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International Journal of Ophthalmology(English edition) 2024年第1期17卷 61-65页

作者： Ahmed Mohamed Karara Zeinab el-Sanabary mostafa ali el-helw Tamer Ahmed Macky Mohamad Amr Salah Eddin Abdelhakim Department of Ophthalmology Kasr Al-Ainy HospitalCairo UniversityCairo 11431Egypt

AIM:To develop normative data for meibomian gland dysfunction(MGD)parameters,using non-contact meibography technique of Sirius Costruzione Strumenti Oftalmici(CSO)machine,in an Egyptian population ***:Observational,cross-sectional,analytic study,in which 104 Egyptian volunteers were *** upper lids were examined,using“Sirius CSO”*** eyelid was given a degree of meibomian gland loss(MGL),which was calculated by the software of the ***:Mean percentage MGL in right upper lid was of 30.9%±12.6%,and that of left upper lid was 32.6%±11.8%.Thirty-four volunteers(32.7%)had first-degree MGL in their right upper lid,and 67.3%had second-degree *** volunteer(1%)had zero-degree MGL in left upper lid,28(26.9%)had first-degree loss,and 75(72.1%)had second-degree *** of MGL in right upper eyelid was not related to age,but degree of MGL in left upper eyelid increased with *** was statistically significant difference between both genders for degree of MGL in right eye(P=0.036)and in left eye(P=0.027).CONCLUSION:Noncontact meibography is a useful non-invasive tool for diagnosing *** is diagnosed in 100%of apparently normal individuals;26.9%-32.7%of which have first-degree MGL,and 67.3%-72.1%have second-degree MGL.

关键词： Egyptian population meibomian gland dysfunction non-contact meibography standardization upper lid

A Comprehensive Review on Charging Topologies and Power electronic Converter Solutions for electric Vehicles

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Journal of Modern Power Systems and Clean Energy 2024年第3期12卷 675-694页

作者： Abdelfatah ali Hossam H.H.Mousa mostafa F.Shaaban Maher A.Azzouz Ahmed S.A.Awad the Department of electrical Engineering American University of Sharjah26666 SharjahUnited Arab Emirates the Department of electrical Engineering South Valley University83523 QenaEgypt the Department of electrical and Computer Engineering University of WindsorWindsorON N9B 3P4 Canada electrical Engineering Department Qatar UniversityDoha 2713Qatar Department of electrical and Computer Engineering Sultan Qaboos UniversityMuscat123Oman

electric vehicles(EVs)are becoming more popular worldwide due to environmental concerns,fuel security,and price *** performance of EVs relies on the energy stored in their batteries,which can be charged using either AC(slow)or DC(fast)***,EVs can also be used as mobile power storage devices using vehicle-to-grid(V2G)*** electronic converters(PECs)have a constructive role in EV applications,both in charging EVs and in ***,this paper comprehensively investigates the state of the art of EV charging topologies and PEC solutions for EV *** examines PECs from the point of view of their classifications,configurations,control approaches,and future research prospects and their impacts on power *** can be classified into various topologies:DC-DC converters,AC-DC converters,DC-AC converters,and AC-AC *** address the limitations of traditional DC-DC converters such as switching losses,size,and high-electromagnetic interference(EMI),resonant converters and multiport converters are being used in high-voltage EV ***,power-train converters have been modified for high-efficiency and reliability in EV *** paper offers an overview of charging topologies,PECs,challenges with solutions,and future trends in the field of the EV charging station applications.

关键词： Charging station charging topology electric vehicle power electronic converter vehicle-to-grid

Infectious causes of fever of unknown origin in developing countries: An international ID-IRI study

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Journal of Intensive Medicine 2024年第1期4卷 94-100页

作者： Hakan Erdem Jaffar AAl-Tawfiq Maha Abid Wissal Ben Yahia George Akafity Manar Ezzelarab Ramadan Fatma Amer Amani el-Kholy Atousa Hakamifard Bilal Ahmad Rahimi Farouq Dayyab Hulya Caskurlu Reham Khedr Muhammad Tahir Lysien Zambrano Mumtaz ali Khan Aun Raza Nagwa mostafa el-Sayed Magdalena Baymakova Aysun Yalci Yasemin Cag Umran elbahr Aamer Ikram Department of Infectious Diseases&Clinical Microbiology Gulhane School of MedicineTurkish Health Sciences UniversityAnkaraTurkey Specialty Internal Medicine and Quality and Patient Safety Department Johns Hopkins Aramco HealthcareDhahranSaudi Arabia Division of Infectious Diseases Indiana University School of MedicineIndianapolisINUSA Department of Infectious Diseases Farhat Hached University HospitalIbn El Jazzar Medical SchoolUniversity of SousseSousseTunisia Internal Medicine Department Farhat Hached University HospitalIbn El Jazzar Medical SchoolUniversity of SousseSousseTunisia Cape Coast Teaching Hospital Cape CoastGhana Medical Parasitology Faculty of MedicineSuez UniversitySuezEgypt Department of Medical Microbiology and Immunology Faculty of MedicineZagazig UniversityZagazigEgypt Department of Clinical Pathology Faculty of MedicineCairo UniversityGizaEgypt Department of Infectious Diseases School of MedicineIsfahan University of Medical SciencesIsfahanIran Department of Infectious Diseases Kandahar University Medical FacultyTeaching HospitalKandaharAfghanistan Department of Infectious Diseases Mohammed Bn Khalifa Bn Salman Alkhalifa Specialist Cardiac CenterAwaliBahrain Department of Infectious Diseases and Clinical Microbiology Faculty of MedicineIstanbul Medeniyet UniversityIstanbulTurkey Department of Pediatric Oncology National Cancer Institute–Cairo UniversityChildren Cancer Hospital EgyptCairoEgypt Department of Medicine Federal General HospitalIslamabadPakistan Institute for Research in Medical Sciences and Right to Health(ICIMEDES) Scientific Research Unit(UIC)Faculty of Medical Sciences(FCM)National Autonomous University of Honduras(UNAH)TegucigalpaHonduras National Institute of Health IslamabadPakistan Shaukat Khanum Memorial Cancer Hospital and Research Center LahorePakistan Medical Parasitology Department Research Institute of OphthalmologyGizaEgypt Department of Infectious Diseases Military Medical AcademySofiaBulgaria Department of Infecti

Background:Fever of unknown origin(FUO)in developing countries is an important dilemma and further research is needed to elucidate the infectious causes of ***:A multi-center study for infectious causes of FUO in lower middle-income countries(LMIC)and lowincome countries(LIC)was conducted between January 1,2018 and January 1,*** total,15 participating centers from seven different countries provided the data,which were collected through the Infectious DiseasesInternational Research Initiative *** adult patients with confirmed infection as the cause of FUO were included in the *** severity parameters were quick Sequential Organ Failure Assessment(qSOFA)≥2,intensive care unit(ICU)admission,vasopressor use,and invasive mechanical ventilation(IMV).Results:A total of 160 patients with infectious FUO were included in the ***,148(92.5%)patients had community-acquired infections and 12(7.5%)had hospital-acquired *** most common infectious syndromes were tuberculosis(TB)(n=27,16.9%),infective endocarditis(n=25,15.6%),malaria(n=21,13.1%),brucellosis(n=15,9.4%),and typhoid fever(n=9,5.6%).Plasmodium falciparum,Mycobacterium tuberculosis,Brucellae,Staphylococcus aureus,Salmonella typhi,and Rickettsiae were the leading infectious agents in this study.A total of 56(35.0%)cases had invasive procedures for *** mean qSOFA score was 0.76±0.94{median(interquartile range[IQR]):0(0–1)}.ICU admission(n=26,16.2%),vasopressor use(n=14,8.8%),and IMV(n=10,6.3%)were not ***,38(23.8%)patients had at least one of the severity *** mortality rate was 15(9.4%),and the mortality was attributable to the infection causing FUO in 12(7.5%)***:In LMIC and LIC,tuberculosis and cardiac infections were the most severe and the leading infections causing FUO.

关键词： Developing countries Fever of unknown origin Infection

Challenges to establishing and maintaining kidney transplantation programs in developing countries:What are the coping strategies?

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World Journal of Methodology 2024年第2期14卷 1-16页

作者： Rabea Ahmed Gadelkareem Amr mostafa Abdelgawad Nasreldin Mohammed Mohammed ali Zarzour Mahmoud Khalil Ahmed Reda Hisham Mokhtar Hammouda Department of Urology Assiut Urology and Nephrology HospitalFaculty of MedicineAssiut UniversityAssiut 71515Egypt

Kidney transplantation(KT)is the optimal form of renal replacement therapy for patients with end-stage renal ***,this health service is not available to all patients,especially in developing *** deceased donor KT programs are mostly absent,and the living donor KT centers are ***-center studies presenting experiences from developing countries usually report a variety of *** review addresses these challenges and the opposing strategies by reviewing the single-center experiences of developing *** financial challenges hamper the infrastructural and material availability,coverage of transplant costs,and qualification of medical *** sociocultural challenges influence organ donation,equity of beneficence,and regular follow-up *** interests and motives for transplantation may result from high medicolegal responsibilities in KT practice,intense potential psychosocial burdens,complex qualification protocols,and low productivity or compensation for KT *** medical literacy about KT advantages is prevalent among clinicians,patients,and the *** inefficient organizational and regulatory oversight is translated into inefficient healthcare systems,absent national KT programs and registries,uncoordinated job descriptions and qualification protocols,uncoordinated on-site investigations with regulatory constraints,and the prevalence of commercial KT *** challenges resulted in noticeable differences between KT services in developed and developing *** coping strategies can be summarized in two main mechanisms:The first mechanism is maximizing the available resources by increasing the rates of living kidney donation,promoting the expertise of medical personnel,reducing material consumption,and supporting the establishment and maintenance of KT *** latter warrants the expansion of the public sector and the elimination of non-ethical KT *** second mechanism is recru

关键词： Challenges Coping strategies Developing countries Kidney transplantation Low resources Single-center

Novel Framework of Segmentation 3D MRI of Brain Tumors

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Computers, Materials & Continua 2023年第2期74卷 3489-3502页

作者： Ibrahim Mahmoud el-Henawy mostafa elbaz Zainab H.ali Noha Sakr Department of Computer Science Faculty of Computers and InformaticsZagazig UniversityZagazigEgypt Department of Computer Science Faculty of Computers and InformaticsKafrelsheikh UniversityKafrelsheikhEgypt Department of Embedded Network Sys.and Tec. Faculty of Artificial IntelligenceKafrelsheikh UniversityKafrelsheikhEgypt Computers Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansouraEgypt

Medical image segmentation is a crucial process for computer-aided diagnosis and *** image segmentation refers to portioning the images into small,disjointed parts for simplifying the processes of analysis and *** and speckle noise are different types of noise in magnetic resonance imaging(MRI)that affect the accuracy of the segmentation process ***,image enhancement has a significant role in MRI *** paper proposes a novel framework that uses 3D MRI images from Kaggle and applies different diverse models to remove Rician and speckle noise using the best possible noise-free *** proposed techniques consider the values of Peak Signal to Noise Ratio(PSNR)and the level of noise as inputs to the attention-U-Net model for segmentation of the *** framework has been divided into three stages:removing speckle and Rician noise,the segmentation stage,and the feature extraction *** framework presents solutions for each problem at a different stage of the *** the first stage,the framework uses Vibrational Mode Decomposition(VMD)along with Block-matching and 3D filtering(Bm3D)algorithms to remove the ***,the most significant Rician noise-free images are passed to the three different methods:Deep Residual Network(DeRNet),Dilated Convolution Auto-encoder Denoising Network(Di-Conv-AE-Net),andDenoising Generative Adversarial Network(DGAN-Net)for removing the speckle *** Bm3D have achieved PSNR values for levels of noise(0,0.25,0.5,0.75)for reducing the Rician noise by(35.243,32.135,28.214,24.124)and(36.11,31.212,26.215,24.123)*** framework also achieved PSNR values for removing the speckle noise process for each level as follows:(34.146,30.313,28.125,24.001),(33.112,29.103,27.110,24.194),and(32.113,28.017,26.193,23.121)forDeRNet,Di-Conv-AE-Net,and DGAN-Net,*** experiments that have been conducted have proved the efficiency of the proposed framework a

关键词： MRI Rician noise speckle noise segmentation deep learning

Residual Attention Deep SVDD for COVID-19 Diagnosis Using CT Scans

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Computers, Materials & Continua 2023年第2期74卷 3333-3350页

作者： Akram ali Alhadad Omar Tarawneh Reham R.mostafa Hazem M.el-Bakry Information Systems Department Faculty of Computers and InformationMansoura UniversityMansoura35511Egypt Computer Science Department Ibb UniversityIbbYemen SE Department Faculty of Computer Sciences and InformaticsAmman Arab UniversityAmman11953Jordan

COVID-19 is the common name of the disease caused by the novel coronavirus(2019-nCoV)that appeared in Wuhan,China in *** the infected people is the most important factor in the fight against the *** gold-standard test to diagnose COVID-19 is polymerase chain reaction(PCR),but it takes 5–6 h and,in the early stages of infection,may produce false-negative *** Computed Tomography(CT)images to diagnose patients infected with COVID-19 has become an urgent *** this study,we propose a residual attention deep support vector data description SVDD(RADSVDD)approach to diagnose *** is a novel approach combining residual attention with deep support vector data description(DSVDD)to classify the CT *** the best of our knowledge,we are the first to combine residual attention with DSVDD in general,and specifically in the diagnosis of *** attention with DSVDD naively may cause model *** in the proposed RADSVDD guides the network during training and enables quick learning,residual connectivity prevents vanishing *** approach consists of three models,each model is devoted to recognizing one certain disease and classifying other diseases as *** models learn in an end-to-end *** proposed approach attained high performance in classifying CT images into intact,COVID-19,and non-COVID-19 *** evaluate the proposed approach,we created a dataset from published datasets and had it assessed by an experienced *** proposed approach achieved high performance,with the normal model attained sensitivity(0.96–0.98),specificity(0.97–0.99),F1-score(0.97–0.98),and area under the receiver operator curve(AUC)0.99;the COVID-19 model attained sensitivity(0.97–0.98),specificity(0.97–0.99),F1-score(0.97–0.99),and AUC 0.99;and the non-COVID pneumoniamodel attained sensitivity(0.97–1),specificity(0.98–0.99),F1-score(0.97–0.99),and AUC 0.99.

关键词： Deep learning deep SVDD residual attention anomaly detection COVID-19 Coronavirus

COVID-19 and hepatic injury: cellular and molecular mechanisms in diverse liver cells

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World Journal of Gastroenterology 2023年第3期29卷 425-449页

作者： Fares E M ali mostafa K Abd el-Aziz Mahmoud M ali Osama M Ghogar Adel G Bakr Department of Pharmacology and Toxicology Faculty of PharmacyAl-Azhar UniversityAssiut 71524Egypt Department of Pharmacology Al-Azhar UniversityAssiut 71524Egypt Department of Biochemistry Faculty of Pharmacy Badr University in AssiutEgypt

The coronavirus disease 2019(COVID-19)represents a global health and economic *** injuries have been approved to be associated with severe acute respiratory syndrome coronavirus(SARS-CoV-2)*** viral tropism pattern of SARS-CoV-2 can induce hepatic injuries either by itself or by worsening the conditions of patients with hepatic ***,other factors have been reported to play a crucial role in the pathological forms of hepatic injuries induced by SARS-CoV-2,including cytokine storm,hypoxia,endothelial cells,and even some treatments for *** the other hand,several groups of people could be at risk of hepatic COVID-19 complications,such as pregnant women and *** present review outlines and discusses the interplay between SARS-CoV-2 infection and hepatic injury,hepatic illness comorbidity,and risk ***,it is focused on the vaccination process and the role of developed vac-cines in preventing hepatic injuries due to SARS-CoV-2 infection.

关键词： COVID-19 Hepatic injury Viral tropism COVID-19 comorbidity Vaccination

An ensemble deep learning model for cyber threat hunting in industrial internet of things

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Digital Communications and Networks 2023年第1期9卷 101-110页

作者： Abbas Yazdinejad mostafa Kazemi Reza M.Parizi ali Dehghantanha Hadis Karimipour Cyber Science Lab School of Computer ScienceUniversity of GuelphOntarioCanada Department of electrical Engineering Faculty of EngineeringShahed UniversityTehranIran College of Computing and Software Engineering Kennesaw State UniversityGAUSA School of Engineering University of GuelphOntarioCanada

By the emergence of the fourth industrial revolution,interconnected devices and sensors generate large-scale,dynamic,and inharmonious data in Industrial Internet of Things(IIoT)*** vast heterogeneous data increase the challenges of security risks and data analysis *** IIoT grows,cyber-attacks become more diverse and complex,making existing anomaly detection models less effective to *** this paper,an ensemble deep learning model that uses the benefits of the Long Short-Term Memory(LSTM)and the AutoEncoder(AE)architecture to identify out-of-norm activities for cyber threat hunting in IIoT is *** this model,the LSTM is applied to create a model on normal time series of data(past and present data)to learn normal data patterns and the important features of data are identified by AE to reduce data *** addition,the imbalanced nature of IIoT datasets has not been considered in most of the previous literature,affecting low accuracy and *** solve this problem,the proposed model extracts new balanced data from the imbalanced datasets,and these new balanced data are fed into the deep LSTM AE anomaly detection *** this paper,the proposed model is evaluated on two real IIoT datasets-Gas Pipeline(GP)and Secure Water Treatment(SWaT)that are imbalanced and consist of long-term and short-term dependency on *** results are compared with conventional machine learning classifiers,Random Forest(RF),Multi-Layer Perceptron(MLP),Decision Tree(DT),and Super Vector Machines(SVM),in which higher performance in terms of accuracy is obtained,99.3%and 99.7%based on GP and SWaT datasets,***,the proposed ensemble model is compared with advanced related models,including Stacked Auto-Encoders(SAE),Naive Bayes(NB),Projective Adaptive Resonance Theory(PART),Convolutional Auto-Encoder(C-AE),and Package Signatures(PS)based LSTM(PS-LSTM)model.

关键词： Internet of things IIoT Anomaly detection Ensemble deep learning Neural networks LSTM

Therapeutic interventions of acute and chronic liver disorders:A comprehensive review

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World Journal of Hepatology 2023年第1期15卷 19-40页

作者： Fares EM ali mostafa K Abd el-Aziz elham I Sharab Adel G Bakr Department of Pharmacology and Toxicology Faculty of PharmacyAl-Azhar UniversityAssiut BranchAssiut 71524Egypt Faculty of Pharmacy Al-Azhar UniversityAssiut BranchAssiut 71524Egypt

Liver disorders are one of the most common pathological problems *** affects more than 1.5 billion *** types of hepatic cells have been reported to be involved in the initiation and propagation of both acute and chronic liver diseases,including hepatocytes,Kupffer cells,sinusoidal endothelial cells,and hepatic stellate cells(HSCs).In addition,oxidative stress,cytokines,fibrogenic factors,microRNAs,and autophagy are also *** the molecular mechanisms of liver diseases leads to discovering new therapeutic interventions that can be used in ***,antioxidant,anti-inflammatory,anti-HSCs therapy,gene therapy,cell therapy,gut microbiota,and nanoparticles have great potential for preventing and treating liver ***,we explored the recent possible molecular mechanisms involved in the pathogenesis of acute and chronic liver ***,we overviewed the recent therapeutic interventions that targeted liver diseases and summarized the recent studies concerning liver disorders therapy.

关键词： Liver disorders Autophagy Gene therapy Anti-hepatic stellate cells Cell therapy

Hybrid of Distributed Cumulative Histograms and Classification Model for Attack Detection

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Computer Systems Science & Engineering 2023年第5期45卷 2235-2247页

作者： mostafa Nassar Anas M.ali Walid el-Shafai Adel Saleeb Fathi E.Abd el-Samie Naglaa F.Soliman Hussah Nasser AlEisa Hossam eldin H.Ahmed Department of electronics and electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Alexandria Higher Institute of Engineering&Technology(AIET) AlexandriaEgypt Department of Computer Science Security Engineering LaboratoryPrince Sultan UniversityRiyadh11586Saudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadhSaudi Arabia

Traditional security systems are exposed to many various attacks,which represents a major challenge for the spread of the Internet in the *** techniques have been suggested for detecting attacks using machine learning and deep *** significant advantage of deep learning is that it is highly efficient,but it needs a large training time with a lot of ***,in this paper,we present a new feature reduction strategy based on Distributed Cumulative Histograms(DCH)to distinguish between dataset features to locate the most effective *** histograms assess the dataset instance patterns of the applied features to identify the most effective attributes that can significantly impact the classification *** different models for detecting attacks using Convolutional Neural Network(CNN)and Long Short-Term Memory Network(LSTM)are also *** accuracy test of attack detection using the hybrid model was 98.96%on the UNSW-NP15 *** proposed model is compared with wrapper-based and filter-based Feature Selection(FS)*** proposed model reduced classification time and increased detection accuracy.

关键词： Feature selection DCH LSTM CNN security systems