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Advanced liquid crystal-based switchable optical devices for light protection applications:principles and strategies

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Light(science & Applications) 2023年第4期12卷 512-541页

作者： Ruicong Zhang Zhibo Zhang Jiecai Han Lei Yang Jiajun li Zicheng Song Tianyu Wang Jiaqi Zhu National Key Laboratory of Science and Technology on Advanced Composites in Special Environments Harbin Institute of TechnologyHarbin 150080China Research Center of Analysis and Measurement Harbin Institute of TechnologyHarbin 150080China School of Energy Science&Engineering Harbin Institute of TechnologyHarbin 150001China Key Laboratory of Micro-systems and Micro-structures Manufacturing Ministry of EducationHarbin 150080China

With the development of optical technologies,transparent materials that provide protection from light have received considerable attention from *** important channels for external light,windows play a vital role in the regulation of light in buildings,vehicles,and *** is a need for windows with switchable optical properties to prevent or attenuate damage or interference to the human eye and light-sensitive instruments by inappropriate optical *** this context,liquid crystals(LCs),owing to their rich responsiveness and unique optical properties,have been considered among the best candidates for advanced light protection *** this review,we provide an overview of advances in research on LC-based methods for protection against ***,we introduce the characteristics of different light sources and their protection ***,we introduce several classes of light modulation principles based on liquid crystal materials and demonstrate the feasibility of using them for light *** addition,we discuss current light protection strategies based on liquid crystal materials for different ***,we discuss the problems and shortcomings of current *** propose several suggestions for the development of liquid crystal materials in the field of light protection.

关键词： optical crystal liquid

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Developing deep learning-based large-scale organic reaction classification model via sigma-profiles

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Green Chemical engineering 2025年第2期6卷 181-192页

作者： Wenlong Wang Chenyang Xu Jian Du Lei Zhang State Key Laboratory of Fine Chemical Frontiers Science Center for Smart Materials Oriented Chemical EngineeringInstitute of Chemical Process Systems EngineeringSchool of Chemical EngineeringDalian University of TechnologyDalian116024China Department of Chemical and Biomolecular Engineering National University of SingaporeSingapore117585Singapore

Advanced technologies like deep learning have accelerated the discovery of novel chemical reactions,especially in the field of organic *** hundreds of thousands of reactions available for reference,one way to effectively leverage them is by classifying chemical reactions into different clusters based on their specific characteristics,which makes target-guided navigation in the vast chemical space *** previous attempts that apply deep learning to reaction classification tasks have made substantial progress,developing a model with good interpretability as well as high accuracy for large-scale reaction classification tasks remains an open *** this work,a deep learning-based model for a large-scale reaction classification task is first constructed by utilizing pre-trained BERT and ***,the model is trained under the open-source dataset USPTO_TPL which contains recorded reactions of up to 1000 different *** multi-classification accuracy of the model on the testing dataset is 99.382%,showing its great potential for practical ***,a reaction similarity map is presented to correlate the reactions in the USPTO_TPL dataset based on their sigmaprofile-based statistical ***,representative reactions from the testing dataset are provided to illustrate the model's effectiveness on the reaction classification task.

关键词： Reaction classification Reaction fingerprint Sigma-profiles Deep learning

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On the upper bounds of (1,0)-super solutions for the regular balanced random (k,2s)-SAT problem

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Frontiers of Computer science 2024年第4期18卷 139-146页

作者： Yongping WANG Daoyun XU Jincheng ZHOU School of Information Guizhou University of Finance and EconomicsGuiyang 550025China College of Computer Science and Technology Guizhou UniversityGuiyang 550025China School of Computer and Information Qiannan Normal University for NationalitiesDuyun 558000China Key Laboratory of Complex Systems and Intelligent Optimization of Guizhou Province Duyun 558000China

This paper explores the conditions which make a regular balancedrandom(k,2s)-CNFformula(1,O)-unsatisfiable with high *** conditions also make a random instance of the regular balanced(k-1,2(k-1)s)-SAT problem unsatisfiable with high probability,where the instance obeys a distribution which differs from the distribution obeyed by a regular balanced random(k-1,2(k-1)s)-CNF *** F be a regular balanced random(k,2s)-CNF formula where k≥3,then there exists a number so such that F is(1,O)-unsatisfiable with high probability if s>so.A numerical solution of the number so when k e(5,6,...,14)is given to conduct simulated *** simulated experiments verify the theoretical ***,the experiments also suggest that F is(1,O)-satisfiable with high probability if s is less than a certain value.

关键词： regular balanced random(k,2s)-SAT problem (1,0)-super solution upper bound

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AIR-PV: a benchmark dataset for photovoltaic panel extraction in optical remote sensing imagery

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science China(information sciences) 2023年第4期66卷 122-123页

作者： Zhiyuan YAN Peijin WANG Feng XU Xian SUN Wenhui DIAO Aerospace Information Research Institute Chinese Academy of Sciences School of Electronic Electrical and Communication Engineering University of Chinese Academy of Sciences Key Laboratory of Network Information System Technology(NIST) Aerospace Information Research Institute Chinese Academy of Sciences Key Laboratory for Information Science of Electromagnetic Waves(MoE) Fudan University

The energy crisis has been a hot topic of global *** devices, a typical new energy source, have progressed rapidly and become among the main sources of power generation in the world [1]. Most photovoltaic fields are often constructed in large areas, making it difficult to monitor photovoltaic panel situations. Combining remote sensing(RS) and deep learning [2],

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Density-matrix-formalism based scheme for polarization mode dispersion monitoring and compensation in optical fiber communication systems

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Optoelectronics Letters 2023年第12期19卷 739-743页

作者： DU Qiuping ZHANG Xia GUO Yao YANG Zhenshan ZHANG Xiaoguang School of Physics Science and Information Engineering Shandong Provincial Key Laboratory of Optical Communications Science and TechnologyLiaocheng UniversityLiaocheng 252000China State Key Laboratory of Information Photonics and Optical Communications Beijing University of Posts and TelecommunicationsBeijing 100876China

We propose a density-matrix-formalism based scheme to study polarization mode dispersion(PMD)monitoring and compensation in optical fiber communication *** to traditional monitoring and compensation schemes based on the PMD vector in the Stokes space,the scheme we proposed requires no auxiliary matrices and can be handily extended to any higher-dimensional modal space,which is advantageous in mode-division multiplexing(MDM)systems.A 28 GBaud polarization division multiplexing quadrature phase-shift keying(PDM-QPSK)coherent simulation system is built to demonstrate that our scheme can implement the monitoring and compensation of 170 ps large differential-group-delay(DGD)that far exceeds the typical DGDs in practical optical communication *** results verify the effectiveness of the density-matrix-formalism based scheme in PMD monitoring and compensation,thus pave the way for further applications of the scheme in more general MDM optical communication systems.

关键词： polarization communication fiber

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A Torsion-Bending Antagonistic Bistable Actuator Enables Untethered Crawling and Swimming of Miniature Robots

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Research 2023年第4期2023卷 609-618页

作者： Nan Hu Bo Li Ruiyu Bai Kai Xie Guimin Chen State Key Laboratory for Manufacturing Systems Engineering and Shaanxi Key Laboratory of Intelligent Robots School of Mechanical EngineeringXi’an Jiaotong UniversityXi’an 710049China School of Aerospace Science and Technology Xidian UniversityXi’an 710126China

Miniature robots show great potential in exploring narrow and confined spaces to perform various tasks,but many applications are limited by the dependence of these robots on electrical or pneumatic tethers to power supplies *** an onboard actuator that is small in size and powerful enough to carry all the components onboard is a major challenge to eliminate the need for a *** can trigger a dramatic energy release during switching between the 2 stable states,thus providing a promising way to overcome the intrinsic limitation of insufficient power of small *** this work,the antagonistic action between torsional deflection and bending deflection in a lamina emergent torsional joint is utilized to achieve bistability,yielding a buckling-free bistable *** unique configuration of this bistable design enables integrating of a single bending electroactive artificial muscle in the structure to form a compact,self-switching bistable actuator.A low-voltage ionic polymer-metal composites artificial muscle is employed,yielding a bistable actuator capable of generating an instantaneous angular velocity exceeding 300°/s by a 3.75-V *** untethered robotic demonstrations using the bistable actuator are presented,including a crawling robot(gross weight of 2.7 g,including actuator,battery,and on-board circuit)that can generate a maximum instantaneous velocity of 40 mm/s and a swimming robot equipped with a pair of origami-inspired paddles that swims *** low-voltage bistable actuator shows potential for achieving autonomous motion of various fully untethered miniature robots.

关键词： robot yielding torsional

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Residual deep fuzzy system with randomized fuzzy modules for accurate time series forecasting

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Neural Computing and Applications 2024年第17期36卷 9989-10014页

作者： Liu, Yunxia Peng, Wei Wang, Haixia Li, Chengdong Lu, Xiao College of Electrical Engineering and Automation Shandong University of Science and Technology Qingdao266590 China Shandong Key Laboratory of Intelligent Buildings Technology School of Information and Electrical Engineering Shandong Jianzhu University Jinan250101 China College of Energy Storage Technology Shandong University of Science and Technology Qingdao266590 China Engineering Training Center Shandong University of Science and Technology Qingdao266590 China

The data-driven modular deep fuzzy model has demonstrated excellent forecasting performance due to its clear architecture and powerful fuzzy inference ability. However, the fixed structure predesigned for specific types of datasets limits the further improvement of generalization ability, especially when facing high-dimensional datasets with the challenging problem of rule explosion, thereby suffering from the time-consuming training process. To overcome these limitations, a novel randomized fuzzy modules (RFMs) stacked residual deep fuzzy system (RFM-RDFS) is proposed in this study. Firstly, to obtain high-precision outputs, this paper presents a residual deep fuzzy framework by stacking RFMs layer by layer, where the modules in the current layer only learn the residual of the previous layer. Secondly, to improve the design freedom for different applications, the RFM with multiple inputs is raised, where the input variables are allocated by a sliding window along the input spaces of the layers, so the number of the parallel modules in the same layer can be flexibly adjusted. Meanwhile, in the RFM, inspired by the extreme learning machine, the centers and widths of Gaussian membership functions are randomly generated, which can greatly accelerate the training speed. Thirdly, to strengthen the approximation performance, the consequent parameters of the fuzzy rules in each RFM are learned by minimizing the loss function with the regularization terms through the ridge regression algorithm. Finally, extensive experiments on various datasets are conducted to compare the proposed RFM-RDFS with several state-of-the-art shallow and deep models. The detailed comparison results clearly show that the proposed RFM-RDFS is more flexible and compact, and has greater advantages in terms of the interpretability, generalization ability and robustness. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Forecasting

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Energy conversion due to non-ideal electric field in separatrix region of magnetotail reconnection

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Earth and Planetary Physics 2024年第5期8卷 787-796页

作者： YiNan Liu Keizo Fujimoto JianQiang Wang XiaoChuan Duan School of Space and Environment Beihang UniversityBeijing 102206China Key Laboratory of Space Environment Monitoring and Information Processing Ministry of Industry and Information TechnologyBeijing 102206China School of Automation Science and Electrical Engineering Beihang UniversityBeijing 100191China

A recent satellite observation has revealed the presence of energy conversion in the separatrix region(SR)of magnetotail reconnection,driven by perpendicular *** investigated this phenomenon by means of particle-in-cell simulations in two-dimensional(2D)and three-dimensional(3D)*** result indicates that in the 2D simulation,energy conversion in the SR is dominated by parallel components,with the main influencing factor being the parallel electric field,which is not consistent with the ***,a case that is similar to the observation is found in the 3D simulation,suggesting that the observation result may be attributed to the 3D *** findings provide a potential explanation for the satellite observation.

关键词： magnetic reconnection energy conversion PIC simulation separatrix region

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REQUIRED NUMBER OF ITERATIONS FOR SPARSE SIGNAL RECOVERY VIA ORTHOGONAL LEAST SQUARES

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Journal of Computational Mathematics 2023年第1期41卷 1-17页

作者： Haifeng Li Jing Zhang Jinming Wen Dongfang Li Henan Engineering Laboratory for Big Data Statistical Analysis and Optimal Control College of Mathematics and Information ScienceHenan Normal UniversityXinxiang 453007China College of Information Science and Technology Jinan UniversityGuangzhou 510632China School of Mathematics and Statistics Huazhong University of Science and TechnologyWuhan 430074China Hubei Key Laboratory of Engineering Modeling and Scientific Computing Huazhong University of Science and TechnologyWuhan 430074China

In countless applications,we need to reconstruct a K-sparse signal x∈R n from noisy measurements y=Φx+v,whereΦ∈R^(m×n)is a sensing matrix and v∈R m is a noise *** least squares(OLS),which selects at each step the column that results in the most significant decrease in the residual power,is one of the most popular sparse recovery *** this paper,we investigate the number of iterations required for recovering x with the OLS *** show that OLS provides a stable reconstruction of all K-sparse signals x in[2.8K]iterations provided thatΦsatisfies the restricted isometry property(RIP).Our result provides a better recovery bound and fewer number of required iterations than those proposed by Foucart in 2013.

关键词： Sparse signal recovery Orthogonal least squares(OLS) Restricted isometry property(RIP)

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Organic-2D composite material-based RRAM with high reliability for mimicking synaptic behavior

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Journal of Materiomics 2024年第2期10卷 440-447页

作者： Tangyou Sun Fantao Yu Xiaosheng Tang Haiou Li Fabi Zhang Zhimou Xu Qing Liao Zhiqiang Yu Xingpeng Liu Peihua Wangyang Hezhang Li Ying Peng Guangxi Key Laboratory of Precision Navigation Technology and Application Guilin University of Electronic TechnologyGuilin541004China College of Optoelectronic Engineering Chongqing UniversityChongqing400044China School of Optical and Electronic Information Huazhong University of Science and TechnologyWuhan430074China School of Electrical and Information Engineering Guangxi University of Science and TechnologyLiuzhou545006China Department of Precision Instrument Tsinghua UniversityBeijing100084China

The field of artificial intelligence and neural computing has been rapidly expanding due to the imple-mentation of resistive random-access memory(RRAM)based artificial ***,the low flexibility of conventional RRAM materials hinders their ability to mimic synaptic behavior *** overcome such limitation,organic-2D composites with high mechanical properties are proposed as the active layer of ***,we enhance the reliability of the device by ZrO_(2)insertion layer,resulting in stable synaptic *** Ag/PVA:h-BN/ZrO_(2)/ITO devices show stable bipolar resistive switching behavior with an ON/OFF ratio of over 5×10^(2),a~2400 cycles endurance and a long retention time(>6×10^(3)s),which are essential for the development of high-performance *** also study the possible synaptic mechanism and dynamic plasticity of the memory device,observing the transition from short-term potentiation(STP)to long-term potentiation(LTP)under the effect of continuous voltage ***,the device exhibits both long-term depression(LTD)and paired-pulse facili-tation(PPF)properties,which have significant implications for the design of organic-2D composite material RRAMs that aim to mimic biological synapses,representing promising avenues for the devel-opment of advanced neuromorphic computing systems.

关键词： Resistive random-access memory Synaptic mimicking Organic-2D composite material Neuromorphic computing

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