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Understanding the corrosion and bio-corrosion behaviour of Magnesium composites – a critical review

Journal of Magnesium and Alloys 2024年第3期12卷 890-939页

作者： Prithivirajan sekar s.K.Panigrahi Department of Mechanical Engineering Indian Institute of Technology MadrasChennai600036India Applied Magnesium Research Center Center of Excellence in Materials and Manufacturing for Futuristic MobilityIndian Institute of Technology MadrasChennai600036India

Realising the potential of Magnesium(Mg),several globally leading ventures have invested in the Mg industry,but their relatively poor corrosion resistance is a never ending saga till date.The corrosion and bio-corrosion behaviour of Mg has gained research attention and still remains a hot topic in the application of automobile,aerospace and biomedical industries.The intrinsic high electrochemical nature of Mg limits their utilization in diverse application.This scenario has prompted the development of Mg composites with an aim to achieve superior corrosion and bio-corrosion resistance.The present review enlightens the influence of grain size(Gs),secondary phase,texture,type of matrix and reinforcement on the corrosion and bio-corrosion behaviour of Mg composites.Firstly,the corrosion and bio-corrosion behaviour of Mg composites manufactured by primary and secondary processing routes are elucidated.secondly,the comprehensive corrosion and bio-corrosion mechanisms of these Mg composites are proposed.Thirdly,the individual role of Gs,texture and corrosive medium on corrosion and bio-corrosion behaviour of Mg composites are clarified and revealed.The challenges encountered,unanswered issues in this field are explained in detail and accordingly the scope for future research is framed.The review is presented from basic concrete background to advanced corrosion mechanisms with an aim of creating interest among the readers like students,researchers and industry experts from various research backgrounds.Indeed,the corrosion and bio-corrosion behaviour of Mg composites are critically reviewed for the first time to:(i)contribute to the body of knowledge,(ii)foster research and development,(iii)make breakthrough,and(iv)create life changing innovations in the field of Mg composite corrosion.

关键词： Corrosion Bio corrosion Magnesium alloys Magnesium composites Magnesium implants.

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Real-Time Prediction of Urban Traffic Problems Based on Artificial Intelligence-Enhanced Mobile Ad Hoc Networks(MANETs)

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Computers, Materials & Continua 2024年第5期79卷 1903-1923页

作者： Ahmed Alhussen Arshiya s.Ansari Department of Computer Engineering College of Computer and Information SciencesMajmaah UniversityAl-Majmaah11952Saudi Arabia Department of Information Technology College of Computer and Information SciencesMajmaah UniversityAl-Majmaah11952Saudi Arabia

Traffic in today’s cities is a serious problem that increases travel times,negatively affects the environment,and drains financial resources.This study presents an Artificial Intelligence(AI)augmentedMobile Ad Hoc Networks(MANETs)based real-time prediction paradigm for urban traffic challenges.MANETs are wireless networks that are based on mobile devices and may self-organize.The distributed nature of MANETs and the power of AI approaches are leveraged in this framework to provide reliable and timely traffic congestion forecasts.This study suggests a unique Chaotic spatial Fuzzy Polynomial Neural Network(CsFPNN)technique to assess real-time data acquired from various sources within theMANETs.The framework uses the proposed approach to learn from the data and create predictionmodels to detect possible traffic problems and their severity in real time.Real-time traffic prediction allows for proactive actions like resource allocation,dynamic route advice,and traffic signal optimization to reduce congestion.The framework supports effective decision-making,decreases travel time,lowers fuel use,and enhances overall urban mobility by giving timely information to pedestrians,drivers,and urban planners.Extensive simulations and real-world datasets are used to test the proposed framework’s prediction accuracy,responsiveness,and scalability.Experimental results show that the suggested framework successfully anticipates urban traffic issues in real-time,enables proactive traffic management,and aids in creating smarter,more sustainable cities.

关键词： Mobile AdHocNetworks(MANET) urban traffic prediction artificial intelligence(AI) traffic congestion chaotic spatial fuzzy polynomial neural network(CsFPNN)

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MAIPFE:An Efficient Multimodal Approach Integrating Pre-Emptive Analysis,Personalized Feature selection,and Explainable AI

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Computers, Materials & Continua 2024年第5期79卷 2229-2251页

作者： Moshe Dayan sirapangi s.Gopikrishnan school of Computer science and Engineering VIT-AP UniversityAmaravathiAndhra Pradesh522241India

Medical Internet of Things(IoT)devices are becoming more and more common in healthcare.This has created a huge need for advanced predictive health modeling strategies that can make good use of the growing amount of multimodal data to find potential health risks early and help individuals in a personalized way.Existing methods,while useful,have limitations in predictive accuracy,delay,personalization,and user interpretability,requiring a more comprehensive and efficient approach to harness modern medical IoT devices.MAIPFE is a multimodal approach integrating pre-emptive analysis,personalized feature selection,and explainable AI for real-time health monitoring and disease detection.By using AI for early disease detection,personalized health recommendations,and transparency,healthcare will be transformed.The Multimodal Approach Integrating Pre-emptive Analysis,Personalized Feature selection,and Explainable AI(MAIPFE)framework,which combines Firefly Optimizer,Recurrent Neural Network(RNN),Fuzzy C Means(FCM),and Explainable AI,improves disease detection precision over existing methods.Comprehensive metrics show the model’s superiority in real-time health analysis.The proposed framework outperformed existing models by 8.3%in disease detection classification precision,8.5%in accuracy,5.5%in recall,2.9%in specificity,4.5%in AUC(Area Under the Curve),and 4.9%in delay reduction.Disease prediction precision increased by 4.5%,accuracy by 3.9%,recall by 2.5%,specificity by 3.5%,AUC by 1.9%,and delay levels decreased by 9.4%.MAIPFE can revolutionize healthcare with preemptive analysis,personalized health insights,and actionable recommendations.The research shows that this innovative approach improves patient outcomes and healthcare efficiency in the real world.

关键词： Predictive health modeling Medical Internet of Things explainable artificial intelligence personalized feature selection preemptive analysis

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Provenance and depositional setting of the Late MiocenePleistocene clastic sediments in the eastern Arabian Peninsula and western Iraq using rare earth elements geochemistry

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Acta Geochimica 2024年第2期43卷 399-410页

作者： salih M.Awadh Zinah s.Al-Ankaz Mohanad R.A.Al-Owaidi John s.Armstrong-Altrin Department of Geology College of ScienceUniversity of BaghdadBaghdadIraq Department of Geology College of ScienceUniversity of WasitWasit 52011Iraq Department of Applied Geology College of ScienceUniversity of BabylonBabylon 51001Iraq Unidad de Procesos Oceanicos y Costeros Instituto de Ciencias del Mar y LimnologíaUniversidad Nacional Autonoma de MexicoCiudad Universitaria04510 Mexico CityCDMXMexico Department of Marine sciences Bharathidasan UniversityTiruchirapalliTamil Nadu 620024India

The sandstones of the Late miocene–Pliocene Dibdibba Formation in the Najaf–Karbala Plateau and Basra were examined to determine their source rocks and origin. The rare earth elements(REE) and trace elements(sc, Co, V, and Th) concentrations in these sandstones revealed that they likely derived from a single source. The steep light rare earth elements(LREE) and flat, heavy rare earth element(HREE) patterns, negative Eu anomaly, and high ΣREE contents in sandstones suggest its derivation from a suggests that a passive continental margin environment and originated from felsic source rocks. The average concentration of ΣREE is 93.5 ppm, which is lower than that of the average crustal compositions like Upper Continental Crust and Post Archean Australian shale. The higher proportion of LREE compared to HREE implies that these sandstones were recycled and derived from a distal source. The Th/Co, Th/sc, La/sc, La/Co, Eu/Eu*and(La/Lu)cn elemental ratios indicated that these Late Miocene–Pliocene sandstones were derived from felsic rocks located in the marginal region of the Arabian shield.

关键词： REE Dibdibba formation Clastic sediments Passive continental margin

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Optimizing oncolytic virus design:a“swiss army knife”approach to create a systemically delivered therapeutic

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signal Transduction and Targeted Therapy 2024年第5期9卷 1791-1792页

作者： Carolina s.Ilkow John Cameron Bell Ottawa Hospital Research Institute 501 Smyth RoadOttawaONK1H 8L6Canada

In a recent paper published in Nature Biotechnology,Chen et al.1 describe a multiplex oncolytic virus platform that coupled with adoptive T cell therapy could solve the problem of repeat,systemic delivery of virus based therapeutics.It is widely accepted that multi-targeted therapeutic approaches attacking several facets of cancer biology are necessary to effectively deal with the tumor heterogeneity that exists within and between patients.

关键词： therapeutic al. targeted

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Early Phases of star Formation: Testing Chemical Tools

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Research in Astronomy and Astrophysics 2024年第1期24卷 96-118页

作者： N.C.Martinez s.Paron CONICET-Universidad de Buenos Aires.Instituto de Astronomía y Física del Espacio Ciudad Universitaria(C1428EGA)Ciudad Autónoma de Buenos AiresArgentina

star-forming processes strongly influence the IsM chemistry.Nowadays,many high-quality databases are available at millimeter wavelengths.Using them,it is possible to carry out studies that review and deepen previous results.If these studies involve large samples of sources,it is preferred to use direct tools to study the molecular gas.With the aim of testing these tools such as the use of the HCN/HNC ratio as a thermometer,and the use of H^(13)CO^(+),HC_(3)N,N_(2)H^(+) and C_(2)H as "chemical clocks," we present a molecular line study toward 55 sources representing massive young stellar objects at different evolutionary stages:infrared dark clouds(IRDCs),highmass protostellar objects(HMPOs),hot molecular cores(HMCs) and ultracompact H II regions.We found that the use of the HCN/HNC ratio as a universal thermometer in the IsM should be taken with care because the HCN optical depth is a big issue that can affect the method.Hence,this tool should be utilized only after a careful analysis of the HCN spectrum,checking that no line,neither the main nor the hyperfine ones,presents absorption features.We point out that the analysis of the emission of H^(13)CO^(+),HC_(3)N,N_(2)H^(+) and C_(2)H could be useful to trace and distinguish regions among IRDCs,HMPOs and HMCs.The molecular line widths of these four species increase from the IRDC to the HMC stage,which can be a consequence of the gas dynamics related to the starforming processes taking place in the molecular clumps.Our results not only contribute with more statistics,acting as a probe of such chemical tools,useful to obtain information in large samples of sources,but also complement previous works through the analysis of other types of sources.

关键词： stars:formation IsM:molecules IsM:clouds

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An Efficient Modelling of Oversampling with Optimal Deep Learning Enabled Anomaly Detection in streaming Data

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China Communications 2024年第5期21卷 249-260页

作者： R.Rajakumar s.sathiya Devi srinivasa Ramanujan Centre SASTRA Deemed UniversityKumbakonamTamil Nadu 612001India University College of Engineering BIT CampusAnna UniversityTiruchirappalli 620024India

Recently,anomaly detection(AD)in streaming data gained significant attention among research communities due to its applicability in finance,business,healthcare,education,etc.The recent developments of deep learning(DL)models find helpful in the detection and classification of anomalies.This article designs an oversampling with an optimal deep learning-based streaming data classification(Os-ODLsDC)model.The aim of the OsODLsDC model is to recognize and classify the presence of anomalies in the streaming data.The proposed Os-ODLsDC model initially undergoes preprocessing step.since streaming data is unbalanced,support vector machine(sVM)-synthetic Minority Over-sampling Technique(sVM-sMOTE)is applied for oversampling process.Besides,the Os-ODLsDC model employs bidirectional long short-term memory(Bi LsTM)for AD and classification.Finally,the root means square propagation(RMsProp)optimizer is applied for optimal hyperparameter tuning of the Bi LsTM model.For ensuring the promising performance of the Os-ODLsDC model,a wide-ranging experimental analysis is performed using three benchmark datasets such as CICIDs 2018,KDD-Cup 1999,and NsL-KDD datasets.

关键词： anomaly detection deep learning hyperparameter optimization oversampling sMOTE streaming data

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Parametric investigation on the novel and cost-effective nano fly ash impregnated geopolymer system for sustainable construction

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Frontiers of structural and Civil Engineering 2024年第2期18卷 170-183页

作者： R.MOHANA s.M.Leela BHARATHI Department of Civil Engineering Mepco Schlenk Engineering CollegeSivakasi 626123India

The hazardous environmental effects of greenhouse gas emissions and climate change demand alternative sources for cementitious materials in the construction industry.The development of geopolymer structures provides a way of producing 100%cement-free construction.In this research work,a novel and simple way of deriving nano particles from waste fly ash particles is promoted.The effect of adding the synthesized nano fly ash particles as a filler medium in geopolymer mortars was investigated by considering strength and durability properties.Parameter optimization was done by using regression analysis on the geopolymer mortar and the impact of adding nano fly ash particles was studied by varying different percentages of addition ranging from 0 to 7.5%by weight of binder content.From the results,it was observed that 1%nano fly ash acted not only as a filler but also as nano-sized precursors of the polymerization process,resulting in denser geopolymer medium.This can explain the extraordinary gain in strength of 72.11 MPa as well as the denser core with negligible level of chloride ion penetration,making the material suitable for the development of structures susceptible to marine environment.

关键词： geopolymer nano fly ash chloride ion penetration durability polymerization fillers

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Improved state-space Modelling for Microgrids Without Virtual Resistances

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Journal of Modern Power systems and Clean Energy 2024年第2期12卷 584-596页

作者： Paranagamage s.A.Peiris shaahin Filizadeh Dharshana Muthumuni Department of Electrical and Computer Engineering University of ManitobaWinnipegMBR3T 5V6Canada Manitoba HVDC Research Center 211 Commerce DriveWinnipegMBR3P 1A3Canada IEEE

Power converters and their interfacing networks are often treated as modular state-space blocks for small-signal stability studies in microgrids;they are interconnected by matching the input and output states of the network and converters.Virtual resistors have been widely used in existing models to generate a voltage for state-space models of the network that require voltage inputs.This paper accurately quantifies the adverse impacts of adding the virtual resistance and proposes an alternative method for network modelling that eliminates the requirement of the virtual resistor when interfacing converters with microgrids.The proposed nonlinear method allows initialization,time-domain simulations of the nonlinear model,and linearization and eigenvalue generation.A numerically linearized small-signal model is used to generate eigenvalues and is compared with the eigenvalues generated using the existing modelling method with virtual resistances.Deficiencies of the existing method and improvements offered by the proposed modelling method are clearly quantified.Electromagnetic transient(EMT)simulations using detailed switching models are used for validation of the proposed modelling method.

关键词： Low-voltage converter state-space modelling dynamic phasor time-domain simulation eigenvalue analysis

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Current perspective on amyloid aggregation accelerating properties of the artificial butter flavoring,diacetyl

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Neural Regeneration Research 2024年第10期19卷 2113-2114页

作者： Ashish P.Vartak swati s.More Center for Drug Design College of PharmacyUniversity of MinnesotaMinneapolisMNUSA

The amyloid—what peptide can resist its entropic bliss?Without kinetic barricades and chaperones,most peptides would simply tumble down that precipice.The amyloid-β(Aβ) peptides are understood to underlie the hallmark pathology of Alzheimer's disease(AD) and are considered one of the causative factors for neurodegeneration and cognitive impairment.AD affects critical connected structures within the brain that are responsible for memory,language,and social behavior.

关键词： amyloid Alzheimer Aβ

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