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Towards implementation of alloy-specific thermo-fluid modelling for laser powder-bed fusion of Mg alloys

Journal of Magnesium and Alloys 2024年第6期12卷 2327-2344页

作者： mohammad hoseini-athar Mikael Ersson Peter Hedström Department of Material Science and Engineering KTH Royal Institute of TechnologyStockholmSE-10044 Sweden

Multi-physics thermo-fluid modeling has been extensively used as an approach to understand melt pool dynamics and defect formation as well as optimizing the process-related parameters of laser powder-bed fusion(L-PBF).However,its capabilities for being implemented as a reliable tool for material design,where minor changes in material-related parameters must be accurately captured,is still in *** the present research,first,a thermo-fluid computational fluid dynamics(CFD)model is developed and validated against experimental *** the predicted material properties of the pure Mg and commercial ZK60 and WE43 Mg alloys,parametric studies are done attempting to elucidate how the difference in some of the material properties,i.e.,saturated vapor pressure,viscosity,and solidification range,can influence the melt pool *** is found that a higher saturated vapor pressure,associated with the ZK60 alloy,leads to a deeper unstable keyhole,increasing the keyhole-induced porosity and evaporation mass *** viscosity and wider solidification range can increase the non-uniformity of temperature and velocity distribution on the keyhole walls,resulting in increased keyhole instability and formation of ***,the WE43 alloy showed the best behavior in terms of defect formation and evaporation mass loss,providing theoretical support to the extensive use of this alloy in *** summary,this study suggests an approach to investigate the effect of materials-related parameters on L-PBF melting and solidification,which can be extremely helpful for future design of new alloys suitable for L-PBF.

关键词： Mg alloys Laser powder-bed fusion(L-PBF) Melt pool dynamics Computational fluid dynamics Fluid flow

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Computational and bioinformatics tools for understanding disease mechanisms

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BIOCELL 2024年第6期48卷 935-944页

作者： MOHD athar ANU MANHAS NISARG RANA AHMAD IRFAN Physics Department University of CagliariCittadella UniversitariaMonserrato(CA)09042Italy Department of Chemistry School of Energy TechnologyPandit Deendayal Energy UniversityGandhinagar382426India Department of Chemistry College of ScienceKing Khalid UniversityAbha61413Saudi Arabia

Computational methods have signiﬁcantly transformed biomedical research,offering a comprehensive exploration of disease mechanisms and molecular protein *** article reviews a spectrum of computational tools and network analysis databases that play a crucial role in identifying potential interactions and signaling networks contributing to the onset of disease *** utilization of protein/gene interaction and genetic variation databases,coupled with pathway analysis can facilitate the identiﬁcation of potential drug *** bridging the gap between molecular-level information and disease understanding,this review contributes insights into the impactful utilization of computational methods,paving the way for targeted interventions and therapeutic advancements in biomedical research.

关键词： Interaction database Disease mechanisms Protein function Network analysis Bioinformatics Genetic variations Protein-protein interactions Signaling pathways

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Exploring the molecular landscape of NNK-induced transformation:A comprehensive genome-wide CRISPR/Cas9 screening

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Genes & Diseases 2024年第4期11卷 42-44页

作者： Trang Dinh Mira Rahm Zhenghe Wang Christopher McFarland athar Khalil Department of Genetics and Genome Sciences Case WesternReserve UniversityClevelandOH44106USA

Lung cancer is the leading cause of cancer-related deaths worldwide,with an estimated 1.8 million deaths in 2020 alone.1 While several risk factors are associated with lung cancer,smoking remains the most significant environmental cause of the disease.1 One of the most potent carcinogens in tobacco smoke is 4-(methylnitrosoamino)-1-(3-pyridyl)-1-butanone(NNK),which is produced from nicotine through a series of metabolic reactions.

关键词： CRISPR/Cas9 NNK lung

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Auto-tuning PVT data using multi-objective optimization: Application of NSGA-Ⅱ algorithm

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Petroleum 2024年第1期10卷 135-149页

作者： Abdolhadi Zarifi mohammad Madani mohammad Jafarzadegan Reservoir Engineering Systems Petroleum Engineering Department Main Office Building of National Iranian South Oil Company (NISOC) Combined Planning Management National Iranian Oil Company (NIOC) Reservoir Engineering Division Petroleum Engineering Department Petroleum Engineering and Development Company (PEDEC)

Reservoir simulation is known as perhaps the most widely used, accurate, and reliable method for field development in the petroleum industry. An integral part of a reliable reservoir simulation process is to consider robust and rigorous tuned EOS models. Traditionally, EOS models are tuned iteratively through arduous workflows against experimental PVT data. However, this comes with a number of drawbacks such as forcingly using weight factors, which upon alteration adversely affects the optimization *** objective of the current work is thus to introduce an auto-tune PVT matching tool using NSGA-II multi-objective optimization. In order to illustrate the robustness of the presented technique, three different PVT samples are used, including two black-oil and one gas condensate sample. We utilize PengRobinson EOS during all the manual and auto-tuning processes. Comparison of auto-tuned EOS-generated results with those of experimental and computed statistical error values for these samples clearly show that the proposed method is robust. In addition, the proposed method, contrary to the manual matching process, provides the engineer with several matched solutions, which allows them to select a match based on the engineering background to be best amenable to the problem at hand. In addition, the proposed technique is fast, and can output several solutions within less time compared to the traditional manual matching method.

关键词： Auto-tuning PVT Equation of state NSGA-II Multi-objective optimization

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Investigation of material composition,design,and performance of open-graded asphalt mixtures for semi-flexible pavement:A comprehensive experimental study

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Journal of Traffic and Transportation Engineering(English Edition) 2024年第1期11卷 92-116页

作者： mohammad Taghipoor Abolfazl Hassani mohammad M.Karimi Department of Civil and Environmental Engineering Tarbiat Modares UniversityTehranIran

The primary goal of this study is the design and construction of semi-flexible pavement(SFP)mixture in accordance with the engineering and mechanical *** study involves the use of a range of gradation curves,air void contents,cellulose and synthesized fibers,and neat and modified asphalt binders to prepare the open-graded asphalt(OGA)*** analyze the characteristics of these mixtures,a variety of test,namely binder drainage,semi-circular bending(SCB),Cantabro,wheel tracking,indirect tensile strength(ITS),and permeability tests were ***,to analyze the prepared grouting material,flexural strength,compressive strength,and fluidity tests were *** the final stage,SFP was compared to HMA in terms of engineering characteristics and *** to the results,SFP was more resistant to skid,rutting,fire,and moisture damage,while HMA had a better performance in fracture tests,including SCB *** to the results of the mechanical performance tests conducted on OGA mixtures,the highest and lowest values for air void content to achieve the highest mechanical performance level were 30%-35%and 25%,***,based on the laboratory results,it was determined that the required void ratio for constructing OGA mixtures was 24%-26%based on the bitumen type and fibers amount in the ***,SFP mixture can be regarded as a viable alternative to common pavements thanks to its high resistance to rutting and moisture damage,long freezing-thawing fatigue life,and adequate fire and skid resistance.

关键词： Semi-flexible pavement mixture Open-graded asphalt mixture Engineering properties Cantabro test Hot mix asphalt

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Survey of Indoor Localization Based on Deep Learning

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Computers, Materials & Continua 2024年第5期79卷 3261-3298页

作者： Khaldon Azzam Kordi Mardeni Roslee Mohamad Yusoff Alias Abdulraqeb Alhammadi athar Waseem Anwar Faizd Osman Centre for Wireless Technology Faculty of EngineeringMultimedia UniversityCyberjaya63100Malaysia Communication Systems&Networks Research Lab Malaysia-Japan International Institute of TechnologyUniversiti Teknologi MalaysiaKuala Lumpur54100Malaysia Department of Electrical Engineering(DEE) International Islamic UniversityIslamabad44000Pakistan Rohde&Schwarz(M)Sdn Bhd Shah Alam40150Malaysia

This study comprehensively examines the current state of deep learning (DL) usage in indoor *** emphasizes the significance and efficiency of convolutional neural networks (CNNs) and recurrent neuralnetworks (RNNs). Unlike prior studies focused on single sensor modalities like Wi-Fi or Bluetooth, this researchexplores the integration of multiple sensor modalities (e.g.,Wi-Fi, Bluetooth, Ultra-Wideband, ZigBee) to expandindoor localization methods, particularly in obstructed environments. It addresses the challenge of precise objectlocalization, introducing a novel hybrid DL approach using received signal information (RSI), Received SignalStrength (RSS), and Channel State Information (CSI) data to enhance accuracy and stability. Moreover, thestudy introduces a device-free indoor localization algorithm, offering a significant advancement with potentialobject or individual tracking applications. It recognizes the increasing importance of indoor positioning forlocation-based services. It anticipates future developments while acknowledging challenges such as multipathinterference, noise, data standardization, and scarcity of labeled data. This research contributes significantly toindoor localization technology, offering adaptability, device independence, and multifaceted DL-based solutionsfor real-world challenges and future advancements. Thus, the proposed work addresses challenges in objectlocalization precision and introduces a novel hybrid deep learning approach, contributing to advancing *** deep learning-based indoor localization techniques have improved accuracy, challenges likedata noise, standardization, and availability of training data persist. However, ongoing developments are expectedto enhance indoor positioning systems to meet real-world demands.

关键词： Deep learning indoor localization wireless-based localization

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Recent Progress in Bionic Hydrogels for Articular Cartilage:Tribological and Mechanical Characteristics

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Journal of Bionic Engineering 2024年第2期21卷 653-673页

作者： mohammad Javan Almasi Dangsheng Xiong School of Materials Science and Engineering Nanjing University of Science and TechnologyNanjing210094China

Cartilage regeneration and repair are considered clinical challenges since cartilage has limited capability for *** tissue-engineered materials have the ability to repair cartilage,they have weak mechanical characteristics and cannot resist long-term *** the other hand,surgery to replace the joint is frequently done to treat significant cartilage deterioration these ***,the materials that are being used for replacement have high friction coefficients,lack shock absorption functions,and lack *** research on natural articular cartilage structure and function may lead to bionic hydrogels,which have suitable physicochemical and biological characteristics(e.g.,tribological and mechanical properties and the ability to support loadbearing capability),but need *** on their tribological and mechanical characteristics,the current review highlights the most recent advancements of bionic hydrogels used for articular cartilage,highlighting both the field's recent progress and its potential for future *** this reason,firstly,some important property improvement methods of bionic hydrogels are discussed and then,the recent findings of various research on the making of those bionic materials are provided and *** seems that by using some modifications such as product design,surface treatments,animal tests,controlling the isoelectric point of hydrogels,and computer simulation,the intended mechanical and tribological characteristics of natural articular cartilage may be attained by the bionic hydrogels.

关键词： Bionic hydrogel Articular cartilage Mechanical property Tribological property Lubrication

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Ultrasensitive plasmonic sensor based on MDM waveguide containing Persian Orsi window cavities for refractive index and blood plasma sensing

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Optoelectronics Letters 2024年第7期20卷 406-411页

作者： mohammad Ghanavati mohammad Azim Karami School of Electrical Engineering Iran University of Science and TechnologyTehran 16846-13114Iran12

We developed a plasmonic refractive index(RI)with a metal-dielectric-metal(MDM)structure that utilizes two Persian Orsi windows-like separated cavities with a high figure of merit(FoM)and *** simulated and optimized Ag-air-Ag MDM sensor for surface plasmon resonance(SPR)offers high RI sensitivity(SRI)and the ability to detect blood plasma concentration(BPC).The results verified that structural parameters have an effect on SRI,full width at half maximum(FWHM),FoM,sensitivity of blood plasma(S_(p))for right and left peaks,whose values are 1345.45 nm·RIU^(−1),32 nm,42.04 RIU^(−1),0.26 and 0.19 nm·L·g^(-1),*** proposed design opens a new horizon in sensor development.

关键词： index utilize MDM

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Enhanced adaptive nonlinear extended state observer for pure feedback systems with matched and mismatched disturbances

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Control Theory and Technology 2024年第2期22卷 254-268页

作者： Mahtab Delpasand mohammad Farrokhi School of Electrical Engineering Iran University of Science and TechnologyTehran16846-13114Iran Center of Excellence for Modelling and Control of Complex Systems Iran University of Science and TechnologyTehran16846-13114Iran

In this paper, an enhanced adaptive nonlinear extended state observer (EANESO) for single-input single-output pure feedback systems in the presence of external time-varying disturbances is proposed. In this paper, a nonlinear system with matched and mismatched disturbances is considered. The conventional extended state observer (ESO) can only be applied to systems that are in the form of integral chains. Moreover, this method has limitations in the face of mismatched disturbances. In the presence of time-varying disturbances, the traditional ESOs cannot estimate the disturbances accurately. To overcome this limitation, an EANESO is proposed in this paper. The main idea is to design the nonlinear ESO (NESO) to estimate the states of the system and multiple disturbances simultaneously. The observer gains are considered time-varying and adjusted with adaptation laws to improve the estimation accuracy and overcome the peaking phenomenon. Next, the proposed controller is designed based on output feedback to eliminate the effects of multiple disturbances and stabilize the closed-loop system. Subsequently, the stability analysis of the closed-loop system and convergence of the observer error are discussed. Finally, the proposed method is applied to the inverted pendulum system. The simulated results show good performance of the proposed method as compared with a recently published scheme in the related literature.

关键词： Nonlinear extended state observer Enhanced adaptive extended state observer Adaptation law Multiple-channel disturbances Inverted pendulum system Time-varying gain

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Smart Energy Management System Using Machine Learning

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Computers, Materials & Continua 2024年第1期78卷 959-973页

作者： Ali Sheraz Akram Sagheer Abbas Muhammad Adnan Khan Atifa athar Taher M.Ghazal Hussam Al Hamadi School of Computer Science National College of Business Administration&EconomicsLahore54000Pakistan Riphah School of Computing&Innovation Faculty of ComputingRiphah International UniversityLahore CampusLahore54000Pakistan Pattern Recognition and Machine Learning Lab Department of SoftwareGachon UniversitySeongnamGyeonggido13120Korea Department of Computer Science COMSATS University IslamabadLahore CampusLahore54000Pakistan School of Information Technology Skyline University CollegeSharjah1797United Arab Emirates Network and Communication Technology Lab Center for Cyber SecurityFaculty of Information Science and TechnologyUniversiti Kebangsaan MalaysiaBangiSelangor43600Malaysia College of Engineering and IT University of DubaiDubaiUnited Arab Emirates

Energy management is an inspiring domain in developing of renewable energy ***,the growth of decentralized energy production is revealing an increased complexity for power grid managers,inferring more quality and reliability to regulate electricity flows and less imbalance between electricity production and *** major objective of an energy management system is to achieve optimum energy procurement and utilization throughout the organization,minimize energy costs without affecting production,and minimize environmental *** energy management is an essential and complex subject because of the excessive consumption in residential buildings,which necessitates energy optimization and increased user *** address the issue of energy management,many researchers have developed various frameworks;while the objective of each framework was to sustain a balance between user comfort and energy consumption,this problem hasn’t been fully solved because of how difficult it is to solve *** inclusive and Intelligent Energy Management System(IEMS)aims to provide overall energy efficiency regarding increased power generation,increase flexibility,increase renewable generation systems,improve energy consumption,reduce carbon dioxide emissions,improve stability,and reduce energy *** Learning(ML)is an emerging approach that may be beneficial to predict energy efficiency in a better way with the assistance of the Internet of Energy(IoE)*** IoE network is playing a vital role in the energy sector for collecting effective data and usage,resulting in smart resource *** this research work,an IEMS is proposed for Smart Cities(SC)using the ML technique to better resolve the energy management *** proposed system minimized the energy consumption with its intelligent nature and provided better outcomes than the previous approaches in terms of 92.11% accuracy,and 7.89% miss-rate.

关键词： Intelligent energy management system smart cities machine learning

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