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A combined strategy for the overproduction of complex ergot alkaloid agroclavine

Synthetic and systems Biotechnology 2022年第4期7卷 1126-1132页

作者： Zhi-Pu Yu Chunyan An Yongpeng Yao Chang-Yun Wang Zhoutong Sun Chengsen Cui Ling Liu Shu-Shan Gao Key Laboratory of Marine Drugs The Ministry of Education of ChinaInstitute of Evolution&Marine BiodiversitySchool of Medicine and PharmacyOcean University of ChinaQingdao266003PR China Tianjin Institute of Industrial Biotechnology Chinese Academy of SciencesTianjin300308PR China Laboratory for Marine Drugs and Bioproducts Qingdao National Laboratory for Marine Science and TechnologyQingdao266003PR China State Key Laboratory of Mycology Institute of MicrobiologyChinese Academy of SciencesBeijing100101PR China Beijing Institute for Drug Control NMPA Key Laboratory for Research and Evaluation of Generic DrugsBeijing Key Laboratory of Analysis and Evaluation on Chinese MedicineBeijing102206PR China National Technology Innovation Center of Synthetic Biology Tianjin300308PR China

Microbial cell factories(MCFs)and cell-free systems(CFSs)are generally considered as two unrelated approaches for the biosynthesis of *** the current study,two systems were combined together for the overproduction of agroclavine(AC),a structurally complex ergot *** whole biosynthetic pathway for AC was split into the early pathway and the late pathway at the point of the FAD-linked oxidoreductase EasE,which was reconstituted in an MCF(Aspergillus nidulans)and a four-enzyme CFS,*** final titer of AC of this combined system is 1209 mg/L,which is the highest one that has been reported so far,to the best of our *** development of such a combined route could potentially avoid the limitations of both MCF and CFS systems,and boost the production of complex ergot alkaloids with polycyclic ring systems.

关键词： Microbial cell factories Cell-free systems Overproduction Agroclavine Ergot alkaloids

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Efficient View Path Planning for Autonomous Implicit Reconstruction

Efficient View Path Planning for Autonomous Implicit Reconst...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Jing Zeng Yanxu Li Yunlong Ran Shuo Li Fei Gao Lincheng Li Shibo He Jiming Chen Qi Ye Zhejiang University Hangzhou China Fuxi AI Lab NetEase Hangzhou China State Key Laboratory of Industrial Control Technology and also the Key Laboratory of Collaborative Sensing and Autonomous Unmanned Systems of Zhejiang Province College of Control Science and Engineering Zhejiang University China

Implicit neural representations have shown promising potential for 3D scene reconstruction. Recent work applies it to autonomous 3D reconstruction by learning information gain for view path planning. Effective as it is, the computation of the information gain is expensive, and compared with that using volumetric representations, collision checking using the implicit representation for a 3D point is much slower. In the paper, we propose to 1) leverage a neural network as an implicit function approximator for the information gain field and 2) combine the implicit fine-grained representation with coarse volumetric representations to improve efficiency. Further with the improved efficiency, we propose a novel informative path planning based on a graph-based planner. Our method demonstrates significant improvements in the reconstruction quality and planning efficiency compared with autonomous reconstructions with implicit and explicit representations. We deploy the method on a real UAV and the results show that our method can plan informative views and reconstruct a scene with high quality.

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Real-time In-situ Defect Detection in 3D Printing of Continuous Fiber-Reinforced Composites 4

Real-time In-situ Defect Detection in 3D Printing of Continu...

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4th IEEE International Conference on Digital Twins and Parallel Intelligence, DTPI 2024

作者： Yue, Zhijian Shen, Zhen Dong, Xiangyang Fang, Qihang Wang, Weixing Dong, Xisong Xiong, Gang Wang, Fei-Yue University of Chinese Academy of Sciences School of Artificial Intelligence Beijing100049 China Chinese Academy of Sciences State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Beijing100190 China Qingdao Academy of Intelligent Industries Intelligent Manufacturing Center Qingdao266109 China Chinese Academy of Sciences Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Dongguan523808 China Chinese Academy of Sciences State Key Laboratory for Management and Control for Complex Systems Institute of Automation Beijing100190 China

ISBN: (纸本)9798350349252

With the development of continuous fiber-reinforced composites (CFRCs) 3D printing technology, timely, efficient and accurate detection of fiber path defects is essential for ensuring product quality and performance. However, challenges still need to be addressed in this field, such as inadequate training data coverage and the complexity of fiber path structures. These factors hinder the capability of traditional methods to accurately assess the status of printed products. Therefore, developing accurate and robust fiber path defect detection techniques is crucial for CFRCs 3D printing technology. In this paper, we propose a precise detection method for fiber path defects in CFRCs 3D printing using the YOLOv7 object detection model combined with a Squeeze-and-Excitation (SE) attention mechanism. By introducing the SE attention mechanism, we enhance the perception capability of the YOLOv7 model for crucial features, thereby improving the accuracy of fiber path defect detection. The experimental results show that the YOLOv7 model, when augmented with an attention mechanism, achieves an average accuracy of 93.9% in identifying fiber path defects during the printing process. Compared to models without this attention mechanism, the results show that there is 10.7% increase, with a notably enhanced learning capacity during the training phase, which substantiates the efficacy and practicality of the proposed approach. © 2024 IEEE.

关键词： Fiber reinforced plastics

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Automatic Depth Optimization for Quantum Approximate Optimization Algorithm

arXiv

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arXiv 2022年

作者： Pan, Yu Tong, Yifan Yang, Yi State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control College of Control Science and Engineering Zhejiang University Hangzhou310027 China Department of Mathematics and Statistics McGill University MontrealQCH3A 0B9 Canada

Quantum Approximate Optimization Algorithm (QAOA) is a hybrid algorithm whose control parameters are classically optimized. In addition to the variational parameters, the right choice of hyperparameter is crucial for improving the performance of any optimization model. control depth, or the number of variational parameters, is considered as the most important hyperparameter for QAOA. In this paper we investigate the control depth selection with an automatic algorithm based on proximal gradient descent. The performances of the automatic algorithm are demonstrated on 7-node and 10-node Max-Cut problems, which show that the control depth can be significantly reduced during the iteration while achieving an sufficient level of optimization accuracy. With theoretical convergence guarantee, the proposed algorithm can be used as an efficient tool for choosing the appropriate control depth as a replacement of random search or empirical rules. Moreover, the reduction of control depth will induce a significant reduction in the number of quantum gates in circuit, which improves the applicability of QAOA on Noisy Intermediate-scale Quantum (NISQ) devices. © 2022, CC BY.

关键词： Optimization

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Multi-service collaboration and composition of cloud manufacturing customized production based on problem decomposition

arXiv

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arXiv 2024年

作者： Yue, Hao Wu, Yingtao Wang, Min Hu, Hesuan Wu, Weimin Zhang, Jihui Shandong Qingdao266580 China College of Information Engineering Yangzhou University Jiangsu Yangzhou225127 China School of Electro-Mechanical Engineering Xidian University Shanxi Xi’an710071 China School of Computer Science and Engineering College of Engineering Nanyang Technological University 639798 Singapore State Key Laboratory of Industrial Control Technology Zhejiang University Zhejiang Hangzhou310027 China Institute of Cyber-Systems and Control Zhejiang University Zhejiang Hangzhou310027 China Institute of Complexity Science School of Automation Qingdao University Shandong Qingdao266071 China Shandong Key Laboratory of Industrial Control Technology Shandong Qingdao266071 China

Cloud manufacturing system is a service-oriented and knowledge-based one, which can provide solutions for the large-scale customized production. The service resource allocation is the primary factor that restricts the production time and cost in the cloud manufacturing customized production (CMCP). In order to improve the efficiency and reduce the cost in CMCP, we propose a new framework which considers the collaboration among services with the same functionality. A mathematical evaluation formulation for the service composition and service usage scheme is constructed with the following critical indexes: completion time, cost, and number of selected services. Subsequently, a problem decomposition based genetic algorithm is designed to obtain the optimal service compositions with service usage schemes. A smart clothing customization case is illustrated so as to show the effectiveness and efficiency of the method proposed in this paper. Finally, the results of simulation experiments and comparisons show that these solutions obtained by our method are with the minimum time, a lower cost, and the fewer selected services. © 2024, CC BY-NC-ND.

关键词： Genetic algorithms

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Optimal Sequential False Data Injection Attack Scheme: Finite-Time Inverse Convergence

Optimal Sequential False Data Injection Attack Scheme: Finit...

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IEEE Conference on Decision and control

作者： Xiaoyu Luo Chongrong Fang Chengcheng Zhao Peng Cheng Jianping He The Department of Automation Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Jiao Tong University Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China The State Key Laboratory of Industrial Control Technology Institute of Cyberspace Research Zhejiang University China

In this paper, we explore the relationship between the injected attack signal and the attack selection strategy in networked control systems where the adversary desires to steer the system state to the expected malicious one. We construct a sequential attack framework, i.e., the injected false data varies with the sampling time in discrete-time systems, and then derive an optimal sequential FDI attack strategy. The optimal sequential FDI attack strategy reveals the strongly coupled relationship between the injected attack signal and the attack selection strategy. Furthermore, we prove the finite-time inverse convergence of the critical parameters in the injected optimal attack signal by discrete-time Lyapunov analysis, which enables the efficient off-line design of the attack strategy and saves computing sources. Extensive simulations are conducted to show the effectiveness of the injected optimal sequential attack and the relationship between the attack signal and the attack selection strategy.

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A Vehicle-to-Vehicle Cooperative control Method for Intersections with Cav- Dedicated Lane

SSRN

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SSRN 2024年

作者： Zhang, Xiqiao Cui, Leqi Yang, Longhai Lv, Yisheng School of Transportation Science and Engineering Harbin Institute of Technology Harbin150090 China The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China

With the development of intelligent connected technology and autonomous driving technology, connected autonomous vehicles (CAV) and connected human-driven vehicles (CHV) will coexist for a long time in the future. The popularization of vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication enables the improvement of CAV platooning efficiency and the joint control of CAV trajectory and signal timing. Therefore, this paper proposes a CAV-dedicated lane-based vehicle-to-vehicle interactive intersection control method, which is suitable for managing mixed traffic flow of CHV and CAV at a single intersection. In the proposed method, the road capacity is enhanced by separating the mixed traffic flow with a CAV-dedicated lane. Through vehicle-to-vehicle interaction and CHV induction, the traffic flow spatiotemporal distribution is regulated by a limited number of controlled vehicles. Furthermore, by jointly controlling CAV trajectory and signal timing, vehicles can efficiently pass through the intersection in the CHV phase without the dedicated CAV phase. The optimization of signal timing and vehicle trajectory at the intersection aims to improve intersection capacity and smooth vehicle trajectories. In addition, the car-following and lane-changing models of CHV are revised based on the prospect theory to validate the performance of platooning strategies under cooperative induction information in practical traffic operations. Simulation results demonstrate that compared to control methods without considering vehicle-to-vehicle interaction, the proposed method in this paper has significant advantages in reducing average vehicle delay and improving intersection efficiency. © 2024, The Authors. All rights reserved.

关键词： Autonomous vehicles

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GAS-LIQUID COUPLING ATTENUATOR ARRAY FOR FLUID PULSATION IN VARIABLE PRESSURE HYDRAULIC systems

GAS-LIQUID COUPLING ATTENUATOR ARRAY FOR FLUID PULSATION IN ...

引用

2024 CSAA/IET International Conference on Aircraft Utility systems, AUS 2024

作者： Yang, Haodong Xu, Yuanzhi Wang, Renyuan Liao, Jian Zhou, Fuming Yu, Shuai Zhang, Hongbo Jiao, Zongxia School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Key Laboratory of Advanced Airborne Systems Beihang University Beijing100191 China Ningbo Institute of Technology Beihang University Ningbo315800 China Tianmushan Laboratory Hangzhou310023 China Institute of Vibration and Noise Naval University of Engineering Wuhan430033 China State Key Laboratory of Ship Vibration and Noise Wuhan430033 China Shanghai Hunter Hydraulic Control. Technology-Co. Ltd Shanghai201612 China CSSC-No. 704-Research-Institution Shanghai200031 China

The pressure pulsation of variable pressure hydraulic system has the characteristics of wide range and wide frequency band, aiming at the pressure pulsation suppression demand of this system, this paper proposes a wide-pressure and wide-frequency gas-liquid coupling attenuator array structure. This structure utilizes the gas-liquid coupling principle to absorb pulsation, achieving complete coverage of the system's variable pressure range in the time domain and broadening the optimal pulsation absorbing frequency band in the frequency domain through the simultaneous use of multiple attenuators pre-charged with different pressure gases. This paper analyses the principle of gas-liquid coupling for absorbing flow pulsation, establishes a mathematical model of the device, studies the frequency-domain impedance characteristics of the structure using the impedance method, and utilizes the simulation software AMESim to investigate the impact of the array structure on the pulsation attenuation capabilities in the time and frequency domains. The simulation results are analysed to verify the wide-pressure and wide-frequency characteristics of the proposed array structure. © The Institution of Engineering & technology 2024.

关键词： Frequency domain analysis

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Lightweight Generative Adversarial Networks Based on Ghost Module

Lightweight Generative Adversarial Networks Based on Ghost M...

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2022 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2022

作者： Xiang, Xinyuan Liu, Meiqin Zhang, Senlin Wei, Ping Chen, Badong Xi'An Jiaotong University Institute of Artihcial Intelligence and Robotics Xi'an710049 China Zhejiang University State Key Laboratory of Industrial Control Technology Hangzhou310027 China Zhejiang University College of Electrical Engineering Hangzhou310027 China

ISBN: (数字)9781665469838

ISBN: (纸本)9781665469838

Generative adversarial networks are widely used in computer vision tasks like image translation and image style transfer. Most of mainstream methods including CycleGAN and pix2pix use the stacking of residual blocks to deepen the number of network layers, which makes the networks have a large number of parameters and floating point operations. This paper presents a ghost-module-based generative adversarial networks. We use the ghost module to replace the residual blocks in the traditional generative adversarial network for building lightweight generative adversarial networks. Experiments shows that our method significantly reducing the parameters and floating point operations of the generative adversarial network on the precondition of assuring the quality of the generated images. © 2022 IEEE.

关键词： Generative adversarial networks

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Research on Multi-objective Active Power Optimization Simulation of Novel Improved Water Cycle Algorithm

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IAENG International Journal of Applied Mathematics 2021年第1期51卷 1页

作者： Chen, Gonggui Han, Ying Zhang, Zhizhong Zeng, Xianjun Li, Shuaiyong Key Laboratory of Industrial Internet of Things & Networked Control Ministry of Education Chongqing University of Posts and Telecommunications Chongqing400065 China Chongqing Key Laboratory of Complex Systems and Bionic Control Chongqing University of Posts and Telecommunications Chongqing400065 China Key Laboratory of Communication Network and Testing Technology Chongqing University of Posts and Telecommunications Chongqing400065 China State Grid Chongqing Electric Power Company Chongqing400015 China

Water cycle algorithm (WCA) is a heuristic algorithm proposed in recent years. To overcome the insufficiency of standard WCA algorithm in solving the non-convex optimal power flow (OPF) problems, the multi-objective novel improved water cycle algorithm (MONIWCA) is proposed in this paper. The evaporation process is improved in WCA by introducing evaporation rate and the normal distribution optimization mechanism is used to mutate the individual position. The modified WCA also adopts a constraint-based strategy to ensure zero constraint violations. In order to obtain a high-quality Pareto optimal solution set (POS) and select the best compromise solution (BCs), a global ranking strategy is proposed. The global ranking strategy includes the novel constraint handling method, the rank index calculation and the BCs on fuzzy satisfaction theory to deal with the complex constraints of the optimization problem. The MONIWCA has been simulated under the constraints of zero violations on IEEE 30, IEEE 57 and IEEE 118 standard test systems, including six dual-objective cases and one tri- objective case. The simulation results are compared with the multi-objective particle swarm optimization (MOPSO). The results show that the improved method can effectively solve the MOOPF problem, not only to obtain a uniform continuous Pareto solution set but also to achieve a better compromise solution. In addition, the two performance indicators of the generational distance (GD) and the spacing (SP) also show that the MONIWCA algorithm has uniform distribution, high convergence and strong stability. © 2021, IAENG International Journal of Applied Mathematics. All Rights Reserved.

关键词： Particle swarm optimization (PSO)

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