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Comparative study between three carbonaceous nanoblades and nanodarts for antimicrobial applications

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Journal of Environmental Sciences 2024年第2期136卷 594-605页

作者： mohamed S.Selim Ahmed M.Azzam mohamed A.Shenashen Shimaa A.Higazy Bayaumy B.Mostafa Sherif A.El-Safty National Institute for Materials Science(NIMS) 1-2-1 SengenTsukuba-ShiIbaraki-Ken 305-0047Japan Petroleum Application Department Egyptian Petroleum Research InstituteNasr City 11727Egypt Department of Environmental Research Theodor Bilharz Research InstituteGizaEgypt

The design of nanostructured materials occupies a privileged position in the development and management of affordable and effective technology in the antibacterial ***,we discuss the antimicrobial properties of three carbonaceous nanoblades and nanodarts materials of graphene oxide(GO),reduced graphene oxide(RGO),and single-wall carbon nanotubes(SWCNTs)that have a mechano-bactericidal effect,and the ability to piercing or slicing bacterial *** demonstrate the significance of size,morphology and composition on the antibacterial activity mechanism,the designed nanomaterials have been *** minimum inhibitory concentration(MIC),standard agar well diffusion,and transmission electron microscopy were utilized to evaluate the antibacterial activity of GO,RGO,and *** on the evidence obtained,the three carbonaceous materials exhibit activity against all microbial strains tested by completely encapsulating bacterial cells and causing morphological disruption by degrading the microbial cell membrane in the order of RGO>GO>*** of the external cell wall structure and outer membrane proteins,the synthesized carbonaceous nanomaterials exhibited higher antibacterial activity against Gram-positive bacterial strains than Gram-negative and fungal *** had the lowest MIC values(0.062,0.125,and 0.25 mg/mL against ***,***,and ***,respectively),as well as minimum fungal concentrations(0.5 mg/mL for both *** and ***).At 12 hr,the cell viability values against tested microbial strains were completely *** lysis and death occurred as a result of severe membrane damage caused by microorganisms perched on RGO *** work gives an insight into the design of effective graphene-based antimicrobial materials for water treatment and remediation.

关键词： Antimicrobial properties Nanoblades Mechano-bactericidal effect RGO nanosheets Gram-positive bacteria Cell viability

A new technique for fault diagnosis in transformer insulating oil based on infrared spectroscopy measurements

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High Voltage 2024年第2期9卷 319-335页

作者： mohamed M.F.Darwish mohamed H.A.Hassan Nagat M.K.Abdel-Gawad Matti Lehtonen Diaa-Eldin A.Mansour Department of Electrical Engineering Faculty of Engineering at ShoubraBenha UniversityCairoEgypt Department of Electrical Engineering and Automation School of Electrical EngineeringAalto UniversityEspooFinland Department of Electrical Power Engineering Egypt-Japan University of Science and Technology(E-JUST)New Borg El-Arab CityEgypt Department of Electrical Power and Machines Engineering Faculty of EngineeringTanta UniversityTantaEgypt

Condition monitoring of the insulating system within power transformers has a massive importance according to the electrical *** gas analysis(DGA)is frequently used for this ***,DGA lacks the necessary level of accuracy to identify all equipment faults,particularly in their initial stages of ***,it does not have the capability for real-time monitoring and relies on manual sampling and laboratory testing,causing potential delays in fault ***,the interpretation of DGA data necessitates specialised expertise,which may pose difficulties for smaller entities that have limited access to ***,the contribution of this research is to use infrared spectroscopy measurements as a new effective technique substituting the DGA method for fault diagnosis in insulating *** inception faults that were considered in this study were the electrical fault(discharges of high energy)and the thermal fault(300°C

关键词： fault diagnosis spectroscopy

An inverse method for characterization of dynamic response of 2D structures under stochastic conditions

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Chinese Journal of Aeronautics 2024年第3期37卷 440-455页

作者： Xuefeng LI Abdelmalek ZINE mohamed ICHCHOU Noureddine BOUHADDI Pascal FOSSAT Laboratory of Tribology and Systems Dynamic Central School of LyonEcully 69134France Institut Camille Jordan Central School of LyonEcully 69134France Department of Applied Mechanics University of Burgundy Franche-ComtéBesancon 25000France

The reliable estimation of the wavenumber space(k-space)of the plates remains a longterm concern for acoustic modeling and structural dynamic behavior *** current analyses of wavenumber identification methods are based on the deterministic *** this end,an inverse method is proposed for identifying wave propagation characteristics of twodimensional structures under stochastic conditions,such as wavenumber space,dispersion curves,and band *** proposed method is developed based on an algebraic identification scheme in the polar coordinate system framework,thus named Algebraic K-Space Identification(AKSI)***,a model order estimation strategy and a wavenumber filter are proposed to ensure that AKSI is successfully *** main benefit of AKSI is that it is a reliable and fast method under four stochastic conditions:(A)High level of signal noise;(B)Small perturbation caused by uncertainties in measurement points’coordinates;(C)Non-periodic sampling;(D)Unknown structural *** validate the proposed method,we numerically benchmark AKSI and three other inverse methods to extract dispersion curves on three plates under stochastic *** experiment is then performed on an isotropic steel *** investigations demonstrate that AKSI is a good in-situ k-space estimator under stochastic conditions.

关键词： Inverse method Dispersion relation Wavenumber space Periodic plates Stochastic conditions Wave propagation characterization

Classified VPN Network Traffic Flow Using Time Related to Artificial Neural Network

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Computers, Materials & Continua 2024年第7期80卷 819-841页

作者： Saad Abdalla Agaili mohamed Sefer Kurnaz Department of Electrical and Computer Engineering Altinbas UniversityIstanbul34000Turkey

VPNs are vital for safeguarding communication routes in the continually changing cybersecurity ***,increasing network attack complexity and variety require increasingly advanced algorithms to recognize and categorizeVPNnetwork *** present a novelVPNnetwork traffic flowclassificationmethod utilizing Artificial Neural Networks(ANN).This paper aims to provide a reliable system that can identify a virtual private network(VPN)traffic fromintrusion attempts,data exfiltration,and denial-of-service *** compile a broad dataset of labeled VPN traffic flows from various apps and usage ***,we create an ANN architecture that can handle encrypted communication and distinguish benign from dangerous *** effectively process and categorize encrypted packets,the neural network model has input,hidden,and output *** use advanced feature extraction approaches to improve the ANN’s classification accuracy by leveraging network traffic’s statistical and behavioral *** also use cutting-edge optimizationmethods to optimize network characteristics and *** suggested ANN-based categorization method is extensively tested and *** show the model effectively classifies VPN traffic *** also show that our ANN-based technique outperforms other approaches in precision,recall,and F1-score with 98.79%*** study improves VPN security and protects against new *** VPNtraffic flows effectively helps enterprises protect sensitive data,maintain network integrity,and respond quickly to security *** study advances network security and lays the groundwork for ANN-based cybersecurity solutions.

关键词： VPN network traffic flow ANN classification intrusion detection data exfiltration encrypted traffic feature extraction network security

Erdafitinib and checkpoint inhibitors for first-line and second-line immunotherapy of hepatic,gastrointestinal,and urinary bladder carcinomas:Recent concept

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World Journal of Hepatology 2024年第4期16卷 490-493页

作者： mohamed Wishahi Department of Urology Theodor Bilharz Research InstituteCairo 12411Egypt

Cancer immunotherapy is administered for first-line,second-line,neoadjuvant,or adjuvant treatment of advanced,metastatic,and recurrent cancer in the liver,gastrointestinal tract,and genitourinary tract,and other solid *** is a fibroblast growth factor receptor(FGFR)inhibitor,and it is an adenosine triphosphate competitive inhibitor of FGFR1,FGFR2,FGFR3,and *** checkpoint inhibitors are monoclonal antibodies that block programmed cell death protein 1(PD-1)and its ligand that exert intrinsic antitumor *** promising results of first-line treatment of advanced and metastatic urothelial carcinoma with PD-1 blockades with single or combined agents,indicate a new concept in the treatment of advanced,metastatic,and recurrent hepatic and gastrointestinal *** immunotherapy as first-line treatment will improve overall survival and provide better quality of *** is arising as to whether to apply the cancer immunotherapy as first-line treatment in invasive carcinomas,or as second-line treatment in recurrent or metastatic carcinoma following the standard *** literature in the field is not definite,and so far,there has been no consensus on the best approach in this *** present,as it is described in this editorial,the decision is applied on a case-by-case basis.

关键词： Programmed cell death protein-ligand 1 Erdafitinib Liver cancer Fibroblast growth factor receptor inhibitors Checkpoint inhibitors Bladder cancer Metastases

A Practical Study of Intelligent Image-Based Mobile Robot for Tracking Colored Objects

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Computers, Materials & Continua 2024年第8期80卷 2181-2197页

作者： Mofadal Alymani mohamed Esmail Karar Hazem Ibrahim Shehata College of Computing and Information Technology Shaqra UniversityShaqra11961Saudi Arabia Faculty of Electronic Engineering Menoufia UniversityMenouf32952Egypt Faculty of Engineering Zagazig UniversityZagazig44519Egypt

Object tracking is one of the major tasks for mobile robots in many real-world ***,artificial intelligence and automatic control techniques play an important role in enhancing the performance of mobile robot *** contrast to previous simulation studies,this paper presents a new intelligent mobile robot for accomplishing multi-tasks by tracking red-green-blue(RGB)colored objects in a real experimental ***,a practical smart controller is developed based on adaptive fuzzy logic and custom proportional-integral-derivative(PID)schemes to achieve accurate tracking results,considering robot command delay and tolerance *** design of developed controllers implies some motion rules to mimic the knowledge of experienced *** scenarios of three colored object combinations have been successfully tested and evaluated by using the developed controlled image-based robot *** PID control failed to handle some tracking scenarios in this *** proposed adaptive fuzzy PID control achieved the best accurate results with the minimum average final error of 13.8 cm to reach the colored targets,while our designed custom PID control is efficient in saving both average time and traveling distance of 6.6 s and 14.3 cm,*** promising results demonstrate the feasibility of applying our developed image-based robotic system in a colored object-tracking environment to reduce human workloads.

关键词： Mobile robot autonomous systems fuzzy logic control real-time image processing

Combined CNN-LSTM Deep Learning Algorithms for Recognizing Human Physical Activities in Large and Distributed Manners:A Recommendation System

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Computers, Materials & Continua 2024年第4期79卷 351-372页

作者： Ameni Ellouze Nesrine Kadri Alaa Alaerjan mohamed Ksantini Control and Energy Management Laboratory National Engineering SchoolPreparatory Institute for Engineering StudiesUniversity of SfaxSfax3029Tunisia Higher Institute of Computer Science and Communication Technologies University of SousseSousseBN19RHTunisia College of Computer and Information Sciences Jouf UniversityPO Box 2014SakakahSaudi Arabia

Recognizing human activity(HAR)from data in a smartphone sensor plays an important role in the field of health to prevent chronic *** and weekly physical activities are recorded on the smartphone and tell the user whether he is moving well or ***,smartphones and their associated sensing devices operate in distributed and unstable ***,collecting their data and extracting useful information is a significant *** this context,the aimof this paper is twofold:The first is to analyze human behavior based on the recognition of physical *** the results of physical activity detection and classification,the second part aims to develop a health recommendation system to notify smartphone users about their healthy physical behavior related to their physical *** system is based on the calculation of calories burned by each user during physical *** this way,conclusions can be drawn about a person’s physical behavior by estimating the number of calories burned after evaluating data collected daily or even weekly following a series of physical *** identify and classify human behavior our methodology is based on artificial intelligence models specifically deep learning techniques like Long Short-Term Memory(LSTM),stacked LSTM,and bidirectional *** human activity data contains both spatial and temporal information,we proposed,in this paper,to use of an architecture allowing the extraction of the two types of information *** Convolutional Neural Networks(CNN)has an architecture designed for spatial information,our idea is to combine CNN with LSTM to increase classification accuracy by taking into consideration the extraction of both spatial and temporal *** results obtained achieved an accuracy of 96%.On the other side,the data learned by these algorithms is prone to error and *** overcome this constraint and improve performance(96%),we proposed to use the

关键词： Human physical activities smartphone sensors deep learning distributed monitoring recommendation system uncertainty healthy calories

Exploring impedance spectrum for lithium-ion batteries diagnosis and prognosis:A comprehensive review

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Journal of Energy Chemistry 2024年第8期95卷 464-483,I0010页

作者： Xinghao Du Jinhao Meng Yassine Amirat Fei Gao mohamed Benbouzid University of Brest UMR CNRS 6027 IRDL29238 BrestFrance School of Electrical Engineering Xi'an Jiaotong UniversityXi'an 710049ShaanxiChina ISEN Yncréa Ouest L@bISEN29200 BrestFrance Universitéde Technolgie de Belfort-Montbéliard UMR CNRS 6174 FEMTO-ST90000 BelfortFrance

Lithium-ion batteries have extensive usage in various energy storage needs,owing to their notable benefits of high energy density and long *** monitoring of battery states and failure identification are indispensable for guaranteeing the secure and optimal functionality of the *** impedance spectrum has garnered growing interest due to its ability to provide a valuable understanding of material characteristics and electrochemical *** inspire further progress in the investigation and application of the battery impedance spectrum,this paper provides a comprehensive review of the determination and utilization of the impedance *** sources of impedance inaccuracies are systematically analyzed in terms of frequency response *** applicability of utilizing diverse impedance features for the diagnosis and prognosis of batteries is further ***,challenges and prospects for future research are discussed.

关键词： Lithium-ion battery Impedance spectrum Temperature monitoring Failure diagnosis Health prognosis

A reinforcement learning approach for thermostat setpoint preference learning

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Building Simulation 2024年第1期17卷 131-146页

作者： Hussein Elehwany mohamed Ouf Burak Gunay Nunzio Cotrufo Jean-Simon Venne Department of Environmental Engineering Carleton UniversityOttawaCanada Departmentof Building Civiland Environmental EngineeringConcordia UniversityMontrealCanada BrainBox Al Inc. MontrealCanada

Occupant-centric controls(OcC)is an indoor climate control approach whereby occupant feedback is used in the sequence of operation of building energy *** OcC has been used in a wide range of building applications,an OcC category that has received considerable research interest is learning occupants'thermal preferences through their thermostat interactions and adapting temperature setpoints *** recent studies used reinforcement learning(RL)as an agent for OcC to optimize energy use and occupant *** studies depended on predicted mean vote(PMV)models or constant comfort ranges to represent comfort,while only few of them used thermostat *** paper addresses this gap by introducing a new off-policy reinforcement learning(RL)algorithm that imitates the occupant behaviour by utilizing unsolicited occupant thermostat *** algorithm is tested with a number of synthetically generated occupant behaviour models implemented via the Python APl of *** simulation results indicate that the RL algorithm could rapidly learn preferences for all tested occupant behaviour scenarios with minimal exploration *** substantial energy savings were observed with most occupant scenarios,the impact on the energy savings varied depending on occupants'preferences and thermostat use behaviour stochasticity.

关键词： reinforcement learning preference learning occupant-centric controls smart thermostats off-policy learning