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Optical properties of stacked liquid crystal superstructures with opposite chirality [Invited]

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Chinese Optics Letters 2024年第6期22卷 158-163页

作者： Lin Zhu Yiheng Zhang Shijun Ge Peng Chen Yanqing Lu National laboratory of Solid State Microstructures Key Laboratory of Intelligent Optical Sensing and ManipulationCollege of Engineering and Applied Sciencesand Collaborative Innovation Center of Advanced MicrostructuresNanjing UniversityNanjing 210093China

Cholesteric liquid crystal (CLC) has been widely used in flat optical elements due to the Pancharatnam–Berry(PB) phase modulation. In order to achieve PB phase modulation for both circular polarizations, it is natural to come up with stacking CLCs with opposite chirality. Here, various optical properties of diverse CLC stacking structures are systematically investigated by numerical calculations. With the thickness of the CLC sublayers becoming smaller, the reflection bandgap splits into three main parts, and the rotatory dispersion gradually becomes negligible. Vector beams provide a more intuitive verification. These results provide theoretical guidance for future studies on stacked chiral anisotropic media.

关键词： cholesteric liquid crystals Pancharatnam–Berry phases chirality vector beams

Multi-sensor multispectral reconstruction framework based on projection and reconstruction

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Science China(Information Sciences) 2024年第3期67卷 246-262页

作者： Tianshuai LI Tianzhu LIU Xian LI Yanfeng GU Yukun WANG Yushi CHEN School of Electronics and Information Engineering Harbin Institute of Technology Heilongjiang Province Key laboratory of Space-Air-Ground Integrated intelligent Remote Sensing

The scarcity and low spatial resolution of hyperspectral images(HSIs) have become a major problem limiting the application of the images. In recent years, spectral reconstruction(SR) has been applied to convert multispectral images(MSIs) with abundant quantities and high spatial resolution into HSIs. With the launch of several new multispectral(MS) satellites with a short repeat period, the simultaneous acquisition of images from multiple MS sensors in the same area is gradually becoming feasible. Unfortunately, existing SR methods only consider the reconstruction of the MSIs of a single sensor without considering using MSIs from different MS sensors to obtain a better construction effect through their complementary bands. However,multi-sensor SR is characterized by two problems: inconsistency in the amplitude information of real multisensor imaging and difficulty in the extraction of the complex correlations of bands from different *** solve these problems, this paper proposes a multi-sensor SR framework based on a two-step approach in which the problems of amplitude inconsistency and band information extraction are solved using an ideal projection network and an ideal multi-sensor SR network, respectively. The effectiveness of the proposed method is verified by experiments on three datasets.

关键词： spectral reconstruction spectral superresolution hyperspectral image multispectral image neural networks multi-sensor

Converting an O-vacancy-rich oxide into a multifunctional separator modifier for long-lifespan lithium metal batteries

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Journal of Energy Chemistry 2024年第10期97卷 371-378,I0007页

作者： Juntao Si Xiaoying Li Yixuan Li Kuo Cao Yiran Zhu Chunhua Chen CAS Key laboratory of Precision and intelligent Chemistry Department of Materials Science and EngineeringUniversity of Science and Technology of ChinaHefei 230026AnhuiChina

The lithium metal anode is hailed as the desired "holy grail" for the forthcoming generation of highenergy-density batteries,given its astounding theoretical capacity and low ***,the formation and growth of dendrites seriously compromise battery life and ***,an yttriastabilized bismuth oxide(YSB) layer is fabricated on the polypropylene(PP) separator,where YSB reacts with Li anode in-situ in the cell to form a multi-component composite interlayer consisting of Li_(3)Bi,Li_(2)O,and Y_(2)O_(3).The interlayer can function not only as a redistributor to regulate Li^(+) distribution but also as an anion adsorber to increase the Li^(+) transference number from 0.37 to 0.79 for suppressing dendrite nucleation and ***,compared with the cell with a baseline separator,those with modified separators exhibit prolonged lifespan in both Li/Li symmetrical cells and Li/Cu ***,the full cells coupled with ultrahigh-loading LiFePO_(4) display an excellent cycling performance of 1700 cycles with a high capacity retention of ~80% at 1 C,exhibiting great potential for practical *** work provides a feasible and effective new strategy for separator modification towards building a much-anticipated dendrite-free Li anode and realizing long-lifespan lithium metal batteries.

关键词： Lithium metal battery Separator Dendrite-free Multifunctional interlayer Conversion-alloying reaction

Machine learning-assisted sparse observation assimilation for real-time aerodynamic field perception

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Science China(Technological Sciences) 2024年第5期67卷 1458-1469页

作者： ZHAO QingYu HUANG Jun GUO YuXin PAN YuXuan JI JingJing HUANG YongAn State Key laboratory of intelligent Manufacturing Equipment and Technology School of Mechanical Science and EngineeringHuazhong University of Science and TechnologyWuhan 430074China

Accurate aerodynamic distribution perception and real-time flight state evaluation are crucial for flight safety,e.g.,stall ***,the observations are usually sparse due to limitations in sensor mounting space and cost,and a reconstruction technology is urgently ***,a machine learning-assisted assimilation method based on sparse observations has been *** from the traditional reconstruction methods focusing on boundary condition correction,the proposed method formulates the flow field pressure distribution as a linear superposition of flow field modes,thereby forming a real-time reconstruction pattern that combines offline modal extraction using computational fluid dynamics(CFD)with real-time determination of modal weights using a neural *** this study,CFD simulations were conducted under 800different operating conditions for common modal extraction and model *** weights of these modes were determined online based on merely five observations for reconstructing the full pressure field.A pressure reconstruction with a relative error of 6.1%and a mean square error of 0.003 was achieved within the prescribed condition *** computational cost was just2 ms for each reconstruction run,significantly faster than the 20 min required by the classical reconstruction ensemble transform Kalman *** also showed that the method maintains almost the same accuracy amidst 1.5%measurement *** practical examples,shock waves and the change of lift coefficient were analyzed using the proposed method,providing remarkable evidence for the capability of the method in supporting stall *** validate the method’s effectiveness and explore its potential in real-time and accurate monitoring of an aircraft.

关键词： aerodynamic force sparse observation neural networks pressure field reconstruction

Planning method of droplet fusion scheduling based on mixedinteger programming

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Science China(Technological Sciences) 2024年第1期67卷 157-171页

作者： XIONG JiaCong CHEN JianKui WANG YiXin YIN ZhouPing LI YiQun State Key laboratory of intelligent Manufacturing Equipment and Technology School of Mechanical Science and EngineeringHuazhong University of Science and TechnologyWuhan 430074China

The emergence of new display devices,such as organic light-emitting diodes,has brought about numerous advantages,including high material utilization,low cost,and high *** devices are manufactured using inkjet printing and possess the potential to become a key technology for display ***,a challenge in achieving this is the display effect that reveals uneven brightness and darkness,which can be avoided by controlling the volume of ink solution in a pixel to within 5%.Currently,the volume difference among the nozzles of commercial printheads does not meet the requirements for volume uniformity,thus challenging the printing ***,designing a suitable printing method that allows for the fusion of different volumes of ink droplets,ultimately reducing the error of the post fusion process,is *** this study,we propose a print display droplet fusion scheduling method comprising two main ***,we use a dichotomous trust domain algorithm to obtain a feasible range of printhead docking point spacings for different nozzle and pixel panel ***,we model the printing process as a droplet fusion scheduling model based on mixed integer programming,with the optimization objective of achieving intra pixel volume uniformity via ensuring the volume uniformity of ink droplets within all *** verified this method through numerical simulations and printing experiments using 394 pixels per inch(ppi)pixel panels and successfully reduced the volume uniformity error among pixels to within 5%.

关键词： printing display droplet fusion mixed-integer programming dichotomous trust domain

Control Policy Learning Design for Vehicle Urban Positioning via BeiDou Navigation

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Journal of systems Science & Complexity 2024年第1期37卷 114-135页

作者： QIN Yahang ZHANG Chengye CHEN Ci XIE Shengli LEWIS Frank L School of Automation Guangdong University of TechnologyGuangzhou 510006China Guangdong Key laboratory of IoT Information Technology Guangzhou 510006China. Center for intelligent Batch Manufacturing Based on IoT Technology Key laboratory of intelligent Detection and The Internet of Things in Manufacturing Ministry of EducationGuangzhou 510006China Guangdong-HongKong-Macao Joint laboratory for Smart Discrete Manufacturing Guangzhou 510006China Key laboratory of intelligent Information Processing and System Integration of IoT Ministry of EducationGuangzhou 510006China. UTA Research Institute The University of Texas at ArlingtonFort WorthTX 76019USA

This paper presents a learning-based control policy design for point-to-point vehicle positioning in the urban environment via BeiDou *** navigating in urban canyons,the multipath effect is a kind of interference that causes the navigation signal to drift and thus imposes severe impacts on vehicle localization due to the reflection and diffraction of the BeiDou ***,the authors formulated the navigation control system with unknown vehicle dynamics into an optimal control-seeking problem through a linear discrete-time system,and the point-to-point localization control is modeled and handled by leveraging off-policy reinforcement learning for feedback *** proposed learning-based design guarantees optimality with prescribed performance and also stabilizes the closed-loop navigation system,without the full knowledge of the vehicle *** is seen that the proposed method can withstand the impact of the multipath effect while satisfying the prescribed convergence rate.A case study demonstrates that the proposed algorithms effectively drive the vehicle to a desired setpoint under the multipath effect introduced by actual experiments of BeiDou navigation in the urban environment.

关键词： BeiDou navigation multipath effect prescribed convergence rate reinforcement learning urban localization.

UAV-Assisted Dynamic Avatar Task Migration for Vehicular Metaverse Services: A Multi-Agent Deep Reinforcement Learning Approach

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IEEE/CAA Journal of Automatica Sinica 2024年第2期11卷 430-445页

作者： Jiawen Kang Junlong Chen Minrui Xu Zehui Xiong Yutao Jiao Luchao Han Dusit Niyato Yongju Tong Shengli Xie IEEE School of Automation Guangdong University of TechnologyGuangzhou 510006China 111 Center for intelligent Batch Manufacturing based on IoT Technology Guangzhou 510006China Key laboratory of intelligent Information Processing and System Integration of IoT Ministry of EducationGuangzhou 510006China School of Computer Science and Engineering Nanyang Technological UniversitySingaporeSingapore Pillar of Information systems Technology and Design Singapore University of Technology and DesignSingaporeSingapore College of Communication Engineering Army Engineering University of PLANanjing 210007China National Natural Science Foundation of China Beijing 100085China Key laboratory of intelligent Detection and IoT in Manufacturing Ministry of EducationGuangzhou 510006China Guangdong Key laboratory of IoT Information Technology Guangzhou 510006China

Avatars, as promising digital representations and service assistants of users in Metaverses, can enable drivers and passengers to immerse themselves in 3D virtual services and spaces of UAV-assisted vehicular Metaverses. However, avatar tasks include a multitude of human-to-avatar and avatar-to-avatar interactive applications, e.g., augmented reality navigation,which consumes intensive computing resources. It is inefficient and impractical for vehicles to process avatar tasks locally. Fortunately, migrating avatar tasks to the nearest roadside units(RSU)or unmanned aerial vehicles(UAV) for execution is a promising solution to decrease computation overhead and reduce task processing latency, while the high mobility of vehicles brings challenges for vehicles to independently perform avatar migration decisions depending on current and future vehicle status. To address these challenges, in this paper, we propose a novel avatar task migration system based on multi-agent deep reinforcement learning(MADRL) to execute immersive vehicular avatar tasks dynamically. Specifically, we first formulate the problem of avatar task migration from vehicles to RSUs/UAVs as a partially observable Markov decision process that can be solved by MADRL algorithms. We then design the multi-agent proximal policy optimization(MAPPO) approach as the MADRL algorithm for the avatar task migration problem. To overcome slow convergence resulting from the curse of dimensionality and non-stationary issues caused by shared parameters in MAPPO, we further propose a transformer-based MAPPO approach via sequential decision-making models for the efficient representation of relationships among agents. Finally, to motivate terrestrial or non-terrestrial edge servers(e.g., RSUs or UAVs) to share computation resources and ensure traceability of the sharing records, we apply smart contracts and blockchain technologies to achieve secure sharing management. Numerical results demonstrate that the proposed approach

关键词： Avatar blockchain metaverses multi-agent deep reinforcement learning transformer UAVs

L-Type Calcium Channel Modulates Low-Intensity Pulsed Ultrasound-Induced Excitation in Cultured Hippocampal Neurons

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Neuroscience Bulletin 2024年第7期40卷 921-936页

作者： Wen-Yong Fan Yi-Ming Chen Yi-Fan Wang Yu-Qi Wang Jia-Qi Hu Wen-Xu Tang Yi Feng Qian Cheng Lei Xue State Key laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science Fudan UniversityShanghai 200433China Department of Physiology and Neurobiology School of Life SciencesFudan UniversityShanghai 200438China Institute of Acoustics School of Physics Science and EngineeringTongji UniversityShanghai 200092China Key laboratory of Spine and Spinal Cord Injury Repair and Regeneration of Ministry of Education Tongji UniversityShanghai 200070China Center for Rehabilitation medicine Department of Pain ManagementZhejiang Provincial People's HospitalAffliated People's HospitalHangzhou Medical CollegeHangzhou 310014China Department of Critical Care medicine Shanghai General HospitalShanghai Jiaotong University School of MedicineShanghai 200080China Shanghai Research Institute for intelligent Autonomous systems Tongji UniversityShanghai 201210China Research Institute of intelligent Complex systems Fudan UniversityShanghai 200433China

As a noninvasive technique,ultrasound stimulation is known to modulate neuronal activity both in vitro and in *** latest explanation of this phenomenon is that the acoustic wave can activate the ion channels and further impact the electrophysiological properties of targeted ***,the underlying mechanism of low-intensity pulsed ultrasound(LIPUS)-induced neuro-modulation effects is still ***,we characterize the excitatory effects of LIPUS on spontaneous activity and the intracellular Ca^(2+)homeostasis in cultured hippocampal *** whole-cell patch clamp recording,we found that 15 min of 1-MHz LIPUS boosts the frequency of both spontaneous action potentials and spontaneous excitatory synaptic currents(sEPSCs)and also increases the amplitude of sEPSCs in hippocampal *** phenomenon lasts for>10 min after LIPUS *** with Ca^(2+)imaging,we clarified that LIPUS increases the[Ca^(2+)]cyto level by facilitating L-type Ca^(2+)channels(LTCCs).In addition,due to the[Ca^(2+)]cyto elevation by LIPUS exposure,the Ca^(2+)-dependent CaMKII-CREB pathway can be activated within 30 min to further regulate the gene transcription and protein *** work suggests that LIPUS regulates neuronal activity in a Ca^(2+)-dependent manner via *** may also explain the multi-activation effects of LIPUS beyond *** stimulation potentiates spontaneous neuronal activity by increasing Ca^(2+)influx.

关键词： Low-intensity pulsed ultrasound Neuromodulation L-type calcium channel Hippocampal neuron

A Tabletop Nano-CT Image Noise Reduction Network Based on 3-Dimensional Axial Attention Mechanism

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Computers, Materials & Continua 2024年第7期80卷 1711-1725页

作者： Huijuan Fu Linlin Zhu ChunhuiWang Xiaoqi Xi Yu Han Lei Li Yanmin Sun Bin Yan Henan Key laboratory of Imaging and intelligent Processing PLA Strategic Support Force Information Engineering UniversityZhengzhou450000China

Nano-computed tomography(Nano-CT)is an emerging,high-resolution imaging ***,due to their low-light properties,tabletop Nano-CT has to be scanned under long exposure conditions,which the scanning process is *** 3D reconstruction data,this paper proposed a lightweight 3D noise reduction method for desktop-level Nano-CT called AAD-ResNet(Axial Attention DeNoise ResNet).The network is framed by theU-net *** encoder and decoder are incorporated with the proposed 3D axial attention mechanism and residual dense *** layer of the residual dense block can directly access the features of the previous layer,which reduces the redundancy of parameters and improves the efficiency of network *** 3D axial attention mechanism enhances the correlation between 3D information in the training process and captures the long-distance *** can improve the noise reduction effect and avoid the loss of image structure *** results show that the network can effectively improve the image quality of a 0.1-s exposure scan to a level close to a 3-s exposure,significantly shortening the sample scanning time.

关键词： Deep learning tabletop Nano-CT image denoising 3D axial attention mechanism