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Primary Non-Hodgkin’s Malignant Lymphoma of the Uterus at the Reference Hospital of Maradi/Niger: A Case Report

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Open Journal of Blood Diseases 2024年第2期14卷 43-46页

作者： Moustapha Elhadji-Chefou Badé Malam-Abdou Amadou Djibrilla-Almoustapha Maman Brah Moustapha Oumou Kimso ibrahim Timi Liman Elhadji ali Issa Abdou Amadou Borges Moreno Yuribet Facult des Sciences de la Sant Universit Dan Dicko Dankoulodo de Maradi Maradi Niger Hopital de Reference de Maradi Maradi Niger Facult des Sciences de la Sant Universit Abdou Moumouni de Niamey Niamey Niger Facult des Sciences de la Sant Universit Andr Salifou de Zinder Zinder Niger

Malignant non-Hodgkins lymphoma (MHNL) of the uterus is uncommon. We report a case diagnosed on the basis of histologic and immunohistochemical studies of a hysterectomy specimen induced by a very painful pelvic mass in a 50-year-old patient with no previous history of the disease. It was classified as Ann Arbor IV Bb after imaging, given the medullary infiltration and signs of clinical and biological evolutivity: the patient had received two courses of chemotherapy, CHOP protocol. She died 23 days after the second treatment due to a hypertensive crisis.

关键词： Malignant Non-Hodgkin’s Lymphoma Uterus Referral Hospital Maradi/Niger

Wireless Sensor Networks Routing Attacks Prevention with Blockchain and Deep Neural Network

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Computers, Materials & Continua 2022年第3期70卷 6127-6140页

作者： mohamed ali ibrahim A.Abd El-Moghith mohamed N.El-Derini Saad M.Darwish Higher Institute for Tourism Hotels and ComputerAl-SeyoufAlexandria21533Egypt Department of Information Technology Institute of Graduate Studies and ResearchAlexandria University21526Egypt Department of Computer and Systems Engineering Faculty of EngineeringAlexandria UniversityAlexandria21544Egypt

Routing is a key function inWireless Sensor Networks(WSNs)since it facilitates data transfer to base *** attacks have the potential to destroy and degrade the functionality ofWSNs.A trustworthy routing system is essential for routing security andWSN *** methods have been implemented to build trust between routing nodes,including the use of cryptographic methods and centralized ***,the majority of routing techniques are unworkable in reality due to the difficulty of properly identifying untrusted routing node *** the moment,there is no effective way to avoid malicious node *** a consequence of these concerns,this paper proposes a trusted routing technique that combines blockchain infrastructure,deep neural networks,and Markov Decision Processes(MDPs)to improve the security and efficiency of WSN *** authenticate the transmission process,the suggested methodology makes use of a Proof of Authority(PoA)mechanism inside the blockchain *** validation group required for proofing is chosen using a deep learning approach that prioritizes each node’s *** are then utilized to determine the suitable next-hop as a forwarding node capable of securely transmitting *** to testing data,our routing system outperforms current routing algorithms in a 50%malicious node routing scenario.

关键词： Wireless sensor networks trusted routing deep neural network blockchain markov decision

Intelligent Beetle Antenna Search with Deep Transfer Learning Enabled Medical Image Classification Model

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Computer Systems Science & Engineering 2023年第9期46卷 3159-3174页

作者： mohamed ibrahim Waly Department of Medical Equipment Technology College of Applied Medical SciencesMajmaah UniversityAl Majmaah11952Saudi Arabia

Recently,computer assisted diagnosis(CAD)model creation has become more dependent on medical picture *** is often used to identify several conditions,including brain disorders,diabetic retinopathy,and skin *** traditional CAD methods relied on textures,colours,and *** many models are issue-oriented,they need a more substantial capacity to generalize and cannot capture high-level problem domain *** deep learning(DL)models have been published,providing a practical way to develop models specifically for classifying input medical *** paper offers an intelligent beetle antenna search(IBAS-DTL)method for classifying medical images facilitated by deep transfer *** IBAS-DTL model aims to recognize and classify medical pictures into various *** order to segment medical pictures,the current IBASDTLM model first develops an entropy based weighting and first-order cumulative moment(EWFCM)***,the DenseNet-121 techniquewas used as a module for extracting *** an extreme learning machine(ELM)model is used to classify the medical photos.A wide variety of tests were carried out using a benchmark medical imaging dataset to demonstrate the IBAS-DTL model’s noteworthy *** results gained indicated the IBAS-DTL model’s superiority over its pre-existing techniques.

关键词： Medical image segmentation image classification decision making computer aided diagnosis deep learning

Direct Power Control Based on Dead-beat Function and Extended Kalman Filter for PV Systems

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Journal of Modern Power Systems and Clean Energy 2023年第3期11卷 863-872页

作者： Mostafa Ahmed ibrahim Harbi Ralph Kennel mohamed Abdelrahem Chair of High-Power Converter Systems(HLU) Technical University of Munich(TUM)80333 MunichGermany Department of Electrical Engineering Faculty of EngineeringAssiut UniversityAssiut 71515Egypt Department of Electrical Engineering Faculty of EngineeringMenoufia UniversityShebin El-Koum 32511Egypt IEEE

In this paper,a new proposal for the implementation of the well-known direct power control(DPC)technique in grid-connected photovoltaic(PV)systems is ***,the DPC is executed using a look-up table procedure based on the error between the actual and reference values of the active and reactive ***,the structure of the DPC is simple and results in a fast transient behavior of the inner current loop(injected currents).Therefore,in the current study,the DPC is reformulated using a dead-beat *** this formulation,the reference voltage vector(RVV)is obtained in theα-βreference ***,the switching states for the inverter can be obtained based on the sign of the components of the *** suggested DPC is compared with the conventional one and other switching tables,which are intended for performance ***,an extended Kalman filter(EKF)is utilized to eliminate all grid-voltage ***,the switching frequency of the proposed technique is minimized without any need for weighting factors or cost function *** overall control technique is validated using a hardware-in-the-loop(HIL)experimental set-up and compared with other schemes under different operating conditions.

关键词： Photovoltaic(PV)system direct power control(DPC) sensorless control switching frequency minimization weighting factor

Serum resistin and the risk for hepatocellular carcinoma in diabetic patients

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World Journal of Gastroenterology 2023年第27期29卷 4271-4288页

作者： Mona mohamed ibrahim Abdalla Department of Human Biology School of MedicineInternational Medical UniversityBukit Jalil 57000Kuala LumpurMalaysia

Hepatocellular carcinoma(HCC),the predominant type of liver cancer,is a major contributor to cancer-related fatalities across the *** has been identified as a significant risk factor for HCC,with recent research indicating that the hormone resistin could be involved in the onset and advancement of HCC in diabetic *** is a hormone that is known to be involved in inflammation and insulin *** with HCC have been observed to exhibit increased resistin levels,which could be correlated with more severe disease stages and unfavourable ***,the exact processes through which resistin influences the development and progression of HCC in diabetic patients remain *** article aims to examine the existing literature on the possible use of resistin levels as a biomarker for HCC development and ***,it reviews the possible pathways of HCC initiation due to elevated resistin and offers new perspectives on comprehending the fundamen-tal mechanisms of HCC in diabetic *** a better understanding of these processes may yield valuable insights into HCC’s development and progression,as well as identify possible avenues for prevention and therapy.

关键词： Hepatocellular carcinoma Resistin Insulin resistance Obesity Diabetes Liver cancer

Role of visfatin in obesity-induced insulin resistance

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World Journal of Clinical Cases 2022年第30期10卷 10840-10851页

作者： Mona mohamed ibrahim Abdalla Physiology Department Human Biology DivisionSchool of MedicineInternational Medical UniversityKuala Lumpur 57000Bukit JalilMalaysia

The growing worldwide burden of insulin resistance(IR) emphasizes the importance of early identification for improved ***,particularly visceral obesity,has been a key contributing factor in the development of *** obesity-associated chronic inflammatory state contributes to the development of obesity-related comorbidities,including ***,which are released by adipose tissue,have been investigated as possible indicators of *** was one of the adipocytokines that attracted attention due to its insulinmimetic *** is released from a variety of sources,including visceral fat and macrophages,and it influences glucose metabolism and increases *** relationship between visfatin and IR in obesity is *** a result,the purpose of this review was to better understand the role of visfatin in glucose homeostasis and to review the literature on the association between visfatin levels and IR,cardiovascular diseases,and renal diseases in obesity.

关键词： Homeostatic model assessment for insulin resistance Insulin resistance Obesity Visfatin pre-B cell colony enhancing factor Nicotinamide phosphoribosyl-transferase enzyme Diabetes Adipocytokines

Machine learning-based seismic assessment of framed structures with soil-structure interaction

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Frontiers of Structural and Civil Engineering 2023年第2期17卷 205-223页

作者： mohamed NOURELDIN Tabish ali Jinkoo KIM Department of Global Smart City Sungkyunkwan UniversitySuwon 16419Korea

The objective of the current study is to propose an expert system framework based on a supervised machine learning technique(MLT)to predict the seismic performance of low-to mid-rise frame structures considering soil-structure interaction(SSI).The methodology of the framework is based on examining different MLTs to obtain the highest possible accuracy for *** the MLT,a sensitivity analysis was conducted on the main SSI parameters to select the most effective input *** limit state criteria were used for the seismic evaluation within the process.A new global seismic assessment ratio was introduced that considers both serviceability and strength aspects by utilizing three different engineering demand parameters(EDPs).The proposed framework is novel because it enables the designer to seismically assess the structure,while simultaneously considering different EDPs and multiple limit ***,the framework provides recommendations for building component design based on the newly introduced global seismic assessment ratio,which considers different levels of seismic *** proposed framework was validated through comparison using non-linear time history(NLTH)*** results show that the proposed framework provides more accurate results than conventional ***,the generalization potential of the proposed framework was tested by investigating two different types of structural irregularities,namely,stiffness and mass *** results from the framework were in good agreement with the NLTH analysis results for the selected case studies,and peak ground acceleration(PGA)was found to be the most influential input parameter in the assessment process for the case study models *** proposed framework shows high generalization potential for low-to mid-rise structures.

关键词： seismic hazard artificial neural network soil-structure interaction seismic analysis

An Optimized Ensemble Model for Prediction the Bandwidth of Metamaterial Antenna

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Computers, Materials & Continua 2022年第4期71卷 199-213页

作者： Abdelhameed ibrahim Hattan F.Abutarboush ali Wagdy mohamed Mohamad Fouad El-Sayed M.El-kenawy Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Electrical Engineering Department College of EngineeringTaibah UniversityMedina42353Saudi Arabia Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Wireless Intelligent Networks Center(WINC) School of Engineering and Applied SciencesNile UniversityGizaEgypt Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyEgypt

Metamaterial Antenna is a special class of antennas that uses metamaterial to enhance their *** size affects the quality factor and the radiation loss of the *** antennas can overcome the limitation of bandwidth for small *** learning(ML)model is recently applied to predict antenna *** can be used as an alternative approach to the trial-and-error process of finding proper parameters of the simulated *** accuracy of the prediction depends mainly on the selected *** models combine two or more base models to produce a better-enhanced *** this paper,a weighted average ensemble model is proposed to predict the bandwidth of the Metamaterial *** base models are used namely:Multilayer Perceptron(MLP)and Support Vector Machines(SVM).To calculate the weights for each model,an optimization algorithm is used to find the optimal weights of the *** Group-Based Cooperative Optimizer(DGCO)is employed to search for optimal weight for the base *** proposed model is compared with three based models and the average ensemble *** results show that the proposed model is better than other models and can predict antenna bandwidth efficiently.

关键词： Metamaterial antenna machine learning ensemble model multilayer perceptron support vector machines

A Multi-Level Selective Maintenance Strategy Combined to Data Mining Approach for Multi-Component System Subject to Propagated Failures

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Journal of Systems Science and Systems Engineering 2022年第3期31卷 313-337页

作者： mohamed ali Kammoun Zied Hajej Nidhal Rezg Universite de Lorraine LGIPMF-57000 MetzFrance Ecole poly technique du Groupe Honoris United Universities-Tunisia

In several industrial fields like air transport,energy industry and military domain,maintenance actions are carried out during downtimes in order to maintain the reliability and availability of production *** such a circumstance,selective maintenance strategy is considered the reliable solution for selecting the faulty components to achieve the next mission without *** this paper,a novel multi-level decision making approach based on data mining techniques is investigated to determine an optimal selective maintenance *** the first-level,the age acceleration factor and its impact on the component nominal age are used to establish the local *** first decision making employed K-means clustering algorithm that exploited the historical maintenance *** on the first-level intervention plan,the remaining-levels identify the stochastic dependence among components by relying upon Apriori association rules algorithm,which allows to discover of the failure occurrence *** addition,at each decision making level,an optimization model combined to a set of exclusion rules are called to supply the optimal selective maintenance plan within a reasonable time,minimizing the total maintenance cost under a required reliability *** illustrate the robustness of the proposed strategy,numerical examples and a FMS real study case have been solved.

关键词： Selective maintenance stochastic dependence age acceleration factor data mining flexible manufacturing system