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Titanate incorporated anodized coating on magnesium alloy for corrosion protection,antibacterial responses and osteogenic enhancement

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Journal of Magnesium and Alloys 2022年第4期10卷 1109-1123页

作者： saranya.k Bhuvaneswari.S Suvro Chatterjee Rajendran.N Department of Chemistry College of Engineering Guindy CampusAnna UniversityChennaiTamil Nadu 600025India Vascular Biology Lab AU-KBC Research CentreAnna UniversityChromepetChennaiTamil Nadu 600044India

The rapid degradation of Mg alloy was reduced by incorporating titanate on a fluorine-based anodized layer.The coating shows(i)excellent biomineralization ability,(ii)improved local and periodical corrosion behavior and(iii)enhanced expression of osteogenic factors(Runx2,Col 1,OCN and OPN)along with(iv)the antibacterial property.The fluoride and magnesium ions dissolution from the anodized layer is responsible for the better expression of osteogenic factors and antibacterial behavior.The preparation of the titanate incorporated anodized Mg alloy(Ti-AMg)is a facile solution to overcome the implant-associated bacterial infections with required biological functions including progression of bone ingrowth and biocompatibility.

关键词： AZ31 Magnesium alloy Titanate Anodization Localized electrochemical impedance spectroscopy Osteogenic factor Anti-bacterial

A comparison of the quality of life of parents of children using hearing aids and those using cochlear implants

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Journal of Otology 2022年第4期17卷 211-217页

作者： saranya Arya Mundayoor Prabuddha Bhatarai Prashanth Prabhu All India Institute of Speech and Hearing MysoreIndia

Objective:The goal of this study was to evaluate the quality of life of parents of children who use hearing aids(HA)with those who use cochlear implants(CI)in the Indian context and document any differences found.Methods:The kannada version of the AQoL-4D was administered in a modified fashion to 131 parents(87 HA and 44 CI).Sociodemographic details were collected for supplemental information on the intervention strategy used.Results:A total of 49 parents(29 HA and 20 CI)responded to the questionnaire sent.The mean total scores for both the groups were similar(HA group=17.9(SD=5.5),CI group=17.2(SD=3.4)),as was the score for the first subscale(HA group=8.6(SD=2.9);CI group=8.5(SD=2.6))of the AQoL-4D.No significant differences were found between the two groups on either scores[Total Score:U(N_(HA)=29,NCI=20)=280.5,z=0.194,p>0.05;Subscale 1 Score:U(N_(HA)=29,NCI=20)=281.5,z=-0.176,p>0.05].The degree of hearing loss in the hearing aid group was equivalent to that of the cochlear implant group but this did not appear to influence parental quality of life.Conclusion:Parents of children with hearing aids and cochlear implants appear to be similar on several psychosocial factors in the realms of functional,social,and psychological well-being.In terms of parental quality of life,hearing aids and cochlear implants appear to be equally effective intervention techniques.

关键词： Quality of life Parents Cochlear implants Hearing aids Children Hearing impaired

Early Detection of Heartbeat from Multimodal Data Using RPA Learning with kDNN-SAE

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Computer Systems Science & Engineering 2023年第4期45卷 545-562页

作者： A.k.S.saranya T.Jaya Department of Electronics and Communication Engineering Ponjesly College of EngineeringNagercoilIndia Department of Electronics and Communication Engineering CSI Institute of TechnologyNagercoilIndia

Heartbeat detection stays central to cardiovascular an electrocardiogram(ECG)is used to help with disease diagnosis and management.Existing Convolutional Neural Network(CNN)-based methods suffer from the less generalization problem thus;the effectiveness and robustness of the traditional heartbeat detector methods cannot be guaranteed.In contrast,this work proposes a heartbeat detector krill based Deep Neural Network Stacked Auto Encoders(kDNN-SAE)that computes the disease before the exact heart rate by combining features from multiple ECG Signals.Heartbeats are classified independently and multiple signals are fused to estimate life threatening conditions earlier without any error in classification of heart beat.This work contained Training and testing stages,in the preparation part at first the Adaptive Filter Enthalpy-based Empirical Mode Decomposition(EMD)is utilized to eliminate the motion artifact in the signal.At that point,the robotic process automation(RPA)learning part extracts the effective features are extracted,and normalized the value of the feature then estimated utilizing the RPA loss function.At last kDNN-SAE prepared training for the data stored in the dataset.In the subsequent stage,input signal compute motion artifact and RPA Learning the evaluation part determines the detection of Heartbeat.So early diagnosis of heart failures is an essential factor.The results of the experiments show that our proposed method has a high score outcome of 0.9997.Comparable to the CIF,which reaches 0.9990.The CNN and Artificial Neural Network(ANN)had less score 0.95115 and 0.90147.

关键词： Deep neural network krill herd optimization stack auto-encoder adaptive filter enthalpy based empirical mode decomposition robotic process automation

Pathology of atherosclerotic coronary artery disease in the young Indian population

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Forensic Sciences Research 2019年第3期4卷 241-246页

作者： Pradeep Vaideeswar Shashank Tyagi saranya Singaravel Department of Pathology(Cardiovascular&Thoracic Division) Seth GS Medical College&KEM HospitalMumbaiIndia Department of Forensic Medicine&Toxicology Seth GS Medical College&KEM HospitalMumbaiIndia

Atherosclerotic coronary artery disease (CAD) is of great concern in young adults because of its potential to cause great incapacitation.This arena of cardiology has gained importance in South Asian countries,particularly India due to increased prevalence that is related to traditional risk factors,altered life styles and inherent risk factors.In this study,we sought to evaluate,at autopsy,the pathology of atherosclerotic CAD in young patients with ischemic heart disease (IHD).A 10-year retrospective autopsy-based study was carried out in a large tertiary-care centre and patients aged ≤45 years with IHD were selected.Out of 545 autopsied cases of IHD,95 patients (17.4%) were young.Among these 95 patients,84 (88.4%) had IHD related to atherosclerotic CAD;the youngest patient was 18years old.Predictably there was sole involvement of left anterior descending artery and the presence of fibrous plaques.Irrespective of the plaque morphology,the commonest complication was thrombosis produced by plaque erosion seen in 36.9% of patients.Acute coronary insufficiency was noted in 52 patients (61.9%),while healed infarctions were surprisingly noted in 28 patients (33.3%).Screening for IHD in the young population may help to improve prognosis by detecting subclinical disease,although more studies are necessary to establish reference limits for this young population.Additional research must also focus on treatment concerns that are specific to young patients.

关键词： Forensic sciences forensic pathology ischemic heart disease coronary atherosclerosis young adults sudden cardiac death

IoT Information Status Using Data Fusion and Feature Extraction Method

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Computers, Materials & Continua 2022年第1期70卷 1857-1874页

作者： S.S.saranya N.Sabiyath Fatima Department of Computer Science and Engineering B.S.Abdur Rahman Crescent Institute of Science and TechnologyVandalurChennaiTamil NaduIndia

The Internet of Things(IoT)role is instrumental in the technological advancement of the healthcare industry.Both the hardware and the core level of software platforms are the progress resulted from the accompaniment of Medicine 4.0.Healthcare IoT systems are the emergence of this foresight.The communication systems between the sensing nodes and the processors;and the processing algorithms to produce output obtained from the data collected by the sensors are the major empowering technologies.At present,many new technologies supplement these empowering technologies.So,in this research work,a practical feature extraction and classification technique is suggested for handling data acquisition besides data fusion to enhance treatment-related data.In the initial stage,IoT devices are gathered and pre-processed for fusion processing.Dynamic Bayesian Network is considered an improved balance for tractability,a tool for CDF operations.Improved Principal Component Analysis is deployed for feature extraction along with dimension reduction.Lastly,this data learning is attained through Hybrid Learning Classifier Model for data fusion performance examination.In this research,Deep Belief Neural Network and Support VectorMachine are hybridized for healthcare data prediction.Thus,the suggested system is probably a beneficial decision support tool for multiple data sources prediction and predictive ability enhancement.

关键词： IoT data fusion improved principal component analysis hybrid learning model

Design and analysis of multi-channel drop filter using dual L defected hexagonal photonic crystal ring resonator

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Digital Communications and Networks 2020年第1期6卷 136-143页

作者： D.saranya Shoba Mohan A.Rajesh school of electronics and engineering vit universityvelloreindia college of science and engineering hamad bin khalifa universitydohaqatar

In this paper,dual L defected hexagonal Photonic Crystal Ring Resonator(PCRR)using Channel Drop Filter(CDF)is designed for Coarse Wavelength Division Multiplexing(CWDM)systems.In this structure,the external rods of the ring resonator are arranged in a hexagon and the internal rods are removed in L arrangement for introducing defects.Scatter rods are used to prevent leakage.By using the L defected hexagonal resonator,a multi-channel CDF is designed,which exhibits multiple wavelengths of CWDM(1500 nm–1600 nm)region.In addition,the selection of rod size and the position of rods in the proposed multi-channel CDF are validated by varying the radius of coupling and scattering rods,as well as the position of resonators,respectively.By using plane wave expansion and opti Finite Difference Time Domain(FDTD)method,the electromagnetic wave propagation and the photonic band gap are obtained.

关键词： Channel drop filter Photonic crystal ring resonator Coarse wavelength division multiplexing Finite difference time domain

Detection of Diabetic Retinopathy from Retinal Images Using DenseNet Models

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Computer Systems Science & Engineering 2023年第4期45卷 279-292页

作者： R.Nandakumar P.saranya Vijayakumar Ponnusamy Subhashree Hazra Antara Gupta Department of ECE K S R Institute for Engineering and TechnologyTiruchengode637215India Department of Computer Science and Engineering SRM Institute of Science and TechnologyChennai603203India Department of Electronics and Communication and Engineering SRM Institute of Science and TechnologyChennai603203India

A prevalent diabetic complication is Diabetic Retinopathy(DR),which can damage the retina’s veins,leading to a severe loss of vision.If treated in the early stage,it can help to prevent vision loss.But since its diagnosis takes time and there is a shortage of ophthalmologists,patients suffer vision loss even before diagnosis.Hence,early detection of DR is the necessity of the time.The primary purpose of the work is to apply the data fusion/feature fusion technique,which combines more than one relevant feature to predict diabetic retinopathy at an early stage with greater accuracy.Mechanized procedures for diabetic retinopathy analysis are fundamental in taking care of these issues.While profound learning for parallel characterization has accomplished high approval exactness’s,multi-stage order results are less noteworthy,especially during beginning phase sickness.Densely Connected Convolutional Networks are suggested to detect of Diabetic Retinopathy on retinal images.The presented model is trained on a Diabetic Retinopathy Dataset having 3,662 images given by APTOS.Experimental results suggest that the training accuracy of 93.51%0.98 precision,0.98 recall and 0.98 F1-score has been achieved through the best one out of the three models in the proposed work.The same model is tested on 550 images of the kaggle 2015 dataset where the proposed model was able to detect No DR images with 96%accuracy,Mild DR images with 90%accuracy,Moderate DR images with 89%accuracy,Severe DR images with 87%accuracy and Proliferative DR images with 93%accuracy.

关键词： Convolutional Neural Networks vision loss pathogenic blood vessels DenseNet AlexNet ResNet

Computational identification and analysis of neurodegenerative disease associated protein kinases in hominid genomes

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Genes & Diseases 2016年第3期3卷 228-237页

作者： saranya Jayapalan Devika Subramanian Jeyakumar Natarajan Data Mining and Text Mining Lab Department of BioinformaticsBharathiar UniversityCoimbatoreIndia

Protein kinases play an important role in the incidence of neurodegenerative diseases.However their incidence in non-human primates is found to be very low.Small differences among the genomes might influence the disease susceptibilities.The present study deals with finding the genetic differences of protein kinases in humans and their three closest evolutionary partners chimpanzee,gorilla and orangutan for three neurodegenerative diseases namely,Alzheimer’s,Parkinson’s and Huntington’s diseases.In total 47 human protein kinases associated with three neurodegenerative diseases and their orthologs from other three nonhuman primates were identified and analyzed for any possible susceptibility factors in humans.Multiple sequence alignment and pairwise sequence alignment revealed that,18 human protein kinases including DYRk1A,RPS6kB1,and GRk6 contained significant indels and substitutions.Further phosphorylation site analysis revealed that eight kinases including MARk2 and LTk contained sites of phosphorylation exclusive to human genomes which could be particular candidates in determining disease susceptibility between human and non-human primates.Final pathway analysis of these eight kinases and their targets revealed that these kinases could have long range consequences in important signaling pathways which are associated with neurodegenerative diseases.

关键词： Hominids Interaction analysis Neurodegenerative diseases Phosphorylation sites Protein kinases

Crosstalk between Wnt and bone morphogenetic protein signaling during osteogenic differentiati

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World Journal of Stem Cells 2024年第2期16卷 102-113页

作者： Pakkath Narayanan Arya Iyyappan saranya Nagarajan Selvamurugan Department of Biotechnology School of BioengineeringSRM Institute of Science and TechnologyKattankulathur 603203India

Mesenchymal stem cells(MSCs)originate from many sources,including the bone marrow and adipose tissue,and differentiate into various cell types,such as osteoblasts and adipocytes.Recent studies on MSCs have revealed that many transcription factors and signaling pathways control osteogenic development.Osteogenesis is the process by which new bones are formed;it also aids in bone remodeling.Wnt/β-catenin and bone morphogenetic protein(BMP)signaling pathways are involved in many cellular processes and considered to be essential for life.Wnt/β-catenin and BMPs are important for bone formation in mammalian development and various regulatory activities in the body.Recent studies have indicated that these two signaling pathways contribute to osteogenic differen-tiation.Active Wnt signaling pathway promotes osteogenesis by activating the downstream targets of the BMP signaling pathway.Here,we briefly review the molecular processes underlying the crosstalk between these two pathways and explain their participation in osteogenic differentiation,emphasizing the canonical pathways.This review also discusses the crosstalk mechanisms of Wnt/BMP signaling with Notch-and extracellular-regulated kinases in osteogenic differentiation and bone development.

关键词： Bone Mesenchymal stem cells Osteogenic differentiation Wnt/β-catenin Bone morphogenetic proteins