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

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

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Modeling and Comprehensive Review of Signaling Storms in 3GPP-Based Mobile Broadband Networks:Causes,Solutions,and Countermeasures

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Computer Modeling in engineering & sciences 2025年第1期142卷 123-153页

作者： Muhammad Qasim Khan Fazal Malik Fahad Alturise Noor Rahman department of Computer science Iqra National UniversityPeshawar25000Pakistan department of Cybersecurity College of ComputerQassim UniversityBuraydah52555Saudi Arabia department of Computer science and engineering Al-Fayha CollegeAl Jubayl31961Saudi Arabia

Control signaling is mandatory for the operation and management of all types of communication networks,including the Third Generation Partnership Project(3GPP)mobile broadband ***,they consume important and scarce network resources such as bandwidth and processing *** have been several reports of these control signaling turning into signaling storms halting network operations and causing the respective Telecom companies big financial *** paper draws its motivation from such real network disaster incidents attributed to signaling *** this paper,we present a thorough survey of the causes,of the signaling storm problems in 3GPP-based mobile broadband networks and discuss in detail their possible solutions and *** provide relevant analytical models to help quantify the effect of the potential causes and benefits of their corresponding *** important contribution of this paper is the comparison of the possible causes and solutions/countermeasures,concerning their effect on several important network aspects such as architecture,additional signaling,fidelity,etc.,in the form of a *** paper presents an update and an extension of our earlier conference *** our knowledge,no similar survey study exists on the subject.

关键词： Signaling storm problems control signaling load analytical modeling 3GPP networks smart devices diameter signaling mobile broadband data access data traffic mobility management signaling network architecture 5G mobile communication

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Aligned Ion Conduction Pathway of Polyrotaxane‑Based Electrolyte with Dispersed Hydrophobic Chains for Solid‑State Lithium–Oxygen Batteries

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Nano-Micro Letters 2025年第2期17卷 169-186页

作者： Bitgaram Kim Myeong‑Chang Sung Gwang‑Hee Lee Byoungjoon Hwang Sojung Seo Ji‑Hun Seo Dong‑Wan Kim department of Materials science and engineering Korea University145 Anam‑RoSeongbuk‑GuSeoul 02841Republic of Korea School of Civil Environmental and Architectural EngineeringKorea University145 Anam‑RoSeongbuk‑GuSeoul 02841Republic of Korea Materials science and Chemical engineering Center Institute for Advanced Engineering(IAE)Yongin 17180Republic of Korea

A critical challenge hindering the practical application of lithium–oxygen batteries(LOBs)is the inevitable problems associated with liquid electrolytes,such as evaporation and safety *** study addresses these problems by proposing a modified polyrotaxane(mPR)-based solid polymer electrolyte(SPE)design that simultaneously mitigates solvent-related problems and improves ***-SPE exhibits high ion conductivity(2.8×10^(−3)S cm^(−1)at 25℃)through aligned ion conduction pathways and provides electrode protection ability through hydrophobic chain *** this mPR-SPE into solid-state LOBs resulted in stable potentials over 300 *** situ Raman spectroscopy reveals the presence of an LiO_(2)intermediate alongside Li_(2)O_(2)during oxygen *** situ X-ray diffraction confirm the ability of the SPE to hinder the permeation of oxygen and moisture,as demonstrated by the air permeability *** present study suggests that maintaining a low residual solvent while achieving high ionic conductivity is crucial for restricting the sub-reactions of solid-state LOBs.

关键词： Solid polymer electrolyte Lithium-oxygen batteries Polyrotaxane ion conductivity Hydrophobic chain

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Locally Enhanced Flow and Electric Fields Through a Tip Effect for Efficient Flow‑Electrode Capacitive Deionization

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Nano-Micro Letters 2025年第2期17卷 1-17页

作者： Ziquan Wang Xiangfeng Chen Yuan Zhang Jie Ma Zhiqun Lin Amor Abdelkader Maria‑Magdalena Titirici Libo Deng College of Chemistry and environmental engineering Shenzhen UniversityShenzhen 518060People’s Republic of China Research Center for environmental Functional Materials College of Environmental Science and EngineeringTongji University1239 Siping RoadShanghai 200092People’s Republic of China department of Chemical and Biomolecular engineering National University of SingaporeSingapore 117585Singapore department of engineering Faculty of Science and TechnologyBournemouth UniversityTalbot CampusFern BarrowPooleEngland BH125BBUK Institut de Chimie de Nice UniversitéCôte d’AzurUMR CNRS 727228 Av.Valrose06108 NiceFrance department of Chemical engineering Imperial College LondonSouth Kensington CampusExhibition RdLondon SW72AZUK

Low-electrode capacitive deionization(FCDI)is an emerging desalination technology with great potential for removal and/or recycling ions from a range of ***,it still suffers from inefficient charge transfer and ion transport kinetics due to weak turbulence and low electric intensity in flow electrodes,both restricted by the current ***,a new tip-array current collector(designated as T-CC)was developed to replace the conventional planar current collectors,which intensifies both the charge transfer and ion transport *** effects of tip arrays on flow and electric fields were studied by both computational simulations and electrochemical impedance spectroscopy,which revealed the reduction of ion transport barrier,charge transport barrier and internal *** the voltage increased from 1.0 to 1.5 and 2.0 V,the T-CC-based FCDI system(T-FCDI)exhibited average salt removal rates(ASRR)of 0.18,0.50,and 0.89μmol cm^(-2) min^(-1),respectively,which are 1.82,2.65,and 2.48 folds higher than that of the conventional serpentine current collectors,and 1.48,1.67,and 1.49 folds higher than that of the planar current ***,with the solid content in flow electrodes increased from 1 to 5 wt%,the ASRR for T-FCDI increased from 0.29 to 0.50μmol cm^(-2) min^(-1),which are 1.70 and 1.67 folds higher than that of the planar current ***,a salt removal efficiency of 99.89%was achieved with T-FCDI and the charge efficiency remained above 95%after 24 h of operation,thus showing its superior long-term stability.

关键词： Flow-electrode Capacitive deionization Current collector Tip effect Desalination

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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

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Impact of Pollutant Concentration and Particle Deposition on the Radiative Flow of Casson-Micropolar Fluid between Parallel Plates

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Computer Modeling in engineering & sciences 2025年第1期142卷 665-690页

作者： Ghaliah Alhamzi Badr Saad T.Alkahtani Ravi Shanker Dubey Vinutha Kalleshachar Neelima Nizampatnam department of Mathematics and Statistics College of ScienceImam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11564Saudi Arabia department of Mathematics College of ScienceKing Saud UniversityRiyadh11989Saudi Arabia department of Mathematics Amity School of Applied SciencesAmity University RajasthanJaipur302002RajasthanIndia department of Studies in Mathematics Davangere UniversityDavangere577002India department of Electronics and Communication engineering Amrita School of EngineeringAmrita Vishwa VidyapeethamBengaluru560035India

Assessing the behaviour and concentration of waste pollutants deposited between two parallel plates is essential for effective environmental *** the effectiveness of treatment methods in reducing pollution scales is made easier by analysing waste discharge *** waste discharge concentration analysis is useful for assessing how effectively wastewater treatment techniques reduce pollution *** study aims to explore the Casson micropolar fluid flow through two parallel plates with the influence of pollutant concentration and thermophoretic particle *** explore the mass and heat transport features,thermophoretic particle deposition and thermal radiation are *** governing equations are transformed into ordinary differential equations with the help of suitable similarity *** Runge-Kutta-Fehlberg’s fourthfifth order technique and shooting procedure are used to solve the reduced set of equations and boundary *** integration of a neural network model based on the Levenberg-Marquardt algorithm serves to improve the accuracy of predictions and optimize the analysis of *** outcomes are displayed to analyze the characteristics of the relevant dimensionless parameters in the current *** reveal that concentration upsurges as the micropolar parameter *** concentration reduces with an upsurge in the thermophoretic *** upsurge in the external pollutant source variation and the local pollutant external source parameters enhances mass *** surface drag force declines for improved values of porosity and micropolar parameters.

关键词： Micropolar fluid thermal radiation porous medium thermophoretic particle deposition waste discharge concentration

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Effects of the extrusion parameters on microstructure,texture and room temperature mechanical properties of extruded Mg-2.49Nd-1.82Gd-0.2Zn-0.2Zr alloy

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International Journal of Minerals,Metallurgy and Materials 2025年第1期32卷 136-146页

作者： Chenjin Zhang Guangyu Yang Lei Xiao Zhiyong Kan Jing Guo Qiang Li Wanqi Jie State Key Laboratory of Solidification Processing Northwestern Polytechnical UniversityXi’an 710072China College of Materials science and engineering Fuzhou UniversityFuzhou 350108China College of Chemistry and environmental science Qujing Normal UniversityQujing 655011China

Microstructure,texture,and mechanical properties of the extruded Mg-2.49Nd-1.82Gd-0.2Zn-0.2Zr alloy were investigated at different extrusion temperatures(260 and 320℃),extrusion ratios(10:1,15:1,and 30:1),and extrusion speeds(3 and 6 mm/s).The experimental results exhibited that the grain sizes after extrusion were much finer than that of the homogenized alloy,and the second phase showed streamline distribution along the extrusion direction(ED).With extrusion temperature increased from 260 to 320℃,the microstructure,texture,and mechanical properties of alloys changed *** dynamic recrystallization(DRX)degree and grain sizes enhanced as the extrusion ratio increased from 10:1 to 30:1,and the strength gradually decreased but elongation(EL)*** the extrusion speed increased from 3 to 6 mm/s,the grain sizes and DRX degree increased significantly,and the samples presented the typical-rare-earth(RE)*** alloy extruded at 260℃ with extrusion ratio of 10:1 and extrusion speed of 3 mm/s showed the tensile yield strength(TYS)of 213 MPa and EL of 30.6%.After quantitatively analyzing the contribution of strengthening mechanisms,it was found that the grain boundary strengthening and dislocation strengthening played major roles among strengthening *** results provide some guidelines for enlarging the industrial application of extruded Mg-RE alloy.

关键词： Mg-rare earth alloys extrusion temperature extrusion ratio extrusion speed strengthening mechanisms

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Role of copper chelating agents: between old applications and new perspectives in neuroscience

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Neural Regeneration Research 2025年第3期20卷 751-762页

作者： Rosalba Leuci Leonardo Brunetti Vincenzo Tufarelli Marco Cerini Marco Paparella Nikola Puvača Luca Piemontese department of Pharmacy-Pharmaceutical science University of Bari Aldo MoroBariItaly department of Precision and Regenerative Medicine and Jonian Area(DiMePRe-J) Section of Veterinary Science and Animal ProductionUniversity of Bari Aldo MoroBariItaly department of engineering Management in Biotechnology Faculty of Economics and Engineering Management in Novi SadUniversity Business Academy in Novi SadNovi SadSerbia

The role of copper element has been an increasingly relevant topic in recent years in the fields of human and animal health, for both the study of new drugs and innovative food and feed supplements. This metal plays an important role in the central nervous system, where it is associated with glutamatergic signaling, and it is widely involved in inflammatory processes. Thus, diseases involving copper(Ⅱ) dyshomeostasis often have neurological symptoms, as exemplified by Alzheimer's and other diseases(such as Parkinson's and Wilson's diseases). Moreover, imbalanced copper ion concentrations have also been associated with diabetes and certain types of cancer, including glioma. In this paper, we propose a comprehensive overview of recent results that show the importance of these metal ions in several pathologies, mainly Alzheimer's disease, through the lens of the development and use of copper chelators as research compounds and potential therapeutics if included in multi-target hybrid drugs. Seeing how copper homeostasis is important for the well-being of animals as well as humans, we shortly describe the state of the art regarding the effects of copper and its chelators in agriculture, livestock rearing, and aquaculture, as ingredients for the formulation of feed supplements as well as to prevent the effects of pollution on animal productions.

关键词： agriculture Alzheimer's disease chelators copper feed supplements multi-target

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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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Co/Co7Fe3 heterostructures with controllable alloying degree on carbon spheres as bifunctional electrocatalyst forrechargeable zinc–air batteries

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International Journal of Minerals,Metallurgy and Materials 2025年第02期 476-487页

作者： Junkang Chen Yongyue Zhuang Yanxin Qiao Yu Zhang Aihua Yuan Hu Zhou School of Materials science and engineering Jiangsu University of Science and Technology School of environmental and Chemical engineering Jiangsu University of Science and Technology

Exploring efficient and nonprecious metal electrocatalysts of oxygen reduction reaction（ORR） and oxygen evolution reaction（OER） is crucial for developing rechargeable zinc–air batteries（ZABs）. Herein, an alloying-degree control strategy was employed to fabricate nitrogen-doped carbon sphere（NCS） decorated with dual-phase Co/Co7Fe3heterojunctions（CoFe@NCS）. The phase composition of materials has been adjusted by controlling the alloying degree. The optimal CoFe0.08@NCS electrocatalyst displays a half-wave potential of 0.80 V for ORR and an overpotential of 283 mV at 10 mA·cm-2for OER in an alkaline electrolyte. The intriguing bifunctional electrocatalytic activity and durability is attributed to the hierarchically porous structure and interfacial electron coupling of highly-active Co7Fe3alloy and metallic Co species. When the CoFe0.08@NCS material is used as air–cathode catalyst of rechargeable liquid-state zinc–air battery（ZAB）, the device shows a high peak power-density(157 mW·cm-2) and maintains a stable voltage gap over 150 h, outperforming those of the benchmark（Pt/C+RuO2）-based device. In particular, the as-fabricated solid-state flexible ZAB delivers a reliable compatibility under different bending conditions. Our work provides a promising strategy to develop metal/alloy-based electrocatalysts for the application in renewable energy conversion technologies.

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