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Scattering exceptional point in the visible

Light(Science & Applications) 2023年第10期12卷 2228-2235页

作者： Tao He Zhanyi Zhang Jingyuan Zhu Yuzhi Shi Zhipeng Li Heng Wei Zeyong Wei Yong Li Zhanshan Wang Cheng-Wei Qiu Xinbin Cheng MOE Key Laboratory of Advanced Micro-Structured Materials Shanghai 200092China Institute of Precision Optical Engineering School of Physics Science and EngineeringTongji UniversityShanghai 200092China Shanghai Institute of Intelligent Science and Technology Tongji UniversityShanghai 200092China Shanghai Frontiers Science Center of Digital Optics Shanghai 200092China Shanghai Professional Technical Service Platform for Full-Spectrum and High-Performance Optical Thin Film Devices and Applications Shanghai 200092China Department of Electronic Science and Technology Tongji UniversityShanghai 201804China Department of Electrical and Computer Engineering National University of SingaporeSingapore 117583Singapore Institute of Acoustics School of Physics Science and EngineeringTongji UniversityShanghai 200092China

Exceptional point (EP) is a special degeneracy of non-Hermitian systems. One-dimensional transmission systems operating at EPs are widely studied and applied to chiral conversion and sensing. Lately, two-dimensional systems at EPs have been exploited for their exotic scattering features, yet so far been limited to only the non-visible waveband. Here, we report a universal paradigm for achieving a high-efficiency EP in the visible by leveraging interlayer loss to accurately control the interplay between the lossy structure and scattering lightwaves. A bilayer framework is demonstrated to reflect back the incident light from the left side ( | r_(−1) | >0.999) and absorb the incident light from the right side ( | r_(+1) | < 10^(–4)). As a proof of concept, a bilayer metasurface is demonstrated to reflect and absorb the incident light with experimental efficiencies of 88% and 85%, respectively, at 532 nm. Our results open the way for a new class of nanoscale devices and power up new opportunities for EP physics.

关键词： visible exceptional incident

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Enhancing Vehicular Emissions Monitoring: A Ga-Gru-Based Soft Sensors Approach for Hddvs

SSRN

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SSRN 2023年

作者： Yang, Luoshu Lyu, Liqun Tan, Jianwei Hao, Lijun Wang, Xin Yin, Hang Wang, Junfang Ge, Yunshan School of Mechanical Engineering Beijing Institute of Technology Beijing100081 China State Environmental Protection Key Laboratory of Vehicle Emission Control and Simulation Chinese Research Academy of Environmental Sciences Beijing100012 China National Laboratory of Automotive Performance & Emission Test

The continuous release of pollutants has posed a significant threat to both public health and the sustainability of the environment. Consequently, governments across the globe have introduced more stringent rules pertaining to vehicle emissions to address this issue. In addition, the Portable Emission Measurement System (PEMS) is now the most widely used approach for detecting NOx and PN emissions from heavy-duty vehicles on real roads. However, this technology is associated with significant requirements in terms of human labor and resources, making it both expensive and time-consuming. Hence, it is imperative to put up a novel approach for the surveillance of actual on-road emissions. Prior research has indicated the potential of employing soft sensors as an alternative to physical sensors for the purpose of CO2 monitoring. However, there exists a scarcity of scholarly investigations pertaining to the monitoring of NOx and PN. The present study presents a soft sensor based on a combination of genetic algorithm (GA) and gated recurrent unit (GRU) for the purpose of monitoring real-time emissions of nitrogen oxides (NOx) and particle number (PN) within the on-board diagnostics (OBD) system. This research addresses the existing research gap in the development of soft sensors specifically designed for NOx and PN emissions. In this study, we present evidence that the described soft sensor exhibits exceptional R2 values and outperforms other conventional models. Our findings illustrate the potential of the described soft sensor to operate by effectively eliminating outliers accurately and promptly and consistently tracking predictions over the lifespan of the vehicle. Moreover, our model exhibits a high degree of reusability in the domain of emissions prediction and possesses significant potential for addressing more stringent emission rules and emerging gas pollutant constituents in forthcoming times. © 2023, The Authors. All rights reserved.

关键词： Genetic algorithms

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Personalized Federated Learning on Heterogeneous and Long-Tailed Data via Expert Collaborative Learning

arXiv

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arXiv 2024年

作者： Lv, Fengling Shang, Xinyi Zhou, Yang Zhang, Yiqun Li, Mengke Lu, Yang Key Laboratory of Multimedia Trusted Perception and Efficient Computing Xiamen University China University College London United Kingdom A*STAR Institute of High Performance Computing Singapore School of Computer Science and Technology Guangdong University of Technology Guangzhou China Guangdong Laboratory of Artificial Intelligence and Digital Economy Shenzhen China Fujian Key Laboratory of Sensing and Computing for Smart City School of Informatics Xiamen University China

Personalized Federated Learning (PFL) aims to acquire customized models for each client without disclosing raw data by leveraging the collective knowledge of distributed clients. However, the data collected in real-world scenarios is likely to follow a long-tailed distribution. For example, in the medical domain, it is more common for the number of general health notes to be much larger than those specifically related to certain diseases. The presence of long-tailed data can significantly degrade the performance of PFL models. Additionally, due to the diverse environments in which each client operates, data heterogeneity is also a classic challenge in federated learning. In this paper, we explore the joint problem of global long-tailed distribution and data heterogeneity in PFL and propose a method called Expert Collaborative Learning (ECL) to tackle this problem. Specifically, each client has multiple experts, and each expert has a different training subset, which ensures that each class, especially the minority classes, receives sufficient training. Multiple experts collaborate synergistically to produce the final prediction output. Without special bells and whistles, the vanilla ECL outperforms other state-of-the-art PFL methods on several benchmark datasets under different degrees of data heterogeneity and long-tailed distribution. Copyright © 2024, The Authors. All rights reserved.

关键词： Federated learning

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Investigation into Rapid State of Health Estimation of Lithium-Ion Batteries in Electric Vehicles

Investigation into Rapid State of Health Estimation of Lithi...

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UNIfied Conference of International Workshop on Defence Applications of Multi-Agent Systems, DAMAS 2023, International Conference on Maintenance Engineering, IncoME-V 2023, International conference on the Efficiency and performance Engineering Network, TEPEN 2023

作者： Wang, Zuolu Zhao, Xiaoyu Li, Eric Brunskill, Henry Zhen, Dong Gu, Fengshou Ball, Andrew Centre for Efficiency and Performance Engineering University of Huddersfield HuddersfieldHD1 3DH United Kingdom School of Computing Engineering and Digital Technologies Teesside University MiddlesbroughTS1 3BX United Kingdom Peak to Peak Measurement Solutions Ltd. SheffieldS3 7HQ United Kingdom Tianjin Key Laboratory of Power Transmission and Safety Technology for New Energy Vehicles School of Mechanical Engineering Hebei University of Technology Tianjin300401 China

ISBN: (纸本)9783031494123

The state of health (SOH) is an important indicator of lithium-ion batteries in electric vehicles (EVs), and therefore accurate SOH estimation plays a fundamental role in ensuring the reliable operation and safety of EVs. Currently, a variety of methods have been developed for online/offline battery SOH estimation, while most of them present high complexity due to complex tests, modelling, and algorithm implementation. Developing a rapid and accurate SOH estimation approach based on the simple test is a research hotspot to reduce the estimation cost. This paper summarizes and reclassifies the existing estimation methods considering the estimation complexity in practical applications. First, the rapid estimation methods are categorized into electrical parameters-based estimation and material properties-based estimation. Second, the working principles and performance of the rapid estimation methods are introduced combined with the review and experimental studies. Finally, this paper compares them in view of advantages and disadvantages and suggests the future trend for further improvement when used in practice. It is believed that this investigation can provide valuable guidance for academic research and engineering applications. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Lithium-ion batteries

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Synergistic Adsorption of Extracellular and Intracellular Antibiotic Resistance Genes in Struvite Crystallization by Using Simulated Swine Wastewater

SSRN

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SSRN 2025年

作者： Zhang, Tianyi Liao, Wenqian Ye, Zhi-Long Huang, Xuewei Lia, Yanlin Cai, Jiasheng State Key Laboratory of Advanced Environmental Technology Institute of Urban Environment Chinese Academy of Sciences No. 1799 Jimei Road Fujian Xiamen City361021 China University of Chinese Academy of Sciences Beijing100049 China Fujian Key Laboratory of Digital Technology for Territorial Space Analysis and Simulation Xiamen361021 China LIWET Department of Green Chemistry and Technology Ghent University Campus Kortrijk Graaf Karel De Goedelaan 5 KortrijkB-8500 Belgium

Struvite recovery from livestock wastewater may pose risks of spreading antibiotic resistance genes (ARGs) into the environment. There are two forms of ARGs existed in the wastewater, i.e. intracellular ARGs (iARGs) and extracellular ARGs (eARGs), which are typically carried by plasmid and bacteria, respectively. To date, few works has been reported on the simultaneous migration behavior of iARGs and eARGs in struvite recovery. In this work, the plasmid DNA and Escherichia coli carrying tetracycline resistance genes were selected as the typical eARGs and iARGs, correspondingly, and the synergistic adsorptions of eARGs and iARGs in struvite crystallization were examined by using simulated wastewater. The adsorption capacities of eARGs and iARGs by pure struvite crystals were 9.20×106 - 8.38×1012 copies/g and 3.45×105 - 1.60×106 CFU/g, respectively. The co-existence of eARGs and iARGs would amplify eARGs adsorption, while excessive Mg2+ ion in the liquid would impair eARGs adsorption, compared to negligible impacts on iARGs adsorption. XPS analysis revealed that the predominant forces of adsorption were weaker forces, such as electrostatic or ionic hydration forces, which was ascribed to magnesium octahedral in the faces of struvite crystallite. Increasing pH values would lead to an ascent of iARGs adsorption coupled with a descent of eARGs adsorption, which was contributed to the shift of Mg density in faces of struvite crystallite and the protonation/deprotonation of eARGs molecules. These outcomes provide new understanding on eARGs and iARGs transport in phosphate recovery from wastewater. © 2025, The Authors. All rights reserved.

关键词： Escherichia coli

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Htem: High-Throughput Toolkit for Elasticity Modeling

SSRN

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SSRN 2025年

作者： Yang, Zhen Xian, Jiawei Xu, Yuanji Lin, De-Ye Wang, Qingchun Gao, Xingyu Tian, Fuyang Song, Haifeng Institute for Applied Physics University of Science and Technology Beijing Beijing100083 China National Key Laboratory of Computational Physics Institute of Applied Physics and Computational Mathematics Beijing100094 China CAEP Software Center for High Performance Numerical Simulation Institute of Applied Physics and Computational Mathematics Beijing100094 China

The elasticity under varying temperatures and pressures is particularly significant for understanding mechanical properties and structural phase transitions. Consequently, there is an increasing demand for tools capable of determining elasticity across wide temperature and pressure ranges, either numerically or analytically. We propose HTEM, a comprehensive toolkit that automates the workflow for input generation, elastic calculations, modeling, and visualization within an integrated framework. HTEM performs simulations with four computational modes, allowing users to balance accuracy and efficiency. It incorporates a semi-analytic model for robust, high-precision elastic modeling with finite data combinations, even using sparse elasticity at high temperatures. To validate the workflows of calculation and modeling, we perform HTEM to study the elasticity of Si across wide temperature and pressure ranges. Results show the high precision and high efficiency of HTEM. And modeling mitigates noise from constant pressure ensemble simulations. Furthermore, HTEM provides detailed visualizations of elasticity and its anisotropy as functions of temperature and pressure, providing comprehensive insights into how the intrinsic properties of materials evolve under varying conditions. © 2025, The Authors. All rights reserved.

关键词： Elasticity

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D4M: Dataset Distillation via Disentangled Diffusion Model

D4M: Dataset Distillation via Disentangled Diffusion Model

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Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Duo Su Junjie Hou Weizhi Gao Yingjie Tian Bowen Tang UCAS School of Computer Science and Technology Research Center on Fictitious Economy and Data Science CAS Key Laboratory of Big Data Mining and Knowledge Management CAS UCAS Sino-Danish College Department of Computer Science NCSU UCAS School of Economics and Management UCAS MOE Social Science Laboratory of Digital Economic Forecasts and Policy Simulation CAS Institute of Computing Technology

ISBN: (数字)9798350353006

ISBN: (纸本)9798350353013

Dataset distillation offers a lightweight synthetic dataset for fast network training with promising test accuracy. To imitate the performance of the original dataset, most approaches employ bi-level optimization and the distillation space relies on the matching architecture. Nevertheless, these approaches either suffer significant computational costs on large-scale datasets or experience performance decline on cross-architectures. We advocate for designing an economical dataset distillation framework that is independent of the matching architectures. With empirical observations, we argue that constraining the consistency of the real and synthetic image spaces will enhance the cross-architecture generalization. Motivated by this, we introduce Dataset Distillation via Disentangled Diffusion Model (D 4 M), an efficient framework for dataset distillation. Compared to architecture-dependent methods, D 4 M employs latent diffusion model to guarantee consistency and incorporates label information into category prototypes. The distilled datasets are versatile, eliminating the need for repeated generation of distinct datasets for various architectures. Through comprehensive experiments, D4M demonstrates superior performance and robust generalization, surpassing the SOTA methods across most aspects.

关键词： Training Computer vision Computational modeling Prototypes Computer architecture Diffusion models Pattern recognition

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Nonlinear Dynamics of Friction Nanogenerators with Bi-Directional Gearing

SSRN

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SSRN 2024年

作者： Mo, Shuai Wang, Zhen Liu, Wenbin Zhou, Yuansheng Zhang, Jielu Zhang, Wei State Key Laboratory of Featured Metal Materials and Life-cycle Safety for Composite Structures Guangxi University Nanning530004 China School of Mechanical Engineering Guangxi University Nanning530004 China State Key Laboratory of Precision Manufacturing for Extreme Service Performance Central South University Changsha410083 China State Key Lab of Digital Manufacturing Equipment and Technology Huazhong University of Science and Technology Wuhan430074 China Jiangsu Wanji Transmission Technology Co. Ltd. Taizhou225400 China

A nonlinear dynamics model of a bidirectional rack-driven friction nanogenerator was constructed by considering the time-varying meshing stiffness and time-varying support stiffness. The Runge-Kutta method is used to obtain the dynamic response of the system and analyse the influence of the load excitation frequency on the dynamic characteristics of the system. The influence of load excitation frequency and meshing stiffness on the mechanical energy conversion of the system is also investigated by combining the friction nanogeneration technology. The results show that the system has obvious nonlinear characteristics, and a reasonable choice of load excitation frequency and engagement stiffness can avoid the unstable interval, improve the mechanical energy conversion efficiency, and increase the power generation capacity of TENG. © 2024, The Authors. All rights reserved.

关键词： Friction

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A data-driven approach for recommending UI element layout

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Science China(Information Sciences) 2020年第9期63卷 61-63页

作者： Yonghao LONG Xiangping CHEN Yuting XIE School of Information Science and Technology National Engineering Research Center of Digital LifeSun Yat-sen University Guangdong Key Laboratory for Big Data Analysis and Simulation of Public Opinion School of Communication and Design Sun Yat-sen University

Dear editor,Smartphones and tablets with rich graphical user interfaces (GUI) are becoming increasingly popular. GUI design plays an important role in offering a smooth user experience. The complexity of the apps often depends on the user interface (UI)[1]with minor data processing or data processing delegates to the backend component.

关键词： UI development Software mining Layout recommendation Data-driven development Intelligent Software Development

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Parallel Optimization of Computational Fluid Dynamics Application code_saturne Based on Next Generation Sunway Supercomputer

Parallel Optimization of Computational Fluid Dynamics Applic...

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International Symposium on Parallel Architectures, Algorithms and Programming (PAAP)

作者： Anjun Liu Yin Liao Xihao Xu YanYan Chen Hongjun Zhong Jianming Wu Bo Kong Alexander Raikov Meng Guo Jinan Key Laboratory of High Performance Industrial Software Jinan Institute of Supercomputing Technology Jinan China Jinan Supercomputing-Zhejiang Yuansuan Industrial Simulation System Joint Laboratory Zhejiang Yuansuan Technology Co. Ltd Hangzhou China Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center (National Supercomputer Center in Jinan ) Qilu University of Technology (Shandong Academy of Sciences) Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer Science Jinan China

code_saturne is an open-source general large-scale computational fluid dynamics software independently developed by Electricite de France since 1997. Due to its high computing performance, code_saturne has been widely used in the nuclear industry, heavy fuel and biomass combustion, particle tracking and other computational fluid dynamics fields. In this work, we implemented code_saturne on the new generation Sunway supercomputer (SW26010pro) at the first time. By applying the data value-taking technology of double cache, combined with Sunway shared memory technology, we have adapted the data structure and Modular programming of code_saturne conducively to the new generation Sunway supercomputer (SW26010pro) and accelerated the software hotspots the software hotspots by 1–2 times. After optimizing and porting, this software has successfully served in the numerical simulation of the lateral flow of fuel assemblies in the nuclear industry.

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