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A Spatially Programmable DNA Nanorobot Arm to Modulate Anisotropic Gold Nanoparticle Assembly by Enzymatic Excision

Angewandte Chemie 2023年第43期135卷

作者： Prof. Jing Yang Yuan Liang Xiang Li Yongpeng Zhang Prof. Long Qian Prof. Yonggang Ke Prof. Cheng Zhang School of Computer Science Key Lab of High Confidence Software Technologies Peking University Beijing 100871 China School of Control and Computer Engineering North China Electric Power University Beijing 102206 China Center for Quantitative Biology Peking University Beijing 100871 China Wallace H. Coulter Department of Biomedical Engineering Georgia Institute of Technology and Emory University Emory University School of Medicine Atlanta GA 30322 USA Department of Chemistry Emory University Atlanta GA 30322 USA

Programmable assembly of gold nanoparticle superstructures with precise spatial arrangement has drawn much attention for their unique characteristics in plasmonics and biomedicine. Bio-inspired methods have already provided programmable, molecular approaches to direct AuNP assemblies using biopolymers. The existing methods, however, predominantly use DNA as scaffolds to directly guide the AuNP interactions to produce intended superstructures. New paradigms for regulating AuNP assembly will greatly enrich the toolbox for DNA-directed AuNP manipulation and fabrication. Here, we developed a strategy of using a spatially programmable enzymatic nanorobot arm to modulate anisotropic DNA surface modifications and assembly of AuNPs. Through spatial controls of the proximity of the reactants, the locations of the modifications were precisely regulated. We demonstrated the control of the modifications on a single 15 nm AuNP, as well as on a rectangular DNA origami platform, to direct unique anisotropic AuNP assemblies. This method adds an alternative enzymatic manipulation to DNA-directed AuNP superstructure assembly.

关键词： AuNPs Assembly DNA Origami Enzymatic Excision Reactions Molecular Spatial Programmability Nanorobot

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Real-time rehabilitation exercise performance evaluation system using deep learning and thermal image

Real-time rehabilitation exercise performance evaluation sys...

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IEEE Instrumentation and Measurement Technology Conference

作者： Chien-Hua Huang Chun-Fu Lin Ching-An Chen Chi-Huang Hwang Der-Chen Huang Department of Eldercare Central Taiwan University of Science and Technology Taiwan Republic of China Taiwan Instrument Research Institute National Applied Research Laboratories Taiwan Republic of China Institute of Electrical Control Engineering National Chiao Tung University Taiwan Republic of China Department of Computer Science and Engineering National Chung Hsing University Taiwan Republic of China

ISBN: (数字)9781728144603

ISBN: (纸本)9781728144610

Rehabilitation exercises are a very useful method of physical therapy. Rehabilitation exercise assistant systems are of three types. The first type provides a platform to perform designed rehabilitation exercises, the second type of system encourages and guides the performer in executing rehabilitation exercises, and the third type of system evaluates the performance of rehabilitation exercise schemes. Many methods have been proposed for evaluating the performance of rehabilitation exercise schemes. However, most of these methods do not consider the effect of compensatory movements. Compensatory movement occurs when a performer performs a rehabilitation exercise with nontarget musculature. This work proposes a system that can evaluate rehabilitation exercise performance by detecting the compensatory movements effectively. The core classification algorithm of the proposed system is designed based on CNN deep learning algorithms. The architecture of the proposed algorithm is concise, and thermal imaging is employed to reduce the interference. Therefore, the proposed system can detect the compensatory movements effectively on time, so that real-time rehabilitation exercise performance evaluation is achieved.

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Encoding-Decoding-Based control and Filtering of Networked Systems： Insights, Developments and Opportunities

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IEEE/CAA Journal of Automatica Sinica 2018年第1期5卷 3-18页

作者： Zidong Wang Licheng Wang Shuai Liu Guoliang Wei Department of Computer Science Brunel Univer-sity London Uxbridge Middlesex UB8 3PH United Kingdom Department of Control Science and Engineering University of Shanghai for Science and Technology Shanghai 200093 China University of Shanghai for Science and Technology Shanghai 200093 China IEEE

In order to make the information transmission more efficient and reliable in a digital communication channel with limited capacity, various encoding-decoding techniques have been proposed and widely applied in many branches of the signal processing including digital communications, data compression,information encryption, etc. Recently, due to its promising application potentials in the networked systems(NSs), the analysis and synthesis issues of the NSs under various encoding-decoding schemes have stirred some research attention. However, because of the network-enhanced complexity caused by the limited network resources, it poses new challenges to the design of suitable encoding-decoding procedures to meet certain control or filtering performance for the NSs. In this survey paper, our aim is to present a comprehensive review of the encoding-decodingbased control and filtering problems for different types of ***, some basic introduction with respect to the coding-decoding mechanism is presented in terms of its engineering insights,specific properties and theoretical formulations. Then, the recent representative research progress in the design of the encodingdecoding protocols for various control and filtering problems is discussed. Some possible further research topics are finally outlined for the encoding-decoding-based NSs.

关键词： Encoding-decoding-based communication mechanism encoding-decoding-based control encoding-decodingbased state estimation networked systems

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Multilayer Formation control in Constrained Space

Multilayer Formation Control in Constrained Space

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作者： Guangfu Ma Dongyu Li Chuanjiang Li Wei Zhang Department of Control Science and Engineering Harbin Institute of Technology Department of Electrical and Computer Engineering National University of Singapore Shanghai Institute of Satellite Engineering

This paper addresses the multilayer formation control(MLFC) problem for multiagent systems in constrained space. A layered distributed finite-time estimator(LDFE) is proposed to acquire the target states for agents in each layer. To avoid collisions with borders,obstacles, as well as the other agents in the constrained space, an artificial potential function is designed based on the Dirac delta function. Based on the LDFE and the proposed potential function, the MLFC algorithm is proposed for multiple Euler-Lagrange systems(MELSs). The semi-global uniform ultimate boundedness of closed-loop errors is guaranteed by Lyapunov stability theory, while the desired formation of each layer can be achieved without collisions occurring in the constrained space. Simulation results are given to show the effectiveness of the proposed approaches.

关键词： agent Multilayer Formation control in Constrained Space

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The 2024 Active Metamaterials Roadmap

arXiv

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arXiv 2024年

作者： Pope, Simon A. Roth, Diane J. Bansal, Aakash Mousa, Mostafa Rezanejad, Ashkan Forte, Antonio E. Nash, Geoff.R. Singleton, Lawrence Langfeldt, Felix Cheer, Jordan Henthorn, Stephen Hooper, Ian R. Hendry, Euan Powell, Alex W. Souslov, Anton Plum, Eric Sun, Kai de Groot, C.H. Muskens, Otto L. Shields, Joe De Galarreta, Carlota Ruiz Wright, C. David Kocabas, Coskun Ergoktas, M. Said Xiao, Jianling Schulz, Sebastian A. Di Falco, Andrea Krasavin, Alexey V. Zayats, Anatoly V. Galiffi, Emanuele Department of Automatic Control and Systems Engineering The University of Sheffield Amy Johnson Building Portobello Street SheffieldS1 3JD United Kingdom Department of Physics London Centre for Nanotechnology King’s College London Strand WC2R 2LS United Kingdom Wolfson School of Mechanical Electrical and Manufacturing Engineering Loughborough University United Kingdom Department of Engineering King’s College London LondonWC2R 2LS United Kingdom Natural Sciences University of Exeter Harrison Building North Park Road Exeter United Kingdom Institute of Sound & Vibration Research University of Southampton University Road Southampton United Kingdom Department of Electronic and Electrical Engineering University of Sheffield Sheffield United Kingdom Centre for Metamaterial Research and Innovation University of Exeter Stoker Road ExeterEX4 4QL United Kingdom T.C.M. Group Cavendish Laboratory University of Cambridge CambridgeCB3 0HE United Kingdom Optoelectronics Research Centre Centre for Photonic Metamaterials University of Southampton Highfield SouthamptonSO17 1BJ United Kingdom School of Physics and Astronomy University of Southampton Southampton United Kingdom Electronics and Computer Science University of Southampton Southampton United Kingdom Institute of Materials Science of Barcelona Universitat Autònoma de Barcelona Bellaterra Barcelona08193 Spain Department of Materials National Graphene Institute University of Manchester United Kingdom Schoolof Physics and Astronomy University of St Andrews North Haugh Fife St. AndrewsKY16 9SS United Kingdom Department of Electrical and Computer Engineering University of Waterloo 200 University Avenue West WaterlooONN2L 3G1 Canada Photonics Initiative Advanced Science Research Centre City University of New York 85 St. Nicholas Terrace New YorkNY10027 United States

Active metamaterials are engineered structures that possess novel properties that can be changed after the point of manufacture. Their novel properties arise predominantly from their physical structure, as opposed to their chemical composition and can be changed through means such as direct energy addition into wave paths, or physically changing/morphing the structure in response to both a user or environmental input. Active metamaterials are currently of wide interest to the physics community and encompass a range of sub-domains in applied physics (e.g. photonic, microwave, acoustic, mechanical, etc.). They possess the potential to provide solutions that are more suitable to specific applications, or which allow novel properties to be produced which cannot be achieved with passive metamaterials, such as time-varying or gain enhancement effects. They have the potential to help solve some of the important current and future problems faced by the advancement of modern society, such as achieving net-zero, sustainability, healthcare and equality goals. Despite their huge potential, the added complexity of their design and operation, compared to passive metamaterials creates challenges to the advancement of the field, particularly beyond theoretical and lab -based experiments. This roadmap brings together experts in all types of active metamaterials and across a wide range of areas of applied physics. The objective is to provide an overview of the current state of the art and the associated current/future challenges, with the hope that the required advances identified create a roadmap for the future advancement and application of this field. Copyright © 2024, The Authors. All rights reserved.

关键词： Microwave acoustics

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Automatic Fault Diagnosis of Smart Water Meter Based on BP Neural Network

Automatic Fault Diagnosis of Smart Water Meter Based on BP N...

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2020国际计算机前沿大会

作者： Jing Lin Chunqiao Mi School of Computer Science and Engineering Huaihua University Key Laboratory of Wuling-Mountain Health Big Data Intelligent Processing and Application in Hunan Province Universities Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan Province

The smart water meter in water supply network can directly affect water production and usage when faults occur. The traditional method of fault detection is inefficient with time lagging, which is not helpful for modernization of water supply system. The capability of automatic fault diagnosis of smart water meter is an important means to improve the service quality of water supply. In this paper, an automatic fault diagnosis method for the smart device is proposed based on BP neural network. And it was applied on Google Tensorflow platform. Fault symptom vectors were constructed using water meter status data and were used to train the neural network model. In order to improve the learning convergence speed and fault classification effect of the network, a method of weighted symptom was also employed. Experimental results show that it has good performance with a general fault diagnosis accuracy of 98.82%.

关键词： Automaticfaultdiagnosis Smartwatermeter BPneuralnetwork Tensorflow

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Coordinating EV Charging and Dynamic CVR in a LV Network: A UK Case Study

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IFAC-PapersOnLine 2018年第10期51卷 193-198页

作者： Gharavi, Hani McLorn, Gareth Liu, Xueqin McLoone, Seán Energy Power and Intelligent Control Research Cluster School of Electronics Electrical Engineering and Computer Science Queen's University Belfast Belfast United Kingdom

The high cost associated with installing new infrastructure to meet the increasing demand in the electricity network, particularly in the context of supporting the increasing deployment of low carbon technologies, such as electric vehicles and rooftop solar PV systems, presents distribution network operators with many challenges. This paper explores the potential for coordinating Conservation Voltage Reduction (CVR) and Electric Vehicle Demand control (EVDC) on distribution networks to reduce overall energy consumption. The study is conducted using a detailed OpenDSS simulation of a low voltage network in the greater Manchester area in the UK under time-varying load conditions representative of a winter weekday. Matlab is employed as a wrapper program to run the optimization, which is performed using uses Particle Swarm Optimisation, while OpenDSS is used for power flow simulation. The results show that energy savings of 4.2% are possible for the scenario considered. © 2016

关键词： Charging (batteries) Electric automobiles Electric load flow Electric power distribution Energy conservation Energy utilization MATLAB Particle swarm optimization (PSO) Voltage control Conservation voltage reductions CVR implementation Distribution network operators Electricity networks Low carbon technologies Optimisations Particle swarm optimisation Power flow simulation

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Flight control design for a highly flexible flutter demonstrator

Flight control design for a highly flexible flutter demonstr...

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AIAA Scitech Forum, 2019

作者： Luspay, Tamás Baár, Tamás Teubl, Dániel Vanek, Bálint Ossmann, Daniel Wüstenhagen, Matthias Pusch, Manuel Kier, Thiemo Waitman, Sérgio Iannelli, Andrea Marcos, Andres Lowenberg, Mark Systems and Control Lab Institute for Computer Science and Control Kende u 13-17 Budapest Hungary DLR German Aerospace Center Institute of Robotics and Mechatronics Wessling82234 Germany Aerospace Engineering Department University of Bristol University Walk BristolBS8 1TR United Kingdom

ISBN: (数字)9781624105784

ISBN: (纸本)9781624105784

The paper presents the control design approaches for the European research project FLEXOP. The ultimate goal is to develop and apply active flutter suppression and load alleviation techniques on an unmanned flying aircraft demonstrator. Due to the flexible wing of the aircraft new challenges rise for the control design: the traditional rigid body (baseline) control loops have to be augmented with flutter control laws. In our approach, the controllers are designed based on a dynamical model, which is briefly discussed first. Details of the baseline control design, as well as the two different flutter suppression algorithms are discussed in the paper. Hardware-in-the-Loop testing of the controllers are reported before the first test flights of the aircraft. © 2019, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： controllers

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ARIMA Models for Predicting the End of COVID-19 Pandemic and the Risk of a Second Rebound

Research Square

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Research Square 2020年

作者： Malki, Zohair Atlam, El-Sayed Ewis, Ashraf Dagnew, Guesh Alzighaibi, Ahmad Reda Elmarhomy, Ghada Elhosseini, Mostafa A. Hassanien, Aboul Ella Gad, Ibrahim College of Computer Science and Engineering Taibah University Yanbu Saudi Arabia Faculty of Science Tanta University Egypt Department of Public Health and Occupational Medicine Faculty of Medicine Minia University El-Minia Egypt Department of Public Health Faculty of Health Sciences – AlQunfudah Umm AlQura University Mecca Saudi Arabia Department of Computer Science Institute of Technology Dire Dawa University Ethiopia Mansoura University Computers Engineering and Control Systems Department Faculty of Engineering Mansoura Egypt Faculty of Computers and Artificial Intelligence Cairo University Egypt

Globally, many research works are going on to study the infectious nature of COVID-19 and every day we learn something new about it through the flooding of the huge data that are accumulating hourly rather than daily which instantly opens hot research topics for artificial intelligence researchers. However, the public’s concern by now is to find answers for two questions;1) when this COVID-19 pandemic will be over? and 2) After coming to its end, will COVID-19 return again in what is known as a second rebound of the pandemic?. This research developed a predictive model that can estimate the expected period of time that the virus can possibly stopped and the risk of a second rebound of COVID-19 pandemic. Therefore, this study considered SARIMA model to predict the spread of the virus on several selected countries and is used for pandemic life cycle and end date predictions. The study can be applied to predict the same for other countries as the nature of the virus is the same everywhere. The advantages of this study are that it helps the governments in making decisions and planning now for the future, reduces anxiety and prepares the mentality of people for the next phases of the pandemic. The most striking finding to emerge from this experimental and simulation study is that the proposed algorithm show that the expected COVID-19 infections for the top countries of highest number of confirmed case will slowdown in October, 2020. Moreover, our study forecasts that there may be a second rebound of the pandemic in a year time, if the current taken precautions are eased completely. We have to consider the uncertain nature of the current COVID-19 pandemic and the growing inter-connected and complex world, what are ultimately required are the flexibility, robustness and resilience to cope up the unexpected future events and scenarios. © 2020, CC BY.

关键词： COVID-19

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Dynamic analysis of high-dimensional fractional-order gene regulation networks with time delay

Dynamic analysis of high-dimensional fractional-order gene r...

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Chinese control Conference (CCC)

作者： Zhe Zhang Can Ding Jing Zhang Feng Liu Yingjie Zhang Fanyong Cheng College of Electrical and Information Engineering Hunan University Changsha China School of Automation China University of Geosciences Wuhan China College of Computer Science and Electronic Engineering Hunan University Changsha China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fujian China

ISBN: (数字)9789881563903

ISBN: (纸本)9781728165233

This paper mainly analyzes the stability of high-dimensional fractional-order gene regulatory network systems with time delay. Based on the judgment of eigenvalues, this paper proposes sufficient information about the stability of high-dimensional fractional-order gene regulatory network systems with time delay. Conditions, and by analyzing the characteristic equations, the bifurcation conditions of the high-dimensional fractional-order gene regulatory network system with time delay are derived. Finally, the theoretical part of this paper is verified by numerical simulation.

关键词： Bifurcation Timing Stability analysis Mathematical model Delay effects Numerical stability Electronic mail

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