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Nonlinear wave dispersion in monoatomic chains with lumped and distributed masses:discrete and continuum models

Applied Mathematics and Mechanics(English Edition) 2024年第4期45卷 633-648页

作者： E.GHAVANLOO s.EL-BORGI school of Mechanical Engineering Shiraz UniversityShiraz 71963-16548Iran Mechanical Engineering Program Texas A&M University at QatarDoha 23874Qatar

The main objective of this paper is to investigate the influence of inertia of nonlinear springs on the dispersion behavior of discrete monoatomic chains with lumped and distributed masses.The developed model can represent the wave propagation problem in a non-homogeneous material consisting of heavy inclusions embedded in a matrix.The inclusions are idealized by lumped masses,and the matrix between adjacent inclusions is modeled by a nonlinear spring with distributed masses.Additionally,the model is capable of depicting the wave propagation in bi-material bars,wherein the first material is represented by a rigid particle and the second one is represented by a nonlinear spring with distributed masses.The discrete model of the nonlinear monoatomic chain with lumped and distributed masses is first considered,and a closed-form expression of the dispersion relation is obtained by the second-order Lindstedt-Poincare method(LPM).Next,a continuum model for the nonlinear monoatomic chain is derived directly from its discrete lattice model by a suitable continualization technique.The subsequent use of the second-order method of multiple scales(MMs)facilitates the derivation of the corresponding nonlinear dispersion relation in a closed form.The novelties of the present study consist of(i)considering the inertia of nonlinear springs on the dispersion behavior of the discrete mass-spring chains;(ii)developing the second-order LPM for the wave propagation in the discrete chains;and(iii)deriving a continuum model for the nonlinear monoatomic chains with lumped and distributed masses.Finally,a parametric study is conducted to examine the effects of the design parameters and the distributed spring mass on the nonlinear dispersion relations and phase velocities obtained from both the discrete and continuum models.These parameters include the ratio of the spring mass to the lumped mass,the nonlinear stiffness coefficient of the spring,and the wave amplitude.

关键词： nonlinear mass-spring chain discrete model continuum model LindstedtPoincare method(LPM) method of multiple scales(MMs) dispersion phase velocity

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Enhanced entropy generation and heat transfer characteristics of magnetic nano-encapsulated phase change materials in latent heat thermal energy storage systems

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Applied Mathematics and Mechanics(English Edition) 2024年第6期45卷 1051-1070页

作者： P.s.REDDY P.sREEDEVI Department of Mathematics Rajeev Gandhi Memorial College of Engineering and TechnologyNandyal 518501India

The objective of the current study is to investigate the importance of entropy generation and thermal radiation on the patterns of velocity,isentropic lines,and temperature contours within a thermal energy storage device filled with magnetic nanoencapsulated phase change materials(NEPCMs).The versatile finite element method(FEM)is implemented to numerically solve the governing equations.The effects of various parameters,including the viscosity parameter,ranging from 1 to 3,the thermal conductivity parameter,ranging from 1 to 3,the Rayleigh parameter,ranging from 102 to 3×10^(2),the radiation number,ranging from 0.1 to 0.5,the fusion temperature,ranging from 1.0 to 1.2,the volume fraction of NEPCMs,ranging from 2%to 6%,the stefan number,ranging from 1 to 5,the magnetic number,ranging from 0.1 to 0.5,and the irreversibility parameter,ranging from 0.1 to 0.5,are examined in detail on the temperature contours,isentropic lines,heat capacity ratio,and velocity fields.Furthermore,the heat transfer rates at both the cold and hot walls are analyzed,and the findings are presented graphically.The results indicate that the time taken by the NEPCMs to transition from solid to liquid is prolonged inside the chamber region as the fusion temperatureθf increases.Additionally,the contours of the heat capacity ratio Cr decrease with the increase in the stefan number ste.

关键词： volume fraction of nano-encapsulated phase change material(NEPCM) radiation stefan number heat capacity ratio entropy generation

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Engineering of efficient visible light photocatalysts:Ti_(1-x+y)Cu_(x)La_(y)O_(2)(x=0.03;y=0,0.005,0.01) compositions

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Journal of Rare Earths 2024年第3期42卷 497-505,I0003页

作者： s.M.Yakout A.M.Youssef Inorganic Chemistry Department National Research Centre(NRC)El Buhouth StDokkiCairo12622Egypt

In dye-photocatalysis, widening the wavelengths absorption range of catalysts as well as aborting the recombination of the photoexcited charge carriers(electrons-holes pairs) are of paramount significance.In the current study, we report the photocatalytic characteristics of four compositions composed of TiO_(2),Ti_(0.97)Cu_(0.03)O_(2), Ti_(0.965)Cu_(0.03)La_(0.005)O_(2)and Ti_(0.96)Cu_(0.03)La_(0.01)O_(2)powders for two harmful dyes(Congo red and methylene blue). The X-ray diffraction technique verified the configuration of mixed anatase and rutile phases in pure TiO_(2)and Ti_(0.97)Cu_(0.03)O_(2)powders while Ti_(0.965)Cu_(0.03)La_(0.005)O_(2)and Ti_(0.96)Cu_(0.03)La_(0.01)O_(2)powders possess anatase phase only. The changes of the band gap structure and dimensions of the unit cell volume of TiO_(2)confirm the substitution of Ti^(4+)sites by Cu^(2+)and La^(3+)ions. Remarkable widening of wavelengths absorption with formation of long absorption tails were found in TiO_(2)(3.13 e V) through insertion of La^(3+)plus Cu^(2+)ions. Ti_(0.965)Cu_(0.03)La_(0.005)O_(2)and Ti_(0.96)Cu_(0.03)La_(0.01)O_(2)samples exhibit a visible light band gap of 2.3 and 2.7 e V, respectively. Based on sEM images, incorporation of Cu^(2+)and La^(3+)ions influences the surface morphology of TiO_(2). The resulting Ti_(0.97)Cu_(0.03)O_(2), Ti_(0.965)Cu_(0.03)La_(0.005)O_(2)and Ti_(0.96)Cu_(0.03)La_(0.01)O_(2)powders present enhanced photocatalytic activity towards Congo red dye degradation compared to pure one under natural solar spectrum. The best Ti_(0.96)Cu_(0.03)La_(0.01)O_(2)catalyst exhibits superior photocatalytic activity of 96% for 10 ppm CR dye in 20 min as well as above average photocatalytic efficiency of 63% for 30 ppm CR dye in 120 min. As well, it showed acceptable photodegradation activity of 52% for 30 ppm MB solution in 140 min of sunlight irradiation. The heightened photodegradation efficiency of Ti_(0.96)Cu_(0.03)La_(0.01)O_(2)catalyst can be clarified in terms of higher charge carriers' separation(Cu^(2+)+ e-→ Cu^(+), L

关键词： semiconductor TiO_(2) Rare earths Congo red Methylene blue solar spectrum Photodegradation

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Identification of gene classifier and modules associated with sARs-CoV-2 ARI in nasal swab

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Genes & Diseases 2024年第1期11卷 38-41页

作者： Pandikannan Krishnamoorthy Athira s.Raj Himanshu Kumar Department of Biological sciences Laboratory of Immunology and Infectious Disease BiologyIndian Institute of Science Education and Research(llSER)BhopalBhopalMP 462066India Laboratory of Host Defense WPl ImmunologyFrontier ResearchCentreOsakaUniversityOsaka 5650871Japan

During a sudden viral pandemic,where the pathogenesis and nature of the infection are unclear,early and accurate identification of the patients infected with the pandemiccausing pathogen is crucial to prevent excess mortality.During the coronavirus disease 2019(COvID-19)pandemic,early diagnosis of severe acute respiratory syndrome virus-2(sARs-CoV-2)is limited by the incidence of the symptoms that are shared with acute respiratory illnesses(ARl)caused by other pathogens.

关键词： acute diagnosis respiratory

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Mathematical modeling and simulations of stress mitigation by coating polycrystalline particles in lithium-ion batteries

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Applied Mathematics and Mechanics(English Edition) 2024年第6期45卷 947-962页

作者： N.IQBAL J.CHOI s.F.sHAH C.LEE s.LEE Department of Mechanical Roboticsand Energy EngineeringDongguk University-SeoulSeoul 04620Republic of Korea

A chemo-mechanical model is developed to investigate the effects on the stress development of the coating of polycrystalline Ni-rich LiNixMnyCo_(z)O_(2)(x≥0.8)(NMC)particles with poly(3,4-ethylenedioxythiophene)(PEDOT).The simulation results show that the coating of primary NMC particles significantly reduces the stress generation by efficiently accommodating the volume change associated with the lithium diffusion,and the coating layer plays roles both as a cushion against the volume change and a channel for the lithium transport,promoting the lithium distribution across the secondary particles more homogeneously.Besides,the lower stiffness,higher ionic conductivity,and larger thickness of the coating layer improve the stress mitigation.This paper provides a mathematical framework for calculating the chemo-mechanical responses of anisotropic electrode materials and fundamental insights into how the coating of NMC active particles mitigates stress levels.

关键词： lithium-ion battery(LIB) polycrystalline particle coating finite element simulation Ni-rich LiNixMnyCo_(z)O_(2)(x>0.8)(NMC)

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Correlation Composition Awareness Model with Pair Collaborative Localization for IoT Authentication and Localization

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Computers, Materials & Continua 2024年第4期79卷 943-961页

作者： Kranthi Alluri s.Gopikrishnan school of Computer science and Engineering VIT-AP UniversityAmaravathiAndhra Pradesh522241India

secure authentication and accurate localization among Internet of Things(IoT)sensors are pivotal for the functionality and integrity of IoT networks.IoT authentication and localization are intricate and symbiotic,impacting both the security and operational functionality of IoT systems.Hence,accurate localization and lightweight authentication on resource-constrained IoT devices pose several challenges.To overcome these challenges,recent approaches have used encryption techniques with well-known key infrastructures.However,these methods are inefficient due to the increasing number of data breaches in their localization approaches.This proposed research efficiently integrates authentication and localization processes in such a way that they complement each other without compromising on security or accuracy.The proposed framework aims to detect active attacks within IoT networks,precisely localize malicious IoT devices participating in these attacks,and establish dynamic implicit authentication mechanisms.This integrated framework proposes a Correlation Composition Awareness(CCA)model,which explores innovative approaches to device correlations,enhancing the accuracy of attack detection and localization.Additionally,this framework introduces the Pair Collaborative Localization(PCL)technique,facilitating precise identification of the exact locations of malicious IoT devices.To address device authentication,a Behavior and Performance Measurement(BPM)scheme is developed,ensuring that only trusted devices gain access to the network.This work has been evaluated across various environments and compared against existing models.The results prove that the proposed methodology attains 96%attack detection accuracy,84%localization accuracy,and 98%device authentication accuracy.

关键词： sensor localization IoT authentication network security data accuracy precise location access control security framework

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A study on the Explainability of Thyroid Cancer Prediction:sHAP Values and Association-Rule Based Feature Integration Framework

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Computers, Materials & Continua 2024年第5期79卷 3111-3138页

作者： sujithra sankar s.sathyalakshmi Department of Computer Applications Hindustan Institute of Technology and ScienceChennaiTamil NaduIndia Department of Computer Engineering Hindustan Institute of Technology and ScienceChennaiTamil NaduIndia

In the era of advanced machine learning techniques,the development of accurate predictive models for complex medical conditions,such as thyroid cancer,has shown remarkable progress.Accurate predictivemodels for thyroid cancer enhance early detection,improve resource allocation,and reduce overtreatment.However,the widespread adoption of these models in clinical practice demands predictive performance along with interpretability and transparency.This paper proposes a novel association-rule based feature-integratedmachine learning model which shows better classification and prediction accuracy than present state-of-the-artmodels.Our study also focuses on the application of sHapley Additive exPlanations(sHAP)values as a powerful tool for explaining thyroid cancer prediction models.In the proposed method,the association-rule based feature integration framework identifies frequently occurring attribute combinations in the dataset.The original dataset is used in trainingmachine learning models,and further used in generating sHAP values fromthesemodels.In the next phase,the dataset is integrated with the dominant feature sets identified through association-rule based analysis.This new integrated dataset is used in re-training the machine learning models.The new sHAP values generated from these models help in validating the contributions of feature sets in predicting malignancy.The conventional machine learning models lack interpretability,which can hinder their integration into clinical decision-making systems.In this study,the sHAP values are introduced along with association-rule based feature integration as a comprehensive framework for understanding the contributions of feature sets inmodelling the predictions.The study discusses the importance of reliable predictive models for early diagnosis of thyroid cancer,and a validation framework of explainability.The proposed model shows an accuracy of 93.48%.Performance metrics such as precision,recall,F1-score,and the area under the receiver operating characteristic(AUROC)

关键词： Explainable AI machine learning clinical decision support systems thyroid cancer association-rule based framework sHAP values classification and prediction

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The dorsal root ganglion as a target for neurorestoration in neuropathic pain

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Neural Regeneration Research 2024年第2期19卷 296-301页

作者： Guillermo Estivill-Torrús Ana Belen Martínez-Padilla Lourdes sánchez-salido Anne Baron-Van Evercooren Beatriz García-Díaz Instituto de Investigación Biomédica de Málaga y Plataforma en Nanomedicina(IBIMA Plataforma BIONAND) MálagaSpain Unidad Clínica de Neurociencias Hospital Regional Universitario de MálagaMálagaSpain Departamento de Biología Molecular y Bioquímica Universidad de MálagaSpain sorbonne Université Institut du Cerveau-Paris Brain Institute-ICMINSERMCNRSAP-HPHôpital Pitié-SalpêtrièreParisFrance

Neuropathic pain is a severe and chronic condition widely found in the general population.The reason for this is the extensive variety of damage or diseases that can spark this unpleasant constant feeling in patients.During the processing of pain,the dorsal root ganglia constitute an important region where dorsal root ganglion neurons play a crucial role in the transmission and propagation of sensory electrical stimulation.Furthermore,the dorsal root ganglia have recently exhibited a regenerative capacity that should not be neglected in the understanding of the development and resolution of neuropathic pain and in the elucidation of innovative therapies.Here,we will review the complex interplay between cells(satellite glial cells and inflammatory cells)and factors(cytokines,neurotrophic factors and genetic factors)that takes place within the dorsal root ganglia and accounts for the generation of the aberrant excitation of primary sensory neurons occurring in neuropathic pain.More importantly,we will summarize an updated view of the current pharmacologic and nonpharmacologic therapies targeting the dorsal root ganglia for the treatment of neuropathic pain.

关键词： cytokines dorsal root ganglia genetic factors neuropathic pain neurotrophic factors pharmacologic and nonpharmacologic therapies satellite glial cells sensory neurons

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Thermogravimetric,kinetic study and gas emissions analysis of the thermal decomposition of waste-derived fuels

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Journal of Environmental sciences 2024年第3期137卷 155-171页

作者： Vadim V.Dorokhov Galina s.Nyashina Pavel A.strizhak Heat and Mass Transfer Laboratory National Research Tomsk Polytechnic University30 Lenin AvenueTomsk 634050Russia

A wide range of wastes can potentially be used to generate thermal and electrical energy.The co-combustion of several types of waste as part of water-containing waste-derived fuels is a promising method for their recovery.In this research,we use thermogravimetric analysis and differential scanning calorimetry to study the thermal behavior and kinetics of coal slime,biomass,waste oils,and blends on their basis.We also analyze the concentrations of gaseous emissions.The results show that biomass,oils,and coal slime significantly affect each other in the course of their co-combustion when added to slurry fuels.The preparation of coal-water slurry based on slime and water reduced the ignition and burnout temperature by up to 16%.Adding biomass and waste oils additionally stimulated the slurry ignition and burnout,which occurred at lower temperatures.Relative to dry coal slime,threshold ignition temperatures and burnout temperatures decreased by 6%–9%and 17%–25%,respectively.Also,the use of biomass and waste oils as part of slurries inhibited NOхand sO_(2)emission by 2.75 times.According to the kinetic analysis,added biomass and waste turbine oil provide a 28%–51%reduction in the activation energy as compared to a coal-water slurry without additives.

关键词： Coal-water slurry Water-containing composite fuels Combustion Emission Kinetic TGA-DsC

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Big data challenge for monitoring quality in higher education institutions using business intelligence dashboards

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Journal of Electronic science and Technology 2024年第1期22卷 25-41页

作者： Ali sorour Anthony s.Atkins Faculty of Digital TechnologyInnovationand BusinessStaffordshire UniversityStoke-on-TrentST42DEUnited Kingdom

As big data becomes an apparent challenge to handle when building a business intelligence(BI)system,there is a motivation to handle this challenging issue in higher education institutions(HEIs).Monitoring quality in HEIs encompasses handling huge amounts of data coming from different sources.This paper reviews big data and analyses the cases from the literature regarding quality assurance(QA)in HEIs.It also outlines a framework that can address the big data challenge in HEIs to handle QA monitoring using BI dashboards and a prototype dashboard is presented in this paper.The dashboard was developed using a utilisation tool to monitor QA in HEIs to provide visual representations of big data.The prototype dashboard enables stakeholders to monitor compliance with QA standards while addressing the big data challenge associated with the substantial volume of data managed by HEIs’QA systems.This paper also outlines how the developed system integrates big data from social media into the monitoring dashboard.

关键词： Big data Business intelligence(BI) Dashboards Higher education(HE) Quality assurance(QA) social media

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