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SURFACE-ENHANCED CANTILEVER SENSORS WITH NANO-POROUS FILMS

Acta Mechanica Solida Sinica 2010年第1期23卷 1-12页

作者： Huiling Duan(State key laboratory for Turbulence and complex system,CAPT and Department of Mechanics and Aerospace engineering,College of engineering,Peking University,Beijing 100871,China) [a] State Key Laboratory for Turbulence Complex System CAPT Department of Mechanics Aerospace Engineering College of Engineering Peking University Beijing 100871 China

Developing surface-enhanced microcantilevers with improved sensitivities is of longstanding interest. In this paper, the design of surface-enhanced cantilever sensors using nano- （micro-） porous films as surface layers is proposed. The static deformation and resonance frequencies of these surface-enhanced sensors with the simultaneous effects of the eigenstrain, the surface stress and the adsorption mass are analyzed. It is shown that the sensitivities of these novel cantilever sensors for the static deformation and resonance frequencies can be tuned by the porosity, the size of the pores and the structure of the porous films. For the three kinds of cantilever consisting of solid films, films with aligned cylindrical micro-scale pores, and those with nano-scale pores, the nano-porous one has the highest static and dynamic sensitivities, whereas the solid one has the lowest.

关键词： cantilever sensors nano- （micro-） porous films surface stress curvature resonance frequency

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Trajectory tracking control of a bionic robotic fish based on iterative learning

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Science China(Information Sciences) 2020年第7期63卷 79-87页

作者： Ming WANG Yanlu ZHANG Huifang DONG Junzhi YU School of Information and Electrical Engineering Shandong Jianzhu University State Key Laboratory for Turbulence and Complex System Department of Mechanics and Engineering ScienceBIC-ESAT College of Engineering Peking University

A bionic robotic fish has great potential application prospect. High maneuverability swimming control of a bionic robotic fish has been one of the research hotspots in the robotic fish field. In this paper,an iterative learning method has been proposed to solve the trajectory tracking control problem of robotic fish swimming. First, a dynamic model of the multi-joint bionic robotic fish is established. By considering a three-joint robotic fish as an example, the unified expression of the dynamic equation of the three-joint bionic robotic fish is obtained by Lagrange method. Second, the iterative learning controller for controlling the bionic robotic fish is designed. Then the convergence of the iterative learning controller is ***, the trajectory tracking control simulation experiment based on iterative learning is conducted. The simulation results show that the trajectory tracking control method based on iterative learning for a bionic robotic fish is effective.

关键词： bionic robot fish iterative learning trajectory tracking motion control

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Fast and scalable in-network lock management using lock fission 24

Fast and scalable in-network lock management using lock fiss...

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Proceedings of the 18th USENIX Conference on Operating systems Design and Implementation

作者： Hanze Zhang Ke Cheng Rong Chen Haibo Chen Institute of Parallel and Distributed Systems SEIEE Shanghai Jiao Tong University and Shanghai AI Laboratory and MoE Key Lab of Artificial Intelligence AI Institute Shanghai Jiao Tong University Institute of Parallel and Distributed Systems SEIEE Shanghai Jiao Tong University and Engineering Research Center for Domain-specific Operating Systems Ministry of Education China Institute of Parallel and Distributed Systems SEIEE Shanghai Jiao Tong University and Shanghai AI Laboratory and Engineering Research Center for Domain-specific Operating Systems Ministry of Education China Institute of Parallel and Distributed Systems SEIEE Shanghai Jiao Tong University and Engineering Research Center for Domain-specific Operating Systems Ministry of Education China and Key Laboratory of System Software (Chinese Academy of Sciences)

ISBN: (纸本)9781939133403

Distributed lock services are extensively utilized in distributed systems to serialize concurrent accesses to shared resources. The need for fast and scalable lock services has become more pronounced with decreasing task execution times and expanding dataset scales. However, traditional lock managers, reliant on server CPUs to handle lock requests, experience significant queuing delays in lock grant latency. Advanced network hardware (e.g. programmable switches) presents an avenue to manage locks without queuing delays due to their high packet processing power. Nevertheless, their constrained memory capacity restricts the manageable lock scale, thereby limiting their effect in large-scale *** paper presents FISSLOCK, a fast and scalable distributed lock service that exploits the programmable switch to improve (tail) latency and peak throughput for millions of locks. The key idea behind FISSLOCK is the concept of lock fission, which decouples lock management into grant decision and participant maintenance. FISSLOCK leverages the programmable switch to decide lock grants synchronously and relies on servers to maintain participants (i.e., holders and waiters) asynchronously. By using the programmable switch for routing, FISSLOCK enables on-demand fine-grained lock migration, thereby reducing the lock grant and release delays. FISSLOCK carefully designs and implements grant decision procedure on the programmable switch, supporting over one million locks. Evaluation using various benchmarks and a real-world application shows the efficiency of FISSLOCK. Compared to the state-of-the-art switch-based approach (NetLock), FISSLOCK cuts up to 79.1% (from 43.0%) of median lock grant time in the microbenchmark and improves transaction throughput for TATP and TPC-C by 1.76× and 2.28×, respectively.

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Neural network as a function approximator and its application in solving differential equations

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Applied Mathematics and Mechanics(English Edition) 2019年第2期40卷 237-248页

作者： Zeyu LIU Yantao YANG Qingdong CAI State Key Laboratory for Turbulence and Complex System Peking University Department of Mechanics and Engineering Science College of EngineeringPeking University Center for Applied Physics and Technology College of EngineeringPeking University

A neural network(NN) is a powerful tool for approximating bounded continuous functions in machine learning. The NN provides a framework for numerically solving ordinary differential equations(ODEs) and partial differential equations(PDEs)combined with the automatic differentiation(AD) technique. In this work, we explore the use of NN for the function approximation and propose a universal solver for ODEs and PDEs. The solver is tested for initial value problems and boundary value problems of ODEs, and the results exhibit high accuracy for not only the unknown functions but also their derivatives. The same strategy can be used to construct a PDE solver based on collocation points instead of a mesh, which is tested with the Burgers equation and the heat equation(i.e., the Laplace equation).

关键词： neural network(NN) function approximation ordinary differential equation(ODE)solver partial differential equation(PDE)solver

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CM-UNet++: A Multi-Level Information Optimized Network for Urban Water Body Extraction from High-Resolution Remote Sensing Imagery

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Remote Sensing 2025年第6期17卷 980-980页

作者： Cai, Jiangchen Tao, Liufeng Li, Yang National Engineering Research Center of Geographic Information System China University of Geosciences Wuhan 430074 China School of Computer Science China University of Geosciences Wuhan 430074 China Key Laboratory of Urban Land Resources Monitoring and Simulation Ministry of Natural Resource Shenzhen518000 China Engineering Research Center of Natural Resource Information Management and Digital Twin Engineering Software Ministry of Education Wuhan 430074 China School of Geophysics and Geomatics China University of Geosciences Wuhan 430074 China Anhui Urban & Rural Planning and Design Institute Co. Ltd. Hefei230022 China

Urban water bodies are crucial in urban planning and flood detection, and they are susceptible to changes due to climate change and rapid urbanization. With the development of high-resolution remote sensing technology and the success of semantic segmentation using deep learning in computer vision, it is possible to extract urban water bodies from high-resolution remote sensing images. However, many urban water bodies are small, oddly shaped, silted, or spectrally similar to other objects, making their extraction extremely challenging. In this paper, we propose a neural network named CM-UNet++, a combination of the dense-skip module based on UNet++ and the CSMamba module to encode different levels’ information with interactions and then extract global and local information at each level. We use a size-weighted auxiliary loss function to balance feature maps of different levels. Additionally, features beyond RGB are incorporated into the input of the neural network to enhance the distinction between water bodies and other objects. We produced a labeled urban water extraction dataset, and experiments on this dataset show that CM-UNet++ attains 0.8781 on the IOU (intersection over union) metric, which indicates that this method outperforms other recent semantic segmentation methods and achieves better completeness, connectivity, and boundary accuracy. The proposed dense-skip module and CSMamba module significantly improve the extraction of small and spectrally indistinct water bodies. Furthermore, experiments on a public dataset confirm the method’s robustness. © 2025 by the authors.

关键词： Semantic Segmentation

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Long-term effects of PM2.5 constituents on childhood attention deficit hyperactivity disorder: evidence from a large population-based study in the Pearl River Delta Region, China

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Environmental Research 2025年 277卷 121641页

作者： Zeng, Hui-Xian Meng, Wen-Jie Zeng, Qing-Guo Wei, Jing Liu, Lu-Sheng Wu, Qi-Zhen Zhao, Bin Oudin, Anna Yang, Mo Jalava, Pasi Dong, Guang-Hui Zeng, Xiao-Wen Joint International Research Laboratory of Environment and Health Ministry of Education Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment Department of Occupational and Environmental Health School of Public Health Sun Yat-sen University Guangzhou510080 China Department of Atmospheric and Oceanic Science Earth System Science Interdisciplinary Center University of Maryland College ParkMD United States State Key Joint Laboratory of Environmental Simulation and Pollution Control School of Environment Tsinghua University Beijing100084 China State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex Beijing100084 China Department of Public Health and Clinical Medicine Umeå University Umeå Sweden Department of Environmental and Biological Science University of Eastern Finland Kuopio Finland

Background: Evidence linking fine particulate matter (PM2.5) constituents to childhood attention deficit hyperactivity disorder (ADHD) was limited. Objectives: To investigate the individual and joint effects of exposure to PM2.5 constituents on ADHD. Methods: We conducted a large population-based survey involving 110,818 school children aged 6–18 years across six cities in the Pearl River Delta region, China. The three-year average concentrations of PM2.5 constituents (black carbon (BC), organic matter (OM), sulfate, nitrate, and ammonium) were estimated using the ChinaHighAirPollutants dataset. Parents completed an ADHD checklist using the Diagnostic and Statistical Manual of Mental Disorders-IV criteria. The individual and joint associations between PM2.5 components and ADHD were estimated using generalized linear mixed models and the quantile g-computation regression model, respectively. Results: The exposure-response relationships between PM2.5 constituents and ADHD primarily exhibited a nonlinear pattern. Compared with the lowest tertile, the highest tertiles of PM2.5 and its components were linked to greater odds for ADHD (e.g., the adjusted odds ratio (OR) was 1.37 (95 % confidential interval (CI): 1.27, 1.47) for PM2.5, 1.51 (95 %CI: 1.40, 1.63) for OM, 1.29 (95 %CI: 1.20, 1.39) for BC, and 1.20 (95 %CI:1.08, 1.34) for sulfate). Similar positive associations were observed between BC and sulfate exposure and ADHD subtypes. Moreover, joint exposure to PM2.5 components was associated with ADHD (OR = 1.14, 95 % CI:1.10, 1.18), with OM and BC contributing more to the observed associations. Conclusions: These findings highlight the varying contributions of PM2.5 constituents to ADHD and underscore the importance of reducing specific PM2.5 component emissions to mitigate the burden of PM2.5-associated neurodevelopmental diseases. © 2025 Elsevier Inc.

关键词： Regression analysis

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On the Fourier approximation method for steady water waves

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Acta Oceanologica Sinica 2014年第5期33卷 37-47页

作者： ZHAO Hongjun SONG Zhiyao LI Ling KONG Jun State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering College of HarborCoastal and Offshore Engineering Hohai University Key Laboratory of Virtual Geographic Environment Key Laboratory for Numerical Simulation of Largescale Complex System Nanjing Normal University School of Engineering The University of Queensland

A computational method for steady water waves is presented on the basis of potential theory in the physical plane with spatial variables as independent quantities. The finite Fourier series are applied to approximating the free surface and potential function. A set of nonlinear algebraic equations for the Fourier coefficients are derived from the free surface kinetic and dynamic boundary conditions. These algebraic equations are numerically solved through Newton＇s iterative method, and the iterative stability is further improved by a relaxation technology. The integral properties of steady water waves are numerically analyzed, showing that （1） the set-up and the set-down are both non-monotonic quantities with the wave steepness, and （2） the Fourier spectrum of the free surface is broader than that of the potential function. The latter further leads us to explore a modification for the present method by approximating the free surface and potential function through different Fourier series, with the truncation of the former higher than that of the latter. Numerical tests show that this modification is effective, and can notably reduce the errors of the free surface boundary conditions.

关键词： steady water waves Fourier series Newton＇s method relaxation technology wave properties

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CodeIF-Bench: Evaluating Instruction-Following Capabilities of Large Language Models in Interactive Code Generation

arXiv

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arXiv 2025年

作者： Wang, Peiding Zhang, Li Liu, Fang Shi, Lin Li, Minxiao Shen, Bo Fu, An School of Computer Science and Engineering State Key Laboratory of Complex & Critical Software Environment Beihang University China Huawei Cloud Computing Technologies Co. Ltd China

Large Language Models (LLMs) have demonstrated exceptional performance in code generation tasks and have become indispensable programming assistants for developers. However, existing code generation benchmarks primarily assess the functional correctness of code generated by LLMs in single-turn interactions, offering limited insight into their capabilities to generate code that strictly follows users’ instructions, especially in multi-turn interaction scenarios. In this paper, we introduce CodeIF-Bench, a benchmark for evaluating LLMs’ instruction-following capabilities in interactive code generation. Specifically, CodeIF-Bench incorporates nine types of verifiable instructions aligned with the real-world software development requirements, which can be independently and objectively validated through specified test cases, facilitating the evaluation of instruction-following capability in multi-turn interactions. We evaluate nine prominent LLMs using CodeIF-Bench, and the experimental results reveal a significant disparity between their basic programming capability and instruction-following capability, particularly as task complexity, context length, and the number of dialogue rounds increase. The data and code are available at https://***/r/CodeIFBench. Copyright © 2025, The Authors. All rights reserved.

关键词： software design

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Viscous Rayleigh-Taylor instability with and without diffusion effect

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Applied Mathematics and Mechanics(English Edition) 2017年第2期38卷 263-270页

作者： Chenyue XIE Jianjun TAO Ji LI Center for Applied Physics and Technology (CAPT)-MOE Key Laboratory of High Energy Density Physics Simulation (HEDPS) State Key Laboratory for Turbulence and Complex System (SKLTCS) Department of Mechanics and Engineering ScienceCollege of Engineering Peking University Department of Engineering University of Cambridge

The approximate but analytical solution of the viscous Rayleigh-Taylor insta- bility （RTI） has been widely used recently in theoretical and numerical investigations due to its clarity. In this paper, a modified analytical solution of the growth rate for the viscous RTI of incompressible fluids is obtained based on an approximate method. Its accuracy is verified numerically to be significantly improved in comparison with the previous one in the whole wave number range for different viscosity ratios and Atwood numbers. Fur- thermore, this solution is expanded for viscous RTI including the concentration-diffusion effect.

关键词： viscous Rayleigh-Taylor instability （RTI） dispersion relation diffusioneffect

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Effects of Reduced Frequency on Network Configuration and Synchronization Transition

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Chinese Physics Letters 2016年第5期33卷 14-17页

作者：朱留华 Guangxi Colleges and Universities Key Laboratory of Complex System Optimization and Big Data Processing College of Physics Science and Engineering TechnologyYulin Normal University

Synchronization of networked phase oscillators depends essentially on the correlation between the topological structure of the graph and the dynamical property of the elements. We propose the concept of ＇reduced frequency＇, a measure which can quantify natural frequencies of each pair of oscillators. Then we introduce an evolving network whose linking rules are controlled by its own dynamical property. The simulation results indicate that when the linking probability positively correlates with the reduced frequency, the network undergoes a first-order phase transition. Meanwhile, we discuss the circumstance under which an explosive synchronization can be ignited. The numerical results show that the peculiar butterfly shape correlation between frequencies and degrees of the nodes contributes to an explosive synchronization transition.

关键词： of work as it Effects of Reduced Frequency on Network Configuration and Synchronization Transition is that

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