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Regulating microstructure and composition by carbonizing in-situ grown metal-organic frameworks on cotton fabrics for boosting electromagnetic wave absorption

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Nano Research 2024年第8期17卷 7290-7300页

作者： Jie Jin Hongsen Long Hu Liu Yan Guo Tiantian Bai Ben Bin Xu Mohammed A.Amin Hua Qiu mohamed H.Helal Chuntai Liu Changyu Shen Zeinhom M.el-Bahy Zhanhu Guo State Key Laboratory of Structural Analysis Optimization and CAE Software for Industrial EquipmentNational Engineering Research Center for Advanced Polymer Processing TechnologyZhengzhou UniversityZhengzhou 450002China China State Key Laboratory of Powder Metallurgy Central South UniversityChangsha 410000China School of electronic Engineering North China University of Water Resources and Electric PowerZhengzhou 450046China Complex Conditions of High-end Tire Technology Innovation Center Shuguang Rubber Industry Research&Design Institute Co.LtdGuilin 541004China Integrated Composites Lab Department of Mechanical and Civil EngineeringNorthumbria UniversityNewcastle Upon TyneNE18STUK Department of Chemistry College of ScienceTaif UniversityP.O.Box 11099Taif 21944Saudi Arabia Shaanxi Key Laboratory of Macromolecular Science and Technology School of Chemistry and Chemical EngineeringNorthwestern Polytechnical UniversityXi’an 710072China Department of Chemistry Faculty of Arts and ScienceNorthern Border UniversityRafha 73213Saudi Arabia Department of Chemistry Faculty of ScienceAl-Azhar UniversityNasr City 11884CairoEgypt

High-temperature carbonized metal-organic frameworks(MOFs)derivatives have demonstrated their superiority for promising electromagnetic wave(EMW)absorbers,but they still suffer from limited EMW absorption capacity and narrow *** the advantage of microstructure and chemical composition regulation for the design of EMW absorber,hierarchical heterostructured MoS_(2)/CoS_(2)-Co_(3)O_(4)@cabonized cotton fabric(CF)(MCC@CCF)is prepared by growing ZIF-67 MOFs onto CF surface,chemical etching,and *** from the dual loss mechanism of magnetic-dielectric multicomponent carbonized MOFs,chemical etching and carbonization process can effectively introduce abundant micro-gap structure that can result in better impedance matching and stronger absorption capacity via internal reflection,doped heteroatoms(Mo,N,S)to supply additional dipolar polarization loss,and numerous heterointerfaces among MoS_(2),CoS_(2),Co_(3)O_(4),and CCF that produce promoted conduction loss and interfacial polarization ***,a minimal reflection loss of−52.87 dB and a broadest effective absorption bandwidth of 6.88 GHz were achieved via tunning the sample thickness and filler loading,showing excellent EMW absorption *** research is of great value for guiding the research on MOFs derivatives based EMW absorbing materials.

关键词： metal-organic frameworks hierarchical structure chemical etching sulfurization electromagnetic wave absorption

TFN-FICFM:sEMG-Based Gesture Recognition Using Temporal Fusion Network and Fuzzy Integral-based Classifier Fusion

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Journal of Bionic Engineering 2024年第4期21卷 1878-1891页

作者： Fo Hu Kailun He Mengyuan Qian mohamed Amin Gouda College of Information Engineering Zhejiang University of TechnologyHangzhou310023China Department of Mechanical Engineering and Automation Northeastern UniversityShenyang110819China

Surface electromyography(sEMG)-based gesture recognition is a key technology in the field of human–computer ***,existing gesture recognition methods face challenges in effectively integrating discriminative temporal feature representations from sEMG *** this paper,we propose a deep learning framework named TFN-FICFM comprises a Temporal Fusion Network(TFN)and Fuzzy Integral-Based Classifier Fusion method(FICFM)to improve the accuracy and robustness of gesture ***,we design a TFN module,which utilizes an attention-based recurrent multi-scale convolutional module to acquire multi-level temporal feature representations and achieves deep fusion of temporal features through a feature pyramid ***,the deep-fused temporal features are utilized to generate multiple sets of gesture category prediction confidences through a feedback ***,we employ FICFM to perform fuzzy fusion on prediction confidences,resulting in the ultimate *** study conducts extensive comparisons and ablation studies using the publicly available datasets Ninapro DB2 and *** demonstrate that the TFN-FICFM model outperforms state-of-the-art methods in classification *** research can serve as a benchmark for sEMG-based gesture recognition and related deep learning modeling.

关键词： Gesture recognition sEMG Deep learning Temporal fusion Fuzzy fusion

Primary gastroduodenal tuberculosis presenting as gastric outlet obstruction:A case report and review of literature

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World Journal of Clinical Cases 2024年第8期12卷 1536-1543页

作者： Abdihamid mohamed Ali Yahye Garad mohamed Abdirahman Ahmed Mohamud Abdulkadir Nor mohamed mohamed Rage Ahmed Ismail Mohamud Abdullahi Tuba Saydam Department of General Surgery Mogadishu Somali Turkey Recep Tayyip Erdogan Training and Research HospitalMogadishu 2526Somalia Department of Radiology Mogadishu Somali TurkeyTraining and Research HospitalMogadishu 2526Somalia Department of Pathology Mogadishu Somali Turkey Recep Tayyip Erdogan Training and Research HospitalMogadishu 2526Somalia

BACKGROUND Mycobacterium tuberculosis(TB)is the causative agent of TB,a chronic granulo-matous *** disease is prevalent in low-income countries,posing a significant global health *** TB is one of the three *** disease can mimic other intra-abdominal conditions,leading to delayed diagnosis owing to the absence of specific *** gastric outlet obs-truction(GOO)remains a frequent complication,its incidence has declined with the advent of proton pump inhibitors and Helicobacter pylori eradication *** TB can cause upper gastrointestinal hemorrhage,obstruction,and malignancy-like *** SUMMARY A 23-year-old male presented with recurrent epigastric pain,distension,nausea,vomiting,and weight loss,prompting a referral to a gastroenterologist *** examination revealed distorted gastric mucosa and signs of chronic ***,treatment was interrupted,possibly owing to vomiting or comorbidities such as human immunodeficiency virus infection or *** surgical intervention revealed a dilated stomach and diffuse thickening of the duodenal *** revealed gastric wall effacement with *** Primary gastric TB is rare,frequently leading to *** its rarity,suspicions should be promptly raised when encountering relevant symptoms,often requiring surgical intervention for diagnosis and treatment.

关键词： Tuberculosis Gastrointestinal tuberculosis Gastric outlet obstruction Gastroduodenal tuberculosis Case report

Machine Learning Enabled Novel Real-Time IoT Targeted DoS/DDoS Cyber Attack Detection System

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Computers, Materials & Continua 2024年第9期80卷 3655-3683页

作者： Abdullah Alabdulatif Navod Neranjan Thilakarathne mohamed Aashiq Department of Cybersecurity College of ComputerQassim UniversityBuraydah51452Saudi Arabia Department of ICT Faculty of TechnologyUniversity of ColomboColombo00700Sri Lanka Department of Computer Science and Engineering Faculty of EngineeringSouth Eastern University of Sri LankaOluvil32360Sri Lanka

The increasing prevalence of Internet of Things(IoT)devices has introduced a new phase of connectivity in recent years and,concurrently,has opened the floodgates for growing cyber *** the myriad of potential attacks,Denial of Service(DoS)attacks and Distributed Denial of Service(DDoS)attacks remain a dominant concern due to their capability to render services inoperable by overwhelming systems with an influx of *** IoT devices often lack the inherent security measures found in more mature computing platforms,the need for robust DoS/DDoS detection systems tailored to IoT is paramount for the sustainable development of every domain that IoT *** this study,we investigate the effectiveness of three machine learning(ML)algorithms:extreme gradient boosting(XGB),multilayer perceptron(MLP)and random forest(RF),for the detection of IoTtargeted DoS/DDoS attacks and three feature engineering methods that have not been used in the existing stateof-the-art,and then employed the best performing algorithm to design a prototype of a novel real-time system towards detection of such DoS/DDoS *** CICIoT2023 dataset was derived from the latest real-world IoT traffic,incorporates both benign and malicious network traffic patterns and after data preprocessing and feature engineering,the data was fed into our models for both training and validation,where findings suggest that while all threemodels exhibit commendable accuracy in detectingDoS/DDoS attacks,the use of particle swarmoptimization(PSO)for feature selection has made great improvements in the performance(accuracy,precsion recall and F1-score of 99.93%for XGB)of the ML models and their execution time(491.023 sceonds for XGB)compared to recursive feature elimination(RFE)and randomforest feature importance(RFI)*** proposed real-time system for DoS/DDoS attack detection entails the implementation of an platform capable of effectively processing and analyzing network traffic in *** inv

关键词： Machine learning Internet of Things(IoT),DoS,DDoS cybersecurity intrusion prevention network security,feature optimization,sustainability

Shear Let Transform Residual Learning Approach for Single-Image Super-Resolution

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Computers, Materials & Continua 2024年第5期79卷 3193-3209页

作者： Israa Ismail Ghada.eltaweel mohamed Meselhy eltoukhy Department of Computer Science Faculty of Computers and InformaticsSuez Canal UniversityIsmailia51422Egypt Department of Information Technology College of Computing and Information Technology at KhulaisUniversity of JeddahJeddahSaudi Arabia

Super-resolution techniques are employed to enhance image resolution by reconstructing high-resolution images from one or more low-resolution ***-resolution is of paramount importance in the context of remote sensing,sa.ellite,aerial,security and surveillance ***-resolution remote sensing imagery is essential for surveillance and security purposes,enabling authorities to monitor remote or sensitive areas with greater *** study introduces a single-image super-resolution approach for remote sensing images,utilizing deep shearlet residual learning in the shearlet transform domain,and incorporating the Enhanced Deep Super-Resolution network(EDSR).Unlike conventional approaches that estimate residuals between high and low-resolution images,the proposed approach calculates the shearlet coefficients for the desired high-resolution image using the provided low-resolution image instead of estimating a residual image between the high-and low-resolution *** shearlet transform is chosen for its excellent sparse approximation ***,remote sensing images are transformed into the shearlet domain,which divides the input image into low and high *** shearlet coefficients are fed into the EDSR *** high-resolution image is subsequently reconstructed using the inverse shearlet *** incorporation of the EDSR network enhances training stability,leading to improved generated *** experimental results from the Deep Shearlet Residual Learning approach demonstrate its superior performance in remote sensing image recovery,effectively restoring both global topology and local edge detail information,thereby enhancing image *** to other networks,our proposed approach outperforms the state-of-the-art in terms of image quality,achieving an average peak signal-to-noise ratio of 35 and a structural similarity index measure of approxima.ely 0.9.

关键词： Super-resolution shearlet transform shearlet coefficients enhanced deep super-resolution network

Insulin resistance as the molecular link between diabetes and Alzheimer's disease

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World Journal of Diabetes 2024年第7期15卷 1430-1447页

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

Diabetes mellitus(DM)and Alzheimer's disease(AD)are two major health concerns that have seen a rising prevalence *** studies have indicated a possible link between DM and an increased risk of developing ***,while primarily known for its role in regulating blood sugar,also plays a vital role in protecting brain *** resistance(IR),especially prevalent in type 2 diabetes,is believed to play a significant role in AD's *** insulin signalling becomes dysfunctional,it can negatively affect various brain functions,making individuals more susceptible to AD's defining features,such as the buildup of beta-amyloid plaques and tau protein *** research suggests that addressing insulin-related issues might help reduce or even reverse the brain changes linked to *** review aims to explore the relationship between DM and AD,with a focus on the role of *** also explores the molecular mechanisms by which IR might lead to brain changes and assesses current treatments that target *** IR's role in the connection between DM and AD offers new possibilities for treatments and highlights the importance of continued research in this interdisciplinary field.

关键词： Alzheimer's disease Insulin resistance Obesity Dementia Diabetes Metabolic syndrome

An inverse method for characterization of dynamic response of 2D structures under stochastic conditions

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Chinese Journal of Aeronautics 2024年第3期37卷 440-455页

作者： Xuefeng LI Abdelmalek ZINE mohamed ICHCHOU Noureddine BOUHADDI Pascal FOSSAT Laboratory of Tribology and Systems Dynamic Central School of LyonEcully 69134France Institut Camille Jordan Central School of LyonEcully 69134France Department of Applied Mechanics University of Burgundy Franche-ComtéBesancon 25000France

The reliable estimation of the wavenumber space(k-space)of the plates remains a longterm concern for acoustic modeling and structural dynamic behavior *** current analyses of wavenumber identification methods are based on the deterministic *** this end,an inverse method is proposed for identifying wave propagation characteristics of twodimensional structures under stochastic conditions,such as wavenumber space,dispersion curves,and band *** proposed method is developed based on an algebraic identification scheme in the polar coordinate system framework,thus named Algebraic K-Space Identification(AKSI)***,a model order estimation strategy and a wavenumber filter are proposed to ensure that AKSI is successfully *** main benefit of AKSI is that it is a reliable and fast method under four stochastic conditions:(A)High level of signal noise;(B)Small perturbation caused by uncertainties in measurement points’coordinates;(C)Non-periodic sampling;(D)Unknown structural *** validate the proposed method,we numerically benchmark AKSI and three other inverse methods to extract dispersion curves on three plates under stochastic *** experiment is then performed on an isotropic steel *** investigations demonstrate that AKSI is a good in-situ k-space estimator under stochastic conditions.

关键词： Inverse method Dispersion relation Wavenumber space Periodic plates Stochastic conditions Wave propagation characterization

A new technique for fault diagnosis in transformer insulating oil based on infrared spectroscopy measurements

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High Voltage 2024年第2期9卷 319-335页

作者： mohamed M.F.Darwish mohamed H.A.Hassan Nagat M.K.Abdel-Gawad Matti Lehtonen Diaa.eldin A.Mansour Department of electrical Engineering Faculty of Engineering at ShoubraBenha UniversityCairoEgypt Department of electrical Engineering and Automation School of Electrical EngineeringAalto UniversityEspooFinland Department of electrical Power Engineering Egypt-Japan University of Science and Technology(E-JUST)New Borg El-Arab CityEgypt Department of electrical Power and Machines Engineering Faculty of EngineeringTanta UniversityTantaEgypt

Condition monitoring of the insulating system within power transformers has a massive importance according to the electrical *** gas analysis(DGA)is frequently used for this ***,DGA lacks the necessary level of accuracy to identify all equipment faults,particularly in their initial stages of ***,it does not have the capability for real-time monitoring and relies on manual sampling and laboratory testing,causing potential delays in fault ***,the interpretation of DGA data necessitates specialised expertise,which may pose difficulties for smaller entities that have limited access to ***,the contribution of this research is to use infrared spectroscopy measurements as a new effective technique substituting the DGA method for fault diagnosis in insulating *** inception faults that were considered in this study were the electrical fault(discharges of high energy)and the thermal fault(300°Cells were crafted especially for serving the simulation processes inside the laboratory for both types of inception ***,six samples of pure paraffinic mineral oil were taken to be degraded in the *** that,all of them besides another sample that were not subjected to any kind of faults were taken to be examined by Fourier transform infrared(FTIR)spectroscopy to obtain an overview of the oil's behaviour in each fault *** that,the FTIR analysis was initially verified utilising the DGA ***,for further affirmation,the dielectric dissipation factor(DDF)for all samples was *** the final analysis,the verification tests provide experimental evidence about the outperformance of this new optical technique in detecting the transformer's inception faults in addition to proving its potential for being a superior alternative to the well-known traditional diagnostic techniques.

关键词： fault diagnosis spectroscopy

Classified VPN Network Traffic Flow Using Time Related to Artificial Neural Network

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Computers, Materials & Continua 2024年第7期80卷 819-841页

作者： Saad Abdalla Agaili mohamed Sefer Kurnaz Department of electrical and Computer Engineering Altinbas UniversityIstanbul34000Turkey

VPNs are vital for safeguarding communication routes in the continually changing cybersecurity ***,increasing network attack complexity and variety require increasingly advanced algorithms to recognize and categorizeVPNnetwork *** present a novelVPNnetwork traffic flowclassificationmethod utilizing Artificial Neural Networks(ANN).This paper aims to provide a reliable system that can identify a virtual private network(VPN)traffic fromintrusion attempts,data exfiltration,and denial-of-service *** compile a broad dataset of la.eled VPN traffic flows from various apps and usage ***,we create an ANN architecture that can handle encrypted communication and distinguish benign from dangerous *** effectively process and categorize encrypted packets,the neural network model has input,hidden,and output *** use advanced feature extraction approaches to improve the ANN’s classification accuracy by leveraging network traffic’s statistical and behavioral *** also use cutting-edge optimizationmethods to optimize network characteristics and *** suggested ANN-based categorization method is extensively tested and *** show the model effectively classifies VPN traffic *** also show that our ANN-based technique outperforms other approaches in precision,recall,and F1-score with 98.79%*** study improves VPN security and protects against new *** VPNtraffic flows effectively helps enterprises protect sensitive data,maintain network integrity,and respond quickly to security *** study advances network security and lays the groundwork for ANN-based cybersecurity solutions.

关键词： VPN network traffic flow ANN classification intrusion detection data exfiltration encrypted traffic feature extraction network security