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Sport and exercise during viral acute respiratory illness——Time to revisit

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Journal of Sport and Health Science 2024年第5期13卷 663-665页

作者： Olli Ruuskanen Maarit Valtonen Matti Waris Raakel Luoto Olli JHeinonen department of Pediatrics and Adolescent Medicine Turku University Hospital and University of TurkuTurku 20521Finland Finnish Institute of high performance Sport KIHU Jyvaskyla 40700Finland Institute of Biomedicine University of Turku and Department of Clinical VirologyTurku University HospitalTurku 20520Finland Paavo Nurmi Centre and Unit for Health and Physical Activity University of TurkuTurku 20520Finland

Athletes are commonly advised not to compete or train during major symptoms of a viral acute respiratory illness(ARI),which most commonly is a common *** has been traditionally thought that heavy physical stress could induce the worsening of symptoms of ARI and possibly cause potentially severe complications like myocarditis or sudden cardiac death(SCD).In addition,viral ARI may decrease athlete's performance.1 These concerns have been recently stressed during the coronavirus disease 2019(COVID-19)pandemic.2 However,it is anecdotally well-known that athletes commonly compete while experiencing common colds,most commonly due to picornaviral *** this perspective,we discuss what is known or not known regarding the risks of exercising during the viral ARI.

关键词： traditionally illness tally

Unleashing the Power of Bio-based Thermotropic Liquid Crystal Modifiers:Toughening and Reinforcing Petroleum-based Epoxy Resin without Compromising Other Properties

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Chinese Journal of Polymer Science 2024年第8期42卷 1093-1102页

作者： Qing-Yun Lu Hong-Wei Gu Jia-Hui Li Qian-Qian Fan Bei-Tao Liu Yan Kou Xi-Gao Jian Zhi-Huan Weng State Key Laboratory of Fine Chemicals Frontiers Science Center for Smart MaterialsLiaoning Technology Innovation Center of High Performance Resin MaterialsDepartment of Polymer Science&EngineeringDalian University of TechnologyDalian 116024China Thermochemistry Laboratory Liaoning Province Key Laboratory of Thermochemistry for Energy and MaterialsDalian National Laboratory for Clean EnergyDalian Institute of Chemical PhysicsChinese Academy of SciencesDalian 116023China

Toughening the petroleum-based epoxy resin blends with bio-based modifiers without compromising their modulus,mechanical strength,and other properties is still a big challenge in view of the *** this study,a bio-based liquid crystal epoxy resin(THMT-E P)with an s-triazine ring structure was utilized to modify a petroleum-based bisphenol A epoxy resin(E51)with 4,4'-diaminodiphenylsulfone(DDS)as a curing agent,and the blended systems were evaluated for their thermal stability,mechanical properties,and flame *** results showed that the impact strength of the blended system initially increased and then decreased with the increase in THMT-EP content,and it reached the a maximum value of 26.5 kJ/m^(2)when the THMT-EP content was 5%,which was 31.2%higher than that of E51/***,the flexural strength,modulus,and glass transition tem perature of the blended system were all simultaneously improved with the addition of *** the same time,the addition of THMT-EP enhanced the flame retardancy of the system by increasing the char yield at 700℃and decreasing the peak heat release rate and total heat release *** work paves the way for a more sustainable improvement in the comprehensive performance of epoxy resin.

关键词： Epoxy resin Toughening Bio-based Thermotropic liquid crystal

A Robust Method of Bipolar Mental Illness Detection from Facial Micro Expressions Using Machine Learning Methods

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Intelligent Automation & Soft computing 2024年第1期39卷 57-71页

作者： Ghulam Gilanie Sana Cheema Akkasha Latif AnumSaher Muhammad Ahsan Hafeez Ullah Diya Oommen department of Artificial Intelligence Faculty of ComputingThe Islamia University of BahawalpurBahawalpur63100Pakistan Biophotonics Imaging Techniques Laboratory Institute of PhysicsThe Islamia University of BahawalpurBahawalpur63100Pakistan West high School Salt Lake CityUT84103USA

Bipolar disorder is a serious mental condition that may be caused by any kind of stress or emotional upset experienced by the *** affects a large percentage of people globally,who fluctuate between depression and mania,or vice versa.A pleasant or unpleasant mood is more than a reflection of a state of ***,it is a difficult task to analyze through physical examination due to a large patient-psychiatrist ratio,so automated procedures are the best options to diagnose and verify the severity of *** this research work,facial microexpressions have been used for bipolar detection using the proposed Convolutional Neural Network(CNN)-based *** Action Coding System(FACS)is used to extract micro-expressions called Action Units(AUs)connected with sad,happy,and angry *** have been conducted on a dataset collected from Bahawal Victoria Hospital,Bahawalpur,Pakistan,Using the Patient Health Questionnaire-15(PHQ-15)to infer a patient’s mental *** experimental results showed a validation accuracy of 98.99%for the proposed CNN modelwhile classification through extracted featuresUsing SupportVectorMachines(SVM),K-NearestNeighbour(KNN),and Decision Tree(DT)obtained 99.9%,98.7%,and 98.9%accuracy,***,the outcomes demonstrated the stated method’s superiority over the current best practices.

关键词： Bipolar mental illness detection facial micro-expressions facial landmarked images

Intelligent Machine Learning Based Brain Tumor Segmentation through Multi-Layer Hybrid U-Net with CNN Feature Integration

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Computers, Materials & Continua 2024年第4期79卷 1301-1317页

作者： Sharaf J.Malebary department of Information Technology Faculty of Computing and Information TechnologyKing Abdulaziz UniversityP.O.Box 344Rabigh21911Saudia Arabia

Brain tumors are a pressing public health concern, characterized by their high mortality and morbidity ***, the manual segmentation of brain tumors remains a laborious and error-prone task, necessitatingthe development of more precise and efficient methodologies. To address this formidable challenge, we proposean advanced approach for segmenting brain tumorMagnetic Resonance Imaging (MRI) images that harnesses theformidable capabilities of deep learning and convolutional neural networks (CNNs). While CNN-based methodshave displayed promise in the realm of brain tumor segmentation, the intricate nature of these tumors, markedby irregular shapes, varying sizes, uneven distribution, and limited available data, poses substantial obstacles toachieving accurate semantic segmentation. In our study, we introduce a pioneering Hybrid U-Net framework thatseamlessly integrates the U-Net and CNN architectures to surmount these challenges. Our proposed approachencompasses preprocessing steps that enhance image visualization, a customized layered U-Net model tailoredfor precise segmentation, and the inclusion of dropout layers to mitigate overfitting during the training ***, we leverage the CNN mechanism to exploit contextual information within brain tumorMRI images,resulting in a substantial enhancement in segmentation *** experimental results attest to the exceptionalperformance of our framework, with accuracy rates surpassing 97% across diverse datasets, showcasing therobustness and effectiveness of our approach. Furthermore, we conduct a comprehensive assessment of ourmethod’s capabilities by evaluating various performance measures, including the sensitivity, Jaccard-index, andspecificity. Our proposed model achieved 99% accuracy. The implications of our findings are profound. Theproposed Hybrid U-Net model emerges as a highly promising diagnostic tool, poised to revolutionize brain tumorimage segmentation for radiologists and clinician

关键词： Brain tumor Hybrid U-Net CLAHE transfer learning MRI images

Improved Dynamic Johnson Sequencing Algorithm(DJS)in Cloud computing Environment for Efficient Resource Scheduling for Distributed Overloading

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Journal of Systems Science and Systems Engineering 2024年第4期33卷 391-424页

作者： Anurag Sinha Pallab Banerjee Sharmistha Roy Nitasha Rathore Narendra Pratap Singh Mueen Uddin Maha Abdelhaq Raed Alsaqour department of Computer Science Engineering ICFAI Tech SchoolICFAI UniversityJharkhandRanchi834004India department of Computer Science Engineering Amity UniversityJharkhandRanchi835303India department of computing and Information Technology Usha Martin UniversityRanchi835103India department of Information Technology Bharti Vidyapeeth’s College of EngineeringPaschim ViharNew DelhiIndia department of CSE Delhi UniversityNew DelhiIndia College of computing and Information Technology University of Doha for Science and TechnologyDoha24449Qatar department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdurrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia department of Information Technology College of Computing and InformaticsSaudi Electronic University93499RiyadhSaudi Arabia

This study introduces an innovative approach to optimize cloud computing job distribution using the Improved Dynamic Johnson Sequencing Algorithm(DJS).Emphasizing on-demand resource sharing,typical to Cloud Service Providers(CSPs),the research focuses on minimizing job completion delays through efficient task *** Johnson’s rule from operations research,the study addresses the challenge of resource availability post-task *** advocates for queuing models with multiple servers and finite capacity to improve job scheduling models,subsequently reducing wait times and queue *** Dynamic Johnson Sequencing Algorithm and the M/M/c/K queuing model are applied to optimize task sequences,showcasing their efficacy through comparative *** research evaluates the impact of makespan calculation on data file transfer times and assesses vital performance indicators,ultimately positioning the proposed technique as superior to existing approaches,offering a robust framework for enhanced task scheduling and resource allocation in cloud computing.

关键词： First come first served(FCFS)scheduling round robin task scheduling queuing model Johnson scheduling algorithm

Effect of rare earth on primary carbides in H13 die steel and their addition method:a review

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Journal of Iron and Steel Research International 2024年第3期31卷 531-551页

作者： Jing-feng Wang Lin-zhu Wang Chao-yi Chen Xiang Wang Fei Zhao School of Materials and Metallurgy Guizhou UniversityGuiyang 550025GuizhouChina Zhengzhou Railway Vocational and Technical College Zhengzhou 450000HenanChina Guizhou Provincial University Key Laboratory of high performance Battery Materials Guizhou UniversityGuiyang 550025GuizhouChina Shougang Guiyang Special Steel Co. Guiyang 550005GuizhouChina

Larger-sized primary carbides lead to stress concentration during the application of H13 hot-work die steel,resulting in microcracks and fatigue *** earth was usually added to modify the carbides and *** existing literature is reviewed on the effect of rare earth on primary carbides in H13 steel.A comprehensive review on the effect of rare earth on the characteristics of primary carbides,i.e.,number,size,morphology,and thermal stability in H13 steel,was *** precipitation mechanism and nucleation of primary carbides with rare earth were *** position and form of rare earth in steel and their effects on alloying elements segregation were *** addition techniques of rare earth in H13 steel were compared,and the prospects for other uncommon rare earth and emerging technology were *** on the current references,it can be known that adding rare earth facilitated refined and dispersed primary *** size of primary carbides would be reduced,and their morphology would be improved because the rare earth inclusions formed in H13 steel can act as nucleation cores forγ-Fe orδ-Fe,refining the dendritic ***,the number of primary carbides at grain boundaries would be significantly ***,rare earth had little impact on thermal *** nucleation of primary carbides tended to be inhibited due to the modification of inclusions by rare earth which were likely to be nucleation cores for primary *** earth had been reported to affect the mechanism and process of primary carbide ***,the addition of rare earth can inhibit the segregation of alloying elements and carbon diffusion by ***,laboratory experiments and theoretical calcu-lations need to be conducted to study the states and evolution of rare earth steels.

关键词： Rare earth H13 die steel Primary carbide Nucleation Dendritic structure

Path signature-based XAI-enabled network time series classification

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Science China(Information Sciences) 2024年第7期67卷 91-106页

作者： Le SUN Yueyuan WANG Yongjun REN Feng XIA department of Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology(CICAEET) Nanjing University of Information Science and Technology School of computing Technologies Royal Melbourne Institute of Technology

Classifying network time series(NTS) is crucial for automating network administration and ensuring cyberspace security. It enables the detection of anomalies, the identification of network attacks,and the monitoring of performance issues, thereby providing valuable support for network protection and optimization. However, modern communication networks pose challenges for NTS classification *** include handling large-scale and complex NTS data, extracting features from intricate datasets, and addressing explainability requirements. These challenges are particularly pronounced for complex 5G networks. Notably, explainability has become crucial for the widespread deployment of network automation for 5G networks and beyond. To tackle these challenges, we propose a path-signature-based NTS classification model called recurrent signature(Recur Sig). This innovative model is designed to overcome the time-consuming feature selection problem by utilizing deep-learning(DL) techniques. Additionally, it provides a solution for addressing the black-box issue associated with DL models in network automation systems(NAS) by incorporating an explainable classification approach. Extensive experimentation on various public datasets demonstrates that Recur Sig outperforms existing models in accuracy and explainability. The results indicate its potential for application in cyberspace security and automated network management, offering an explainable solution for network protection and optimization.

关键词： network time series classification explainable artificial intelligence path signature automated network management recurrent neural network

Neutrophils in Atlantic salmon(Salmo salar L.)are MHC class II^(+)and secret IL-12p40 upon bacterial exposure

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Aquaculture and Fisheries 2024年第2期9卷 144-153页

作者： Gyri Teien Haugland Anita Rønneseth Lene Gundersen Harald SæbøLunde Kaja Nordland Heidrun Inger Wergeland department of Biological Sciences Bergen High-Technology CentreUniversity of BergenBergen5020Norway

Antigen-presentation via major histocompatibility complex(MHC)to T cells is the key event to initiate adaptive immune *** teleosts,as in mammals,the main types of professional antigen-presenting cells(APCs)are dendritic cells(DCs),monocytes/macrophages,and B *** the current study,flow cytometry,immunostaining and qPCR have been used to show that neutrophils in the teleost fish Atlantic salmon(Salmo salar L.)have antigen-presenting *** neutrophils were positive for MHC class II,CD83 and CD80/86,and upon in vitro bacterial exposure,gene expression analysis of purified neutrophils showed that IL-12p40,which is essential for proliferation of naïve T cells,was highly upregulated at both 6 and 24 h post bacterial *** on presence of MHC class II and upregulation of molecules involved in antigen presentation and T cell activation,we suggest that neutrophils in Atlantic salmon have potential to function as professional *** work makes an important basis for further exploring the potential of using neutrophils to develop new,targeted immunoprophylactic measures.

关键词： Granulocytes Antigen presenting cells Major histocompatibility complex T cell activation B cells CD83 CD80/86 MHC classⅡ

Caching Strategies in NDN Based Wireless Ad Hoc Network:A Survey

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Computers, Materials & Continua 2024年第7期80卷 61-103页

作者： Ahmed Khalid Rana Asif Rehman Byung-Seo Kim department of Computer Science FAST School of ComputingNational University of Computer and Emerging SciencesLahore54000Pakistan department of Software and Communications Engineering Hongik UniversitySejong City30016Republic of Korea

Wireless Ad Hoc Networks consist of devices that are wirelessly *** Ad Hoc Networks(MANETs),Internet of Things(IoT),and Vehicular Ad Hoc Networks(VANETs)are the main domains of wireless ad hoc *** is used in wireless ad hoc *** is based on Transmission Control Protocol(TCP)/Internet Protocol(IP)network where clients and servers interact with each other with the help of IP in a pre-defined *** fetches data from a fixed *** redundancy,mobility,and location dependency are the main issues of the IP network *** these factors result in poor performance of wireless ad hoc *** main disadvantage of IP is that,it does not provide in-network ***,there is a need to move towards a new network that overcomes these *** Data Network(NDN)is a network that overcomes these *** is a project of Information-centric Network(ICN).NDN provides in-network caching which helps in fast response to user *** NDN in wireless ad hoc network provides many benefits such as caching,mobility,scalability,security,and *** considering the certainty,in this survey paper,we present a comprehensive survey on Caching Strategies in NDN-based Wireless *** cachingmechanism-based results are also *** the last,we also shed light on the challenges and future directions of this promising field to provide a clear understanding of what caching-related problems exist in NDN-based wireless ad hoc networks.

关键词： Content centric network Internet of Things mobile ad hoc network named data network vehicular ad hoc network