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semantic segmentation of Lumbar vertebrae Using Meijering U-Net(MU-Net)on spine Magnetic Resonance Images

Computer Modeling in Engineering & sciences 2025年第1期142卷 733-757页

作者： Lakshmi s v v shiloah Elizabeth Darmanayagam sunil Retmin Raj Cyril Department of Computer science and Engineering College of Engineering GuindyAnna UniversityChennai600025India Department of Information Technology Madras Institute of TechnologyAnna UniversityChrompetChennai600044India

Lower back pain is one of the most common medical problems in the world and it is experienced by a huge percentage of people *** to its ability to produce a detailed view of the soft tissues,including the spinal cord,nerves,intervertebral discs,and vertebrae,Magnetic Resonance Imaging is thought to be the most effective method for imaging the *** semantic segmentation of vertebrae plays a major role in the diagnostic process of lumbar *** is difficult to semantically partition the vertebrae in Magnetic Resonance Images from the surrounding variety of tissues,including muscles,ligaments,and intervertebral discs.U-Net is a powerful deep-learning architecture to handle the challenges of medical image analysis tasks and achieves high segmentation *** work proposes a modified U-Net architecture namely MU-Net,consisting of the Meijering convolutional layer that incorporates the Meijering filter to perform the semantic segmentation of lumbar vertebrae L1 to L5 and sacral vertebra ***-colour mask images were generated and used as ground truth for training the *** work has been carried out on 1312 images expanded from T1-weighted mid-sagittal MRI images of 515 patients in the Lumbar spine MRI Dataset publicly available from Mendeley *** proposed MU-Net model for the semantic segmentation of the lumbar vertebrae gives better performance with 98.79%of pixel accuracy(PA),98.66%of dice similarity coefficient(DsC),97.36%of Jaccard coefficient,and 92.55%mean Intersection over Union(mean IoU)metrics using the mentioned dataset.

关键词： Computer aided diagnosis(CAD) magnetic resonance imaging(MRI) semantic segmentation lumbar vertebrae deep learning U-Net model

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Unlocking hypoglycemia–associated brain microvascular dysfunction:critical insights from proteomic analysis

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Neural Regeneration Research 2025年第6期20卷 1707-1708页

作者： siva s.v.P.sakamuri Anil sakamuri Department of Chemistry Auburn University at MontgomeryMontgomeryALUSA vascular Biology Center and Department of Medicine Medical College of Georgia at Augusta UniversityAugustaGAUSA

Hypoglycemia-a critical complication linked to worsened brain function in diabetic subjects:Hypoglycemia is characterized by a decline in circulatory glucose levels below sta nda rd physiological *** hypoglycemia,classified as level 1 hypoglycemia,is defined by blood glucose levels below 70 mg/dL and can be effectively addressed through carbohydrate *** hypoglycemia,denoted by blood glucose levels less than 54 mg/dL,poses a life-threatening risk if left *** with type 1 and type 2 diabetes undergoing insulin treatment are particularly susceptible to hypoglycemia due to impaired counterregulatory mechanisms.

关键词： impaired intake critical

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A comprehensive investigation on nonlinear vibration and bending characteristics of bio-inspired helicoidal laminated composite structures

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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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Artificial neural network with modified rider optimization for design and control of Pv-integrated quasi Z-source cascaded multilevel inverter system

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International Journal of Modeling, simulation, and scientific Computing 2021年第1期12卷 87-111页

作者： v.C.Harish Kumar s.Amala shanthi Department of EEE NICHE ThuckalayKanyakumariTamil NaduIndia Department of ECE NICHEThuckalayKanyakumariTamil NaduIndia

The modeling of the controller for quasi Z-source Cascaded Multilevel Inverter(qZsCMI)-dependent 3-phase grid-tie Photovoltaic(Pv)power system is considered in this *** state-of-the-art controller requires precise conceptual models and sophisticated optimization principles based on the derived ***,such processes are limited to known system models,which are uncertain in future ***,the controller for 3-phase qZs-CMI is modeled based on two phases,and the source Pv voltage and output grid current are *** Phase I,optimized Proportional Integral(PI)controller is used for finding out the total Pv voltage,and Phase II utilizes the optimized Proportional Resonant(PR)controller enabled with the Artificial Neural Network(ANN)for controlling the grid *** two phases,the modified optimization algorithm called Fitness Enabled-Rider Optimization Algorithm(FE-ROA)is ***,in Phase II,ANN is trained in an offline mode with the exact dataset arranged by the proposed FE-ROA,and it guarantees the control of grid *** two phases plan to optimize the gain of both PI and PR controllers respectively using the same proposed *** main objective of phase I is to lessen the error among the reference Pv voltage,and measured voltage,and phase II is to lessen the error among the reference and measured grid ***,the grid-tie current injection is achieved by the developed module,and system-level control offers independent Maximum Power Point Tracking(MPPT).Lastly,the performance of the proposed controller for qZs-CMI is compared over the other controllers and substantiates the efficacy of the proposed one.

关键词： qZs-CMI PI controller PR controller artificial neural network fitness enabled-rider optimization algorithm

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Brain-derived neurotrophic factor signaling in the neuromuscular junction during developmental axonal competition and synapse elimination

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Neural Regeneration Research 2025年第2期20卷 394-401页

作者： Josep Tomàs víctor Cilleros-Mañé Laia Just-Borràs Marta Balanyà-segura Aleksandra Polishchuk Laura Nadal Marta Tomàs Carolina silvera-simón Manel M.santafé Maria A.Lanuza Unitat d’Histologia i Neurobiologia(UHNeurob) Facultat de Medicina i Ciències de la SalutUniversitat Rovira i VirgiliReusSpain

During the development of the nervous system,there is an overproduction of neurons and *** competition between neighboring nerve endings and synapses performing different activity levels leads to their elimination or *** have extensively studied the involvement of the brain-derived neurotrophic factor-Tropomyosin-related kinase B receptor neurotrophic retrograde pathway,at the neuromuscular junction,in the axonal development and synapse elimination process versus the synapse *** purpose of this review is to describe the neurotrophic influence on developmental synapse elimination,in relation to other molecular pathways that we and others have found to regulate this *** particular,we summarize our published results based on transmitter release analysis and axonal counts to show the different involvement of the presynaptic acetylcholine muscarinic autoreceptors,coupled to downstream serine-threonine protein kinases A and C(PKA and PKC)and voltage-gated calcium channels,at different nerve endings in developmental *** dynamic changes that occur simultaneously in several nerve terminals and synapses converge across a postsynaptic site,influence each other,and require careful studies to individualize the mechanisms of specific *** describe an activity-dependent balance(related to the extent of transmitter release)between the presynaptic muscarinic subtypes and the neurotrophin-mediated TrkB/p75NTR pathways that can influence the timing and fate of the competitive interactions between the different axon *** downstream displacement of the PKA/PKC activity ratio to lower values,both in competing nerve terminals and at postsynaptic sites,plays a relevant role in controlling the elimination of supernumerary ***,calcium entry through L-and P/Q-subtypes of voltage-gated calcium channels(both channels are present,together with the N-type channel in developing nerve terminals)contributes to red

关键词： acetylcholine release adenosine receptors axonal competition brain-derived neurotrophic factor calcium channels motor end-plate muscarinic acetylcholine receptors postnatal synapse elimination serine kinases tropomyosin-related kinase receptorB

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Intelligent Deep Learning Based Disease Diagnosis Using Biomedical Tongue Images

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Computers, Materials & Continua 2022年第3期70卷 5667-5681页

作者： v.thanik.chalam.s.shanthi K.Kalirajan sayed Abdel-Khalek Mohamed Omri Lotfi M.Ladhar sri sivasubramaniya Nadar College of Engineering Chennai603110India Department of Information Technology Department of Electronics and Communication EngineeringCARE College of EngineeringTiruchirappalli620009India Department of Electronics and Communication Engineering KPR Institute of Engineering and TechnologyCoimbatore641407India Department of Mathematics and statistics College of ScienceTaif UniversityP.O.Box 11099Taif 21944Saudi Arabia Mathematics Department Faculty of ScienceSohag UniversitySohagEgypt Deanship of scientific Research King Abdulaziz UniversityJeddahSaudi Arabia Department of Electrical and Computer Engineering Faculty of EngineeringKing Abdulaziz UniversityJeddahSaudi Arabia

The rapid development of biomedical imaging modalities led to its wide application in disease ***-based diagnostic procedures are proficient and non-invasive in nature to carry out secondary diagnostic processes ***,physicians examine the characteristics of tongue prior to *** this scenario,to get rid of qualitative aspects,tongue images can be quantitatively inspected for which a new disease diagnosis model is *** model can reduce the physical harm made to the *** tongue image analytical methodologies have been proposed ***,there is a need exists to design an intelligent Deep Learning(DL)based disease diagnosis *** this motivation,the current research article designs an Intelligent DL-basedDisease Diagnosis method using Biomedical Tongue Images called IDLDD-BTI *** proposed IDLDD-BTI model incorporates Fuzzy-based Adaptive Median Filtering(FADM)technique for noise removal ***,squeezeNet model is employed as a feature extractor in which the hyperparameters of squeezeNet are tuned using Oppositional Glowworm swarm Optimization(OGsO)*** last,Weighted Extreme Learning Machine(WELM)classifier is applied to allocate proper class labels for input tongue color *** design of OGsO algorithm for squeezeNet model shows the novelty of the *** assess the enhanced diagnostic performance of the presented IDLDD-BTI technique,a series of simulations was conducted on benchmark dataset and the results were examined in terms of several *** resultant experimental values highlighted the supremacy of IDLDD-BTI model over other state-of-the-art methods.

关键词： Biomedical images image processing tongue color image deep learning squeezenet disease diagnosis

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Leveraging Blockchain with Optimal Deep Learning-Based Drug supply Chain Management for Pharmaceutical Industries

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Computers, Materials & Continua 2023年第11期77卷 2341-2357页

作者： shanthi Perumalsamy venkatesh Kaliyamurthy Department of Networking and Communications School of ComputingSRM Institute of Science and TechnologyKattankulathurTamil Nadu603203India

Due to its complexity and involvement of numerous stakeholders,the pharmaceutical supply chain presents many challenges that companies must overcome to deliver necessary medications to patients *** pharmaceutical supply chain poses different challenging issues,encompasses supply chain visibility,cold-chain shipping,drug counterfeiting,and rising prescription drug prices,which can considerably surge out-of-pocket patient ***(BC)offers the technical base for such a scheme,as it could track legitimate drugs and avoid fake *** designers presented the procedure of BC with fabric for creating a secured drug supplychain management(DsCM)*** this motivation,the study presents a new blockchain with optimal deep learning-enabled DsCM and recommendation scheme(BCODL-DsCMRs)for Pharmaceutical ***,Hyperledger fabric is used for DsC management,enabling effective tracking processes in the smart pharmaceutical *** addition,a hybrid deep belief network(HDBN)model is used to suggest the best or top-rated medicines to healthcare providers and *** spotted hyena optimizer(sHO)algorithm is used to optimize the performance of the HDBN *** design of the HsO algorithm for tuning the HDBN model demonstrates the novelty of the *** presented model is tested on the UCI repository’s open-access drug reviews database.

关键词： Drug supply chain pharmaceutical industry deep learning blockchain hyper ledger fabric security drug recommendation

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An Optimized Novel Trust-Based security Mechanism Using Elephant Herd Optimization

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Computer systems science & Engineering 2023年第3期44卷 2489-2500页

作者： saranya veerapaulraj M.Karthikeyan s.sasipriya A.s.shanthi Tamilnadu College of Engineering CoimbatoreIndia Krishna College of Engineering CoimbatoreIndia

Routing strategies and security issues are the greatest challenges in Wireless sensor Network(WsN).Cluster-based routing Low Energy adaptive Clustering Hierarchy(LEACH)decreases power consumption and increases net-work lifetime *** WsN is a challenging issue faced by *** systems are very helpful in detecting interfering nodes in *** have successfully applied Nature-inspired Metaheuristics Optimization Algorithms as a decision-making factor to derive an improved and effective solution for a real-time optimization *** metaheuristic Elephant Herding Optimizations(EHO)algorithm is formulated based on ele-phant herding in their *** considers two herding behaviors to solve and enhance optimization *** on Elephant Herd Optimization,a trust-based security method is built in this *** proposed routing selects routes to destination based on the trust values,thus,finding optimal secure routes for transmitting *** results have demonstrated the effectiveness of the proposed EHO based *** Average Packet Loss Rate of the proposed Trust Elephant Herd Optimization performs better by 35.42%,by 1.45%,and by 31.94%than LEACH,Elephant Herd Optimization,and Trust LEACH,respec-tively at Number of Nodes *** the proposed routing is efficient in selecting secure routes,the average packet loss rate is significantly reduced,improving the network’s *** is also observed that the lifetime of the network is enhanced with the proposed Trust Elephant Herd Optimization.

关键词： Wireless sensor network low energy adaptive clustering hierarchy trust systems elephant herding optimizations algorithm trust-based elephant herd optimization

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Reckoning the sIX1 mutation＇s effects in branchio-oto-renal syndrome - A bioinformatics approach

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Frontiers in Biology 2015年第5期10卷 448-457页

作者： B. Preethi v. shanthi K. Ramanathan Industrial Biotechnology Division School of Bio Sciences and Technology VIT University Vellore - 632014 Tamil Nadu India

Branchio-oto-renal syndrome （BOR） is autosomal dominant disorder which generates hearing impairment and kidney failures in affected individuals. The disease genomic maps were drawn back in recent years, demonstrating, missense mutations responsible in disease were located in sIX1, EYA1 and EYA2 genes. We try to uncover molecular biology of the syndrome with bioinformatics perspective, taking s1X1 and EYA2 protein interaction at center point. The study initiated with 23 natural mutations of sIX1 gene. They were first analyzed with prediction servers like sIFT, PolyPhen2, I Mutant, sNPs＆GO, PHD-sNP and Panther, to identify their impact on their structural stability and function. subsequently it narrowed down to seven consistent with our quest. They were analyzed on IUPred disorder prediction server. Later sIX1 and its all mutant proteins were docked with EYA2 protein using GRAMM-X server. The binding affinity of docked structures was analyzed using DFIRE2 algorithm. The results justify the earlier wet laboratory studies and indicate the reason behind them. Finally we summarize that the proven inactivity of all other mutants is due to the structural disorder created by mutations, hence usual molecular interaction is hindered; strangely protein interaction takes place at DNA binding site of sIX1 mutants.

关键词： branchio-oto-renal syndrome (BOR) hearing loss damaging mutations sIX1 EYA2 protein-protein interactions

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Fabrication of three-dimensional graphene anode for augmenting performance in microbial fuel cells

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Carbon Resources Conversion 2019年第2期2卷 134-140页

作者： Alka Pareek J.shanthi sravan s.venkata Mohan Bioengineering and Environmental science Lab CEEFFCSIR-Indian Institute of Chemical Technology(CSIR-IICT)Hyderabad 500007India Academy of scientific and Innovative Research(AcsIR) India

In the present work,we have reported the synthesis of 3D graphene structures by simple chemical reduction method for application in microbial fuel cell(MFC)as an *** synthesis procedure includes synthesis of graphene oxide by modified Hummers method followed by simultaneous reduction of graphene oxide and the formation of *** 3D graphene structures are characterized using X-ray diffraction and Raman spectroscopy *** characterization is carried out to study the capacitive properties and impedance studies of electrodes in conductive electrolyte.3D graphene electrodes show remarkably high capacitive current,charge storage and lower charge transfer resistance as estimated through cyclic voltammetry and Nyquist *** order to evaluate the performance of 3D graphene electrodes in MFC,power density and polarization curves are recorded in three configurations by varying terminal electron acceptors(TEA)viz.,dissolved oxygen(MFC-DO),potassium ferricyanide and MFC without TEA(MFC-NDO).3D graphene electrodes exhibits maximum power density of 0.49 mW/m^(2) in potassium ferricyanide followed by MFC-DO(0.36 mW/m^(2))and MFC-NDO(0.34 mW/m^(2)).Present work highlights the viability of chemically synthesized 3D graphene electrodes as an efficient anode material in MFC.

关键词： Microbial fuel cell 3D graphene Wastewater treatment Chemical reduction Graphene electrodes

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