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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

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)

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

A novel solution treatment and aging for powder bed fusion-laser beam Ti-6Al-2Sn-4Zr-6Mo alloy:Microstructural and mechanical characterization

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International Journal of Minerals,Metallurgy and Materials 2025年第2期32卷 414-424页

作者： Gianluca Pirro Alessandra Martucci Alessandro Morri Mariangela Lombardi Lorella Ceschini department of Industrial engineering(DIN) Alma Mater Studiorum-University of BolognaBologna 40136Italy department of Applied Science and Technology(DISAT) Politecnico di TorinoTorino TO 10129Italy

Ti-6Al-4Zr-2Sn-6Mo alloy is one of the most recent titanium alloys processed using powder bed fusion-laser beam(PBF-LB)*** alloy has the potential to replace Ti-6Al-4V in automotive and aerospace applications,given its superior mechanical properties,which are approximately 10%higher in terms of ultimate tensile strength(UTS)and yield strength after appropriate heat *** as-built conditions,the alloy is characterized by the presence of soft orthorhombicα″martensite,necessitating a postprocessing heat treatment to decompose this phase and enhance the mechanical properties of the ***,PBFed Ti6246 components undergo an annealing process that transforms theα″martensite into anα-βlamellar *** primary objective of this research was to develop a solution treatment and aging(STA)heat treatment tailored to the unique microstructure produced by the additive manufacturing process to achieve an ultrafine bilamellar microstructure reinforced by precipitation *** study investigated the effects of various solution temperatures in theα-βfield(ranging from 800 to 875℃),cooling media(air and water),and aging time to determine the optimal heat treatment parameters for achieving the desired bilamellar *** each heat treatment condition,differentα-βmicrostructures were found,varying in terms of theα/βratio and the size of the primaryα-phase *** attention was given to how these factors were influenced by increases in solution temperature and how microhardness correlated with the percentage of the metastableβphase present after *** tests were performed on samples subjected to the most promising heat treatment parameters.A comparison with literature data revealed that the optimized STA treatment enhanced hardness and UTS by13%and 23%,respectively,compared with those of the annealed *** surface analyses were conducted to investigate fracture mechanisms.

关键词： powder bed fusion-laser beam titanium alloys heat treatments mechanical properties fractographic analysis

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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

Tuning the interfacial reaction environment via pH-dependent and induced ions to understand C–N bonds coupling performance in NO3- integrated CO2 reduction to carbon and nitrogen compounds over dual Cu-based N-doped carbon catalyst

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Journal of Energy Chemistry 2025年第1期100卷 273-285页

作者： Tianhang Zhou Chen Shen Zhenghao Wu Xingying Lan Yi Xiao College of Carbon Neutrality Future Technology State Key Laboratory of Heavy Oil Processing China University of Petroleum (Beijing) Institute of Materials Science TU Darmstadt department of Chemistry Xi'an Jiaotong-Liverpool University department of mechanical and Mechatronics engineering and Waterloo Institute of Nanotechnology University of Waterloo Waterloo

Dual atomic catalysts （DAC）,particularly copper （Cu2）-based nitrogen （N） doped graphene,show great potential to effectively convert CO2and nitrate （NO3-） into important industrial chemicals such as ethylene,glycol,acetamide,and urea through an efficient catalytical process that involves C–C and C–N ***,the origin of the coupling activity remained unclear,which substantially hinders the rational design of Cu-based catalysts for the N-integrated CO2reduction reaction （CO2RR）.To address this challenge,this work performed advanced density functional theory calculations incorporating explicit solvation based on a Cu2-based N-doped carbon (Cu2N6C10) catalyst for *** calculations are aimed to gain insight into the reaction mechanisms for the synthesis of ethylene,acetamide,and urea via coupling in the interfacial reaction *** to the sluggishness of CO2,the formation of a solvation electric layer by anions （F-,Cl-,Br-,and I-） and cations (Na+,Mg2+,K+,and Ca2+) leads to electron transfer towards the Cu *** process significantly accelerates the reduction of *** results reveal that*CO intermediates play a pivotal role in N-integrated ***,the Cu2-based N-doped carbon catalyst examined in this study has demonstrated the most potential for C–N coupling to *** findings reveal that through the process of a condensation reaction between*CO and NH2OH for urea synthesis,*NO3-is reduced to*NH3,and*CO2to*CCO at dual Cu atom *** dual-site reduction facilitates the synthesis of acetamide through a nucleophilic reaction between NH3and the ketene ***,we found that the I-and Mg2+ions,influenced by pH,were highly effective for acetamide and ammonia synthesis,except when F-and Ca2+were ***,the mechanisms of C–N bond formation were investigated via ab-initio molecular dynamics simulations,and we found that adjusting the micro-environment can change the dominant side reaction,shift

关键词： pH-dependent micro-environments C–N coupling Dual Cu-based nitrogen carbon catalysts Explicit solvation model Ion stabilizer AIMD

Artificial Circulation System Algorithm:A Novel Bio-Inspired Algorithm

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Computer Modeling in engineering & Sciences 2025年第1期142卷 635-663页

作者： NerminÖzcan Semih Utku Tolga Berber department of Biomedical Technologies Dokuz Eylül UniversityIzmir35390Turkey department of Biomedical engineering Iskenderun Technical UniversityIskenderun31200Turkey department of Computer engineering Dokuz Eylül UniversityIzmir35390Turkey department of Statistics and Computer Sciences Karadeniz Technical UniversityTrabzon61080Turkey

Metaheuristics are commonly used in various fields,including real-life problem-solving and engineering appli*** present work introduces a novel metaheuristic algorithm named the Artificial Circulatory System Algorithm(ACSA).The control of the circulatory system inspires it and mimics the behavior of hormonal and neural regulators involved in this *** work initially evaluates the effectiveness of the suggested approach on 16 two-dimensional test functions,identified as classical benchmark *** method was subsequently examined by application to 12 CEC 2022 benchmark problems of different ***,the paper evaluates ACSA in comparison to 64 metaheuristic methods that are derived from different approaches,including evolutionary,human,physics,and ***,a sequence of statistical tests was undertaken to examine the superiority of the suggested algorithm in comparison to the 7 most widely used algorithms in the existing *** results show that the ACSA strategy can quickly reach the global optimum,avoid getting trapped in local optima,and effectively maintain a balance between exploration and *** outperformed 42 algorithms statistically,according to post-hoc *** also outperformed 9 algorithms *** study concludes that ACSA offers competitive solutions in comparison to popüler methods.

关键词： Bio-inspired evolutionary heuristic metaheuristic optimization

Magnetron sputtered nickel oxide with suppressed interfacial defect states for efficient inverted perovskite solar cells

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Journal of Energy Chemistry 2025年第1期100卷 348-355页

作者： Guoqiang Ma Qin Tan Zhaoning Li Jingwei Xiu Jiafeng Wang Tianle Cheng Dong He Qiang Sun Xuhang Ma Francesco Lamberti Zhubing He department of Materials Science and engineering Institute of Innovative Materials (I2M) Shenzhen Key Laboratory of Full Spectral Solar Electricity Generation (FSSEG)Southern University of Science and Technology (SUSTech) Core Research Facilities Southern University of Science and Technology department of Chemical Sciences Department of Industrial Engineering University of Padova

Widely used spin-coated nickle oxide （NiOx） based perovskite solar cells often suffer from severe interfacial reactions between the NiOxand adjacent perovskite layers due to surface defect states,which inherently impair device performance in a long-term view,even with surface molecule *** this study,we developed high-quality magnetron-sputtered NiOxthin films through detailed process optimization,and compared systematically sputtered and spin-coated NiOxthin film surfaces from materials to *** sputtered NiOxfilms exhibit improved crystallinity,smoother surfaces,and significantly reduced Ni3+or Ni vacancies compared to their spin-coated ***,the interface between the perovskite and sputtered NiOxfilm shows a substantially reduced density of defect *** solar cells （PSCs） fabricated with our optimally sputtered NiOxfilms achieved a high power conversion efficiency （PCE） of up to 19.93%and demonstrated enhanced stability,maintaining 86.2% efficiency during 500 h of maximum power point tracking under one standard sun ***,with the surface modification using (4-(2,7-dibromo-9,9-dimethylacridin-10（9H）-yl)butyl)p hosphonic acid （DMAcPA）,the device PCE was further promoted to 23.07%,which is the highest value reported for sputtered NiOxbased PSCs so far.

关键词： Nickle oxide Magnetron sputter Defect Stability Perovskite solar cell

High-temperature-tolerant flexible supercapacitors: Gel polymer electrolytes and electrode materials

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Journal of Energy Chemistry 2025年第1期100卷 426-457页

作者： Chong Peng Xinyi Huang Mingwei Zhao Shuling Liao Quanhong Yang Nianjun Yang Siyu Yu School of Chemistry & Chemical engineering Southwest University Nanoyang Group Tianjin Key Laboratory of Advanced Carbon and Electrochemical Energy Storage School of Chemical Engineering and Technology and Collaborative Innovation Center of Chemical Science and Engineering (Tianjin) Tianjin University department of Chemistry & IMO-IMOMEC Hasselt University

The development of flexible supercapacitors(FSCs) capable of operating at high temperatures is crucial for expanding the application areas and operating conditions of supercapacitors. Gel polymer electrolytes and electrode materials stand as two key components that significantly impact the efficacy of hightemperature-tolerant FSCs(HT-FSCs). They should not only exhibit high electrochemical performance and excellent flexibility, but also withstand intense thermal stress. Considerable efforts have been devoted to enhancing their thermal stability while maintaining high electrochemical and mechanical performance. In this review, the fundamentals of HT-FSCs are outlined. A comprehensive overview of state-of-the-art progress and achievements in HT-FSCs, with a focus on thermally stable gel polymer electrolytes and electrode materials is provided. Finally, challenges and future perspectives regarding HT-FSCs are discussed, alongside strategies for elevating operational temperatures and *** review offers both theoretical foundations and practical guidelines for designing and manufacturing HT-FSCs, further promoting their widespread adoption across diverse fields.

关键词： Flexible supercapacitors High-temperature tolerance Gel polymer electrolytes Electrode materials