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CDR视角下的风险探究——从ADR到CDR如何更为稳健

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河北法学 2019年第4期37卷 22-34页

作者：黄勇严文斌对外经济贸易大学法学院北京100029

2018年3月,证监会发布《关于开展创新企业境内发行股票或存托凭证试点的若干意见》。随后证监会于6月份正式发布《存托凭证发行与交易管理办法(试行)》等系列文件,使得存托凭证(Depositary Receipt,DR)的概念再度走热。比较分析美国存... 详细信息

2018年3月,证监会发布《关于开展创新企业境内发行股票或存托凭证试点的若干意见》。随后证监会于6月份正式发布《存托凭证发行与交易管理办法(试行)》等系列文件,使得存托凭证(Depositary Receipt,DR)的概念再度走热。比较分析美国存托凭证(American Depositary Receipt,ADR)和中国存托凭证(Chinese Depositary Receipt,CDR),进而探究CDR市场的潜藏风险。通过对比ADR和CDR在发行主体、设立背景、监管机制和资金流向等四个方面的异同,在发行CDR的过程中可能存在管辖权模糊、资本跨境转换管制以及法律关系不明等诸多问题。这些问题都需要通过进一步的立法和行政手段加以明确和完善。

关键词：存托凭证中国存托凭证(CDR) 美国存托凭证(ADR) 风险监管

The intrinsic strength prediction by machine learning for refractory high entropy alloys

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钨科技(英文) 2023年第4期5卷 531-538页

作者： yong-Gang yan Kun Wang Kazuo Inamori School of Engineering Alfred UniversityAlfredNY14802USA

Herein,we trained machine learning(ML)model to quickly and accurately conduct the strength prediction of refractory high entropy alloys(RHEAs)matrix.Gradient Boosting(GB)regression model shows an outstanding performance against other ML models.In addition,the heat of fusion and atomic size difference is shown to be paramount to the strength of the high entropy alloys(HEAs)matrix.In addition,we discussed the contribution of each feature to the solid solution strengthening(SSS)of HE As.The excellent predictive accuracy shows that the GB model can be efficient and reliable for the design of RHEAs with desired strength.

关键词： Refractory high entropy alloys Solid solution strengthening Machine learning Lattice distortion Heat of fusion

Fusing Syntactic Structure Information and Lexical Semantic Information for End-to-End Aspect-Based Sentiment Analysis

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Tsinghua Science and Technology 2023年第2期28卷 230-243页

作者： yong Bie yan yang Yiling Zhang School of Computing and Artificial Intelligence Southwest Jiaotong UniversityChengdu 611756China

The aspect-based sentiment analysis(ABSA)consists of two subtasksaspect term extraction and aspect sentiment prediction.Most methods conduct the ABSA task by handling the subtasks in a pipeline manner,whereby problems in performance and real application emerge.In this study,we propose an end-to-end ABSA model,namely,SSi-LSi,which fuses the syntactic structure information and the lexical semantic information,to address the limitation that existing end-to-end methods do not fully exploit the text information.Through two network branches,the model extracts syntactic structure information and lexical semantic information,which integrates the part of speech,sememes,and context,respectively.Then,on the basis of an attention mechanism,the model further realizes the fusion of the syntactic structure information and the lexical semantic information to obtain higher quality ABSA results,in which way the text information is fully used.Subsequent experiments demonstrate that the SSi-LSi model has certain advantages in using different text information.

关键词： deep learning natural language processing aspect-based sentiment analysis graph convolutional

Numerical study of transonic separation flow using an anisotropic turbulence model

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航空动力学报 2020年第1期35卷 114-125页

作者： yan Wenhui PENG Tengfei Yong Yan QIN Ruixin MA Ruige School of Mechanical and Materials Engineering North China University of TechnologyBeijing 100144China Department of Civil Environmental and Geomatics EngineeringFlorida Atlantic UniversityBoca RatonFlorida 33431U.S.A.

A transonic turbulent separation flow in a converging-diverging transonic diffuser was studied,when there existed a separation bubble on the top wall of the diffuser triggered by strong shock-wave-boundary-layer-interaction(SWBLI).To capture the essential behavior of this complex flow,the current study utilized an anisotropic turbulence model developed on the basis of a statistical partial average scheme.The first order moment of turbulent fluctuations,retained by a novel average scheme,and the turbulent length scale,can be determined from the momentum equations and mechanical energy equation of the fluctuation flow,respectively.The two physical quantities were readily used to construct the nonlinear anisotropic eddy viscosity tensor and to significantly improve the computational results.Comparisons between the computational results and experimental data were carried out for velocity profiles,pressure distribution,skin friction coefficient,Reynolds stress as well as streamline vectors distribution.Without using any empirical coefficients and wall functions,the numerical results were in good agreement with the available experimental data,further confirming that the nonlinear anisotropic eddy viscosity tensor is the decisive factor for the success of the computational results.

关键词： transonic separation flow eddy viscosity tensor shock wave boundary layer interaction anisotropic turbulence model statistical partial average scheme

Extending Structures for Gel'fand-Dorfman Bialgebras

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Acta Mathematica Sinica,English Series 2024年第2期40卷 619-638页

作者： Jia Jia WEN yan yong HONG School of Mathematics Hangzhou Normal UniversityHangzhou 311121P.R.China

Gel'fand-Dorfman bialgebra,which is both a Lie algebra and a Novikov algebra with some compatibility condition,appeared in the study of Hamiltonian pairs in completely integrable systems.They also emerged in the description of a class special Lie conformal algebras called quadratic Lie conformal algebras.In this paper,we investigate the extending structures problem for Gel'fand-Dorfman bialgebras,which is equivalent to some extending structures problem of quadratic Lie conformal algebras.Explicitly,given a Gel'fand-Dorfman bialgebra(A,o,[.,.]),this problem is how to describe and classify all Gel'fand-Dorfman bialgebra structures on a vector space E(A⊂E)such that(A,o,[.,.])is a subalgebra of E up to an isomorphism whose restriction on A is the identity map.Motivated by the theories of extending structures for Lie algebras and Novikov algebras,we construct an object gH2(V,A)to answer the extending structures problem by introducing the notion of a unified product for Gel'fand-Dorfman bialgebras,where V is a complement of A in E.In particular,we investigate the special case when dim(V)=1 in detail.

关键词： Gel'fand-Dorfman bialgebra Lie conformal algebra Extending structures problem Novikovalgebra

A giant atom with modulated transition frequency

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Frontiers of physics 2023年第1期18卷 209-218页

作者： Lei Du yan Zhang yong Li Center for Theoretical Physics and School of Science Hainan UniversityHaikou 570228China Beijing Computational Science Research Center Beijing 100193China Center for Quantum Sciences and School of Physics Northeast Normal UniversityChangchun 130024China Synergetic Innovation Center for Quantum Effects and Applications Hunan Normal UniversityChangsha 410081China

Giant atoms are known for the frequency-dependent spontaneous emission and associated interference effects.In this paper,we study the spontaneous emission dynamics of a two-level giant atom with dynamically modulated transition frequency.It is shown that the retarded feedback effect of the giant-atom system is greatly modified by a dynamical phase arising from the frequency modulation and the retardation effect itself.Interestingly,such a modification can in turn suppress the retarded feedback such that the giant atom behaves like a small one.By introducing an additional phase difference between the two atom-waveguide coupling paths,we also demonstrate the possibility of realizing chiral and tunable temporal profiles of the output fields.The results in this paper have potential applications in quantum information processing and quantum network engineering.

关键词： giant atoms frequency modulation spontaneous emission dynamics non-Markovian retardation effect

Prefrontocortical Astrocytes Regulate Dominance Hierarchy in Male Mice

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Neuroscience Bulletin 2024年第3期40卷 415-417页

作者： yong Tang Hai-yan Yin Peter Illes School of Acupuncture and Tuina Chengdu University of Traditional Chinese MedicineChengdu 610075China International Joint Research Center on Purinergic Signaling Chengdu University of Traditional Chinese MedicineChengdu 610075China Rudolf Boehm Institute for Pharmacology and Toxicology University of Leipzig04107 LeipzigGermany

Social hierarchy is a general self-organizational scheme in animal societies in which each member achieves a certain status of domination or subordination when getting access to resources,with profound consequences for survival,health,reproductive success,and multiple behaviors[1,2].The prefrontal cortex(PFC)was recognized as a central regulator of neuronal circuits determining the formation of social hierarchy;brain areas upstream of the PFC convey information about social status,and downstream brain regions execute dominance behavior[3].Social deficits have been suggested to be due to an elevation of excitatory/inhibitory(E/l)balance within the mouse dorsomedial(dm)PFC[4].A compensatory increase of inhibitory cell excitability partially rescued social deficits caused by such a disturbance of E/l balance.

关键词： consequences hierarchy determining

Overview:recent studies of machine learning in phase prediction of high entropy alloys

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Tungsten 2023年第1期5卷 32-49页

作者： yong-Gang yan Dan Lu Kun Wang Alfred University AlfredNY 14802USA

High entropy alloys(HEAs),especially refractory HEAs,have become a subject of interest in the past years due to their exceptional properties in terms of high-temperature strength,corrosion resistance,radiation tolerance,etc.under extreme environments.While the phase formation of these alloys significantly affects their properties.If the phase of HEAs can be forecasted before the experiments,the material design process can be greatly accelerated.The phase formation study of HEAs mainly relied on trial-and-error experiments and multi-scale computational simulations such as calculation of phase diagrams(CALPHAD) and density functional theory(DFT).However,those methods require massive time,man-power,and resources.As a highly efficient tool,machine learning(ML) method has been developed and applied to predict the phase formation of HEAs very recently.This review provided a comprehensive overview and analysis of the most recent research work in this area.First,we introduce ML methodologies applied in HEAs’ phase prediction in terms of principles,database,algorithm,and validation.We then summarize recent applications of the ML method in the phase prediction of HEAs.In the end,we propose possible solutions to the current problems and future research pathways for various challenges in the phase prediction of HEAs using ML.

关键词： Machine learning High entropy alloys Phase prediction

Identification of injury type using somatosensory and motor evoked potentials in a rat spinal cord injury model

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Neural Regeneration Research 2023年第2期18卷 422-427页

作者： Rong Li Han-Lei Li Hong-yan Cui yong-Can Huang yong Hu Department of Orthopedics and Traumatology The University of Hong Kong-Shenzhen HospitalShenzhenGuangdong ProvinveChina Department of Neurosurgery Neuroscience CenterIntegrated Hospital of Traditional Chinese MedicineSouthern Medical UniversityGuangzhouGuangdong ProvinveChina Institute of Biomedical Engineering Chinese Academy of Medical Sciences and Peking Union Medical CollegeTianjinChina Shenzhen Engineering Laboratory of Orthopedic Regenerative Technologies Department of Spine SurgeryPeking University Shenzhen HospitalShenzhenGuangdong ProvinveChina Department of Orthopedics and Traumatology The University of Hong KongPokfulamHong Kong Special Administrative RegionChina

The spinal cord is at risk of injury during spinal surgery.If intraoperative spinal co rd injury is identified early,irreve rsible impairment or loss of neurological function can be prevented.Different types of spinal cord injury result in damage to diffe rent spinal cord regions,which may cause diffe rent somatosensory and motor evoked potential signal res ponses.In this study,we examined electrophysiological and histopathological changes between contusion,distra ction,and dislocation spinal cord injuries in a rat model.We found that contusion led to the most severe dorsal white matter injury and caused considerable attenuation of both somatosensory and motor evoked potentials.Dislocation resulted in loss of myelinated axons in the lateral region of the injured spinal cord along the rostrocaudal axis.The amplitude of attenuation in motor evoked potential responses caused by dislocation was greater than that caused by contusion.After distraction injury,extracellular spaces were slightly but not significantly enlarged;somatosensory evoked potential res ponses slightly decreased and motor evoked potential responses were lost.Correlation analysis showed that histological and electrophysiological findings we re significantly correlated and related to injury type.Intraope rative monitoring of both somatosensory and motor evoked potentials has the potential to identify iatrogenic spinal cord injury type during surgery.

关键词： contusion injury dislocation injury distraction injury electropnysiology heterogeneity histopathology injury mechanism motor evoked potential somatosensory evoked potential spinal cord injury