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Evaluation of toppling rock slopes using a composite cloud model with DEMATEL–CRITIC method

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Water Science and Engineering 2023年第3期16卷 280-288页

作者： Huan-ling Wang Xu-fei Zhao Hong-jie Chen Kui Yi wei-chau xie wei-ya Xu Research Institute of Geotechnical Engineering Hohai UniversityNanjing 210098China Huaneng Lancang River Hydropower Ltd. Technology R&D CenterKunming 650214China Department of Civil and Environmental Engineering University of WaterlooWaterlooOntario N2L 3G1Canada

Safety evaluation of toppling rock slopes developing in reservoir areas is crucial. To reduce the uncertainty of safety evaluation, this study developed a composite cloud model, which improved the combination weights of the decision-making trial and evaluation laboratory (DEMATEL) and criteria importance through intercriteria correlation (CRITIC) methods. A safety evaluation system was developed according to in situ monitoring data. The backward cloud generator was used to calculate the numerical characteristics of a cloud model of quantitative indices, and different virtual clouds were used to synthesize some clouds into a generalized one. The synthesized numerical characteristics were calculated to comprehensively evaluate the safety of toppling rock slopes. A case study of a toppling rock slope near the Huangdeng Hydropower Station in China was conducted using monitoring data collected since operation of the hydropower project began. The results indicated that the toppling rock slope was moderately safe with a low safety margin. The composite cloud model considers the fuzziness and randomness of safety evaluation and enables interchange between qualitative and quantitative knowledge. This study provides a new theoretical method for evaluating the safety of toppling rock slopes. It can aid in the predication, control, and even prevention of disasters.

关键词： Toppling rock slope Safety evaluation Composite cloud model DEMATEL CRITIC Huangdeng Hydropower Project

A Novel Hybrid Intelligent Prediction Model for Valley Deformation: A Case Study in Xiluodu Reservoir Region, China

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Computers, Materials & Continua 2021年第1期66卷 1057-1074页

作者： Mengcheng Sun weiya Xu Huanling Wang Qingxiang Meng Long Yan wei-chau xie Research Institute of Geotechnical Engineering Hohai UniversityNanjing210098China Key Laboratory of Ministry of Education for Geomechanics and Embankment Engineering Hohai UniversityNanjing210098China Key Laboratory of Coastal Disaster and Defense Ministry of EducationHohai UniversityNanjing210098China Department of Civil and Environmental Engineering University of WaterlooWaterlooN2L 3G1Canada

The narrowing deformation of reservoir valley during the initial operation period threatens the long-term safety of the dam,and an accurate prediction of valley deformation(VD)remains a challenging part of risk *** order to enhance the accuracy of VD prediction,a novel hybrid model combining Ensemble empirical mode decomposition based interval threshold denoising(EEMD-ITD),Differential evolutions—Shuffled frog leaping algorithm(DE-SFLA)and Least squares support vector machine(LSSVM)is *** non-stationary VD series is firstly decomposed into several stationary subseries by EEMD;then,ITD is applied for redundant information denoising on special sub-series,and the denoised deformation is divided into the trend and periodic deformation ***,several relevant triggering factors affecting the VD are considered,from which the input features are extracted by Grey relational analysis(GRA).After that,DE-SFLA-LSSVM is separately performed to predict the trend and periodic deformation with the optimal ***,the two individual forecast components are reconstructed to obtain the final predicted *** VD series monitored in Xiluodu reservoir region are utilized to verify the proposed *** results demonstrate that:(1)Compared with Discrete wavelet transform(DWT),better denoising performance can be achieved by EEMD-ITD;(2)Using GRA to screen the optimal input features can effectively quantify the deformation response relationship to the triggering factors,and reduce the model complexity;(3)The proposed hybrid model in this study displays superior performance on some compared models(e.g.,LSSVM,Backward Propagation neural network(BPNN),and DE-SFLA-BPNN)in terms of forecast accuracy.

关键词： Valley deformation prediction multiple triggering factors DE-SFLALSSVM EEMD-ITD Xiluodu hydropower station

Stiffness-tunable biomaterials provide a good extracellular matrix environment for axon growth and regeneration

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Neural Regeneration Research 2025年第5期20卷 1364-1376页

作者： Ronglin Han Lanxin Luo Caiyan wei Yaru Qiao Jiming xie Xianchao Pan Juan Xing Department of Pathophysiology School of Basic Medical SciencesSouthwest Medical UniversityLuzhouSichuan ProvinceChina Department of Medicinal Chemistry School of PharmacySouthwest Medical UniversityLuzhouSichuan ProvinceChina

Neuronal growth, extension, branching, and formation of neural networks are markedly influenced by the extracellular matrix—a complex network composed of proteins and carbohydrates secreted by cells. In addition to providing physical support for cells, the extracellular matrix also conveys critical mechanical stiffness cues. During the development of the nervous system, extracellular matrix stiffness plays a central role in guiding neuronal growth, particularly in the context of axonal extension, which is crucial for the formation of neural networks. In neural tissue engineering, manipulation of biomaterial stiffness is a promising strategy to provide a permissive environment for the repair and regeneration of injured nervous tissue. Recent research has fine-tuned synthetic biomaterials to fabricate scaffolds that closely replicate the stiffness profiles observed in the nervous system. In this review, we highlight the molecular mechanisms by which extracellular matrix stiffness regulates axonal growth and regeneration. We highlight the progress made in the development of stiffness-tunable biomaterials to emulate in vivo extracellular matrix environments, with an emphasis on their application in neural repair and regeneration, along with a discussion of the current limitations and future prospects. The exploration and optimization of the stiffness-tunable biomaterials has the potential to markedly advance the development of neural tissue engineering.

关键词： alginate axon growth biomaterials extracellular matrix neural repair neurons neuroregeneration polyacrylamide polydimethylsiloxane stiffness

Extending LaSalle’s invariance principle to impulsive switched systems with an application to hybrid epidemic dynamics

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Extending LaSalle’s invariance principle to impulsive switc...

Integration of perioperative features and intragraft TCF7L2 expression to predict lipid metabolic disorder in liver transplant recipients

2010 Chinese Control and Decision Conference

作者： Jun Liu~1,Xinzhi Liu~1,wei-chau xie~2 1.Department of Applied Mathematics 2.Department of Civil and Environmental Engineering University of Waterloo,Waterloo,Ontario N2L 3G1,Canada

＜正＞By introducing the notions of persistent limit set and persistent mode,we extend the classical LaSalle’s invariance principle to hybrid systems exhibiting both impulses and switchings.A weak invariance principle is established for such systems,under a weak dwell-time condition on the impulsive and switching *** weak invariance principle is then applied to derive two asymptotic stability criteria for impulsive switched *** an application of the stability criteria,we investigate a switched SEIR epidemic model with pulse treatment and establish sufficient conditions for the global asymptotic stability of the disease-free solution under weak dwell-time signals.

关键词： Switched system Impulsive system Hybrid system Invariance principle Stability Weak dwell-time Multiple Lyapunov functions Hybrid SEIR model.

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Science China Life Sciences 2025年第1期 297-299页

作者： Junbin Zhou Rongli wei Guanghan Fan Zhengxing Lian Xuanyu Zhang Linsong Tang Zhetuo Qi Haiyang xie Shusen Zheng Qiang wei Xiao Xu Department of Hepatobiliary and Pancreatic Surgery People's Hospital of LishuiAffiliated Lishui Hospital of Wenzhou Medical UniversityThe First Affiliated Hospital of Lishui University NHFPC Key Laboratory of Combined Multi-Organ Transplantation Key Laboratory of Integrated Oncology and Intelligent Medicine of Zhejiang Province Department of Hepatobiliary and Pancreatic SurgeryHangzhou First People's Hospital Department of Hepatobiliary and Pancreatic Surgery The First Affiliated HospitalZhejiang University School of Medicine Department of Urology The Second Affiliated HospitalZhejiang University School of Medicine Department of Hepatobiliary and Pancreatic Surgery Department of Liver TransplantationShulan (Hangzhou) Hospital Hangzhou Medical College Zhejiang University School of Medicine

Dear Editor, Liver transplantation(LT) is the only curative therapy for patients with endstage liver disease(He et al., 2023; Ling et al., 2022). Post-transplant hypertriglyceridemia(PTHT), which has an incidence of up to 32.8% in 6 months after LT, is one of the major post-transplant complications(Toshima et al., 2020).

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Local-contrastive-learning machine with both generalization and adversarial robustness: A statistical physics analysis

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Science China(Physics,Mechanics & Astronomy) 2025年第1期Mechanics & Astronomy) .卷 109-123页

作者： Mingshan xie Yuchen Wang Haiping Huang PMI Lab School of Physics Sun Yat-sen University Guangdong Provincial Key Laboratory of Magnetoelectric Physics and Devices Sun Yat-sen University

Distinct from human cognitive processing, deep neural networks trained by backpropagation can be easily fooled by adversarial examples. To design a semantically meaningful representation learning, we discard backpropagation, and instead, propose a local contrastive learning, where the representations for the inputs bearing the same label shrink(akin to boson) in hidden layers,while those of different labels repel(akin to fermion). This layer-wise learning is local in nature, being biologically plausible.A statistical mechanics analysis shows that the target fermion-pair-distance is a key parameter. Moreover, the application of this local contrastive learning to MNIST benchmark dataset demonstrates that the adversarial vulnerability of standard perceptron can be greatly mitigated by tuning the target distance, i.e., controlling the geometric separation of prototype manifolds.

关键词： machine learning statistical mechanics adversarial robustness neural networks

Multi-layer multi-pass friction rolling additive manufacturing of Al alloy:Toward complex large-scale high-performance components

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International Journal of Minerals,Metallurgy and Materials 2025年第2期32卷 425-438页

作者： Haibin Liu Run Hou Chenghao Wu Ruishan xie Shujun Chen College of Mechanical&Energy Engineering Beijing University of TechnologyBeijing 100124China Chongqing Research Institute of Beijing University of Technology Chongqing 401121China

At present,the emerging solid-phase friction-based additive manufacturing technology,including friction rolling additive man-ufacturing(FRAM),can only manufacture simple single-pass *** this study,multi-layer multi-pass FRAM-deposited alumin-um alloy samples were successfully prepared using a non-shoulder tool *** material flow behavior and microstructure of the over-lapped zone between adjacent layers and passes during multi-layer multi-pass FRAM deposition were studied using the hybrid 6061 and 5052 aluminum *** results showed that a mechanical interlocking structure was formed between the adjacent layers and the adja-cent passes in the overlapped center *** friction and rolling of the tool head led to different degrees of lateral flow and plastic deformation of the materials in the overlapped zone,which made the recrystallization degree in the left and right edge zones of the over-lapped zone the highest,followed by the overlapped center zone and the non-overlapped *** tensile strength of the overlapped zone exceeded 90%of that of the single-pass deposition *** is proved that although there are uneven grooves on the surface of the over-lapping area during multi-layer and multi-pass deposition,they can be filled by the flow of materials during the deposition of the next lay-er,thus ensuring the dense microstructure and excellent mechanical properties of the overlapping *** multi-layer multi-pass FRAM deposition overcomes the limitation of deposition width and lays the foundation for the future deposition of large-scale high-performance components.

关键词： aluminum alloy additive manufacturing solid-state friction stir welding multi-layer multi-pass

Superhydrophobic and corrosion-resistant siloxane-modified MgAl-LDHs coatings on magnesium alloy prepared under mild conditions

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International Journal of Minerals,Metallurgy and Materials 2025年第2期32卷 450-463页

作者： Wenxi Zhang Zhangzelong Zhuo Dan Xu Liang Wu Zhihui xie Chemical Synthesis and Pollution Control Key Laboratory of Sichuan Province College of Chemistry and Chemical EngineeringChina West Normal UniversityNanchong 637002China College of Materials Science and Engineering/National Engineering Research Center for Magnesium Alloys Chongqing UniversityChongqing 400044China

We have developed a superhydrophobic and corrosion-resistant LDH-W/PFDTMS composite coating on the surface of Mg *** composite comprised a tungstate-intercalated(LDH-W)underlayer that was grown at low temperature(relative to hydrothermal reaction conditions)under atmospheric pressure and an outer polysiloxane layer created from a solution containing perfluorodecyltrimethoxysilane(PFDTMS)using a simple immersion *** successful intercalation of tungstate into the LDH phase and the following formation of the polysiloxane layer were confirmed through X-ray diffraction(XRD),Fourier transform infrared(FTIR)spectroscopy,and X-ray photoelectron spectroscopy(XPS).The corrosion resistance of the LDH-W film,both before and after the PFDTMS modification,was evaluated using electrochemical impedance spectroscopy(EIS),Tafel curves,and immersion *** results showed that Mg coated with LDH-W/PFDTMS exhibited significantly enhanced corrosion protection compared to the unmodified LDHW film,with no apparent signs of corrosion after exposure to 3.5wt%NaCl solution for 15 ***,the LDH-W/PFDTMS coating demonstrated superior superhydrophobicity and self-cleaning properties against water and several common beverages,as confirmed by static contact angle and water-repellency *** results offer valuable insights into preparing superhydrophobic and corrosion-resistant LDH-based composite coatings on Mg alloy surfaces under relatively mild reaction conditions.

关键词： Mg alloy corrosion coating layered double hydroxide

Bioinspired Ultrasensitive Flexible Strain Sensors for Real-Time Wireless Detection of Liquid Leakage

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NANO-MICRO LETTERS 2025年第1期17卷 1-18页

作者： Zhou, weilong Du, Yu Chen, Yingying Zhang, Congyuan Ning, Xiaowei xie, Heng Wu, Ting Hu, Jinlian Qu, Jinping Huazhong Univ Sci & Technol Sch Chem & Chem Engn Key Lab Mat Chem Energy Convers & Storage Minist EducHubei Key Lab Mat Chem & Serv Failure Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Hubei Engn Res Ctr Biomat & Med Protect Mat Sch Chem & Chem Engn Wuhan 430074 Peoples R China Wuhan Inst Technol Sch Mat Sci & Engn Wuhan 430205 Peoples R China City Univ Hong Kong Dept Biomed Engn Hong Kong 999077 Peoples R China

Micro-extrusion compression molding and surface modification were proposed for the mass fabrication of a superhydrophobic thermoplastic polyurethane sensor (TCGS).Inspired by scorpions, TCGS features Archimedean spiral crack arrays and micropores, achieving 218.13 sensitivity at 2% strain, a 4300% increase, and over 5000 usage cycles of *** robust superhydrophobicity of TCGS improves sensitivity and stability for detecting small-scale liquid leakage, allowing precise monitoring across various sizes and compositions while providing early warnings in various scenarios. Liquid leakage of pipeline networks not only results in considerable resource wastage but also leads to environmental pollution and ecological imbalance. In response to this global issue, a bioinspired superhydrophobic thermoplastic polyurethane/carbon nanotubes/graphene nanosheets flexible strain sensor (TCGS) has been developed using a combination of micro-extrusion compression molding and surface modification for real-time wireless detection of liquid leakage. The TCGS utilizes the synergistic effects of Archimedean spiral crack arrays and micropores, which are inspired by the remarkable sensory capabilities of scorpions. This design achieves a sensitivity of 218.13 at a strain of 2%, which is an increase of 4300%. Additionally, it demonstrates exceptional durability by withstanding over 5000 usage cycles. The robust superhydrophobicity of the TCGS significantly enhances sensitivity and stability in detecting small-scale liquid leakage, enabling precise monitoring of liquid leakage across a wide range of sizes, velocities, and compositions while issuing prompt alerts. This provides critical early warnings for both industrial pipelines and potential liquid leakage scenarios in everyday life. The development and utilization of bioinspired ultrasensitive flexible strain sensors offer an innovative and effective solution for the early wireless detection of liquid leakage.

关键词： Thermoplastic polyurethane Bioinspired Cracks Liquid leakage Flexible strain sensor