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Incidence, Clinical Presentation and Angiographic Findings among Patients with Coronary Artery Ectasia in Gaza

Health 2024年第3期16卷 234-241页

作者： mohammed Habib Cardiology Department Alshifa Hospital Gaza Palestine

Background: Coronary artery ectasia (CAE) is a rare form of aneurysmal coronary heart disease. This condition increases risk of ischemia that leaded to stable angina pectoris and also acute coronary syndrome. Objective: To evaluate the incidence of CAE and to analyze clinical and angiographic characteristics among patients with symptomatic coronary artery disease. Methods: Retrospective trial of diagnostic coronary angiography which was performed at Alshifa hospital in Gaza, included all patients with coronary heart disease and underwent diagnostic coronary angiography from March 2014 to March 2023. We evaluate the incidence, clinical presentation and angiographic findings of patients with symptomatic coronary ectasia. Results: Of the 12,534 angiograms analyzed, CAE was found in 539 patients, an incidence of 4.3%. The mean age was 59.2 ± 11.7 years, and male gender predominate 81.8%. A 285 (52.9%) of patients found to have single ectatic vessel at their angiographic results. In two vessels 120 patients (22.3%), in three vessels 95 patients (17.6%) and in three vessel plus left main in 39 patients (7.2%). 70.9% angiograms showed pure ectasia without associated significant stenotic lesions in the same vessel. The right coronary artery (RCA) was the commonest affected vessel by ectasia. The most common presentation of patients is non ST segment elevation acute coronary syndrome. Conclusion: The incidence of coronary ectasia was 4.3%. Non ST segment elevation acute coronary syndrome was the most common clinical presenting. Only 30% of patients have additionally significant coronary artery stenosis. The majority of patients had single vessel involvement and right coronary artery was the most common involved vessel. Despite a dapper understanding of CAE in last years, there are still come critical issues about optimal treatment. Large multicenter randomized control trials are recommended to guide the clinician in the management of this complex sitting of patients.

关键词： CAE STEMI Non-STE-ACS Stable Angina Pectoris

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Flood susceptibility mapping using a novel integration of multi-temporal sentinel-1 data and eXtreme deep learning model

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Geoscience Frontiers 2024年第3期15卷 67-84页

作者： Rami Al-Ruzouq Abdallah Shanableh Ratiranjan Jena mohammed Barakat A.Gibril Nezar Atalla Hammouri Fouad Lamghari GIS&Remote Sensing Center Research Institute of Sciences and EngineeringUniversity of SharjahSharjah 27272United Arab Emirates Civil and Environmental Engineering Department University of SharjahSharjah 27272United Arab Emirates Department of Earth and Environmental Sciences Prince El-Hassan bin Talal Faculty for Natural Resources&EnvironmentThe Hashemite UniversityZarqaJordan Fujairah Research Centre Fujairah CityAl Hilal TowerAl Hilal CityFujairahUnited Arab Emirates

Flash floods(FFs)are amongst the most devastating hazards in arid regions in response to climate change and can cause the loss of agricultural land,human lives and *** of the major challenges is the high-intensity rainfall events affecting low-lying areas that are vulnerable to *** works in this field have been conducted using ensemble machine learning models and geohydrological ***,the current advancement of eXtreme deep learning,which is named eXtreme deep factorisation machine(xDeepFM),for FF susceptibility mapping(FSM)is lacking in the *** current study introduces a new model and employs a previously unapplied approach to enhance FSM for capturing the severity of *** proposed approach has three main objectives:(i)During-and after-flood effects are assessed through flood detection techniques using Sentinel-1 data.(ii)Flood inventory is updated using remote sensing-based *** derived flood effects are implemented in the next step.(iii)An FSM map is generated using an xDeepFM ***,this study aims to apply xDeepFM to estimate susceptible areas using 13 factors in the emirates of Fujairah,*** performance metrics show a recall of 0.9488),an F1-score of 0.9107),precision of(0.8756)and an overall accuracy of 90.41%.The accuracy of the applied xDeepFM model is compared with that of traditional machine learning models,specifically the deep neural network(78%),support vector machine(85.4%)and random forest(88.75%).Random forest achieves high accuracy,which is due to its strong performance that depends on factors contribution,dataset size and quality,and available computational ***,the xDeepFM model works efficiently for complicated prediction problems having high non-collinearity and huge *** obtained map denotes that the narrow basins,lowland coastal areas and riverbank areas up to 5 km(Fujairah)are highly prone to FF,whilst the alluvial plains in Al Dhaid and hilly regio

关键词： Flood susceptibility mapping eXtreme Deep Factorisation Machine Sentinel-1 Remote sensing

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Integrating petrophysical data into efficient iterative cluster analysis for electrofacies identification in clastic reservoirs

Energy Geoscience

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Energy Geoscience 2024年第4期5卷 291-305页

作者： mohammed A.Abbas Watheq J.Al-Mudhafar Aqsa Anees David A.Wood Basrah Oil Company BasrahIraq Institute of International Rivers and Eco-Security Yunnan UniversityKunming650500China Institute for Ecological Research and Pollution Control of Plateau Lakes School of Ecology and Environmental ScienceYunnan UniversityKunming650500China DWA Energy Limited LincolnUK

Efficient iterative unsupervised machine learning involving probabilistic clustering analysis with the expectation-maximization(EM)clustering algorithm is applied to categorize reservoir facies by exploiting latent and observable well-log variables from a clastic reservoir in the Majnoon oilfield,southern *** observable well-log variables consist of conventional open-hole,well-log data and the computer-processed interpretation of gamma rays,bulk density,neutron porosity,compressional sonic,deep resistivity,shale volume,total porosity,and water saturation,from three wells located in the Nahr Umr *** latent variables include shale volume and water *** EM algorithm efficiently characterizes electrofacies through iterative machine learning to identify the local maximum likelihood estimates(MLE)of the observable and latent variables in the studied *** optimized EM model developed successfully predicts the core-derived facies classification in two of the studied *** EM model clusters the data into three distinctive reservoir electrofacies(F1,F2,and F3).F1 represents a gas-bearing electrofacies with low shale volume(Vsh)and water saturation(Sw)and high porosity and permeability values identifying it as an attractive reservoir *** results of the EM model are validated using nuclear magnetic resonance(NMR)data from the third studied well for which no cores were *** NMR results confirm the effectiveness and accuracy of the EM model in predicting *** utilization of the EM algorithm for electrofacies classification/cluster analysis is ***,the clusters it establishes are less rigidly constrained than those derived from the more commonly used K-means clustering *** EM methodology developed generates dependable electrofacies estimates in the studied reservoir intervals where core samples are not ***,once calibrated with core data in some wells,the model is suitable for

关键词： Cluster analysis Electrofacies classification Expectation-maximization(EM)algorithm Clastic reservoir Maximum likelihood estimate(MLE)

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Investigating and predicting the role of photovoltaic, wind, and hydrogen energies in sustainable global energy evolution

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Global Energy Interconnection 2024年第4期7卷 429-445页

作者： Mahmood Swadi Dheyaa Jasim Kadhim Mohamed Salem Firas mohammed Tuaimah Ammar Sabri Majeed Ali Jawad Alrubaie Department of Electrical Engineering College of EngineeringUniversity of BaghdadBaghdad 10001Iraq Libyan Authority for Scientific Research Tripoli 80045Libya School of Electrical and Electronic Engineering Universiti Sains Malaysia(USM)Nibong Tebal 14300PenangMalaysia Continuing Education Center University of BaghdadBaghdad 10001Iraq Al-Furat Al-Awsat Technical University AL-Mussaib Technical CollegeBabylonIraq

The global shift toward next-generation energy systems is propelled by the urgent need to combat climate change and the dwindling supply of fossil *** review explores the intricate challenges and opportunities for transitioning to sustainable renewable energy sources such as solar,wind,and *** transition economically challenges traditional energy sectors while fostering new industries,promoting job growth,and sustainable economic *** transition to renewable energy demands social equity,ensuring universal access to affordable energy,and considering community *** environmental benefits include a significant reduction in greenhouse gas emissions and a lesser ecological *** study highlights the rapid growth of the global wind power market,which is projected to increase from$112.23 billion in 2022 to$278.43 billion by 2030,with a compound annual growth rate of 13.67%.In addition,the demand for hydrogen is expected to increase,significantly impacting the market with potential cost reductions and making it a critical renewable energy source owing to its affordability and zero *** 2028,renewables are predicted to account for 42%of global electricity generation,with significant contributions from wind and solar photovoltaic(PV)technology,particularly in China,the European Union,the United States,and *** developments signify a global commitment to diversifying energy sources,reducing emissions,and moving toward cleaner and more sustainable energy *** review offers stakeholders the insights required to smoothly transition to sustainable energy,setting the stage for a resilient future.

关键词： Next energy Renewable energy Sustainability Environmental benefits Economic opportunities

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Proteome profiling to advance management of metabolic dysfunction-associated fatty liver disease

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Hepatobiliary Surgery and Nutrition 2024年第1期13卷 147-149页

作者： mohammed Eslam Nahum Méndez-Sánchez Ming-Hua Zheng Storr Liver Centre Westmead Institute for Medical ResearchWestmead Hospital and University of SydneySydneyNSWAustralia Liver Research Unit Medica Sur Clinic FoundationMexico CityMexico MAFLD Research Center Department of HepatologyThe First Affiliated Hospital of Wenzhou Medical UniversityWenzhouChina Institute of Hepatology Wenzhou Medical UniversityWenzhouChina Key Laboratory of Diagnosis and Treatment for The Development of Chronic Liver Disease in Zhejiang Province WenzhouChina

Metabolic dysfunction-associated fatty liver disease(MAFLD)is a complex,heterogenous and progressive disease that is characterised by substantial phenotypic variability,which results in disparate clinical presentations and outcomes(1-4).Notably,only a proportion of patients with MAFLD progress to the more advanced stages of the ***,the identification of the subgroups that have a high risk of disease progression is of paramount importance for clinical care,as well as drug development and clinical trials(5).

关键词： Metabolic dysfunction-associated fatty liver disease(MAFLD) fatty liver disease(FLD) fibrosis proteome biomarkers

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Does progress in microfracture techniques necessarily translate into clinical effectiveness?

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World Journal of Orthopedics 2024年第3期15卷 266-284页

作者： Sathish Muthu Vibhu Krishnan Viswanathan Manoharan Sakthivel mohammed Thabrez Department of Orthopaedics Orthopaedic Research GroupCoimbatore 641045Tamil NaduIndia Department of Biotechnology Karpagam Academy of Higher EducationCoimbatore 641021Tamil NaduIndia Manoharan Sakthivel Department of OrthopaedicsGovernment Medical CollegeKarur 639004Tamil NaduIndia Department of Orthopaedics Devadoss Multispecialty HospitalMadurai 625007Tamil NaduIndia Department of Medical Oncology Aster Medcity HospitalKochi 682034India

BACKGROUND Multitudinous advancements have been made to the traditional microfracture(MFx)technique,which have involved delivery of various acellular 2nd generation MFx and cellular MFx-III components to the area of cartilage *** relative benefits and pitfalls of these diverse modifications of MFx technique are still not widely *** To comparatively analyze the functional,radiological,and histological outcomes,and complications of various generations of MFx available for the treatment of cartilage *** A systematic review was performed using PubMed,EMBASE,Web of Science,Cochrane,and *** of any age and sex with cartilage defects undergoing any form of MFx were considered for *** included only randomized controlled trials(RCTs)reporting functional,radiological,histological outcomes or complications of various generations of MFx for the management of cartilage *** meta-analysis(NMA)was conducted in Stata and Cochrane’s Confidence in NMA approach was utilized for appraisal of *** Forty-four RCTs were included in the analysis with patients of mean age of 39.40(±9.46)*** comparing the results of the other generations with MFX-I as a constant comparator,we noted a trend towards better pain control and functional outcome(KOOS,IKDC,and Cincinnati scores)at the end of 1-,2-,and 5-year time points with MFx-III,although the differences were not statistically significant(P>0.05).We also noted statistically significant Magnetic resonance observation of cartilage repair tissue score in the higher generations of microfracture(weighted mean difference:17.44,95%confidence interval:0.72,34.16,P=0.025;without significant heterogeneity)at 1 ***,the difference was not maintained at 2 *** was a trend towards better defect filling on MRI with the second and third generation MFx,although the difference was not statistically significant(P>0.05).CONCLUSION The higher generations of traditional MFx

关键词： Cartilage injury Microfracture Mesenchymal stem cells Platelet-rich plasma Bone marrow aspiration concentrates Clinical outcome Radiological outcome Meta-analysis Network meta-analysis

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Communication-less Management Strategy for Electric Vehicle Charging in Droop-controlled Islanded Microgrids

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Journal of Modern Power Systems and Clean Energy 2024年第4期12卷 1227-1238页

作者： Abdullah Azhar Al-Obaidi mohammed Zaki El-Sharafy Hany E.Z.Farag Saifullah Shafiq Ali Al-Awami Independent Electricity System Operator(IESO) MississaugaCanada Department of Electrical Engineering and Computer Science York UniversityTorontoCanada University of Queensland StLucia QLD 4067Australia Department of Electrical Engineering King Fahd University of Petroleum&MineralsDhahranSaudi Arabia

Adopting high penetration levels of electric vehicles(EVs)necessitates the implementation of appropriate charging management systems to mitigate their negative impacts on pow-er distribution ***,most of the proposed Ev charging management techniques rely on the availability of high-bandwidth communication *** techniques are far from realization due to①the lack of utility-grade communica-tion systems in many cases such as secondary(low-voltage)pow-er distribution systems to which EVs are connected,rural ar-eas,remote communities,and islands,and②existing fears and concerns about the data privacy of EV users and cyber-physical *** these cases,appropriate local control schemes are needed to ensure the adequate management of EV charging without violating the grid operation ***,this paper introduces a new communication-less management strategy for EV charging in droop-controlled islanded *** proposed strategy is autonomous,as it is based on the measurement of system frequency and local bus *** proposed strategy implements a social charging fairness policy during periods when the microgrid distributed genera-tors(DGs)are in short supply by allocating more system capaci-ty to the EVs with less charging in the ***,a novel communication-less EV load shedding scheme is incorpo-rated into the management strategy to provide relief to the mi-crogrid during events of severe undervoltage or underfrequency occurrences due to factors such as high loading or DG *** simulations demonstrate the superiority of the pro-posed strategy over the state-of-the-art controllers in modulat-ing the EV charging demand to counteract microgrid instability.

关键词： Charging battery management communication-less control droop control electric vehicle islanded microgrid

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Posture Detection of Heart Disease Using Multi-Head Attention Vision Hybrid(MHAVH)Model

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Computers, Materials & Continua 2024年第5期79卷 2673-2696页

作者： Hina Naz Zuping Zhang mohammed Al-Habib Fuad A.Awwad Emad A.A.Ismail Zaid Ali Khan School of Computer Science and Engineering Central South UniversityChangsha410003China Department of Quantitative analysis College of Business AdministrationKing Saud UniversityP.O.Box 71115Riyadh11587Saudi Arabia Electrical and Computer Engineering University of VictoriaVictoriaV9A1B8Canada

Cardiovascular disease is the leading cause of death *** disease causes loss of heart muscles and is also responsible for the death of heart cells,sometimes damaging their functionality.A person’s life may depend on receiving timely assistance as soon as ***,minimizing the death ratio can be achieved by early detection of heart attack(HA)*** the United States alone,an estimated 610,000 people die fromheart attacks each year,accounting for one in every four ***,by identifying and reporting heart attack symptoms early on,it is possible to reduce damage and save many lives *** objective is to devise an algorithm aimed at helping individuals,particularly elderly individuals living independently,to safeguard their *** address these challenges,we employ deep learning *** have utilized a vision transformer(ViT)to address this ***,it has a significant overhead cost due to its memory consumption and computational complexity because of scaling dot-product ***,since transformer performance typically relies on large-scale or adequate data,adapting ViT for smaller datasets is more *** response,we propose a three-in-one steam model,theMulti-Head Attention Vision Hybrid(MHAVH).Thismodel integrates a real-time posture recognition framework to identify chest pain postures indicative of heart attacks using transfer learning techniques,such as ResNet-50 and VGG-16,renowned for their robust feature extraction *** incorporatingmultiple heads into the vision transformer to generate additional metrics and enhance heart-detection capabilities,we leverage a 2019 posture-based dataset comprising RGB images,a novel creation by the author that marks the first dataset tailored for posture-based heart attack *** the limited online data availability,we segmented this dataset into gender categories(male and female)and conducted testing on both segmented and original dat

关键词： Image analysis posture of heart attack(PHA)detection hybrid features VGG-16 ResNet-50 vision transformer advance multi-head attention layer

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Mechanical performance of cold mix asphalt containing cup lump rubber as a sustainable bio-modifier

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Journal of Traffic and Transportation Engineering(English Edition) 2024年第3期11卷 424-440页

作者： Syed Abdul Ghafar Muhammad Naqiuddin Mohd Warid Norhidayah Abdul Hassan Zulfiqar Ali Jattak Ashraf Abdalla mohammed Radwan Faculty of Civil Engineering Universiti Teknologi MalaysiaSkudai 81310Malaysia Department of Civil Engineering Balochistan University of Information TechnologyEngineering&Management SciencesQuettaPakistan Department of Civil Engineering Balochistan University of Engineering and TechnologyKhuzdarPakistan Department of Civil Engineering Faculty of EngineeringUniversity of TripoliTripoliLibya

The road construction industry aims to contribute to the protection of already compromised *** mix asphalt(CMA)is a measure initiated by the road industry to protect the environment and preserve *** having additional benefits,CMA has attracted little attention due to its inferior ***'s performance is enhanced using a sustainable binder bio-modifier,natural cup lump rubber(CLR)is one of *** study evaluated the tensile properties,rutting,moisture susceptibility,and adhesion properties of CLR-modified CMA(CMA-CR).The tensile property was enhanced by 26%due to CLR ***-CR had excellent rutting resistance of less than 2 mm rut depth at 10,000 load cycles,showing 70%improvement compared with conventional *** susceptibility evaluation indicated that CMA-CR had tensile strength ratio(TSR)value of 104%,satisfying the minimum 80%requirement of AASHTO *** also retained more than 96%bitumen *** moisture damage resistance was improved by 12%and 10%in terms of TSR and stripping,*** durability results revealed that the CMA-CR mixture prevented higher mass loss,representing 14%improvement compared with conventional CMA.

关键词： Cup lump rubber Cup lump modified cold mix asphalt Moisture damage Tensile property Rutting Digital imaging

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Fine-Tuning Cyber Security Defenses: Evaluating Supervised Machine Learning Classifiers for Windows Malware Detection

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Computers, Materials & Continua 2024年第8期80卷 2917-2939页

作者： Islam Zada mohammed Naif Alatawi Syed Muhammad Saqlain Abdullah Alshahrani Adel Alshamran Kanwal Imran Hessa Alfraihi Department of Software Engineering International Islamic UniversityIslamabad25000Pakistan Information Technology Department Faculty of Computers and Information TechnologyUniversity of TabukTabuk71491Saudi Arabia Department of Computer Science and Artificial Intelligence College of Computer Science and EngineeringUniversity of JeddahJeddah21493Saudi Arabia Department of Cybersecurity College of Computer Science and EngineeringUniversity of JeddahJeddah21493Saudi Arabia Department of Computer Science University of PeshawarPeshawar25121Pakistan Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia

Malware attacks on Windows machines pose significant cybersecurity threats,necessitating effective detection and prevention *** machine learning classifiers have emerged as promising tools for malware ***,there remains a need for comprehensive studies that compare the performance of different classifiers specifically for Windows malware *** this gap can provide valuable insights for enhancing cybersecurity *** numerous studies have explored malware detection using machine learning techniques,there is a lack of systematic comparison of supervised classifiers for Windows malware *** the relative effectiveness of these classifiers can inform the selection of optimal detection methods and improve overall security *** study aims to bridge the research gap by conducting a comparative analysis of supervised machine learning classifiers for detecting malware on Windows *** objectives include Investigating the performance of various classifiers,such as Gaussian Naïve Bayes,K Nearest Neighbors(KNN),Stochastic Gradient Descent Classifier(SGDC),and Decision Tree,in detecting Windows *** the accuracy,efficiency,and suitability of each classifier for real-world malware detection *** the strengths and limitations of different classifiers to provide insights for cybersecurity practitioners and *** recommendations for selecting the most effective classifier for Windows malware detection based on empirical *** study employs a structured methodology consisting of several phases:exploratory data analysis,data preprocessing,model training,and *** data analysis involves understanding the dataset’s characteristics and identifying preprocessing *** preprocessing includes cleaning,feature encoding,dimensionality reduction,and optimization to prepare the data for *** training utilizes various

关键词： Security and privacy challenges in the context of requirements engineering supervisedmachine learning malware detection windows systems comparative analysis Gaussian Naive Bayes K Nearest Neighbors Stochastic Gradient Descent Classifier Decision Tree

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