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Bearing Fault Diagnosis Based on the Markov Transition Field and SE-IShufflenetV2 Model

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Structural Durability & Health Monitoring 2025年第1期19卷 125-144页

作者： Chaozhi Cai Tiexin Xu Jianhua Ren Yingfang Xue School of mechanical and Equipment engineering Hebei University of EngineeringHandan056038China

A bearing fault diagnosis method based on the Markov transitionﬁeld(MTF)and SEnet(SE)-IShufﬂenetV2 model is proposed in this paper due to the problems of complex working conditions,low fault diagnosis accuracy,and poor generalization of rolling ***,MTF is used to encode one-dimensional time series vibration sig-nals and convert them into time-dependent and unique two-dimensional feature ***,the generated two-dimensional dataset is fed into the SE-IShufﬂenetV2 model for training to achieve fault feature extraction and classiﬁ*** paper selects the bearing fault datasets from Case Western Reserve University and Paderborn University to experimentally verify the effectiveness and superiority of the proposed *** generalization performance of the proposed method is tested under the variable load condition and different signal-to-noise ratios(SNRs).The experimental results show that the average accuracy of the proposed method under different working conditions is 99.2%without adding *** accuracy under different working conditions from 0 to 1 HP is 100%.When the SNR is 0 dB,the average accuracy of the proposed method can still reach 98.7%under varying working ***,the bearing fault diagnosis method proposed in this paper is characterized by high accuracy,strong anti-noise ability,and ***,the proposed method can also overcome the inﬂuence of variable working conditions on diagnosis accuracy,providing method support for the accurate diagnosis of bearing faults under strong noise and variable working conditions.

关键词： Bearings Markov transitionﬁeld SE-IShufﬂenetV2

Influence of introducing Zr,Ti,Nb and Ce elements on externally solidified crystals and mechanical properties of high-pressure die-casting Al–Si alloy

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International Journal of Minerals,Metallurgy and Materials 2025年第1期32卷 147-153页

作者： Junjie Li Wenbo Yu Zhenyu Sun Weichen Zheng Liangwei Zhang Yanling Xue Wenning Liu Shoumei Xiong Center of Materials Science and engineering School of Mechanical and Electronic Control EngineeringBeijing Jiaotong UniversityBeijing 100044China Traffic&Transportation engineering Central South UniversityChangsha 410075China Shanghai Synchrotron Radiation Facility Shanghai Advanced Research InstituteChinese Academy of SciencesShanghai 201204China School of Materials Science and engineering Tsinghua UniversityBeijing 100084China

High pressure die casting(HPDC)AlSi10Mn Mg alloy castings are widely used in the automobile *** can optimize the mechanical properties of castings through heat treatment,while the release of thermal stress arouses the deformation of large integrated ***,the development of non-heat treatment Al alloys is becoming the hot *** addition,HPDC contains externally solidified crystals(ESCs),which are detrimental to the mechanical properties of *** achieve high strength and toughness of non-heat treatment die-casting Al-Si alloy,we used AlSi9Mn alloy as matrix with the introduction of Zr,Ti,Nb,and *** influences on ESCs and mechanical properties were systematically investigated through three-dimensional reconstruction and thermodynamic *** results reveal that the addition of Ti increased ESCs'size and porosity,while the introduction of Nb refined ESCs and decreased ***,large-sized Al_3(Zr,Ti)phases formed and degraded the mechanical *** introduction of Ce resulted in the poisoning effect and reduced mechanical properties.

关键词： aluminium alloy high-pressure die-casting externally solidified crystals non-heat treatment

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Dynamic stress concentration in an infinitely long cylindrical cavity due to a point spherical source embedded within a fluid-saturated poroelastic formation of infinite extent

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Applied Mathematics and Mechanics(English Edition) 2025年第01期 139-156页

作者： H.HOSSEINI O.BALILASHAKI department of mechanical engineering Faculty of EngineeringGolestan University

The effects of a harmonically exciting monopole source on an infinitely long cylindrical cavity embedded entirely within a fluid-saturated poroelastic formation of infinite extent are examined theoretically. It is assumed that the source is located outside the cavity at a specified distance from the borehole axis. The magnitudes of the hoop and radial stresses beside the pore pressures exerted on the interface and inside the porous medium surrounding the borehole are calculated and discussed. Biot's poroelastic modeling along with three types of boundary conditions for the cylindrical interface including the ideal fluid, empty borehole, and rigid inclusion with a hard boundary is employed for the analysis. Utilizing a proper translational addition theorem for expressing the incident spherical wave in terms of cylindrical wave expansions, the proposed boundary conditions at the interface are satisfied. Stresses are formulated by means of wave potential functions in a three-dimensional(3D) manner. The effects of the frequency and the radial distance between the source and borehole on the induced stresses are examined for the first cylindrical modes over frequency spectra. Two permeability conditions for the interface and three types of soils for the porous formation are considered throughout the analysis. To give an overall outline of the study, a numerical example is presented. The results clearly indicate that the distance is a key parameter and has considerable effects on the induced stress values. In addition, the interface permeability condition and soil characteristics play an important role in determining the dynamic response of the borehole. Finally,the obtained results are compared with the relevant analyses existing in the literature for some limit cases, and good agreement is achieved.

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Nonlinear forced vibration in a subcritical regime of a porous functionally graded pipe conveying fluid with a retaining clip

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Applied Mathematics and Mechanics(English Edition) 2025年第01期 101-122页

作者： M.GHOLAMI M.EFTEKHARI department of mechanical engineering Shahid Bahonar University of Kerman

This study examines the nonlinear behaviors of a clamped-clamped porous pipe made of a functionally graded material(FGM) that conveys fluids and is equipped with a retaining clip, focusing on primary resonance and subcritical dynamics. The nonlinear governing equations for the FGM pipe are derived by the extended Hamilton's principle, and subsequently discretized through the application of the Galerkin *** direct method of multi-scales is then used to solve the derived equations. A thorough analysis of various parameters, including the clip stiffness, the power-law index, the porosity, and the clip location, is conducted to gain a comprehensive understanding of the system's nonlinear dynamics. Through the analysis of the first natural frequency, the study highlights the influence of the flow velocity and the clip stiffness, while the comparisons with metallic pipes emphasize the role of FGM composition. The examination of the forced response curves reveals saddle-node bifurcations and their dependence on parameters such as the detuning parameter and the power-law index, offering valuable insights into the system's nonlinear resonant behavior. Furthermore, the frequency-response curves illustrate the hardening nonlinearities influenced by factors such as the porosity and the clip stiffness, revealing nuanced effects on the system response and resonance characteristics. This comprehensive analysis enhances the understanding of nonlinear behaviors in FGM porous pipes with a retaining clip, providing key insights for practical engineering applications in system design and optimization.

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Few-shot learning for screening 2D Ga2CoS4-x supported single-atom catalysts for hydrogen production

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Journal of Energy Chemistry 2025年第01期 665-673页

作者： Nabil Khossossi Poulumi Dey department of mechanical engineering (ME) Delft University of Technology

Hydrogen generation and related energy applications heavily rely on the hydrogen evolution reaction（HER）,which faces challenges of slow kinetics and high *** electrocatalysts,particularly single-atom catalysts （SACs） on two-dimensional （2D） materials,are *** study presents a few-shot machine learning （ML） assisted high-throughput screening of 2D septuple-atomic-layer Ga2CoS4-xsupported SACs to predict HER catalytic ***,density functional theory （DFT）calculations showed that 2D Ga2CoS4is inactive for ***,defective Ga2CoS4-x（x=0–0.25）monolayers exhibit excellent HER activity due to surface sulfur vacancies （SVs）,with predicted overpotentials （0–60 mV） comparable to or lower than commercial Pt/C,which typically exhibits an overpotential of around 50 m V in the acidic electrolyte,when the concentration of surface SV is lower than 8.3%.SVs generate spin-polarized states near the Fermi level,making them effective HER *** demonstrate ML-accelerated HER overpotential predictions for all transition metal SACs on 2D *** DFT data from 18 SACs,an ML model with high prediction accuracy and reduced computation time was *** intrinsic descriptor linking SAC atomic properties to HER overpotential was *** study thus provides a framework for screening SACs on 2D materials,enhancing catalyst design.

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Congruent Feature Selection Method to Improve the Efficacy of Machine Learning-Based Classification in Medical Image Processing

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Computer Modeling in engineering & Sciences 2025年第1期142卷 357-384页

作者： Mohd Anjum Naoufel Kraiem Hong Min Ashit Kumar Dutta Yousef Ibrahim Daradkeh department of Computer engineering Aligarh Muslim UniversityAligarh202002India College of Computer Science King Khalid UniversityAbha61413Saudi Arabia School of Computing Gachon UniversitySeongnam13120Republic of Korea department of Computer Science and Information Systems College of Applied SciencesAlMaarefa UniversityRiyadh13713Saudi Arabia department of Computer engineering and Information College of Engineering in Wadi AlddawasirPrince Sattam bin Abdulaziz UniversityAl-Kharj16273Saudi Arabia

Machine learning(ML)is increasingly applied for medical image processing with appropriate learning *** applications include analyzing images of various organs,such as the brain,lung,eye,etc.,to identify specific flaws/diseases for *** primary concern of ML applications is the precise selection of flexible image features for pattern detection and region *** of the extracted image features are irrelevant and lead to an increase in computation ***,this article uses an analytical learning paradigm to design a Congruent Feature Selection Method to select the most relevant image *** process trains the learning paradigm using similarity and correlation-based features over different textural intensities and pixel *** similarity between the pixels over the various distribution patterns with high indexes is recommended for disease ***,the correlation based on intensity and distribution is analyzed to improve the feature selection ***,the more congruent pixels are sorted in the descending order of the selection,which identifies better regions than the ***,the learning paradigm is trained using intensity and region-based similarity to maximize the chances of ***,the probability of feature selection,regardless of the textures and medical image patterns,is *** process enhances the performance of ML applications for different medical image *** proposed method improves the accuracy,precision,and training rate by 13.19%,10.69%,and 11.06%,respectively,compared to other models for the selected *** mean error and selection time is also reduced by 12.56%and 13.56%,respectively,compared to the same models and dataset.

关键词： Computer vision feature selection machine learning region detection texture analysis image classification medical images

Advancements in Liver Tumor Detection:A Comprehensive Review of Various Deep Learning Models

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Computer Modeling in engineering & Sciences 2025年第1期142卷 91-122页

作者： Shanmugasundaram Hariharan D.Anandan Murugaperumal Krishnamoorthy Vinay Kukreja Nitin Goyal Shih-Yu Chen Deptartment of Artificial Intelligence and Data Science Vardhaman College of EngineeringHyderabad501218India Deptartment of CSE V.S.B College of EngineeringKarur639111India Deptartment of Electrical and Electronics engineering Vardhaman College of EngineeringHyderabad501218India Centre for Research Impact&Outcome Chitkara UniversityRajpura140401PunjabIndia department of Computer Science and engineering School of Engineering and TechnologyCentral University of HaryanaMahendergarh123031HaryanaIndia department of Computer Science and Information engineering National Yunlin University of Science and TechnologyYunlin64002Taiwan Intelligence Recognition Industry Service Research Center National Yunlin University of Science and TechnologyYunlin64002Taiwan

Liver cancer remains a leading cause of mortality worldwide,and precise diagnostic tools are essential for effective treatment *** Tumors(LTs)vary significantly in size,shape,and location,and can present with tissues of similar intensities,making automatically segmenting and classifying LTs from abdominal tomography images crucial and *** review examines recent advancements in Liver Segmentation(LS)and Tumor Segmentation(TS)algorithms,highlighting their strengths and limitations regarding precision,automation,and *** metrics are utilized to assess key detection algorithms and analytical methods,emphasizing their effectiveness and relevance in clinical *** review also addresses ongoing challenges in liver tumor segmentation and identification,such as managing high variability in patient data and ensuring robustness across different imaging *** suggests directions for future research,with insights into technological advancements that can enhance surgical planning and diagnostic accuracy by comparing popular *** paper contributes to a comprehensive understanding of current liver tumor detection techniques,provides a roadmap for future innovations,and improves diagnostic and therapeutic outcomes for liver cancer by integrating recent progress with remaining challenges.

关键词： Liver tumor detection liver tumor segmentation image processing liver tumor diagnosis feature extraction tumor classification deep learning machine learning

Bioinspired Passive Tactile Sensors Enabled by Reversible Polarization of Conjugated Polymers

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Nano-Micro Letters 2025年第1期17卷 361-377页

作者： Feng He Sitong Chen Ruili Zhou Hanyu Diao Yangyang Han Xiaodong Wu School of mechanical engineering Sichuan UniversityChengdu 610065People’s Republic of China School of Software engineering Chongqing University of Posts and TelecommunicationsChongqing 400065People’s Republic of China State Key Laboratory of Polymer Materials engineering Sichuan UniversityChengdu 610065People’s Republic of China

Tactile perception plays a vital role for the human body and is also highly desired for smart prosthesis and advanced *** to active sensing devices,passive piezoelectric and triboelectric tactile sensors consume less power,but lack the capability to resolve static ***,we address this issue by utilizing the unique polarization chemistry of conjugated polymers for the first time and propose a new type of bioinspired,passive,and bio-friendly tactile sensors for resolving both static and dynamic ***,to emulate the polarization process of natural sensory cells,conjugated polymers(including poly(3,4-ethylenedioxythiophen e):poly(styrenesulfonate),polyaniline,or polypyrrole)are controllably polarized into two opposite states to create artificial potential *** controllable and reversible polarization process of the conjugated polymers is fully in situ ***,a micro-structured ionic electrolyte is employed to imitate the natural ion channels and to encode external touch stimulations into the variation in potential difference *** with the currently existing tactile sensing devices,the developed tactile sensors feature distinct characteristics including fully organic composition,high sensitivity(up to 773 mV N^(−1)),ultralow power consumption(nW),as well as superior *** demonstrations,both single point tactile perception(surface texture perception and material property perception)and two-dimensional tactile recognitions(shape or profile perception)with high accuracy are successfully realized using self-defined machine learning *** tactile sensing concept innovation based on the polarization chemistry of conjugated polymers opens up a new path to create robotic tactile sensors and prosthetic electronic skins.

关键词： Passive tactile sensors Reversible polarization of conjugated polymers Tactile perception Machine learning algorithm Object recognition

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Potassium ions and cyano group modified g-C3N4 for effective generation of H2O2 through two-electron oxygen reduction

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Science China Chemistry 2025年第01期 192-200页

作者： Dongying Wang Shulan Pu Yongmin Chen Ke Lei Yujie Duan Linjiao Mao Xuhui Zeng Xi Luo Yuntao Zhang Yuqin Dong Jin Zhong Zhang Yan Sun School of mechanical engineering Chengdu University department of Chemistry and Biochemistry University of California

Potassium ions （K+） doped graphitic carbon nitride （g-C3N4） was prepared by a thermal etching method using potassium hydroxide （KOH） as an ion *** transform infrared spectroscopy （FTIR） and X-ray photoelectron spectroscopy （XPS）results showed that the generation of the cyano group was detected while introducing K+.Under simulated sunlight irradiation,the sample with a K+doping amount of 10%showed the highest hydrogen peroxide （H2O2） generation rate of2,140.2μmol *** apparent quantum yield （AQY） at 400 nm and the solar-to-chemical conversion （SCC） are 4.35%and1.23%,respectively.K+acted as a bridge between g-C3N4layers,which enhanced charge transfer ***,the cyano group enhanced the adsorption capacity of protons （H+） and promoted the yield of *** catalyst exhibited excellent photocatalytic stability based on four-cycle *** addition,a mechanism study showed that superoxide radicals （·O2-）were the most important active species in the reaction *** production of H2O2was achieved through consecutive single-electron *** study deepens the understanding of the oxygen reduction reaction process and opens up a new venue for improving H2O2generation.

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