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STCF conceptual design report (Volume 1): physics & detector

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Frontiers of physics 2024年第1期19卷 1-154页

作者： M.Achasov X.C.Ai L.p.An R.Aliberti Q.An X.Z.Bai Y.Bai O.Bakina A.Barnyakov V.Blinov V.Bobrovnikov D.Bodrov A.Bogomyagkov A.Bondar I.Boyko Z.H.Bu F.M.Cai H.Cai J.J.Cao Q.H.Cao X.Cao Z.Cao Q.Chang K.T.Chao D.Y.Chen H.Chen H.X.Chen J.F.Chen K.Chen L.L.Chen p.Chen S.L.Chen S.M.Chen S.Chen S.p.Chen W.Chen X.Chen X.F.Chen X.R.Chen Y.Chen Y.Q.Chen H.Y.Cheng J.Cheng S.Cheng T.G.Cheng J.p.Dai L.Y.Dai X.C.Dai D.Dedovich A.Denig I.Denisenko J.M.Dias D.Z.Ding L.Y.Dong W.H.Dong V.Druzhinin D.S.Du Y.J.Du Z.G.Du L.M.Duan D.Epifanov Y.L.Fan S.S.Fang Z.J.Fang G.Fedotovich C.Q.Feng X.Feng Y.T.Feng J.L.Fu J.Gao Y.N.Gao p.S.Ge C.Q.Geng L.S.Geng A.Gilman L.Gong T.Gong B.Gou W.Gradl J.L.Gu A.Guevara L.C.Gui A.Q.Guo F.K.Guo J.C.Guo J.Guo Y.p.Guo Z.H.Guo A.Guskov K.L.Han L.Han M.Han X.Q.Hao J.B.He S.Q.He X.G.He Y.L.He Z.B.He Z.X.Heng B.L.Hou T.J.Hou Y.R.Hou C.Y.Hu H.M.Hu K.Hu R.J.Hu W.H.Hu X.H.Hu Y.C.Hu J.Hua G.S.Huang J.S.Huang M.Huang Q.Y.Huang W.Q.Huang X.T.Huang X.J.Huang Y.B.Huang Y.S.Huang N.Hüsken V.Ivanov Q.p.Ji J.J.Jia S.Jia Z.K.Jia H.B.Jiang J.Jiang S.Z.Jiang J.B.Jiao Z.Jiao H.J.Jing X.L.Kang X.S.Kang B.C.Ke M.Kenzie A.Khoukaz I.Koop E.Kravchenko A.Kuzmin Y.Lei E.Levichev C.H.Li C.Li D.Y.Li F.Li G.Li G.Li H.B.Li H.Li H.N.Li H.J.Li H.L.Li J.M.Li J.Li L.Li L.Li L.Y.Li N.Li p.R.Li R.H.Li S.Li T.Li W.J.Li X.Li X.H.Li X.Q.Li X.H.Li Y.Li Y.Y.Li Z.J.Li H.Liang J.H.Liang Y.T.Liang G.R.Liao L.Z.Liao Y.Liao C.X.Lin D.X.Lin X.S.Lin B.J.Liu C.W.Liu D.Liu F.Liu G.M.Liu H.B.Liu J.Liu J.J.Liu J.B.Liu K.Liu K.Y.Liu K.Liu L.Liu Q.Liu S.B.Liu T.Liu X.Liu Y.W.Liu Y.Liu Y.L.Liu Z.Q.Liu Z.Y.Liu Z.W.Liu I.Logashenko Y.Long C.G.Lu J.X.Lu N.Lu Q.F.Lü Y.Lu Y.Lu Z.Lu p.lukin F.J.Luo T.Luo X.F.Luo Y.H.Luo H.J.Lyu X.R.Lyu J.p.Ma p.Ma Y.Ma Y.M.Ma F.Maas S.Malde D.Matvienko Z.X.Meng R.Mitchell A.Nefediev Y.Nefedov S.L.Olsen Q.Ouyang p.pakhlov G.pakhlova X.pan Y.pan E.passemar Y.p.pei H.p.peng L.peng X.Y.peng X.J.peng K.peters S.pivovarov E.pyata B.B.Qi Y.Q.Qi W.B.Qian Y.Qian C.F.Qiao J.J.Qin J.J.Qin L.Q.Qin X.S.Qin T.L.Qiu J.Rademacker C.F.Redmer H.Y.Sang Anhui University Hefei 230039China Beihang University Beijing 100191China Budker Institute of Nuclear physics Novosibirsk 630090Russia CAS Key Laboratory of Theoretical physics Institute of Theoretical PhysicsChinese Academy of SciencesBeijing 100190China Cavendish Laboratory University of CambridgeJJ Thomson AveCambridge CB30HEUnited Kingdom Central China Normal University Wuhan 430079China Central South University Changsha 410083China China University of Geosciences Wuhan 430074China China University of Mining and Technology Xuzhou 221116China École polytechnique Fédérale de Lausanne(EpFL) LausanneSwitzerland Fudan University Shanghai 200433China Goethe University Frankfurt D-60325 Frankfurt am MainGermany Guangxi Normal University Guilin 541004China Guangxi Uninversity Nanning 530004China Hangzhou Institute for Advanced Study UCASHangzhou 310024China Hebei Normal University Shijiazhuang 050024China Hebei University Baoding 071002China Hefei University of Technology Hefei 230601China Helmholtz Institute Mainz Staudinger Weg 18D-55099 MainzGermany Henan Normal University Xinxiang 453007China Henan University Kaifeng 475004China High Energy physics Center Chung-Ang UniversitySeoul 06974Korea Higher School of Economy 11 pokrovsky Bulvar Moscow 109028Russia Huangshan University Huangshan 245000China Hubei University of Automotive Technology Shiyan 442002China Hunan Normal University Changsha 410081China Hunan University of Science and Technology Xiangtan 411201China Hunan University Changsha 410082China Indiana University BloomingtonIndiana 47405USA Inner Mongolia University Hohhot 010021China Institute of Advanced Science Facilities Shenzhen 518107China Institute of High Energy physics Chinese Academy of SciencesBeijing 100049China Institute of Modern physics Chinese Academy of SciencesLanzhou 730000China Institute of physics Academia SinicaTaipeiTaiwan 11529China Institute of Theoretical physics Chinese Academy of SciencesBeijing 100190China Jilin University Changch

The superτ-charm facility(STCF)is an electron–positron collider proposed by the Chinese particle physics *** is designed to operate in a center-of-mass energy range from 2 to 7 GeV with a peak luminosity of 0.5×10^(35) cm^(–2)·s^(–1) or *** STCF will produce a data sample about a factor of 100 larger than that of the presentτ-charm factory—the BEpCII,providing a unique platform for exploring the asymmetry of matter-antimatter(charge-parity violation),in-depth studies of the internal structure of hadrons and the nature of non-perturbative strong interactions,as well as searching for exotic hadrons and physics beyond the Standard *** STCF project in China is under development with an extensive R&D *** document presents the physics opportunities at the STCF,describes conceptual designs of the STCF detector system,and discusses future plans for detector R&D and physics case studies.

关键词： electron–positron collider tau-charm region high luminosity STCF detector conceptual design

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

Cryogenic and conventional milling of AZ91 magnesium alloy

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Journal of Magnesium and Alloys 2024年第6期12卷 2503-2519页

作者： Vikas Marakini Srinivasa pai p Gururaj Bolar Bhaskara p Achar Department of Mechanical Engineering Nitte(Deemed to be University)NMAM Institute of Technology(NMAMIT)Nitte 574110India Department of Mechanical and Industrial Engineering Manipal Institute of TechnologyManipal Academy of Higher EducationManipal 576104India

Use of magnesium is the need of the hour due to its low density as well as its high strength-to-weight and stiffness-to-weight ratio *** study focuses on the effectiveness of liquid nitrogen(LN_(2))assisted cryogenic machining on the surface integrity(SI)characteristics of AZ91 magnesium *** milling using uncoated carbide inserts have been performed under liquid nitrogen(LN_(2))assisted cryogenic condition and compared with conventional(dry)*** are performed using machining parameters in terms of cutting speeds of 325,475,625 m/min,feed rates of 0.05,0.1,0.15 mm/teeth and depth of cuts of 0.5,1,1.5 mm *** significant surface integrity characteristics such as surface roughness,microhardness,microstructure,and residual stresses have been *** of SI characteristics with respect to milling parameters have been identified using statistical technique such as ANOVA and signal-to-noise(S/N)ratio ***,the multi criteria decision making(MCDM)techniques such as additive ratio assessment method(ARAS)and complex proportional assessment(COpRAS)have been utilized to identify the optimal conditions for milling AZ91 magnesium alloy under both dry and cryogenic *** of LN_(2)during machining,resulted in reduction in machining temperature by upto 29%with a temperature drop from 251.2℃under dry condition to 178.5℃in cryogenic *** showed the advantage of performing cryogenic milling in improving the surface integrity to a significant *** machining considerably minimized the roughness by upto 28%and maximised the microhardness by upto 23%,when compared to dry *** speed has caused significant impact on surface roughness(95.33%-dry,92.92%-cryogenic)and surface microhardness(80.33%-dry,82.15%-cryogenic).Due to the reduction in machining temperature,cryogenic condition resulted in compressive residual stresses(maximumσ║=-113 Mpa)on the alloy *** indicate no

关键词： Magnesium alloy Cryogenic machining Roughness Microhardness Microstructure Residual stress Multi criteria decision making

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

Selection of digital fabrication technique in the construction industry--A multi-criteria decision-making approach

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Frontiers of Structural and Civil Engineering 2024年第7期18卷 977-997页

作者： M.p.SALAIMANIMAGUDAM J.JAYApRAKASH Department of Structural and Geotechnical Engineering School of Civil EngineeringVellore Institute of TechnologyVellore 632014India

Digital fabrication techniques,in recent decades,have provided the basis of a sustainable revolution in the construction ***,selecting the digital fabrication method in terms of manufacturability and functionality requirements is a complex *** paper presents alternatives and criteria for selection of digital fabrication techniques by adopting the multi-criteria decision-making *** alternatives considered in the study are concrete three-dimensional(3D)printing,shotcrete,smart dynamic casting,material intrusion,mesh molding,injection concrete 3D printing,and thin forming *** criteria include formwork utilization,reinforcement incorporation,geometrical complexity,material enhancement,assembly complexity,surface finish,and build *** demonstrates different multi-criteria decision-making techniques,with both subjective and objective weighting *** given ranking is based on the current condition of digital fabrication in the construction *** study reveals that in the selection of digital fabrication techniques,the criteria including reinforcement incorporation,build area,and geometrical complexity play a pivotal role,collectively accounting for nearly 70% of the overall *** the evaluated techniques,concrete 3D printing emerged as the best performer,however the shotcrete and mesh molding techniques in the second and third positions.

关键词： digital fabrication multicriteria decision-making concrete 3D printing

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