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Anti-diabetic activity of quercetin extracted from Phyllanthus emblica ***: In silico and in vivo approaches

Journal of Pharmaceutical Analysis 2018年第2期8卷 109-118页

作者： Prabhu Srinivasan S.vijayakumar Swaminathan kothandaraman Manogar Palani Computational Phytochemistry Lab PG and Research Department of Botany and Microbiology A. V. V. M Sri Pushpam College (Autonomous) Department of Physics RKM Vivekananda College (Autonomous)

In this study, molecular interactions of the ligands, quercetin, gallic acid, and metformin with various diabetes mellitus-related protein targets, such as glycogen phosphorylase and peroxisome proliferatoractivated receptor gamma, were assessed. It was revealed that quercetin possesses good binding affinity to both targets. Quercetin is a major constituent of methanolic extracts of Phyllanthus emblica fruit. The antihyperglycemic effect of quercetin in streptozotocin(STZ)-induced diabetic rats was examined. The isolated quercetin administered at a dose of 75 mg/kg body weight produced a maximum decrease of14.78% in blood glucose levels in the diabetic rats after 7 days of treatment. Furthermore, quercetin doses of 50 and 75 mg/kg were shown to significantly improve the profiles of triglycerides, high-density lipoprotein, very-low-density lipoprotein, low-density lipoprotein, and total cholesterol at the end of the study in STZ-induced diabetic rats. The administration of quercetin(25, 50, and 75 mg/kg body weight)daily for 28 days in STZ-induced diabetic rats resulted in a significant decrease in blood glucose and urine sugar levels, with a considerable rise in plasma insulin and hemoglobin levels. Therefore, quercetin is a potential drug with antidiabetic and antihyperglycemic action mediated by changes in the levels of glucose, cholesterol, and triglycerides as indicated by in silico and in vivo studies.

关键词： Bioactive molecules Glycogen phosphorylase Molecular docking Phyllanthus emblica Quercetin Albino Wister male rats

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SHT-based public auditing protocol with error tolerance in FDL-empowered IoVs

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Digital Communications and Networks 2024年第1期10卷 142-149页

作者： kui Zhu Yongjun Ren Jian Shen Pandi vijayakumar Pradip kumar Sharma School of Computer and Software Nanjing University of Information Science&TechnologyNanjing210044China Peng Cheng Laboratory Shenzhen518000China Department of Computer Science and Engineering University College of Engineering TindivanamTamil Nadu604001India Department of Computing Science University of AberdeenAberdeenAB243UEUK

With the intelligentization of the Internet of Vehicles(lovs),Artificial Intelligence(Al)technology is becoming more and more essential,especially deep *** Deep Learning(FDL)is a novel distributed machine learning technology and is able to address the challenges like data security,privacy risks,and huge communication overheads from big raw data ***,FDL can only guarantee data security and privacy among multiple clients during data *** the data sets stored locally in clients are corrupted,including being tampered with and lost,the training results of the FDL in intelligent IoVs must be negatively *** this paper,we are the first to design a secure data auditing protocol to guarantee the integrity and availability of data sets in FDL-empowered ***,the cuckoo filter and Reed-Solomon codes are utilized to guarantee error tolerance,including efficient corrupted data locating and *** addition,a novel data structure,Skip Hash Table(SHT)is designed to optimize data ***,we illustrate the security of the scheme with the Computational Diffie-Hellman(CDH)assumption on bilinear *** theoretical analyses and performance evaluations demonstrate the security and efficiency of our scheme for data sets in FDL-empowered IoVs.

关键词： Internet of vehicles Federated deep learning Data security Data auditing Data locating and recovery

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Assessment of public perspectives and barriers towards dengue preventive practices using the Health Belief Model in Puducherry,India:A cross-sectional study

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Asian Pacific Journal of Tropical Medicine 2024年第8期17卷 358-368,I0001页

作者： Dharani Govindasamy Gnanasekaran Vijalakashmi Balakrishnan vijayakumar Arya Rahul Indian Council of Medical Research-Vector Control Research Centre Deapartment of Health ResearchMinistry of Health and Family WelfareGovernment of IndiaPuducherryIndia

Objective:To assess the perspectives and barriers towards dengue preventive practices among the residents of Puducherry,***:A cross-sectional survey was conducted in 300 households in Puducherry,using a population-proportionate(7:3)distribution from urban and rural areas by grid *** adult interview per household was conducted and the participants were selected using a kISH grid.A semi-structured questionnaire based on the Health Belief Model(HBM)with additional questions on knowledge assessment was *** was assessed based on the correctness of answers and the HBM scores were calculated on a 5-point Likert *** were categorized based on the median score under each *** regression was used for adjusted analysis and models were built to predict the performances in each ***:Four percent of the participants lacked basic knowledge regarding dengue *** 208(69.3%)participants did not consider themselves at risk of contracting dengue within the next year,majority perceived dengue as a disease with low *** 49.3%(148)were skeptical about the benefit of time and money spent on dengue *** government efforts were stated as the major barrier(47.0%)and frequent reminders(142,47.3%)as the major cue to *** above 50 years(aOR 1.78,95%CI 1.04-3.06,P=0.037)and rural locality(aOR 2.68,95%CI 1.52-4.71,P=0.001)were found to be significantly associated with poor knowledge *** participants had a significantly higher chance to perceive low susceptibility as compared to the rural counterparts(aOR 1.74,95%CI 1.05-2.9,P=0.03).Participants with less than a high school education had low perceived benefits(aOR 2.46,95%CI 1.52-3.96,Pkey gaps in dengue prevention,including low perceived susceptibility,mild disease perception,limited knowledge of breeding sites,and overrelian

关键词： Dengue Public perspectives Prevention Barriers Health belief model

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Improvised Seagull Optimization Algorithm for Scheduling Tasks in Heterogeneous Cloud Environment

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Computers, Materials & Continua 2023年第2期74卷 2461-2478页

作者： Pradeep krishnadoss vijayakumar kedalu Poornachary Parkavi krishnamoorthy Leninisha Shanmugam Vellore Institute of Technology Chennai632014India

Well organized datacentres with interconnected servers constitute the cloud computing *** requests are submitted through an interface to these servers that provide service to them in an on-demand *** scientific applications that get executed at cloud by making use of the heterogeneous resources being allocated to them in a dynamic manner are grouped under NP hard problem *** scheduling in cloud poses numerous challenges impacting the cloud *** not handled properly,user satisfaction becomes *** recently researchers had come up with meta-heuristic type of solutions for enriching the task scheduling activity in the cloud *** prime aim of task scheduling is to utilize the resources available in an optimal manner and reduce the time span of task *** improvised seagull optimization algorithm which combines the features of the Cuckoo search(CS)and seagull optimization algorithm(SOA)had been proposed in this work to enhance the performance of the scheduling activity inside the cloud computing *** proposed algorithm aims to minimize the cost and time parameters that are spent during task scheduling in the heterogeneous cloud *** evaluation of the proposed algorithm had been performed using the Cloudsim 3.0 toolkit by comparing it with Multi objective-Ant Colony Optimization(MO-ACO),ACO and Min-Min *** proposed SOA-CS technique had produced an improvement of 1.06%,4.2%,and 2.4%for makespan and had reduced the overall cost to the extent of 1.74%,3.93%and 2.77%when compared with PSO,ACO,IDEA algorithms respectively when 300 vms are *** comparative simulation results obtained had shown that the proposed improvised seagull optimization algorithm fares better than other contemporaries.

关键词： Cloud computing task scheduling cuckoo search(CS) seagull optimization algorithm(SOA)

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Double-Blockchain Assisted Secure and Anonymous Data Aggregation for Fog-Enabled Smart Grid

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Engineering 2022年第1期8卷 159-169页

作者： Siguang Chen Li Yang Chuanxin Zhao vijayakumar Varadarajan kun Wang Jiangsu key Lab of Broadband Wireless Communication and Internet of Things Nanjing University of Posts and TelecommunicationsNanjing 210003China Jiangsu Engineering Research Center of Communication and Network Technology Nanjing University of Posts and TelecommunicationsNanjing 210003China Anhui Provincial key Laboratory of Network and Information Security Anhui Normal UniversityWuhu 241000China School of Computer Science and Engineering Vellore Institute of TechnologyChennai 600127India Department of Electrical and Computer Engineering University of CaliforniaLos AngelesCA 90095USA

As a future energy system,the smart grid is designed to improve the efficiency of traditional power systems while providing more stable and reliable ***,this efficient and reliable service relies on collecting and analyzing users’electricity consumption data frequently,which induces various security and privacy *** address these challenges,we propose a double-blockchain assisted secure and anonymous data aggregation scheme for fog-enabled smart grid named ***,we design a three-tier architecture-based data aggregation framework by integrating fog computing and the blockchain,which provides strong support for achieving efficient and secure data collection in smart ***,we develop a secure and anonymous data aggregation mechanism with low computational overhead by jointly leveraging the Paillier encryption,batch aggregation signature and anonymous *** particular,the system achieves fine-grained data aggregation and provides effective support for power dispatching and price adjustment by the designed double-blockchain and two-level data ***,the superiority of the proposed scheme is illustrated by a series of security and computation cost analyses.

关键词： Blockchain Fog computing Homomorphic encryption Smart grid Anonymity

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MCWOA Scheduler:Modified Chimp-Whale Optimization Algorithm for Task Scheduling in Cloud Computing

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Computers, Materials & Continua 2024年第2期78卷 2593-2616页

作者： Chirag Chandrashekar Pradeep krishnadoss vijayakumar kedalu Poornachary Balasundaram Ananthakrishnan School of Computer Science and Engineering Vellore Institute of TechnologyChennai600127India Center for Cyber Physical Systems School of Computer Science and EngineeringVellore Institute of TechnologyChennai600127India

Cloud computing provides a diverse and adaptable resource pool over the internet,allowing users to tap into various resources as *** has been seen as a robust solution to relevant challenges.A significant delay can hamper the performance of IoT-enabled cloud ***,efficient task scheduling can lower the cloud infrastructure’s energy consumption,thus maximizing the service provider’s revenue by decreasing user job processing *** proposed Modified Chimp-Whale Optimization Algorithm called Modified Chimp-Whale Optimization Algorithm(MCWOA),combines elements of the Chimp Optimization Algorithm(COA)and the Whale Optimization Algorithm(WOA).To enhance MCWOA’s identification precision,the Sobol sequence is used in the population initialization phase,ensuring an even distribution of the population across the solution ***,the traditional MCWOA’s local search capabilities are augmented by incorporating the whale optimization algorithm’s bubble-net hunting and random search mechanisms into MCWOA’s position-updating *** study demonstrates the effectiveness of the proposed approach using a two-story rigid frame and a simply supported beam *** outcomes reveal that the new method outperforms the original MCWOA,especially in multi-damage detection *** excels in avoiding false positives and enhancing computational speed,making it an optimal choice for structural damage *** efficiency of the proposed MCWOA is assessed against metrics such as energy usage,computational expense,task duration,and *** simulated data indicates that the new MCWOA outpaces other methods across all *** study also references the Whale Optimization Algorithm(WOA),Chimp Algorithm(CA),Ant Lion Optimizer(ALO),Genetic Algorithm(GA)and Grey Wolf Optimizer(GWO).

关键词： Cloud computing scheduling chimp optimization algorithm whale optimization algorithm

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Shining Light on Anion-Mixed Nanocatalysts for Efficient Water Electrolysis: Fundamentals, Progress, and Perspectives

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Nano-Micro Letters 2022年第3期14卷 79-119页

作者： Yaoda Liu Paranthaman vijayakumar Qianyi Liu Thangavel Sakthivel Fuyi Chen Zhengfei Dai State key Laboratory for Mechanical Behavior of Materials Xi’an Jiaotong UniversityXi’an 710049People’s Republic of China State key Laboratory of Solidification Processing Northwestern Polytechnical UniversityXi’an 710072People’s Republic of China

Hydrogen with high energy density and zero carbon emission is widely acknowledged as the most promising candidate toward world’s carbon neutrality and future sustainable ***-splitting is a constructive technology for unpolluted and high-purity H2 production,and a series of non-precious electrocatalysts have been developed over the past *** further improve the catalytic activities,metal doping is always adopted to modulate the 3d-electronic configuration and electron-donating/accepting(e-DA)properties,while for anion doping,the electronegativity variations among different non-metal elements would also bring some potential in the modulations of e-DA and metal valence for tuning the *** this review,we summarize the recent developments of the many different anion-mixed transition metal compounds(e.g.,nitrides,halides,phosphides,chalcogenides,oxyhydroxides,and borides/borates)for efficient water electrolysis ***,we have introduced the general information of water-splitting and the description of anion-mixed electrocatalysts and highlighted their complementary functions of mixed ***,some latest advances of anion-mixed compounds are also categorized for hydrogen and oxygen evolution *** rationales behind their enhanced electrochemical performances are *** but not least,the challenges and future perspectives are briefly proposed for the anion-mixed water dissociation catalysts.

关键词： Multianions Electrocatalysts Water electrolysis Hydrogen energy Oxygen evolution

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Novel ligand-based docking; molecular dynamic simulations;and absorption, distribution, metabolism, and excretion approach to analyzing potential acetylcholinesterase inhibitors for Alzheimer's disease

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Journal of Pharmaceutical Analysis 2018年第6期8卷 413-420页

作者： Subramaniyan vijayakumar Palani Manogar Srinivasan Prabhu Ram Avadhar Sanjeevkumar Singh Computational Phytochemistry Laboratory PG and Research Department of Botany and Microbiology AVVM Sri Pushpam College (Autonomous) Poondi Computer Aided Drug Design and Molecular Modeling Laboratory Department of Bioinformatics Alagappa University

Acetylcholinesterase(AChE) plays an important role in Alzheimer's disease(AD). The excessive activity of AChE causes various neuronal problems, particularly dementia and neuronal cell deaths. Generally, antiAChE drugs induce some serious neuronal side effects in humans. Therefore, this study sought to identify alternative drug molecules from natural products with fewer side effects than those of conventional drugs for treating AD. To achieve this, we developed computational methods for predicting drug and target binding affinities using the Schrodinger suite. The target and ligand molecules were retrieved from established databases. The target enzyme has 539 amino acid residues in its sequence alignment. Ligand molecules of 20 bioactive molecules were obtained from different kinds of plants, after which we performed critical analyses such as molecular docking; molecular dynamic(MD) simulations; and absorption, distribution, metabolism, and excretion(ADME) analysis. In the docking studies, the natural compound rutin showed a superior docking score of à 12.335 with a good binding energy value ofà73.313 kcal/mol. Based on these findings, rutin and the target complex was used to perform MD simulations to analyze rutin stability at 30 ns. In conclusion, our study demonstrates that rutin is a superior drug candidate for AD. Therefore, we propose that this molecule is worth further investigation using in vitro studies.

关键词： Alzheimer's disease Acetylcholinesterase Phytocompounds Molecular docking Free energy calculations Molecular dynamic simulations

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LSTM Based Spectrum Prediction for Real-Time Spectrum Access for IoT Applications

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Intelligent Automation & Soft Computing 2023年第3期35卷 2805-2819页

作者： R.Nandakumar vijayakumar Ponnusamy Aman kumar Mishra kSR Institute for Engineering and Technology Tiruchencode637215India ECE Department SRMISTChengalpattuChennai603202India

In the Internet of Things(IoT)scenario,many devices will communi-cate in the presence of the cellular network;the chances of availability of spec-trum will be very scary given the presence of large numbers of mobile users and large amounts of *** prediction is very encouraging for high trafﬁc next-generation wireless networks,where devices/machines which are part of the Cognitive Radio Network(CRN)can predict the spectrum state prior to transmission to save their limited energy by avoiding unnecessarily sen-sing radio *** short-term memory(LSTM)is employed to simulta-neously predict the Radio Spectrum State(RSS)for two-time slots,thereby allowing the secondary node to use the prediction result to transmit its information to achieve lower waiting time hence,enhanced performance capacity.A frame-work of spectral transmission based on the LSTM prediction is formulated,named as positive prediction and sensing-based spectrum *** proposed scheme provides an average maximum waiting time gain of 2.88 *** proposed scheme provides 0.096 bps more capacity than a conventional energy detector.

关键词： Cognitive radio network encoder-decoder LSTM waiting time capacity

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Intelligent Financial Fraud Detection Using Artificial Bee Colony Optimization Based Recurrent Neural Network

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Intelligent Automation & Soft Computing 2023年第8期37卷 1483-1498页

作者： T.karthikeyan M.Govindarajan V.vijayakumar Department of Computer Science and Engineering Annamalai UniversityAnnamalai NagarTamil NaduIndia Department of Computer Science and Engineering Sri Manakula Vinayagar Engineering CollegePuducherryIndia

Frauds don’t follow any recurring *** require the use of unsupervised learning since their behaviour is continually ***-sters have access to the most recent technology,which gives them the ability to defraud people through online *** make assumptions about consumers’routine behaviour,and fraud develops *** learning must be used by fraud detection systems to recognize online payments since some fraudsters start out using online channels before moving on to other *** a deep convolutional neural network model to identify anomalies from conventional competitive swarm optimization pat-terns with a focus on fraud situations that cannot be identified using historical data or supervised learning is the aim of this paper Artificial Bee Colony(ABC).Using real-time data and other datasets that are readily available,the ABC-Recurrent Neural Network(RNN)categorizes fraud behaviour and compares it to the current *** compared to the current approach,the findings demonstrate that the accuracy is high and the training error is minimal in ABC_*** this paper,we measure the Accuracy,F1 score,Mean Square Error(MSE)and Mean Absolute Error(MAE).Our system achieves 97%accuracy,92%precision rate and F1 score 97%.Also we compare the simulation results with existing methods.

关键词： Fraud activity optimization deep learning classification online transaction neural network credit card

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