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Current Zoology 2024年第4期70卷 421-429页

作者： rüdiger riesch Luis r.Arriaga Ingo Schlupp Department of Biological Sciences Royal Holloway University of LondonEghamTW20 OEXUK CEFE CNRSUnivMontpellierEPHEIRDMontpellierFrance Department of Biology University of OklahomaNormanOK 73019USA

Evaluating the fitness of hybrids can provide important insights into genetic differences between species or diverging *** focused on surface-and cave-ecotypes of the widespread Atlantic molly Poecilia mexicana and raised F1 hybrids of reciprocal crosses to sexual maturity in a common-garden *** were reared in a fully factorial 2 x 2 design consisting of lighting(light ***)and resource availability(high *** food).We quantified survival,ability to realize their full reproductive potential(i.e.,completed maturation for males and 3 consecutive births for females)and essential life-history *** to the performance of pure cave and surface fish from a previous experiment,F1s had the highest death rate and the lowest proportion of fish that reached their full reproductive *** also uncovered an intriguing pattern of sex-specific phenotype expression,because male hybrids expressed cave molly life histories,while female hybrids expressed surface molly life *** results provide evidence for strong selection against hybrids in the cave molly system,but also sug-gest a complex pattern of sex-specific(opposing)dominance,with certain surface molly genes being dominant in female hybrids and certain cavemollygenes beingdominant in malehybrids.

关键词： dominance life-history evolution local adaptation postzygotic isolation selection against hybrids.

Changes in snow cover extent in the Central Taurus Mountains from 1981 to 2021 in relation to temperature, precipitation, and atmospheric teleconnections

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Journal of Mountain Science 2024年第1期21卷 49-67页

作者： Ecmel ErLAT Fulya AYDIN-KANDEMİr Department of Geography Ege UniversityIzmir 35100Türkiye Climate Change and Zero Waste Department Antalya Metropolitan MunicipalityAntalya 07310Türkiye Hydropolitics Association Ankara 06680Türkiye

The snow cover over the Taurus Mountains affects water supply, agriculture, and hydropower generation in the region. In this study, we analyzed the monthly Snow Cover Extent(SCE) from November to April in the Central Taurus Mountains(Bolkar, Aladaglar, Tahtali and Binboga Mountains) from 1981 to 2021. Linear trends of snow cover season(November to April) over the last 41 years showed decreases in SCE primarily at lower elevations. The downward trend in SCE was found to be more pronounced and statistically significant for only November and March. SCE in the Central Taurus Mountains has declined about-6.3% per decade for 2500-3000 m in November and about-6.0% per decade for 1000-1500 m and 3000+ m in March over the last 41 years. The loss of SCE has become evident since the 2000s, and the lowest negative anomalies in SCE have been observed in 2014, 2001, and 2007 in the last 41 years, which are consistent with an increase in air temperature and decreased precipitation. SCE was correlated with both mean temperature and precipitation, with temperature having a greater relative importance at all elevated gradients. results showed that there is a strong linear relationship between SCE and the mean air temperature(r =-0.80) and precipitation(r = 0.44) for all elevated gradients during the snow season. The Arctic Oscillation(AO), the North Atlantic Oscillation(NAO), and the Mediterranean Oscillation(MO) winter indices were used to explain the year-to-year variability in SCE over the Central Taurus Mountains. The results showed that the inter-annual variability observed in the winter SCE on the Central Taurus Mountains was positively correlated with the phases of the winter AO, NAO and MO, especially below 2000 m elevation.

关键词： Snow cover extent Atmospheric teleconnection Central Taurus Mountains Air temperature and precipitation Geographic Information Systems Türkiye

Neurogenic potential of NG2 in neurotrauma:a systematic review

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Neural regeneration research 2024年第12期19卷 2673-2683页

作者： Yuri r.rigo radharani Benvenutti Luis V.Portela nathan r.Strogulski Departamento de Bioquímica Instituto de Ciências Básicas da SaúdeUniversidade Federal do Rio Grande do Sul(UFRGS)Porto AlegreBrazil School of Pharmacy and Biomolecular Sciences RCSI University of Medicine and Health SciencesDublinIreland School of Biochemistry and Immunology Trinity Biomedical Sciences InstituteTrinity College DublinUniversity of DublinDublinIreland

regenerative approaches towards neuronal loss following traumatic brain or spinal cord injury have long been considered a dogma in neuroscience and remain a cutting-edge area of *** is reflected in a large disparity between the number of studies investigating primary and secondary injury as therapeutic to rgets in spinal co rd and traumatic brain *** advances in biotechnology may have the potential to reshape the current state-of-the-art and bring focus to primary injury neurotrauma *** studies using neural-glial factor/antigen 2(NG2)cells indicate that they may differentiate into neurons even in the developed *** these cells show great potential to play a regenerative role,studies have been conducted to test various manipulations in neurotrauma models aimed at eliciting a neurogenic response from *** the present study,we systematically reviewed the experimental protocols and findings described in the scientific literature,which were peer-reviewed original research articles(1)describing preclinical experimental studies,(2)investigating NG2 cells,(3)associated with neurogenesis and neurotrauma,and(4)in vitro and/or in vivo,available in PubMed/MEDLINE,Web of Science or SCOPUS,from 1998 to ***,we have reviewed a total of 1504 papers,and summarized findings that ultimately suggest that NG2 cells possess an inducible neurogenic potential in animal models and in *** also discriminate findings of NG2 neurogenesis promoted by different pharmacological and genetic approaches over functional and biochemical outcomes of traumatic brain injury and spinal co rd injury models,and provide mounting evidence for the potential benefits of manipulated NG2 cell ex vivo transplantation in primary injury *** findings indicate the feasibility of NG2 cell neurogenesis strategies and add new players in the development of therapeutic alternatives for neurotrauma.

关键词： neural-glial antigen 2 neural-glial factor 2 neuron differentiation NG2 cell regeneration spinal cord injury(SCI) traumatic brain injury(TBI)

Parametric investigation on the novel and cost-effective nano fly ash impregnated geopolymer system for sustainable construction

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Frontiers of Structural and Civil Engineering 2024年第2期18卷 170-183页

作者： r.MOHANA S.M.Leela BHArATHI Department of Civil Engineering Mepco Schlenk Engineering CollegeSivakasi 626123India

The hazardous environmental effects of greenhouse gas emissions and climate change demand alternative sources for cementitious materials in the construction *** development of geopolymer structures provides a way of producing 100%cement-free *** this research work,a novel and simple way of deriving nano particles from waste fly ash particles is *** effect of adding the synthesized nano fly ash particles as a filler medium in geopolymer mortars was investigated by considering strength and durability *** optimization was done by using regression analysis on the geopolymer mortar and the impact of adding nano fly ash particles was studied by varying different percentages of addition ranging from 0 to 7.5%by weight of binder *** the results,it was observed that 1%nano fly ash acted not only as a filler but also as nano-sized precursors of the polymerization process,resulting in denser geopolymer *** can explain the extraordinary gain in strength of 72.11 MPa as well as the denser core with negligible level of chloride ion penetration,making the material suitable for the development of structures susceptible to marine environment.

关键词： geopolymer nano fly ash chloride ion penetration durability polymerization fillers

Nonlinear dynamic modeling of planar moving Timoshenko beam considering non-rigid non-elastic axial effects

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Applied Mathematics and Mechanics(English Edition) 2024年第3期45卷 479-496页

作者： M.ABBASI GAVArI M.r.HOMAEINEZHAD Faculty of Mechanical Engineering K.N.Toosi University of TechnologyTehran 19991-43344Iran

Due to the importance of vibration effects on the functional accuracy of mechanical systems,this research aims to develop a precise model of a nonlinearly vibrating single-link mobile flexible *** manipulator consists of an elastic arm,a rotary motor,and a rigid carrier,and undergoes general in-plane rigid body motion along with elastic transverse *** accurately model the elastic behavior,Timoshenko’s beam theory is used to describe the flexible arm,which accounts for rotary inertia and shear deformation *** applying Newton’s second law,the nonlinear governing equations of motion for the manipulator are derived as a coupled system of ordinary differential equations(ODEs)and partial differential equations(PDEs).Then,the assumed mode method(AMM)is used to solve this nonlinear system of governing equations with appropriate shape *** assumed modes can be obtained after solving the characteristic equation of a Timoshenko beam with clamped boundary conditions at one end and an attached mass/inertia at the *** addition,the effect of the transverse vibration of the inextensible arm on its axial behavior is *** the axial rigidity,the effect makes the rigid body dynamics invalid for the axial behavior of the ***,numerical simulations are conducted to evaluate the performance of the developed model,and the results are compared with those obtained by the finite element *** comparison confirms the validity of the proposed dynamic model for the *** to the mentioned features,this model can be reliable for investigating the system’s vibrational behavior and implementing vibration control algorithms.

关键词： planar moving Timoshenko beam non-rigid non-elastic axial effect as-sumed mode method(AMM) nonlinear motion analysis

An Intelligent SDN-IoT Enabled Intrusion Detection System for Healthcare Systems Using a Hybrid Deep Learning and Machine Learning Approach

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China Communications 2024年第10期21卷 267-287页

作者： r Arthi S Krishnaveni Sherali Zeadally Computational Intelligence School of ComputingSRMISTKattankulathurChennaiIndia College of Communication and Information University of KentuckyUSA

The advent of pandemics such as COVID-19 significantly impacts human behaviour and lives every ***,it is essential to make medical services connected to internet,available in every remote location during these ***,the security issues in the Internet of Medical Things(IoMT)used in these service,make the situation even more critical because cyberattacks on the medical devices might cause treatment delays or clinical ***,services in the healthcare ecosystem need rapid,uninterrupted,and secure *** solution provided in this research addresses security concerns and services availability for patients with critical health in remote *** research aims to develop an intelligent Software Defined Networks(SDNs)enabled secure framework for IoT healthcare *** propose a hybrid of machine learning and deep learning techniques(DNN+SVM)to identify network intrusions in the sensor-based healthcare *** addition,this system can efficiently monitor connected devices and suspicious ***,we evaluate the performance of our proposed framework using various performance metrics based on the healthcare application *** experimental results show that the proposed approach effectively detects and mitigates attacks in the SDN-enabled IoT networks and performs better that other state-of-art-approaches.

关键词： deep neural network healthcare intrusion detection system IoT machine learning software-defined networks

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

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

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

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