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Regression analysis of squeezing-induced hybrid nanofluid flow in Darcy-Forchheimer porous medium

Applied Mathematics and Mechanics(English Edition) 2025年第1期46卷 193-208页

作者： K.MUHAMMAD M.SARFRAZ department of Humanities and sciences School of Electrical Engineering and Computer Science National University of Sciences and Technology department of Mathematics Quaid-i-Azam University

This article presents a mathematical model addressing a scenario involving a hybrid nanofluid flow between two infinite parallel plates. One plate remains stationary, while the other moves downward at a squeezing velocity. The space between these plates contains a Darcy-Forchheimer porous medium. A mixture of water-based fluid with gold(Au) and silicon dioxide(Si O2) nanoparticles is formulated. In contrast to the conventional Fourier's heat flux equation, this study employs the Cattaneo-Christov heat flux equation. A uniform magnetic field is applied perpendicular to the flow direction, invoking magnetohydrodynamic(MHD) effects. Further, the model accounts for Joule heating, which is the heat generated when an electric current passes through the fluid. The problem is solved via NDSolve in MATHEMATICA. Numerical and statistical analyses are conducted to provide insights into the behavior of the nanomaterials between the parallel plates with respect to the flow, energy transport, and skin *** findings of this study have potential applications in enhancing cooling systems and optimizing thermal management strategies. It is observed that the squeezing motion generates additional pressure gradients within the fluid, which enhances the flow rate but reduces the frictional drag. Consequently, the fluid is pushed more vigorously between the plates, increasing the flow velocity. As the fluid experiences higher flow rates due to the increased squeezing effect, it spends less time in the region between the plates. The thermal relaxation, however, abruptly changes the temperature, leading to a decrease in the temperature fluctuations.

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Inspires effective alternatives to backpropagation:predictive coding helps understand and build learning

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Neural Regeneration Research 2025年第11期20卷 3215-3216页

作者： Zhenghua Xu Miao Yu Yuhang Song School of Health sciences and Biomedical Engineering Hebei University of TechnologyTianjinChina department of computer Science University of OxfordOxfordUK

Artificial neural networks are capable of machine learning by simulating the hiera rchical structure of the human *** enable learning by brain and machine,it is essential to accurately identify and correct the prediction errors,referred to as credit assignment(Lillicrap et al.,2020).It is critical to develop artificial intelligence by understanding how the brain deals with credit assignment in neuroscience.

关键词： assignment learning enable

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A Novel Self-Supervised Learning Network for Binocular Disparity Estimation

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computer Modeling in Engineering & sciences 2025年第1期142卷 209-229页

作者： Jiawei Tian Yu Zhou Xiaobing Chen Salman A.AlQahtani Hongrong Chen Bo Yang Siyu Lu Wenfeng Zheng department of computer Science and Engineering Major in Bio Artificial IntelligenceHanyang UniversityAnsan-si15577Republic of Korea School of Electrical and computer Engineering Louisiana State UniversityBaton RougeLA 70803USA department of computer Engineering College of Computer and Information SciencesKing Saud UniversityRiyadh11574Saudi Arabia School of Automation University of Electronic Science and Technology of ChinaChengdu610054China

Two-dimensional endoscopic images are susceptible to interferences such as specular reflections and monotonous texture illumination,hindering accurate three-dimensional lesion reconstruction by surgical *** study proposes a novel end-to-end disparity estimation model to address these *** approach combines a Pseudo-Siamese neural network architecture with pyramid dilated convolutions,integrating multi-scale image information to enhance robustness against lighting *** study introduces a Pseudo-Siamese structure-based disparity regression model that simplifies left-right image comparison,improving accuracy and *** model was evaluated using a dataset of stereo endoscopic videos captured by the Da Vinci surgical robot,comprising simulated silicone heart sequences and real heart video *** results demonstrate significant improvement in the network’s resistance to lighting interference without substantially increasing ***,the model exhibited faster convergence during training,contributing to overall performance *** study advances endoscopic image processing accuracy and has potential implications for surgical robot applications in complex environments.

关键词： Parallax estimation parallax regression model self-supervised learning Pseudo-Siamese neural network pyramid dilated convolution binocular disparity estimation

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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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MARIE:One-Stage Object Detection Mechanism for Real-Time Identifying of Firearms

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computer Modeling in Engineering & sciences 2025年第1期142卷 279-298页

作者： Diana Abi-Nader Hassan Harb Ali Jaber Ali Mansour Christophe Osswald Nour Mostafa Chamseddine Zaki computer Science department Faculty of SciencesLebanese UniversityBeirut146404Lebanon College of Engineering and technology American University of the Middle EastEgaila54200Kuwait Lab-STICC CNRS UMR 6285ENSTA-BretagneBrest29200France

Security and safety remain paramount concerns for both governments and individuals *** today’s context,the frequency of crimes and terrorist attacks is alarmingly increasing,becoming increasingly intolerable to ***,there is a pressing need for swift identification of potential threats to preemptively alert law enforcement and security forces,thereby preventing potential attacks or violent *** advancements in big data analytics and deep learning have significantly enhanced the capabilities of computer vision in object detection,particularly in identifying *** paper introduces a novel automatic firearm detection surveillance system,utilizing a one-stage detection approach named MARIE(Mechanism for Realtime Identification of Firearms).MARIE incorporates the Single Shot Multibox Detector(SSD)model,which has been specifically optimized to balance the speed-accuracy trade-off critical in firearm detection *** SSD model was further refined by integrating MobileNetV2 and InceptionV2 architectures for superior feature extraction *** experimental results demonstrate that this modified SSD configuration provides highly satisfactory performance,surpassing existing methods trained on the same dataset in terms of the critical speedaccuracy *** these innovations,MARIE sets a new standard in surveillance technology,offering a robust solution to enhance public safety effectively.

关键词： Firearm and gun detection single shot multi-box detector deep learning one-stage detector MobileNet inception convolutional neural network

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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

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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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Multi-Step Clustering of Smart Meters Time Series:Application to Demand Flexibility Characterization of SME Customers

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computer Modeling in Engineering & sciences 2025年第1期142卷 869-907页

作者： Santiago Bañales Raquel Dormido Natividad Duro department of computer sciences and Automatic Control Universidad Nacional de Educación a Distancia(UNED)Madrid28040Spain Iberdrola Innovation Middle East Doha210177Qatar

Customer segmentation according to load-shape profiles using smart meter data is an increasingly important application to vital the planning and operation of energy systems and to enable citizens’participation in the energy *** study proposes an innovative multi-step clustering procedure to segment customers based on load-shape patterns at the daily and intra-daily time *** meter data is split between daily and hourly normalized time series to assess monthly,weekly,daily,and hourly seasonality patterns *** dimensionality reduction implicit in the splitting allows a direct approach to clustering raw daily energy time series *** intraday clustering procedure sequentially identifies representative hourly day-unit profiles for each customer and the entire *** the first time,a step function approach is applied to reduce time series *** attributes embedded in surveys are employed to build external clustering validation metrics using Cramer’s V correlation factors and to identify statistically significant determinants of load-shape in energy *** addition,a time series features engineering approach is used to extract 16 relevant demand flexibility indicators that characterize customers and corresponding clusters along four different axes:available Energy(E),Temporal patterns(T),Consistency(C),and Variability(V).The methodology is implemented on a real-world electricity consumption dataset of 325 Small and Medium-sized Enterprise(SME)customers,identifying 4 daily and 6 hourly easy-to-interpret,well-defined *** application of the methodology includes selecting key parameters via grid search and a thorough comparison of clustering distances and methods to ensure the robustness of the *** research can test the scalability of the methodology to larger datasets from various customer segments(households and large commercial)and locations with different weather and socioeconomic conditio

关键词： Electric load clustering load profiling smart meters machine learning data mining demand flexibility demand response

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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

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Einstein Probe discovery of EP240408a: A peculiar X-ray transient with an intermediate timescale

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Science China(Physics,Mechanics & Astronomy) 2025年第1期Mechanics & Astronomy) .卷 222-240页

作者： Wenda Zhang Weimin Yuan Zhixing Ling Yong Chen Nanda Rea Arne Rau Zhiming Cai Huaqing Cheng Francesco Coti Zelati Lixin Dai Jingwei Hu Shumei Jia Chichuan Jin Dongyue Li Paul O’Brien Rongfeng Shen Xinwen Shu Shengli Sun Xiaojin Sun Xiaofeng Wang Lei Yang Bing Zhang Chen Zhang Shuang-Nan Zhang Yonghe Zhang Jie An David Buckley Alexis Coleiro Bertrand Cordier Liming Dou Rob Eyles-Ferris Zhou Fan Hua Feng Shaoyu Fu Johan P.U.Fynbo Lluis Galbany Saurabh W.Jha Shuaiqing Jiang Albert Kong Erik Kuulkers Weihua Lei Wenxiong Li Bifang Liu Mingjun Liu Xing Liu Yuan Liu Zhu Liu Chandreyee Maitra Alessio Marino Itumeleng Monageng Kirpal Nandra Jeremy Sanders Roberto Soria Lian Tao Junfeng Wang Song Wang Tinggui Wang Zhongxiang Wang Qingwen Wu Xuefeng Wu Dong Xu Yanjun Xu Suijian Xue Yongquan Xue Zijian Zhang Zipei Zhu Hu Zou Congying Bao Fansheng Chen Houlei Chen Tianxiang Chen Wei Chen Yehai Chen Yifan Chen Chenzhou Cui Weiwei Cui Yanfeng Dai Dongwei Fan Ju Guan Dawei Han Dongjie Hou Haibo Hu Maohai Huang Jia Huo Zhenqing Jia Bowen Jiang Ge Jin Chengkui Li Junfei Li Longhui Li Maoshun Li Wei Li Zhengda Li Tianying Lian Congzhan Liu Heyang Liu Huaqiu Liu Fangjun Lu Laidan Luo Jia Ma Xuan Mao Haiwu Pan Xin Pan Liming Song Hui Sun Yunyin Tan Qingjun Tang Yihan Tao Hao Wang Juan Wang Lei Wang Wenxin Wang Yilong Wang Yusa Wang Qinyu Wu Haitao Xu Jingjing Xu Xinpeng Xu Yunfei Xu Zhao Xu Changbin Xue Yulong Xue Ailiang Yan Haonan Yang Xiongtao Yang Yanji Yang Juan Zhang Mo Zhang Wenjie Zhang Zhen Zhang Zhen Zhang Ziliang Zhang Donghua Zhao Haisheng Zhao Xiaofan Zhao Zijian Zhao Hongyan Zhou Yilin Zhou Yuxuan Zhu Zhencai Zhu National Astronomical Observatories Chinese Academy of sciences School of Astronomy and Space sciences University of Chinese Academy of sciences Key Laboratory of Particle Astrophysics Institute of High Energy Physics Chinese Academy of sciences Institute of Space sciences (ICE) CSIC Institut d’Estudis Espacials de Catalunya (IEEC) Max Planck Institute for Extraterrestrial Physics Innovation Academy for Microsatellites Chinese Academy of sciences department of Physics University of Hong Kong School of Physics and Astronomy University of Leicester School of Physics and Astronomy Sun Yat-sen University department of Physics Anhui Normal University Shanghai Institute of Technical Physics Chinese Academy of sciences Physics department Tsinghua University Nevada Center for Astrophysics University of Nevada Las Vegas department of Physics and Astronomy University of Nevada Las Vegas South African Astronomical Observatory department of Astronomy University of Cape Town department of Physics University of the Free State Université Paris Cité CNRS Astroparticule et Cosmologie Université Paris Cité CEA Paris-Saclay IRFU/DAp-AIM department of Astronomy Guangzhou University Cosmic Dawn Center (DAWN) Niels Bohr Institute University of Copenhagen department of Physics and Astronomy Rutgers the State University of New Jersey Institute for Cosmic Ray Research The University of Tokyo ESA/ESTEC department of Astronomy School of Physics Huazhong University of Science and technology INAF-Osservatorio Astrofisico di Torino Sydney Institute for Astronomy School of Physics The University of Sydney department of Astronomy Xiamen University Institute for Frontiers in Astronomy and Astrophysics Beijing Normal University department of Astronomy University of Science and technology School of Astronomy and Space sciences University of Science and technology of China Institute of Deep Space sciences Deep Space Exploration Laboratory department of Astronomy School of Physics and Astronomy Yunnan University Shanghai Astronomical Observatory Chi

We report the discovery of a peculiar X-ray transient,EP240408a,by Einstein Probe （EP） and follow-up studies made with EP,Swift,NICER,GROND,ATCA and other ground-based multiwavelength *** new transient was first detected with Wide-field X-ray Telescope （WXT） on board EP on April 8th,2024,manifested in an intense yet brief X-ray flare lasting for *** flare reached a peak flux of 3.9×10-9erg cm-2s-1in 0.5-4 ke V,～300 times brighter than the underlying X-ray emission detected throughout the *** and more precise follow-up observations by EP/FXT,Swift and NICER confirmed the finding of this new *** X-ray spectrum is non-thermal in 0.5-10 ke V,with a power-law photon index varying *** X-ray light curve shows a plateau lasting for ～4 d,followed by a steep decay till becoming undetectable ～10 d after the initial *** on its temporal property and constraints from previous EP observations,an unusual timescale in the range of 7-23 d is found for EP240408a,which is intermediate between the commonly found fast and long-term *** counterparts have been found in optical and near-infrared,with the earliest observation at 17 h after the initial X-ray detection,suggestive of intrinsically weak emission in these *** demonstrate that the remarkable properties of EP240408a are inconsistent with any of the transient types known so far,by comparison with,in particular,jetted tidal disruption events,gamma-ray bursts,X-ray binaries and fast blue optical *** nature of EP240408a thus remains an *** suggest that EP240408a may represent a new type of transients with intermediate timescales of the order of～10 *** detection and follow-ups of more of such objects are essential for revealing their origin.

关键词： X-ray transients ${\bm~{Einstein~~Probe}}$

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