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| 1 | Design and Experiments of a Robotic Fish Imitating Cow-Nosed Ray显示文摘The cow-nosed ray is studied as natural sample of a flapping-foil robotic fish.Body structure, motion discipline, and dynamicfoil deformation of cow-nosed ray are analyzed.Based on the analysis results, a robotic fish imitating cow-nosed ray,named Robo-ray Ⅱ, mainly composed of soft body, flexible ribs and pneumatic artificial muscles, is developed.Structure andswimming morphology of the robotic prototype are as that of a normal cow-nosed ray in nature.Key propulsion parameters ofRobo-ray Ⅱ at normal conditions, including the St Number at linear swimming, thrust coefficient at towing are studied throughexperiments.The suitable driving parameters are confirmed considering the efficiency and swimming velocity.Swimmingvelocity of 0.16 m·s-1’and thrust coefficient of 0.56 in maximum are achieved in experiments. | Yueri Cai,Shusheng Bi,Licheng Zheng Robotics Institute,Beihang University,Beijing 100191,P.R.China | 2010 | Journal of Bionic Engineering2010，7，2： | 20 |
| 2 | Generative Adversarial Network-Based Electromagnetic Signal Classification: A Semi- Supervised Learning Framework显示文摘Generative adversarial network(GAN)has achieved great success in many fields such as computer vision,speech processing,and natural language processing,because of its powerful capabilities for generating realistic samples.In this paper,we introduce GAN into the field of electromagnetic signal classification(ESC).ESC plays an important role in both military and civilian domains.However,in many specific scenarios,we can’t obtain enough labeled data,which cause failure of deep learning methods because they are easy to fall into over-fitting.Fortunately,semi-supervised learning(SSL)can leverage the large amount of unlabeled data to enhance the classification performance of classifiers,especially in scenarios with limited amount of labeled data.We present an SSL framework by incorporating GAN,which can directly process the raw in-phase and quadrature(IQ)signal data.According to the characteristics of the electromagnetic signal,we propose a weighted loss function,leading to an effective classifier to realize the end-to-end classification of the electromagnetic signal.We validate the proposed method on both public RML2016.04c dataset and real-world Aircraft Communications Addressing and Reporting System(ACARS)signal dataset.Extensive experimental results show that the proposed framework obtains a significant increase in classification accuracy compared with the state-of-the-art studies. | Huaji Zhou Licheng Jiao Shilian Zheng Lifeng Yang Weiguo Shen Xiaoniu Yang | 2020 | China Communications2020，17，10： | 8 |
| 3 | Green and Near-Infrared Dual-Mode Afterglow of Carbon Dots and Their Applications for Confidential Information Readout显示文摘Near-infrared(NIR),particularly NIR-containing dual-/multimode afterglow,is very attractive in many fields of application,but it is still a great challenge to achieve such property of materials. Herein,we report a facile method to prepare green and NIR dual-mode afterglow of carbon dots(CDs) through in situ embedding o-CDs(being prepared from o-phenylenediamine) into cyanuric acid(CA) matrix(named o-CDs@CA). Further studies reveal that the green and NIR afterglows of o-CDs@CA originate from thermal activated delayed fluorescence(TADF) and room temperature phosphorescence(RTP) of o-CDs,respectively. In addition,the formation of covalent bonds between o-CDs and CA,and the presence of multiple fixation and rigid e ects to the triplet states of o-CDs are confirmed to be critical for activating the observed dual-mode afterglow. Due to the shorter lifetime and insensitiveness to human vision of the NIR RTP of o-CDs@CA,it is completely covered by the green TADF during directly observing. The NIR RTP signal,however,can be readily captured if an optical filter(cut-o wavelength of 600 nm) being used. By utilizing these unique features,the applications of o-CDs@CA in anti-counterfeiting and information encryption have been demonstrated with great confidentiality. Finally,the as-developed method was confirmed to be applicable to many other kinds of CDs for achieving or enhancing their afterglow performances. | Yuci Wang Kai Jiang Jiaren Du Licheng Zheng Yike Li Zhongjun Li Hengwei Lin | 2021 | Nano-Micro Letters2021，13，12： | 4 |
| 4 | Enabling robust and hour-level organic long persistent luminescence from carbon dots by covalent fixation显示文摘The first carbon dot(CD)-based organic long persistent luminescence(OLPL)system exhibiting more than 1 h of duration was developed.In contrast to the established OLPL systems,herein,the reported CDs-based system(named m-CDs@CA)can be facilely and effectively fabricated using a household microwave oven,and more impressively,its LPL can be observed under ambient conditions and even in aqueous media.XRD and TEM characterizations,afterglow decay,time-resolved spectroscopy,and ESR analysis were performed,showing the successful composition of CDs and.CA,the formation of exciplexes and long-lived charged-separated states.Further studies suggest that the production of covalent bonds between CA and CDs plays pivotal roles in activating LPL and preventing its quenching from oxygen and water.To the best of our knowledge,this is a very rare example of an OLPL system that exhibits hourlevel afterglow under ambient conditions.Finally,applications of m-CDs@C.A in glow-in-the-dark paints for emergency signs and multicolored luminous pearls were preliminarily demonstrated.This work may provide new insights for the development of rare earth-free and robust OLPL materials. | Kai Jiang Yuci Wang Cunjian Lin Licheng Zheng Jiaren Du Yixi Zhuang Rongjun Xie Zhongjun Li Hengwei Lin | 2022 | Light(Science & Applications)2022，11，4： | 3 |
| 5 | A chromosome-level genome assembly reveals that a bipartite gene cluster formed via an inverted duplication controls monoterpenoid biosynthesis in Schizonepeta tenuifolia显示文摘Biosynthetic gene clusters(BGCs)are regions of a genome where genes involved in a biosynthetic pathway are in proximity.The origin and evolution of plant BGCs as well as their role in specialized metabolism remain largely unclear.In this study,we have assembled a chromosome-scale genome of Japanese catnip(Schizonepeta tenuifolia)and discovered a BGC that contains multiple copies of genes involved in four adjacent steps in the biosynthesis of p-menthane monoterpenoids.This BGC has an unprecedented bipartite structure,with mirrored biosynthetic regions separated by 260 kilobases.This bipartite BGC includes identical copies of a gene encoding an old yellow enzyme,a type of flavin-dependent reductase.In vitro assays and virus-induced gene silencing revealed that this gene encodes the missing isopiperitenone reductase.This enzyme evolved from a completely different enzyme family to isopiperitenone reductase from closely related Mentha spp.,indicating convergent evolution of this pathway step.Phylogenomic analysis revealed that this bipartite BGC has emerged uniquely in the S.tenuifolia lineage and through insertion of pathway genes into a region rich in monoterpene synthases.The cluster gained its bipartite structure via an inverted duplication.The discovered bipartite BGC for p-menthane biosynthesis in S.tenuifolia has similarities to the recently described duplicated p-menthane biosynthesis gene pairs in the Mentha longifolia genome,providing an example of the convergent evolution of gene order.This work expands our understanding of plant BGCs with respect to both form and evolution,and highlights the power of BGCs for gene discovery in plant biosynthetic pathways. | Chanchan Liu Samuel J.Smit Jingjie Dang Peina Zhou Grant T.Godden Zheng Jiang Wukun Liu Licheng Liui Wei Lin Jinao Duan Qinan Wu Benjamin R.Lichman | 2023 | Molecular Plant2023，16，3： | 2 |
| 6 | Will the Historic Southeasterly Wind over the Equatorial Pacific in March 2022 Trigger a Third-year La Niña Event?显示文摘Based on the updates of the Climate Prediction Center and International Research Institute for Climate and Society(CPC/IRI)and the China Multi-Model Ensemble(CMME)El Niño-Southern Oscillation(ENSO)Outlook issued in April 2022,La Niña is favored to continue through the boreal summer and fall,indicating a high possibility of a three-year La Niña(2020-23).It would be the first three-year La Niña since the 1998-2001 event,which is the only observed three-year La Niña event since 1980.By examining the status of air-sea fields over the tropical Pacific in March 2022,it can be seen that while the thermocline depths were near average,the southeasterly wind stress was at its strongest since 1980.Here,based on a quaternary linear regression model that includes various relevant air-sea variables over the equatorial Pacific in March,we argue that the historic southeasterly winds over the equatorial Pacific are favorable for the emergence of the third-year La Niña,and both the anomalous easterly and southerly wind stress components are important and contribute~50%of the third-year La Niña growth,respectively.Additionally,the possible global climate impacts of this event are discussed. | Xianghui FANG Fei ZHENG Kexin LI Zeng-Zhen HU Hongli REN Jie WU Xingrong CHEN Weiren LAN Yuan YUAN Licheng FENG Qifa CAI Jiang ZHU | 2023 | Advances in Atmospheric Sciences2023，40，1： | 2 |
| 7 | Provably secure and efficient identity-based signature scheme based on cubic residues 显示文摘 | Wang Zhiwei Wang Licheng Zheng Shihui | 2012 | International Journal of Network Security2012，14，1： | 1 |
| 8 | Few-shot electromagnetic signal classification:A data union augmentation method显示文摘Deep learning has been fully verified and accepted in the field of electromagnetic signal classification. However, in many specific scenarios, such as radio resource management for aircraft communications, labeled data are difficult to obtain, which makes the best deep learning methods at present seem almost powerless, because these methods need a large amount of labeled data for training. When the training dataset is small, it is highly possible to fall into overfitting, which causes performance degradation of the deep neural network. For few-shot electromagnetic signal classification, data augmentation is one of the most intuitive countermeasures. In this work, a generative adversarial network based on the data augmentation method is proposed to achieve better classification performance for electromagnetic signals. Based on the similarity principle, a screening mechanism is established to obtain high-quality generated signals. Then, a data union augmentation algorithm is designed by introducing spatiotemporally flipped shapes of the signal. To verify the effectiveness of the proposed data augmentation algorithm, experiments are conducted on the RADIOML 2016.04C dataset and real-world ACARS dataset. The experimental results show that the proposed method significantly improves the performance of few-shot electromagnetic signal classification. | Huaji ZHOU Jing BAI Yiran WANG Licheng JIAO Shilian ZHENG Weiguo SHEN Jie XU Xiaoniu YANG | 2022 | Chinese Journal of Aeronautics2022，35，9： | 1 |
| 9 | A New Fast Fuzzy Processing Method for B-Scan Image显示文摘 | Zheng Chunhong Jiao Licheng | 2001 | IEEE2001，2331，： | 1 |
| 10 | DISTRIBUTED PARAMETER NEURAL NETWORKS FOR SOLVING PARTIAL DIFFERENTIAL EQUATIONS显示文摘Novel distributed parameter neural networks are proposed for solving partial differential equations, and their dynamic performances are studied in Hilbert space. The locally connected neural networks are obtained by separating distributed parameter neural networks. Two simulations are also given. Both theoretical and computed results illustrate that the distributed parameter neural networks are effective and efficient for solving partial differential equation problems. | Feng Dazheng Bao Zheng Jiao Licheng(Electronic Engineering Institute, Xidian University, Xi’an 710071) | 1997 | Journal of Electronics(China)1997，14，2： | 1 |
| 11 | Automatic Parameters Selection for SVM Based on GA显示文摘 | Zheng Chunhong Jiao Licheng | 2004 | IEEE2004，2，： | 1 |
| 12 | A NEW METHOD FOR SOLVING MSDE BASED ON WAVELET NEURAL NETWORKS显示文摘In this paper, a new method to solve multiscale difference equation(MSDE) with the M-band wavelet neural networks is proposed. It is shown that the method has many advantages over the existing methods and enlarges the range of the solvable equations. | Shui Penglang Bao Zheng Jiao Licheng (Key Lab. for Radar Signal Processing, Xidian Univ., Xi’an 710071) | 1998 | Journal of Electronics(China)1998，15，3： | 1 |
| 13 | The chloroplast-localized protein LTA1 regulates tiller angle and yield of rice显示文摘Plant architecture strongly influences rice grain yield.We report the cloning and characterization of the LTA1 gene,which simultaneously controls tiller angle and yield of rice.LTA1 encodes a chloroplastlocalized protein with a conserved YbaB DNA-binding domain,and is highly expressed in photosynthetic tissues including leaves and leaf sheaths.Disrupting the function of LTA1 leads to large tiller angle and yield reduction of rice.LTA1 affects the gravity response by mediating the distribution of endogenous auxin,thereby regulating the tiller angle.An lta1 mutant showed abnormal chloroplast development and decreased chlorophyll content and photosynthetic rate,in turn leading to reduction of rice yield.Our findings shed light on the genetic basis of tiller angle and provide a potential gene resource for the improvement of plant architecture and rice yield. | Xiaowu Pan Yongchao Li Haiwen Zhang Wenqiang Liu Zheng Dong Licheng Liu Sanxiong Liu Xinnian Sheng Jun Min Rongfeng Huang Xiaoxiang Li | 2022 | The Crop Journal2022，10，4： | 1 |
| 14 | Support vector classifier based on principal component analysis显示文摘Support vector classifier (SVC) has the superior advantages for small sample learning problems with high dimensions, with especially better generalization ability. However there is some redundancy among the high dimensions of the original samples and the main features of the samples may be picked up first to improve the performance of SVC. A principal component analysis (PCA) is employed to reduce the feature dimensions of the original samples and the pre-selected main features efficiently, and an SVC is constructed in the selected feature space to improve the learning speed and identification rate of SVC. Furthermore, a heuristic genetic algorithm-based automatic model selection is proposed to determine the hyperparameters of SVC to evaluate the performance of the learning machines. Experiments performed on the Heart and Adult benchmark data sets demonstrate that the proposed PCA-based SVC not only reduces the test time drastically, but also improves the identify rates effectively. | Zheng Chunhong Jiao Licheng Li Yongzhao | 2008 | Journal of Systems Engineering and Electronics2008，19，1： | 1 |
| 15 | Generation of color-controllable room-temperature phosphorescence via luminescent center engineering and in-situ immobilization显示文摘Materials with controllable luminescence colors are highly desirable for numerous promising applications, however, the preparation of such materials, particularly with color-controllable room-temperature phosphorescence(RTP), remains a formidable challenge. In this work, we reported on a facile strategy to prepare color-controllable RTP materials via the pyrolysis of a mixture containing 1-(2-hydroxyethyl)-urea(H-urea) and boric acid(BA). By controlling the pyrolysis temperatures, the as-prepared materials exhibited ultralong RTP with emission colors ranging from cyan, green, to yellow. Further studies revealed that multiple luminescent centers formed from H-urea, which were in-situ embedded in the B2O3matrix(produced from BA) during the pyrolysis process. The contents of the different luminescent centers could be regulated by the pyrolysis temperatures, resulting in color-tunable RTP. Significantly, the luminescent center engineering and in-situ immobilization strategy not only provided a facile method for conveniently preparing color-controllable RTP materials, but also endowed the materials prepared at relatively lower temperatures with color-changeable RTP features under thermal stimulus. Considering their unique properties, the potential applications of the as-obtained materials for advanced anti-counterfeiting and information encryption were preliminarily demonstrated. | Licheng Zheng Kai Jiang Jiaren Du Yike Li Zhongjun Li Hengwei Lin | 2023 | Chinese Chemical Letters2023，34，7： | 0 |
| 16 | Event-triggered distributed optimization for model-free multi-agent systems显示文摘In this paper,the distributed optimization problem is investigated for a class of general nonlinear model-free multi-agent systems.The dynamical model of each agent is unknown and only the input/output data are available.A model-free adaptive control method is employed,by which the original unknown nonlinear system is equivalently converted into a dynamic linearized model.An event-triggered consensus scheme is developed to guarantee that the consensus error of the outputs of all agents is convergent.Then,by means of the distributed gradient descent method,a novel event-triggered model-free adaptive distributed optimization algorithm is put forward.Sufficient conditions are established to ensure the consensus and optimality of the addressed system.Finally,simulation results are provided to validate the effectiveness of the proposed approach. | Shanshan ZHENG Shuai LIU Licheng WANG | 2024 | Frontiers of Information Technology & Electronic Engineering2024，25，2： | 0 |
| 17 | BP neural network model for material distribution prediction based on variable amplitude anti-blocking screening DEM simulations显示文摘The material feeding changing of combine harvester is easy to cause accumulation and blockage of the vibrating screen,which seriously affects the harvest operation.In order to alleviate such accumulation and blockages on the vibrating screen surface,the guide chute rotation angle of the improved variable amplitude screening mechanism was selected as the target variable,and EDEM-RecurDyn was employed to simulate the anti-blocking process of the variable amplitude under a changing feeding quantity(0.5 kg/s abnormal,0.2 kg/s normal)of materials(rice grain and stem mixture).A BP(an error back propagation algorithm)neural network was designed and the prediction model of the material distribution was subsequently constructed on the variable screening surface under different chute angles during abnormal feeding.The results revealed a continuous decrease in the quality and time of the material blockage at the front end of the screen surface with the increasing guide chute angle.At the guide chute angle of 20°-45°and adjustment time of 3-6 s,the blocked and accumulated materials at the front-end screen surface was be moved back to Grid 6 for screening.However,overtime,the screen surface materials continued to move back under the chute angle of 40°-45°,which had a great impact on the screening performance.At the guide chute angle of 30°-35°and adjustment time of 4 s,the materials on the screen surface were evenly distributed in Grid 1-6.This was able to alleviate the accumulation and blockage of the screen surface materials.The R of the material distribution prediction model(BP neural network)on the screen surface was determined as 0.97,indicating the high reliability and accuracy of the material distribution model on the screen surface based on the BP neural network.This work provides an important reference for the variable amplitude intelligent control of screen surface material anti-blocking. | Zheng Ma Yongle Zhu Zhiping Wu Souleymane Nfamoussa Traore Du Chen Licheng Xing | 2023 | International Journal of Agricultural and Biological Engineering2023，16，4： | 0 |
| 18 | Distributed Parameter Neural Networks via Adaptive Wavelet显示文摘The paper outlines a new neural net (DPNN) for describing brain’s action based on one-dimensional cable theory. While the traditional neural network system only finding its character involving time changing (as HNN, BP etc.), the model-DPNNs (distributed parameter neural networks) are not only the transmitted neurons of time variation, but also the functions of positions by the voltage u(x. I). With the neuroscientific relevance, some bionural features like intermittent conduction and dendritic spike are fixed well by DPNNs which considered as complicated and adaptive devices contract to the functional elementary units. To find the semi-analytical representation of DPNNs, adaptive wavelets are utilized as new microlocalization tools. While maintaining all advantages of wavelet function, the adaptive wavelet offers a viable alternative learning procedure to the orthogonal least squares method (OLS), Adaptive wavelet method develops a fairly general, low-cost multiscale method for neural net optimization. | Zhuoer, Shi Licheng, Jiao Zheng, Bao | 1993 | Journal of Systems Engineering and Electronics1993，4，2： | 0 |
| 19 | In vivo imaging of the neuronal response to spinal cord injury:a narrative review显示文摘Deciphering the neuronal response to injury in the spinal cord is essential for exploring treatment strategies for spinal cord injury(SCI).However,this subject has been neglected in part because appropriate tools are lacking.Emerging in vivo imaging and labeling methods offer great potential for observing dynamic neural processes in the central nervous system in conditions of health and disease.This review first discusses in vivo imaging of the mouse spinal cord with a focus on the latest imaging techniques,and then analyzes the dynamic biological response of spinal cord sensory and motor neurons to SCI.We then summarize and compare the techniques behind these studies and clarify the advantages of in vivo imaging compared with traditional neuroscience examinations.Finally,we identify the challenges and possible solutions for spinal cord neuron imaging. | Junhao Deng Chang Sun Ying Zheng Jianpeng Gao Xiang Cui Yu Wang Licheng Zhang Peifu Tang | 2024 | Neural Regeneration Research2024，19，4： | 0 |
| 20 | Selective adsorption behavior of ion-imprinted magnetic chitosan beads for removal of Cu(Ⅱ) ions from aqueous solution显示文摘Heavy metal ion is one of the major environmental pollutants.In this study,a Cu(Ⅱ)ions imprinted magnetic chitosan beads are prepared to use chitosan as functional monomer,Cu(Ⅱ)ions as template,Fe_(3)O_(4) as magnetic core and epichlorohydrin and glutaraldehyde as crosslinker,which can be used for removal Cu(Ⅱ)ions from wastewater.The kinetic study shows that the adsorption process follows the pseudosecond-order kinetic equations.The adsorption isotherm study shows that the Langmuir isotherm equation best fits for the monolayer adsorption processes.The selective adsorption properties are performed in Cu(Ⅱ)/Zn(Ⅱ),Cu(Ⅱ)/Ni(Ⅱ),and Cu(Ⅱ)/Co(Ⅱ)binary systems.The results shows that the ⅡMCD has a high selectivity for Cu(Ⅱ)ions in binary systems.The mechanism of ⅡMCD recognition Cu(Ⅱ)ions is also discussed.The results show that the ⅡMCD adsorption Cu(Ⅱ)ions is an enthalpy controlled process.The absolute value of DH(Cu(Ⅱ))and DS(Cu(Ⅱ))is greater than DH(Zn(Ⅱ),Ni(Ⅱ),Co(Ⅱ))and DS(Zn(Ⅱ),Ni(Ⅱ),Co(Ⅱ)),respectively,this indicates that the Cu(Ⅱ)ions have a good spatial matching with imprinted holes on ⅡMCD.The FTIR and XPS also demonstrates the strongly combination of function groups on imprinted holes in the suitable space position.Finally,the ⅡMCD can be regenerated and reused for 10 times without a significantly decreasing in adsorption capacity.This information can be used for further application in the selective removal of Cu(Ⅱ)ions from industrial wastewater. | Licheng Ma Qi Zheng | 2021 | Chinese Journal of Chemical Engineering2021，34，11： | 0 |
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