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Noise-tolerant LiDAR approaching the standard quantum-limited precision

光：科学与应用（英文版） 2025年第5期14卷 1387-1397页

作者： Haochen Li Kaimin Zheng Rui Ge Labao Zhang Lijian Zhang Weiji He Biao Zhang Miao Wu Ben Wang Minghao Mi Yanqiu Guan Jingrou Tan Hao Wang Qi Chen Xuecou Tu Qingyuan Zhao Xiaoqing Jia Jian Chen Lin Kang Qian Chen Peiheng Wu Research Institute of Superconductor Electronics & Key Laboratory of Optoelectronic Devices and Systems with Extreme Performances of MOE Nanjing UniversityNanjing 210023China College of Engineering and Applied Sciences Nanjing UniversityNanjing 210023China Research Institute of Superconductor Electronics & Key Laboratory of Optoelectronic Devices and Systems with Extreme Performances of MOE Nanjing UniversityNanjing 210023China College of Engineering and Applied Sciences Nanjing UniversityNanjing 210023China Research Institute of Superconductor Electronics & Key Laboratory of Optoelectronic Devices and Systems with Extreme Performances of MOE Nanjing UniversityNanjing 210023China Hefei National Laboratory Hefei 230088China Jiangsu Key Laboratory of Spectral Imaging and Intelligence Sense Nanjing University of Science and TechnologyNanjing 210094China

Quantum-inspired imaging techniques have been proven to be effective for LiDAR with the advances of single photon detectors and computational ***,due to the disturbance of background noise and the varies of signal in outdoor environment,the performance of LiDAR is still far from its ultimate limit set by the quantum fluctuations of coherent probe *** this work,we propose and demonstrate a LiDAR from the detection perspective for approaching the standard quantum-limited *** photon numbers of echo signals are recorded by a photon-number-resolving detector and applied to overcome heavy background noise through an active photon number filter in the *** can approach the standard quantum limit in intensity estimation in a wide photon-flux range,and achieve a Fisher information of only 0.04 dB less than the quantum Fisher information when the mean signal photon number is ***,a noise-free target reconstruction and imaging is demonstrated in the daytime by the proposed *** also performs better in reflectivity resolution when taking only 1/1000 of the measurements based on on/off *** work provides a fundamental strategy for constructing a LiDAR to quickly extract targets and identify materials in complex environments,which is important for intelligent agents such as autonomous vehicles.

关键词： precision standard lidar approaching noise-tolerant quantum-limited

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A Li_(3)Bi/LiF interfacial layer enabling highly stable lithium metal anode

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Rare Metals 2023年第12期42卷 4081-4090页

作者： Lei Tan Peng Chen Qiao-Yun Chen Xing Huang Kang-Yu Zou Yan-Mei Nie Ling-Jun Li Changsha University of Science and Technology Changsha 410114China Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province College of Physics and Optoelectronic EngineeringShenzhen UniversityShenzhen 518060China

Lithium metal anode is considered the alternative to graphite anode due to its ultra-high theoretical capacity of 3860 mAh·g^(-1).However,serious Li dendrite growth and drastic electrolyte side reactions restrain the commercial application of Li metal *** this work,a Li_(3)Bi/LiF interfacial layer is constructed on the surface of the Li metal anode by a spontaneous substitution *** composite interfacial layer possesses excellent ionic conductivity,high mechanical strength,and great electrolyte wettability,which ensures fast Li-ion transfer and uniform Li deposition of the Li_(3)Bi/LiF@Li ***,the Li_3Bi/LiF@Li symmetric cell provides a cycle life of more than 400 h with only 73 mV voltage polarization at 10 mA·cm^(-2).By pairing with commercial NCM622 cathode,the Li_(3)Bi/LiF@Li full cell exhibits a long cycle at a rate of 2 C.

关键词： Lithium metal anode Li_(3)Bi LiF interfacial layer Dendrite-free High current density

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Bridging Sentence and Document Contexts: A PEFT-Enhanced Framework for Document-Level Neural Machine Translation 4

Bridging Sentence and Document Contexts: A PEFT-Enhanced Fra...

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4th International Conference on Artificial Intelligence, Robotics, and Communication, ICAIRC 2024

作者： Liu, Chunjiao Guo, Junjun Kunming University of Science and Technology Yunnan Key Laboratory of Artificial Intelligence Faculty of Information Engineering and Automation Kunming China

ISBN: (纸本)9798331531225

Document-level neural machine translation (DNMT) faces challenges in integrating context and maintaining semantic consistency. This paper proposes a coarse-to-fine semantic transfer approach that captures both fine-grained and coarse-grained document-level context. By employing a two-stage training strategy with Adapter-enhanced modules, the method ensures effective semantic adaptation from sentence to document levels. Experiments on three datasets demonstrate significant improvements in s-BLEU and d-BLEU metrics, outperforming existing approaches. © 2024 IEEE.

关键词： Neural machine translation

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Self-healable gels in electrochemical energy storage devices

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Nano Research 2024年第4期17卷 3302-3323页

作者： Yang Li PeiPei Ding Yuzhe Gu Sheng Qian Yuncong Pang Lele Wang Jiayang Feng Baoguang Liu Qi Wan Ping Li Zhiwei Liu College of Electronic and Optical Engineering&College of Flexible Electronics(Future Technology) Nanjing University of Posts&Telecommunications(NJUPT)Nanjing 210023China State Key Laboratory of Organic Electronics and Information Displays&Jiangsu Key Laboratory for Biosensors Institute of Advanced Materials(IAM)Nanjing University of Posts and Telecommunications(NJUPT)Nanjing 210023China College of Materials Science&Engineering Beijing University of TechnologyBeijing 100124China Beijing Advanced Innovation Center for Materials Genome Engineering Institute for Advanced Materials and TechnologyUniversity of Science and Technology BeijingBeijing 100083China Pillar of Engineering Product Development Singapore University of Technology and DesignSingapore 487372Singapore School of Energy and Environmental Engineering University of Science and Technology BeijingBeijing 100083China

In the green energy and carbon-neutral technology,electrochemical energy storage devices have received continuously increasing attention ***,due to the unavoidable volume expansion/shrinkage of key materials or irreversible mechanical damages during application,the stability of energy storage and delivery as well as the lifetime of these devices are severely shortened,leading to serious performance degradation or even safety ***,the utilization of self-healable gels into electrochemical energy storage devices,such as electrodes,binders,and electrolytes,is proven as an effective method to realize long-term stable operation of these devices via the self-repairing of mechanical and electrochemical ***,this review first summarizes the feature and fabrication of different gels,paying special attention to hydrogels,organohydrogels,and ***,basic concepts and figure of merit of self-healable gels are analyzed with a detailed discussion at the healing mechanisms,from reversible dynamic bonds to physical molecular diffusion,and to external healing *** we introduce all the important parts of electrochemical energy storage devices,which could be replaced by healable gels to enhance the durability,including electrodes,binders,and ***,the critical challenges and future perspectives regarding the future development of healable gels based high-performance electrochemical energy storage devices or electronics are provided.

关键词： self-healable gels healing mechanisms electrodes binders gel electrolytes

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Structure deformation of Ni-Fe-Se enables efficient oxygen evolution via RE atoms doping

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Rare Metals 2025年第1期44卷 336-348页

作者： Hong-Rui Zhao Cheng-Zong Yuan Cong-Hui Li Wen-Kai Zhao Fu-Ling Wu Lei Xin Hong Yin Shu-Feng Ye Xiao-Meng Zhang Yun-Fa Chen Jiangxi Province Research Institute of Rare Earths Ganjiang Innovation AcademyChinese Academy of SciencesGanzhou341119China School of Rare Earths University of Science and Technology of ChinaHefei230026China Key Laboratory of Hunan Province for Advanced Carbon-Based Functional Materials School of Chemistry and Chemical EngineeringHunan Institute of Science and TechnologyYueyang414006China State Key Laboratory of Multiphase Complex Systems Institute of Process EngineeringChinese Academy of SciencesBeijing100190China

The development of cost-effective and highly stable electrocatalysts for oxygen evolution reactions holds paramount importance in practical hydrogen ***,we present a novel self-supported electrode comprising Ce-doped Ni-Fe-Se nanosheets grown on carbon cloth(Ni-Fe-Ce-Se/CC).This electrode was synthesized through a selenylation process,utilizing Ni-Fe-Ce-layered double hydroxide/carbon cloth(Ni-Fe-Ce LDH/CC)as the ***,Ni-Fe-Ce-Se/CC electrode demonstrates remarkable performance,requiring a low overpotential of 300 mV to attain a current density of 100 mA·cm^(-2)under harsh alkaline ***,the electrode exhibits exceptional stability during continuous operation for 100 *** into the underlying mechanisms was gained through a combination of experimental results and density functional theory *** findings reveal that Ce doping induces crystal structure deformation in Ni-Fe-Se and enhances electron enrichment around Ni *** structural modification optimizes the adsorption energy of oxygen-based intermediates on the Ni-Fe-Se *** work offers a valuable strategy for regulating the electron transfer and adsorption capabilities of transition metal selenide electrocatalysts through RE atoms doping,opening new avenues for enhanced electrocatalytic performance.

关键词： Ce doping Structure deformation Ni-Fe-Se Electron transfer Oxygen evolution

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Emerging hierarchical mesoporous materials of covalent organic frameworks

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science China Chemistry 2024年第9期67卷 2796-2802页

作者： Lingyan Huang Wenda Li Hongyi Zhang Shanzhe Ke Hao Chen Jianwei Fu Chengbin Jing Jiangong Cheng Shaohua Liu State Key Laboratory of Precision Spectroscopy/Engineering Research Center of Nanophotonics&Advanced Instrument(Ministry of Education) School of Physics and Electronic ScienceEast China Normal UniversityShanghai 200241China School of Materials Science and Engineering Zhengzhou UniversityZhengzhou 450052China State Key Lab of Transducer Technology Shanghai Institute of Microsystem and Information TechnologyChinese Academy of SciencesShanghai 200050China

Benefiting from abundant exposed active sites,minimized diffusion resistance of guest molecules,facilitated mass transfer process and enhanced storage capacity,covalent organic frameworks(COFs)have gained widespread scientific attention[1–4].Further construction of mesopores regarding pore engineering(pore size,pore geometry,pore volume,and framework compositions)in COFs can improve mass transport,accessibility as well as size-selectivity of the special guest moieties,thus exhibiting potential in catalysis,energy storage and separation and so on[5,6].

关键词： gained catalysis separation

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A novel deep domain-adversarial method based on DRN-DATL for rolling bearing 43

A novel deep domain-adversarial method based on DRN-DATL for...

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43rd Chinese Control Conference, CCC 2024

作者： Li, Zhuorui Wang, Xiaodong Ma, Bao Kunming University of Science and Technology Faculty of Information Engineering and Automation Kunming650500 China Yunnan University Yunnan Key Laboratory of Intelligent Systems and Computing Kunming650500 China

ISBN: (纸本)9789887581581

In recent years, a variety of rolling bearing fault diagnosis methods based on deep learning has become an emerging research orientation. However, there is still a gap between the existing diagnostic model and the practical application, i.e., 1) due to the variability of working conditions, the domain shift problem between source domain and the target domain have led to the obvious degradation of the diagnostic performance. 2) It is time-consuming and expensive to label a mass of monitoring data in practical situation. To address this problem, a domain-adversarial transfer learning method based on deep residual network (DRN-DATL) for rolling bearing fault diagnosis is proposed. Firstly, DRN is designed to extract features from raw vibration signal, which can avoid gradient problems. Then, the APReLU activation function is adopted to improved diagnostic accuracy under different working conditions. Meanwhile, domain-adversarial training is utilized to minimize distribution differences between source domain and target domain. Finally, seven comparison methods are selected for systematic analysis, and the results show that the proposed method can effectively improve the overall performance of the diagnosis model, which has achieved higher classification accuracy. © 2024 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Adversarial machine learning

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Representation Alignment and Adversarial Networks for Cross-lingual Dependency Parsing

Representation Alignment and Adversarial Networks for Cross-...

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2024 Conference on Empirical Methods in Natural Language Processing, EMNLP 2024

作者： Li, Ying Liu, Jianjian Yu, Zhengtao Gao, Shengxiang Huang, Yuxin Mao, Cunli Yunnan Provincial Key Laboratory of Artificial Intelligence Faculty of Information Engineering and Automation Kunming University of Science and Technology China

ISBN: (纸本)9798891761681

With the strong representational capabilities of pre-trained language models, dependency parsing in resource-rich languages has seen significant ***, the parsing accuracy drops sharply when the model is transferred to low-resource language due to distribution *** alleviate this issue, we propose a representation alignment and adversarial model to filter out useful knowledge from rich-resource language and ignore useless *** proposed model consists of two components, i.e., an alignment network in the input layer for selecting useful language-specific features and an adversarial network in the encoder layer for augmenting the language-invariant contextualized *** on the benchmark datasets show that our proposed model outperforms RoBERTa-enhanced strong baseline models by 1.37 LAS and 1.34 *** analysis shows that both alignment and adversarial networks are equally important in alleviating the distribution shifts problem and can complement each *** addition, the comparative experiments demonstrate that both the alignment and adversarial networks can substantially facilitate extracting and utilizing relevant target language features, thereby increasing the adaptation capability of our proposed model. © 2024 Association for Computational Linguistics.

关键词： Computational linguistics

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Construction of generic core loss prediction model based on APSO algorithm 7

Construction of generic core loss prediction model based on ...

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7th International Conference on Data science and information technology, DSIT 2024

作者： Fu, Xianyi Diao, Boyang Yang, Zhong Liu, Bin Zhu, Cheng National University of Defense Technology National Key Laboratory of Information Systems Engineering Changsha China National University of Defense Technology Laboratory for Big Data and Decision Changsha China

ISBN: (纸本)9798350384093

Aiming at the current problem of insufficient core loss prediction accuracy of magnetic components under complex operating conditions, this paper firstly constructs the temperature-dependent Steinmetz equation TDSE by introducing the temperature factor on the basis of the original Steinmetz equation, and further constructs the TDSEm and TDSEa models by multiplication and addition, and verifies experimentally that the temperature is more The TDSE models are further constructed by multiplication and addition. Then the TDMSE model is constructed on the basis of the TDSE model to adapt to different waveform excitations. In order to improve the applicability of the model, the iTDMSE core loss prediction model is constructed on the basis of the TDMSE model by introducing dummy variables to introduce the material and excitation waveform categories into the model, and finally the iTDMSE core loss prediction model is constructed that can span different material types and operating environment conditions. Finally, the APSO algorithm is used to find the optimal combination of variable parameters, and the experiments show that the model guarantees the high accuracy of core loss prediction on the basis of strong generalization. © 2024 IEEE.

关键词： Prediction models

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HCMHS: High-Order SNP Interactions Detection Based on Hierarchical Clustering and Multi-Task Harmony Search Algorithm

HCMHS: High-Order SNP Interactions Detection Based on Hierar...

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Tan, Kaiwen Tian, Jin Zhang, Yongbing Shu, Zhenqiu Yu, Zhengtao Kunming University of Science and Technology Faculty of Information Engineering and Automation Yunnan Key Laboratory of Artificial Intelligence Kunming China

ISBN: (纸本)9798350386226

The interaction between SNPs plays a key role in revealing the genetic mechanisms of complex diseases. However, as the order of SNP interactions increases, the number of SNP combinations increases exponentially, presenting a serious combinatorial explosion problem. Although swarm intelligence algorithms can alleviate the combinatorial explosion problem by optimizing search paths and have been widely used in SNP interaction detection, the performance of swarm intelligence algorithms is greatly affected by initialization and search direction. To mitigate these issues, we propose a high-order SNP interaction detection algorithm based on hierarchical clustering and multitask harmony search (abbreviated as HCMHS). In harmony memory initialization, considering that similar SNPs are more likely to form pathogenic combinations, hierarchical clustering is first used to cluster SNPs into different clusters, and then based on these clusters, harmony memory is initialized. In harmony search, considering the correlation between different orders of SNP interactions, the search directions for SNPs of various orders are optimized through a multi-task framework. To verify the performance of HCMHS, we carried out experiments on 58 simulated datasets and one real dataset, and HCMHS achieved the best results compared to nine advanced algorithms. The code of HCMHS is available at https://***/huoluan17-tian/HCMHS. © 2024 IEEE.

关键词： Hierarchical clustering

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