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Enhanced entropy generation and heat transfer characteristics of magnetic nano-encapsulated phase change materials in latent heat thermal energy storage systems

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Applied Mathematics and Mechanics(English Edition) 2024年第6期45卷 1051-1070页

作者： p.S.REDDY p.SREEDEVI Department of Mathematics Rajeev Gandhi Memorial College of Engineering and TechnologyNandyal 518501India

The objective of the current study is to investigate the importance of entropy generation and thermal radiation on the patterns of velocity,isentropic lines,and temperature contours within a thermal energy storage device filled with magnetic nanoencapsulated phase change materials(NEpCMs).The versatile finite element method(FEM)is implemented to numerically solve the governing *** effects of various parameters,including the viscosity parameter,ranging from 1 to 3,the thermal conductivity parameter,ranging from 1 to 3,the Rayleigh parameter,ranging from 102 to 3×10^(2),the radiation number,ranging from 0.1 to 0.5,the fusion temperature,ranging from 1.0 to 1.2,the volume fraction of NEpCMs,ranging from 2%to 6%,the Stefan number,ranging from 1 to 5,the magnetic number,ranging from 0.1 to 0.5,and the irreversibility parameter,ranging from 0.1 to 0.5,are examined in detail on the temperature contours,isentropic lines,heat capacity ratio,and velocity ***,the heat transfer rates at both the cold and hot walls are analyzed,and the findings are presented *** results indicate that the time taken by the NEpCMs to transition from solid to liquid is prolonged inside the chamber region as the fusion temperatureθf ***,the contours of the heat capacity ratio Cr decrease with the increase in the Stefan number Ste.

关键词： volume fraction of nano-encapsulated phase change material(NEpCM) radiation Stefan number heat capacity ratio entropy generation

A Hybrid Optimization Approach of Single point Incremental Sheet Forming of AISI 316L Stainless Steel Using Grey Relation Analysis Coupled with principal Component Analysiss

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Journal of Wuhan University of Technology(Materials Science) 2024年第1期39卷 160-166页

作者： A Visagan p Ganesh Department of production Technology Madras Institute of TechnologyChennai-600044India

We investigated the parametric optimization on incremental sheet forming of stainless steel using Grey Relational Analysis(GRA) coupled with principal Component Analysis(pCA). AISI 316L stainless steel sheets were used to develop double wall angle pyramid with aid of tungsten carbide tool. GRA coupled with pCA was used to plan the experiment conditions. Control factors such as Tool Diameter(TD), Step Depth(SD), Bottom Wall Angle(BWA), Feed Rate(FR) and Spindle Speed(SS) on Top Wall Angle(TWA) and Top Wall Angle Surface Roughness(TWASR) have been studied. Wall angle increases with increasing tool diameter due to large contact area between tool and workpiece. As the step depth, feed rate and spindle speed increase,TWASR decreases with increasing tool diameter. As the step depth increasing, the hydrostatic stress is raised causing severe cracks in the deformed surface. Hence it was concluded that the proposed hybrid method was suitable for optimizing the factors and response.

关键词： single point incremental forming AISI 316L taguchi grey relation analysis principal component analysis surface roughness scanning electron microscopy

On the functions of astrocyte-mediated neuronal slow inward currents

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Neural Regeneration Research 2024年第12期19卷 2602-2612页

作者： Balázs pál Department of physiology Faculty of MedicineUniversity of DebrecenDebrecenHungary

Slow inward currents are known as neuronal excitatory currents mediated by glutamate release and activation of neuronal extra synaptic N-met hyl-D-aspartate receptors with the contribution of *** events are significantly slower than the excitatory postsynaptic *** of slow inward currents are determined by seve ral factors including the mechanisms of astrocytic activation and glutamate release,as well as the diffusion pathways from the release site towards the extra synaptic recepto *** are stimulated by neuronal network activity,which in turn excite neurons,forming an astrocyte-neuron feedback *** as a consequence of brain edema,astrocytic swelling can also induce slow inward currents under pathological *** is a growing body of evidence on the roles of slow inward currents on a single neuron or local network *** events often occur in synchro ny on neurons located in the same astrocytic *** synchronization of neuronal excitability,slow inward currents also set synaptic strength via eliciting timing-dependent synaptic *** addition,slow inward currents are also subject to non-synaptic plasticity triggered by long-la sting stimulation of the excitatory *** note,there might be important regionspecific differences in the roles and actions triggering slow inward *** greater networks,the pathophysiological roles of slow inward currents can be better understood than physiological *** inward currents are identified in the pathophysiological background of autism,as slow inward currents drive early hypersynchrony of the neural *** inward currents are significant contributors to paroxysmal depolarizational shifts/interictal *** events are related to epilepsy,but also found in Alzheimer's disease,parkinson's disease,and stroke,leading to the decline of cognitive *** with features overlapping with slow inward currents(excitatory,N-methyl-Dasp

关键词： astrocyte cortical spreading depolarization gliotransmission glutamate neural synchronization NMDA receptor paroxysmal depolarizational shift slow inward current

An Efficient Approach to Escalate the Speed of Training Convolution Neural Networks

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China Communications 2024年第2期21卷 258-269页

作者： p pabitha Anusha Jayasimhan Department of Computer Technology Anna UniversityMadras Institute of Technology CampusChennai 600044India

Deep neural networks excel at image identification and computer vision applications such as visual product search, facial recognition, medical image analysis, object detection, semantic segmentation,instance segmentation, and many others. In image and video recognition applications, convolutional neural networks(CNNs) are widely employed. These networks provide better performance but at a higher cost of computation. With the advent of big data, the growing scale of datasets has made processing and model training a time-consuming operation, resulting in longer training times. Moreover, these large scale datasets contain redundant data points that have minimum impact on the final outcome of the model. To address these issues, an accelerated CNN system is proposed for speeding up training by eliminating the noncritical data points during training alongwith a model compression method. Furthermore, the identification of the critical input data is performed by aggregating the data points at two levels of granularity which are used for evaluating the impact on the model *** experiments are conducted using the proposed method on CIFAR-10 dataset on ResNet models giving a 40% reduction in number of FLOps with a degradation of just 0.11% accuracy.

关键词： CNN deep learning image classification model compression

proteins as nanomagnets and magnetoreceptors

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Zoological Research 2024年第4期45卷 831-832页

作者： p.J.Hore Department of Chemistry University of OxfordUK

It is an appealing notion that a protein molecule could act as a nanomagnet.A genetically encodable biomolecule with a permanent magnetic moment at room temperature could have a range of applications:a magnetogenetic actuator,a magnetic tag for purifying and immobilizing enzymes,a contrast agent for magnetic resonance imaging,and a basis for a biomimetic magnetic sensing device,to name just a few.A magnetic protein could perhaps also function as the sensor in the magnetic compass that enables small songbirds to navigate the huge distances between their breeding and wintering *** though such possibilities may be,how realistic are they?

关键词： magnetic magnets enable

CL2ES-KDBC:A Novel Covariance Embedded Selection Based on Kernel Distributed Bayes Classifier for Detection of Cyber-Attacks in IoT Systems

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Computers, Materials & Continua 2024年第3期78卷 3511-3528页

作者： Talal Albalawi p.Ganeshkumar Computer Science Department College of Computer and Information SciencesImam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11432Saudi Arabia

The Internet of Things(IoT)is a growing technology that allows the sharing of data with other devices across wireless ***,IoT systems are vulnerable to cyberattacks due to its opennes The proposed work intends to implement a new security framework for detecting the most specific and harmful intrusions in IoT *** this framework,a Covariance Linear Learning Embedding Selection(CL2ES)methodology is used at first to extract the features highly associated with the IoT ***,the Kernel Distributed Bayes Classifier(KDBC)is created to forecast attacks based on the probability distribution value *** addition,a unique Mongolian Gazellas Optimization(MGO)algorithm is used to optimize the weight value for the learning of the *** effectiveness of the proposed CL2ES-KDBC framework has been assessed using several IoT cyber-attack datasets,The obtained results are then compared with current classification methods regarding accuracy(97%),precision(96.5%),and other *** analysis of the CL2ES-KDBC system on IoT intrusion datasets is performed,which provides valuable insight into its performance,efficiency,and suitability for securing IoT networks.

关键词： IoT security attack detection covariance linear learning embedding selection kernel distributed bayes classifier mongolian gazellas optimization

presynaptic endoplasmic reticulum architecture and hereditary spastic paraplegia

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Neural Regeneration Research 2024年第3期19卷 485-486页

作者： Juan Josépérez-Moreno Instituto de Biomedicina de Sevilla(IBiS) Hospital Universitario Virgen Del Rocío/CSIC/Universidad de Sevillaand Departamento de Biología CelularFacultad de BiologíaUniversidad de SevillaSevilleSpain

Hereditary spastic paraplegia(HSp)is a clinically and genetically heterogeneous neurodegenerative disorder,characterized primarily by progressive spasticity and weakness in the lower *** ients can also experience peripheral neuropathy,cognitive impairment,and other neurological *** date,more than 80 genes have been implicated in HSp,encompassing various cellular components,although mutations in genes encoding endoplasmic reticulum(ER)-shaping proteins are the most prevalent(parodi et al.,2017).ER-shaping proteins are generally known for regulating the tubulation and curvation of the ER,but most of them show additional functions,including fusion of ER tubules,microtubule-severing,ER autophagy,lipid droplet synthesis,contact sites with other organelles(Öztürk et al.,2020).This highlights the complexity of studying the role of these proteins and the link between ER function and HSp.

关键词： reticulum endoplasmic

Drought events influence nutrient canopy exchanges and green leaf partitioning during senescence in a deciduous forest

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Forest Ecosystems 2024年第1期11卷 110-119页

作者： J.Touche C.Calvaruso p.De Donato M.-p.Turpault INRAE BEFF-54000NancyFrance UMR 7359 GeoRessourcesFaculte des Sciences-Campus des Aiguillettes54506Vandoeuvre Les NancyFrance EcoSustain Environmental Engineering OfficeResearch and DevelopmentKanfen57330France

The increase in the frequency and intensity of drought events expected in the coming decades in Western Europe may disturb forest biogeochemical cycles and create nutrient deficiencies in *** possible origin of nutrient deficiency is the disturbance of the partitioning of the green leaf pool during the leaf senescence period between resorption,foliar leaching and senesced ***,the effects of drought events on this partitioning and the consequences for the maintenance of tree nutrition are poorly *** experiment in a beech forest in Meuse(France)was conducted to assess the effect of drought events on nutrient canopy exchanges and on the partitioning of the green leaf pool during the leaf senescence *** aim was to identify potential nutritional consequences of droughts for *** nutrient dynamics,including resorption,chemistry of green and senesced leaves,foliar absorption and leaching in mature beech stands from 2012 to 2019 allowed us to compare the nutrient exchanges for three nondry and three dry years(i.e.,with an intense drought event during the growing season).During dry years,we observed a decrease by almost a third of the potassium(K)partitioning to resorption(*** efficiency),thus reducing the K reserve in trees for the next growing *** result suggests that with the increased drought frequency and intensity expected for the coming decades,there will be a risk of potassium deficiency in trees,as already observed in a rainfall exclusion experiment on the same study *** foliar leaching and higher parititioning to the senesced leaves for K and phosphorus(p)were also *** addition,a slight increase in nitrogen(N)resorption efficiency occurred during dry years which is more likely to improve tree *** calcium(Ca)negative resorption decreased,with no apparent consequence in our study *** results show that nutrient exchanges in the canopy and the partitioning of the green leaf

关键词： Natural drought Beech forest Canopy Resorption Foliar leaching Senesced leaves Nutrition

Direct-to-indirect mapping for optimal low-thrust trajectories

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Astrodynamics 2024年第1期8卷 27-46页

作者： David Ottesen Ryan p.Russell Department of Aerospace Engineering and Engineering Mechanics The University of Texas at AustinAustinTexas78712USA

Optimal,many-revolution spacecraft trajectories are challenging to solve.A connection is made for a class of models between optimal direct and indirect *** transfers that minimize thrust-acceleration-squared,primer vector theory maps direct,many-impulsive-maneuver trajectories to the indirect,continuous-thrust-acceleration *** mapping algorithm is independent of how the direct solution is obtained and requires only a solver for a boundary value problem and its partial derivatives.A Lambert solver is used for the two-body problem in this *** mapping is simple because the impulsive maneuvers and co-states share the same linear space around an optimal *** numerical results,the direct coast-impulse solutions are demonstrated to converge to the indirect continuous solutions as the number of impulses and segments *** two-body design space is explored with a set of three many-revolution,many-segment examples changing semimajor axis,eccentricity,and *** first two examples involve a small change to either semimajor axis or eccentricity,and the third example is a transfer to geosynchronous *** a single processor,the optimization runtime is seconds to minutes for revolution counts of 10 to 100,and on the order of one hour for examples with up to 500 *** of these thrust-acceleration-squared solutions are good candidates to start a homotopy to a higher-fidelity minimization problem with practical constraints.

关键词： direct optimization indirect optimization impulsive maneuvers Lambert's problem two-body dynamics primer vectortheory