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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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A bio-inspired spider-like structure isolator for low-frequency vibration

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Applied Mathematics and Mechanics(English Edition) 2023年第8期44卷 1263-1286页

作者： Guangdong SUI Shuai HOU Xiaofan ZHANG Xiaobiao SHAN Chengwei HOU Henan SONG Weijie HOU Jianming LI State Key Laboratory of Robotics and System Harbin Institute of TechnologyHarbin 150001China School of Astronautics Harbin Institute of TechnologyHarbin 150001China Yangtze River Delta HIT Robot Technology Research Institute Wuhu 241000Anhui ProvinceChina Tianjin Key Laboratory of Microgravity and Hypogravity Environment Simulation Technology Tianjin 300301China

This paper proposes a quasi-zero stiffness(QZS)isolator composed of a curved beam(as spider foot)and a linear spring(as spider muscle)inspired by the precise capturing ability of spiders in vibrating *** curved beam is simplified as an inclined horizontal spring,and a static analysis is carried out to explore the effects of different structural parameters on the stiffness performance of the QZS *** finite element simulation analysis verifies that the QZS isolator can significantly reduce the first-order natural frequency under the load in the QZS *** harmonic balance method(HBM)is used to explore the effects of the excitation amplitude,damping ratio,and stiffness coefficient on the system’s amplitude-frequency response and transmissibility performance,and the accuracy of the analytical results is verified by the fourth-order Runge-Kutta integral method(RK-4).The experimental data of the QZS isolator prototype are fitted to a ninth-degree polynomial,and the RK-4 can theoretically predict the experimental *** experimental results show that the QZS isolator has a lower initial isolation frequency and a wider isolation frequency bandwidth than the equivalent linear *** frequency sweep test of prototypes with different harmonic excitation amplitudes shows that the initial isolation frequency of the QZS isolator is 3 Hz,and it can isolate 90%of the excitation signal at 7 *** proposed biomimetic spider-like QZS isolator has high application prospects and can provide a reference for optimizing low-frequency or ultra-low-frequency isolators.

关键词： bionic isolation structure curved beam nonlinear stiffness quasi-zero stiffness(QzS) low-frequency vibration isolator

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Online Queue-Aware Service Migration and Resource Allocation in Mobile Edge Computing

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IEEE Transactions on Vehicular technology 2025年第5期74卷 8063-8078页

作者： Du, An Jia, Jie Chen, Jian Wang, Xingwei Huang, Min Northeastern University School of Computer Science and Engineering The Engineering Research Center of Security Technology of Complex Network System Shenyang110819 China Northeastern University Key Laboratory of Intelligent Computing in Medical Image Ministry of Education Shenyang110819 China Northeastern University College of Information Science and Engineering State Key Laboratory of Synthetical Automation for Process Industries Shenyang110819 China

Mobile edge computing (MEC) integrated with Network Functions Virtualization (NFV) helps run a wide range of services implemented by Virtual Network Functions (VNFs) deployed at MEC networks. This emerging paradigm offers flexible edge resource management for Internet Service Providers (ISPs) and improves service satisfaction of diverse applications. However, a critical challenge lies in processing extremely unpredictable and bursty traffic flow, especially in event-trigger sensing tasks. In this paper, we study queue-aware service migration and resource allocation in an MEC network, where different devices with different arrival patterns request different network services. To this end, we first formulate a novel long-term operation cost minimization problem subject to the stability of multiple queues by adopting a simultaneous migration scheme and determining resource allocation dynamically. To address the problem efficiently, we propose an online control framework to make decisions without any prior system *** first adopt the Lyapunov optimization technique to decompose the long-term optimization problem into multiper-slot subproblems. Then, we adopt a decoupled optimization algorithm based on the coordinate descent method and augmented Lagrangian method to solve the offline mixed integer non-linear programming (MINLP) subproblems. Extensive results reveal that the proposed online optimization framework can efficiently balance queue stability and cost consumption. © 1967-2012 IEEE.

关键词： Mobile edge computing

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A Rigid-Soft Pneumatic Wrist with Fixed Rotation Axes and Active Jamming Variable Stiffness Mechanisms 16th

A Rigid-Soft Pneumatic Wrist with Fixed Rotation Axes and Ac...

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16th International Conference on intelligent Robotics and Applications, ICIRA 2023

作者： Ding, Kehan Jiang, Li Zhen, Ruichen State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin China

ISBN: (纸本)9789819964888

The wrist can greatly enhance the manipulative performance of dexterous hands. In addition, due to the flexibility of soft materials, the soft wrist has obvious advantages in environmental adaptability and safety. However, existing soft wrists often have small motion curvatures and cannot modulate stiffness. Inspired by the human wrist, we proposed a rigid-soft pneumatic wrist design with fixed axes, realizing variable stiffness through jamming mechanisms. The wrist is composed of two rotatory joints in series to achieve pronation/supination and flexion/extension motions. Each joint is driven by two opposite-mounted actuators, resulting in active bidirectional movement. The pre-stretched mounting of pneumatic actuators eliminates the stiffness torque effects. Both joints have independent jamming stiffening mechanisms controlled by air pressure and require no additional power source, which makes the stiffness control more flexible. Experimental results demonstrated that the maximum output torques of the two joints reached 1.18 Nm and 1.40 Nm, and the jamming mechanism increased the stiffness of the joints by 55.3% and 67.2% in the practical test, respectively. The proposed rigid-soft wrist provides a feasible solution for enhancing the manipulative ability of soft dexterous hands. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

关键词： Pneumatic actuators

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Shape Memory Polymer Composite Booms with Applications in Reel-Type Solar Arrays

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Chinese Journal of Mechanical Engineering 2023年第3期36卷 326-338页

作者： Hong Xiao Sijie Wu Dongdong Xie Hongwei Guo Li Ma Yuxuan Wei Rongqiang Liu State Key Laboratory of Robotics and System Harbin Institute of TechnologyHarbin 150006China Yinhe Hangtian Internet Technology Co. Ltd.Beijing 100192China China Academy of Space Technology Beijing 100098China

Solar arrays are the primary energy source for *** traditional rigid solar arrays improve power supply,the quality increases ***,it is difficult to satisfy the requirements of high-power and low-cost space *** this study,a shape-memory polymer composite(SMPC)boom was designed,fabricated,and characterized for flexible reel-type solar *** SMPC boom was fabricated from a smart material,a shape-memory polymer composite,whose mechanical properties were ***,a mathematical model of the bending stiffness of the SMPC boom was developed,and the bending and buckling behaviors of the boom were further analyzed using the ABAQUS *** SMPC boom was fabricated to demonstrate its shape memory characteristics,and the driving force of the booms with varying geometric parameters was *** also designed and manufactured a reel-type solar array based on an SMPC boom and verified its self-deployment *** results indicated that the SMPC boom can be used as a deployable unit to roll out flexible solar arrays.

关键词： Shape memory polymer composite Reel-type solar array Deployable boom Bending behavior

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Optimizing Dataset Configuration for Improving Convolutional Neural Networks Performance in Chest X-ray Image Classification 8

Optimizing Dataset Configuration for Improving Convolutional...

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8th International Conference on intelligent Computing and Signal Processing, ICSP 2023

作者： He, Zengmin Ren, Yi Wang, Honggang Harbin Institute of Technology State Key Laboratory of Robotics and System Harbin China

ISBN: (纸本)9798350302455

Chest X-ray (CXR) is essential for physicians to diagnose lung diseases in clinical medicine. With the development of computer and deep learning techniques, creating CXR datasets to train convolutional neural networks (CNNs) has become a popular research topic. However, there are still challenges in creating datasets due to class imbalance and the ratio setting of datasets. This study investigated the impact of class imbalance and the ratio of training, validation, and test sets on CNNs classification performance by optimizing the dataset configuration. This was achieved by directly modifying the ratio, applying oversampling based on the adaptive contrast enhancement (ACE) algorithm, and random undersampling to balance the dataset classes, followed by modifying the ratio again. Therefore, seven datasets were obtained, which were utilized to individually train four CNNs based on transfer learning and fine-tuning techniques. Evaluation metrics based on the confusion matrix were utilized to demonstrate the enhanced classification performance of CNNs. The results indicated that at least 17% of the accuracy of CNNs trained by the dataset with modified ratios was improved as compared with the dataset with an unreasonable initial configuration. Additionally, the overall evaluation metrics of CNNs were further improved by balancing the dataset classes and modifying the ratios. ChexNet demonstrated the best classification performance among the four CNNs, as evidenced by the area under the receiver operating characteristic (ROC) curves (AUC). Furthermore, ChexNet was trained by a class balanced dataset with a ratio of 7:2:1, resulting in the best evaluation metrics, including F1 Score, balanced accuracy, accuracy, recall, specificity, and precision, which were 97.81%, 97.78%, 97.78%, 98.73%, 96.84%, and 96.89%, respectively. Therefore, optimizing dataset configuration can effectively improve the performance of CNNs, providing empirical guidance for researchers in creating dat

关键词： Convolutional neural networks

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A Multi Target Drug Design Method Based on Target Protein Sequence and Feature Similarity

A Multi Target Drug Design Method Based on Target Protein Se...

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Liu, Haoran Lin, Xiaoli Hu, Jing Zhang, Xiaolong Wuhan University of Science and Technology Hubei Key Laboratory of Intelligent Information Processing and Real-Time Industrial System School of Computer Science and Technology Wuhan China

ISBN: (纸本)9798350386226

This paper describes a multi target drug design method based on features of the target proteins. The multi target drug which inhibit multiple proteins have prospective applications, but design is difficult. In this study, the target protein sequences are embedded to obtain target features. The features of each target are independently encoded as target latent vectors, and the features of multiple targets are jointly encoded as target similarity latent vectors. Based on the features of targets and the similarity features among the targets, multi target drugs are efficiently designed. In the experiments, the designed multi target drugs can be docked with target proteins with a proprietary molecular structure according to the requirements of different target pocket structures. The excellent fitness among the molecular structure of multi target drugs and the protein structure of multiple targets confirms the performance of the proposed method. In the molecular docking part of the experi¬ments, the binding affinity of designed multi target drugs is far better than that in the previous studies, which administrates the better performance of this work. © 2024 IEEE.

关键词： Molecular docking

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A Kinematic Decoupling Whole-body Control Method for a Mobile Humanoid Upper Body Robot

A Kinematic Decoupling Whole-body Control Method for a Mobil...

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2023 International Conference on Frontiers of Robotics and Software Engineering, FRSE 2023

作者： Ju, Fengjia Jin, Hongzhe Zhao, Jie Harbin Institute of Technology State Key Laboratory of Robotics and System Harbin China

ISBN: (纸本)9798350301113

The mobile humanoid upper body robot combines the humanoid upper body robot with the mobile platform. It has high redundancy and can complete complex tasks. However, coupling joints, including the waist joints and the mobile platform, exist in the configuration of the robot. During the task execution, the motion of the end-effectors on the dual arms are not independent, but interfere with each other through the motion of the waist and the mobile platform. Therefore, we need to decouple the waist and mobile platform from the dual arms. Based on the pseudo-inverse method of the redundant manipulators, we consider the motion of the coupling joints as a disturbance term and propose a kinematic decoupling whole-body control method. The method realizes the decoupling and cooperation of dual arms, avoids the interference of the inverse kinematics model of the dual arms, and fully releases the application potential of the high redundancy. The decoupling method allows the waist joints and the mobile platform to move randomly without affecting the task operation at the end-effectors, and to further plan their movements separately in order to smooth the whole body motion. The simulations on the mobile humanoid upper body robot verifies our method. © 2023 IEEE.

关键词： End effectors

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AMA-Net: Adaptive Masking Attention Network for Agricultural Crop Classification From UAV Images

IEEE Transactions on AgriFood Electronics

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IEEE Transactions on AgriFood Electronics 2025年第1期3卷 246-253页

作者： Wang, Xu Wang, Deyi He, Zhaoshui Lin, Zhijie Xie, Shengli Guangdong Mechanical and Electrical Polytechnic School of Electronics and Communication Guangzhou510550 China Guangdong University of Technology School of Automation Guangzhou510006 China Key Laboratory for IoT Intelligent Information Processing and System Integration of Ministry of Education Guangzhou510006 China Guangdong Provincial Key Laboratory of Intelligent Systems and Optimization Integration Guangzhou510006 China

Agriculture crop classification is helpful for agricultural production. However, it is challenging to classify crops from the agriculture image suffering from these problems: 1) Crops are often masked in complex backgrounds;2) There is high similarity between crop categories. To address these problems, an adaptive masking attention network (AMA-Net) is proposed for agriculture crop identification from natural images, where the adaptive masking (AM) module is developed to distinguish the crop from the complex background by selectively eliminating redundant information of feature maps, and the fair attention module is devised to identify similar crops between categories by modeling the fine-grained features. Experiments conducted on the benchmark show the effectiveness and superiority of the proposed AMA-Net, achieving the performance of 96.65%, 96.65%, 97.13%, and 96.72% on the accuracy, precision, recall, and F1-score, respectively, which is better than other state-of-the-art methods. © 2023 IEEE.

关键词： Crops Agriculture Accuracy Visualization Training Production Autonomous aerial vehicles Attention mechanisms Adaptive systems Support vector machines

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GCA-Net: A Global Context Aggregation Network for Effective Optical Flow 49

GCA-Net: A Global Context Aggregation Network for Effective ...

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49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023

作者： Xie, Tao Gao, Jinghan Wang, Ke Li, Ruifeng Harbin Institute of Technology State Key Laboratory of Robotics and System Harbin China

ISBN: (纸本)9798350331820

Optical flow seeks to estimate the per-pixel 2D motion between two frames by identifying corresponding pixels. Current flow estimators typically involve per-pixel feature extraction, multi-scale 4D correlation volume construction, and iterative flow field updates through a Conv-GRU module. However, the locality of convolutional features in these methods renders the calculated correlations vulnerable to different noises. In addition, the Conv-GRU module of these methods is only executed with a convolution layer, which is incapable of exploiting context clues from larger window sizes even inside the image being queried itself, thus raising it more difficult for the model to process images with challenging regions, e.g., textureless areas. To this end, we introduce GCA-Net, a global context aggregation network for credible yet effective optical flow estimation. More specifically, we propose a highly efficient multi-scale transformer (MSFormer) layer which enables the per-pixel feature to aggregate long-range information from other features, hence building more accurate 4D correlation volumes. Besides, we develop an attention-enhanced Conv-GRU block (AttGRU) that can incorporate information alongside a larger context window even within itself empowering our network to estimate optical flow in even the most challenging regions. Experimentally, we demonstrate that GCA-Net outperforms previous state-of-the-art methods by large margins on Sintel (Final) and KITTI 2015 (background and foreground) benchmarks. © 2023 IEEE.

关键词： Optical flows

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