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Optimal Contract for the Principal-Agent Under Knightian Uncertainty

Journal of the Operations Research Society of China 2020年第4期8卷 637-654页

作者： kun-lun wang Chen Fei Wei-Yin Fei Department of Financial Engineering Anhui Polytechnic UniversityWuhu 241000AnhuiChina Glorious Sun School of Business and Management Donghua UniversityShanghai 200051China

Under the Knightian uncertainty,this paper constructs the optimal principal(he)-agent(she)contract model based on the principal’s expected profit and the agent’s expected utility function by using the sublinear expectation theory.The output process in the model is provided by the agent’s continuous efforts and the principal cannot directly observe the agent’s efforts.In the process of work,risk-averse agent will have the opportunity to make external choices.In order to promote the agent’s continuous efforts,the principal will continuously provide the agents with consumption according to the observable output process after the probation period.In this paper,the Hamilton–Jacobi–Bellman equation is deduced by using the optimality principle under sublinear expectation while the smoothness viscosity condition of the principal-agent optimal contract is given.Moreover,the continuation value of the agent is taken as the state variable to characterize the optimal expected profit of the principal,the agent’s effort and the consumption level under different degrees of Knightian uncertainty.Finally,the behavioral economics is used to analyze the simulation results.The research findings are that the increasing Knightian uncertainty incurs the decline of the principal’s maximum profit;within the probation period,the increasing Knightian uncertainty leads to the shortening of probation period and makes the agent give higher effort when she faces the outside option;what’s more,after the smooth completion of the probation period for the agent,the agent’s consumption level will rise and her effort level will drop as Knightian uncertainty increasing.

关键词： Knightian uncertainty Principal-agent Sublinear expectation HJB equation Behavioral economics

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X-ray emission characteristics in magnetically driven plasma jet experiments on PTS facility

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Matter and Radiation at Extremes 2020年第1期5卷 8-15页

作者： Qiang Xu Shaotong Zhou kun-lun wang Siqun Zhang Hongchun Cai Xiao Ren Pan Liu Xian bin Huang Li Zhao Wenkang Zou Key Laboratory of Pulsed Power Institute of Fluid PhysicsChina Academy of Engineering PhysicsP.O.Box 919-108Mianyang 621999China Southwest University of Science and Technology Mianyang CitySichuan Province 621010China

Jets are commonly observed astrophysical phenomena.To study the x-ray emission characteristics of jets,a series of radial foil Z-pinch experiments are carried out on the Primary Test Stand at the Institute of Fluid Physics,China Academy of Engineering Physics.In these experiments,x-ray emission ranging from the soft region(0.1–10 keV)to the hard region(10 keV–500 keV)is observed when the magnetic cavity breaks.The radiation flux of soft x-rays is measured by an x-ray diode and the dose rate of the hard x-rays by an Si-PIN detector.The experimental results indicate that the energy of the soft x-rays is several tens of kilojoules and that of the hard x-rays is∼200 J.The radiation mechanismof the x-ray emission is briefly analyzed.This analysis indicates that the x-ray energy and the plasma kinetic energy come from the magnetic energy when the magnetic cavity breaks.The soft x-rays are thought to be produced by bremsstrahlung of thermal electrons(∼100 eV),and the hard x-rays by bremsstrahlung of super-hot electrons(∼mega-electron-volt).These results may be helpful to explain the xray emission by the jets from young stellar objects.

关键词： magnetic explain characteristics

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Semi-supervised remote sensing image scene classification with prototype-based consistency

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Chinese Journal of Aeronautics 2024年第2期37卷 459-470页

作者： Yang LI Zhang LI Zi wang kun wang Qifeng YU College of Aerospace Science and Engineering National University of Defense TechnologyChangsha 410073China

Deep learning significantly improves the accuracy of remote sensing image scene classification,benefiting from the large-scale datasets.However,annotating the remote sensing images is time-consuming and even tough for experts.Deep neural networks trained using a few labeled samples usually generalize less to new unseen images.In this paper,we propose a semi-supervised approach for remote sensing image scene classification based on the prototype-based consistency,by exploring massive unlabeled images.To this end,we,first,propose a feature enhancement module to extract discriminative features.This is achieved by focusing the model on the foreground areas.Then,the prototype-based classifier is introduced to the framework,which is used to acquire consistent feature representations.We conduct a series of experiments on NWPU-RESISC45 and Aerial Image Dataset(AID).Our method improves the State-Of-The-Art(SOTA)method on NWPU-RESISC45 from 92.03%to 93.08%and on AID from 94.25%to 95.24%in terms of accuracy.

关键词： Semi-supervised learning Remote sensing Scene classification Prototype network Deep learning

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Numerical and experimental investigation into the evolution of the shock wave when a muzzle jet impacts a constrained moving body

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Defence Technology（防务技术） 2024年第3期33卷 317-326页

作者： Zijie Li Hao wang Changshun Chen kun Jiang School of Energy and Power Engineering Nanjing University of Science and TechnologyNanjing 210016China

The gun-track launch system is a new special launch device that connects the track outside the muzzle.Because it is constrained by the track,the characteristics of development of the muzzle jet differ from those of the traditional muzzle jet.Specifically,it changes from freely developing to doing so in a constrained manner,where this results in an asymmetric direction of flow as well as spatio-temporal coupling-induced interference between various shock waves and the formation of vortices.In this background,the authors of this article formulate and consider the development and characteristics of evolution of the muzzle jet as it impacts a constrained moving body.We designed simulations to test the gun-track launch system,and established a numerical model based on the dynamic grid method to explore the development and characteristics of propagation of disturbances when the muzzle jet impacted a constrained moving body.We also considered models without a constrained track for the sake of comparison.The results showed that the muzzle jet assumed a circumferential asymmetric shape,and tended to develop in the area above the muzzle.Because the test platform was close to the ground,the muzzle jet was subjected to reflections from it that enhanced the development and evolution of various forms of shock waves and vortices in the muzzle jet to exacerbate its rate of distortion and asymmetric characteristics.This in turn led to significant differences in the changes in pressure at symmetric points that would otherwise have been identical.The results of a comparative analysis showed that the constrained track could hinder the influence of reflections from the ground on the muzzle jet to some extent,and could reduce the velocity of the shock waves inducing the motion of the muzzle as well as the Mach number of the moving body.The work here provides a theoretical basis and the requisite technical support for applications of the gun-track launch system.It also sheds light on the technical bottlenecks that need to be considered

关键词： Shock wave/vortex interference Muzzle jet Constrained boundary Dynamic grid

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Topology Optimization of Two Fluid Heat Transfer Problems for Heat Exchanger Design

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Computer Modeling in Engineering & Sciences 2024年第8期140卷 1949-1974页

作者： kun Yan Yunyu wang Jun Yan School of Chemical Engineering Dalian University of TechnologyDalian116024China Jianghuai Advanced Technology Center Hefei230000China State Key Laboratory of Structural Analysis for Industrial Equipment Department of Engineering MechanicsInternational Research Center for Computational MechanicsDalian University of TechnologyDalian116024China

Topology optimization of thermal-fluid coupling problems has received widespread attention.This article proposes a novel topology optimization method for laminar two-fluid heat exchanger design.The proposed method utilizes an artificial density field to create two permeability interpolation functions that exhibit opposing trends,ensuring separation between the two fluid domains.Additionally,a Gaussian function is employed to construct an interpolation function for the thermal conductivity coefficient.Furthermore,a computational program has been developed on the OpenFOAM platform for the topology optimization of two-fluid heat exchangers.This program leverages parallel computing,significantly reducing the time required for the topology optimization process.To enhance computational speed and reduce the number of constraint conditions,we replaced the conventional pressure drop constraint condition in the optimization problem with a pressure inlet/outlet boundary condition.The 3D optimization results demonstrate the characteristic features of a surface structure,providing valuable guidance for designing heat exchangers that achieve high heat exchange efficiency while minimizing excessive pressure loss.At the same time,a new structure appears in large-scale topology optimization,which proves the effectiveness and stability of the topology optimization program written in this paper in large-scale calculation.

关键词： Topology optimization two fluid heat exchanger OpenFOAM large scale

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A review on ultra-small undoped MoS_(2) as advanced catalysts for renewable fuel production

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Carbon Energy 2024年第2期6卷 92-112页

作者： Guoping Liu Lingling Ding Yuxuan Meng Ahmad Ali Guifu Zuo Xianguang Meng kun Chang Oi lun Li Jinhua Ye Hebei Provincial Laboratory of Inorganic Nonmetallic Materials College of Materials Science and EngineeringNorth China University of Science and TechnologyTangshanChina College of Materials Science and Technology Nanjing University of Aeronautics and AstronauticsNanjingChina School of Materials Science and Engineering Pusan National UniversityBusanKorea International Center for Materials Nanoarchitectonics(WPIMANA) National Institute for Materials Science(NIMS)1-1 NamikiTsukubaIbarakiJapan

Molybdenum disulfide(MoS_(2))has garnered significant attention in the field of catalysis due to the high density of active sites in its unique two-dimensional(2D)structure,which could be developed into numerous high-performance catalysts.The synthesis of ultra-small MoS2 particles(<10 nm)is highly desired in various experimental studies.The ultra-small structure could often lead to a distinct S-Mo coordination state and nonstoichiometric composition in MoSx,minimizing in-plane active sites of the 2D structure and making it probable to regulate the atomic and electronic structure of its intrinsic active sites on a large extent,especially in MoSx clusters.This article summarizes the recent progress of catalysis over ultra-small undoped MoS_(2) particles for renewable fuel production.Through a systematic review of their synthesis,structural,and spectral characteristics,as well as the relationship between their catalytic performance and inherent defects,we aim to provide insights into catalysis over this matrix that may potentially enable advancement in the development of high-performance MoS_(2)-based catalysts for sustainable energy generation in the future.

关键词： applications catalytic MoS_(2) structure synthesis

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Editorial Commentary:Copper Homeostasis in Neurodegenerative Diseases

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Current Medical Science 2024年第1期44卷 244-245页

作者： Ying-hui LI kun wang Institute for Translational Medicine The Affiliated Hospital of Qingdao UniversityCollege of MedicineQingdao UniversityQingdao 266021China

Copper,as an essential trace nutrient,plays a crucial role in biological processes such as mitochondrial respiration,antioxidant stress response,and the synthesis of biomolecules.Typically,cellular copper concentrations are maintained at very low levels,a pattern also observed in cancer cells to prevent adverse consequences of copper overload,such as cuproptosis.This involves copper dependency,accumulation of lipidated proteins,and a reduction in Fe-S cluster proteins[1].Various neurodegenerative diseases are associated with imbalances in copper homeostasis.

关键词： copper Copper consequences

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Using MsfNet to Predict the ISUP Grade of Renal Clear Cell Carcinoma in Digital Pathology Images

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Computers, Materials & Continua 2024年第1期78卷 393-410页

作者： kun Yang Shilong Chang Yucheng wang Minghui wang Jiahui Yang Shuang Liu kun Liu Linyan Xue College of Quality and Technical Supervision Hebei UniversityBaoding071002China National and Local Joint Engineering Research Center of Metrology Instrument and System Hebei UniversityBaoding071002China Hebei Technology Innovation Center for Lightweight of New Energy Vehicle Power System Hebei UniversityBaoding071002China

Clear cell renal cell carcinoma(ccRCC)represents the most frequent form of renal cell carcinoma(RCC),and accurate International Society of Urological Pathology(ISUP)grading is crucial for prognosis and treatment selection.This study presents a new deep network called Multi-scale Fusion Network(MsfNet),which aims to enhance the automatic ISUP grade of ccRCC with digital histopathology pathology images.The MsfNet overcomes the limitations of traditional ResNet50 by multi-scale information fusion and dynamic allocation of channel quantity.The model was trained and tested using 90 Hematoxylin and Eosin(H&E)stained whole slide images(WSIs),which were all cropped into 320×320-pixel patches at 40×*** achieved a micro-averaged area under the curve(AUC)of 0.9807,a macro-averaged AUC of 0.9778 on the test dataset.The Gradient-weighted Class Activation Mapping(Grad-CAM)visually demonstrated MsfNet’s ability to distinguish and highlight abnormal areas more effectively than ResNet50.The t-Distributed Stochastic Neighbor Embedding(t-SNE)plot indicates our model can efficiently extract critical features from images,reducing the impact of noise and redundant information.The results suggest that MsfNet offers an accurate ISUP grade of ccRCC in digital images,emphasizing the potential of AI-assisted histopathological systems in clinical practice.

关键词： Renal cell carcinoma computer-aided diagnosis pathology image deep learning machine learning

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A Review of Computing with Spiking Neural Networks

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Computers, Materials & Continua 2024年第3期78卷 2909-2939页

作者： Jiadong Wu Yinan wang Zhiwei Li lun Lu Qingjiang Li College of Electronic Science and Technology National University of Defense TechnologyChangsha410073China

Artificial neural networks(ANNs)have led to landmark changes in many fields,but they still differ significantly fromthemechanisms of real biological neural networks and face problems such as high computing costs,excessive computing power,and so on.Spiking neural networks(SNNs)provide a new approach combined with brain-like science to improve the computational energy efficiency,computational architecture,and biological credibility of current deep learning applications.In the early stage of development,its poor performance hindered the application of SNNs in real-world scenarios.In recent years,SNNs have made great progress in computational performance and practicability compared with the earlier research results,and are continuously producing significant results.Although there are already many pieces of literature on SNNs,there is still a lack of comprehensive review on SNNs from the perspective of improving performance and practicality as well as incorporating the latest research results.Starting from this issue,this paper elaborates on SNNs along the complete usage process of SNNs including network construction,data processing,model training,development,and deployment,aiming to provide more comprehensive and practical guidance to promote the development of SNNs.Therefore,the connotation and development status of SNNcomputing is reviewed systematically and comprehensively from four aspects:composition structure,data set,learning algorithm,software/hardware development platform.Then the development characteristics of SNNs in intelligent computing are summarized,the current challenges of SNNs are discussed and the future development directions are also prospected.Our research shows that in the fields of machine learning and intelligent computing,SNNs have comparable network scale and performance to ANNs and the ability to challenge large datasets and a variety of tasks.The advantages of SNNs over ANNs in terms of energy efficiency and spatial-temporal data processing have been more fully exploited.And the developme

关键词： Spiking neural networks neural networks brain-like computing artificial intelligence learning algorithm

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Electrochemical Analysis of Single Glucose Oxidase with a Nanopipette

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Chemical Research in Chinese Universities 2024年第2期40卷 272-278页

作者： wang Yongyong MA Hui LONG Yi-Tao YING Yi-lun School of Chemistry and Chemical Engineering Molecular Sensing and Imaging Center(MSIC)Nanjing UniversityNanjing210023P.R.China

Nanopore-based electrochemical technique is a promising tool for detecting single proteins.However,detecting single proteins using a nanopipette in their native state without labeling is challenging due to the rapid translocation,which results in an inefficient signal identification.In our study,we finely tuned the driving force equilibrium between electrophoretic force(EPF)and electroosmotic flow(EOF)inside the nanopipette for efficient sensing of single glucose oxidase(GOD)molecules.The duration time of GOD within the nanopipette is extended to about 4 ms.This strategy provided clear ionic current signals with a signal-to-noise ratio of 3.3.As EPF increased in the direction opposite to the motion of GOD,we observed a nonlinear growth in GOD’s duration time.This extended the duration to about 4.4 times longer at−1000 mV compared to at−800 mV.Hence,nanopore-based electrochemical sensing could be used for single GOD molecule analysis as an ultrasensitive method.

关键词： Nanopore Single-molecule analysis Glucose oxidase Electrophoretic force Electroosmotic flow

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