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CEUR Workshop Proceedings 2022年 3091卷

作者： Kovalev, Igor Semenkin, Eugene Schwenker, Friedhelm Shaidurov, Vladimir Ganchev, Todor Škraba, Andrej Stanimirović, Predrag Kolehmainen, Mikko Kronberger, Gabriel Affenzeller, Michael Brester, Christina Ryzhikov, Ivan Kazakovtsev, Lev Sopov, Evgenii Semenkina, Maria Akhmedova, Shakhnaz Stanovov, Vladimir Krasnoyarsk Regional Science and Technology City Hall Department of Computer Science of Siberian Federal University Krasnoyarsk Russia Siberian Institute of Applied System Analysis named after A.N. Antamoshkin The Department ofsystem analysis and operations research of Reshetnev University Krasnoyarsk Russia Institute of Neural Information Processing Ulm University Ulm Germany The Institute of Computational Modeling SB RAS Krasnoyarsk Russia Technical University of Varna Varna Bulgaria University of Maribor UM Faculty of Organizational Sciences Cybernetics and Decision Support Systems Laboratory Slovenia Department of Computer Science Niš Serbia Department of Environmental and Biological Sciences Environmental Informatics University of Eastern Finland Kuopio Finland University of Applied Sciences Upper Austria Hagenberg Austria Department of Software Engineering School of Informatics Communications and Media University of Applied Sciences Upper Austria Hagenberg Austria University of Eastern Finland UEF · Department of Environmental Science Kuopio Finland The Department of Systems Analysis Reshetnev University of Science and Technology Krasnoyarsk Russia Siberian Institute of Applied System Analysis Krasnoyarsk Russia University of Applied Sciences Upper Austria and Softwarepark Hagenberg Austria Reshetnev Siberian States University of Science and Technology Siberian Institute of Applied System Analysis Krasnoyarsk Russia SibSAU · Institute of computer science and telecommunications Krasnoyarsk Russia

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The Loewner framework for nonlinear identification and reduction of Hammerstein cascaded dynamical systems

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PAMM 2021年第1期20卷

作者： Dimitrios S. Karachalios Ion Victor Gosea Athanasios C. Antoulas Max Planck Institute for Dynamics of Complex Technical Systems Data-Driven System Reduction and Identification (DRI) group Sandtorstraße 1 Magdeburg 39106 Max Planck Institute for Dynamics of Complex Technical Systems Data-Driven System Reduction and Identification (DRI) group Sandtorstraße 1 Magdeburg 39106 Rice University Houston Electrical and Computer Engineering Department 6100 Main St. Houston TX 77005 Baylor College of Medicine 1 Baylor Plaza Houston TX 77030

We present an algorithm for data-driven identification and reduction of nonlinear cascaded systems with Hammerstein structure. The proposed algorithm relies on the Loewner framework (LF) which constitutes a non-intrusive algorithm for identification and reduction of dynamical systems based on interpolation. We address the following problem: the actuator (control input) enters a static nonlinear block. Then, this processed signal is used as an input for a linear time-invariant system (LTI). Additionally, it is considered that the orders of the linear transfer function and of the static nonlinearity are not a priori known.

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Data-driven (Bilinear) identification and reduction

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PAMM 2021年第S1期20卷

Identifying dynamical systems from measured data is an important step towards accurate modeling and control. Model order reduction (MOR) constitutes a class of methods that can be used to replace large, complex models of dynamical processes with simpler, smaller models. The reduced-order models (ROMs) can be then used for further tasks such as control, design, and simulation. One typical approach for projection-based model reduction for both linear and nonlinear dynamical systems is by employing interpolation. Projection-based methods require access to the internal dynamics of the system which is not always available. The aim here is to compute ROMs without having access to the internal dynamics, by means of a realization independent method. The proposed methodology will fall into the broad category of data-driven approaches. The method under consideration, which will be referred to as the Loewner framework (LF), was originally introduced by the third author. Based on data, LF identifies state-space models in a direct way. In the original setup, the framework relies on compressing the full data set to extract dominant features and, at the same time, to eliminate the inherent redundancies. In the broader class of nonlinear control systems, the LF has been already extended to certain classes with a special structure such as quadratic or bilinear systems. The LF in combination with Volterra series-(VS) offers a non-intrusive approximation method that is capable of identifying bilinear models from input-output time-domain measurements. This method uses harmonic inputs which establish a natural way for data acquisition. The Fourier transform associates these measurements with the derived generalized frequency response functions GFRFs and the LF makes the connection with system theory. In the linear case, the LF associates the so-called S-parameters with the linear transfer function by interpolating in the frequency domain. The goal of the proposed method is to extend ide

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Continuous-time digital twin with analog memristive neural ordinary differential equation solver

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Science advances 2025年第22期11卷 eadr7571页

作者： Hegan Chen Jichang Yang Jia Chen Songqi Wang Shaocong Wang Dingchen Wang Xinyu Tian Yifei Yu Xi Chen Yinan Lin Qifan Zhu Yangu He Xiaoshan Wu Yi Li Xinyuan Zhang Ning Lin Meng Xu Xumeng Zhang Xiaojuan Qi Zhongrui Wang Han Wang Dashan Shang Qi Liu Kwang-Ting Cheng Ming Liu Department of Electrical and Electronic Engineering the University of Hong Kong Hong Kong China. School of Microelectronics Southern University of Science and Technology Shenzhen 518055 China. Center for Advanced Semiconductors and Integrated Circuits the University of Hong Kong Hong Kong China. Department of Electronic and Computer Engineering the Hong Kong University of Science and Technology Hong Kong China. School of Integrated Circuits Hubei Key Laboratory for Advanced Memories Huazhong University of Science and Technology Wuhan 430074 China. State Key Laboratory of Integrated Chips and Systems Frontier Institute of Chip and System Fudan University Shanghai 200433 China. State Key Lab of Fabrication Technologies for Integrated Circuits and Key Laboratory of Microelectronic Devices & Integrated Technology Institute of Microelectronics Chinese Academy of Sciences Beijing 100029 China. University of Chinese Academy of Sciences Beijing 100049 China.

Digital twins, which replicate real-world entities through computational models, are transforming manufacturing and automation. While recent advances in machine learning have enabled data-driven digital twin development using discrete-time data and finite-depth models on digital hardware, these approaches face significant limitations. They struggle to capture continuous-time dynamics and model complex systems, and suffer from substantial time and energy overheads due to physically separated storage and processing as well as frequent analog-digital (A/D) conversions. Here, we propose a memristive neural ordinary differential equation (ODE) solver for digital twins. Our approach is intrinsically time-continuous using infinite-depth neural networks to model complex dynamics. Fully analog memristor arrays collocate storage and computation, addressing the von Neumann bottleneck and reducing A/D conversion requirements. We experimentally validate our solver on digital twins of HP variable-resistor model and Lorenz96 dynamics, demonstrating a 166.5-fold/369.3-fold speedup and a 499.0-fold/673.9-fold improvement in energy efficiency, respectively. This work paves the way to future digital twins for Industry 4.0.

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Analysis of Harmonics Detection and their Filtration by using Active Band Pass Filter for Domestic Appliances

Analysis of Harmonics Detection and their Filtration by usin...

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IEEE International Conference on Automation Science and engineering (CASE)

作者： Ehtisham Lodhi Zeeshan Lodhi Zhu Fenghua Gang Xiong Feiyue Wang Waheed ur Rehman Tariku Sinshaw The SKL for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China Department of Electrical and Computer Engineering COMSATS University Islamabad Abbottabad Campus Pakistan Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Chinese Academy of Sciences Dongguan Guangdong China Beijing Engineering Research Center of Intellectual System and Technology Chinese Academy of Sciences Beijing China College of Mechanical Engineering and Applied Electronics Technologies Beijing University of Technology Beijing China

ISBN: (数字)9781728169040

ISBN: (纸本)9781728169057

In modern era, one of the rising power quality (PQ) concern is harmonics distortion (HD). The HD is usually produced by increase in the utilization of nonlinear user loads at domestic level. It not only spoils the PQ but also have harmful effects on electrical appliances. So, this paper presents a new approach to mitigate the HD in home appliances rapidly by utilizing the active band pass filter (ABPF). The fast Fourier transform (FFT) technique is employed for the detection of harmonics in appliances. The band pass filter dramatically affects the response time of active filter. The suggested control methodology is capable to eliminate harmonics from distorted input voltage waveform and provides a pure sinusoidal waveform. The prototype of this model is also implemented. Experimental results along with simulation show that the proposed model is quite effective in eliminating HD despite load variations and also useful to compensate the reactive power in electronic home appliances. Hence, this technique is cost effective for domestic users with high quality performance in all aspects.

关键词： Power harmonic filters Harmonic analysis Band-pass filters Harmonic distortion Home appliances

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Corrigendum to “Makerchain: A blockchain with chemical signature for self-organizing process in social manufacturing” [J. Clean. Prod. 234 (2019) 767–778]

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Journal of Cleaner Production 2022年 360卷

作者： Jiewu Leng Pingyu Jiang Kailin Xu Qiang Liu J. Leon Zhao Yiyang Bian Rui Shi Guangdong Provincial Key Laboratory of Computer Integrated Manufacturing System State Key Laboratory of Precision Electronic Manufacturing Technology and Equipment And School of Biomedical and Pharmaceutical Sciences Guangdong University of Technology Guangzhou Guangdong 510006 China Shenzhen Research Institute City University of Hong Kong Shenzhen 518057 China State Key Laboratory for Manufacturing Systems Engineering Xi'an Jiaotong University Xi'an Shaanxi 710049 China School of Information Management Nanjing University Nanjing Jiangsu 210000 China

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THz near-field imaging of extreme subwavelength metal structures

arXiv

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arXiv 2021年

作者： Chen, Xinzhong Liu, Xiao Guo, Xiangdong Chen, Shu Hu, Hai Nikulina, Elizaveta Yao, Ziheng Betchel, Hans Martin, Michael C. Carr, G. Lawrence Dai, Qing Zhuang, Songlin Hu, Qing Zhu, Yiming Hillenbrand, Rainer Liu, Mengkun You, Guanjun Department of Physics and Astronomy Stony Brook University Stony BrookNY11794 United States Shanghai Key Lab of Modern Optical Systems Terahertz Technology Innovation Research Institute Engineering Research Center of Optical Instrument and System Ministry of Education University of Shanghai for Science and Technology Shanghai200093 China Division of Nanophotonics CAS Center for Excellence in Nanoscience National Center for Nanoscience and Technology Beijing100190 China CIC nanoGUNE Donostia-San Sebastián20018 Spain CIC nanoGUNE UPV/EHU Donostia-San Sebastián20018 Spain IKERBARSQUE Basque Foundation of Science Bilbao48013 Spain Advanced Light Source Division Lawrence Berkeley National Laboratory BerkeleyCA94720 United States National Synchrotron Light Source II Brookhaven National Laboratory UptonNY11973 United States Department of Electrical Engineering and Computer Science Research Laboratory of Electronics Massachusetts Institute of Technology CambridgeMA02139 United States

Modern scattering-type scanning near-field optical microscopy (s-SNOM) has become an indispensable tool in material research. However, as the s-SNOM technique marches into the far-infrared (IR) and terahertz (THz) regimes, emerging experiments sometimes produce puzzling results. For example, "anomalies" in the near-field optical contrast have been widely reported. In this letter, we systematically investigate a series of extreme subwavelength metallic nanostructures via s-SNOM near-field imaging in the GHz to THz frequency range. We find that the near-field material contrast is greatly impacted by the lateral size of the nanostructure, while the spatial resolution is practically independent of it. The contrast is also strongly affected by the connectivity of the metallic structures to a larger metallic "ground plane". The observed effect can be largely explained by a quasi-electrostatic analysis. We also compare the THz s-SNOM results to those of the mid-IR regime, where the size-dependence becomes significant only for smaller structures. Our results reveal that the quantitative analysis of the near-field optical material contrasts in the long-wavelength regime requires a careful assessment of the size and configuration of metallic (optically conductive) structures. Copyright © 2021, The Authors. All rights reserved.

关键词： Metals

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The glycolytic reaction PGAM restrains Th17 pathogenicity and Th17-dependent autoimmunity

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Cell Reports 2025年第6期44卷

作者： Chao Wang Allon Wagner Johannes Fessler David DeTomaso Sarah Zaghouani Yulin Zhou Kerry Pierce Raymond A. Sobel Clary Clish Nir Yosef Vijay K. Kuchroo Biological Sciences Platform Sunnybrook Research Institute Toronto ON M4N 3M5 Canada Department of Immunology University of Toronto Toronto ON M5S 1A8 Canada Department of Electrical Engineering and Computer Sciences University of California Berkeley Berkeley CA 94720 USA Department of Molecular and Cell Biology University of California Berkeley Berkeley CA 94720 USA Center for Computational Biology University of California Berkeley Berkeley CA 94720 USA Division of Immunology Otto Loewi Research Center Medical University of Graz Graz Austria The Gene Lay Institute of Immunology and Inflammation Brigham and Women’s Hospital Mass General Hospital and Harvard Medical School Boston MA 02115 USA Broad Institute of MIT and Harvard Cambridge MA 02142 USA Palo Alto Veteran’s Administration Health Care System and Department of Pathology Stanford University School of Medicine Stanford CA 94305 USA Department of Systems Immunology Weizmann Institute of Science Rehovot Israel

Glucose metabolism is a critical regulator of T cell function, largely thought to support their activation and effector differentiation. Here, we investigate how individual glycolytic reactions determine the pathogenicity of T helper 17 (Th17) cells using Compass, an algorithm we previously developed for inferring metabolic states from single-cell RNA sequencing. Surprisingly, Compass predicted that the metabolic shunt between 3-phosphoglycerate (3PG) and 2-phosphoglycerate (2PG) is inversely correlated with pathogenicity in Th17 cells. Indeed, perturbation of phosphoglycerate mutase (PGAM), the enzyme catalyzing 3PG to 2PG conversion, induces a pathogenic gene expression program by suppressing a gene module associated with the least pathogenic state of Th17 cells. Finally, PGAM inhibition in Th17 cells exacerbates neuroinflammation in the adoptive transfer model of experimental autoimmune encephalomyelitis, consistently with PGAM promoting the non-pathogenic phenotype of Th17 cells. Overall, our study identifies PGAM, contrary to other glycolytic enzymes, as a negative regulator of pathogenic Th17 cell differentiation.

关键词： T helper 17 immune metabolism immunometabolism phosphoglycerate mutase PGM PGAM epigallocatechin-3-gallate EGCG glycolysis central carbon metabolism CP: Immunology CP: Metabolism

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Using nuclear observations to improve climate research and GHG emission estimates – the NuClim project

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EPJ - Nuclear Sciences & Technologies 2025年 11卷 14-14页

作者： Susana Barbosa Scott Chambers Wlodzimierz Pawlak Krzysztof Fortuniak Jussi Paatero Annette Röttger Stefan Röttger Xuemeng Chen Anca Melintescu Damien Martin Dafina Kikaj Angelina Wenger Kieran Stanley Joana Barcelos Ramos Juha Hatakka Timo Anttila Hermanni Aaltonen Nuno Dias Maria Eduarda Silva João Castro Markku Kulmala INESC TEC – Institute for Systems and Computer Engineering Technology and Science Rua Dr Roberto Frias Porto Portugal ANSTO Australian Nuclear Science and Technology Organisation New Illawarra Road Lucas Heights Australia University of Lodz Department of Meteorology and Climatology Narutowicza 88 Lodz Poland Finnish Meteorological Institute PO Box 503 FI-00101 Helsinki Finland Physikalisch-Technische Bundesanstalt (PTB) Bundesallee 100 38116 Braunschweig Germany Institute for Atmospheric and Earth System Research Faculty of Science University of Helsinki Helsinki Finland Horia Hulubei National Institute for Physics and Nuclear Engineering 30 Reactorului St. POB MG-6 RO-077125 Bucharest-Magurele Romania University of Galway Ryan Institutes School of Physics University Road H91 TK33 Galway Ireland National Physical Laboratory Teddington UK School of Chemistry University of Bristol Cantocks Closed BS81TS Bristol UK UAc University of the Azores IITAA Rua Capitão d’Ávila São Pedro PT-9700-042 Angra do Heroísmo Portugal

Project NuClim (Nuclear observations to improve Climate research and GHG emission estimates) aims to use high-quality measurements of atmospheric radon activity concentration and ambient radioactivity to advance climate science and improve radiation protection and nuclear surveillance capabilities. It is supported by new metrological capabilities developed in the EMPIR project 19ENV01 traceRadon. This work reviews the scientific objectives of project NuClim in terms of both climate science and radiological protection, and provides an overview of the NuClim field campaign and the various nuclear measurements being implemented within the scope of the project.

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An improved memetic algorithm with novel level comparison for constrained optimization 2nd

An improved memetic algorithm with novel level comparison fo...

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2nd International Conference on Intelligent and Interactive systems and Applications, IISA 2017

作者： Qu, Xinghua Zhao, Wei Feng, Xiaoyi Bai, Liang Liu, Bo School of Computer Science & Engineering Nanyang Technological University Singapore Singapore Beijing Institute of Astronautical System Engineering Beijing100076 China National Computer Network Emergency Response Technical Team/Coordination Center of China Beijing China Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China

ISBN: (纸本)9783319690957

Memetic algorithms combining with effective constraints handling techniques have been becoming the focus of concern as well as the subject of substantial research issue in decision-making in complex systems. As one of the most effective techniques for constraints handling, level comparison based method has been used to solve various constraint optimization problems. However, in most of the existing research, the constraint satisfaction level keeps constant or follows a fixed regulation during search, which may weaken the efficiency of relaxation of constraint violation. In this paper, we propose a TLBO based constrained optimization method, labeled as TLBO–LCSQP by incorporating a novel level comparison technique to effectively handle the constraints, and the sequential quadratic program (SQP) to enhance the searching performance. According to the simulation on a well-known constrained benchmark, the proposed TLBO–LCSQP could effectively enhance the constraints handling efficiency and greatly improve the searching ability. © 2018, Springer International Publishing AG.

关键词： Constraint handling

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