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Applied Mathematics and Mechanics(English Edition) 2025年第1期46卷 81-100页

作者： S.SAUrABH r.KIrAN D.singh r.VAISH V.S.cHAUHAN School of Mechanical and Materials Engineering Indian Institute of Technology Mandi

Bio-inspired helicoidal composite laminates, inspired by the intricate helical structures found in nature, present a promising frontier for enhancing the mechanical properties of structural designs. Hence, this study provides a comprehensive investigation into the nonlinear free vibration and nonlinear bending behavior of bio-inspired composite plates. The inverse hyperbolic shear deformation theory(IHSDT) of plates is employed to characterize the displacement field, with the incorporation of Green-Lagrange nonlinearity. The problem is modeled using the c0finite element method(FEM), and an in-house code is developed in the MATLAB environment to solve it numerically. Various helicoidal layup configurations including helicoidal recursive(Hr), helicoidal exponential(HE), helicoidal semi-circular(HS), linear helicoidal(LH), and Fibonacci helicoidal(FH)with different layup sequences and quasi-isotropic configurations are studied. The model is validated, and parametric studies are conducted. These studies investigate the effects of layup configurations, side-to-thickness ratio, modulus ratios, boundary conditions, and loading conditions at different load amplitudes on the nonlinear vibration and nonlinear bending behaviors of bio-inspired composite plates. The results show that the laminate sequence exerts a substantial impact on both nonlinear natural frequencies and nonlinear bending behaviors. Moreover, this influence varies across different side-to-thickness ratios and boundary conditions of the bio-inspired composite plate.

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Three-Stage Transfer Learning with AlexNet50 for MrI Image Multi-class classification with Optimal Learning rate

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computer Modeling in Engineering & Sciences 2025年第1期142卷 155-183页

作者： Suganya Athisayamani A.robert singh Gyanendra Prasad Joshi Woong cho School of computing Sastra Deemed to be UniversityThanjavur613401India Department of computational Intelligence SRM Institute of Science and TechnologyKattankulathur603203India Department of AI and Software Engineering Kangwon National UniversitySamcheok25913Republic of Korea Department of Electronics Information and Communication EngineeringKangwon National UniversitySamcheok25913Republic of Korea

In radiology,magnetic resonance imaging(MrI)is an essential diagnostic tool that provides detailed images of a patient’s anatomical and physiological *** is particularly effective for detecting soft tissue ***,radiologists manually interpret these images,which can be labor-intensive and time-consuming due to the vast amount of *** address this challenge,machine learning,and deep learning approaches can be utilized to improve the accuracy and efficiency of anomaly detection in MrI *** manuscript presents the use of the Deep AlexNet50 model for MrI classification with discriminative learning *** are three stages for learning;in the first stage,the whole dataset is used to learn the *** the second stage,some layers of AlexNet50 are frozen with an augmented dataset,and in the third stage,AlexNet50 with an augmented dataset with the augmented *** method used three publicly available MrI classification datasets:Harvard whole brain atlas(HWBA-dataset),the School of Biomedical Engineering of Southern Medical University(SMU-dataset),and The National Institute of Neuroscience and Hospitals brain MrI dataset(NINS-dataset)for *** hyperparameter optimizers like Adam,stochastic gradient descent(SGD),root mean square propagation(rMS prop),Adamax,and AdamW have been used to compare the performance of the learning ***-dataset registers maximum classification *** evaluated the performance of the proposed classification model using several quantitative metrics,achieving an average accuracy of 98%.

关键词： MrI tumors classification AlexNet50 transfer learning hyperparameter tuning optimizer

Multi-Scale Dilated convolution Network for SPEcT-MPI cardiovascular Disease classification with Adaptive Denoising and Attenuation correction

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computer Modeling in Engineering & Sciences 2025年第1期142卷 299-327页

作者： A.robert singh Suganya Athisayamani Gyanendra Prasad Joshi Bhanu Shrestha Department of computational Intelligence SRM Institute of Science and TechnologyKattankulathur603203Tamil NaduIndia School of computing Sastra Deemed to be UniversityThanjavur613401Tamil NaduIndia Department of Artificial Intelligence&Software Kangwon National UniversitySamcheok25913Republic of Korea Department of Information convergence System Graduate School of Smart ConvergenceKwangwoon UniversitySeoul01897Republic of Korea

Myocardial perfusion imaging(MPI),which uses single-photon emission computed tomography(SPEcT),is a well-known estimating tool for medical diagnosis,employing the classification of images to show situations in coronary artery disease(cAD).The automatic classification of SPEcT images for different techniques has achieved near-optimal accuracy when using convolutional neural networks(cNNs).This paper uses a SPEcT classification framework with three steps:1)Image denoising,2)Attenuation correction,and 3)Image *** denoising is done by a U-Net architecture that ensures effective image *** correction is implemented by a convolution neural network model that can remove the attenuation that affects the feature extraction process of ***,a novel multi-scale diluted convolution(MSDc)network is *** merges the features extracted in different scales and makes the model learn the features more *** scales of filters with size 3×3 are used to extract *** three steps are compared with state-of-the-art *** proposed denoising architecture ensures a high-quality image with the highest peak signal-to-noise ratio(PSNr)value of *** proposed classification method is compared with the five different cNN models,and the proposed method ensures better classification with an accuracy of 96%,precision of 87%,sensitivity of 87%,specificity of 89%,and F1-score of 87%.To demonstrate the importance of preprocessing,the classification model was analyzed without denoising and attenuation correction.

关键词： SPEcT-MPI cAD MSDc denoising attenuation correction classification

Exploring the role of N-acetyltransferases in diseases:a focus on N-acetyltransferase 9 in neurodegeneration

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Neural regeneration research 2025年第10期20卷 2862-2871页

作者： Prajakta Deshpande Anuradha Venkatakrishnan chimata Amit singh Department of Biology University of DaytonDaytonOHUSA Premedical Program University of DaytonDaytonOHUSA center for Tissue regeneration and Engineering at Dayton(TrEND) University of DaytonDaytonOHUSA Integrative Science and Engineering center University of DaytonDaytonOHUSA center for Genomic Advocacy(TcGA) Indiana State UniversityTerre HauteINUSA

Acetyltransferases,required to transfer an acetyl group on protein are highly conserved proteins that play a crucial role in development and *** acetylation is a common post-translational modification pivotal to basic cellular *** to 80%-90%of proteins are acetylated during translation,which is an irreversible process that affects protein structure,function,life,and *** this review,we have discussed the various N-acetyltransferases present in humans,their function,and how they might play a role in ***,we have focused on N-acetyltransferase 9 and its role in microtubule *** have shed light on how N-acetyltransferase 9 and acetylation of proteins can potentially play a role in neurodegenerative *** have specifically discussed the N-acetyltransferase 9-acetylation independent function and regulation of c-Jun N-terminal kinase signaling and microtubule stability during development and neurodegeneration.

关键词： acetyl-coenzyme A Alzheimer’s disease animal models cell death drosophila eye human disease c-Jun N-terminal kinase signaling N-Acetyltransferases N-acetyltransferase 9 neurodegeneration

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Fibrinogen’s potential role in connecting cerebrovascular abnormalities with glymphatic dysfunction in Alzheimer’s disease

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Neural regeneration research 2025年第1期20卷 203-204页

作者： Vishal singh Arnab choudhury Hyung Jin Ahn Department of Pharmacology Physiology and NeurosciencesRutgers-New Jersey Medical SchoolNewarkNJUSA Brain Health Institute Rutgers UniversityPiscatawayNJUSA

Alzheimer’s disease(AD)stands out as the primary manifestation of age-related dementia,portraying a chronic neurodegenerative disorder distinguished by the accumulation of fibrillar amyloid-β(Aβ)plaques and neurofibrillary tangles of hyperphosphorylated ***,from a clinical standpoint,AD presents itself as a complex condition with a spectrum of dysfunctions rather than a singular pathological *** often-overlooked aspect of the disease is the presence of extensive cerebrovascular abnormalities,given that the majority of AD patients experience altered cerebral blood flow,damaged vasculature,increased microinfarcts and *** models of AD further support this observation,showing cerebrovascular dysfunction such as impaired cerebral blood flow and altered cerebrovascular reactivity(Tataryn et al.,2021;Gareau et al.,2023).

关键词： cerebrovascular dysfunction Alzheimer

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Synthetic data as an investigative tool in hypertension and renal diseases research

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World Journal of Methodology 2025年第1期15卷 9-13页

作者： Aleena Jamal Som singh Fawad Qureshi Sidney Kimmel Medical college Thomas Jefferson UniversityPhiladelphiaPA 19107United States School of Medicine University of Missouri Kansas CityKansasMO 64106United States Division of Nephrology and Hypertension Mayo ClinicRochesterMN 55905United States

There is a growing body of clinical research on the utility of synthetic data derivatives,an emerging research tool in *** nephrology,clinicians can use machine learning and artificial intelligence as powerful aids in their clinical decision-making while also preserving patient *** is especially important given the epidemiology of chronic kidney disease,renal oncology,and hypertension ***,there remains a need to create a framework for guidance regarding how to better utilize synthetic data as a practical application in this research.

关键词： Synthetic data Artificial intelligence Nephrology Blood pressure research Editorial

A comprehensive Survey on Federated Learning Applications in computational Mental Healthcare

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computer Modeling in Engineering & Sciences 2025年第1期142卷 49-90页

作者： Vajratiya Vajrobol Geetika Jain Saxena Amit Pundir Sanjeev singh Akshat Gaurav Savi Bansal razaz Waheeb Attar Mosiur rahman Brij B.Gupta Institute of Informatics and communication University of DelhiDelhi110021India Maharaja Agrasen college University of DelhiDelhi110096India computer Engineering Ronin InstituteMontclairNJ 07043USA Department of research and Innovation Insights2TechinfoJaipur302001India University centre for research and Development(UcrD) Chandigarh UniversityChandigarh140413India Management Department College of Business AdministrationPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia ccrI&Department of computer Science and Information Engineering Asia UniversityTaichung413Taiwan Symbiosis centre for Information Technology(ScIT) Symbiosis International UniversityPune411057India center for Interdisciplinary research University of Petroleum and Energy Studies(UPES)Dehradun248007India

Mental health is a significant issue worldwide,and the utilization of technology to assist mental health has seen a growing *** aims to alleviate the workload on healthcare professionals and aid *** applications have been developed to support the challenges in intelligent healthcare ***,because mental health data is sensitive,privacy concerns have *** learning has gotten some *** research reviews the studies on federated learning and mental health related to solving the issue of intelligent healthcare *** explores various dimensions of federated learning in mental health,such as datasets(their types and sources),applications categorized based on mental health symptoms,federated mental health frameworks,federated machine learning,federated deep learning,and the benefits of federated learning in mental health *** research conducts surveys to evaluate the current state of mental health applications,mainly focusing on the role of Federated Learning(FL)and related privacy and data security *** survey provides valuable insights into how these applications are emerging and evolving,specifically emphasizing FL’s impact.

关键词： Depression emotional recognition intelligent healthcare systems mental health federated learning stress detection sleep behaviour

MHD free convective flow past semi-infinite vertical permeable wall

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Applied Mathematics and Mechanics(English Edition) 2012年第9期33卷 1207-1222页

作者： r.K.singh A.K.singh Department of Mathematics Banaras Hindu University

In this paper, the basic equations governing the flow and heat transfer of an incompressible viscous and electrically conducting fluid past a semi-infinite vertical per- meable plate in the form of partial differential equations are reduced to a set of non-linear ordinary differential equations by applying a suitable similarity transformation. Approx- imate solutions of the transformed equations are obtained by employing the perturbation method for two cases, i.e., small and large values of the suction parameter. From the numerical evaluations of the solution, it can be seen that the velocity field at any point decreases as the values of the magnetic and suction parameters increase. The effect of the magnetic parameter is to increase the thermM boundary layer. It is also found that the velocity and temperature fields decrease with the increase in the sink parameter.

关键词： magnetohydrodynamics (MHD) suction source/sink Prandtl number permeability boundary layer

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Mathematical modeling of atmospheric internal waves phenomenon and its solution by Elzaki Adomian decomposition method

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Journal of Ocean Engineering and Science 2022年第3期7卷 203-212页

作者： Archana c.Varsoliwala Twinkle r.singh Applied Mathematics and Humanities Department Sardar Vallabhbhai National Institute of TechnologySurat395007GujaratIndia

This article involves the study of atmospheric internal waves phenomenon,also referred to as gravity *** phenomenon occurs inside the fluid,not on the *** model is based on a shallow fluid hypothesis represented by a system of nonlinear partial differential *** basic assumption of the shallow flow model is that the horizontal size is much larger than the vertical *** internal waves can be perfectly represented by this model as the waves are spread over a large horizontal *** we used the Elzaki Adomian Decomposition Method(EADM)to obtain the solution for the considered model along with its convergence *** Adomian decomposition method together with the Elzaki transform gives the solution in a convergent series without any linearization or *** are built between the results obtained by EADM and HAM to examine the accuracy of the proposed method.

关键词： Atmospheric internal waves Shallow-fluid equations System of nonlinear PDEs Elzaki Adomian decomposition method climate prediction

Searching systematics for nonfactorizable contributions to B^(-)and B^(0) hadronic decays

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chinese Physics c 2022年第7期46卷 47-55页

作者： Maninder Kaur Supreet Pal singh r.c.ver.a Department of Physics Punjabi UniversityPatiala-147002India

The two-body weak decays B→πD/B→ρD and B→πD are examined using isospin analysis to study nonfactorizable *** determining strong interaction phases and obtaining factorizable contributions from spectator-quark diagrams for Nc=3,we determine nonfactorizable isospin amplitudes from the experimental data for these *** results support the universality of the ratio of nonfactorizable isospin reduced amplitudes for these decays within experimental *** demonstrate that these systematics are not coincidental,we also plot our results *** ratio.

关键词： nonfactorization weak hadronic decays HEP-PHE