检索结果-南通市图书馆

Hepatitis B virus as a risk factor for hepatocellular carcinoma: There is still much work to do

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Assessment of the Characteristics of the Municipal Solid Waste Compost in Lebanon

Liver Research 2024年第2期8卷 83-90页

作者： walaa Abdelhamed Mohamed El-Kassas Endemic Medicine Department Sohag University Sohag Egypt Endemic Medicine Department Faculty of Medicine Helwan University Cairo Egypt Liver Disease Research Center College of Medicine King Saud University Riyadh Saudi Arabia

Hepatitis B virus (HBV) infection is a significant health problem that can result in progression to liver cirrhosis, decompensation, and the development of hepatocellular carcinoma (HCC). On a country level, the prevalence of chronic HBV infection varies between 0.1% and 35.0%, depending on the locality and the population being investigated. One-third of all liver cancer fatalities worldwide are attributable to HBV. The adoption of standard birth-dose immunization exerted the most significant impact on the decline of HBV prevalence. HCC incidence ranges from 0.01% to 1.40% in noncirrhotic patients and from 0.9% to 5.4% annually, in the settings of liver cirrhosis. Although antiviral therapy significantly reduces the risk of developing HBV-related HCC, studies have demonstrated that the risk persists, and that HCC screening is still essential. This review discusses the complex relationship between HBV infection and HCC, recent epidemiological data, different aspects of clinical disease characteristics, and the impact of antiviral therapy in this context.

关键词： Hepatitis B virus (HBV) Hepatocellular carcinoma (HCC) HBV vaccine Carcinogenesis Antiviral therapy

来源：评论

学校读者我要写书评

暂无评论

Journal of Geoscience and Environment Protection 2024年第5期12卷 17-39页

作者： Rana Sawaya Jalal Halwani Nada Nehme Hiba Alawiye walaa Diab Water & Environment Science Lab Lebanese University Tripoli Lebanon Faculty of Sciences Lebanese University Hadath Lebanon Faculty of Agriculture Engineering and Veterinary Sciences Lebanese University Dekwaneh Lebanon

Waste management is crucial due to the fast increase of human population, causing an increase in solid waste generation which if not properly managed causes environmental problems. Around 57% of the wastes generated from homes are made up of green material (fruits, vegetables…). Thus, reusing and recycling green wastes through composting is one way of reducing the waste load to landfills. Composting is the transformation of raw organic materials into organic soil amendments that provide nutrients to crops and enhance the tilth, fertility, and productivity of soils. Aerobic windrow composting system at Sukomi Greensite facility located at Karantina is performed, where materials biodegrade under controlled conditions to produce compost. However, assessment of the quality of the compost is fundamental in order to determine its usages. Thus, regular testing of physical, chemical and biological parameters was performed for adequate monitoring purposes. The basic objective of this study was to determine the characteristics of the Lebanese municipal solid waste compost on a yearly basis and compare these characteristics amongst the years. Hence, each parameter was tested and compared to the BNQ international Canadian standards for proper classification of the compost and adequate identification of its usages. The preliminary data obtained were statistically diagnosed through principal component analysis by Spadv55 software. All the data reflected the normal content value of the studied parameters with minor differences between the years except for year 2007 which demonstrated higher levels of Potassium, Phosphate, Lead and Cadmium. The characteristics of the compost enabled it to be used as a soil amendment on all types of agricultural and landscape commodities at the adequate dosages and proper timing. This data will additionally reflect the efficiency of the solid waste management practices adopted via highlighting the importance of the implementation of the integrated s

关键词： Composting Organic Material Lebanon Contamination Solid Waste Management

Fibrolamellar hepatocellular carcinoma:A rare but unpleasant event

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

World Journal of Gastrointestinal Oncology 2022年第6期14卷 1103-1114页

作者： walaa Abdelhamed Mohamed El-Kassas Department of Endemic Medicine Sohag UniversitySohag 14322Egypt Department of Endemic Medicine Faculty of MedicineHelwan UniversityCairo 11795Egypt

Fibrolamellar carcinoma(FLC)is a rare variant of hepatocellular carcinoma(HCC),comprising 1%–9%of all *** is a poorly understood malignancy,which seems to be more prevalent in young patients with no underlying liver *** term“fibrolamellar”is derived from thick fibrous collagen bands surrounding the tumor *** HCC,cirrhosis and viral hepatitis infection are not predisposing to FLC,and it is not associated with elevations in serum *** patients often present with vague abdominal pain,nausea,malaise,and weight *** cases present are at an advanced stage at the time of initial ***,curative treatment options can still be offered to up to 70%of ***(resection/liver transplantation)is the mainstay of treatment and the only potentially curative *** have been less chemoresponsive than the conventional HCC,however,in advanced cases,multimodality treatments can be *** advances in molecular studies of FLC have found a unique DNAJB1–PRKACA fusion transcript in most of the cases *** review aims to describe clinical characteristics,diagnostic methods,and therapeutic modalities for this rare tumor to raise awareness among clinicians and surgeons.

关键词： Fibrolamellar carcinoma Hepatocellular carcinoma Hepatitis Cirrhosis Viral hepatitis infection

GA-Stacking:A New Stacking-Based Ensemble Learning Method to Forecast the COVID-19 Outbreak

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2023年第2期74卷 3945-3976页

作者： walaa N.Ismail Hessah A.Alsalamah Ebtesam Mohamed Department of Management Information Systems College of Business AdministrationAl Yamamah UniversityRiyadh11512Saudi Arabia Faculty of Computers and Information Minia UniversityMinia61519Egypt Information Systems Department College of Computer and Information SciencesKing Saud UniversityRiyadh4545Saudi Arabia Computer Engineering Department College of Engineering and ArchitectureAl Yamamah UniversityRiyadh11512Saudi Arabia

As a result of the increased number of COVID-19 cases,Ensemble Machine Learning(EML)would be an effective tool for combatting this pandemic *** ensemble of classifiers can improve the performance of single machine learning(ML)classifiers,especially stacking-based ensemble *** utilizes heterogeneous-base learners trained in parallel and combines their predictions using a meta-model to determine the final prediction ***,building an ensemble often causes the model performance to decrease due to the increasing number of learners that are not being properly ***,the goal of this paper is to develop and evaluate a generic,data-independent predictive method using stacked-based ensemble learning(GA-Stacking)optimized by aGenetic Algorithm(GA)for outbreak prediction and health decision aided ***-Stacking utilizes five well-known classifiers,including Decision Tree(DT),Random Forest(RF),RIGID regression,Least Absolute Shrinkage and Selection Operator(LASSO),and eXtreme Gradient Boosting(XGBoost),at its first *** also introduces GA to identify comparisons to forecast the number,combination,and trust of these base classifiers based on theMean Squared Error(MSE)as a fitness *** the second level of the stacked ensemblemodel,a Linear Regression(LR)classifier is used to produce the final *** performance of the model was evaluated using a publicly available dataset from the Center for Systems Science and Engineering,Johns Hopkins University,which consisted of 10,722 data *** experimental results indicated that the GA-Stacking model achieved outstanding performance with an overall accuracy of 99.99%for the three selected ***,the proposed model achieved good performance when compared with existing baggingbased *** proposed model can be used to predict the pandemic outbreak correctly and may be applied as a generic data-independent model 3946 CMC,2023,vol.74,no.2 to pre

关键词： COVID-19 ensemble machine learning genetic algorithm machine learning stacking ensemble unbalanced dataset vaccine

Hepatocellular carcinoma recurrence:Predictors and management

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Liver Research 2023年第4期7卷 321-332页

作者： walaa Abdelhamed Mohamed El-Kassas Endemic Medicine Department Sohag UniversitySohagEgypt Endemic Medicine Department Faculty of MedicineHelwan UniversityCairoEgypt

Hepatocellular carcinoma(HCC),the sixth most common cancer globally,is associated with high mortality rates and more than 830,000 annual *** advances in the available management options including surgical resection and local ablative therapies,recurrence rates after the initial treatment exceed 50%,even among patients who have undergone curative-intent ***,postsurgical HCC recurrence occurs in about 70%of cases five years *** management of recurrent HCC remains *** review discusses different predictors for HCC recurrence after each treatment modality and different approaches available to stratify these *** specific guidelines for managing HCC recurrence and strict surveillance protocols for such recurrence after initial HCC management are needed.

关键词： Hepatocellular carcinoma(HCC) Recurrence Ablation Liver resection Liver transplantation

Hybrid Chaotic Salp Swarm with Crossover Algorithm for Underground Wireless Sensor Networks

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2022年第8期72卷 2963-2980页

作者： Mariem Ayedi walaa H.ElAshmawi Esraa Eldesouky First Department of Computer Science College of Computer Engineering and SciencesPrince Sattam Bin Abdulaziz UniversityAl-Kharj11942Saudi Arabia MEDIATRON Lab. SUP’COMCarthage UniversityTunis2083Tunisia Department of Computer Science Faculty of Computers and InformaticsSuez Canal UniversityIsmailia41522Egypt Faculty of Computer Science Misr International UniversityCairoEgypt

Resource management in Underground Wireless Sensor Networks(UWSNs)is one of the pillars to extend the network *** intriguing design goal for such networks is to achieve balanced energy and spectral resource *** paper focuses on optimizing the resource efficiency in UWSNs where underground relay nodes amplify and forward sensed data,received from the buried source nodes through a lossy soil medium,to the aboveground base station.A new algorithm called the Hybrid Chaotic Salp Swarm and Crossover(HCSSC)algorithm is proposed to obtain the optimal source and relay transmission powers to maximize the network resource *** proposed algorithm improves the standard Salp Swarm Algorithm(SSA)by considering a chaotic map to initialize the population along with performing the crossover technique in the position updates of *** experimental results,the HCSSC algorithm proves its outstanding superiority to the standard SSA for resource efficiency ***,the network’s lifetime is ***,the proposed algorithm achieves an improvement performance of 23.6%and 20.4%for the resource efficiency and average remaining relay battery per transmission,***,simulation results demonstrate that the HCSSC algorithm proves its efficacy in the case of both equal and different node battery capacities.

关键词： Underground wireless sensor networks resource efficiency chaotic theory crossover algorithm salp swarm algorithm

DLBT:Deep Learning-Based Transformer to Generate Pseudo-Code from Source Code

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2022年第2期70卷 3117-3132页

作者： walaa Gad Anas Alokla Waleed Nazih Mustafa Aref Abdel-badeeh Salem Faculty of Computers and Information Sciences Ain Shams UniversityAbassiaCairo11566Egypt College of Computer Engineering and Sciences Prince Sattam Bin Abdulaziz UniversityAl Kharj11942Saudi Arabia

Understanding the content of the source code and its regular expression is very difficult when they are written in an unfamiliar ***-code explains and describes the content of the code without using syntax or programming language ***,writing Pseudo-code to each code instruction is ***,neural machine translation is used to generate textual descriptions for the source *** this paper,a novel deep learning-based transformer(DLBT)model is proposed for automatic Pseudo-code generation from the source *** proposed model uses deep learning which is based on Neural Machine Translation(NMT)to work as a language *** DLBT is based on the transformer which is an encoder-decoder *** are three major components:tokenizer and embeddings,transformer,and *** code line is tokenized to dense *** transformer captures the relatedness between the source code and the matching Pseudo-code without the need of Recurrent Neural Network(RNN).At the post-processing step,the generated Pseudo-code is *** proposed model is assessed using a real Python dataset,which contains more than 18,800 lines of a source code written in *** experiments show promising performance results compared with other machine translation methods such as Recurrent Neural Network(RNN).The proposed DLBT records 47.32,68.49 accuracy and BLEU performance measures,respectively.

关键词： Natural language processing long short-term memory neural machine translation pseudo-code generation deep learning-based transformer

Fusion Strategy for Improving Medical Image Segmentation

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2023年第2期74卷 3627-3646页

作者： Fahad Alraddady E.A.Zanaty Aida HAbu bakr walaa M.Abd-Elhafiez Department of Computer Engineering College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Information System Department Faculty of Computers and InformationSohag UniversitySohagEgypt Mathematical and Computer Science Department Faculty of ScienceAswan UniversityAswanEgypt College of Computer Science&Information Technology Jazan UniversityJazanKingdom of Saudi Arabia Computer Science Department Faculty of Computers and Artificial IntelligenceSohag UniversitySohagEgypt

In this paper,we combine decision fusion methods with four metaheuristic algorithms(Particle Swarm Optimization(PSO)algorithm,Cuckoo search algorithm,modification of Cuckoo Search(CS McCulloch)algorithm and Genetic algorithm)in order to improve the image *** proposed technique based on fusing the data from Particle Swarm Optimization(PSO),Cuckoo search,modification of Cuckoo Search(CS McCulloch)and Genetic algorithms are obtained for improving magnetic resonance images(MRIs)*** algorithms are used to compute the accuracy of each method while the outputs are passed to fusion *** order to obtain parts of the points that determine similar membership values,we apply the different rules of incorporation for these *** proposed approach is applied to challenging applications:MRI images,gray matter/white matter of brain segmentations and original black/white images Behavior of the proposed algorithm is provided by applying to different medical *** is shown that the proposed method gives accurate results;due to the decision fusion produces the greatest improvement in classification accuracy.

关键词： Decision fusion particle swarmoptimization(PSO) cuckoo search algorithm CS McCulloch algorithm genetic algorithm CT and MRI

Characteristics and outcome of newborn admitted with acute bilirubin encephalopathy to a tertiary neonatal intensive care unit

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

World Journal of Pediatrics 2019年第1期15卷 42-48页

作者： Nahed Fahmy Helal Eman Abdel Ghany Abdel Ghany walaa Alsharany Abuelhamd Amna Yehea Ahmed Alradem Department of Pediatrics Faculty of MedicineCairo UniversityCairoEgypt Ministry of Health CairoEgypt

Background Acute bilirubin encephalopathy (ABE) still represents a significant cause of morbidity and mortality throughout the world,especially in developing *** aimed to determine the prevalence of ABE based on the Johnson bilirubininduced neurologic dysfunction (BIND) score and to describe the discharge *** We prospectively studied all newborns ≥ 35 weeks with ABE by evaluating signs of mental sensorium,muscle tone,and cry patterns over 1 *** 12% (81 out of 674) of the newborns admitted for neonatal hyperbilirubinemia had a BIND score > *** admission age was 6 ± 4.1 days;total serum bilirubin (TSB) was 31.2± 10 mg/dL (range 17.5-75.2).Of these newborns,40.7% and 21% had evidence of haemolysis and sepsis,*** mortality was 9.9%;58% of the newborns showed signs of mild-to-moderate BIND at discharge,while 32.1% survived with an apparently normal *** BIND score was significantly correlated with admission TSB (r=0.476,P < 0.001).Similarly,BIND score at discharge was correlated with admission TSB (r=0.442,P < 0.001) and admission BIND score (r =0.888,P < 0.001).The regression model showed that admission TSB (P < 0.001) and maternal illiteracy (P =0.034) were predictors of the BIND score at admission,while admission BIND score was the best indicator of the discharge score (P < 0.001).Conclusions ABE is still a major problem in our *** TSB and maternal illiteracy are good predictors of bilirubin encephalopathy at admission and discharge.

关键词： Bilirubin-induced neurologic dysfunction Bilirubin encephalopathy Kernicterus Neonatal hyperbilirubinemia