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Diversity of Sodium Transporter HKT1;5 in Genus Oryza

Rice science 2022年第1期29卷 31-46,I0002-I0017页

作者： Shalini PULIPATI Suji SOMASUNDARAM Nitika RANA kavitha kumaresan Mohamed SHAFI Peter CIVÁŇ Gothandapani SELLAMUTHU Deepa JAGANATHAN Prasanna Venkatesan RAMARAVI S.PUNITHA Kalaimani RAJU Shrikant S.MANTRI R.SOWDHAMINI Ajay PARIDA Gayatri VENKATARAMAN M.S.Swaminathan Research Foundation Chennai 600113India National Agri-Food Biotechnology Institute Punjab 140306India Krishi Vigyan Kendra Kanyakumari 629901India National Centre for Biological Sciences/Tata Institute of Fundamental Research Bangalore 560065India National Research Institute for Agriculture Food and Environment UniversityClermont-AuvergneClermont-Ferrand 63000France Forest Molecular Entomology Laboratory Faculty of Forestry and Wood SciencesCzech University of Life SciencesPraguePraha 16500Czech Republic Tamil Nadu Agricultural University Coimbatore 641003India International Business Machines India Chennai 600125India Institute of Life Sciences Bhubaneswar 751023India

Asian cultivated rice shows allelic variation in sodium transporter,OsHKT1;5,correlating with shoot sodium exclusion(salinity tolerance).These changes map to intra/extracellularly-oriented loops that occur between four transmembrane-P loop-transmembrane(MPM)motifs in OsHKT1;***1;5 sequences from more recently evolved Oryza species(***/*** complex species)contain two expansions that involve two intracellularly oriented loops/helical regions between MPM domains,potentially governing transport characteristics,while more ancestral HKT1;5 sequences have shorter intracellular *** compared homology models for homoeologous OcHKT 1;5-K and OcHKT1;5-L from halophytic *** to identify complementary amino acid residues in OcHKT1;5-L that potentially enhance affinity for Na+.Using haplotyping,we showed that Asian cultivated rice accessions only have a fraction of HKT1;5 diversity available in progenitor wild rice species(*** and ***).Progenitor HKT1;5 haplotypes can thus be used as novel potential donors for enhancing cultivated rice salinity *** Asian rice accessions,10 non-synonymous HKT1;5 haplotypic groups *** HKT1;5 haplotypic diversities occur in cultivated indica gene pool compared to *** Haplotypes 2 and 10 occur in mutually exclusive japonica and indica groups,corresponding to haplotypes in *** salt-sensitive and salt-tolerant landraces,*** distinct haplotype partitioning may have originated in separate ancestral gene pools of indica and japonica,or from different haplotypes selected during *** of specific HKT1;5 haplotypes within the 3000 rice dataset may relate to eco-physiological fitness in specific geo-climatic and/or edaphic contexts.

关键词： HKT1 5 diversity single nucleotide polymorphism haplotype bacterial artificial chromosome salinity tolerance sodium transporter Oryza species

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A Novel Eccentric Intrusion Detection Model Based on Recurrent Neural Networks with Leveraging LSTM

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Computers, Materials & Continua 2024年第3期78卷 3089-3127页

作者： Navaneetha Krishnan Muthunambu Senthil Prabakaran Balasubramanian Prabhu Kavin Kishore Senthil Siruvangur kavitha Chinnadurai Jehad Ali Department of Computer Applications Karpagam College of EngineeringCoimbatore641032India Department of Computer Science and Engineering Karpagam College of EngineeringCoimbatore641032India Department of Data Science and Business Systems College of Engineering and TechnologySRM Institute of Science and TechnologyKattankulathur603203India Department of Computer Science and Engineering Sathyabama Institute of Science and TechnologyJeppiaar NagarRajiv Gandhi SalaiChennai600119India Department of AI Convergence Network Ajou UniversitySuwon16499Korea

The extensive utilization of the Internet in everyday life can be attributed to the substantial accessibility of online services and the growing significance of the data transmitted via the ***,this development has expanded the potential targets that hackers might *** adequate safeguards,data transmitted on the internet is significantly more susceptible to unauthorized access,theft,or *** identification of unauthorised access attempts is a critical component of cybersecurity as it aids in the detection and prevention of malicious *** research paper introduces a novel intrusion detection framework that utilizes Recurrent Neural Networks(RNN)integrated with Long Short-Term Memory(LSTM)*** proposed model can identify various types of cyberattacks,including conventional and distinctive *** networks,a specific kind of feedforward neural networks,possess an intrinsic memory *** Neural Networks(RNNs)incorporating Long Short-Term Memory(LSTM)mechanisms have demonstrated greater capabilities in retaining and utilizing data dependencies over extended *** such as data types,training duration,accuracy,number of false positives,and number of false negatives are among the parameters employed to assess the effectiveness of these models in identifying both common and unusual *** are utilised in conjunction with LSTM to support human analysts in identifying possible intrusion events,hence enhancing their decision-making capabilities.A potential solution to address the limitations of Shallow learning is the introduction of the Eccentric Intrusion Detection *** model utilises Recurrent Neural Networks,specifically exploiting LSTM *** proposed model achieves detection accuracy(99.5%),generalisation(99%),and false-positive rate(0.72%),the parameters findings reveal that it is superior to state-of-the-art techniques.

关键词： Cybersecurity intrusion detection machine learning leveraging long short-term memory(LLSTM) CICIDS2019 dataset innovative cyberattacks

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An Intelligent Big Data Security Framework Based on AEFS-KENN Algorithms for the Detection of Cyber-Attacks from Smart Grid Systems

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Big Data Mining and Analytics 2024年第2期7卷 399-418页

作者： Sankaramoorthy Muthubalaji Naresh Kumar Muniyaraj Sarvade Pedda Venkata Subba Rao kavitha Thandapani Pasupuleti Rama Mohan Thangam Somasundaram Yousef Farhaoui Department of Electrical and Electronics Engineering CMR College of Engineering&TechnologyHyderabad 501401India Department of Electronics and Communication Engineering Vardhaman College of Engineering KacharamShamshabad 501218India Department of Electronics and Communication Engineering Sreenidhi Institute of Science and TechnologyHyderabad 501301India Department of Electronics and Communication Engineering Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and TechnologyChennai 600062India Department of Electrical and Electronics Engineering Bharat Institute of Engineering and TechnologyHyderabad 501510India Department of Computer Science and Engineering Amrita School of ComputingAmrita Vishwa VidhyapeethamBengaluru 560035India T-IDMS Department of Computer ScienceFaculty of Sciences and TechniquesMoulay Ismail UniversityErrachidia 52000Morocco

Big data has the ability to open up innovative and ground-breaking prospects for the electrical grid,which also supports to obtain a variety of technological,social,and financial *** is an unprecedented amount of heterogeneous big data as a consequence of the growth of power grid technologies,along with data processing and advanced *** main obstacles in turning the heterogeneous large dataset into useful results are computational burden and information *** original contribution of this paper is to develop a new big data framework for detecting various intrusions from the smart grid systems with the use of AI ***,an AdaBelief Exponential Feature Selection(AEFS)technique is used to efficiently handle the input huge datasets from the smart grid for boosting ***,a Kernel based Extreme Neural Network(KENN)technique is used to anticipate security vulnerabilities more *** Polar Bear Optimization(PBO)algorithm is used to efficiently determine the parameters for the estimate of radial basis ***,several types of smart grid network datasets are employed during analysis in order to examine the outcomes and efficiency of the proposed AdaBelief Exponential Feature Selection-Kernel based Extreme Neural Network(AEFS-KENN)big data security *** results reveal that the accuracy of proposed AEFS-KENN is increased up to 99.5%with precision and AUC of 99%for all smart grid big datasets used in this study.

关键词： smart grid Machine Learning(ML) big data analytics AdaBelief Exponential Feature Selection(AEFS) Polar Bear Optimization(PBO) Kernel Extreme Neural Network(KENN)

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Downwash airflow distribution pattern of hexa-copter unmanned aerial vehicles

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International Journal of Agricultural and Biological Engineering 2024年第4期17卷 24-34页

作者： Dengeru Yallappa Ramasamy kavitha Allimuthu Surendrakumar Kannan Balaji Balakrishnan Suthakar Ayyasamy Paramasivam Mohan Kumar Yathendranaik Ravi Narayananaik Ashoka Kumar Kavan Department of Farm Machinery and Power Engineering Agricultural Engineering College and Research InstituteTamil Nadu Agricultural UniversityCoimbatore

In recent times,the use of vertical take-off and landing(VTOL)multi-rotor Unmanned Aerial Vehicle(UAVs)for spraying chemical pesticides against weeds and pests has recently become *** current aerial spray application research is primarily focused on examining the influence of UAV spraying parameters such as flight height,travel speed,rotor configuration,droplet size,payload and wind *** downwash airflow velocity generated by the UAV rotor propeller has a significant impact on the droplet deposition process.A test rig was developed to measure the downwash airflow pattern generated by the rotor propeller of a *** this investigation,a six-rotor electric autonomous UAV sprayer was used to investigate the parameters and distribution laws of downwash airflow *** downwash airflow velocity was measured using portable anemometers mounted on the test rig at radial positions viz.,0 m,0.5 m,1 m,1.5 m and 2 m,perpendicular to(X)and parallel to the UAV’s flight direction(Y).The experiment was conducted at three levels of hover height,viz.,1 m,2 m and 3 m(Z)and three levels of payload,viz.,0 kg,5 kg,and 10 *** special downwash airflow distribution pattern was analysed using the Python programming language(Version 3.7).Results show that the downwash airflow velocity generated by the radial position of the UAV rotor is evenly distributed on the rotating loop and the standard deviation of the downwash airflow velocity is less than 0.5 m/*** maximum downwash airflow velocity of 13.8 m/s was observed below the rotor at 10 kg payload capacity,1 m hover height(Z),and 0.5 m in the *** minimum downwash wind field of 0.3 m/s was observed at 0 kg pay load capacity,1 m height,and 2 m in the *** downwash airflow velocity along each position in the radial direction of the rotor increases initially and then *** downwash airflow distribution results helps in mounting of spray nozzle configuration to drone sprayer which helps to

关键词： downwash air payload rotor propeller flight height distribution analysis flight direction

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Fuzzy Difference Equations in Diagnoses of Glaucoma from Retinal Images Using Deep Learning

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Computer Modeling in Engineering & Sciences 2024年第4期139卷 801-816页

作者： D.Dorathy Prema kavitha L.Francis Raj Sandeep Kautish Abdulaziz S.Almazyad Karam M.Sallam Ali Wagdy Mohamed Department of Mathematics Voorhees CollegeVelloreTamil NaduIndia Chandigarh Group of Colleges JhanjeriMohaliPunjabIndia Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityP.O.Box 51178Riyadh11543Saudi Arabia Faculty of Science and Technology School of IT and SystemsUniversity of CanberraCanberraAustralia Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Applied Science Research Center Applied Science Private UniversityAmman11937Jordan

The intuitive fuzzy set has found important application in decision-making and machine *** enrich and utilize the intuitive fuzzy set,this study designed and developed a deep neural network-based glaucoma eye detection using fuzzy difference equations in the domain where the retinal images *** image detections are categorized as normal eye recognition,suspected glaucomatous eye recognition,and glaucomatous eye *** degrees associated with weighted values are calculated to determine the level of concentration between the fuzzy partition and the retinal *** proposed model was used to diagnose glaucoma using retinal images and involved utilizing the Convolutional Neural Network(CNN)and deep learning to identify the fuzzy weighted regularization between *** methodology was used to clarify the input images and make them adequate for the process of glaucoma *** objective of this study was to propose a novel approach to the early diagnosis of glaucoma using the Fuzzy Expert System(FES)and Fuzzy differential equation(FDE).The intensities of the different regions in the images and their respective peak levels were *** the peak regions were identified,the recurrence relationships among those peaks were then *** partitioning was done due to varying degrees of similar and dissimilar concentrations in the *** and dissimilar concentration levels and spatial frequency generated a threshold image from the combined fuzzy matrix and *** distinguished between a normal and abnormal eye condition,thus detecting patients with glaucomatous eyes.

关键词： Convolutional Neural Network(CNN) glaucomatous eyes fuzzy difference equation intuitive fuzzy sets image segmentation retinal images

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Investigations on pool boiling critical heat flux, transient characteristics and bonding strength of heater wire with aqua based reduced graphene oxide nanofluids

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Chinese Journal of Chemical Engineering 2018年第3期26卷 445-454页

作者： R. Kamatchi G. kumaresan School of Mechanical Engineering VIT University Vellore Institute of Technology 632014 Tamil Nadu India Department of Mechanical Engineering Bannari Amman Institute of Technology Sathyamangalam 638401 Tamil Nadu India

In the present work, the pool boiling critical heat flux, transient heat transfer characteristics, and bonding strength of thin Ni-Cr wire with aqua based reduced graphene oxide(r GO) nanofluids are experimentally studied. Results indicate:(i) the critical heat flux(CHF) of 0.01, 0.05, 0.1, 0.2, and 0.3 g·L^(-1) concentrations of r GO-water nanofluids varies from 1.42 to 2.40 MW·m^(-2);(ii) the CHF remains same for the tested samples during transient heat transfer studies and(iii) a constant value of CHF upto 10 tests when the nanocoated Ni-Cr wire is tested with DI water and deterioration occurs beyond this which implies a chance of peel off of r GO layer below the critical coating thickness.

关键词： Reduced graphene oxide Pool boiling Nanoparticle deposition Transient characteristics

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Preliminary studies for a new antibiotic from the marine mollusk Melo melo(Lightfoot,1786)

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Asian Pacific Journal of Tropical Medicine 2011年第4期4卷 310-314页

作者： Kanagasabapathy Sivasubramanian Samuthirapandian Ravichandran kumaresan M Centre of Advanced Study in Marine Biology Annamalai University

Objective:To search for new bioactive compounds from marine mollusks Melo melo(***). Methods:Preliminary work for bioactive compound was identified by using disc diffusion methods against human *** analyses of compound were done by using TLC, *** also estimate the amount of protein in the samples by following Biuret ***:In antibacterial activity the maximum diameter of 24 mm zone of inhibition was recorded against Klebsiella pneumoniae(***) strain of the mucus extract and minimum zone of inhibition of 11 mm was observed in Salmonella typhi(***) strain of body tissue *** antifungal activity of the extraction shows maximum activity against Trichophyton mentagarophytes(***)(14 mm) and minimum activity was recorded in Aspergillus flavus(***)(11 mm).The extract of mucus,nerve tissue,body tissue and kidney that showed antimicrobial activity was subjected to TLC to determine the presence of the peptides and amide groups,and also subjected to SDS-PACE to estimate the molecular weight of proteins in a clear band were detected in the gel that represented kidney,body tissue,brain and mucus represent 14,17,22,45 ***:The extracts from marine mollusks *** is the potential source of producing bioactive compounds against human pathogens and can be used for synthesis of new drugs.

关键词： Antibacterial Antifungal TLC SDS-PAGE Melo melo

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Factors influencing adoption of soil and water conservation practices in the northwest Ethiopian highlands

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International Soil and Water Conservation Research 2020年第1期8卷 80-89页

作者： Agere Belachew Wuletaw Mekuria kavitha Nachimuthu Department of Rural Development and Agricultural Extension University of GondarP.O.Box 196GondarEthiopia RD National Arts and Science(Co-education)College ErodeTamilnaduIndia

Soil erosion has long been a problem in the Ethiopian highlands in general and Dembecha district in particular. The objective of this study was to identify factors influencing adoption of soil and water conservation practices. Both quantitative and qualitative data were collected from primary and sec-ondary sources. The primary data were collected from respondent samples and key informants through interview and personal observation. The secondary data were collected from sources such as books, journals, statistical reports and official documents. A multistage sampling technique was applied to select sample households. Sample sizes of 150 households were selected using simple random sampling. Both descriptive statistics and a multivariate probit econometric model were employed to analyze the data. The model results revealed that the likelihood of decisions to adopt soil bund, stone bund, check dam and strip cropping were 74, 56, 29 and 56%respectively. The joint probability of adopting the selected soil and water conservation practices was 14.2%. The model results also confirmed that age, sex, education level, household size, livestock holding, land size, access to credit, access to extension service and training were significant factors that affected the adoption of soil and water conservation practices in the study area. Based on our findings, the study suggests that the government and stakeholders should focus on strengthening the provision of formal and non-formal training and facilitate an effective extension service.

关键词： Adoption Multivariate probit model Soil degradation Strip cropping

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OSCILLATORY BEHAVIOR OF SOLUTIONS OF CERTAIN THIRD ORDER MIXED NEUTRAL DIFFERENCE EQUATIONS

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Acta Mathematica Scientia 2013年第1期33卷 218-226页

作者： E.THANDAPANI N.kavitha Ramanujan Institute for Advanced Study in Mathematics University of MadrasChennai 600 005India

The objective of this paper is to study the oscillatory and asymptotic properties of the mixed type third order neutral difference equation of the form△（an△^2（xn＋bnxn-τ1＋cnxn＋τ2））＋qnx^βn＋1-σ1＋pnx^^βn＋1＋σ2=0,where （an）, （bn}, （cn}, （qn} and （pn} are positive real sequences, β is a ratio of odd positive integers, τ1, τ2, and σ2 are positive integers. We establish some sufficient conditions which ensure that all solutions are either oscillatory or converges to zero. Some examples are presented to illustrate the main results.

关键词： oscillation third order mixed type neutral difference equation

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An Efficient Stacked-LSTM Based User Clustering for 5G NOMA Systems

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Computers, Materials & Continua 2022年第9期72卷 6119-6140页

作者： S.Prabha kumaresan Chee Keong Tan Yin Hoe Ng Faculty of Engineering Multimedia UniversityCyberjaya63100Malaysia School of Information Technology Monash UniversitySubang Jaya47500Malaysia

Non-orthogonal multiple access(NOMA)has been a key enabling technology for the fifth generation(5G)cellular *** on the NOMA principle,a traditional neural network has been implemented for user clustering(UC)to maximize the NOMA system’s throughput performance by considering that each sample is independent of the prior and the subsequent ***,the prediction of UC for the future ones is based on the current clustering information,which is never used again due to the lack of memory of the ***,to relate the input features of NOMA users and capture the dependency in the clustering information,time-series methods can assist us in gaining a helpful insight into the *** its mathematical complexity,the essence of time series comes down to examining past behavior and extending that information into the ***,in this paper,we propose a novel and effective stacked long short term memory(S-LSTM)to predict the UC formation of NOMA users to enhance the throughput performance of the 5G-based NOMA *** the proposed strategy,the S-LSTM is modelled to handle the time-series input data to improve the predicting accuracy of UC of the NOMA users by implementing multiple LSTM layers with hidden *** implemented LSTM layers have feedback connections that help to capture the dependency in the clustering information as it propagates between the ***,we develop,train,validate and test the proposed model to predict the UC formation for the futures ones by capturing the dependency in the clustering information based on the time-series *** results demonstrate that the proposed scheme effectively predicts UC and thereby attaining near-optimal throughput performance of 98.94%compared to the exhaustive search method.

关键词： Non-orthogonal multiple access(NOMA) deep neural network(DNN) long short term memory(LSTM) temporal channel user clustering

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