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Isolated lateral leg compartment syndrome:A case report

World Journal of Orthopedics 2023年第7期14卷 582-588页

作者： Majd M Alrayes Mohammad Alqudah walaa bani hamad Mohamed Sukeik Department of Trauma and Orthopedics Dammam Medical ComplexDammam 32210Saudi Arabia Department of Trauma and Orthopaedics Dr.Sulaiman Al-Habib HospitalKhobar 34423Saudi Arabia Department of Radiology Dr.Sulaiman Al-Habib HospitalKhobar 34423Saudi Arabia

BACKGROUND Acute leg compartment syndrome is a well-known orthopedic emergency associated with potentially devastating consequences if not treated *** compartments are usually involved with a clear history of trauma and classic symptoms and ***,isolated lateral leg compartment syndrome is relatively rare and is often misdiagnosed due to the atypical presentation of no trauma and the lack of pathognomonic *** SUMMARY A 31-year-old male patient presented to our emergency room with excruciating left calf pain and inability to mobilize one-day after participating in a football match despite no clear history of preceding *** patient went to another hospital before presenting to us where he was diagnosed to have a soft tissue injury and was discharged home on simple *** clinical examination,the left leg showed a tense lateral compartment with severe *** pain was aggravated by dorsiflexion and ankle *** examination of the limb was *** suspected a compartment syndrome but as the presentation was atypical and an magnetic resonance imaging(MRI)was readily available in our institution,we immediately performed an MRI and this confirmed a large hematoma in the lateral compartment with a possible partial proximal peroneus longus muscle *** patient was taken immediately for an emergency open *** patient is now 18 mo postoperatively having recovered completely and engages fully in sports with no *** Atypical presentation due to the lack of pathognomonic signs makes the diagnosis of isolated lateral leg compartment syndrome *** on passive inversion and dorsiflexion and weak active eversion may be suggested as sensitive signs.

关键词： Isolated Lateral compartment Peroneal compartment Atraumatic compartment syndrome Case report

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

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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

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

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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

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Fibrolamellar hepatocellular carcinoma:A rare but unpleasant event

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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

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

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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

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Hepatocellular carcinoma recurrence:Predictors and management

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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

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

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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

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Arabic Fake News Detection Using Deep Learning

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Computers, Materials & Continua 2022年第5期71卷 3647-3665页

作者： Khaled M.Fouad Sahar F.Sabbeh walaa Medhat Faculty of Computers&Artificial Intelligence Benha UniversityEgypt University of Jeddah College of Computer Science and EngineeringJeddah21493Saudi Arabia Information Technology and Computer Science Nile UniversityEgypt

Nowadays,an unprecedented number of users interact through social media platforms and generate a massive amount of content due to the explosion of online ***,because user-generated content is unregulated,it may contain offensive content such as fake news,insults,and harassment *** identification of fake news and rumors and their dissemination on social media has become a critical *** have adverse effects on users,businesses,enterprises,and even political regimes and *** of the art has tackled the English language for news and used feature-based *** paper proposes a model architecture to detect fake news in the Arabic language by using only textual *** learning and deep learning algorithms were *** deep learning models are used depending on conventional neural nets(CNN),long short-term memory(LSTM),bidirectional LSTM(BiLSTM),CNN+LSTM,and CNN+*** datasets were used in the experiments,each containing the textual content of Arabic news articles;one of them is reallife *** results indicate that the BiLSTM model outperforms the other models regarding accuracy rate when both simple data split and recursive training modes are used in the training process.

关键词： Fake news detection deep learning machine learning natural language processing

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Effect of Mechanical Vibrations on Human Body

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World Journal of Mechanics 2016年第9期6卷 273-304页

作者： Mohammad AlShabi walaa Araydah Hani ElShatarat Mohammad Othman Mohammed bani Younis Stephen Andrew Gadsden Mechanical Engineering Department University of Sharjah Sharjah United Arab Emirates Department of Mechatronics Engineering Philadelphia University Philadelphia PA USA Department of Mechanical Engineering Jordan University of Science and Technology Al Ramtha Jordan Department of Computer Engineering Philadelphia University Philadelphia PA USA School of Engineering University of Guelph Guelph Ontario Canada

Mechanical vibrations cause forces that affect human bodies. One of the most common positions for human bodies is the seated position. In this work, mathematical models of the seated human body are investigated and simulated in a Simulink/ MATLAB environment. In addition, segments of the human body are studied and models are developed and built by using Simulink/MATLAB. As part of this work, model analysis and state-space methods are used in order to check and validate the results obtained from the simulations. Two types of forces are used to test the whole seated human body under low frequency citation. The first is a sinusoidal wave signal based on literature, and the second is an impulse function. The effects of mechanical vibration on the head and lumbar are studied as these parts of the human body are usually the most effected areas. Kinematic states of the head segment and lumbar are considered. The characteristics of the vibration response on the two segments are also obtained. In addition to the me-chanical vibrations study, this paper is a resource for the development and implementation of models in the Simulink/MATLAB environment.

关键词： Vibration Human Body MATLAB State-Space

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

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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

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