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Poor maternal nutrition inhibits muscle development in ovine offspring

Journal of Animal science and Biotechnology 2015年第1期6卷 79-89页

作者： sarah A Reed joseline s raja Maria L Hoffman steven A Zinn Kristen E Govoni Department of Animal science University of ConnecticutStorrsCT 06269USA

Background： Maternal over and restricted nutrition has negative consequences on the muscle of offspring by reducing muscle fiber number and altering regulators of muscle growth. To determine if over and restricted maternal nutrition affected muscle growth and gene fed 60%, 100% or 140% of National Research Council and protein expression in offspring, 36 pregnant ewes were requirements from d 31 ＋ 1,3 of gestation until parturition. Lambs from control-fed （CON）, restricted-fed （REs） or over-fed （OVER） ewes were necropsied within 1 d of birth （n = 18） or maintained on a control diet for 3 mo （n = ] 5）. semitendinosus muscle was collected for immunohistochemistry, and protein and gene expression analysis. Results： Compared with CON, muscle fiber cross-sectional area （CsA） increased in REs （58%） and OVER （47%） lambs at 1 d of age （P〈 0.01）; however at 3 mo, CsA decreased 15% and 17% compared with CON, respectively （P 〈 0.01）. Compared with CON, muscle lipid content was increased in OVER （212.4%） and REs （92.5%） at d 1 （P 〈 0.0001）. Muscle lipid content was increased 36.1% in OVER and decreased 23.6% in REs compared with CON at 3 mo （P 〈 0.0001）. At d 1, myostatin mRNA abundance in whole muscle tended to be greater in OVER （P = 0.07） than CON. Follistatin mRNA abundance increased in OVER （P = 0.04） and tended to increase in REs （P = 0.06） compared with CON at d 1. However, there was no difference in myostatin or follistatin protein expression （P 〉 0.3）. Phosphorylated Akt （ser473） was increased in REs at 3 mo compared with CON （P = 0.006）. Conclusions： In conclusion, maternal over and restricted nutrient intake alters muscle lipid content and growth of offspring, possibly through altered gene and protein expression.

关键词： Growth Maternal nutrition Muscle development sheep

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MXenes and heterostructures-based electrocatalysts for hydrogen evolution reaction:Recent developments and future outlook

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Journal of Energy Chemistry 2024年第5期92卷 176-206页

作者： Abdul Hanan Hafiz Taimoor Ahmed Awan Faiza Bibi raja Rafidah raja sulaiman Wai Yin Wong Rashmi Walvekar seema singh Mohammad Khalid sunway Centre for Electrochemical Energy and sustainable Technology(sCEEsT) School of Engineering and TechnologySunway UniversityNo.5 Jalan UniversitiBandar Sunway47500 Petaling JayaSelangorMalaysia Fuel Cell Institute Universiti Kebangsaan Malaysia43600 UKM BangiSelangorMalaysia Faculty of Innovation and Technology School of EngineeringChemical Engineering ProgrammeNo.1 Jalan Taylor’sTaylor’s University Malaysia47500 Subang JayaSelangorMalaysia Chitkara Centre for Research and Development Chitkara UniversityHimachal Pradesh 174103India school of Applied and Life sciences Uttaranchal UniversityDehradunUttarakhand 248007India Manipal Institute of Technology Manipal Academy of Higher EducationManipal 576104KarnatakaIndia Centre of Research Impact and Outcome Chitkara UniversityPunjab 140401India

The increasing focus on electrocatalysis for sustainable hydrogen(H_(2))production has prompted significant interest in MXenes,a class of two-dimensional(2D)materials comprising metal carbides,carbonitrides,and nitrides.These materials exhibit intriguing chemical and physical properties,including excellent electrical conductivity and a large surface area,making them attractive candidates for the hydrogen evolution reaction(HER).This scientific review explores recent advancements in MXene-based electrocatalysts for HER kinetics.It discusses various compositions,functionalities,and explicit design principles while providing a comprehensive overview of synthesis methods,exceptional properties,and electro-catalytic approaches for H_(2) production via electrochemical reactions.Furthermore,challenges and future prospects in designing MXenes-based electrocatalysts with enhanced kinetics are highlighted,emphasizing the potential of incorporating different metals to expand the scope of electrochemical reactions.This review suggests possible efforts for developing advanced MXenes-based electrocatalysts,particularly for efficient H_(2) generation through electrochemical water-splitting reactions..

关键词： MXenes Electrocatalyst Water splitting Hydrogen Generation Clean Energy

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Epidemiological and histopathological characteristics of thyroid carcinoma in a Tunisian health care center

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World Journal of Otorhinolaryngology-Head and Neck surgery 2024年第1期10卷 37-42页

作者： Maissa Ben Thayer Fatma Khanchel Imen Helal Dorra Chiboub Hedhli Raoueh Ehsen Ben Brahim raja Jouini Aschraf Chadli-Debbiche Faculty of Medicine of Tunis Tunis El Manar UniversityTunisTunisia Depatment of Pathology Habib Thameur's HospitalTunisTunisia Department of Otorhinolaryngology-Head and Neck surgery Habib Thameur's HospitalTunisTunisia

Background:Thyroid carcinoma(TC)accounts for almost 0.5%–1%of total malignancies.Its incidence is increasing rapidly worldwide.several studies have drawn up the epidemiological profile of TC and its clinical and pathological features.However,to date,no similar studies have been conducted in Tunisia.Aims:To establish an epidemiological profile of TC in a Tunisian health care institute and to analyze its clinical and histopathological characteristics in our institute.Materials and Methods:We present a retrospective study reviewing the cases of TC diagnosed in our institution in a 4-year period.Results:We collected a sample of 192 cases of TC.It consisted of 31 males and 161 females(83.8%)with a sex-ratio M/F of 0.19.The mean age was 46.4 years.Papillary thyroid carcinoma was the most frequent histological subtype.The multifocality rate was 33.8%.The mean size of TC was 2.2±1.9 cm.60.9%of TC were staged pT1 and 20.3%had nodal involvement.Papillary thyroid microcarcinomas were noted in 37.5%of cases.Conclusion:Our results were consistent with those of the literature.A high proportion of pT1 and pN0 tumors were noted in our series,suggesting that TC's diagnosis and management was performed at an early stage of the disease in our institution.In addition,our study enabled us to notice the impact of the Coronavirus disease 19 crisis on the management of TC in our institution.Further studies are needed to establish the epidemiological profile of TC in Tunisia and to assess its clinical and pathological features.

关键词： coronavirus disease 19 epidemiology papillary thyroid carcinoma papillary thyroid microcarcinoma pathology thyroid carcinoma

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Optimizing spatial Pattern Analysis in serial Remote sensing Images through Empirical Mode Decomposition and Ant Colony Optimization

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Journal of Harbin Institute of Technology(New series) 2024年

作者： J srinivasan s Uma saleem raja Abdul samad Jayabrabu Ramakrishnan Department of Information Technology Panimalar Engineering College Information Technology Department College of Computing and Information sciences University of Technology and Applied sciences-shinas 324 Department of Information Technology and security College of Computer science and Information Technology Jazan University Department of Computer Applications Madanapalle Institute of Technology & science (MITs)

serial remote sensing images offer a valuable means of tracking the evolutionary changes and growth of a specific geographical area over time. Although the original images may provide limited insights， they harbor considerable potential for identifying clusters and patterns. The aggregation of these serial remote sensing images (sRsI) becomes increasingly viable as distinct patterns emerge in diverse scenarios， such as suburbanization， the expansion of native flora， and agricultural activities. In a novel approach， we propose an innovative method for extracting sequential patterns by combining Ant Colony Optimization and Empirical Mode Decomposition. This integration of the newly developed Empirical Mode Decomposition (EMD) and Ant Colony Optimization (ACO) techniques proves remarkably effective in identifying the most significant characteristic features within serial remote sensing images， guided by specific criteria. Our findings highlight a substantial improvement in the efficiency of sequential pattern mining through the application of this unique hybrid method， seamlessly integrating EMD and ACO for feature selection. This study exposes the potential of our innovative methodology， particularly in the realms of urbanization， native vegetation expansion， and agricultural activities.

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An Efficient stabbing Based Intrusion Detection Framework for sensor Networks

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Computer systems science & Engineering 2022年第10期43卷 141-157页

作者： A.Arivazhagi s.raja Kumar Department of Computer science and Engineering University College of EngineeringAriyalurTamilnaduIndia Department of Mathematics University College of EngineeringAriyalurTamilnaduIndia

Intelligent Intrusion Detection system(IIDs)for networks provide a resourceful solution to network security than conventional intrusion defence mechanisms like a firewall.The efficiency of IIDs highly relies on the algorithm performance.The enhancements towards these methods are utilized to enhance the classification accuracy and diminish the testing and training time of these algorithms.Here,a novel and intelligent learning approach are known as the stabbing of intrusion with learning framework(sILF),is proposed to learn the attack features and reduce the dimensionality.It also reduces the testing and training time effectively and enhances Linear support Vector Machine(l-sVM).It constructs an auto-encoder method,an efficient learning approach for feature construction unsupervised manner.Here,the inclusive certified signature(ICs)is added to the encoder and decoder to preserve the sensitive data without being harmed by the attackers.By training the samples in the preliminary stage,the selected features are provided into the classifier(lsVM)to enhance the prediction ability for intrusion and classification accuracy.Thus,the model efficiency is learned linearly.The multi-classification is examined and compared with various classifier approaches like conventional sVM,Random Forest(RF),Recurrent Neural Network(RNN),sTL-IDs and game theory.The outcomes show that the proposed l-sVM has triggered the prediction rate by effectual testing and training and proves that the model is more efficient than the traditional approaches in terms of performance metrics like accuracy,precision,recall,F-measure,pvalue,MCC and so on.The proposed sILF enhances network intrusion detection and offers a novel research methodology for intrusion detection.Here,the simulation is done with a MATLAB environment where the proposed model shows a better trade-off compared to prevailing approaches.

关键词： Network security sensor network intrusion detection learning framework linear support vector machine the detection mechanism

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Conditional Generative Adversarial Network Approach for Autism Prediction

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Computer systems science & Engineering 2023年第1期44卷 741-755页

作者： K.Chola raja s.Kannimuthu Department of Computer science and Engineering Sri Eshwar College of EngineeringCoimbatore641202TamilnaduIndia Department of Information Technology Karpagam College of EngineeringCoimbatore641032TamilnaduIndia

Autism spectrum Disorder(AsD)requires a precise diagnosis in order to be managed and rehabilitated.Non-invasive neuroimaging methods are disease markers that can be used to help diagnose AsD.The majority of available techniques in the literature use functional magnetic resonance imaging(fMRI)to detect AsD with a small dataset,resulting in high accuracy but low generality.Traditional supervised machine learning classification algorithms such as support vector machines function well with unstructured and semi structured data such as text,images,and videos,but their performance and robustness are restricted by the size of the accompanying training data.Deep learning on the other hand creates an artificial neural network that can learn and make intelligent judgments on its own by layering algorithms.It takes use of plentiful low-cost computing and many approaches are focused with very big datasets that are concerned with creating far larger and more sophisticated neural networks.Generative modelling,also known as Generative Adversarial Networks(GANs),is an unsupervised deep learning task that entails automatically discovering and learning regularities or patterns in input data in order for the model to generate or output new examples that could have been drawn from the original dataset.GANs are an exciting and rapidly changingfield that delivers on the promise of generative models in terms of their ability to generate realistic examples across a range of problem domains,most notably in image-to-image translation tasks and hasn't been explored much for Autism spectrum disorder prediction in the past.In this paper,we present a novel conditional generative adversarial network,or cGAN for short,which is a form of GAN that uses a generator model to conditionally generate images.In terms of prediction and accuracy,they outperform the standard GAN.The pro-posed model is 74%more accurate than the traditional methods and takes only around 10 min for training even with a huge dataset.

关键词： Autism classification attributes imaging adversarial fMRI functional graph neural networks

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Hierarchical stream Clustering Based NEWs summarization system

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Computers, Materials & Continua 2022年第1期70卷 1263-1280页

作者： M.Arun Manicka raja s.swamynathan Department of Computer science and Engineering RMKCollege of Engineering and TechnologyChennai602106India Department of Information science and Technology College of Engineering GuindyAnna UniversityChennai600025India

News feed is one of the potential information providing sources which give updates on various topics of different domains.These updates on various topics need to be collected since the domain specific interested users are in need of important updates in their domains with organized data from various sources.In this paper,the news summarization system is proposed for the news data streams from Rss feeds and Google news.since news stream analysis requires live content,the news data are continuously collected for our experimentation.Themajor contributions of thiswork involve domain corpus based news collection,news content extraction,hierarchical clustering of the news and summarization of news.Many of the existing news summarization systems lack in providing dynamic content with domain wise representation.This is alleviated in our proposed systemby tagging the news feed with domain corpuses and organizing the news streams with the hierarchical structure with topic wise representation.Further,the news streams are summarized for the users with a novel summarization algorithm.The proposed summarization system generates topic wise summaries effectively for the user and no system in the literature has handled the news summarization by collecting the data dynamically and organizing the content hierarchically.The proposed system is compared with existing systems and achieves better results in generating news summaries.The Online news content editors are highly benefitted by this system for instantly getting the news summaries of their domain interest.

关键词： News feed content similarity parallel crawler collaborative filtering hierarchical clustering news summarization

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An Efficient Framework for Utilizing Underloaded servers in Compute Cloud

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Computer systems science & Engineering 2023年第1期44卷 143-156页

作者： M.Hema s.Kanaga suba raja Department of Information Technology Easwari Engineering CollegeChennai600089India Department of Computer science and Engineering Easwari Engineering CollegeChennai600089India

In cloud data centers,the consolidation of workload is one of the phases during which the available hosts are allocated tasks.This phenomenon ensures that the least possible number of hosts is used without compromise in meeting the service Level Agreement(sLA).To consolidate the workloads,the hosts are segregated into three categories:normal hosts,under-loaded hosts,and over-loaded hosts based on their utilization.It is to be noted that the identification of an extensively used host or underloaded host is challenging to accomplish.Thresh-old values were proposed in the literature to detect this scenario.The current study aims to improve the existing methods that choose the underloaded hosts,get rid of Virtual Machines(VMs)from them,andfinally place them in some other hosts.The researcher proposes a Host Resource Utilization Aware(HRUAA)Algorithm to detect those underloaded and place its virtual machines on different hosts in a vibrant Cloud environment.The mechanism presented in this study is contrasted with existing mechanisms empirically.The results attained from the study estab-lish that numerous hosts can be shut down,while at the same time,the user's workload requirement can also be met.The proposed method is energy-efficient in workload consolidation,saves cost and time,and leverages active hosts.

关键词： Workload consolidation energy consumption under load server resource utilization

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structural,optical and dielectric investigations on RECr_(0.85)Mn_(0.15)O_(3)(RE=Ho,Gd and Pr) nanoparticles

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Journal of Rare Earths 2024年第2期42卷 399-408,I0006页

作者： Komal Kanwar sonali Pradhan s.satapathy Yugandhar Bitla Neeraj Panwar Department of Physics Central University of Rajasthan BandarsindrAjmer305817RajasthanIndia Laser Material section HBNIRaja Ramanna Centre for Advanced TechnologyIndore452013India

We hereby report the room-temperature structural and optical characterization of RECr_(0.85)Mn_(0.15)O_(3)(RECMO,RE=Ho,Gd and Pr) compounds synthesized by the auto-combustion sol-gel route.Their low temperature dielectric properties are also presented.The RECMO compounds crystallize in an orthorhombic Pbnm symmetry with an average grain size range of 51-80 nm.structural analysis reveals an increase in the structural distortion compared to that of the undoped bulk compounds.Optical measurements exhibit a significant reduction in bandgap values for RECMO nanoparticles when compared with their undoped bulk compounds.Further,from the absorbance measurements various optical parameters such as skin depth,extinction coefficient,refractive index and optical conductivity were also calculated.The dielectric analysis confirms the lower values of the dielectric permittivity and dielectric loss than those of their corresponding bulk compounds.AC conductivity versus frequency and temperature data are fitted according to the Jonscher's power law and Arrhenius law,respectively.The small polaron hopping is responsible for the electric conduction in these compounds.The tunability of the optical and dielectric properties as a result of substitution and particle size reduction makes these materials useful for various potential applications in photocatalysis,optoelectronics and low permittivity dielectrics.

关键词： Rare-earth orthochromites Nanoparticles Optical properties Dispersion parameters Dielectric properties small polaron hopping

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Medicago truncatula resources to study legume biology and symbiotic nitrogen fixation

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Fundamental Research 2023年第2期3卷 219-224页

作者： raja sekhar Nandety Jiangqi Wen Kirankumar s.Mysore Institute for Agricultural Biosciences Oklahoma State University3210 Sam Noble ParkwayArdmoreOK 73401United States UsDA-ARs Cereal Crops Research UnitEdward T.Schafer Agricultural Research CenterFargoND 58102United States Department of Biochemistry and Molecular Biology Oklahoma State UniversityStillwaterOK 74078United States

Medicago truncatula is a chosen model for legumes towards deciphering fundamental legume biology,especially symbiotic nitrogen fixation.Current genomic resources for M.truncatula include a completed whole genome sequence information for R108 and Jemalong A17 accessions along with the sparse draft genome sequences for other 226 M.truncatula accessions.These genomic resources are complemented by the availability of mutant resources such as retrotransposon(Tnt1)insertion mutants in R108 and fast neutron bombardment(FNB)mutants in A17.In addition,several M.truncatula databases such as small secreted peptides(ssPs)database,transporter protein database,gene expression atlas,proteomic atlas,and metabolite atlas are available to the research community.This review describes these resources and provide information regarding how to access these resources.

关键词： Medicago truncatula Model legume Medicago resources Tnt1 Mutagenesis Medicago gene atlas

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