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Takotsubo cardiomyopathy in orthotopic liver transplant recipients: A cohort study using multi-center pooled electronic health record data

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World Journal of Hepatology 2022年第2期14卷 400-410页

作者： Mohammad Zmaili Jafar Alzubi Motasem Alkhayyat Joshua Cohen Saqer Alkharabsheh Mariam Rana Paulino A Alvarez emad mansoor Bo Xu Robert and Suzanne Tomsich Department of Cardiovascular Medicine Sydell and Arnold Miller Family HeartVascular and Thoracic InstituteCleveland Clinic FoundationClevelandOH 44195United States Department of Medicine Division of CardiologyEinstein Medical CenterPhiladelphiaPA 19141United States Department of Gastroenterology Hepatology and NutritionDigestive Disease and Surgery InstituteCleveland Clinic FoundationClevelandOH 44195United States Department of Medicine University Hospitals Cleveland Medical CenterCase Western Reserve UniversityClevelandOH 44106United States Department of Gastroenterology University Hospitals Cleveland Medical CenterCase Western Reserve UniversityClevelandOH 44106United States

BACKGROUND Takotsubo cardiomyopathy(TCM),or stress-induced cardiomyopathy,is associated with adverse *** data suggest that TCM occurring in orthotopic liver transplant(OLT)recipients is associated with elevated perioperative *** To characterize the predictors of TCM in OLT recipients,using a large,multicenter pooled electronic health *** A multi-institutional database(Explorys Inc,Cleveland,OH,USA),an aggregate of de-identified electronic health record data from 26 United States healthcare systems was surveyed.A cohort of patients with a Systematized Nomenclature of Medicine-Clinical Terms of“liver transplant”between 09/2015 and 09/2020 was ***,individuals who developed a new diagnosis of TCM following OLT were ***,the risk associations with TCM among this patient population were characterized using linear *** Between 09/2015 and 09/2020,of 37718540 patients in the database,38740(0.10%)had a history of OLT(60.6%had an age between 18-65 years,58.1%female).A new diagnosis of TCM was identified in 0.3%of OLT recipients(45.5%had an age between 18-65 years,72.7%female),compared to 0.04%in non-OLT patients[odds ratio(OR):7.98,95%confidence intervals:6.62-9.63,(P<0.0001)].OLT recipients who developed TCM,compared to those who did not,were more likely to be greater than 65 years of age,Caucasian,and female(P<0.05).There was also a significant association with cardiac arrhythmias,especially ventricular arrhythmias(P<0.0001).CONCLUSION TCM was significantly more likely to occur in LT recipients vs *** age,Caucasian ethnicity,female gender,and presence of arrhythmias were significantly associated with TCM in LT recipients.

关键词： Takotsubo cardiomyopathy Orthotopic liver transplant Stress-induced cardiomyopathy Clinical outcomes

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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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On the analytical soliton approximations to fractional forced Korteweg-de Vries equation arising in fluids and plasmas using two novel techniques

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Communications in Theoretical Physics 2024年第8期76卷 1-10页

作者： Weaam Alhejaili emad A Az-Zo’bi Rasool Shah S A El-Tantawy Department of Mathematical Sciences College of SciencePrincess Nourah bint Abdulrahman UniversityPO Box 84428Riyadh 11671Saudi Arabia Department Mathematics and Statistics Mutah UniversityAl-KarakJordan Department of Computer Science and Mathematics Lebanese American UniversityBeirutLebanon Department of Physics Faculty of SciencePort Said UniversityPort Said 42521Egypt Department of Physics Faculty of ScienceAl-Baha UniversityAl-Baha P.O.Box 1988Saudi Arabia

The current investigation examines the fractional forced Korteweg-de Vries(FF-KdV) equation,a critically significant evolution equation in various nonlinear branches of science. The equation in question and other associated equations are widely acknowledged for their broad applicability and potential for simulating a wide range of nonlinear phenomena in fluid physics, plasma physics, and various scientific domains. Consequently, the main goal of this study is to use the Yang homotopy perturbation method and the Yang transform decomposition method, along with the Caputo operator for analyzing the FF-KdV equation. The derived approximations are numerically examined and discussed. Our study will show that the two suggested methods are helpful, easy to use, and essential for looking at different nonlinear models that affect complex processes.

关键词： forced fractional KdV equation Caputo operator Yang homotopy perturbation method Yang transform decomposition method solitons

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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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Stability analysis and soliton solutions of the(1+1)-dimensional nonlinear chiral Schrodinger equation in nuclear physics

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Communications in Theoretical Physics 2024年第9期76卷 1-15页

作者： Fazal Badshah Kalim U Tariq Ahmet Bekir S M Raza Kazmi emad Az-Zo'bi School of Electrical and Information Engineering Hubei University of Automotive TechnologyShiyan 442002China Department of Mathematics Mirpur University of Science and TechnologyMirpur-10250(AJK)Pakistan Neighbourhood of Akcaglan Imarli StreetNumber:28/426030EskisehirTurkey Department of Mathematics and Statistics Faculty of ScienceMutah UniversityAlKarak 61710Jordan

The nonlinear Schrodinger equation equation is one of the most important physical models used in optical fiber theory to explain the transmission of an optical *** field of chiral soliton propagation in nuclear physics is very interesting because of its numerous applications in communications and ultra-fast signal routing ***(1+1)-dimensional chiral dynamical structure that describes the soliton behaviour in data transmission is dealt with in this work using a variety of in-depth analytical *** work has applications in particle physics,ionised science,nuclear physics,optics,and other applied mathematical *** are able to develop a variety of solutions to demonstrate the behaviour of solitary wave structures,periodic soliton solutions,chiral soliton solutions,and bell-shaped soliton solutions with the use of applied ***,in order to verify the scientific calculations,the stability analysis for the observed solutions of the governing model is taken into *** addition,the3-dimensional,contour,and 2-dimensional visuals are supplied for a better understanding of the behaviour of the *** employed strategies are dependable,uncomplicated,and effective;yet have not been utilised with the governing model in the literature that is now *** resulting outcomes have impressive applications across a large number of study areas and computational physics phenomena representing real-world *** methods applied in this model are not utilized on the given models in previous literature so we can say that these describe the novelty of the work.

关键词： solitons the nonlinear Schrodinger equation stability analysis chiral solitons exact solutions

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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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