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Novel injectable composite incorporating denosumab promotes bone regeneration via bone homeostasis regulation

Engineered Regeneration 2024年第4期5卷 482-494页

作者： Guang Yang Zili Guo Xiangfeng Zhang Jiayu Chen Jie Weng Jiapeng Bao Xiaohua Yu Department of Orthopedic Surgery the Second Affiliated HospitalZhejiang University School of MedicineHangzhouZhejiang 310000PR China Orthopedics Research Institute of Zhejiang University HangzhouZhejiang 310000PR China Key Laboratory of Motor System Disease Research and Precision Therapy of Zhejiang Province HangzhouZhejiang 310000PR China Clinical Research Center of Motor System Disease of Zhejiang Province HangzhouZhejiang 310000PR China Key Laboratory of Advanced Technologies of Materials Ministry of Education School of Materials Science and EngineeringSouthwest Jiaotong UniversityChengduSichuan610031PR China Institute of Biomedical Engineering College of MedicineSouthwest Jiaotong UniversityChengdu 610031SichuanChina

Repair of large bone defects remains to be clinically challenging,yet current bone repair strategies focus on optimizing the osteogenic capacity of bone grafts,while the role of osteoclasts in bone regeneration has been largely ***,we designed a injectable self-curing bone grafting paste capable of regulating both an-abolic/catabolic activities during bone healing by immobilizing the RANKL inhibitor denosumab on dermal-derived extracellular matrix(ECM)microfibres,which were then incorporated into an injectable paste via a hydration reaction between𝛽-tricalcium phosphate(𝛽-TCP),monocalcium phosphate monohydrate(MCPM)and calcium sulfate hemihydrate(CSH).The incorporation of ECM microfibres not only serves as a sustained-release denosumab carrier to inhibit osteoclastogenesis but also improves the mechanical properties of the resulting com-posite by increasing the interaction between the organic and inorganic *** vitro,calcium supply from the composite along with ECM enhanced osteogenic differentiation of BMSC while release of denosumab effectively inhibits osteoclast fusion and alleviate osteoclastic *** vivo,it was observed that CSH/CP@ECM-Deno significantly reduced the number of osteoclasts,slowed down the process of bone resorption,and accelerated collagen deposition to promote new bone *** results suggest that modulation of osteoclastogenesis by interfering with bone homeostasis may be an effective bone repair strategy.

关键词： Bone regeneration Denosumab Osteoclastogenesis Osteogenesis

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Open-Source Codes of Topology Optimization: A Summary for Beginners to Start Their research

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Computer Modeling in engineering & Sciences 2023年第10期137卷 1-34页

作者： Yingjun Wang Xinqing Li Kai Long Peng Wei National Engineering Research Center of Novel Equipment for Polymer Processing The Key Laboratory of Polymer Processing Engineering of the Ministry of EducationGuangdong Provincial Key Laboratory of Technique and Equipment for Macromolecular Advanced ManufacturingSouth China University of TechnologyGuangzhou510641China State Key Laboratory of Alternate Electrical Power Systemwith Renewable Energy Sources North China Electric Power UniversityBeijing102206China State Key Laboratory of Subtropical Building Science School of Civil Engineering and TransportationSouth China University of TechnologyGuangzhou510641China

Topology optimization(TO),a numerical technique to find the optimalmaterial layoutwith a given design domain,has attracted interest from researchers in the field of structural optimization in recent *** beginners,opensource codes are undoubtedly the best alternative to learning TO,which can elaborate the implementation of a method in detail and easily engage more people to employ and extend the *** this paper,we present a summary of various open-source codes and related literature on TO methods,including solid isotropic material with penalization(SIMP),evolutionary method,level set method(LSM),moving morphable components/voids(MMC/MMV)methods,multiscale topology optimization method,***,we classify the codes into five levels,fromeasy to difficult,depending on their difficulty,so that beginners can get started and understand the form of code implementation more quickly.

关键词： Topology optimization open-source code optimization methods code classification beginners

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Exploring the correlation between hard-braking events and traffic crashes in regional transportation networks: A geospatial perspective

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Multimodal transportation 2024年第2期3卷

作者： Feng, Suoyao Wang, Aobo Tian, Zong Park, Seri Center for Advanced Transportation Education and Research (CATER) Department of Civil and Environmental Engineering University of Nevada Reno Reno 89557 NV United States

Traffic crashes are deemed a leading cause of death and injury in the United States. To improve traffic safety, historical traffic crash data are typically analyzed with a focus on factors such as roadway geometry and traffic volume. However, due to the infrequent and sporadic nature of traffic crashes, obtaining traffic safety evaluation for specific roadways requires a time and resource-intensive process, which involves extended periods of data collection and rigorous statistical reasoning. This paper explores alternative approaches, using hard-braking data collected from connected vehicles to develop a cost-efficient surrogate traffic safety measure. The geospatial correlations between hard-braking events and traffic crash locations are examined through two geospatial analysis methods: colocation analysis and network cross K-function. A case study was conducted in northern Nevada to identify hard-braking hot spots and reveal the overall cluster pattern. The colocation analysis identified that individual hard-braking events can be spatially related to crashes based on the network cross K-function result. The cases of four tracts in Reno, Nevada also demonstrate that the selection of clustering distances can influence the correlation between hard braking events and traffic crashes. This study shows the potential of using connected vehicle data to produce safety analyses for transportation networks. © 2024

关键词： Cluster analysis Connected vehicle data Hard-braking events Traffic safety

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Segmenting Anything in the Dark via Depth Perception

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IEEE Transactions on Multimedia 2025年 27卷 2975-2986页

作者： Liu, Peng Deng, Jinhong Duan, Lixin Li, Wen Lv, Fengmao University of Electronic Science and Technology of China Chengdu611731 China University of Electronic Science and Technology of China School of Computer Science and Engineering Chengdu611731 China UESTC Shenzhen Institute for Advanced Study Shenzhen518110 China University of Electronic Science and Technology of China Sichuan Provincial Key Laboratory for Human Disease Gene Study Center for Medical Genetics Department of Laboratory Medicine Sichuan Academy of Medical Sciences Sichuan Provincial People's Hospital Chengdu610032 China Southwest Jiaotong University Engineering Research Center of Sustainable Urban Intelligent Transportation Ministry of Education School of Computing and Artificial Intelligence Chengdu611756 China

Image segmentation under low-light conditions is essential in real-world applications, such as autonomous driving and video surveillance systems. The recent Segment Anything Model (SAM) exhibits strong segmentation capability in various vision applications. However, its performance could be severely degraded under low-light conditions. On the other hand, multimodal information has been exploited to help models construct more comprehensive understanding of scenes under low-light conditions by providing complementary information (e.g., depth). Therefore, in this work, we present a pioneer attempt that elevates a unimodal vision foundation model (e.g., SAM) to a multimodal one, by efficiently integrating additional depth information under low-light conditions. To achieve that, we propose a novel method called Depth Perception SAM (DPSAM) based on the SAM framework. Specifically, we design a modality encoder to extract the depth information and the Depth Perception Layers (DPLs) for mutual feature refinement between RGB and depth features. The DPLs employ the cross-modal attention mechanism to mutually query effective information from both RGB and depth for the subsequent feature refinement. Thus, DPLs can effectively leverage the complementary information from depth to enrich the RGB representations and obtain comprehensive multimodal visual representations for segmenting anything in the dark. To this end, our DPSAM maximally maintains the instinct expertise of SAM for RGB image segmentation and further leverages on the strength of depth for enhanced segmenting anything capability, especially for cases that are likely to fail with RGB only (e.g., low-light or complex textures). As demonstrated by extensive experiments on four RGBD benchmark datasets, DPSAM clearly improves the performance for the segmenting anything performance in the dark, e.g., +12.90% mIoU and +16.23% mIoU on LLRGBD and DeLiVER, respectively. © 1999-2012 IEEE.

关键词： Image segmentation

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Adaptive Robust Control of an Uncertain Robotic Manipulator with Guaranteed Transient and Steady State Performance 8

Adaptive Robust Control of an Uncertain Robotic Manipulator ...

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8th IEEE International Conference on advanced Robotics and Mechatronics, ICARM 2023

作者： Liu, Yifan Yu, Dejie Wang, Zilu Zhang, Zheshuo Yin, Hui Hunan University State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body Changsha410082 China School of Information and Electrical Engineering Zhejiang Uni-versity City College Intelligent Transportation System Research Center Zhejiang Hangzhou310015 China School of Mechanical and Automotive Engineering South China University of Technology Guangdong Guangzhou510641 China

ISBN: (纸本)9798350300178

Guaranteeing human-specified performance in robot control subject to complex uncertainties is challenging. This study takes time-varying (possibly fast), bounded with unknown bounds uncertainties into consideration in controlling an uncertain robotic manipulator system (URMS). We employ an adaptive law to on-line estimate the unknown bounds for uncertainty compensation, and prescribed transient and steady state performance (TSSP) are guaranteed by using a state transformation technique. As a result, a class of adaptive robust control with prescribed TSSP is proposed. Simulation results are provided to validate the effectiveness of the proposed approach. © 2023 IEEE.

关键词： Uncertainty analysis

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RCS: Automatic Navigation Framework for Legged Robots with Incremental RGB and Consistent Semantics Information

RCS: Automatic Navigation Framework for Legged Robots with I...

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2023 IEEE International Conference on Robotics and Biomimetics, ROBIO 2023

作者： Liu, Dayu Chen, Teng Zhang, Guoteng Zhao, Zhicheng Rong, Xuewen Fan, Yong Li, Yibin Shandong Youbaote Intelligent Robotics CO. LTD Jinan250098 China Shandong University School of Control Science and Engineering 17923 Jingshi Road Jinan250061 China Ministry of Education Engineering Research Center of Lntelligent Unmanned System Jinan250061 China Shandong Jiaotong University School of Rail Transportation Jinan250357 China

ISBN: (纸本)9798350325706

Autonomous movement of legged robots in outdoor scenes requires accurate state estimation and environment navigation maps. Different from wheeled and tracked mobile robots, legged robots can adjust parameters such as gait type, step height, gait frequency, torso height, foot friction, and other coefficients to better adapt to the geometric characteristics and physical properties of verstile terrains. To this end, in this paper, we propose a framework for autonomous navigation of legged robots, including the construction of geometric-property RGB consistent semantic map (RCS) and the autonomous navigation method under the RCS map. The method for building RCS map formulates lidar-inertial odometry based on a factor graph. Through end-to-end semantic segmentation of images, terrain information is projected and saved while mapping. For achieving pose and point cloud consistency, local and global lidar boudle adjustment (BA) is introduced to the optimization process. We demonstrated the effectiveness of RCS through outdoor navigation experiments on a quadruped robot. The experiment shows that our terrain detection method can achieve an average detection time of 30 ms on an embedded board. © 2023 IEEE.

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Set-point Determination and Regualtion for Flue Gas Desulphurization Process by ELM-assisted MOPSO and LQIR controller 41

Set-point Determination and Regualtion for Flue Gas Desulphu...

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第41届中国控制会议

作者： Quanbo Liu Xiaoli Li Kang Wang Faculty of Information Technology Beijing University of Technology Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing Advanced Innovation Center for Future Internet TechnologyBeijing University of Technology Engineering Research Center of Digital Community Ministry of EducationBeijing University of Technology

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

In China,coal accounts for over a half of the total energy consumption and it is primarily used in coal-fired power ***,the change of a dominant role that coal played in electricity generation appears to be impossible in the near *** operation of coal-fired power stations involves combustion of coal,which would generate a vast amount of sulphur dioxide（SO）,the resulting SO in turn pose numbers of environmental and human-health *** view of the above considerations,optimization and control techiniques should be incorporated in flue gas desulphurization（FGD） system,so that further improvement in overall performance of FGD can be *** this paper,based upon historical operational data from FGD system at a 1000 MW unit coal-fired power station,we formulate the set-point determination in FGD process into a constrained many-objective optimization *** of all,multiple objective particle swarm optimization（MOPSO） algorithm along with extreme learning machine（ELM） is utilized to yield Pareto-optimal ***,for control purpose,setpoint is determined from the obtained Pareto ***,with the use of linear quadratic integral controller（LQIR）,the setpoint regualation task is *** simulation studies,derived respresentative point is theoretically justified and FGD process can be regulated to it successfully.

关键词： many-objective optimization flue Gas Desulphurization linear quadratic regulator multiple objective particle swarm optimization extreme learning machine

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A dynamics model for Self-Propelled Modular Transporter*

A dynamics model for Self-Propelled Modular Transporter*

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IEEE Symposium on Intelligent Vehicle

作者： Zhenggan Cai Chaozhong Wu Yi He Pu Shao Intelligent Transportation System Research Center Wuhan University of Technology Wuhan China Engineering Research Center of Transportation Information and Safety Ministry of Education Wuhan China Hubei University of Arts and Science Xiangyang China Hubei Sanjiang Space Wanshan Special Vehicle Company Ltd Xiaogan China

ISBN: (数字)9798350348811

ISBN: (纸本)9798350348828

This study constructs a three-degree-of-freedom (3-DOF) dynamics model for a Self-Propelled Modular Transporter (SPMT) with six axles. A novel particle swarm optimization with variable control factors and elitist learning (PSO-VFEL) is developed to quantify unknown terms and is compared with three existing optimizers, including an initial PSO, a traditional PSO, and a PSO with variable control factors (PSO-VF). Compared to the existing optimizers, the PSO-VFEL demonstrates higher flying flexibility and particle diversity, attributed to the generationally variable factors and additional guidance from the elitist learning strategy. Simulation data from the Carla software is employed for model calibration. Results show that the developed PSO-VFEL is superior for calibrating the dynamics model, achieving fitness improvements of 31.852%, 20.231%, and 5.154% compared to the initial PSO, the traditional PSO, and the PSO-VF, respectively. This research provides a dynamics model and a complementary calibrator for engineering applications.

关键词： Intelligent vehicles Heuristic algorithms 3-DOF Software Data models Calibration Vehicle dynamics

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Numerical process simulation of hot forming

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Keikinzoku/Journal of Japan Institute of Light Metals 2021年第3期71卷 152-157页

作者： YOSHIDA, Yoshinori Center for Advanced and Smart Die Engineering and Technology G-CADET Gifu University Tokai National Higher Education and Research System 1-1 Yanagido Gifu-shi Gifu501-1193 Japan

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The First Experimental Study of Monocular Visual Localization for Train using Deep Learning Method 9

The First Experimental Study of Monocular Visual Localizatio...

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9th IEEE International Conference on Cloud Computing and Intelligence systems, CCIS 2023

作者： Wang, Yong Xie, Junqing Zhang, Jingtao Li, Shu Fan, Kai Zhang, Miao Hangzhou Innovation Institute Beihang University Hangzhou310000 China The Center of National Railway Intelligent Transportation System Engineering and Technology Beijing100081 China Advanced Institute of Information Technology of Peking University Hangzhou311200 China Signal Communication Research Institute China Academy of Railway Sciences Corporation Limited Beijing100081 China

ISBN: (纸本)9798350304428

The development of a scalable and adaptable trackside and on-board coordinated control system (CCS+) is a top priority for the digital and automated train operations of future railways. One of the most important and reliable solutions in CCS+ is train positioning, which is called GLAT (Generic Location-Awareness Tools). The technologies of GLAT can rely on many methods like GNSS such as INS/GPS. In this paper we introduce a deep learning method to recognize the location through only monocular cameras. This method can be very useful when, for example, in 'satellite signal blind spots' such as tunnels and mountainous areas or even no GPS signals at all. We carried out the first visual train positioning research experiment in the China National Railway Test center (East Suburban Branch). By using a well-trained Train Localization Network, we demonstrate that trains can successfully recognize the real-time location when it moves along its route. Compared with traditional INS/GNSS integrated navigation scheme, the computer vision method is more robust and attractive since it brings trains an 'intelligent brain', the train can deduce the localization by exploring its own 'visual memory'. This kind of capability can accelerate more intelligence utilized by modern trains. © 2023 IEEE.

关键词： Location

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