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classification of conversational Sentences Using an Ensemble Pre-Trained Language Model with the Fine-Tuned Parameter

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computers, Materials & continua 2024年第2期78卷 1669-1686页

作者： r.Sujatha K.Nimala Department of Networking and communications SRM Institute of Science and TechnologyKattankulathurChengalpattuTamilnadu603203India

Sentence classification is the process of categorizing a sentence based on the context of the *** categorization requires more semantic highlights than other tasks,such as dependence parsing,which requires more syntactic *** existing strategies focus on the general semantics of a conversation without involving the context of the sentence,recognizing the progress and comparing *** ensemble pre-trained language model was taken up here to classify the conversation sentences from the conversation *** conversational sentences are classified into four categories:information,question,directive,and *** classification label sequences are for analyzing the conversation progress and predicting the pecking order of the *** of Bidirectional Encoder for representation of Transformer(BErT),robustly Optimized BErT pretraining Approach(roBErTa),Generative Pre-Trained Transformer(GPT),DistilBErT and Generalized Autoregressive Pretraining for Language Understanding(XLNet)models are trained on conversation corpus with *** tuning approach is carried out for better performance on sentence *** Ensemble of Pre-trained Language Models with a Hyperparameter Tuning(EPLM-HT)system is trained on an annotated conversation *** proposed approach outperformed compared to the base BErT,GPT,DistilBErT and XLNet transformer *** proposed ensemble model with the fine-tuned parameters achieved an F1_score of 0.88.

关键词： Bidirectional encoder for representation of transformer conversation ensemble model fine-tuning generalized autoregressive pretraining for language understanding generative pre-trained transformer hyperparameter tuning natural language processing robustly optimized BErT pretraining approach sentence classification transformer models

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Modified Black Widow Optimization-Based Enhanced threshold Energy Detection Technique for Spectrum Sensing in cognitive radio Networks

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computer Modeling in Engineering & Sciences 2024年第3期138卷 2339-2356页

作者： r.Saravanan r.Muthaiah A.rajesh School of computing SASTRA Deemed UniversityThanjavur613401India School of Electrical&Electronics Engineering SASTRA Deemed UniversityThanjavur613401India

this study develops an Enhanced threshold Based Energy Detection approach(ETBED)for spectrum sensing in a cognitive radio *** threshold identification method is implemented in the received signal at the secondary user based on the square *** proposed method is implemented with the signal transmission of multiple outputs-orthogonal frequency division ***,the proposed method is considered the dynamic detection threshold adjustments and energy identification spectrum sensing technique in cognitive radio *** the dynamic threshold,the signal ratio-based threshold is *** threshold is computed by considering the Modified Black Widow Optimization Algorithm(MBWO).So,the proposed methodology is a combination of dynamic threshold detection and *** general threshold-based detection technique has different limitations such as the inability optimal signal threshold for determining the presence of the primary user *** limitations undermine the sensing accuracy of the energy identification ***,the ETBED technique is developed to enhance the energy efficiency of cognitive radio *** projected approach is executed and analyzed with performance and comparison *** proposed method is contrasted with the conventional techniques of theWhale Optimization Algorithm(WOA)and GreyWolf Optimization(GWO).It indicated superior results,achieving a high average throughput of 2.2 Mbps and an energy efficiency of 3.8,outperforming conventional techniques.

关键词： cognitive radio network spectrum sensing noise uncertainty modified black widow optimization algorithm energy detection technique

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Unsteady MHD casson Nanofluid Flow Past an Exponentially Accelerated Vertical Plate:An Analytical Strategy

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computer Modeling in Engineering & Sciences 2024年第7期140卷 431-460页

作者： T.Aghalya r.Tamizharasi Department of Mathematics School of Advanced SciencesVellore Institute of TechnologyVelloreTamilnadu632014India

In this study,the characteristics of heat transfer on an unsteady magnetohydrodynamic(MHD)casson nanofluid over an exponentially accelerated vertical porous plate with rotating effects were *** flow was driven by the combined effects of the magnetic field,heat radiation,heat source/sink and chemical *** oxide(cuO)and titanium oxide(TiO2)are acknowledged as nanoparticle *** nondimensional governing equations were subjected to the Laplace transformation technique to derive closed-form *** representations are provided to analyze how changes in physical parameters,such as the magnetic field,heat radiation,heat source/sink and chemical reaction,affect the velocity,temperature and concentration *** computed values of skin friction,heat and mass transfer rates at the surface were tabulated for various sets of input *** is perceived that there is a drop in temperature due to the rise in the heat source/sink and the Prandtl *** should be noted that a boost in the thermal radiation parameter prompts an increase in *** increase in the Prandtl number,heat source/sink parameter,time and a decrease in the thermal radiation parameter result in an increase in theNusselt *** computed values of the skin friction,heat andmass transfer rates at the surface were tabulated for various values of the flow *** present results were compared with those of previously published studies andwere found to be in excellent *** research has practical applications in areas such as drug delivery,thermal medicine and cancer treatment.

关键词： thermal radiation radiative flux nanofluid copper oxide titanium oxide accelerated plate

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constraining the variable generalized chaplygin gas model in matter creation cosmology

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communications in theoretical Physics 2024年第10期76卷 121-136页

作者： Yogesh Bhardwaj c P Singh Department of Applied Mathematics Delhi Technological University

We explore the variable generalized chaplygin gas（VGcG） model in the theory of matter creation cosmology within the framework of a spatially homogeneous and isotropic flat Friedmann—Lemai tre—robertson—Walker space-time. Matter creation cosmology is based on reinterpretation of the energy–momentum tensor in Einstein's field equations. this creation corresponds to an irreversible energy flow from the gravitational field to the created matter constituents. the variable chaplygin gas（VcG） is also studied as a particular solution. We use the Markov chain Monte carlo method to constrain the free parameters of three models, namely,Lambda-cold-Dark matter（ΛcDM）, VGcG and VcG models with and without matter creation from the latest observational data from baryon acoustic oscillations, cosmic chronometer, type Ia supernovae（Pantheon） including gamma-ray bursts, quasars and the local measurement of H0from r21 data. Two different combinations of dataset provide a fairly tight constraint on the parameters of the ΛcDM, VGcG and VcG models. the present values of various cosmological parameters are obtained, which are very close to the ΛcDM model. Furthermore, we perform stability analysis, Bayesian evidence analysis and information criteria analysis for these models through studying the sound speed, Bayes factor, and Akaike information criteria（AIc） and Bayesian information criteria（BIc） selection criteria. the values of sound speed for VGcG and VcG models shows that both the models are stable. According to AIc, it is observed that VGcG and VcG models with matter creation are supported considerably less by current observations,while BIc shows that these models are not favoured by observational data.

关键词： chaplygin gas model cosmological model dark energy matter creation

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Effect of radiative loss mechanisms on FIr thermometric parameters of Nd^(3+)-doped lithium tellurite glasses

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Journal of rare Earths 2024年第7期42卷 1250-1257,I0002页

作者： c.Y.Morassuti A.P.L Silva L.A.O.Nunes S.M.Lima L.H.c.Andrade Optical and Photothermal Spectroscopy Group(GEOF) Center for Studies in Natural Resources(CERNA)State University of Mato Grosso do Sul(UEMS)C.P.351DouradosMSBrazil renato Archer Information Technology center Dom Pedro I Highway(SP-65)Km 1436-Chácaras Campos dos AmaraisCampinasSPBrazil Institute of Physics of São carlos University of São PauloSão CarlosSPBrazil

Nd^(3+)-doped tellurite glasses are promising materials for thermometers based on the fluorescence intensity ratio(FIr)***,at high Nd^(3+)concentrations,energy transfer(ET)processes such as optical reabsorption and cross-relaxation can affect the Nd^(3+)emission,which has been little explored in the ***,the present work investigated the use of Nd^(3+)-doped tellurite glass(samples doped with Nd^(3+)at 0.2 mol%,0.5 mol%,2.0 mol%,and 4.0 mol%)in fluorescence thermometers,in the temperature range from 299 to 371 *** results indicate a strong dependence of the FIr parameters on the Nd^(3+)concentration,due to changes in the emission band profiles caused by optical reabsorption of the Nd^(3+)emissions and cross-relaxation processes.A decrease of the relative sensitivity of the ratio^(4)F_(5/2)→^(4)I_(9/2)/^(4)F_(3/2)→^(4)I_(9/2)is observed for samples doped with higher amounts of Nd^(3+).the maximum relative sensitivity at 299 K is 3.00%/K,which is the highest value among the reported Nd^(3+)ions.

关键词： Nd^(3+)-doped tellurite glass Fluorescence intensity ratio Optical thermometry Judd-Ofelt rare earths

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An Efficient Modelling of Oversampling with Optimal Deep Learning Enabled Anomaly Detection in Streaming Data

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china communications 2024年第5期21卷 249-260页

作者： r.rajakumar S.Sathiya Devi Srinivasa ramanujan centre SASTRA Deemed UniversityKumbakonamTamil Nadu 612001India University college of Engineering BIT CampusAnna UniversityTiruchirappalli 620024India

recently,anomaly detection(AD)in streaming data gained significant attention among research communities due to its applicability in finance,business,healthcare,education,*** recent developments of deep learning(DL)models find helpful in the detection and classification of *** article designs an oversampling with an optimal deep learning-based streaming data classification(OS-ODLSDc)*** aim of the OSODLSDc model is to recognize and classify the presence of anomalies in the streaming *** proposed OS-ODLSDc model initially undergoes preprocessing *** streaming data is unbalanced,support vector machine(SVM)-Synthetic Minority Over-sampling Technique(SVM-SMOTE)is applied for oversampling ***,the OS-ODLSDc model employs bidirectional long short-term memory(Bi LSTM)for AD and ***,the root means square propagation(rMSProp)optimizer is applied for optimal hyperparameter tuning of the Bi LSTM *** ensuring the promising performance of the OS-ODLSDc model,a wide-ranging experimental analysis is performed using three benchmark datasets such as cIcIDS 2018,KDD-cup 1999,and NSL-KDD datasets.

关键词： anomaly detection deep learning hyperparameter optimization oversampling SMOTE streaming data

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Peri-implant gas accumulation in response to magnesium-based musculoskeletal biomaterials:reframing current evidence for preclinical research and clinical evaluation

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Journal of Magnesium and Alloys 2024年第1期12卷 59-71页

作者： Yu Sun Heike Helmholz regine Willumeit-römer Institute of Metallic Biomaterials Helmholtz-Zentrum HereonMax-Planck-Str.1Geesthacht 21502Germany

Historically,the rapid degradation and massive gas release from magnesium(Mg)implants resulted in severe emphysema and mechanical *** the advent of new alloys and surface treatment methods,optimized Mg implants have re-entered clinics since last decade with reliable ***,the optimization aims at slowing down the degradation process,rather than exemption of the gas *** study involved a systematic evaluation of current preclinical and clinical evidence,regarding the physical signs,symptoms,radiological features,pathological findings and complications potentially associated with peri±implant gas accumulation(PIGA)after musculoskeletal Mg *** literature search identified 196 potentially relevant publications,and 51 papers were enrolled for further analysis,including 22 preclinical tests and 29 clinical studies published from 2005 to *** Mg-based materials have been evaluated in animal research,and the application of pure Mg and Mg alloys have been reported in clinical follow-ups involving multiple anatomical sites and musculoskeletal *** tissue and intraosseous PIGA are common in both animal tests and clinical follow-ups,and potentially associated with certain adverse *** examinations especially micro-cT and clinical cT scans provide valuable information for quantitative and longitudinal *** according to simulation tests involving Mg implantation and chemical processing,tissue fixation could lead to an increase in the volume of gas cavity,thus the results obtained from ex vivo imaging or histopathological evaluations should be interpreted with *** still lacks standardized procedures or consensus for both preclinical and clinical evaluation of ***,by providing focused insights into the topic,this evidence-based study will facilitate future animal tests and clinical evaluations,and support developing biocompatible Mg implants for the treatment of musculoskeletal

关键词： Magnesium implant Degradation Hydrogen Gas release Postoperative follow-up

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Systemic modulation of skeletal mineralization by magnesium implant promoting fracture healing: radiological exploration enhanced with PcA-based machine learning in a rat femoral model

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Journal of Magnesium and Alloys 2024年第3期12卷 1009-1020页

作者： Yu Sun Heike Helmholz regine Willumeit-römer Institute of Metallic Biomaterials Helmholtz-Zentrum HereonGermany

the clinical application of magnesium(Mg)and its alloys for bone fractures has been well supported by in vitro and in vivo ***,there were studies indicating negative effects of high dose Mg intake and sustained local release of Mg ions on bone metabolism or repair,which should not be ignored when developing Mg-based ***,it remains necessary to assess the biological effects of Mg implants in animal models relevant to clinical treatment *** primary purpose of this study was to validate the beneficial effects of intramedullary Mg implants on the healing outcome of femoral fractures in a modified rat *** addition,the mineralization parameters at multiple anatomical sites were evaluated,to investigate their association with healing outcome and potential clinical *** to the control group without Mg implantation,postoperative imaging at week 12 demonstrated better healing outcomes in the Mg group,with more stable unions in 3D analysis and high-mineralized bridging in 2D *** bone tissue mineral density(TMD)was higher in the Mg group at the non-operated femur and lumbar vertebra,while no differences between groups were identified regarding the bone tissue volume(TV),TMD and bone mineral content(BMc)in *** the surgical femur,the Mg group presented higher TMD,but lower TV and BMc in the distal metaphyseal region,as well as reduced BMc at the osteotomy *** component analysis(PcA)-based machine learning revealed that by selecting clinically relevant parameters,radiological markers could be constructed for differentiation of healing outcomes,with better performance than 2D *** study provides insights and preclinical evidence for the rational investigation of bioactive materials,the identification of potential adverse effects,and the promotion of diagnostic capabilities for fracture healing.

关键词： Magnesium Implants Bone fracture Mineralization Systemic modulation Principal component analysis.

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Design of computer vision assisted machine learning based controller for the Stewart platform to track spatial objects

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Frontiers of Structural and civil Engineering 2024年第8期18卷 1195-1208页

作者： Dev Kunwar Singh cHAUHAN Pandu r.VUNDAVILLI Indian Institute of Technology Bhubaneswar Bhubaneswar 752050India

the present work aims to develop an object tracking controller for the Stewart platform using a computer vision-assisted machine learning-based *** research is divided into two *** first module focuses on the design of a motion controller for the Physik Instrumente(PI)-based Stewart *** contrast,the second module deals with the development of a machine-learning-based spatial object tracking algorithm by collecting information from the Zed 2 stereo vision ***,simple feed-forward neural networks(NN)are used to predict the orientation of the top table of the *** training,the x,y,and z coordinates of the three-dimensional(3D)object,extracted from images,are used as the input to the *** contrast,the orientation information of the platform(that is,rotation about the x,y,and z-axes)is considered as the output from the *** orientation information obtained from the network is fed to the inverse kinematics-based motion controller(module 1)to move the platform while tracking the *** training,the optimised NN is used to track the continuously moving 3D *** experimental results show that the developed NN-based controller has successfully tracked the moving spatial object with reasonably good accuracy.

关键词： Stewart platform feed-forward neural networks motion controller inverse kinematics stereo vision

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cOVID-19 vaccination produces exercise-responsive SArS-coV-2 specific T-cells regardless of infection history

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Journal of Sport and Health Science 2024年第1期13卷 99-107页

作者： Kyle A.Smith Tiffany M.Zúñiga Forrest L.Baker Helena Batatinha charles r.Pedlar Shane c.Burgess Michael P.Gustafson Emmanuel Katsanis richard J.Simpson School of Nutritional Sciences and Wellness The University of ArizonaTucsonAZ 85721USA Department of Pediatrics The University of ArizonaTucsonAZ 85724USA Faculty of Sport Allied Health and Performance ScienceSt.Mary's UniversityTwickenham TW14SXUK Institute of Sport Exercise and Health University College LondonLondon WC1E 7HUUK Department of Animal and comparative Biomedical Sciences The University of ArizonaTucsonAZ 85721USA the University of Arizona cancer center The University of ArizonaTucsonAZ 85719USA Laboratory Medicine and Pathology Mayo Clinic ArizonaPhoenixAZ 85054USA Department of Immunobiology The University of ArizonaTucsonAZ 85724USA Department of Medicine The University of ArizonaTucsonAZ 85724USA Department of Pathology The University of ArizonaTucsonAZ 85724USA

Background:the mobilization and redistribution of severe acute respiratory syndrome coronavirus 2(SArS-coV-2)specific T-cells and neutralizing antibodies(nAbs)during exercise is purported to increase immune surveillance and protect against severe coronavirus disease 2019(cOVID-19).We sought to determine if cOVID-19 vaccination would elicit exercise-responsive SArS-coV-2 T-cells and transiently alter nAb ***:Eighteen healthy participants completed a 20-min bout of graded cycling exercise before and/or after receiving a cOVID-19 *** major leukocyte subtypes were enumerated before,during,and after exercise by flow cytometry,and immune responses to SArS-coV-2 were determined using whole blood peptide stimulation assays,T-cell receptor(Tcr)-βsequencing,and SArS-coV-2 nAb ***:cOVID-19 vaccination had no effect on the mobilization or egress of major leukocyte subsets in response to intensity-controlled graded ***,non-infected participants had a significantly reduced mobilization of cD4+and cD8+naive T-cells,as well as cD4+central memory T-cells,after vaccination(synthetic immunity group);this was not seen after vaccination in those with prior SArS-coV-2 infection(hybrid immunity group).Acute exercise after vaccination robustly mobilized SArS-coV-2 specific T-cells to blood in an intensity-dependent *** groups mobilized T-cells that reacted to spike protein;however,only the hybrid immunity group mobilized T-cells that reacted to membrane and nucleocapsid *** increased significantly during exercise only in the hybrid immunity ***:these data indicate that acute exercise mobilizes SArS-coV-2 specific T-cells that recognize spike protein and increases the redistribution of nAbs in individuals with hybrid immunity.

关键词： Anti-viral cOVID-19 Exercise immunology SArS-coV-2 T-cells Vaccine

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