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Synchronous Rotation-Based Knot Tying on Mini-Incisions Using Dual-Arm Nanorobot

IEEE Transactions on Biomedical engineering 2025年第6期72卷 1920-1930页

作者： Jiang, Yujie Zhong, Chengxi Qin, Chao Sun, Zhenhuan Liu, Song ShanghaiTech University School of Information Science and Technology China Shanghai Engineering Research Center of Intelligent Vision and Imaging Shanghai201210 China

Knot tying is a critical task in robotic surgery, which is considerably important for surgical success and postoperative recovery. Despite of the well-established protocols and significant progress using medical robots at macro scale, the need for automatedly tying mechanically robust knots on mini-incisions remains largely unmet, particularly with relieved suture deformation, avoided suture slippage, reduced workspace consumption, and enhanced precision and biomechanical compatibility. Here, we propose an innovative dual-arm nanorobotic system featured by stereo microscope and additional rotation degree of freedom (DOF) mounted on each arm, enabling automated, precise, and controllable knot tying on mini-incisions. With this system, a synchronous rotation-based knot tying (SRKT) trajectory is designed to mitigate undesired suture deformation, suture slippage, and minimize workspace consumption. The theoretical and simulation analysis of the topology and tension force distribution on suture validated the efficacy of SRKT trajectory. The experiments demonstrated that the dual-arm nanorobotic system with SRKT trajectory can be used for tying various knot types, using different micro-sutures, conducting on mini-incisions of different tissues, especially keeping suture slippage avoidance, minimal workspace, and robust mechanical strength of the tied knots. The proposed dual-arm nanorobotic system and SRKT trajectory render a significant potential for various practical medical applications. © 1964-2012 IEEE.

关键词： Nanorobots

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Sea Surface Height Inversion Model Based on Multimodal Deep Learning for the Fusion of Heterogeneous FY-3E GNSS-R Data

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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2025年 18卷 11979-11995页

作者： Zhang, Yun Qin, Ganyao Yang, Shuhu Han, Yanling Hong, Zhonghua Shanghai Ocean University College of Information Technology Shanghai201306 China Shanghai Ocean University Shanghai Marine Intelligent Information and Navigation Remote Sensing Engineering Technology Research Center Shanghai201306 China

Sea surface height (SSH) is of great significance in oceanography and meteorology. Traditional physical altimetry methods based on delay–Doppler mapping (DDM) are subject to errors that are difficult to correct computationally. The current deep-learning-based SSH inversion techniques primarily relying on single-modal data are unable to fully leverage the rich feature information from global navigation satellite system reflectometry (GNSS-R) remote sensing data, therefore limiting the potential accuracy improvement. This study proposes a physics-informed multimodal deep-learning framework, physical-informed multimodal heterogeneous altimetry network (PIMFA-Net), to fuse heterogeneous spaceborne GNSS-R data to retrieve SSH. The GNSS-R data are acquired from the GNOS II instrument onboard the Fengyun-3E satellite, which can receive reflected signals from both global positioning system (GPS) and BeiDou navigation satellite system (BDS). GNSS-R parameters are used to construct the PIMFA-Net, which includes cropped DDM images, signal parameters, and system parameters in combination with environmental parameters (wind speed and convective rain rate from the European Centre for Medium-Range Weather Forecast, and SSH derived from physical altimetry models). The global sea surface dataset Danmarks Tekniske Universitet 2018 is used as ground truth for model training and evaluation. Data from 1 to 31 July 2022 are used to train PIMFA-Net, while data from August to October 2022 are used to evaluate the general ability of PIMFA-Net. Results demonstrate that the PIMFA-Net not only improves the accuracy and generalization by integrating heterogeneous data sources but also achieves all-weather, all-day, and wide-area SSH inversion with a precision of less than 40 cm for both GPS and BDS signals. This outcome holds significant potential for applications in marine ecological security monitoring and research. © 2008-2012 IEEE.

关键词： Submarine geophysics

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BentRay-NeRF: Bent-Ray Neural Radiance Fields for Robust Speed-of-Sound Imaging in Ultrasound Computed Tomography

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IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control 2025年第5期72卷 612-623页

作者： Cui, Shilong Wu, Qing Huang, Yiming Dai, Haizhao Zhang, Yuyao Yu, Jingyi Cai, Xiran ShanghaiTech University School of Information Science and Technology Shanghai201210 China ShanghaiTech University School of Information Science and Technology Shanghai Engineering Research Center of Intelligent Vision and Imaging Shanghai201210 China

Ultrasound computed tomography (USCT) is a promising technique for breast cancer detection because of its quantitative imaging capability of the speed of sound (SOS) of soft tissues and the fact that malignant breast lesions often have a higher SOS compared to healthy tissues in the human breast. Compared to waveform inversion-based USCT, bent-ray tracing USCT is relatively less computationally expensive, which particularly suits breast cancer screening in a large population. However, SOS image reconstruction using bent-ray tracing in USCT is a highly ill-conditioned problem, making it susceptible to measurement errors. This presents significant challenges in achieving stable and high-quality reconstructions. In this study, we show that using implicit neural representation (INR), the ill-conditioned problem can be well mitigated, and stable reconstruction is achievable. This INR approach uses a multilayer perceptron (MLP) with hash encoding to model the slowness map as a continuous function, to better regularize the inverse problem and has been shown more effective than classical approaches of solely adding regularization terms in the loss function. Thereby, we propose the bent-ray neural radiance fields (BentRay-NeRF) method for SOS image reconstruction to address the aforementioned challenges in classical SOS image reconstruction methods, such as the Gauss-Newton method. In silico and in vitro experiments showed that BentRay-NeRF has remarkably improved performance compared to the classical method in many aspects, including the image quality and the robustness of the inversion to different acquisition settings in the presence of measurement errors. © 1986-2012 IEEE.

关键词： Inverse problems

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A comprehensive review on rectification and power management strategies for triboelectric nanogenerators

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Science China(Technological Sciences) 2025年第3期68卷 1-29页

作者： Zhongjie LI Bingyan CUI Biao WANG Fan SHEN Hao WU Ying GONG Yan PENG Hengyu GUO Dan ZHANG Institute of Artificial Intelligence School of Future TechnologyShanghai UniversityShanghai200444China School of Mechatronic Engineering and Automation Shanghai UniversityShanghai200444China Department of Applied Physics Chongqing UniversityChongqing400044China Engineering Research Center of Unmanned Intelligent Marine Equipment Shanghai UniversityShanghai200444China

Nanogenerators utilize nanomaterials to harvest mechanical or thermal energy at the micro-nano scale,thereby providing power for small self-sustaining *** to traditional generators,nanogenerators offer advantages such as compact size,high flexibility,and broad *** nanogenerators(TENGs),based on triboelectric theory,can collect energy from mechanical sources such as vibrations or sliding *** hold promise for powering small ***,the high pulse characteristics of their output voltage prevent them from directly charging electronic *** address the requirements of the internet of things(IoTs),this paper comprehensively reviews state-of-the-art power management systems used to enhance the current stability and output power of ***,the working principle and resistive load output characteristics of TENGs are *** management circuits(PMCs)based on full-wave rectifiers,half-wave rectifiers,and Bennet's doublers are subsequently analyzed and *** and electronic switches proposed to further improve rectifier performance are also *** switches are categorized as travel and voltagetriggered switches,while electronic switches include silicon-controlled rectifiers(SCRs),metal-oxide-semiconductor fieldeffect transistors(MOSFETs),and integrated *** conclusion,the characteristics and applications of PMCs are summarized,along with the identification of existing limitations in their ***,appropriate solutions and prospects for further development are explored.

关键词： triboelectric nanogenerators power management circuit rectifier switch

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Dynamic Regret for Distributed Online Composite Optimization

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IEEE Transactions on Automatic Control 2025年第5期70卷 3056-3071页

作者： Hou, Ruijie Yu, Yang Li, Xiuxian Tongji University Department of Control Science and Engineering College of Electronics and Information Engineering Shanghai201800 China Tongji University Shanghai Research Institute for Intelligent Autonomous Systems National Key Laboratory of Autonomous Intelligent Unmanned Systems Frontiers Science Center for Intelligent Autonomous Systems Ministry of Education Shanghai Institute of Intelligent Science and Technology Shanghai201210 China

This article focuses on online composite optimization over multiagent networks. In the distributed setting, each agent has its own local loss function, which consists of a convex, strongly convex or strongly convex and smooth function, and a time-varying nonsmooth regularizer. Two distributed online algorithms are proposed and corresponding dynamic regrets are analyzed. Two proposed algorithms are based on signs of relative states. The first algorithm obtains (Formula presented) dynamic regret bound when each local loss is a general convex composite function, where CT is the path variation. If CT can be estimated in advance for convex or strongly convex local loss with a time-varying nonsmooth regularizer, then dynamic regret bounds are, respectively, in the order of (Formula presented) and o (log T(1 + CT)). The second algorithm is based on the first one, especially for handling the local loss composed of a strongly convex and smooth function with a nonsmooth regularizer, and then obtains o (1 + CT) dynamic regret bound. In the end, numerical results are given to support the theoretical findings. © 1963-2012 IEEE.

关键词： Optimization algorithms

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Prospective Role of Foundation Models in Advancing Autonomous Vehicles

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research 2025年第1期7卷 667-691页

作者： Jianhua Wu Bingzhao Gao Jincheng Gao Jianhao Yu Hongqing Chu Qiankun Yu Xun Gong Yi Chang H Eric Tseng Hong Chen Jie Chen School of Automotive Studies Tongji UniversityShanghai 201804China Frontiers Science Center for Intelligent Autonomous Systems Tongji UniversityShanghai 201210China SAIC Intelligent Technology Shanghai 201805China College of Artificial Intelligence Jilin UniversityChangchun 130012China Research and Advanced Engineering Ford Motor CompanyDearbornMI 48124USA College of Electronic and Information Engineering Tongji UniversityShanghai 201804China National Key Laboratory of Autonomous Intelligent Unmanned Systems Shanghai 201210China

With the development of artificial intelligence and breakthroughs in deep learning,large-scale foundation models(FMs),such as generative pre-trained transformer(GPT),Sora,etc.,have achieved remarkable results in many fields including natural language processing and computer *** application of FMs in autonomous driving holds considerable *** example,they can contribute to enhancing scene understanding and *** pre-training on rich linguistic and visual data,FMs can understand and interpret various elements in a driving scene,and provide cognitive reasoning to give linguistic and action instructions for driving decisions and ***,FMs can augment data based on the understanding of driving scenarios to provide feasible scenes of those rare occurrences in the long tail distribution that are unlikely to be encountered during routine driving and data *** enhancement can subsequently lead to improvement in the accuracy and reliability of autonomous driving *** testament to the potential of FMs'applications lies in world models,exemplified by the DREAMER series,which showcases the ability to comprehend physical laws and *** from massive data under the paradigm of self-supervised learning,world models can generate unseen yet plausible driving environments,facilitating the enhancement in the prediction of road users'behaviors and the off-line training of driving *** this paper,we synthesize the applications and future trends of FMs in autonomous *** utilizing the powerful capabilities of FMs,we strive to tackle the potential issues stemming from the long-tail distribution in autonomous driving,consequently advancing overall safety in this domain.

关键词： autonomous driving computer visionthe artificial intelligence natural language processing deep learninglarge scale autonomous vehicles understand interpr enhancing scene understanding reasoningby

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From Requirement to Solution: Unveiling Problem-Driven Design Patterns in Visual Analytics

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IEEE Transactions on Visualization and Computer Graphics 2025年第05期31卷 3481-3491页

作者： Wu, Yuchen Gao, Shenghan Zhang, Shizhen Dou, Xiaofeng Wang, Xingbo Li, Quan ShanghaiTech University School of Information Science and Technology Shanghai Engineering Research Center of Intelligent Vision and Imaging Shanghai201210 China Cornell University Weill Cornell Medical College United States

Visual Analytics (VA) researchers frequently collaborate closely with domain experts to derive requirements and select appropriate solutions to fulfill these requirements. Despite strides made in exploring requirement and solution spaces, challenges persist due to the absence of guidance in the initial consideration space and the lack of shared problem-solving knowledge, often resulting in suboptimal solutions. To address these issues, we conducted an empirical study of VA research, with a focus on mapping the relations between requirement and solution spaces. Analyzing 220 VA papers, we formulate refined topologies for data, requirements, and solutions. We propose conceptualizing the connections between requirements, data, and solutions through knowledge graphs and utilizing solution paths to encapsulate fundamental problem-solving knowledge in visual analytics research. Through the integration of solution paths into a graph and analyzing their interconnections, we identified a subset of problem-driven design patterns that demonstrated the efficacy of our approach. By externalizing problem-solving knowledge and formulating problem-driven design patterns, our aim is to streamline the exploration of consideration space, facilitating the inclusion of "good"solutions, and establish a benchmark for shared design decisions among researchers and readers. © 1995-2012 IEEE.

关键词： Visual analytics

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Path Integral Policy Improvement and Dynamic Movement Primitives Fusion-Based Impedance Force Control With Error Loop Correction

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IEEE Transactions on Automation Science and engineering 2025年 22卷 15034-15044页

作者： Liu, Mujie Chen, Haifei Li, Lijun Ma, Zhiqiang Xu, Yong Zhang, Hui Central South University of Forestry and Technology National Forestry and Grassland Engineering Technology Research Center for Harvesting Equipment of Nonwood Forest Fruits Engineering Research Center for Forestry Equipment of Hunan Province School of Mechanical and Intelligent Manufacturing Changsha410004 China Northwestern Polytechnical University Research Center for Intelligent Robotics School of Astronautics Xi’an710072 China Beijing Institute of Technology School of Automation Beijing100081 China Hunan University National Engineering Research Center of Robot Visual Perception and Control Technology School of Robotics Changsha410082 China

Path Integral Strategy Improvement(PI2)-based impedance control is a superior scheme for preventing damage to the physical structure of the fruit during the harvesting process. However, it is highly sensitive to disturbances and has limited generalization ability during the parameter learning process, making it difficult to apply the correct gripping force to fruits with uncertain stiffness. To solve this problem, this paper proposes a variable impedance force control method that integrates PI2 with Dynamic Movement Primitives (DMPs), supplemented by a force error correction loop. Firstly, an adaptive impedance parameter matching mechanism based on gain schedules is designed to facilitate dynamic estimation of impedance parameters and enable precise force control. To further accelerate impedance parameter matching in unknown environments, the PI2 algorithm is introduced to optimize gain schedules, and DMPs are integrated to suppress disturbances, thereby improving the generalization ability of the impedance model’s parameter learning. In addition, an additional force error control loop has been designed to minimize the deviation between the desired and actual gripping force. Finally, the effectiveness of the proposed method is verified through simulation and experiment in fruit teleoperation picking robot. In the local-remote heterogeneous fruit teleoperation picking robot system, preventing fruit damage is critical to improving harvesting efficiency and quality. However, the existing PI2 algorithm suffers from limited generalization ability during the parameter learning process and is highly susceptible to environmental disturbances, presenting challenges in force control. To address this issue, this study proposes integrating DMPs into PI2 to optimize gain schedules and designing a force error control loop to refine trajectories, thereby achieving the force control objectives and effectively compensating for the shortcomings of PI2. Simulation and experimental res

关键词： Rotation

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Multi-Scale Feature Fusion and Advanced Representation Learning for Multi Label Image Classification

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Computers, Materials & Continua 2025年第3期82卷 5285-5306页

作者： Naikang Zhong Xiao Lin Wen Du Jin Shi Institute of Artificial Intelligence on Education Research College of InformationMechanical and Electrical EngineeringShanghai Normal UniversityShanghai200234China Lab for Educational Big Data and Policymaking Ministry of EducationShanghai Normal UniversityShanghai200234China Shanghai Intelligent Education Big Data Engineering Technology Research Center Shanghai Normal UniversityShanghai200234China Shanghai Online Education Research Base for Primary and Secondary Schools Shanghai200234China DS Information Technology Co. Ltd.Shanghai200032China Faculty of Innovation Engineering Macao university of Science and TechnologyMacao999078China

Multi-label image classification is a challenging task due to the diverse sizes and complex backgrounds of objects in *** class-specific precise representations at different scales is a key aspect of feature ***,existing methods often rely on the single-scale deep feature,neglecting shallow and deeper layer features,which poses challenges when predicting objects of varying scales within the same *** some studies have explored multi-scale features,they rarely address the flow of information between scales or efficiently obtain class-specific precise representations for features at different *** address these issues,we propose a two-stage,three-branch Transformer-based *** first stage incorporates multi-scale image feature extraction and hierarchical scale *** design enables the model to consider objects at various scales while enhancing the flow of information across different feature scales,improving the model’s generalization to diverse object *** second stage includes a global feature enhancement module and a region selection *** global feature enhancement module strengthens interconnections between different image regions,mitigating the issue of incomplete represen-tations,while the region selection module models the cross-modal relationships between image features and ***,these components enable the efficient acquisition of class-specific precise feature *** experiments on public datasets,including COCO2014,VOC2007,and VOC2012,demonstrate the effectiveness of our proposed *** approach achieves consistent performance gains of 0.3%,0.4%,and 0.2%over state-of-the-art methods on the three datasets,*** results validate the reliability and superiority of our approach for multi-label image classification.

关键词： Image classification multi-label multi scale attention mechanisms feature fusion

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Structural plasticity of the contralesional subfields of hippocampus and amygdala in patients with IDH-mutant astrocytoma and oligodendroglioma

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Neuroradiology 2025年 1-9页

作者： Han, Qiuyue Wang, Dongdong Geng, Daoying Department of Radiology Huashan Hospital Fudan University Shanghai China Center for Shanghai Intelligent Imaging for Critical Brain Diseases Engineering and Technology Research Shanghai China

Purpose: To detect the structural plasticity of the contralesional hippocampus and amygdala in patients with unilateral IDH-mutant astrocytoma and oligodendroglioma, and to compare the differences between these two types of tumors. Methods: 3D T1-weighted MRI images were collected from 46 patients with left-hemispheric tumors (IDH-mutant astrocytoma, n = 22;oligodendroglioma, n = 24) and 23 healthy controls (HCs). Volumetric differences in the subregional volumes of the hippocampus and amygdala were assessed using FreeSurfer software. The differences were compared across groups. Results: In comparison to HCs, patients with unilateral IDH-mutant astrocytoma and oligodendroglioma exhibited a significantly larger volume of the hippocampal fissure in the contralesional hippocampus (p = 0.021, p = 0.041). In the astrocytoma group, volumetric increases were also observed in the contralesional amygdala subregions, including the medial-nucleus (p = 0.009), central-nucleus (p = 0.011), and cortical-nucleus (p = 0.039). Compared to the oligodendroglioma group, the astrocytoma group demonstrated significantly larger gray matter volume in the subiculum head (p = 0.008) of the contralesional hippocampus, as well as in the anterior amygdaloid area (AAA) (p = 0.044), central-nucleus (p = 0.025), and cortical-nucleus (p = 0.021) of the contralesional amygdala. Conclusion: These findings provide robust evidence of macrostructural plasticity in the contralateral hippocampus and amygdala in patients with unilateral IDH-mutant astrocytomas and oligodendrogliomas. Furthermore, the structural differences between tumor types may reflect distinct effects on brain plasticity and variations in tumor invasiveness. These insights could contribute to optimization of clinical management strategies and personalized cognitive rehabilitation strategies for glioma patients. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025.

关键词： Amygdala Astrocytoma Hippocampus Oligodendroglioma Structural plasticity

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