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Early detection of hepatocellular carcinoma co-occurring with hepatitis C virus infection: A mathematical model

World Journal of Gastroenterology 2016年第16期22卷 4168-4182页

作者： Abdel-Rahman Nabawy Zekri amira salah el-din youssef Yasser Mabrouk Bakr Reham Mohamed Gabr Ola Sayed Ahmed Mostafa Hamed elberry Ahmed Mahmoud Mayla Mohamed Abouelhoda Abeer A Bahnassy Molecular Virology and Immunology Unit Cancer Biology Department National Cancer Institute Cairo University Systems and Biomedical Engineering Department Faculty of Engineering Cairo University Center for Informatics Sciences Nile University Sheikh Zayed City Pathology Department National Cancer Institute Cairo University

AIM: To develop a mathematical model for the early detection of hepatocellular carcinoma (HCC) with a panel of serum proteins in combination with α-fetoprotein (AFP).METHODS: Serum levels of interleukin (IL)-8, soluble intercellular adhesion molecule-1 (sICAM-1), soluble tumor necrosis factor receptor II (sTNF-RII), proteasome, and β-catenin were measured in 479 subjects categorized into four groups: (1) HCC concurrent with hepatitis C virus (HCV) infection (n = 192); (2) HCV related liver cirrhosis (LC) (n = 96); (3) Chronic hepatitis C (CHC) (n = 96); and (4) Healthy controls (n = 95). The R package and different modules for binary and multi-class classifiers based on generalized linear models were used to model the data. Predictive power was used to evaluate the performance of the model. Receiver operating characteristic curve analysis over pairs of groups was used to identify the best cutoffs differentiating the different ***: We revealed mathematical models, based on a binary classifier, made up of a unique panel of serum proteins that improved the individual performance of AFP in discriminating HCC patients from patients with chronic liver disease either with or without cirrhosis. We discriminated the HCC group from the cirrhotic liver group using a mathematical model (-11.3 + 7.38 × Prot + 0.00108 × sICAM + 0.2574 × β-catenin + 0.01597 × AFP) with a cutoff of 0.6552, which achieved 98.8% specificity and 89.1% sensitivity. For the discrimination of the HCC group from the CHC group, we used a mathematical model [-10.40 + 1.416 × proteasome + 0.002024 × IL + 0.004096 × sICAM-1 + (4.251 × 10-4) × sTNF + 0.02567 × β-catenin + 0.02442 × AFP] with a cutoff 0.744 and achieved 96.8% specificity and 89.7% sensitivity. Additionally, we derived an algorithm, based on a binary classifier, for resolving the multi-class classification

关键词： Mathematical model Hepatocellular carcinoma α -fetoprotein Soluble intercellular adhesion molecule-1 β -catenin Interleukin-8 Soluble tumor necrosis factor receptor II Proteasome

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Natural Convection of a Power-Law Nanofluid in a Square Cavity with a Vertical Fin

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Fluid Dynamics & Materials Processing 2024年第9期20卷 2091-2108页

作者： amira M’hadbi Mohammed el Ganaoui Haïkel Ben Hamed Amenallah Guizani Khalid Chtaibi LERMAB Department of Transition and Energy Efficiency ProfessionsIUT H Poincaréde LongwyUniversity of LorraineLongwy54400France LPT Center for Energy Research and Technologies(Borj Cedria2084)University of Tunis El ManarTunis1068Tunisia LTI Department of Mechanical Engineering and ProductionIUTUniversity of Picardie Jules-VerneAmiens80025France

The behavior of non-Newtonian power-law nanofluids under free convection heat transfer conditions in a cooled square enclosure equipped with a heated fin is investigated *** particular,the impact of nanofluids,composed of water and Al_(2)O_(3),TiO_(2),and Cu nanoparticles,on heat transfer enhancement is *** aim of this research is also to analyze the influence of different parameters,including the Rayleigh number(Ra=10^(4)-10^(6)),nanoparticle volume fraction(φ=0%-20%),non-Newtonian power-law indexes(n=0.6-1.4),and fin dimensions(Ar=0.3,0.5,and 0.7).Streamlines and isotherms are used to depict flow and related heat transfer *** indicate that thermal performance improves with increasing Rayleigh number,regardless of the nanoparticle type or nanofluid rheological *** suggests that the buoyancy force has a significant impact on heat transfer,particularly near the heat *** Nusselt number is more sensitive to variations in Cu nanoparticle volume fractions compared to Al₂O₃and TiO₂.Moreover,the average Nusselt numbers for power-law nanofluids with n1)are greater(smaller)than for Newtonian fluids due to the decrease(increase)in viscosity with increasing(decreasing)shear rate,at the same values of Rayleigh number Ra owing to the amplification(attenuation)of the convective ***,the most substantial enhancement is observed with Cu-water shear-thinning nanofluid,where the Nusselt number increases by 136%when changing from Newtonian to shear thinning behavior and by 154.9%when adding 16%nanoparticle volume ***,an even larger increase of 57%in the average Nusselt number is obtained on increasing the fin length from 0.3 to 0.7.

关键词： Heat transfer nanofluid non-Newtonian fluid natural convection

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Transfer learning from T1-weighted to T2-weighted Magnetic resonance sequences for brain image segmentation

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CAAI Transactions on Intelligence Technology 2024年第1期9卷 26-39页

作者： Imene Mecheter Maysam Abbod Habib Zaidi Abbes amira Brunel University LondonUK Geneva University Hospital GenevaSwitzerland Geneva University GenevaSwitzerland University of Groningen GroningenNetherlands University of Southern Denmark OdenseDenmark University of Sharjah SharjahUAE De Montfort University LeicesterUK

Magnetic resonance(MR)imaging is a widely employed medical imaging technique that produces detailed anatomical images of the human *** segmentation of MR im-ages plays a crucial role in medical image analysis,as it enables accurate diagnosis,treatment planning,and monitoring of various diseases and *** to the lack of sufficient medical images,it is challenging to achieve an accurate segmentation,especially with the application of deep learning *** aim of this work is to study transfer learning from T1-weighted(T1-w)to T2-weighted(T2-w)MR sequences to enhance bone segmentation with minimal required computation *** the use of an excitation-based convolutional neural networks,four transfer learning mechanisms are proposed:transfer learning without fine tuning,open fine tuning,conservative fine tuning,and hybrid transfer ***,a multi-parametric segmentation model is proposed using T2-w MR as an intensity-based augmentation *** novelty of this work emerges in the hybrid transfer learning approach that overcomes the overfitting issue and preserves the features of both modalities with minimal computation time and *** segmentation results are evaluated using 14 clinical 3D brain MR and CT *** results reveal that hybrid transfer learning is superior for bone segmentation in terms of performance and computation time with DSCs of 0.5393±*** T2-w-based augmentation has no significant impact on the performance of T1-w MR segmentation,it helps in improving T2-w MR segmentation and developing a multi-sequences segmentation model.

关键词： computer vision convolution image segmentation learning(artificial intelligence)

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Exploring Sequential Feature Selection in Deep Bi-LSTM Models for Speech Emotion Recognition

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Computers, Materials & Continua 2024年第2期78卷 2689-2719页

作者： Fatma Harby Mansor Alohali Adel Thaljaoui amira Samy Talaat Computer Science Department Future Academy-Higher Future Institute for Specialized Technological StudiesCairo12622Egypt Department of Computer Science and Information College of Science at Zulfi Majmaah UniversityP.O.Box 66Al-Majmaah11952Saudi Arabia Preparatory Institute for Engineering Studies of Gafsa ZarrougGafsa2112Tunisia Computers and Systems Department Electronics Research InstituteCairo12622Egypt

Machine Learning(ML)algorithms play a pivotal role in Speech Emotion Recognition(SER),although they encounter a formidable obstacle in accurately discerning a speaker’s emotional *** examination of the emotional states of speakers holds significant importance in a range of real-time applications,including but not limited to virtual reality,human-robot interaction,emergency centers,and human behavior *** identifying emotions in the SER process relies on extracting relevant information from audio *** studies on SER have predominantly utilized short-time characteristics such as Mel Frequency Cepstral Coefficients(MFCCs)due to their ability to capture the periodic nature of audio signals *** these traits may improve their ability to perceive and interpret emotional depictions appropriately,MFCCS has some *** this study aims to tackle the aforementioned issue by systematically picking multiple audio cues,enhancing the classifier model’s efficacy in accurately discerning human *** utilized dataset is taken from the EMO-DB database,preprocessing input speech is done using a 2D Convolution Neural Network(CNN)involves applying convolutional operations to spectrograms as they afford a visual representation of the way the audio signal frequency content changes over *** next step is the spectrogram data normalization which is crucial for Neural Network(NN)training as it aids in faster *** the five auditory features MFCCs,Chroma,Mel-Spectrogram,Contrast,and Tonnetz are extracted from the spectrogram *** attitude of feature selection is to retain only dominant features by excluding the irrelevant *** this paper,the Sequential Forward Selection(SFS)and Sequential Backward Selection(SBS)techniques were employed for multiple audio cues features ***,the feature sets composed from the hybrid feature extraction methods are fed into the deep Bidirectional Long Short

关键词： Artificial intelligence application multi features sequential selection speech emotion recognition deep Bi-LSTM

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A Weighted Multi-Layer Analytics Based Model for Emoji Recommendation

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Computers, Materials & Continua 2024年第1期78卷 1115-1133页

作者： amira M.Idrees Abdul Lateef Marzouq Al-Solami Faculty of Computers and Information Technology Future University in EgyptCairo11835Egypt Alkamil College of Science and Arts University of JeddahJeddah21959Saudi Arabia

The developed system for eye and face detection using Convolutional Neural Networks(CNN)models,followed by eye classification and voice-based assistance,has shown promising potential in enhancing accessibility for individuals with visual *** modular approach implemented in this research allows for a seamless flow of information and assistance between the different components of the *** research significantly contributes to the field of accessibility technology by integrating computer vision,natural language processing,and voice *** leveraging these advancements,the developed system offers a practical and efficient solution for assisting blind *** modular design ensures flexibility,scalability,and ease of integration with existing assistive ***,it is important to acknowledge that further research and improvements are necessary to enhance the system’s accuracy and ***-tuning the CNN models and expanding the training dataset can improve eye and face detection as well as eye classification ***,incorporating real-time responses through sophisticated natural language understanding techniques and expanding the knowledge base of ChatGPT can enhance the system’s ability to provide comprehensive and accurate ***,this research paves the way for the development of more advanced and robust systems for assisting visually impaired *** leveraging cutting-edge technologies and integrating them into amodular framework,this research contributes to creating a more inclusive and accessible society for individuals with visual *** work can focus on refining the system,addressing its limitations,and conducting user studies to evaluate its effectiveness and impact in real-world scenarios.

关键词： Social networks text analytics emoji prediction features extraction information retrieval

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Solute transport and geochemical modeling of the coastal quaternary aquifer, Delta Dahab Basin, South Sinai, Egypt

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Acta Geochimica 2024年第1期43卷 16-39页

作者： amira Samy Mustafa Eissa Seham Shahen Moustafa M.Said Rabab M.Abou-shahaba Division of Water Resources and Arid Land Department of HydrogeochemistryDesert Research CenterCairoEgypt Egypt Desalination Research Center of Excellence Desert Research CenterCairoEgypt Center for Water Supply Studies S&E-Physical&Environmental SciencesTexas A&M University Corpus ChristiCorpus ChristiUSA Department of Chemistry Faculty of Science(Girls)Al-Azhar UniversityYousef Abbas StrNasr CityP.O.Box:11754CairoEgypt

The wadi dahab delta is in a dry, arid coastal zone within Egypt’s south Sinai Peninsula’s eastern portion. The primary water source is the Quaternary coastal alluvial aquifer. The groundwater salinity varies from 890to 8213 mg/L, with a mean value of 3417 mg/L. The dissolved major ions have been used to calculate the seawater mixing index(SWMI) using a linear equation that discriminates the groundwater mostly affected by water–rock interaction(SWMI 1>) and other samples mixed with Seawater(SWMI el constrained by the dissolved significant ions, isotopes, and the rock aquifer forming minerals as phases indicate the mixing percent with the seawater ranges from 9% to 97% of seawater from 91% to 3% of original recharge water. According to the SEAWAT 3-D flow models, seawater has penetrated the Northeastern Dahab delta aquifer, with the intrusion zone extending1500 m inland. The salt dissolution, upwelling of saline water, recharge from the upstream mountain block, and seawater encroachment are the primary aspects contributing to the deterioration of groundwater quality. These findings may have significance for effective groundwater withdrawal management in arid locations worldwide with similar hydrogeological systems.

关键词： Groundwater geochemistry Seawater intrusion Solute transport SEAWAT

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A Proposed Feature Selection Particle Swarm Optimization Adaptation for Intelligent Logistics--A Supply Chain Backlog elimination Framework

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Computers, Materials & Continua 2024年第6期79卷 4081-4105页

作者： Yasser Hachaichi Ayman E.Khedr amira M.Idrees College of Computing and Information Technology at Khulais Department of Information SystemsUniversity of JeddahJeddah21959Saudi Arabia Faculty of Computers and Information Technology Future University in EgyptCairo11835Egypt

The diversity of data sources resulted in seeking effective manipulation and *** challenge that arises from the increasing dimensionality has a negative effect on the computation performance,efficiency,and stability of *** of the most successful optimization algorithms is Particle Swarm Optimization(PSO)which has proved its effectiveness in exploring the highest influencing features in the search space based on its fast convergence and the ability to utilize a small set of parameters in the search *** research proposes an effective enhancement of PSO that tackles the challenge of randomness search which directly enhances PSO *** the other hand,this research proposes a generic intelligent framework for early prediction of orders delay and eliminate orders backlogs which could be considered as an efficient potential solution for raising the supply chain *** proposed adapted algorithm has been applied to a supply chain dataset which minimized the features set from twenty-one features to ten significant *** confirm the proposed algorithm results,the updated data has been examined by eight of the well-known classification algorithms which reached a minimum accuracy percentage equal to 94.3%for random forest and a maximum of 99.0 for Naïve ***,the proposed algorithm adaptation has been compared with other proposed adaptations of PSO from the literature over different *** proposed PSO adaptation reached a higher accuracy compared with the literature ranging from 97.8 to 99.36 which also proved the advancement of the current research.

关键词： Optimization particle swarm optimization algorithm feature selection logistics supply chain management backlogs

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Mixed Neuroendocrine-Non-Neuroendocrine Neoplasm (MiNEN) of the Colon: A Case Report

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Open Journal of Pathology 2024年第1期14卷 16-24页

作者： amira Mohammad Azah Syahrina Alias Department of Pathology Hospital Sultanah Aminah Johor Bahru Johor Malaysia

Here we report a rare case of mixed neuroendocrine-non-neuroendocrine neoplasms (MiNENs). A 51-year-old lady with no known family history of malignancies developed this rare type of malignancy without any active gastrointestinal symptoms. However, during a routine health check, physicians noticed a raised Carcinoembryonic Antigen (CEA) level and the patient subsequently was referred to the surgical department for further management. A colonoscopy and CECT abdomen were done and she was electively admitted for a left hemicolectomy operation for a splenic flexure tumour. The histopathological report revealed the tumour is a case of mixed neuroendocrine-non-neuroendocrine neoplasms (MiNENs) [moderately differentiated adenocarcinoma and neuroendocrine tumour grade 3]. TNM (8th edition, 2016): pT3, pN2 (20/21), pMX. Both resection margins were clear from malignant cells. Colorectal MiNENs, constitute a rare group of gastrointestinal tumours composed of both neuroendocrine and non-neuroendocrine components. Given their non-diagnostic macroscopic features, specific histological features and lack of disease awareness which are responsible for the underestimated incidence and conflicting data. In this case, a multidisciplinary team approach is important in managing patients with this malignancy to achieve the best outcome.

关键词： Mixed Neuroendocrine-Non-Neuroendocrine Neoplasms (MiNENs) Contrast-Enhanced Computed Tomography (CECT) Carcinoembryonic Antigen (CEA)

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Rooted Tree Optimization for Wind Turbine Optimum Control Based on Energy Storage System

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Computers, Materials & Continua 2023年第2期74卷 3977-3996页

作者： Billel Meghni Afaf Benamor Oussama Hachana Ahmad Taher Azar amira Boulmaiz salah Saad el-Sayed M.el-kenawy Nashwa Ahmad Kamal Suliman Mohamed Fati Naglaa K.Bahgaat Department of electrical Engineering Badji Mokhtar UniversityLSEM LaboratoryAnnaba23000Algeria Department of electrical Engineering Biskra UniversityLGEB LaboratoryBiskra07000Algeria Department of Drilling and Rig Mechanics Ksadi Merbah UniversityOuargla30000Algeria College of Computer and Information Sciences Prince Sultan UniversityRiyadh11586Saudi Arabia Faculty of Computers and Artificial Intelligence Benha UniversityBenha13518Egypt Department of electronics University of Badji MokhtarLERICA LaboratoryAnnaba23000Algeria Delta Higher Institute for Engineering&Technology(DHIET) Mansoura35511Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt Faculty of Engineering Cairo UniversityGiza12613Egypt Department of Communications and electronics Engineering Faculty of EngineeringCanadian International College(CIC)ElShiekh ZayedEgypt

The integration of wind turbines(WTs)in variable speed drive systems belongs to the main factors causing lowstability in electrical ***,in order to avoid this issue,WTs hybridization with a storage system is a *** paper investigates WT system operating at variable *** system contains of a permanent magnet synchronous generator(PMSG)supported by a battery storage system(BSS).To enhance the quality of active and reactive power injected into the network,direct power control(DPC)scheme utilizing space-vector modulation(SVM)technique based on proportional-integral(PI)control is ***,to improve the rendition of this method(DPC-SVM-PI),the rooted tree optimization technique(RTO)algorithm-based controller parameter identification is used to achieve PI optimal *** compare the performance ofRTO-based controllers,they were implemented and tested along with some other popular controllers under different working *** obtained results have shown the supremacy of the suggested PIRTO algorithm compared to competing controllers regarding total harmonic distortion(THD),overshoot percentage,settling time,rise time,average active power value,overall efficiency,and active power steadystate error.

关键词： Rooted tree optimization(RTO)method direct power control(DPC) wind turbine(WT) proportional integral(PI) PMSG

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Outcome of Nurses with Occupational Dermatitis

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Open Journal of Nursing 2024年第6期14卷 239-251页

作者： amira Omrane Chayma Harrathi Asma Kheder Maher Maoua Malek Ben Abdelkader Taoufik Khalfallah Najib Mrizak Mohamed Akrout Mohamed Adnene Henchi Hichem Bel Hadj Ali Department of Occupational Medicine and Ergonomics Taher Sfar Teaching Hospital Mahdia Tunisia Department of Occupational Medicine Houcine Bouzaiene Teaching Hospital Gafsa Tunisia Department of Occupational Medicine Farhat Hached Teaching Hospital Sousse Tunisia Department of Occupational Medicine and Ergonomics Fattouma Bourguiba Teaching Hospital Monastir Tunisia Department of Dermatology Fattouma Bourguiba Teaching Hospital Monastir Tunisia

Background: Occupational dermatitis is considered as the second most common occupational disease. It accounts for 25% of all lost workdays. Several international studies reported a prevalence of occupational dermatitis in healthcare workers between 17% and 55%. This study aims to identify factors that affect the professional outcome of nurses suffering from occupational dermatitis. Methods: This was a multicenter cross-sectional study concerning nurses declared having occupational dermatitis in the central region of Tunisia. A synoptic sheet related to socio-professional and administrative data was completed. A self-administered Questionnaire going over medical and occupational characteristics was completed during a direct interview. Results: The study involved forty nurses working in four public hospitals in the center of Tunisia. Only 37 workers were included in the study. A professional reclassification was introduced among 19 workers (51% of study population). Work-station adaptation was requested in 14 cases (38%). Exposure to allergens in the workplace was eliminated in 20 cases. Two study participants were transferred to other departments (5.4%) and three people retired (8.1%). A statistically significant association was found between professional reclassification and a history of allergic manifestations (p = 0.003). Similarly, a significant association was found between professional reclassification and the allergic agent (p = 0.014). Workstation layout was significantly associated with a history of allergic manifestations (p = 0.039), the palm hand location (p = 0.04), professional eviction (p Conclusion: This study identified the main factors influencing the occupational outcome of nurses suffering from occupational dermatitis. This outcome depended on a history of atopy (especially allergic rhinitis) and sensitization to allergens (thiuram mix).

关键词： Nursing Occupational Dermatitis Hospital

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