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Tailoring Light–Matter Interactions in Overcoupled Resonator for Biomolecule Recognition and Detection

Nano-Micro Letters 2025年第1期17卷 262-280页

作者： Dongxiao Li Hong Zhou Zhihao Ren Cheng Xu Chengkuo Lee department of electrical and Computer engineering National University of SingaporeSingapore 117583Singapore Center for Intelligent Sensors and MEMS(CISM) National University of SingaporeSingapore 117608Singapore

Plasmonic nanoantennas provide unique opportunities for precise control of light–matter coupling in surface-enhanced infrared absorption(SEIRA)spectroscopy,but most of the resonant systems realized so far suffer from the obstacles of low sensitivity,narrow bandwidth,and asymmetric Fano resonance ***,we demonstrated an overcoupled resonator with a high plasmon-molecule coupling coefficient(μ)(OC-Hμresonator)by precisely controlling the radiation loss channel,the resonator-oscillator coupling channel,and the frequency detuning *** observed a strong dependence of the sensing performance on the coupling state,and demonstrated that OC-Hμresonator has excellent sensing properties of ultra-sensitive(7.25%nm^(−1)),ultra-broadband(3–10μm),and immune asymmetric Fano *** characteristics represent a breakthrough in SEIRA technology and lay the foundation for specific recognition of biomolecules,trace detection,and protein secondary structure analysis using a single array(array size is 100×100μm^(2)).In addition,with the assistance of machine learning,mixture classification,concentration prediction and spectral reconstruction were achieved with the highest accuracy of 100%.Finally,we demonstrated the potential of OC-Hμresonator for SARS-CoV-2 *** findings will promote the wider application of SEIRA technology,while providing new ideas for other enhanced spectroscopy technologies,quantum photonics and studying light–matter interactions.

关键词： Plasmonic nanoantennas Light-matter interaction Surface-enhanced infrared absorption Overcoupled Biosensing

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Endoscopy-assisted lightweight diagnosis system based on transformers for colon polyp detection

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Optoelectronics Letters 2025年第1期21卷 57-64页

作者： FAN Weiming YU Jiahui JU Zhaojie School of Automation and electrical engineering Shenyang Ligong University department of Biomedical engineering Zhejiang University School of Computing University of Portsmouth

The integration of endoscopy has significantly propelled the diagnosis and treatment of gastrointestinal diseases, with colonoscopy establishing itself as the primary method for early diagnosis and preventive care in colorectal cancer(CRC). Although deep learning holds promise in mitigating missed polyp rates, modern endoscopy examinations pose additional challenges, such as image blurring and atomizing. This study explores lightweight yet powerful attention mechanisms, introducing the spatial-channel transformer(SCT), an innovative approach that leverages spatial channel relationships for attention weight calculation. The method utilizes rotation operations for inter-dimensional dependencies, followed by residual transformation, encoding inter-channel and spatial information with minimal computational overhead. Extensive experiments on the CVC-Clinic DB polyp detection dataset, addressing endoscopy pitfalls, underscore the superiority of our SCT over other state-of-the-art methods. The proposed model maintains high performance, even in challenging scenarios.

关键词： Endoscopy

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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1期46卷 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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Luminescence: a new perspective for investigating perovskite precursors

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Science China Materials 2025年第01期 312-313页

作者： Haofeng Zheng Shaocong Hou School of electrical engineering and Automation Wuhan University Wuhan University Shenzhen Research Institute

In the past two decades, perovskite materials have made significant progress in optoelectronic semiconductors, emerging as formidable candidates for the next generation of commercial solar cells, light-emitting diodes (LEDs), and *** the fundamental solution chemistry and photophysics in solution-processed perovskite devices is crucial for comprehending to achieve highly efficient optoelectronic devices.

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Semantic Segmentation of Lumbar Vertebrae Using Meijering U-Net(MU-Net)on Spine Magnetic Resonance Images

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Computer Modeling in engineering & Sciences 2025年第1期142卷 733-757页

作者： Lakshmi S V V Shiloah Elizabeth Darmanayagam Sunil Retmin Raj Cyril department of Computer Science and engineering College of Engineering GuindyAnna UniversityChennai600025India department of Information Technology Madras Institute of TechnologyAnna UniversityChrompetChennai600044India

Lower back pain is one of the most common medical problems in the world and it is experienced by a huge percentage of people *** to its ability to produce a detailed view of the soft tissues,including the spinal cord,nerves,intervertebral discs,and vertebrae,Magnetic Resonance Imaging is thought to be the most effective method for imaging the *** semantic segmentation of vertebrae plays a major role in the diagnostic process of lumbar *** is difficult to semantically partition the vertebrae in Magnetic Resonance Images from the surrounding variety of tissues,including muscles,ligaments,and intervertebral discs.U-Net is a powerful deep-learning architecture to handle the challenges of medical image analysis tasks and achieves high segmentation *** work proposes a modified U-Net architecture namely MU-Net,consisting of the Meijering convolutional layer that incorporates the Meijering filter to perform the semantic segmentation of lumbar vertebrae L1 to L5 and sacral vertebra ***-colour mask images were generated and used as ground truth for training the *** work has been carried out on 1312 images expanded from T1-weighted mid-sagittal MRI images of 515 patients in the Lumbar Spine MRI Dataset publicly available from Mendeley *** proposed MU-Net model for the semantic segmentation of the lumbar vertebrae gives better performance with 98.79%of pixel accuracy(PA),98.66%of dice similarity coefficient(DSC),97.36%of Jaccard coefficient,and 92.55%mean Intersection over Union(mean IoU)metrics using the mentioned dataset.

关键词： Computer aided diagnosis(CAD) magnetic resonance imaging(MRI) semantic segmentation lumbar vertebrae deep learning U-Net model

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An SPH Framework for Earthquake-Induced Liquefaction Hazard Assessment of Geotechnical Structures

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Computer Modeling in engineering & Sciences 2025年第1期142卷 251-277页

作者： Sourabh Mhaski G.V.Ramana department of Civil engineering Indian Institute of Technology DelhiNew Delhi110016India

Earthquake-induced soil liquefaction poses significant risks to the stability of geotechnical structures *** understanding of the liquefaction triggering,and the post-failure large deformation behaviour is essential for designing resilient *** present study develops a Smoothed Particle Hydrodynamics(SPH)framework for earthquake-induced liquefaction hazard assessment of geotechnical *** coupled flowdeformation behaviour of soils subjected to cyclic loading is described using the PM4Sand model implemented in a three-phase,single-layer SPH framework.A staggered discretisation scheme based on the stress particle SPH approach is adopted to minimise numerical inaccuracies caused by zero-energy modes and tensile ***,non-reflecting boundary conditions for seismic analysis of semi-infinite soil domains using the SPH method are *** numerical framework is employed for the analysis of cyclic direct simple shear test,seismic analysis of a level ground site,and liquefaction-induced failure of the Lower San Fernando *** agreement for liquefaction triggering and post-failure behaviour demonstrates that the SPH framework can be utilised to assess the effect of seismic loading on field-scale geotechnical *** present study also serves as the basis for future advancements of the SPH method for applications related to earthquake geotechnical engineering.

关键词： Earthquake seismic liquefaction stress particle PM4Sand smoothed particle hydrodynamics(SPH)

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Steel Surface Defect Recognition in Smart Manufacturing Using Deep Ensemble Transfer Learning-Based Techniques

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Computer Modeling in engineering & Sciences 2025年第1期142卷 231-250页

作者： Tajmal Hussain Jongwon Seok department of Information and Communication engineering Changwon National UniversityChangwon51140Republic of Korea

Smart manufacturing and Industry 4.0 are transforming traditional manufacturing processes by utilizing innovative technologies such as the artificial intelligence(AI)and internet of things(IoT)to enhance efficiency,reduce costs,and ensure product *** light of the recent advancement of Industry 4.0,identifying defects has become important for ensuring the quality of products during the manufacturing *** this research,we present an ensemble methodology for accurately classifying hot rolled steel surface defects by combining the strengths of four pre-trained convolutional neural network(CNN)architectures:VGG16,VGG19,Xception,and Mobile-Net V2,compensating for their individual *** evaluated our methodology on the Xsteel surface defect dataset(XSDD),which comprises seven different *** ensemble methodology integrated the predictions of individual models through two methods:model averaging and weighted *** evaluation showed that the model averaging ensemble achieved an accuracy of 98.89%,a recall of 98.92%,a precision of 99.05%,and an F1-score of 98.97%,while the weighted averaging ensemble reached an accuracy of 99.72%,a recall of 99.74%,a precision of 99.67%,and an F1-score of 99.70%.The proposed weighted averaging ensemble model outperformed the model averaging method and the individual models in detecting defects in terms of accuracy,recall,precision,and *** analysis with recent studies also showed the superior performance of our methodology.

关键词： Smart manufacturing CNN steel defects ensemble models

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Stability Prediction in Smart Grid Using PSO Optimized XGBoost Algorithm with Dynamic Inertia Weight Updation

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Computer Modeling in engineering & Sciences 2025年第1期142卷 909-931页

作者： Adel Binbusayyis Mohemmed Sha department of Software engineering College of Computer engineering and Sciences in Al-Kharj Prince Sattam Bin Abdulaziz UniversityAl-Kharj11942Saudi Arabia

Prediction of stability in SG(Smart Grid)is essential in maintaining consistency and reliability of power supply in grid *** the fluctuations in power generation and consumption patterns of smart cities assists in effectively managing continuous power supply in the *** also possesses a better impact on averting overloading and permitting effective energy *** though many traditional techniques have predicted the consumption rate for preserving stability,enhancement is required in prediction measures with minimized *** overcome the complications in existing studies,this paper intends to predict stability from the smart grid stability prediction dataset using machine learning *** accomplish this,pre-processing is performed initially to handle missing values since it develops biased models when missing values are mishandled and performs feature scaling to normalize independent data ***,the pre-processed data are taken for training and *** that,the regression process is performed using Modified PSO(Particle Swarm Optimization)optimized XGBoost Technique with dynamic inertia weight update,which analyses variables like gamma(G),reaction time(tau1–tau4),and power balance(p1–p4)for providing effective future stability in *** PSO attains optimal solution by adjusting position through dynamic inertial weights,it is integrated with XGBoost due to its scalability and faster computational speed *** hyperparameters of XGBoost are fine-tuned in the training process for achieving promising outcomes on *** results are measured through evaluation metrics such as MSE(Mean Square Error)of 0.011312781,MAE(Mean Absolute Error)of 0.008596322,and RMSE(Root Mean Square Error)of 0.010636156 and MAPE(Mean Absolute Percentage Error)value of 0.0052 which determine the efficacy of the system.

关键词： Smart Grid machine learning particle swarm optimization XGBoost dynamic inertia weight update

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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1期46卷 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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Nano-Enhanced Dairy Scum Biodiesel Blends:Unleashing the Power of Aluminium Oxide for Sustainable and Efficient Engine Performance

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Journal of Thermal Science 2025年第1期 283-302页

作者： Veeranna MODI Prasad B.RAMPURE Sunil Kumar SHETTY Madeva NAGARAL Channa Keshava NAIK N Johar MGM Muhammad Irsyad ABDULLAH Abdullah I.AL-MANSOUR Shamshad ALAM KLE College of engineering and Technology ChikodiVisvesvaraya Technological University Nitte (Deemed to be University) NMAM Institute of Technology (NMAMIT)Department of Mechanical Engineering Aircraft Research and Design Centre HAL department of Mechanical engineering BGS College of Engineering and TechnologyBengaluruAffiliated to Visvesvaraya Technological University Management and Science University department of Civil engineering College of EngineeringKing Saud University

This study investigates the effect of aluminium oxide nanoparticlesaddition to biodiesel blends made from dairy milk scum on performance and combustion characteristics of the diesel *** dispersion of Al2O3nanoparticles in B20 blends at different concentrations was done with the help of *** number of blends were prepared for the *** Machine learning algorithms(Random Forest（RF）and CatBoost) was used for the *** results show that in comparison to biodiesel blends without nanoparticles,the kinematic viscosity and density is higher for fuel blends with *** these Fuel blends have higher calorific *** blends exhibited reduced Brake Specific Fuel Consumption（BSFC） of2.85% than the blends without nano particles(Dairy Scum Methyl Ester Biodiesel 20%+Neat Diesel 80%（in volume）,DSMEB20),57.14% less CO,40.8% less hydrocarbon,and increased NOxemissions compared to conventional diesel,contributing to the development of environmentally friendly and renewable biofuel blends with *** B20NP30 is the optimal blend for performance and emission *** study concludes with findings on enhanced Brake Thermal Efficiency（BTE） of 26.29% in 3×10-5（in volume） Al2O3nanoparticle-blended DSME B20 and other DSME B20 fuel blends,emphasizing the importance of optimal nanoparticle *** correlation matrix shows how engine load,efficiency measures（BTE,BSFC）,and emissions（CO,CO2,NOx,Smoke） are connected in complex *** results help us understand the complicated dynamics of engine performance and emission characteristics ***'s diagram for BTE and BSFC shows that CatBoost-based BTE models perform superior to RF-based models during the training as well as testing *** results were obtained for CO and CO2emission results.

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