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Obstetric Anesthesia Practice significantly Evolved: A Field for Cesarean Delivery Parturient for the Provision of safe Anesthesia in Urgent Circumstances

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Open Journal of Anesthesiology 2024年第3期14卷 66-92页

作者： Mustafa Zakaria amal Haoudar said Makani Mariame Kabbour Oumaima Taoussi Karim Elaidaoui Yousra Rajaa Chafik El Kettani Adil Elghanmi Department of Anesthesia and Resuscitation Hospital ZNA Middelheim Antwerpen Belgium European Society of Anaesthesiology and Intensive Care Ghent Belgium Anesthesia and Resuscitation Services Mohammed VI University of Sciences and Health-UM6SS Casablanca Morocco Cardiologist Vascular surgery Mohammed VI University of Sciences and Health-UM6SS Casablanca Morocco Faculty of science and Technology Hassan II University of Casablanca Casablanca Morocco Departement of services Cardiology Mohammed VI University of Sciences and Health-UM6SS Casablanca Morocco Department of Anesthesia and Resuscitation Mohammed VI University of Sciences and Health-UM6SS Casablanca Morocco Obstetrics and Gynecology services Mohammed VI University of Sciences and Health-UM6SS Casablanca Morocco

General anesthesia and Obstetric Anesthesia is the gold standard for a cesarean section but there are some cases where general anesthesia is unavoidable. The use of general anesthesia for cesarean delivery has decreased in recent years due to the widespread use of neuraxial techniques. The choice of anesthesia techniques for cesarean delivery depends on several factors, including the patient’s psychology and the attending physician’s experience. It is chosen because of its safety profile and its benefits to the mother and fetus. It may be indicated due to emergency, maternal refusal of regional techniques, or regional contraindications. Major complications include failed intubation, gastric content aspiration, and increased bleeding risk. This study aims to evaluate the impact of a newly launched team on obstetric anesthesia practice.

关键词： General Anesthesia Cesarean Delivery Intubation Maternal Refusal Obstetric Anesthetists

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Hyperparameter Tuned Deep Learning Enabled Intrusion Detection on Internet of Everything Environment

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Computers, Materials & Continua 2022年第12期73卷 6579-6594页

作者： Manar Ahmed Hamza Aisha hassan Abdalla Hashim Heba G.Mohamed saud s.Alotaibi Hany Mahgoub amal s.Mehanna Abdelwahed Motwakel Department of Electrical and Computer Engineering International Islamic University MalaysiaKuala Lumpur53100Malaysia Department of Computer and self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Department of Electrical Engineering College of EngineeringPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Information systems College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Computer science College of Science&Art at MahayilKing Khalid UniversitySaudi Arabia Faculty of Computers and Information Computer Science DepartmentMenoufia UniversityEgypt Department of Digital Media Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11845Egypt

Internet of Everything(IoE),the recent technological advancement,represents an interconnected network of people,processes,data,and *** recent times,IoE gained significant attention among entrepreneurs,individuals,and communities owing to its realization of intense values from the connected *** the other hand,the massive increase in data generation from IoE applications enables the transmission of big data,from contextawaremachines,into useful *** and privacy pose serious challenges in designing IoE environment which can be addressed by developing effective Intrusion Detection systems(IDs).In this background,the current study develops Intelligent Multiverse Optimization with Deep Learning Enabled Intrusion Detection system(IMVO-DLIDs)for IoT *** presented IMVO-DLIDs model focuses on identification and classification of intrusions in IoT *** proposed IMVO-DLIDs model follows a three-stage *** first,data pre-processing is performed to convert the actual data into useful *** addition,Chaotic Local search Whale Optimization Algorithm-based Feature selection(CLsWOA-Fs)technique is employed to choose the optimal feature ***,MVO algorithm is exploited with Bidirectional Gated Recurrent Unit(BiGRU)model for ***,the novelty of the work is the application of MVO algorithm in fine-turning the hyperparameters involved in BiGRU *** experimental validation was conducted for the proposed IMVO-DLIDs model on benchmark datasets and the results were assessed under distinct *** extensive comparative study was conducted and the results confirmed the promising outcomes of IMVO-DLIDs approach compared to other approaches.

关键词： Internet of everything deep learning feature selection classification intrusion detection cybersecurity

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Open charm mesons and charmonia in magnetized strange hadronic matter

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Chinese Physics C 2022年第8期46卷 91-113页

作者： amal Jahan C.s. Amruta Mishra Department of Physics Indian Institute of TechnologyNew Delhi-110016India

We investigate the in-medium masses of open charm mesons(D(D^(0),D^(+)),■(■^(0),D^(-)),D_(s)(D_(s)^(+),D_(s)^(-)))and charmonium states(J/ψ,ψ(3686),ψ(3770),χ_(c0),χ_(c2)) in strongly magnetized isospin asymmetric strange hadronic matter using a chiral effective *** the presence of a magnetic field,the number and scalar densities of charged baryons have contributions from Landau energy *** mass modifications of open charm mesons result from their interactions with nucleons,hyperons,and the scalar fields(the non-strange field σ,strange field C and isovector field δ) in the presence of a magnetic *** mass modifications of the charmonium states result from the modification of gluon condensates in a medium simulated by the variation in the dilaton field(χ) in the chiral effective *** effects of finite quark masses are also incorporated in the trace of the energy-momentum tensor in quantum chromodynamics to investigate the mass shifts of charmonium *** in-medium masses of open charm mesons and charmonia are observed to decrease with an increase in baryon *** charged D^(+),D^(-),Z_(s)^(+),and D_(s)^(-)mesons have additional positive mass shifts due to Landau quantization in the presence of a magnetic *** effects of the strangeness fraction are observed to be more dominant for ■ mesons compared with D *** mass shifts of charmonia are observed to be larger in hyperonic media compared with nuclear media when the effect of the finite quark mass term is *** medium mass modifications can have observable consequences on the production of the open charm mesons and charmonia in high-energy asymmetric heavy-ion collision experiments.

关键词： open charm mesons charmonium states strange hadronic matter magnetic field heavy-ion collision chiral effective model

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Cytokine profile in Egyptian hepatitis C virus genotype-4 in relation to liver disease progression

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World Journal of Gastroenterology 2005年第42期11卷 6624-6630页

作者： Abdel-Rahman N Zekri Mohammed s El-Din Ashour Ahmed hassan Hanaa M Alam El-Din amal MR El-shehaby Maha A Abu-shady Virology and Immunology Unit Cancer Biology Department National Cancer Institute Cairo University Egypt Microbiology Department Faculty of Pharmacy Azhar University Egypt Microbiology and Immunology Department sohag Faculty of Medicine South Valley University Egypt Virology and Immunology Unit Cancer Biology Department National Cancer Institute Cairo University Egypt Biochemistry Department El-Kaser El-Aini school of Medicine Cairo University Egypt

AIM： To observe the imbalance between T helper cell Th1 and Th2 cytokines in several chronic hepatitis disease at different stages of disease progression. METHODs： We measured the cytokine levels of Thl （IL-2 and IL-2R）, Th2 （IL-10） and the pro-inflammatory cytokines （IL-6 and IL-6R and TNF and TNF-RI and II） by the ELIsA technique in the sera of 33 hepatocellular carcinoma （HCC） patients and 20 chronic liver disease （CLD） patients. In addition, 20 asymptomatic hepatitis C virus carriers and 20 healthy subjects negative for hepatitis C virus（HCV） markers served as controls. REsULTs： Anti-HCV antibodies were found to be positive in 94% of HCC cases and 75% of CLD cases. On the other hand, HCV viremia was detected using RT- PCR in 67% of HCC cases and 65% of CLD cases. HBsAg was positive in 9% of HCC cases and 30% of CLD cases. Also bilharziaI-Ab was positive in 55% of HCC cases, 65% of CLD cases and in 70% of asymptomatic carriers （AsC）. HCC patients had significantly higher values of IL- 2R, TNF-RII （P〈0.001）, and TNF-RI （P〉0.05）, but lower TNFα （P〈0.001） and IL-6 （P = 0.032） in comparison to AsC. But, in comparison to non-cancer controls, HCC patients had higher values of IL-2R, IL-6R, TNF-RI and TNF-RII, but lower TNF-α （P〈0.001）. CLD patients had higher IL-2R, TNF-RI, and TNF-RII （P〈0.001） than AsC. But, in comparison to non-cancer controls, CLD patients had higher values of IL-2R, TNF-RI and TNF-RII, but lower TNF-α （P〈0.001）. IL-10 was higher （though not significantly） in HCC and CLD patients than in symptomatic carriers and non-cancer controls. CONCLUsION： Liver disease progression from CLD to HCC due to HCV genotype-4 infection is associated with an imbalance between Th1 and Th2 cytokines. IL-2R, TNF-RI, and TNF-RII could be used as potential markers.

关键词： Cytokine HCV Genotype-4 Liver disease

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Educational Videos subtitles’summarization Using Latent Dirichlet Allocation and Length Enhancement

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Computers, Materials & Continua 2022年第3期70卷 6205-6221页

作者： sarah s.Alrumiah amal A.Al-shargabi Department of Information Technology College of ComputerQassim UniversityBuraydah51452Saudi Arabia

Nowadays,people use online resources such as educational videos and ***,such videos and courses are mostly long and thus,summarizing them will be *** video contents(visual,audio,and subtitles)could be analyzed to generate textual summaries,i.e.,***’subtitles contain significant ***,summarizing subtitles is effective to concentrate on the necessary *** of the existing studies used Term Frequency-Inverse Document Frequency(TF-IDF)and Latent semantic Analysis(LsA)models to create lectures’*** study takes another approach and applies LatentDirichlet Allocation(LDA),which proved its effectiveness in document ***,the proposed LDA summarization model follows three *** first phase aims to prepare the subtitle file for modelling by performing some preprocessing steps,such as removing stop *** the second phase,the LDA model is trained on subtitles to generate the keywords list used to extract important *** in the third phase,a summary is generated based on the keywords *** generated summaries by LDA were lengthy;thus,a length enhancement method has been *** the evaluation,the authors developed manual summaries of the existing“EDUVsUM”educational videos *** authors compared the generated summaries with the manual-generated outlines using two methods,(i)Recall-Oriented Understudy for Gisting Evaluation(ROUGE)and(ii)human *** performance of LDA-based generated summaries outperforms the summaries generated by TF-IDF and *** reducing the summaries’length,the proposed length enhancement method did improve the summaries’precision *** domains,such as news videos,can apply the proposed method for video summarization.

关键词： subtitle summarization educational videos topic modelling LDA extractive summarization

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sine Cosine Optimization with Deep Learning-Based Applied Linguistics for sentiment Analysis on COVID-19 Tweets

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Computers, Materials & Continua 2023年第6期75卷 4767-4783页

作者： Abdelwahed Motwakel Hala J.Alshahrani Abdulkhaleq Q.A.hassan Khaled Tarmissi amal s.Mehanna Ishfaq Yaseen Amgad Atta Abdelmageed Mohammad Mahzari Department of Computer and self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Department of Applied Linguistics College of LanguagesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of English College of Science and Arts at MahayilKing Khalid UniversityMuhayil63763Saudi Arabia Department of Computer sciences College of Computing and Information SystemUmm Al-Qura UniversityMakkah24211Saudi Arabia Department of Digital Media Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11845Egypt Department of English College of Science&HumanitiesPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Applied linguistics is an interdisciplinary domain which identifies,investigates,and offers solutions to language-related real-life *** new coronavirus disease,otherwise known as Coronavirus disease(COVID-19),has severely affected the everyday life of people all over the ***,since there is insufficient access to vaccines and no straight or reliable treatment for coronavirus infection,the country has initiated the appropriate preventive measures(like lockdown,physical separation,and masking)for combating this extremely transmittable ***,individuals spent more time on online social media platforms(i.e.,Twitter,Facebook,Instagram,LinkedIn,and Reddit)and expressed their thoughts and feelings about coronavirus *** has become one of the popular social media platforms and allows anyone to post *** study proposes a sine cosine optimization with bidirectional gated recurrent unit-based senti-ment analysis(sCOBGRU-sA)on COVID-19 *** sCOBGRU-sA technique aimed to detect and classify the various sentiments in Twitter data during the COVID-19 *** sCOBGRU-sA technique follows data pre-processing and the Fast-Text word embedding process to accomplish ***,the BGRU model is utilized to recognise and classify sen-timents present in the ***,the sCO algorithm is exploited for tuning the BGRU method’s hyperparameter,which helps attain improved classification *** experimental validation of the sCOBGRU-sA technique takes place using a benchmark dataset,and the results signify its promising performance compared to other DL models.

关键词： Applied linguistics deep learning sentiment analysis COVID-19 pandemic sine cosine optimization twitter

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Hunter Prey Optimization with Hybrid Deep Learning for Fake News Detection on Arabic Corpus

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Computers, Materials & Continua 2023年第5期75卷 4255-4272页

作者： Hala J.Alshahrani Abdulkhaleq Q.A.hassan Khaled Tarmissi amal s.Mehanna Abdelwahed Motwakel Ishfaq Yaseen Amgad Atta Abdelmageed Mohamed I.Eldesouki Department of Applied Linguistics College of LanguagesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of English College of Science and Arts at MahayilKing Khalid UniversityMuhayil63763Saudi Arabia Department of Computer sciences College of Computing and Information SystemUmm Al-Qura UniversityMakkah24211Saudi Arabia Department of Digital Media Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11845Egypt Department of Computer and self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Department of Information system College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Nowadays,the usage of socialmedia platforms is rapidly increasing,and rumours or false information are also rising,especially among Arab *** false information is harmful to society and *** and detecting the spread of fake news in Arabic becomes *** artificial intelligence(AI)methods,including contemporary transformer techniques,BERT,were used to detect fake ***,fake news in Arabic is identified by utilizing AI *** article develops a new hunterprey optimization with hybrid deep learning-based fake news detection(HPOHDL-FND)model on the Arabic *** HPOHDL-FND technique undergoes extensive data pre-processing steps to transform the input data into a useful ***,the HPOHDL-FND technique utilizes long-term memory with a recurrent neural network(LsTM-RNN)model for fake news detection and ***,hunter prey optimization(HPO)algorithm is exploited for optimal modification of the hyperparameters related to the LsTM-RNN *** performance validation of the HPOHDL-FND technique is tested using two Arabic *** outcomes exemplified better performance over the other existing techniques with maximum accuracy of 96.57%and 93.53%on Covid19Fakes and satirical datasets,respectively.

关键词： Arabic corpus fake news detection deep learning hunter prey optimizer classification model

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Decomposition of biomass gasification tar model compounds over waste tire pyrolysis char

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Waste Disposal and sustainable Energy 2022年第2期4卷 75-89页

作者： amal s.Al-Rahbi Paul T.Williams Present address:Applied sciences Department Higher College of TechnologyUniversity of Technology and Applied SciencesMuscatSultanate of Oman school of Chemical and Process Engineering University of LeedsLeedsLS29JTUK

Gasification of biomass produces a syngas containing trace amounts of viscous hydrocarbon tar,which causes serious problems in downstream pipelines,valves and processing *** study focuses on the use of tire-derived pyrolysis char for tar conversion using biomass tar model compounds representative of *** catalytic decomposition of tar model compounds,including methylnaphthalene,furfural,phenol,and toluene,over tire char was investigated using a fixed bed reactor at a bed temperature of 700℃and 60 min time on *** influence of temperature,reaction time,porous texture,and acidity of the tire char was investigated with the use of methylnaphthalene as the tar model *** tar model compounds were found to have higher conversion than those containing a single or multi-aromatic *** reactivity of tar compounds followed the order of furfural>phenol>toluene>*** conversion of the model compounds in the presence of the tire char was much higher than tar thermal *** production increased dramatically with the introduction of tire *** H_(2)potential for the studied tar model compounds was found to be in the range of 40%–50%.The activity of tire char for naphthalene removal was compared with two commercial activated carbons possessing a very well-developed porous *** results suggest that the influence of Brunauer-Emmett-Teller surface area of the carbon on tar cracking is negligible compared with the mineral content in the carbon samples.

关键词： Biomass Gasification syngas Tar Tire Char

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Computerized Detection of Limbal stem Cell Deficiency from Digital Cornea Images

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Computer systems science & Engineering 2022年第2期40卷 805-821页

作者： Hanan A.Hosni Mahmoud Doaa s.Khafga amal H.Alharbi Department of Computer sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11047KSA

Limbal stem Cell Deficiency(LsCD)is an eye disease that can cause corneal opacity and *** its advanced stage it can lead to a degree of visual *** involves the changing in the semispherical shape of the cornea to a drooping shape to downwards *** is hard to be diagnosed at early *** color and texture of the cornea surface can provide significant information about the cornea affected by *** such as shape and texture are very crucial to differentiate normal from LsCD *** several medical approaches exist,most of them requires complicated procedure and medical ***,in this paper,we pursued the development of a LsCD detection technique(LDT)utilizing image processing *** diagnosis of LsCD is very crucial for physicians to arrange for effective *** the proposed technique,we developed a method for LsCD detection utilizing frontal eye images.A dataset of 280 eye images of frontal and lateral LsCD and normal patients were used in this ***,the cornea region of both frontal and lateral images is segmented,and the geometric features are extracted through the automated active contour model and the spline *** the texture features are extracted using the feature selection *** experimental results exhibited that the combined features of the geometric and texture will exhibit accuracy of 95.95%,sensitivity of 97.91% and specificity of 94.05% with the random forest classifier of n=*** a result,this research developed a Limbal stem cell deficiency detection system utilizing features’fusion using image processing techniques for frontal and lateral digital images of the eyes.

关键词： Feature extraction corneal opacity geometric features computerized detection image processing

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A highly concentrated vanadium protic ionic liquid electrolyte for the vanadium redox flow battery

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Journal of Energy Chemistry 2021年第6期30卷 238-246,I0007页

作者： Georgios Nikiforidis amal Belhcen Mérièm Anouti Laboratoire PCM2E Universitéde ToursParc de Grandmont37200 ToursFrance LE sTUDIUM Institute for Advanced studies 45000 OrléansFrance

A protic ionic liquid is designed and implemented for the first time as a solvent for a high energy density vanadium redox flow *** being less conductive than standa rd aqueous electrolytes,it is thermally stable on a 100 ℃ temperature window,chemically stable for at least 60 days,equally viscous and dense with typical aqueous solvents and most importantly able to solubilize to 6 mol L^(-1) vanadium sulfate,thus increasing the VRFB energy density by a factor of *** measurements revealed quasi-reversible redox transitions for both catholyte and anolyte at 25 ℃ while a proof-of-concept redox flow cell with the proposed electrolyte was tested for a total of 150 cycles at 25 ℃,showing an open circuit potential of 1.39 V and energy and coulombic efficiencies of 65% and 93%,***’s more,the battery can be equally cycled at 45℃ showing good thermal *** study underlines a new route to improve the energy-to-volume ratio of energy storage system.

关键词： Protic ionic liquids Redox flow battery Electrolyte High energy density

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