks relative to You Only Look Once for Panoptic Driving Perception (YOLOP, a multitask detection network), an 8.9 % improvement in IoU, a 22.1 % improvement in accuracy. It reached a speed of 46fps, which serves the practical applications' requirements more effectively.
作者机构：
[Shuling Hou; Gaoshang Xiao; Huiying Zhou] School of Electronic Information and Physics, Central South University of Forestry and Technology, Changsha, China
通讯机构：
[Huiying Zhou] S;School of Electronic Information and Physics, Central South University of Forestry and Technology, Changsha, China
关键词：
Attack detection;Natural language processing;Security;Vertical domain models;Unknown scenarios dataset
摘要：
In the field of cybersecurity, most research on unknown attack detection still faces challenges such as low detection accuracy, slow detection speed, and imprecise category identification. Therefore, we propose the first combination of vertical language models with unknown scenario attack detection to predict binary and multi-class attacks. Two improved architectures based on the SecureBERT vertical model are built into our method: the fine-tuned FTSecureBert and the lightweight BLWSecureBert. The evaluation results show that our fine-tuned FTSecureBert outperforms the other comparative algorithms. In the binary unknown scenario, only 1% of the False Positive Rate (FPR) is produced. Furthermore, our lightweight BLWSecureBert model reduces the number of parameters by approximately 3.3 times compared to the original, Compared with the other two lightweight models, BLWSecureBert is better considering category prediction, and Matthews Correlation Coefficient (MCC). Moreover, our method offers an efficient evaluation for unbalanced intrusion detection and effectively avoids several pitfalls.
期刊：
Postharvest Biology and Technology,2025年219:113192 ISSN：0925-5214
通讯作者：
Zhou Wenhua
作者机构：
[Yaoying Zeng; Jiaming Zhang; Hui Su; Yubo Xiong; Zhou Wenhua] Central South University of Forestry and Technology, School of Food Science and Engineering, Hunan Key Laboratory of Processed Food for Special Medical Purpose, National Engineering Research Center for Deep Processing of Rice and By-products, 498 Shaoshan South Road, Tianxin District, Changsha City, Hunan Province, China;College of Food and Chemical Engineering, Shaoyang University, Shaoyang, Hunan Province 422000, PR China;Lingling District Market Supervision Administration, Yongzhou City, Hunan Province, China;[Le Xie] Central South University of Forestry and Technology, School of Food Science and Engineering, Hunan Key Laboratory of Processed Food for Special Medical Purpose, National Engineering Research Center for Deep Processing of Rice and By-products, 498 Shaoshan South Road, Tianxin District, Changsha City, Hunan Province, China<&wdkj&>College of Food and Chemical Engineering, Shaoyang University, Shaoyang, Hunan Province 422000, PR China;[Ye Zhao] Central South University of Forestry and Technology, School of Food Science and Engineering, Hunan Key Laboratory of Processed Food for Special Medical Purpose, National Engineering Research Center for Deep Processing of Rice and By-products, 498 Shaoshan South Road, Tianxin District, Changsha City, Hunan Province, China<&wdkj&>Lingling District Market Supervision Administration, Yongzhou City, Hunan Province, China
通讯机构：
[Zhou Wenhua] C;Central South University of Forestry and Technology, School of Food Science and Engineering, Hunan Key Laboratory of Processed Food for Special Medical Purpose, National Engineering Research Center for Deep Processing of Rice and By-products, 498 Shaoshan South Road, Tianxin District, Changsha City, Hunan Province, China
关键词：
Shine Muscat grapes;Melatonin;24-Epibrassinolide;Cell wall metabolism;Reactive oxygen species;Fruit quality
期刊：
Computers and Geotechnics,2025年177:106814 ISSN：0266-352X
通讯作者：
Jun Shen
作者机构：
State Key Laboratory of Intelligent Geotechnics and Tunnelling, College of Civil and Transportation Engineering, Shenzhen University, Shenzhen, Guangdong 518060, China;Key Laboratory of Coastal Urban Resilient Infrastructures (Shenzhen University), Ministry of Education, Shenzhen 518060, China;[Cong Zhang] School of Civil Engineering, Central South University of Forestry and Technology, Changsha 410004, China;[Xiaohua Bao; Junhong Li; Jun Shen; Xiangsheng Chen; Hongzhi Cui] State Key Laboratory of Intelligent Geotechnics and Tunnelling, College of Civil and Transportation Engineering, Shenzhen University, Shenzhen, Guangdong 518060, China<&wdkj&>Key Laboratory of Coastal Urban Resilient Infrastructures (Shenzhen University), Ministry of Education, Shenzhen 518060, China
通讯机构：
[Jun Shen] S;State Key Laboratory of Intelligent Geotechnics and Tunnelling, College of Civil and Transportation Engineering, Shenzhen University, Shenzhen, Guangdong 518060, China<&wdkj&>Key Laboratory of Coastal Urban Resilient Infrastructures (Shenzhen University), Ministry of Education, Shenzhen 518060, China
关键词：
Multivariate joint distribution model;Marine soft soil;Physical property;Correlation analysis;Vine copula
作者机构：
[Deng, Minwen; Liu, Ziyi; Zhou, Haibin; Liu, Donglin; Chen, Qi; Han, Yong; Wang, Xing; Yao, Pingping; Xu, Yuxuan; Zhou, Peiyu; Yao, PP] Cent South Univ, State Key Lab Powder Met, Changsha 410083, Peoples R China.;[Zhou, Haibin] Cent South Univ Forestry & Technol, Hunan Prov Key Lab Mat Surface Interface Sci & Tec, Changsha 410004, Peoples R China.
通讯机构：
[Yao, PP ] C;Cent South Univ, State Key Lab Powder Met, Changsha 410083, Peoples R China.
关键词：
CMMC;C/C-SiC;Pitch coke;Braking
摘要：
By substituting 10 wt% of conventional graphite particles, pitch coke particles with fine mosaics demonstrate superior performance in enhancing the braking properties of copper metal matrix composites (CMMCs) operating at various conditions. When mated with C/C-SiC, the coefficient of friction increases by 18.6 % at low speeds and 38.8 % at high braking speeds, along with a significant enhancement in wear resistance across various counterparts. This improvement is attributed to the incorporation of pitch coke with fine mosaics and superior mechanical properties, which not only imparts high thermal capacity and mechanical strength to the CMMCs but also fosters a synergistic interaction between pitch coke and the iron oxide layer, stabilizing the friction layer.
期刊：
INDUSTRIAL CROPS AND PRODUCTS,2025年223 ISSN：0926-6690
通讯作者：
Li, Yalan;Cheng, FC
作者机构：
[Huang, Houkai; Chen, Bowen; Cheng, Fangchao; Li, Yalan; Huang, Xiaolin; Tang, Zhiwei; Shi, Shenghong; Zhu, Weizhi] Guangxi Univ, Sch Resources Environm & Mat, State Key Lab Featured Met Mat & Life Cycle Safety, Nanning 530004, Peoples R China.;[Wu, Yiqiang; Cheng, Fangchao] Cent South Univ Forestry & Technol, Coll Mat Sci & Engn, Changsha 410004, Peoples R China.
通讯机构：
[Li, YL; Cheng, FC ] G;Guangxi Univ, Sch Resources Environm & Mat, State Key Lab Featured Met Mat & Life Cycle Safety, Nanning 530004, Peoples R China.;Cent South Univ Forestry & Technol, Coll Mat Sci & Engn, Changsha 410004, Peoples R China.
摘要：
With the massive consumption of energy resources and increasingly severe environmental problems, the development of renewable, environmentally friendly, highly efficient energy conversion and storage devices has become a top priority. Here, a microstructure modulation strategy was proposed to fabricate the oriented regenerated cellulose (ORC) dielectric composites with outstanding mechanical and dielectric properties via a combination of dissolution, crosslinking, stretching, and hot-pressing techniques. ORC films with a stretch ratio of 100 % (ORC-100 film) exhibit a significant increase in displacement values (2.96 mu C/cm2), breakdown strength (404.04 MV/m), dielectric constant (14.37 at 1 kHz), and energy density (3.42 J/cm3 at 250 MV/m) as compared to the unstretched regenerated cellulose films. These enhancements are attributed to the anisotropic alignment of cellulose chains and the enhanced crystalline phase of cellulose II, both of which are significantly higher in ORC-100 film. This work offers a feasible and serviceable approach for the development of environmentally friendly cellulose dielectric composites with high performance.
期刊：
Separation and Purification Technology,2025年356:130003 ISSN：1383-5866
通讯作者：
Haiyin Xu<&wdkj&>Zhaohui Yang
作者机构：
[Weiping Xiong; Zhaohui Yang] College of Environmental Science and Engineering, Hunan University, Changsha 410082, China;[Dong He; Shangru Tang; Jiani Gao; Meiying Jia; Rui Guo; Haiyin Xu] College of Life and Environmental Sciences, Central South University of Forestry and Technology, Changsha 410004, China;Changsha Environmental Protection College, Changsha 410004, China;[Jing Huang] Hunan Academy of Forestry and State Key Laboratory of Utilization of Woody Oil Resource, Changsha 410004, China;[Huaming Xie] Hunan Modern Environmental Technology Co., Ltd, Changsha 410004, China
通讯机构：
[Haiyin Xu; Zhaohui Yang] C;College of Life and Environmental Sciences, Central South University of Forestry and Technology, Changsha 410004, China<&wdkj&>College of Environmental Science and Engineering, Hunan University, Changsha 410082, China
摘要：
Aging isda natural and inevitable physiological process that poses a serious threat to physical health, leading to age-related diseases and placing a heavy burden on the public health system. This study explores intervention measures to promote healthy aging and prolong lifespan. Anthocyanins (ACNs), as a class of flavonoids widely presented in fruits, vegetables and grains, exhibit strong antioxidant and anti-inflammatory activities. Recent studies indicate that ACNs exert health effects primarily by interacting with gut microbiota. Here, we introduced the digestion and absorption of ACNs, and mainly elaborated on the role of ACNs in delaying aging through gut microbiota. In addition, we described the changes in gut microbiota mediated by ACNs and their impact on age-related chronic diseases, including cardiovascular diseases, neurodegenerative diseases, cancer, and sarcopenia. Therefore, ACNs have a broad application prospect in the development of functional foods with ant-aging effects by regulating gut microbiota 1 2025 Beijing Academy of Food Sciences. Publishing services by Elsevier B.V on behalf of KeAi Communications Co., Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)..
期刊：
Communications in Nonlinear Science and Numerical Simulation,2025年140:108332 ISSN：1007-5704
通讯作者：
Hao Zhang
作者机构：
[Jun Zhou] College of Computer and Mathematics, Central South University of Forestry and Technology, Changsha, Hunan, 410004, PR China;[Hao Zhang; Mengmeng Liu; Da Xu] School of Mathematics and Statistics, Hunan Normal University, Changsha, Hunan, 410081, PR China
通讯机构：
[Hao Zhang] S;School of Mathematics and Statistics, Hunan Normal University, Changsha, Hunan, 410081, PR China
