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Electrospinning drug-loaded polycaprolactone/polycaprolactone-gelatin multi-functional bilayer nanofibers composite scaffold for postoperative wound healing of cutaneous squamous cell carcinoma

Biomedical Technology

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Biomedical Technology 2024年 8卷 65-80页

作者： Song, Yongteng Hu, Qingxi Liu, Suihong Yao, Guotai Zhang, Haiguang Rapid Manufacturing Engineering Center School of Mechatronic Engineering and Automation Shanghai University Shanghai 200444 China Shanghai Key Laboratory of Intelligent Manufacturing and Robotics Shanghai University Shanghai 200072 China National Demonstration Center for Experimental Engineering Training Education Shanghai University Shanghai 200444 China Department of Dermatology Shanghai Fourth People's Hospital School of Medicine Tongji University Shanghai 200434 China Engineering Science and Mechanics Department Penn State University University Park 16802 PA United States

Cutaneous squamous cell carcinoma (cSCC) tumor resection surgery poses challenges due to incomplete cancer cell removal, which increases the risk of local recurrence and micrometastasis, while large-scale surgical wounds are susceptible to severe infections. Therefore, a drug-loaded multi-functional bilayer nanofibers skin scaffold was fabricated for postoperative wound care of cSCC. Briefly, the antibacterial drug enrofloxacin (ENR) was loaded into polycaprolactone (PCL) nanofibers using electrospinning to form an antibacterial nanofiber membrane (PCL-ENR) as the outer layer of scaffold. The anticancer drug bleomycin (BLM) was loaded into PCL/Gelatin (Gel) nanofibers via electrospinning to form an anticancer nanofiber membrane (PG-BLM) as the inner layer of scaffold. ENR and BLM were successfully loaded into the scaffold. The scaffold had excellent physicochemical properties, with the outer layer exhibiting hydrophobicity and excellent antibacterial activity, and the inner layer showing hydrophilicity and outstanding anticancer activity. The elongation at break and tensile modulus of the scaffold were 26.35 ± 1.61 % and 15.25 ± 1.56 MPa, respectively. In vitro and in vivo experiments suggested that the scaffold not only has good biocompatibility to promote wound healing but also could inhibit the proliferation of A431 cells, which has great potential clinical application in postoperative wound care of cSCC. © 2024 The Authors

关键词： Antibacterial and anticancer Bilayer nanofibers skin scaffold Cutaneous squamous cell carcinoma Drug-loaded Electrospinning Postoperative wound care

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Minimizing Long-Term Energy Consumption in RIS-Assisted UAV-Enabled MEC Network

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IEEE Internet of Things Journal 2025年第12期12卷 20942-20958页

作者： Yao, Zheng Zhu, Qiwu Zhang, Yanhui Huang, Haibo Luo, Min Hubei University of Automotive Technology School of Robotics and Automation Shiyan442002 China Hong Kong Polytechnic University National Rail Transit Electrification and Automation Engineering Technology Research Center Hong Kong Branch Hongkong999077 Hong Kong Chinese Academy of Sciences Shenzhen Institute of Advanced Technology Shenzhen517085 China

In recent years, Unmanned Aerial Vehicles (UAVs) are increasingly becoming flight-based communicative and computing platforms, but the scarcity of communication resources can significantly hinder their performance and scalability. Therefore, this paper proposes a Reconfigurable Intelligent Surface (RIS)-assisted UAV-enabled Mobile Edge Computing (MEC) network, aiming to reduce long-term energy consumption while maintaining system stability by jointly optimizing computing resources, time slot allocation, transmit power, RIS phase angles, and UAV trajectory. By applying the Lyapunov method, we transform the long-term stochastic optimization problem into manageable deterministic online subproblems, and obtain approximate optimal solutions using successive convex approximation, penalty functions, and convex optimization techniques. Simulation results show that compared to the baseline scheme, the proposed scheme approximately reduces energy consumption by 10%, improves system stability by approximately 16%, and maintains computational efficiency. © 2014 IEEE.

关键词： Aircraft communication

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BrainCLIP: Brain Representation via CLIP for Generic Natural Visual Stimulus Decoding

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IEEE Transactions on Medical Imaging 2025年 PP卷 PP页

作者： Ma, Yongqiang Liu, Yulong Chen, Liangjun Zhu, Guibo Chen, Badong Zheng, Nanning Xi'an Jiaotong University National Key Laboratory of Human-Machine Hybrid Augmented Intelligence National Engineering Research Center of Visual Information and Applications Institute of Artificial Intelligence and Robotics Shaanxi Xi'an710049 China Institute of Automation Beijing China

Functional Magnetic Resonance Imaging (fMRI) presents challenges due to limited paired samples and low signal-to-noise ratios, particularly in tasks involving reconstructing natural images or decoding their semantic content. To address these challenges, we introduce BrainCLIP, an innovative fMRI-based brain decoding model. BrainCLIP leverages Contrastive Language-Image Pre-training's (CLIP) cross-modal generalization abilities to bridge brain activity, images, and text for the first time. Our experiments demonstrate CLIP's effectiveness in diverse brain decoding tasks, including zero-shot visual category decoding, fMRI-image/text alignment, and fMRI-to-image generation. The core objective of BrainCLIP is to train a mapping network that translates fMRI patterns into a unified CLIP embedding space, achieved through visual and textual supervision integration. Our experiments highlight that this approach significantly enhances performance in tasks such as fMRI-text alignment and fMRI-based image generation. Notably, BrainCLIP surpasses BraVL, a recent multi-modal method, in zero-shot visual category decoding. Moreover, BrainCLIP demonstrates strong capability in reconstructing visual stimuli with high semantic fidelity, competing favorably with state-of-the-art methods in capturing high-level semantic features during fMRI-based natural image reconstruction. © 1982-2012 IEEE.

关键词： Signal to noise ratio

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Deep Learning Based Neovascularization Detection in Color Fundus Photography Image 23

Deep Learning Based Neovascularization Detection in Color Fu...

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9th International Conference on Computing and Artificial Intelligence, ICCAI 2023

作者： Guo, Tianjiao Yang, Jie Yu, Qi Institute of Medical Robotics Institute of Image Processing and Pattern Recognition Department of Automation School of Biomedical Engineering Shanghai Jiao Tong University Shanghai China Institute of Image Processing and Pattern Recognition Department of Automation Shanghai Jiao Tong University Shanghai China Department of Ophthalmology Shanghai General Hospital Shanghai Jiao Tong University School of Medicine Shanghai China National Clinical Research Center for Eye Diseases Shanghai China

ISBN: (纸本)9781450399029

Diabetic retinopathy (DR) has already been one of the leading causes of vision loss. A large number of researches about deep learning-based DR screening using color retinal photography images have been proposed in recent years. However, existing works mainly concentrated on non-proliferative diabetic retinopathy (NPDR) lesions. The exploration of proliferative diabetic retinopathy (PDR) lesion, which is more serious, is still insufficient. In this paper, we explored into one typical PDR lesion named neovascularization (NV). We collected and annotated retinal images from public and private datasets to construct and release a new dataset for NV detection. Three tasks including segmentation, detection, and grading were conducted on our dataset by using a set of state-of-the-art deep learning models. The results show that introducing NV detection can benefit DR grading. However, the segmentation and detection of NV are still challenging and have considerable room for improvement. © 2023 Copyright held by the owner/author(s).

关键词： Color

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METDrive: Multi-modal End-to-end Autonomous Driving with Temporal Guidance

arXiv

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arXiv 2024年

作者： Guo, Ziang Lin, Xinhao Yagudin, Zakhar Lykov, Artem Wang, Yong Li, Yanqiang Tsetserukou, Dzmitry Intelligent Space Robotics Laboratory Center for Digital Engineering Skolkovo Institute of Science and Technology Moscow Russia Insititute of Automation Qilu University of Technology Shandong Academy of Sciences Jinan250399 China

Multi-modal end-to-end autonomous driving has shown promising advancements in recent work. By embedding more modalities into end-to-end networks, the system’s understanding of both static and dynamic aspects of the driving environment is enhanced, thereby improving the safety of autonomous driving. In this paper, we introduce METDrive, an end-to-end system that leverages temporal guidance from the embedded time series features of ego states, including rotation angles, steering, throttle signals, and waypoint vectors. The geometric features derived from perception sensor data and the time series features of ego state data jointly guide the waypoint prediction with the proposed temporal guidance loss function. We evaluated METDrive on the CARLA leaderboard benchmarks, achieving a driving score of 70%, a route completion score of 94%, and an infraction score of 0.78. © 2024, CC BY-NC-ND.

关键词： Autonomous vehicles

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Two-Stage Grasping: A New Bin Picking Framework for Small Objects

Two-Stage Grasping: A New Bin Picking Framework for Small Ob...

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IEEE International Conference on robotics and automation (ICRA)

作者： Hanwen Cao Jianshu Zhou Junda Huang Yichuan Li Ng Cheng Meng Rui Cao Qi Dou Yunhui Liu Department of Mechanical and Automation Engineering T Stone Robotics Institute The Chinese University of Hong Kong. Hong Kong Center for Logistics Robotics (HKCLR) Department of Compute Science and Engineering The Chinese University of Hong Kong.

This paper proposes a novel bin picking framework, two-stage grasping, aiming at precise grasping of cluttered small objects. Object density estimation and rough grasping are conducted in the first stage. Fine segmentation, detection, grasping, and pushing are performed in the second stage. A small object bin picking system has been realized to exhibit the concept of two-stage grasping. Experiments have shown the effectiveness of the proposed framework. Unlike traditional bin picking methods focusing on vision-based grasping planning using classic frameworks, the challenges of picking cluttered small objects can be solved by the proposed new framework with simple vision detection and planning.

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Towards Flexible Interactive Reflection Removal with Human Guidance

arXiv

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arXiv 2024年

作者： Chen, Xiao Jiang, Xudong Tao, Yunkang Lei, Zhen Li, Qing Lei, Chenyang Zhang, Zhaoxiang The Hong Kong Polytechnic University Hong Kong ETH Zurich Switzerland Center for Artificial Intelligence and Robotics HKISI CAS Hong Kong NLPR Institute of Automation Chinese Academy of Sciences China

Single image reflection removal is inherently ambiguous, as both the reflection and transmission components requiring separation may follow natural image statistics. Existing methods attempt to address the issue by using various types of low-level and physics-based cues as sources of reflection signals. However, these cues are not universally applicable, since they are only observable in specific capture scenarios. This leads to a significant performance drop when test images do not align with their assumptions. In this paper, we aim to explore a novel flexible interactive reflection removal approach that leverages various forms of sparse human guidance, such as points and bounding boxes, as auxiliary high-level prior to achieve robust reflection removal. However, incorporating the raw user guidance naively into the existing reflection removal network does not result in performance gains. To this end, we innovatively transform raw user input into a unified form – reflection masks using an Interactive Segmentation Foundation Model. Such a design absorbs the quintessence of the foundational segmentation model and flexible human guidance, thereby mitigating the challenges of reflection separations. Furthermore, to fully utilize user guidance and reduce user annotation costs, we design a mask-guided reflection removal network, comprising our proposed self-adaptive prompt block. This block adaptively incorporates user guidance as anchors and refines transmission features via cross-attention mechanisms. Extensive results on real-world images validate that our method demonstrates state-of-the-art performance on various datasets with the help of flexible and sparse user guidance. Our code and dataset will be publicly available here https://***/ShawnChenn/FlexibleReflectionRemoval. Copyright © 2024, The Authors. All rights reserved.

关键词： Air navigation

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Performance analysis of Lambda Tuning Single Input Fuzzy Logic Controller for Remotely Operated Vehicle depth control

Performance analysis of Lambda Tuning Single Input Fuzzy Log...

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IEEE International Conference on Underwater System Technology: Theory and Applications (USYS)

作者： Fauzal Naim Zohedi Mohd Shahrieel Mohd Aras Hyreil Anuar Kasdirin Mohd Bazli Bahar Muhamad Khairi Aripin Fadilah Abdul Azis Center for Robotics and Industrial Automation (CeRIA) Fakulti Kejuruteraan Elektrik Universiti Teknikal Malaysia Melaka Malaysia

Underwater Remotely Operated Vehicle (ROV) is important to substitute human in doing underwater task. In marine industries, ROV is used to do underwater surveillance or observation. Due uncertainty of underwater environment and dynamic of ROV itself, depth trajectory control of ROV is difficult. Lambda tuning single input fuzzy logic (SIFLC) controller was implemented to the ROV to control the depth trajectory of the ROV. Performance analysis of Lambda SIFLC had been conducted for open frame and close frame ROV. The close frame ROV model is first order system while the open frame ROV is second order system. The transient responds analysis had been made using MATLAB Simulink. The implementation of the Lambda SIFLC shows significant improvement in the transient responds of the system.

关键词： Fuzzy logic Remotely guided vehicles Uncertainty Surveillance Trajectory Performance analysis Transient analysis

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A CT-guided Control Framework of a Robotic Flexible Endoscope for the Diagnosis of the Maxillary Sinusitis

A CT-guided Control Framework of a Robotic Flexible Endoscop...

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Puchen Zhu Huayu Zhang Xin Ma Xiaoyin Zheng Xuchen Wang Kwok Wai Samuel Au Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Hong Kong Department of Mechanical and Automation Engineering The Chinese Univerisity of Hong Kong Hong Kong The Multi-Scale Medical Robotics Center Hong Kong Autonomous Driving Center XMotors.ai Inc. Santa Clara CA USA

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Flexible endoscopes are commonly adopted in narrow and confined anatomical cavities due to their higher reachability and dexterity. However, prolonged and unintuitive manipulation of these endoscopes leads to an increased workload on surgeons and risks of collision. To address these challenges, this paper proposes a CT-guided control framework for the diagnosis of maxillary sinusitis by using a robotic flexible endoscope. In the CT-guided control framework, a feasible path to the target position in the maxillary sinus cavity for the robotic flexible endoscope is designed. Besides, an optimal control scheme is proposed to autonomously control the robotic flexible endoscope to follow the feasible path. This greatly improves the efficiency and reduces the workload for surgeons. Several experiments were conducted based on a widely utilized sinus phantom, and the results showed that the robotic flexible endoscope can accurately and autonomously follow the feasible path and reach the target position in the maxillary sinus cavity. The results also verified the feasibility of the CT-guided control framework, which contributes an effective approach to early diagnosis of sinusitis in the future.

关键词： Technological innovation Three-dimensional displays Medical robotics Endoscopes Surgery Phantoms Optimal control Collision avoidance Root mean square Robots

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The Impact of Domain Name Server(DNS)over Hypertext Transfer Protocol Secure(HTTPS)on Cyber Security:Limitations,Challenges,and Detection Techniques

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Computers, Materials & Continua 2024年第9期80卷 4513-4542页

作者： Muhammad Dawood Shanshan Tu Chuangbai Xiao Muhammad Haris Hisham Alasmary Muhammad Waqas Sadaqat Ur Rehman Faculty of Information Technology Beijing University of TechnologyBeijing100124China National Center of Robotics and Automation University of Engineering and TechnologyPeshawar25000Pakistan Department of Computer Science College of Computer ScienceKing Khalid UniversityAbha61421Saudi Arabia School of Computing and Engineering Sciences Faculty of Engineering and ScienceUniversity of GreenwichLondonSE109LSUnited Kingdom School of Engineering Edith Cowan UniversityPerthWA 6027Australia School of Computer Science and Engineering University of SalfordManchesterM54BRUnited Kingdom

The DNS over HTTPS(Hypertext Transfer Protocol Secure)(DoH)is a new technology that encrypts DNS traffic,enhancing the privacy and security of ***,the adoption of DoH is still facing several research challenges,such as ensuring security,compatibility,standardization,performance,privacy,and increasing user *** significantly impacts network security,including better end-user privacy and security,challenges for network security professionals,increasing usage of encrypted malware communication,and difficulty adapting DNS-based security ***,it is important to understand the impact of DoH on network security and develop newprivacy-preserving techniques to allowthe analysis of DoH traffic without compromising user *** paper provides an in-depth analysis of the effects of DoH on *** discuss various techniques for detecting DoH tunneling and identify essential research challenges that need to be addressed in future security ***,this paper highlights the need for continued research and development to ensure the effectiveness of DoH as a tool for improving privacy and security.

关键词： DNS DNS over HTTPS cybersecurity machine learning

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