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Swarming magnetic photonic-crystal microrobots withon-the-fly visual pH detection and self-regulated drug delivery

InfoMat 2023年第10期5卷 64-79页

作者： Zheng Yu Luolin Li Fangzhi Mou Shimin Yu Di Zhang Manyi Yang Qing Zhao Huiru Ma Wei Luo Tianlong Li Jianguo Guan State Key Laboratory of Advanced Technology for Materials Synthesis and Processing International School of Materials Science and Engineering Wuhan University of TechnologyWuhanthe People's Republic of China State Key Laboratory of Robotics and System Harbin Institute of TechnologyHarbinthe People's Republic of China Wuhan Institute of Photochemistry and Technology Wuhanthe People's Republic of China

Swarming magnetic micro/nanorobots hold great promise for biomedical applications,but at present suffer from inferior capabilities to perceive and respond to chemical signals in local *** we demonstrate swarming magnetic photonic crystal microrobots(PC-bots)capable of sponta-neously performing on-the-fly visual pH detection and self regulated drug delivery by perceiving local pH *** magnetic PC-bots consist of pH-responsive hydrogel microspheres with encapsulated one-dimensional periodic assemblies of Fe3O4 *** programming extemnal rotating magnetic fields,they can self-organize into large swarms with much-enhanced collective velocity to actively find targets while shining bright“blinking”structural *** approaching the target with abnormal pH conditions(*** ulcerated superficial tumor lesion),the PC-bots can visualize local pH changes on the fly via pH-responsive structural colors,and realize self-regulated release of the loaded drugs by recognizing local *** work facilita tes the develop-ment of intelligent micro/nanorobots for active“motile-targeting”tumor diag-nosis and treatment.

关键词： collective behaviors drug delivery micro/nanorobots on-the-fly sensing responsivephotonic crystals

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Retrieval of high spatial resolution mountainous land surface temperature considering topographic and adjacency effects

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science China Earth sciences 2024年第11期67卷 3610-3625页

作者： Zhiwei HE Bohui TANG Zhaoliang LI Faculty of Land Resources Engineering Kunming University of Science and TechnologyKunming 650093China Key Laboratory of Plateau Remote Sensing Department of Education of Yunnan ProvinceKunming 650093China State Key Lab of Resources and Environmental Information System Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijing 100101China Key Laboratory of Agricultural Remote Sensing Ministry of Agriculture and Rural AffairsInstitute of Agricultural Resources and Regional PlanningChinese Academy of Agricultural SciencesBeijing 100081China

Land surface temperature(LST) is a key parameter reflecting the interaction between land and atmosphere. Currently,thermal infrared(TIR) quantitative remote sensing technology is the only means to obtain large-scale, high spatial resolution LST. Accurately retrieving high spatial resolution mountainous LST(MLST) plays an important role in the study of mountain climate change. The complex terrain and strong spatial heterogeneity in mountainous areas change the geometric relationship between the surface and satellite sensors, affecting the radiation received by the sensors, and rendering the assumption of planar parallelism invalid. In this study, considering the influence of complex terrain in mountainous areas on atmospheric downward radiation and the thermal radiation contribution of adjacent pixels, a mountainous TIR radiative transfer model based on the sky view factor was developed. Combining with the atmospheric radiative transfer model MODTRAN 5.2, a nonlinear generalized split-window algorithm suitable for high spatial resolution MLST retrieval was constructed and applied to Landsat-9 TIRS-2satellite TIR remote sensing data. The analysis results indicate that neglecting the topographic and adjacency effects would lead to significant discrepancies in LST retrieval, with simulated data showing LST differences of up to 2.5 K. Furthermore, due to the lack of measured MLST in the field, the MLST accuracy obtained by this retrieval method was indirectly validated using the currently recognized highest-accuracy forward 3D radiative transfer model DART. The MLST and emissivity were input into the DART model to simulate the brightness temperature at the top of the atmosphere(TOA) of Landsat-9 band 10, and compared with the brightness temperature at TOA of Landsat-9 band 10. The RMSE(Root Mean Square Error) for the two subregions was0.50 and 0.61 K, respectively, indicating that the method proposed can retrieve high-precision MLST.

关键词： Mountainous land surface temperature Topographic and adjacency effects Nonlinear generalized split-window algorithm Landsat-9 data DART model

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Broadband Optically Transparent Absorber and Multi-Band Stealth Based on Organic Metasurface

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Chinese Physics Letters 2025年第5期42卷 93-99页

作者： Chuwen Lan Yutong Gao Zehua Gao Hongye Wang Ke Bi Ming Lei Guoan Zhao School of Information and Communication Engineering Beijing Laboratory of Advanced Information NetworksBeijing Key Laboratory of Network System Architecture and ConvergenceBeijing University of Posts and TelecommunicationsBeijing 100876China State Key Laboratory of Information Photonics and Optical Communications School of ScienceBeijing University of Posts and TelecommunicationsBeijing 100876China School of Integrated Circuits Beijing University of Posts and TelecommunicationsBeijing 100876China Network Education College of Beijing University of Posts and Telecommunications Beijing 100876China

Optically transparent microwave absorbers and multi-band stealth have extensive potential applications in military defense and wireless communication fields, and thus have attracted considerable attention. So far,most related work is based on inorganic transparent conductive metasurfaces. In this paper, we proposed and experimentally demonstrated a flexible, broadband and optically transparent microwave absorber using an organic metasurface. The metasurface absorber is composed of a sandwich structure, in which electric resonances and magnetic resonances are induced resulting in broadband absorption. A spraying process was developed to prepare this metasurface absorber. Both simulations and experiment show that this metasurface has broadband microwave absorption and good optical transparency. We further found that by using a multi-layer structure, visible, radar,and infrared stealth(multi-band stealth) can be achieved simultaneously. With the advantages of excellent foldability and low cost, the proposed metasurfaces may have applications in military and wireless communication fields.

关键词： microwave absorber broadband microwave absorption organic metasurface metasurface absorber microwave absorbers inorganic transparent conductive metasurfaces military defense sandwich structure

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Modification of the RUSLE slope length factor based on a multiple flow algorithm considering vertical leakage at karst landscapes

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International Soil and Water Conservation Research 2024年第2期12卷 446-454页

作者： Teng Feng Yuemin Yue Kelin Wang Hongsong Chen Lu Zhai Xianzhao Liu Yuanqi Chen Yong Zhang School of Earth Sciences and Spatial Information Engineering Hunan University of Science and TechnologyXiangtan411201HunanChina Guangxi Key Laboratory of Karst Ecological Processes and Services Institute of Subtropical AgricultureChinese Academy of SciencesChangsha410125HunanChina Huanjiang Observation and Research Station for Karst Ecosystems Chinese Academy of SciencesHuanjiang547100GuangxiChina Hunan Provincial Key Laboratory of Geo-Information Engineering in Surveying Mapping and Remote SensingHunan University of Science and TechnologyXiangtan411201HunanChina

Heterogeneous karst surfaces exerted scaling effects whereby specific runoff decrease with increasing *** existing RUSLE-L equations are limited by the default implicit assumption that the surface-runoff intensity is constant at any slope *** objective of this study was to modify the L-equation by establishing the functional relationship between surface-runoff intensity and karst slope length,and to evaluate its predictive capability at different resolution *** grid layers were generated based on the area rate of surface karstification and considered the runoff transmission percentage at the exposed karst fractures or conduits to be *** the multiple flow direction algorithm united with the transfer grid(MFDTG),the flow accumulation of each grid cell was simulated to estimate the average surface-runoff intensity over different slope *** effectiveness of MFDTG algorithm was validated by runoff plot data in Southwestern *** simulated results in a typical peak-cluster depression basin with an area rate of surface karstification of 6.5%showed that the relationship between surface-runoff intensity and slope length was a negative power *** by the proposed modified L-equation((al_(x)^((b+1))/22.13)^(m)),the L-factor averages of the study basin ranged from 0.35 to 0.41 at 1,5,25 and 90 m resolutions *** study indicated that the modified L-equation enables an improved prediction of the much smaller L-factor and the use of any resolution DEMs on karst *** attention should be given to the variation of surface-runoff intensity with slope length when predicting L-factor on hillslopes with runoff scale effect.

关键词： RUSLE-L factor Modified equation Scale effect Runoff transmission loss Flow algorithm Transfer grid

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Prediction of NO_(x)concentration using modular long short-term memory neural network for municipal solid waste incineration

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Chinese Journal of Chemical engineering 2023年第4期56卷 46-57页

作者： Haoshan Duan Xi Meng Jian Tang Junfei Qiao Faculty of Information Technology Beijing University of TechnologyBeijing 100124China Beijing Laboratory of Smart Environmental Protection Beijing 100124China Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing 100124China Engineering Research Center of Intelligence Perception and Autonomous Control Ministry of Education Beijing 100124China

Air pollution control poses a major problem in the implementation of municipal solid waste incineration(MSWI).Accurate prediction of nitrogen oxides(NO_(x))concentration plays an important role in efficient NO_(x)emission *** this study,a modular long short-term memory(M-LSTM)network is developed to design an efficient prediction model for NO_(x)***,the fuzzy C means(FCM)algorithm is utilized to divide the task into several sub-tasks,aiming to realize the divide-and-conquer ability for complex ***,long short-term memory(LSTM)neural networks are applied to tackle corresponding sub-tasks,which can improve the prediction accuracy of the ***,a cooperative decision strategy is designed to guarantee the generalization performance during the testing or application ***,after being evaluated by a benchmark simulation,the proposed method is applied to a real MSWI *** the experimental results demonstrate the considerable prediction ability of the M-LSTM network.

关键词： Municipal solid waste incineration NO_(x)concentration prediction Modular neural network Model

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Action Recognition and Detection Based on Deep Learning: A Comprehensive Summary

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Computers, Materials & Continua 2023年第10期77卷 1-23页

作者： Yong Li Qiming Liang Bo Gan Xiaolong Cui College of Information Engineering Engineering University of PAPXi’an710086China PAP of Heilongjiang Province Heihe DetachmentHeihe164300China National Key Laboratory of Science and Technology on Electromagnetic Energy Naval University of EngineeringWuhan430033China Joint Laboratory of Counter Terrorism Command and Information Engineering Engineering University of PAPXi’an710086China

Action recognition and detection is an important research topic in computer vision,which can be divided into action recognition and action *** present,the distinction between action recognition and action detection is not clear,and the relevant reviews are not ***,this paper summarized the action recognition and detection methods and datasets based on deep learning to accurately present the research status in this ***,according to the way that temporal and spatial features are extracted from the model,the commonly used models of action recognition are divided into the two stream models,the temporal models,the spatiotemporal models and the transformer models according to the *** this paper briefly analyzes the characteristics of the four models and introduces the accuracy of various algorithms in common data ***,from the perspective of tasks to be completed,action detection is further divided into temporal action detection and spatiotemporal action detection,and commonly used datasets are *** the perspectives of the twostage method and one-stage method,various algorithms of temporal action detection are reviewed,and the various algorithms of spatiotemporal action detection are summarized in ***,the relationship between different parts of action recognition and detection is discussed,the difficulties faced by the current research are summarized in detail,and future development was prospected。

关键词： Action recognition action detection deep learning convolutional neural networks dataset

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Effect of Er_(30)Cu_(70) on microstructure and properties of sintered Nd-Fe-B by grain boundary reconstruction

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Journal of Rare Earths 2024年第2期42卷 345-353,I0004页

作者： Kai Wang Yongtao Dai Jianqiu Deng Jiang Wang Huaiying Zhou Qingrong Yao Weichao Huang Guangxi Key Laboratory of Information Materials Schoolof Materials Science and EngineeringGuilin University of Electronic TechnologyGuilin54004China China Rare Metals and Rare Earth(Guangxi)Jinyuan New Materials Co Ltd.Hezhou542603China

Usually it is generally believed that the Er element forms the Er_(2)Fe_(14)B phase,which will seriously deteriorate the magnetic ***,here we report the balance of corrosion resistance and coercivity in Nd-Fe-B sintered magnets through using simple Er_(30)Cu_(70) additive whose price is much lower than Dy and *** reasonably controlling Er_(30)Cu_(70) addition,the corrosion resistance is improved at the minimum limit of reducing the magnetic *** studying the influence mechanism of Er element,it is found that the main effect of Er elements is to replace the Nd elements at the edge of the main phase grains to form a(Er,Nd)_(2)Fe_(14)B shell with low H_(A),resulting in the reduction of magnetic *** improvement of corrosion resistance mainly comes from the more stable Cu element introduced at the grain *** the same time,the target magnets also show different advantages under different heat treatment *** findings may spur progress towards developing the lowcost permanent magnets that rival the commercial Nd-Fe-B counterpart.

关键词： Er_(30)Cu_(70)alloy Grain boundary reconstruction Magnetic properties Corrosion resistance Heat treatment Rare earths

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Towards Privacy-Aware Causal Structure Learning in Federated Setting

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IEEE Transactions on Big Data 2023年第6期9卷 1525-1535页

作者： Huang, Jianli Guo, Xianjie Yu, Kui Cao, Fuyuan Liang, Jiye Intelligent Interconnected Systems Laboratory of Anhui Province School of Computer Science and Information Engineering Hefei University of Technology Hefei230601 China Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry of Education School of Computer and Information Technology Shanxi University Taiyuan030006 China

Causal structure learning has been extensively studied and widely used in machine learning and various applications. To achieve an ideal performance, existing causal structure learning algorithms often need to centralize a large amount of data from multiple data sources. However, in the privacy-preserving setting, it is impossible to centralize data from all sources and put them together as a single dataset. To preserve data privacy, federated learning as a new learning paradigm has attached much attention in machine learning in recent years. In this paper, we study a privacy-aware causal structure learning problem in the federated setting and propose a novel federated PC (FedPC) algorithm with two new strategies for preserving data privacy without centralizing data. Specifically, we first propose a novel layer-wise aggregation strategy for a seamless adaptation of the PC algorithm into the federated learning paradigm for federated skeleton learning, then we design an effective strategy for learning consistent separation sets for federated edge orientation. The extensive experiments validate that FedPC is effective for causal structure learning in federated learning setting. © 2023 IEEE.

关键词： Big data

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‘Catalyst + X’ strategies for transition metal-catalyzed olefin-polar monomer copolymerization

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Trends in Chemistry 2023年第2期5卷 147-159页

作者： Tan, Chen Chen, Min Chen, Changle Institutes of Physical Science and Information Technology Key Laboratory of Structure and Functional Regulation of Hybrid Materials of Ministry of Education Key Laboratory of Environment-Friendly Polymeric Materials of Anhui Province Anhui University Anhui Hefei230601 China CAS Key Laboratory of Soft Matter Chemistry Department of Polymer Science and Engineering University of Science and Technology of China Hefei230026 China

Transition metal-catalyzed olefin-polar monomer copolymerization holds great potential for the synthesis of polar group-functionalized polyolefin materials. The dominant approach to developing a new catalytic system is trial-and-error, which is challenging and time-consuming due to the poisoning reactions of polar groups toward the metal center. Recently, ‘catalyst + X’ strategies based on the interactions between the catalyst and other components in the copolymerization system have emerged. Different ‘X’ factors, including the solid support(s), comonomer(s), chemical agent(s), and light, have been demonstrated to influence the catalyst reactivity toward polar comonomers, olefin-comonomer copolymerization process, copolymer microstructure, and resulting copolymer material properties. This short review summarizes selected examples of these ‘catalyst + X’ strategies and discusses future perspectives. © 2022 Elsevier Inc.

关键词： Catalysts

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OSAP‐Loss:Efficient optimization of average precision via involving samples after positive ones towards remote sensing image retrieval

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CAAI Transactions on Intelligence technology 2023年第4期8卷 1191-1212页

作者： Xin Yuan Xin Xu Xiao Wang Kai Zhang Liang Liao Zheng Wang Chia‐Wen Lin School of Computer Science and Technology Wuhan University of Science and TechnologyWuhanChina Hubei Province Key Laboratory of Intelligent Information Processing and Real‐time Industrial System Wuhan University of Science and TechnologyWuhanChina Nanyang Technological University SingaporeSingapore School of Computer Science Wuhan UniversityWuhanChina Department of Electrical Engineering Industrial Technology Research InstituteNational Tsing Hua UniversityHsinchuChina

In existing remote sensing image retrieval(RSIR)datasets,the number of images among different classes varies dramatically,which leads to a severe class imbalance *** studies propose to train the model with the ranking‐based metric(e.g.,average precision[AP]),because AP is robust to class ***,current AP‐based methods overlook an important issue:only optimising samples ranking before each positive sample,which is limited by the definition of AP and is prone to local *** achieve global optimisation of AP,a novel method,namely Optimising Samples after positive ones&AP loss(OSAP‐Loss)is proposed in this ***,a novel superior ranking function is designed to make the AP loss differentiable while providing a tighter upper ***,a novel loss called Optimising Samples after Positive ones(OSP)loss is proposed to involve all positive and negative samples ranking after each positive one and to provide a more flexible optimisation strategy for each ***,a graphics processing unit memory‐free mechanism is developed to thoroughly address the non‐decomposability of AP *** experimental results on RSIR as well as conventional image retrieval datasets show the superiority and competitive performance of OSAP‐Loss compared to the state‐of‐the‐art.

关键词： computer vision image retrieval metric learning

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