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Explainable Conformer Network for Detection of COVID-19 Pneumonia from Chest CT Scan: From Concepts toward Clinical Explainability

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Computers, Materials & Continua 2024年第1期78卷 1171-1187页

作者： mohamed Abdel-Basset Hossam Hawash mohamed Abouhawwash S.S.Askar Alshaimaa A.Tantawy Faculty of Computers and Informatics Zagazig UniversityZagazig44519Egypt Department of Computational Mathematics Scienceand Engineering(CMSE)Michigan State UniversityEast LansingMI48824USA Department of Mathematics Faculty of ScienceMansoura UniversityMansoura35516Egypt Department of Statistics and Operations Research College of ScienceKing Saud UniversityP.O.Box 2455Riyadh11451Saudi Arabia

The early implementation of treatment therapies necessitates the swift and precise identification of COVID-19 pneumonia by the analysis of chest CT *** study aims to investigate the indispensable need for precise and interpretable diagnostic tools for improving clinical decision-making for COVID-19 *** paper proposes a novel deep learning approach,called Conformer Network,for explainable discrimination of viral pneumonia depending on the lung Region of Infections(ROI)within a single modality radiographic CT ***,an efficient U-shaped transformer network is integrated for lung image ***,a robust transfer learning technique is introduced to design a robust feature extractor based on pre-trained lightweight Big Transfer(BiT-L)and finetuned on medical data to effectively learn the patterns of infection in the input ***,this work presents a visual explanation method to guarantee clinical explainability for decisions made by Conformer *** evaluation of real-world CT data demonstrated that the diagnostic accuracy of ourmodel outperforms cutting-edge studies with statistical *** Conformer Network achieves 97.40% of detection accuracy under cross-validation *** model not only achieves high sensitivity and specificity but also affords visualizations of salient features contributing to each classification decision,enhancing the overall transparency and trustworthiness of our *** findings provide obvious implications for the ability of our model to empower clinical staff by generating transparent intuitions about the features driving diagnostic decisions.

关键词： Deep learning COVID-19 multi-modal medical image fusion diagnostic image fusion

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Treatment-induced neuroendocrine prostate cancer and de novo neuroendocrine prostate cancer:Identification,prognosis and survival,genetic and epigenetic factors

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World Journal of Clinical Cases 2024年第13期12卷 2143-2146页

作者： mohamed Wishahi Department of Urology Theodor Bilharz Research InstituteCairo 12411Egypt

Neuroendocrine prostate cancer(NEPC)shows an aggressive behavior compared to prostate cancer(PCa),also known as prostate *** foci in PCa can harbor genetic alternation that can arise in a heterogeneity of prostate *** may arise de novo or develop following androgen deprivation therapy(ADT).NEPC that arise following ADT has the nomenclature“treatmentemerging/induced NEPC(t-NEPC)”.t-NEPC would be anticipated in castration resistant prostate cancer(CRPC)and metastatic PCa.t-NEPC is characterized by low or absent androgen receptor(AR)expression,independence of AR signaling,and gain of neuroendocrine phenotype.t-NEPC is an aggressive metastatic tumor,develops from PCa in response to drug induced ADT,and shows very short response to conventional therapy.t-NEPC occurs in 10%-17%of patients with *** novo NEPC is rare and is accounting for less than 2%of all *** molecular mechanisms underlying the trans-differentiation from CRPC to t-NEPC are not fully *** kinase 1 plays a significant role in t-NEPC *** neuroendocrine markers:Synaptophysin,chromogranin A,and insulinoma associated protein 1(INSM1)are expressed in t-NEPC,they are non-specific for diagnosis,prognosis,and follow-up of therapy.t-NEPC shows enriched genomic alteration in tumor protein P53(TP53)and retinoblastoma 1(RB1).There are evidences suggest that t-NEPC might develop through epigenetic *** are genomic,epigenetic,and transcriptional alterations that are reported to be involved in development of ***-outs of TP53 and RB1 were found to contribute in development of *** is resistant to immunotherapy,and at present there are running trials to approach immunotherapy for PCa,CRPC,and t-NEPC.

关键词： Prostate cancer Neuroendocrine carcinoma Treatment induced neuroendocrine prostate cancer Androgen deprivation therapy Genetic and epigenetic factors Castration resistant prostate cancer De novo neuroendocrine prostate cancer

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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

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A review on the multi-scaled structures and mechanical/thermal properties of tool steels fabricated by laser powder bed fusion additive manufacturing

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International Journal of Minerals,Metallurgy and Materials 2024年第5期31卷 1048-1071页

作者： Huajing Zong Nan Kang Zehao Qin mohamed El Mansori Arts et Metiers Institute of Technology MSMPHESAM UniversitéChâlons-en-Champagne F-51006France Texas A&M Engineering Experiment Station Institute for Manufacturing SystemsCollege Station TX77843USA

The laser powder bed fusion(LPBF) process can integrally form geometrically complex and high-performance metallic parts that have attracted much interest,especially in the molds *** appearance of the LPBF makes it possible to design and produce complex conformal cooling channel systems in ***,LPBF-processed tool steels have attracted more and more *** complex thermal history in the LPBF process makes the microstructural characteristics and properties different from those of conventional manufactured tool *** paper provides an overview of LPBF-processed tool steels by describing the physical phenomena,the microstructural characteristics,and the mechanical/thermal properties,including tensile properties,wear resistance,and thermal *** microstructural characteristics are presented through a multiscale perspective,ranging from densification,meso-structure,microstructure,substructure in grains,to ***,a summary of tool steels and their challenges and outlooks are introduced.

关键词： additive manufacturing laser powder bed fusion tool steel multi-scaled structure mechanical properties thermal properties

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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

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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

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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,satellite,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 approximately 0.9.

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

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Comparative study between three carbonaceous nanoblades and nanodarts for antimicrobial applications

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Journal of Environmental Sciences 2024年第2期136卷 594-605页

作者： mohamed S.Selim Ahmed M.Azzam mohamed A.Shenashen Shimaa A.Higazy Bayaumy B.Mostafa Sherif A.El-Safty National Institute for Materials Science(NIMS) 1-2-1 SengenTsukuba-ShiIbaraki-Ken 305-0047Japan Petroleum Application Department Egyptian Petroleum Research InstituteNasr City 11727Egypt Department of Environmental Research Theodor Bilharz Research InstituteGizaEgypt

The design of nanostructured materials occupies a privileged position in the development and management of affordable and effective technology in the antibacterial ***,we discuss the antimicrobial properties of three carbonaceous nanoblades and nanodarts materials of graphene oxide(GO),reduced graphene oxide(RGO),and single-wall carbon nanotubes(SWCNTs)that have a mechano-bactericidal effect,and the ability to piercing or slicing bacterial *** demonstrate the significance of size,morphology and composition on the antibacterial activity mechanism,the designed nanomaterials have been *** minimum inhibitory concentration(MIC),standard agar well diffusion,and transmission electron microscopy were utilized to evaluate the antibacterial activity of GO,RGO,and *** on the evidence obtained,the three carbonaceous materials exhibit activity against all microbial strains tested by completely encapsulating bacterial cells and causing morphological disruption by degrading the microbial cell membrane in the order of RGO>GO>*** of the external cell wall structure and outer membrane proteins,the synthesized carbonaceous nanomaterials exhibited higher antibacterial activity against Gram-positive bacterial strains than Gram-negative and fungal *** had the lowest MIC values(0.062,0.125,and 0.25 mg/mL against ***,***,and ***,respectively),as well as minimum fungal concentrations(0.5 mg/mL for both *** and ***).At 12 hr,the cell viability values against tested microbial strains were completely *** lysis and death occurred as a result of severe membrane damage caused by microorganisms perched on RGO *** work gives an insight into the design of effective graphene-based antimicrobial materials for water treatment and remediation.

关键词： Antimicrobial properties Nanoblades Mechano-bactericidal effect RGO nanosheets Gram-positive bacteria Cell viability

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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

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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

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