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AHermitian C^(2) Differential Reproducing Kernel Interpolation Meshless Method for the 3D Microstructure-Dependent Static Flexural Analysis of Simply Supported and Functionally Graded Microplates

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Computer Modeling in Engineering & Sciences 2024年第10期141卷 917-949页

作者： Chih-Ping Wu Ruei-Syuan Chang Department of Civil Engineering National Cheng Kung UniversityTainan70101TaiwanChina

This work develops a Hermitian C^(2) differential reproducing kernel interpolation meshless(DRKIM)method within the consistent couple stress theory(CCST)framework to study the three-dimensional(3D)microstructuredependent static flexural behavior of a functionally graded(FG)microplate subjected to mechanical loads and placed under full simple *** the formulation,we select the transverse stress and displacement components and their first-and second-order derivatives as primary ***,we set up the differential reproducing conditions(DRCs)to obtain the shape functions of the Hermitian C^(2) differential reproducing kernel(DRK)interpolant’s derivatives without using direct *** interpolant’s shape function is combined with a primitive function that possesses Kronecker delta properties and an enrichment function that constituents *** a result,the primary variables and their first-and second-order derivatives satisfy the nodal interpolation ***,incorporating ourHermitianC^(2)DRKinterpolant intothe strong formof the3DCCST,we develop a DRKIM method to analyze the FG microplate’s 3D microstructure-dependent static flexural *** Hermitian C^(2) DRKIM method is confirmed to be accurate and fast in its convergence rate by comparing the solutions it produces with the relevant 3D solutions available in the ***,the impact of essential factors on the transverse stresses,in-plane stresses,displacements,and couple stresses that are induced in the loaded microplate is *** factors include the length-to-thickness ratio,the material length-scale parameter,and the inhomogeneity index,which appear to be significant.

关键词： Consistent/modified couple stress theory differential reproducing kernel methods microplates point collocation methods static flexural 3D microstructure-dependent analysis

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Highly Accurate Golden Section Search Algorithms and Fictitious Time Integration Method for Solving Nonlinear Eigenvalue Problems

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Computer Modeling in Engineering & Sciences 2024年第5期139卷 1317-1335页

作者： Chein-Shan Liu Jian-Hung Shen Chung-Lun Kuo Yung-Wei Chen Center of Excellence for Ocean Engineering Taiwan Ocean UniversityKeelung202301TaiwanChina Department of Marine Engineering Taiwan Ocean UniversityKeelung202301TaiwanChina

This study sets up two new merit functions,which are minimized for the detection of real eigenvalue and complex eigenvalue to address nonlinear eigenvalue *** each eigen-parameter the vector variable is solved from a nonhomogeneous linear system obtained by reducing the number of eigen-equation one less,where one of the nonzero components of the eigenvector is normalized to the unit and moves the column containing that component to the right-hand side as a nonzero input vector.1D and 2D golden section search algorithms are employed to minimize the merit functions to locate real and complex ***,the real and complex eigenvectors can be computed very accurately.A simpler approach to the nonlinear eigenvalue problems is proposed,which implements a normalization condition for the uniqueness of the eigenvector into the eigenequation *** real eigenvalues can be computed by the fictitious time integration method(FTIM),which saves computational costs compared to the one-dimensional golden section search algorithm(1D GSSA).The simpler method is also combined with the Newton iterationmethod,which is convergent very *** the proposed methods are easily programmed to compute the eigenvalue and eigenvector with high accuracy and efficiency.

关键词： Nonlinear eigenvalue problem quadratic eigenvalue problem two new merit functions golden section search algorithm fictitious time integration method

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High glucose reduces Nrf2-dependent cRAGE release and enhances inflammasome-dependent IL-1βproduction in monocytes:the modulatory effects of EGCG

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Food Science and Human Wellness 2024年第3期13卷 1531-1542页

作者： Chi-Hao Wu Yin-Hsuan Chang Chin-Lin Hsu Sheng-Yi Chen Gow-Chin Yen Graduate Programs of Nutrition Science School of Life ScienceTaiwan Normal UniversityTaipei 106209TaiwanChina Department of Food Science and Biotechnology Chung Hsing UniversityTaichung 40227TaiwanChina School of Nutrition Chung Shan Medical UniversityTaichung 40201TaiwanChina

Soluble receptor for advanced glycation end products(sRAGE)acts as a decoy sequestering of RAGE ligands,thus preventing the activation of the ligand-RAGE axis linking human ***,the molecular mechanisms underlying sRAGE remain *** this study,THP-1 monocytes were cultured in normal glucose(NG,5.5 mmol/L)and high glucose(HG,15 mmol/L)to investigate the effects of diabetesrelevant glucose concentrations on sRAGE and interleukin-1β(IL-1β)*** modulatory effects of epigallocatechin gallate(EGCG)in response to HG challenge were also *** enhanced intracellular reactive oxygen species(ROS)generation and RAGE *** secretion of sRAGE,including esRAGE and cRAGE,was reduced under HG conditions,together with the downregulation of a disintegrin and metallopeptidase 10(ADAM10)and nuclear factor erythroid 2-related factor 2(Nrf2)nuclear ***,the HG effects were counteracted by siRAGE and exacerbated by *** immunoprecipitation results showed that Nrf2 binding to the ADAM10 promoter and HG interfered with this *** data reinforce the notion that RAGE and Nrf2 might be sRAGE-regulating *** HG conditions,the treatment of EGCG reduced ROS generation and RAGE ***-stimulated cRAGE release was likely caused by the upregulation of the Nrf2-ADAM10 *** inhibited HG-mediated NLRP3 inflammasome activation at least partly by stimulating sRAGE,thereby reducing IL-1βrelease.

关键词： Epigallocatechin gallate(EGCG) Inflammasome Nuclear factor erythroid 2-related factor 2(Nrf2) Receptor for advanced glycation end products(RAGE) Soluble RAGE(sRAGE)

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Optimal Shape Factor and Fictitious Radius in the MQ-RBF:Solving Ill-Posed Laplacian Problems

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Computer Modeling in Engineering & Sciences 2024年第6期139卷 3189-3208页

作者： Chein-Shan Liu Chung-Lun Kuo Chih-Wen Chang Center of Excellence for Ocean Engineering Taiwan Ocean UniversityKeelung202301TaiwanChina Department of Mechanical Engineering National United UniversityMiaoli36063TaiwanChina

To solve the Laplacian problems,we adopt a meshless method with the multiquadric radial basis function(MQRBF)as a basis whose center is distributed inside a circle with a fictitious radius.A maximal projection technique is developed to identify the optimal shape factor and fictitious radius by minimizing a merit function.A sample function is interpolated by theMQ-RBF to provide a trial coefficient vector to compute the merit *** can quickly determine the optimal values of the parameters within a preferred rage using the golden section search *** novel method provides the optimal values of parameters and,hence,an optimal MQ-RBF;the performance of the method is validated in numerical ***,nonharmonic problems are transformed to the Poisson equation endowed with a homogeneous boundary condition;this can overcome the problem of these problems being *** optimal MQ-RBF is extremely *** further propose a novel optimal polynomial method to solve the nonharmonic problems,which achieves high precision up to an order of 10^(−11).

关键词： Laplace equation nonharmonic boundary value problem Ill-posed problem maximal projection optimal shape factor and fictitious radius optimal MQ-RBF optimal polynomial method

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The Effect of Uncaria gambir on Optical Properties and Thermal Stability of CNF/PVA Biocomposite Films

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Journal of Renewable Materials 2024年第9期12卷 1593-1603页

作者： Remon Lapisa Anna Niska Fauza Dieter Rahmadiawan Krismadinata Dori Yuvenda Randi Purnama Putra Waskito Nandy Putra Hairul Abral Mechanical Engineering Department Universitas Negeri PadangPadang25173Indonesia Centre for Energy and Power Electronics Research Universitas Negeri PadangPadang25173Indonesia Department of Mechanical Engineering National Cheng Kung University(NCKU)Tainan70101Taiwan Mechanical Engineering Department Universitas IndonesiaDepok16424Indonesia Mechanical Engineering Department Universitas AndalasPadang25163Indonesia

Cellulose-based film has gained popularity as an alternative to synthetic polymers due to its outstanding *** all types of cellulose materials available,cellulose nanofiber(CNF)has great potential to be utilized in a diverse range of applications,including as a film *** this study,CNF biocomposite film was prepared by using polyvinyl alcohol(PVA)as a matrix and Uncaria gambir extract as a *** study aims to investigate the effect of Uncaria gambir extract on the optical properties and thermal stability of the produced *** formation of the CNF biocomposite films was confirmed using Fourier Transform Infrared Spectroscopy,their transmittance characteristics were measured using UV-Vis spectroscopy and a transmittance meter,while their reflectance was determined using a reflectance *** results revealed that the addition of Uncaria gambir extract to the CNF biocomposite film improved its UV-shielding properties,as indicated by the lower percentage of transmittance in the visible region,10%–70%.In addition,its reflectance increased to 10.6%compared to the CNF film without the addition of Uncaria gambir ***,the thermal stability of the CNF biocomposite film with the addition of Uncaria gambir extract improved to around 400℃–500℃.In conclusion,the results showed that CNF biocomposite film prepared by adding Uncaria gambir extract can be a promising candidate for optical and thermal management materials.

关键词： Cellulose nanofiber biocomposite film optical properties Uncaria gambir thermal stability

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Time Parameter Based Low-Energy Data Encryption Method for Mobile Applications

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Computer Modeling in Engineering & Sciences 2024年第9期140卷 2779-2794页

作者： Li-Woei Chen Kun-Lin Tsai Fang-Yie Leu Wen-Cheng Jiang Shih-Ting Tseng Department of Computer and Information Sciences Chinese Military AcademyKaohsiung830TaiwanChina Department of Electrical Engineering Tunghai UniversityTaichung407TaiwanChina Department of Computer Science Tunghai UniversityTaichung407TaiwanChina

Various mobile devices and applications are now used in daily *** devices require high-speed data processing,low energy consumption,low communication latency,and secure data transmission,especially in 5G and 6G mobile ***-security cryptography guarantees that essential data can be transmitted securely;however,it increases energy consumption and reduces data processing ***,this study proposes a low-energy data encryption(LEDE)algorithm based on the Advanced Encryption Standard(AES)for improving data transmission security and reducing the energy consumption of encryption in Internet-of-Things(IoT)*** the proposed LEDE algorithm,the system time parameter is employed to create a dynamic S-Box to replace the static S-Box of *** indicated that six-round LEDE encryption achieves the same security level as 10-round conventional AES *** reduction in encryption time results in the LEDE algorithm having a 67.4%lower energy consumption and 43.9%shorter encryption time than conventional AES;thus,the proposed LEDE algorithm can improve the performance and the energy consumption of IoT edge devices.

关键词： Mobile application security AES data encryption time parameter mobile device

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Coupling Analysis of Multiple Machine Learning Models for Human Activity Recognition

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Computers, Materials & Continua 2024年第6期79卷 3783-3803页

作者： Yi-Chun Lai Shu-Yin Chiang Yao-Chiang Kan Hsueh-Chun Lin Department of Public Health China Medical UniversityTaichung406040Taiwan Department of Information and Telecommunications Engineering Ming Chuan UniversityGui-ShanTaoyuan333Taiwan Department of Electrical Engineering Yuan Ze UniversityChung-Li32003Taiwan Department and Institute of Health Service Administrations China Medical UniversityTaichung406040Taiwan

Artificial intelligence(AI)technology has become integral in the realm of medicine and healthcare,particularly in human activity recognition(HAR)applications such as fitness and rehabilitation *** study introduces a robust coupling analysis framework that integrates four AI-enabled models,combining both machine learning(ML)and deep learning(DL)approaches to evaluate their effectiveness in *** analytical dataset comprises 561 features sourced from the UCI-HAR database,forming the foundation for training the ***,the MHEALTH database is employed to replicate the modeling process for comparative purposes,while inclusion of the WISDM database,renowned for its challenging features,supports the framework’s resilience and *** ML-based models employ the methodologies including adaptive neuro-fuzzy inference system(ANFIS),support vector machine(SVM),and random forest(RF),for data *** contrast,a DL-based model utilizes one-dimensional convolution neural network(1dCNN)to automate feature ***,the recursive feature elimination(RFE)algorithm,which drives an ML-based estimator to eliminate low-participation features,helps identify the optimal features for enhancing model *** best accuracies of the ANFIS,SVM,RF,and 1dCNN models with meticulous featuring process achieve around 90%,96%,91%,and 93%,*** analysis using the MHEALTH dataset showcases the 1dCNN model’s remarkable perfect accuracy(100%),while the RF,SVM,and ANFIS models equipped with selected features achieve accuracies of 99.8%,99.7%,and 96.5%,***,when applied to the WISDM dataset,the DL-based and ML-based models attain accuracies of 91.4%and 87.3%,respectively,aligning with prior research *** conclusion,the proposed framework yields HAR models with commendable performance metrics,exhibiting its suitability for integration into the healthcare services system through AI-driven applications.

关键词： Human activity recognition artificial intelligence support vector machine random forest adaptive neuro-fuzzy inference system convolution neural network recursive feature elimination

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Identifying Brand Consistency by Product Differentiation Using CNN

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Computer Modeling in Engineering & Sciences 2024年第7期140卷 685-709页

作者： Hung-Hsiang Wang Chih-Ping Chen Department of Industrial Design National Taipei University of TechnologyTaipeiTaiwan Department of Product Design Ming Chuan UniversityTaoyuanTaiwan

This paper presents a new method of using a convolutional neural network(CNN)in machine learning to identify brand consistency by product appearance *** Experiment 1,we collected fifty mouse devices from the past thirty-five years from a renowned company to build a dataset consisting of product pictures with pre-defined design features of their appearance and *** show that it is a challenge to distinguish periods for the subtle evolution of themouse devices with such traditionalmethods as time series analysis and principal component analysis(PCA).In Experiment 2,we applied deep learning to predict the extent to which the product appearance variation ofmouse devices of various *** investigation collected 6,042 images ofmouse devices and divided theminto the Early Stage and the Late *** show the highest accuracy of 81.4%with the CNNmodel,and the evaluation score of brand style consistency is 0.36,implying that the brand consistency score converted by the CNN accuracy rate is not always perfect in the real *** relationship between product appearance variation,brand style consistency,and evaluation score is beneficial for predicting new product styles and future product style *** addition,the CNN heat maps highlight the critical areas of design features of different styles,providing alternative clues related to the blurred *** study provides insights into practical problems for designers,manufacturers,and marketers in product *** not only contributes to the scientific understanding of design development,but also provides industry professionals with practical tools and methods to improve the design process and maintain brand *** can use these techniques to find features that influence brand ***,capture these features as innovative design elements and maintain core brand values.

关键词： Machine learning product differentiation brand consistency principal component analysis convolutional neural network computer mouse

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Paclitaxel induces human KOSC3 oral cancer cell apoptosis through caspase pathways

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BIOCELL 2024年第7期48卷 1047-1054页

作者： YU-YAN LAN TSUN-CHIH CHENG YI-PING LEE CHIA-YIH WANG BU-MIIN HUANG School of Medicine College of MedicineI-Shou UniversityKaohsiung82445Taiwan Department of Otolaryngology An Nan HospitalChina Medical UniversityTainan70965Taiwan Department of Cell Biology and Anatomy College of MedicineNational Cheng Kung UniversityTainan70101Taiwan Department of Medical Research China Medical University HospitalChina Medical UniversityTaichung40402Taiwan

Background:Paclitaxel is a compound derived from Paciﬁc yew bark that induces various cancer cell ***,whether it also has anticancer activities in KOSC3 cells,an oral cancer cell line,is ***:3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide,ﬂow cytometry,and western blotting assays were carried out to assess cell viability,subG1 phase of the cell cycle,and apoptosis-related protein expression,***:Ourﬁndings indicate that paclitaxel could inhibit cell viability and increase the expression of apoptotic markers,including plasma membrane blebbing and the cleavage of poly ADP-ribose polymerase in KOSC3 ***,the treatment with paclitaxel remarkably elevated the percentage of the subG1 phase in KOSC3 *** addition,treatment with a pan-caspase inhibitor could recover paclitaxel-inhibited cell ***,caspase-8,caspase-9,caspase-7,and BH3 interacting domain death agonist(Bid)were activated in paclitaxel-treated KOSC3 ***:Paclitaxel induced apoptosis through caspase cascade in KOSC3 cells.

关键词： Paclitaxel Oral cancer KOSC3 cells Apoptosis Caspase pathways

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Automatic fovea detection and choroid segmentation for choroidal thickness assessment in optical coherence tomography

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International Journal of Ophthalmology(English edition) 2024年第10期17卷 1763-1771页

作者： Chen Yu Lin Hung Ju Chen Yi Kit Chan Wei Ping Hsia Yu Len Huang Chia Jen Chang Department of Ophthalmology Taichung Veterans General HospitalTaichung 407TaiwanChina Department of Computer Science Tunghai UniversityTaichung 407TaiwanChina

AIM:To develop an automated model for subfoveal choroidal thickness(SFCT)detection in optical coherence tomography(OCT)images,addressing manual fovea location and choroidal contour ***:Two procedures were proposed:defining the fovea and segmenting the *** localization from B-scan OCT image sequence with three-dimensional reconstruction(LocBscan-3D)predicted fovea location using central foveal depression features,and fovea localization from two-dimensional en-face OCT(LocEN-2D)used a mask region-based convolutional neural network(Mask R-CNN)model for optic disc detection,and determined the fovea location based on optic disc relative *** segmentation also employed Mask ***:For 53 eyes in 28 healthy subjects,LocBscan-3D’s mean difference between manual and predicted fovea locations was 170.0μm,LocEN-2D yielded 675.9μ***-2D performed better in non-high myopia group(P=0.02).SFCT measurements from Mask R-CNN aligned with manual ***:Our models accurately predict SFCT in OCT ***-3D excels in precise fovea localization even with high ***-2D shows high detection rates but lower accuracy especially in the high myopia *** both models offers a robust SFCT assessment approach,promising efficiency and accuracy for large-scale studies and clinical use.

关键词： subfoveal choroidal thickness optical coherence tomography automatic foveal detection automatic choroid segmentation

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