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Real time endoscopic ultrasound elastography and strain ratio in the diagnosis of solid pancreatic lesions

World Journal of Gastroenterology 2017年第32期23卷 5962-5968页

作者： Hussein Okasha Shaimaa Elkholy Ramy El-Sayed Mohamed-Naguib Wifi Mohamed El-Nady Walid El-Nabawi Waleed A El-Dayem Mohamed I Radwan ali Farag Yahya El-sherif emad al-gemeie Ahmed Salman Mohamed El-Sherbiny Ahmed El-Mazny Reem E Mahdy Internal Medicine Department Cairo University Department of Tropical Medicine Zagazig University Internal Medicine Department Beni Suef University Tropical Medicine Department El Manial Specialized Hospital Pathology Department National Cancer InstituteCairo University Internal Medicine Department Assiut University

AIM To evaluate the accuracy of the elastography score combined to the strain ratio in the diagnosis of solid pancreatic lesions(SPL). METHODS A total of 172 patients with SPL identified by endoscopic ultrasound were enrolled in the study to evaluate the efficacy of elastography and strain ratio in differentiating malignant from benign lesions. The semi quantitative score of elastography was represented by the strain ratio method. Two areas were selected, area(A) representing the region of interest and area(B) representing the normal area. Area(B) was then divided by area(A). Sensitivity, specificity, positive predictive value(PPV), negative predictive value(NPV), and accuracy were calculated by comparing diagnoses made by elastography, strain ratio and final *** SPL were shown to be benign in 49 patients and malignant in 123 patients. Elastography alone had a sensitivity of 99%, a specificity of 63%, and an accuracy of 88%, a PPV of 87% and an NPV of 96%. The best cut-off level of strain ratio to obtain the maximal area under the curve was 7.8 with a sensitivity of 92%, specificity of 77%, PPV of 91%, NPV of 80% and an accuracy of 88%. Another estimated cut off strain ratio level of 3.8 had a higher sensitivity of 99% and NPV of 96%, but with less specificity, PPV and accuracy 53%, 84% and 86%, respectively. Adding both elastography to strain ratio resulted in a sensitivity of 98%, specificity of 77%, PPV of 91%, NPV of 95% and accuracy of 92% for the diagnosis of SPL. CONCLUSION Combining elastography to strain ratio increases the accuracy of the differentiation of benign from malignant SPL.

关键词： Endoscopic Ultrasound Elastography Strain Ratio Real Time Pancreatic lesions

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Numerical Treatments for Crossover Cancer Model of Hybrid Variable-Order Fractional Derivatives

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Computer Modeling in Engineering & Sciences 2024年第8期140卷 1619-1645页

作者： Nasser Sweilam Seham al-Mekhlafi Aya Ahmed Ahoud alsheri emad Abo-Eldahab Mathematics Department Faculty of ScienceCairo UniversityGiza12613Egypt Mathematics Department Faculty of EducationSana’a UniversitySana’a1247Yemen Mathematics Department Faculty of ScienceHelwan UniversityCairo11795Egypt Department of Mathematics College of ScienceUniversity of BishaAl Namas67398-5644Saudi Arabia

In this paper,two crossover hybrid variable-order derivatives of the cancer model are ***ünwald-Letnikov approximation is used to approximate the hybrid fractional and variable-order fractional *** existence,uniqueness,and stability of the proposed model are *** Bashfourth’s fifth-step method with a hybrid variable-order fractional operator is developed to study the proposed *** studies with generalized fifth-order Runge-Kutta method are *** examples and comparative studies to verify the applicability of the used methods and to demonstrate the simplicity of these approximations are *** have showcased the efficiency of the proposed method and garnered robust empirical support for our theoretical findings.

关键词： Cancer diseases hybrid variable-order fractional derivatives adams bashfourth fifth step generalized fifth order Runge-Kutta method

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Deep Learning Based Efficient Crowd Counting System

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Computers, Materials & Continua 2024年第6期79卷 4001-4020页

作者： Waleed Khalid al-Ghanem emad Ul Haq Qazi Muhammad Hamza Faheem Syed Shah Amanullah Quadri Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityRiyadh12372Saudi Arabia Centre of Excellence in Cybercrime and Digital Forensics Naif Arab University for Security SciencesRiyadh14812Saudi Arabia Center of Excellence for Information Assurance(COEIA) King Saud UniversityRiyadh12372Saudi Arabia

Estimation of crowd count is becoming crucial nowadays,as it can help in security surveillance,crowd monitoring,and management for different *** is challenging to determine the approximate crowd size from an image of the crowd’s *** in this research study,we proposed a multi-headed convolutional neural network architecture-based model for crowd counting,where we divided our proposed model into two main components:(i)the convolutional neural network,which extracts the feature across the whole image that is given to it as an input,and(ii)the multi-headed layers,which make it easier to evaluate density maps to estimate the number of people in the input image and determine their number in the *** employed the available public benchmark crowd-counting datasets UCF CC 50 and ShanghaiTech parts A and B for model training and testing to validate the model’s *** analyze the results,we used two metrics Mean Absolute Error(MAE)and Mean Square Error(MSE),and compared the results of the proposed systems with the state-of-art models of crowd *** results show the superiority of the proposed system.

关键词： Crowd counting EfficientNet multi-head attention convolutional neural network transfer learning

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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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Numerical Analysis of Bacterial Meningitis Stochastic Delayed Epidemic Model through Computational Methods

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Computer Modeling in Engineering & Sciences 2024年第10期141卷 311-329页

作者： Umar Shafique Mohamed Mahyoub al-Shamiri ali Raza emad Fadhal Muhammad Rafiq Nauman Ahmed Department of Mathematics National College of Business Administration and EconomicsLahore54660Pakistan Department of Mathematics Applied CollegeMahayl AssirKing Khalid UniversityAbha62529Saudi Arabia Department of Physical Sciences The University of ChenabGujrat50700Pakistan Department of Mathematics&Statistics College of ScienceKing Faisal UniversityP.O.Box 400Al-Ahsa31982Saudi Arabia Department of Computer Science and Mathematics Lebanese American UniversityBeirut1102-2801Lebanon Department of Mathematics Faculty of Science and TechnologyUniversity of Central PunjabLahore54000Pakistan Department of Mathematics and Statistics University of LahoreLahore54000Pakistan

Based on theWorld Health Organization(WHO),Meningitis is a severe infection of the meninges,the membranes covering the brain and spinal *** is a devastating disease and remains a significant public health *** study investigates a bacterial meningitis model through deterministic and stochastic ***-compartment population dynamics explain the concept,particularly the susceptible population,carrier,infected,and *** model predicts the nonnegative equilibrium points and reproduction number,i.e.,the Meningitis-Free Equilibrium(MFE),and Meningitis-Existing Equilibrium(MEE).For the stochastic version of the existing deterministicmodel,the twomethodologies studied are transition probabilities and non-parametric ***,positivity,boundedness,extinction,and disease persistence are studiedrigorouslywiththe helpofwell-known *** and nonstandard techniques such as EulerMaruyama,stochastic Euler,stochastic Runge Kutta,and stochastic nonstandard finite difference in the sense of delay have been presented for computational analysis of the stochastic ***,standard methods fail to restore the biological properties of the model,so the stochastic nonstandard finite difference approximation is offered as an efficient,low-cost,and independent of time step *** addition,the convergence,local,and global stability around the equilibria of the nonstandard computational method is studied by assuming the perturbation effect is *** simulations and comparison of the methods are presented to support the theoretical results and for the best visualization of results.

关键词： Bacterial Meningitis disease stochastic delayed model stability analysis extinction and persistence computational methods

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The Upper Jurassic sediments,Marib-Shabwa Basin,Yemen:Lithofacies aspects and sequence stratigraphic analysis

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Energy Geoscience 2024年第1期5卷 342-357页

作者： Mohammed albaroot Mohamed M.Elhossainy Nabil M.al-Areeq emad A.Abdullah Abdelhamid M.Salman Department of Applied Geology Faculty of Science and EducationUniversity of Saba RegionMaribYemen Department of Geology Faculty of ScienceKafrelsheikh UniversityKafrelsheikh33516Egypt Department of Geology and Environment Faculty of Applied SciencesThamar UniversityYemen Department of Mineral Developing and Oil&Gas Engineering Academy of EngineeringPeoples’Friendship University of Russia(RUDN University)Moscow117198Russia Department of Geology Faculty of ScienceAssiut UniversityAssiut71516Egypt

The present study is devoted to understanding the evolution of the Upper Jurassic Sab'atayn Formation in the Marib-Shabwa Basin,Yemen,through a sequence stratigraphic analysis based on integrating datasets of sedimentology,seismic sections,and well *** Sab'atayn Formation(Tithonian age)is represented by a series of clastic and evaporites that were deposited under fluvio-deltaic to prodeltaic *** is divided into four members including Yah(at the base),upwards to Seen,alif,and Safir at the *** third-order depositional sequences were determined for the Tithonian succession which were separated by three sequence *** sequences were classified into their systems tracts signifying several sedimentation patterns of progradational,aggradational,and retrogradational parasequence *** first depositional sequence corresponds to the early-middle Tithonian Yah and Seen units that can be classified into lowstand,transgressive,and highstand systems *** second sequence comprises the late Tithonian alif unit that can be subdivided into transgressive and highstand systems *** sandy deposits of the alif Member(highstand deposits)represent the most productive hydrocarbon reservoir in the *** Upper Jurassic sediments in the study area were resulted from a combination of eustatic and tectonic effects.

关键词： Sequence stratigraphy Sandstone reservoir Well logs Upper Jurassic Marib-Shabwa Basin Yemen

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Evaluating the Efficacy of Latent Variables in Mitigating Data Poisoning Attacks in the Context of Bayesian Networks:An Empirical Study

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Computer Modeling in Engineering & Sciences 2024年第5期139卷 1635-1654页

作者： Shahad alzahrani Hatim alsuwat emad alsuwat Independent Researcher Specializing in Data Security and Privacy Taif26571Saudi Arabia Department of Computer Science College of Computer and Information SystemsUmm Al-Qura UniversityMakkah24382Saudi Arabia Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif26571Saudi Arabia

Bayesian networks are a powerful class of graphical decision models used to represent causal relationships among ***,the reliability and integrity of learned Bayesian network models are highly dependent on the quality of incoming data *** of the primary challenges with Bayesian networks is their vulnerability to adversarial data poisoning attacks,wherein malicious data is injected into the training dataset to negatively influence the Bayesian network models and impair their *** this research paper,we propose an efficient framework for detecting data poisoning attacks against Bayesian network structure learning *** framework utilizes latent variables to quantify the amount of belief between every two nodes in each causal model over *** use our innovative methodology to tackle an important issue with data poisoning assaults in the context of Bayesian *** regard to four different forms of data poisoning attacks,we specifically aim to strengthen the security and dependability of Bayesian network structure learning techniques,such as the PC *** doing this,we explore the complexity of this area and offer workablemethods for identifying and reducing these sneaky ***,our research investigates one particular use case,the“Visit to Asia Network.”The practical consequences of using uncertainty as a way to spot cases of data poisoning are explored in this inquiry,which is of utmost *** results demonstrate the promising efficacy of latent variables in detecting and mitigating the threat of data poisoning ***,our proposed latent-based framework proves to be sensitive in detecting malicious data poisoning attacks in the context of stream data.

关键词： Bayesian networks data poisoning attacks latent variables structure learning algorithms adversarial attacks

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Role of endoscopic-ultrasound-guided biliary drainage with electrocautery-enhanced lumen-apposing metal stent for palliation of malignant biliary obstruction

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World Journal of Gastrointestinal Surgery 2024年第7期16卷 1981-1985页

作者： Smit S Deliwala emad Qayed Department of Medicine Division of Digestive DiseasesEmory University School of MedicineAtlantaGA 30303United States

In this editorial,we discuss the article by Peng et al in the recent issue of the World Journal of Gastrointestinal Surgery,focusing on the evolving role of endoscopicultrasound-guided biliary drainage(EUS-BD)with electrocautery lumen apposing metal stent(LAMS)for distal malignant biliary *** endoscopy has rapidly advanced in decompression techniques,with growing evidence of its safety and efficacy surpassing percutaneous and surgical *** endoscopic retrograde cholangiopancreatography(ERCP)has been the gold standard for biliary decompression,its failure rate approaches 10.0%,prompting the exploration of alternatives like *** random-effects meta-analysis demonstrated high technical and clinical success of over 90.0% and an adverse event rate of 17.5%,mainly in the form of stent *** based on stent size were not reported but the majority used 6 mm and 8 mm *** the body of literature continues to demonstrate the effectiveness of this technique,the challenges of stent dysfunction need to be addressed in future *** strategy that has shown promise is placement of double-pigtail stents,only 18% received the prophylactic intervention in this *** expect this to improve with time as the technique continues to be refined and *** results above establish EUS-BD with LAMS as a reliable alternative after failed ERCP and considering EUS to ERCP upfront in the same session is an effective *** the promising results,studies must explore the role of EUS-BD as first-line therapy for biliary decompression.

关键词： Endoscopic-ultrasound Malignant biliary obstruction Lumen apposing metal stent Choledochoduodenostomy Hepaticogastrostomy

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Machine and deep learning driven models for the design of heat exchangers with micro-finned tubes

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Energy and AI 2024年第2期16卷 417-437页

作者： emad Efatinasab Nima Irannezhad Mirco Rampazzo Andrea Diani Department of Information Engineering University of PadovaVia Gradenigo 6/bPadova35131PDItaly Department of Industrial Engineering University of PadovaVia Venezia 1Padova35131PDItaly

The design of micro-finned tube heat exchangers is a complex task due to intricate geometry, heat transfer goals, material selection, and manufacturing challenges. Nowadays, mathematical models provide valuable insights, aid in optimization, and allow us to explore various design parameters efficiently. However, existing empirical models often fall short in facilitating an optimal design because of their limited accuracy, sensitivity to assumption, and context dependency. In this scenario, the use of Machine and Deep Learning (ML and DL) methods can enhance accuracy, manage nonlinearity, adjust to varying conditions, decrease dependence on assumptions, automatically extract pertinent features, and provide scalability. Indeed, ML and DL techniques can derive valuable insights from datasets, contributing to a comprehensive understanding. By means of multiple ML and DL methods, this paper addresses the challenge of estimating key parameters in micro-finned tube heat exchangers such as the heat transfer coefficient (HTC) and frictional pressure drop (FPD). The methods have been trained and tested using an experimental dataset consisting of over a thousand data points associated with flow condensation, involving various tube geometries. In this context, the Artificial Neural Network (ANN) demonstrates superior performance in accurately estimating parameters with MAEs in the range below 4.5% for both HTC and FPD. Finally, recognizing the importance of comprehending the internal mechanisms of the black-box ANN model, the paper explores its interpretability aspects.

关键词： Condensation Micro-finned tube Artificial neural network Machine learning Deep learning

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A Pioneering Approach to the Synthesis of Silver Nanoparticles

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Journal of Materials Science and Chemical Engineering 2024年第7期12卷 14-22页

作者： Wasan A. al-Dulaimi Zeena M. al-Azzawi emad K. al-Shakarchi Physics Department College of Science Al-Nahrain University Baghdad Iraq

Our research introduces a groundbreaking chemical reduction method for synthesizing silver nanoparticles, marking a significant advancement in the field. The nanoparticles were meticulously characterized using various techniques, including optical analysis, structural analysis, transmission electron microscopy (TEM), and field-emission scanning electron microscope (FESEM). This thorough process instills confidence in the accuracy of our findings. The results unveiled that the silver nanoparticles had a diameter of less than 20 nm, a finding of great importance. The absorption spectrum decreased in the peak wavelength range (405 - 394 mm) with increasing concentrations of Ag nanoparticles in the range (1 - 5%). The XRD results indicated a cubic crystal structure for silver nanoparticles with the lattice constant (a = 4.0855 Å), and Miller indices were (111), (002), (002), and (113). The simulation on the XRD pattern showed a face center cubic phase with space group Fm-3m, providing valuable insights into the structure of the nanoparticles.

关键词： Chemical Reduction Method UV-VIS Absorption Spectrometer Field-Emission Scanning Electron Microscope (FESEM) Transmission Electron Microscopy (TEM)

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