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Unconventional photon blockade in the two-photon Jaynes–Cummings model with two-frequency cavity drivings and atom driving

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Chinese Physics B 2024年第2期33卷 164-168页

作者：刘欣田梦雨崔晓宁张馨鹤 School of Physics and technology University of JinanJinan 250022China Marketing service center(center of Metrology) State Grid ShanDong Electric Power CompanyJinan 250001China

In a two-frequency cavity driving and atom driving atom-cavity system,we find the photon blockade effect.In a truncated eigenstates space,we calculate the zero-delay second-order correlation function of the cavity mode analytically and obtain an optimal condition for the photon blockade.By including three transition pathways,we find that higher excitations of the cavity mode can be further suppressed and the zero-delay second-order correlation function can be reduced additionally.Based on the master equation,we simulate the system evolution and find that the analytical solutions match well with the numerical results.Our scheme is robust with small fluctuations of parameters and may be used as a new type of single photon source.

关键词： photon blockade single photon source quantum interference

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Sampling-efficient path planning and improved actor-critic-based obstacle avoidance for autonomous robots

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Science China(Information Sciences) 2024年第5期67卷 197-214页

作者： Yefeng YANG Tao HUANG Tianqi WANG Wenyu YANG Han CHEN Boyang LI Chih-yung WEN Department of Aeronautical and Aviation Engineering The Hong Kong Polytechnic University center for Control Theory and Guidance technology Harbin Institute of Technology School of Engineering The University of Newcastle Research center for Unmanned Autonomous systems The Hong Kong Polytechnic University

Autonomous robots have garnered extensive utilization in diverse fields. Among the critical concerns for autonomous systems, path planning holds paramount importance. Notwithstanding considerable efforts in its development over the years, path planning for autonomous systems continues to grapple with challenges related to low planning efficiency and inadequate obstacle avoidance response in a timely manner.This study proposes a novel and systematic solution to the path planning problem within intricate office buildings. The solution consists of a global planner and a local planner. To handle the global planning aspect, an adaptive clustering-based dynamic programming rapidly exploring random tree(ACDP-RRT) algorithm is proposed. ACDP-RRT effectively identifies obstacles on the map by leveraging geometric features.These obstacles are then represented as a collection of sequentially arranged convex polygons, optimizing the sampling region and significantly enhancing sampling efficiency. For local planning, a network decoupling actor-critic(ND-AC) algorithm is employed. The proposed ND-AC simplifies the local planner design process by integrating planning and control loops into a neural network(NN) trained via an end-to-end model-free deep reinforcement learning(DRL) framework. Moreover, the adoption of network decoupling(ND) techniques leads to an improved obstacle avoidance success rate when compared to conventional actor-critic(AC)-based methods. Extensive simulations and experiments are conducted to demonstrate the effectiveness and robustness of the proposed approach.

关键词： rapidly exploring random tree (RRT) adaptive clustering network decoupling actor critic (AC) path planning

A novel triple periodic minimal surface-like plate lattice and its data-driven optimization method for superior mechanical properties

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Applied Mathematics and Mechanics(English Edition) 2024年第2期45卷 217-238页

作者： Yanda WANG Yanping LIAN Zhidong WANG Chunpeng WANG Daining FANG State Key Laboratory for Turbulence and Complex systems&center for Applied Physics and technology College of EngineeringPeking UniversityBeijing 100871China Institute of Advanced Structure technology Beijing Institute of TechnologyBeijing 100081China

Lattice structures can be designed to achieve unique mechanical properties and have attracted increasing attention for applications in high-end industrial equipment,along with the advances in additive manufacturing(AM)technologies.In this work,a novel design of plate lattice structures described by a parametric model is proposed to enrich the design space of plate lattice structures with high connectivity suitable for AM processes.The parametric model takes the basic unit of the triple periodic minimal surface(TPMS)lattice as a skeleton and adopts a set of generation parameters to determine the plate lattice structure with different topologies,which takes the advantages of both plate lattices for superior specific mechanical properties and TPMS lattices for high connectivity,and therefore is referred to as a TPMS-like plate lattice(TLPL).Furthermore,a data-driven shape optimization method is proposed to optimize the TLPL structure for maximum mechanical properties with or without the isotropic constraints.In this method,the genetic algorithm for the optimization is utilized for global search capability,and an artificial neural network(ANN)model for individual fitness estimation is integrated for high efficiency.A set of optimized TLPLs at different relative densities are experimentally validated by the selective laser melting(SLM)fabricated samples.It is confirmed that the optimized TLPLs could achieve elastic isotropy and have superior stiffness over other isotropic lattice structures.

关键词： lattice structure triple periodic minimal surface(TPMS) plate lattice structural optimization machine learning

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Inhibition of Defect-Induced Ice Nucleation, Propagation, and Adhesion by Bioinspired Self-Healing Anti-Icing Coatings

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Research 2024年第1期2023卷 237-246页

作者： Shu Tian Ruiqi Li Xinmeng Liu Jiancheng Wang Junyu Yu Sijia Xu Yunqing Tian Jing Yang Lei Zhang Department of Biochemical Engineering Frontier Science Center for Synthetic Biology and Key Laboratory of Systems Bioengineering(MOE)School of Chemical Engineering and TechnologyTianjin UniversityTianjin 300350China Binzhou Institute of technology Weiqiao-UCAS Science and Technology ParkBinzhou CityShandong Province 256606China

Anti-icing coatings on outdoor infrastructures inevitably suffer from mechanical injuries in numerous icing scenarios such as hailstorms,sandstorms,impacts of foreign objects,and icing–deicing cycles.Herein,the mechanisms of surface-defect-induced icing are clarified.At the defects,water molecules exhibit stronger adsorption and the heat transfer rate increases,accelerating the condensation of water vapor as well as ice nucleation and propagation.Moreover,the ice–defect interlocking structure increases the ice adhesion strength.Thus,a self-healing(at−20℃)antifreeze-protein(AFP)-inspired anti-icing coating is developed.The coating is based on a design that mimics the ice-binding and non-ice-binding sites in AFPs.It enables the coating to markedly inhibit ice nucleation(nucleation temperature<−29.4℃),prevent ice propagation(propagation rate<0.00048 cm^(2)/s),and reduce ice adhesion on the surface(adhesion strength<38.9 kPa).More importantly,the coating can also autonomously self-heal at−20℃,as a result of multiple dynamic bonds in its structure,to inhibit defect-induced icing processes.The healed coating sustains high anti-icing and deicing performance even under various extreme conditions.This work reveals the in-depth mechanism of defect-induced ice formation as well as adhesion,and proposes a self-healing anti-icing coating for outdoor infrastructures.

关键词： coating defect clarified

A FAS approach for stabilization of generalized chained forms: part 1. Discontinuous control laws

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Science China(Information Sciences) 2024年第2期67卷 118-143页

作者： Guang-Ren DUAN center for Control Theory and Guidance technology Harbin Institute of Technology center for Control Science and technology Southern University of Science and Technology

In this paper, a type of general nonholonomic systems is proposed, which contains both the Brockett’s two example systems, and their extended n-dimensional chained forms, as special cases. For the stabilization of such systems, a stabilizing controller is proposed based on the fully actuated system(FAS)approach, which is discontinuous at the origin but time-invariant when the open-loop system is time-invariant,and drives the feasible trajectories of the system to the origin exponentially. Furthermore, the proposed FAS approach is also extended to the sub-normal system case and the time-delay system case.

关键词： nonholonomic systems feedback stabilization exponential convergence sub-fully actuated systems time-delay systems

Online Consensus Control of Nonlinear Affine systems From Disturbed Data

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IEEE/CAA Journal of Automatica Sinica 2024年第2期11卷 551-553页

作者： Yifei Li Wenjie Liu Jian Sun Chen Chen Jia Zhang Gang Wang National Key Laborary of Autonomous Intelligent Unmanned systems Beijing Institute of TechnologyBeijing 100081 Beijing Institute of technology Chongqing Innovation center Chongqing 401120China

Dear Editor,In this letter, we introduce a novel online distributed data-driven robust control approach for learning controllers of unknown nonlinear multi-agent systems(MASs) using state-dependent representations.

关键词： agent online Online

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Simulating the GRF of Humanoid Robot Vertical Jumping Using a Simplified Model with a Foot Structure for Foot Design

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Journal of Bionic Engineering 2024年第1期21卷 112-125页

作者： Chuanku Yi Xuechao Chen Yu Zhang Zhangguo Yu Haoxiang Qi Yaliang Liu Qiang Huang School of Mechatronical Engineering Beijing Institute of TechnologyZizhuyaunHaidianBeijing 100081China Beijing Advanced Innovation center for Intelligent Robots and systems Beijing Institute of Tec

There are many theories and tools for human or robot motion simulation,but most of them require complex calculations.The LNZN model(a simplified model named by the proposers)simplifies the human model and facilitates simulation of the Ground Reaction Force(GRF)of body landing by spring damping model and ignoring joint rotation movements,which can reduce the amount of computation obviously.In this paper,the LNZN model of human running is selected as the basis and is modified to obtain the LNZN model of a robot,which expands the application of the LNZN model.According to the structure of the human foot,a foot structure is then added to the simplified model to reduce the GRF.We also applied driving forces to the new model to simulate the whole high jump motion of the robot to expand the functions of the LNZN model.The obtained GRF data were anastomotic to the actual experimental results.In addition,the effects of variables,such as the mass,hardness,and damping,of the foot on the GRF at the moment of landing were also explored.Finally,based on the guidelines obtained for the design of the robot’s foot structure,we fabricated new robot’s feet and installed them on the actual robot and achieved a better cushioning effect than the original foot in experiments.

关键词： LNZN model-GRF simulation Humanoid foot structure Foot parameters

Neutrophil-to-lymphocyte ratio associated with renal function in type 2 diabetic patients

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World Journal of Clinical Cases 2024年第14期12卷 2308-2315页

作者： Jin-Li Gao Jue Shen Li-Ping Yang Li Liu Kai Zhao Xiao-Rong Pan Lei Li Ji-Ji Xu Department of Prevention and Health Care Community Health Service Center of Miaohang TownShanghai 200443China Department of Prevention and Health Care Community Health Service Center of Songnan TownShanghai 200434China Department of General Practice Community Health Service Center of Songnan TownShanghai 200434China Department of Administrative Community Health Service Center of Songnan TownShanghai 200434China

BACKGROUND Type 2 diabetes mellitus(T2DM)is a leading risk factor for the development and progression of chronic kidney disease(CKD).However,an accurate and con-venient marker for early detection and appropriate management of CKD in in-dividuals with T2DM is limited.Recent studies have demonstrated a strong correlation between the neutrophil-to-lymphocyte ratio(NLR)and CKD.None-theless,the predictive value of NLR for renal damage in type 2 diabetic patients remains understudied.This study included 1040 adults aged 65 or older with T2DM from Shanghai's Community Health service center.The total number of neutrophils and lym-phocytes was detected,and NLR levels were calculated.CKD was defined as an estimated glomerular filtration rate≤60 mL/min/1.73 m².Participants were di-vided into four groups based on NLR levels.The clinical data and biochemical characteristics were compared among groups.A multivariate logistic regression model was used to analyze the association between NLR levels and CKD.RESULTS Significant differences were found in terms of sex,serum creatinine,blood urea nitrogen,total cholesterol,and low-density lipoprotein cholesterol among patients with T2DM in different NLR groups(P<0.0007).T2DM patients in the highest NLR quartile had a higher prevalence of CKD(P for trend=0.0011).Multivariate logistic regression analysis indicated that a high NLR was an independent risk factor for CKD in T2DM patients even after adjustment for important clinical and pathological parameters(P=0.0001,odds ratio=1.41,95%confidence intervals:1.18-1.68).CONCLUSION An elevated NLR in patients with T2DM is associated with higher prevalence of CKD,suggesting that it could be a marker for the detection and evaluation of diabetic kidney disease.

关键词： Type 2 diabetes mellitus Neutrophil-to-lymphocyte ratio Chronic kidney disease Logistic regression Diabetes mellitus

MDCN:Modified Dense Convolution Network Based Disease Classification in Mango Leaves

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Computers, Materials & Continua 2024年第2期78卷 2511-2533页

作者： Chirag Chandrashekar K.P.Vijayakumar K.Pradeep A.Balasundaram School of Computer Science and Engineering Vellore Institute of Technology(VIT)ChennaiIndia center for Cyber Physical systems School of Computer Science and EngineeringVellore Institute of Technology(VIT)ChennaiIndia

The most widely farmed fruit in the world is mango.Both the production and quality of the mangoes are hampered by many diseases.These diseases need to be effectively controlled and mitigated.Therefore,a quick and accurate diagnosis of the disorders is essential.Deep convolutional neural networks,renowned for their independence in feature extraction,have established their value in numerous detection and classification tasks.However,it requires large training datasets and several parameters that need careful adjustment.The proposed Modified Dense Convolutional Network(MDCN)provides a successful classification scheme for plant diseases affecting mango leaves.This model employs the strength of pre-trained networks and modifies them for the particular context of mango leaf diseases by incorporating transfer learning techniques.The data loader also builds mini-batches for training the models to reduce training time.Finally,optimization approaches help increase the overall model’s efficiency and lower computing *** employed on the MangoLeafBD Dataset consists of a total of 4,000 images.Following the experimental results,the proposed system is compared with existing techniques and it is clear that the proposed algorithm surpasses the existing algorithms by achieving high performance and overall throughput.

关键词： Leaf disease detection deep convolutional neural networks transfer learning optimization MangoLeafBD Dataset