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Comparative study between three carbonaceous nanoblades and nanodarts for antimicrobial applications

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

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Explainable Conformer Network for Detection of COVID-19 Pneumonia from Chest CT scan: From Concepts toward Clinical Explainability

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Computers, Materials & Continua 2024年第1期78卷 1171-1187页

作者： mohamed Abdel-Basset Hossam Hawash mohamed Abouhawwash s.s.Askar Alshaimaa A.Tantawy Faculty of Computers and Informatics Zagazig UniversityZagazig44519Egypt Department of Computational Mathematics Scienceand Engineering(CMSE)Michigan State UniversityEast LansingMI48824USA Department of Mathematics Faculty of ScienceMansoura UniversityMansoura35516Egypt Department of statistics and Operations Research College of ScienceKing Saud UniversityP.O.Box 2455Riyadh11451Saudi Arabia

The early implementation of treatment therapies necessitates the swift and precise identification of COVID-19 pneumonia by the analysis of chest CT *** study aims to investigate the indispensable need for precise and interpretable diagnostic tools for improving clinical decision-making for COVID-19 *** paper proposes a novel deep learning approach,called Conformer Network,for explainable discrimination of viral pneumonia depending on the lung Region of Infections(ROI)within a single modality radiographic CT ***,an efficient U-shaped transformer network is integrated for lung image ***,a robust transfer learning technique is introduced to design a robust feature extractor based on pre-trained lightweight Big Transfer(BiT-L)and finetuned on medical data to effectively learn the patterns of infection in the input ***,this work presents a visual explanation method to guarantee clinical explainability for decisions made by Conformer *** evaluation of real-world CT data demonstrated that the diagnostic accuracy of ourmodel outperforms cutting-edge studies with statistical *** Conformer Network achieves 97.40% of detection accuracy under cross-validation *** model not only achieves high sensitivity and specificity but also affords visualizations of salient features contributing to each classification decision,enhancing the overall transparency and trustworthiness of our *** findings provide obvious implications for the ability of our model to empower clinical staff by generating transparent intuitions about the features driving diagnostic decisions.

关键词： Deep learning COVID-19 multi-modal medical image fusion diagnostic image fusion

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Enhancing Renewable Energy Integration:A Gaussian-Bare-Bones Levy Cheetah Optimization Approach to Optimal Power Flow in Electrical Networks

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Computer Modeling in Engineering & sciences 2024年第8期140卷 1339-1370页

作者： Ali s.Alghamdi mohamed A.Zohdy saad Aldoihi Department of Electrical Engineering College of EngineeringMajmaah UniversityAl-Majmaah11952Saudi Arabia Electrical and Computer Engineering Department Oakland UniversityRochesterMI48309USA Institute of Earth and space science King Abdulaziz City for Science and Technology(KACST)Riyadh11442Saudi Arabia Computer science and systems Engineering Institute Polytechnique de ParisPalaiseau CedexFrance

In the contemporary era,the global expansion of electrical grids is propelled by various renewable energy sources(REss).Efficient integration of stochastic REss and optimal power flow(OPF)management are critical for network *** study introduces an innovative solution,the Gaussian Bare-Bones Levy Cheetah Optimizer(GBBLCO),addressing OPF challenges in power generation systems with stochastic *** primary objective is to minimize the total operating costs of REss,considering four functions:overall operating costs,voltage deviation management,emissions reduction,voltage stability index(VsI)and power loss ***,a carbon tax is included in the objective function to reduce carbon *** scrutiny,using modified IEEE 30-bus and IEEE 118-bus systems,validates GBBLCO’s superior performance in achieving optimal *** results demonstrate GBBLCO’s efficacy in six optimization scenarios:total cost with valve point effects,total cost with emission and carbon tax,total cost with prohibited operating zones,active power loss optimization,voltage deviation optimization and enhancing voltage stability index(VsI).GBBLCO outperforms conventional techniques in each scenario,showcasing rapid convergence and superior solution ***,GBBLCO navigates complexities introduced by valve point effects,adapts to environmental constraints,optimizes costs while considering prohibited operating zones,minimizes active power losses,and optimizes voltage deviation by enhancing the voltage stability index(VsI)*** research significantly contributes to advancing OPF,emphasizing GBBLCO’s improved global search capabilities and ability to address challenges related to local *** emerges as a versatile and robust optimization tool for diverse challenges in power systems,offering a promising solution for the evolving needs of renewable energy-integrated power grids.

关键词： Renewable energy integration optimal power flow stochastic renewable energy sources gaussian-bare-bones levy cheetah optimizer electrical network optimization carbon tax optimization

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A New speed Limit Recognition Methodology Based on Ensemble Learning:Hardware Validation

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Computers, Materials & Continua 2024年第7期80卷 119-138页

作者： mohamed Karray Nesrine Triki mohamed Ksantini EsME ESME Research LabIvry Sur Seine94200France CEM Lab ENISUniversity of SfaxSfax3038Tunisia

Advanced DriverAssistance systems(ADAs)technologies can assist drivers or be part of automatic driving systems to support the driving process and improve the level of safety and comfort on the *** sign Recognition system(TsRs)is one of themost important components *** the challengeswith TsRs is being able to recognize road signs with the highest accuracy and the shortest processing ***,this paper introduces a new real time methodology recognizing speed Limit signs based on a trio of developed ***,the speed Limit Detection(sLD)module uses the Haar Cascade technique to generate a new sL detector in order to localize sL signs within captured ***,the speed Limit Classification(sLC)module,featuring machine learning classifiers alongside a newly developed model called DeepsL,harnesses the power of a CNN architecture to extract intricate features from speed limit sign images,ensuring efficient and precise *** addition,a new speed Limit Classifiers Fusion(sLCF)module has been developed by combining trained ML classifiers and the DeepsL model by using the Dempster-shafer theory of belief functions and ensemble learning’s voting *** rigorous software and hardware validation processes,the proposedmethodology has achieved highly significant F1 scores of 99.98%and 99.96%for Ds theory and the votingmethod,***,a prototype encompassing all components demonstrates outstanding reliability and efficacy,with processing times of 150 ms for the Raspberry Pi board and 81.5 ms for the Nano Jetson board,marking a significant advancement in TsRs technology.

关键词： Driving automation advanced driver assistance systems(ADAs) traffic sign recognition(TsR) artificial intelligence ensemble learning belief functions voting method

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Exact and heuristic formulae to compute the geodetic height from the ellipse equation

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Geodesy and Geodynamics 2024年第2期15卷 150-155页

作者： mohamed Eleiche Ahmed Hamdi Mansi Construction Department Faculty of EngineeringEgyptian Russian UniversityCairoEgypt Istituto Nazionale di Geofisica e Vulcanologia Sezione di PisaPisaPlItaly

The conversion of the cartesian coordinates of a point to its geodetic equivalent coordinates in reference to the geodetic ellipsoid is one of the main challenges in *** ellipse equation in the meridian plane significantly influences the value of the geodetic *** research analyzes this influence and how it can contribute to their *** study investigates the mathematical relation between them and presents an exact formula relating to the geodetic height and the ellipse *** addition,a heuristic formula for the relation between the geodetic height and the ellipse equation is proposed,which is independent of the geodetic latitude and has a relative accuracy better than 99.9 %.The calculation is stable,and the cost is low.

关键词： Ellipse equation Geodetic height Heuristic geodetic height

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Insulin therapy in type 2 diabetes: Insights into clinical efficacy, patient-reported outcomes, and adherence challenges

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World Journal of Diabetes 2024年第5期15卷 828-852页

作者： Mahmoud Emad-Eldin Gehan F Balata Eman A Elshorbagy Mona s Hamed mohamed s Attia Department of Pharmacy Practice Faculty of PharmacyZagazig UniversityZagazig HFQM+872Al-Sharqia GovernorateEgypt Department of Pharmacy Practice Faculty of PharmacyHeliopolis UniversityCairo 44519Egypt Department of Pharmaceutics Faculty of PharmacyZagazig UniversityZagazig 44519Al-Sharqia GovernorateEgypt Department of Internal Medicine Faculty of MedicineZagazig UniversityZagazig 44519Al-Sharqia GovernorateEgypt Department of Community at Faculty of Medicine Zagazig UniversityZagazig 44519Al-Sharqia GovernorateEgypt

Insulin therapy plays a crucial role in the management of type 2 diabetes as the disease *** the past century,insulin formulations have undergone significant modifications and bioengineering,resulting in a diverse range of available insulin *** products show distinct pharmacokinetic and pharmacodynamic ***,various insulin regimens have em-erged for the management of type 2 diabetes,including premixed formulations and combinations of basal and bolus *** utilization of different insulin regimens yields disparate clinical outcomes,adverse events,and,notably,patient-reported outcomes(PROs).PROs provide valuable insights from the patient’s perspective,serving as a valuable mine of information for enhancing healthcare and informing clinical *** to insulin therapy,a critical patient-reported outcome,significantly affects clinical outcomes and is influenced by multiple *** review provides insights into the clinical effectiveness of various insulin preparations,PROs,and factors impacting insulin therapy adherence,with the aim of enhancing healthcare practices and informing clinical decisions for individuals with type 2 diabetes.

关键词： Adherence Diabetes Insulin Patient-reported outcomes Pharmacokinetic Pharmacodynamic

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Prediction of Geopolymer Concrete Compressive strength Using Convolutional Neural Networks

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Computer Modeling in Engineering & sciences 2024年第5期139卷 1455-1486页

作者： Kolli Ramujee Pooja sadula Golla Madhu sandeep Kautish Abdulaziz s.Almazyad Guojiang Xiong Ali Wagdy mohamed Department of Civil Engineering VNR Vignana Jyothi Institute of Engineering and TechnologyHyderabadTelangana500090India Department of Information Technology VNR Vignana Jyothi Institute of Engineering and TechnologyHyderabadTelangana500090India Department of Computer science LBEF Campus(Asia Pacific University of Technology&InnovationMalaysia)Kathmandu44600Nepal Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityP.O.Box 51178Riyadh11543Saudi Arabia Guizhou Key Laboratory of Intelligent Technology in Power system College of Electrical EngineeringGuizhou UniversityGuiyang550025China Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Applied science Research Center Applied Science Private UniversityAmmanJordan

Geopolymer concrete emerges as a promising avenue for sustainable development and offers an effective solution to environmental *** attributes as a non-toxic,low-carbon,and economical substitute for conventional cement concrete,coupled with its elevated compressive strength and reduced shrinkage properties,position it as a pivotal material for diverse applications spanning from architectural structures to transportation *** this context,this study sets out the task of using machine learning(ML)algorithms to increase the accuracy and interpretability of predicting the compressive strength of geopolymer concrete in the civil engineering *** achieve this goal,a new approach using convolutional neural networks(CNNs)has been *** study focuses on creating a comprehensive dataset consisting of compositional and strength parameters of 162 geopolymer concrete mixes,all containing Class F fly *** selection of optimal input parameters is guided by two distinct *** first criterion leverages insights garnered from previous research on the influence of individual features on compressive *** second criterion scrutinizes the impact of these features within the model’s predictive *** to enhancing the CNN model’s performance is the meticulous determination of the optimal *** a systematic trial-and-error process,the study ascertains the ideal number of epochs for data division and the optimal value of k for k-fold cross-validation—a technique vital to the model’s *** model’s predictive prowess is rigorously assessed via a suite of performance metrics and comprehensive score ***,the model’s adaptability is gauged by integrating a secondary dataset into its predictive framework,facilitating a comparative evaluation against conventional prediction *** unravel the intricacies of the CNN model’s learning trajectory,a loss plot is deployed to elucidate its learning rat

关键词： Class F fly ash compressive strength geopolymer concrete prediction deep learning convolutional neural network

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Intravesical instillation of platelet-rich plasma for treatment of interstitial cystitis/bladder pain syndrome:A pilot study

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Current Urology 2024年第1期18卷 49-54页

作者： Ahmed s.El Hefnawy mohamed Attya Ahmed Hasan Esam El sawy mohamed Abdel-Razik Nasr El-Tabey Mansoura Urology and Nephrology Center Faculty of MedicineMansoura UniversityMansouraEgypt

Objective:The aim of this study was to evaluate the feasibility of intravesical instillation of platelet-rich plasma(PRP)to treat interstitial cystitis/bladder pain syndrome(IC/BPs).Materials and methods:Twenty PRP samples were tested in vitro for stability after exposure to urine samples with different pH.A pilot study involving 21 female patients with IC/BPs was conducted,and 6 weekly doses of autologous PRP(50 mL)were *** were followed up at the 2nd,4th,8th,and 12th weeks after terminating *** primary endpoint was the visual analog scale(VAs)for pain,and the secondary endpoints included the IC symptom index,IC problem index of the O'Leary-sant questionnaire and global response assessment,urine culture,and *** was defined as a reduction in VAs by 30%or more compared with basal level,and adverse events were ***:The mean±sD of VAs was significantly reduced compared with basal level(4.4±2.6 vs.8.8±1.1,respectively,p=0.001).Meanwhile,80%of cases were considered successful,with a 50.1%reduction in the mean score compared with the basal *** mean±sD of IC symptom index and IC problem index significantly improved compared with the basal *** response assessment was markedly,moderately,and slightly improved in 2(10%),10(50%),and 5(25%)patients,respectively,and showed no change in 3(15%).Three patients had positive urine cultures at follow-up,but 1 withdrew after 2 sessions because of a lack of ***:Repeated intravesical instillation of PRP could be considered an effective and safe approach for treating IC/BPs.

关键词： Bladder pain syndrome Interstitial cystitis Platelet-rich plasma

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Pyronaridine combined with diminazene aceturate inhibits Babesia in vitro and in vivo

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Asian Pacific Journal of Tropical Biomedicine 2024年第3期14卷 93-99页

作者： shimaa Abd El-salam El-sayed mohamed Z.sayed-Ahmed shaimaa Ahmed Awad Ali Nourah Alsadaan Nawazish Alam Mahmoud s.Alkhoudary Ikuo Igarashi mohamed Abdo Rizk National Research Center for Protozoan Diseases Obihiro University of Agriculture and Veterinary MedicineInada-ChoObihiroHokkaido 080-8555Japan Department of Biochemistry and Chemistry of Nutrition Faculty of Veterinary MedicineMansoura UniversityMansoura 35516Egypt Department of Clinical Pharmacy College of PharmacyJazan UniversityJazan 45142Saudi Arabia Medical-surgical Department College of NursingJouf UniversitySakaka 72388Saudi Arabia Critical Care and Emergency Nursing Faculty of NursingMansoura UniversityEgypt College of Nursing Jouf UniversitySakaka 72388Saudi Arabia Faculty of Pharmacy Mansoura UniversityMansoura 35516DakahliaEgypt Department of Internal Medicine and Infectious Diseases Faculty of Veterinary MedicineMansoura UniversityMansoura 35516Egypt

Objective:To evaluate the combination therapy of pyronaridine tetraphosphate and diminazene aceturate against Babesia in vitro and in ***:Bioinformatic analysis was performed using atom pair *** in vitro combination test was performed against Babesia bovis and Theileria ***,the in vivo chemotherapeutic efficacy of pyronaridine tetraphosphate in combination with diminazene aceturate was investigated against the growth of Babesia microti in mice using a fluorescence inhibitory ***:Pyronaridine tetraphosphate and diminazene aceturate exhibited nearly similar molecular *** in vitro combination of pyronaridine tetraphosphate and diminazene aceturate was synergistic on Babesia bovis and additive on Theileria *** addition,5 mg/kg pyronaridine tetraphosphate combined with 10 mg/kg diminazene aceturate inhibited Babesia microti growth significantly compared with those observed after treatment with 25 mg/kg diminazene aceturate alone from day 6 post treatment to day 12 post *** combination therapy also normalized the hematological parameters of infected ***:An oral dose of pyronaridine tetraphosphate combined with a subcutaneous dose of diminazene aceturate inhibits Babesia in vitro and in mice,suggesting it might be a new paradigm for the treatment of babesiosis.

关键词： Babesia Pyronaridine tetraphosphate Diminazene aceturate Babesiosis Theileria

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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

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