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Preclinical evaluation and pilot clinical study of [^(18)F]AlF-labeled FAPI-tracer for PET imaging of cancer associated fibroblasts

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Acta Pharmaceutica Sinica B 2022年第2期12卷 867-875页

作者： Kongzhen Hu Junqi Li Lijuan Wang Yong Huang Li Li Shimin Ye Yanjiang Han Shun Huang Hubing Wu jin su Ganghua Tang Department of Nuclear Medicine Nanfang HospitalSouthern Medical UniversityGuangzhou 510515China Shenzhen International Institute for Biomedical Research Shenzhen 518116China National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital&Shenzhen Hospital Chinese Academy of Medical Sciences and Peking Union Medical CollegeShenzhen 518116China State Key Laboratory of Respiratory Disease National Clinical Research Center for Respiratory DiseaseGuangzhou Institute of Respiratory Healththe First Affiliated Hospital of Guangzhou Medical UniversityGuangzhou 510182China

In recent years,fibroblast activation protein(FAP)has emerged as an attractive target for the diagnosis and radiotherapy of cancers using FAP-specific radioligands.Herein,we aimed to design a novel^(18)Flabeled FAP tracer([^(18)F]Al F-P-FAPI)for FAP imaging and evaluated its potential for clinical application.The[^(18)F]Al F-P-FAPI novel tracer was prepared in an automated manner within 42 min with a non-decay corrected radiochemical yield of 32±6%(n=8).Among A549-FAP cells,[^(18)F]Al F-P-FAPI demonstrated specific uptake,rapid internalization,and low cellular efflux.Compared to the patent tracer[^(18)F]FAPI-42,[^(18)F]Al F-P-FAPI exhibited lower levels of cellular efflux in the A549-FAP cells and higher stability in vivo.Micro-PET imaging in the A549-FAP tumor model indicated higher specific tumor uptake of[^(18)F]Al F-P-FAPI(7.0±1.0%ID/g)compared to patent tracers[^(18)F]FAPI-42(3.2±0.6%ID/g)and[68 Ga]Ga-FAPI-04(2.7±0.5%ID/g).Furthermore,in an initial diagnostic application in a patient with nasopharyngeal cancer,[^(18)F]Al F-P-FAPI and[^(18)F]FDG PET/CT showed comparable results for both primary tumors and lymph node metastases.These results suggest that[^(18)F]Al F-P-FAPI can be conveniently prepared,with promising characteristics in the preclinical evaluation.The feasibility of FAP imaging was demonstrated using PET studies.

关键词： Fibroblast activation protein [^(18)F]AlF-P-FAPI PET Nasopharyngeal cancer

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Kinetic model of vibration screening for granular materials based on biological neural network

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Particuology 2024年第5期88卷 98-106页

作者： Zhan Zhao Yan Zhang Fang Qin Mingzhi jin School of Agricultural Engineering Jiangsu UniversityZhenjiang212013China Shandong Academy of Agricultural Machinery Sciences Ji'nan250100China

The kinetic model is the theoretical basis for optimizing the structure and operation performance of vibration screening devices.In this paper,a biological neurodynamic equation and neural connections were established according to the motion and interaction properties of the material under vibration excitation.The material feeding to the screen and the material passing through apertures were considered as excitatory and inhibitory inputs,respectively,and the generated stable neural activity landscape was used to describe the material distribution on the 2D screen surface.The dynamic process of material vibration screening was simulated using discrete element method(DEM).By comparing the similarity between the material distribution established using biological neural network(BNN)and that obtained using DEM simulation,the optimum coefficients of BNN model under a certain screening parameter were determined,that is,one relationship between the BNN model coefficients and the screening operation parameters was established.Different screening parameters were randomly selected,and the corresponding relationships were established as a database.Then,with straw/grain ratio,aperture diameter,inclination angle,vibration strength in normal and tangential directions as inputs,five independent adaptive neuro-fuzzy inference systems(ANFIS)were established to predict the optimum BNN model coefficients,respectively.The training results indicated that ANFIS models had good stability and accuracy.The flexibility and adaptability of the proposed BNN method was demonstrated by modeling material distribution under complex feeding conditions such as multiple regions and non-uniform rate.

关键词： Kinetic model Material distribution Vibration screening Biological neural network DEM simulation Adaptive neuro-fuzzy inference systems

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Vibration suppression for Active Magnetic Bearings Using Adaptive Filter with Iterative Search Algorithm

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CES Transactions on Electrical Machines and Systems 2024年第1期8卷 61-71页

作者： jin-Hui Ye Dan Shi Yue-Sheng Qi jin-Hui Gao Jian-Xin Shen IEEE Department of Electrical Engineering Zhejiang UniversityHangzhou 310027China CES and IEEE

Active Magnetic Bearing(AMB) is a kind of electromagnetic support that makes the rotor movement frictionless and can suppress rotor vibration by controlling the magnetic force. The most common approach to restrain the rotor vibration in AMBs is to adopt a notch filter or adaptive filter in the AMB controller. However, these methods cannot obtain the precise amplitude and phase of the compensation current. Thus, they are not so effective in terms of suppressing the vibrations of the fundamental and other harmonic orders over the whole speed range. To improve the vibration suppression performance of AMBs,an adaptive filter based on Least Mean Square(LMS) is applied to extract the vibration signals from the rotor displacement signal. An Iterative Search Algorithm(ISA) is proposed in this paper to obtain the corresponding relationship between the compensation current and vibration signals. The ISA is responsible for searching the compensating amplitude and shifting phase online for the LMS filter, enabling the AMB controller to generate the corresponding compensation force for vibration suppression. The results of ISA are recorded to suppress vibration using the Look-Up Table(LUT) in variable speed range. Comprehensive simulations and experimental validations are carried out in fixed and variable speed range, and the results demonstrate that by employing the ISA, vibrations of the fundamental and other harmonic orders are suppressed effectively.

关键词： Active Magnetic Bearing(AMB) Adaptive filter Iterative search algorithm Least mean square(LMS) Vibration suppression

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Fast solution to the free return orbit's reachable domain of the manned lunar mission by deep neural network

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Journal of Systems Engineering and Electronics 2024年第2期35卷 495-508页

作者： YANG Luyi LI Haiyang ZHANG jin ZHU Yuehe College of Aerospace Science and Engineering National University of Defense TechnologyChangsha 410073China China Astronauts Research and Training Center Beijing 100094China Hunan Key Laboratory of Intelligent Planning and Simulation for Aerospace Missions Changsha 410073China

It is important to calculate the reachable domain(RD)of the manned lunar mission to evaluate whether a lunar landing site could be reached by the spacecraft. In this paper, the RD of free return orbits is quickly evaluated and calculated via the classification and regression neural networks. An efficient databasegeneration method is developed for obtaining eight types of free return orbits and then the RD is defined by the orbit’s inclination and right ascension of ascending node(RAAN) at the perilune. A classify neural network and a regression network are trained respectively. The former is built for classifying the type of the RD, and the latter is built for calculating the inclination and RAAN of the RD. The simulation results show that two neural networks are well trained. The classification model has an accuracy of more than 99% and the mean square error of the regression model is less than 0.01°on the test set. Moreover, a serial strategy is proposed to combine the two surrogate models and a recognition tool is built to evaluate whether a lunar site could be reached. The proposed deep learning method shows the superiority in computation efficiency compared with the traditional double two-body model.

关键词： manned lunar mission free return orbit reachable domain(RD) deep neural network computation efficiency

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Optimization of Band Gap of 1D Elastic Metamaterial Under Impact Load by Regulating Stiffness

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Acta Mechanica Solida Sinica 2024年第1期37卷 148-154页

作者： Tong Li Xianlong jin Yongqiang Li Peizhong Yang School of Mechanical Engineering Shanghai Jiao Tong UniversityShanghai 200240China State Key Laboratory of Mechanical System and Vibration Shanghai Jiaotong UniversityShanghai 200240China College of Science Northeastern UniversityShenyang 110819China

Designing materials that mitigate impacts effectively are crucial for protecting people and structures.Here,a single-resonator metamaterial with negative mass characteristics is proposed for impact mitigation,and numerical analysis of wave propagation shows explicitly how the spring stiffness and number of unit cells influence that mitigation.The results show clearly that a metamaterial with differing microstructural stiffness is better at mitigating the effect of a shock wave than one with a unique stiffness.Also,there is a critical number of unit cells beyond which the shock wave is not attenuated further,but the fabrication complexity increases.In the 40 groups of microstructural regions in this example,the attenuation effect no longer increases when there are more than 35 groups.This work offers guidance for microstructure designs in metamaterials and provides new ideas for using metamaterials to mitigate shock waves.

关键词： Elastic metamaterials Wave attenuation Stiffness Number of unit cells

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Recent progresses in thermal treatment of β-Ga_(2)O_(3) single crystals and devices

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International Journal of Minerals,Metallurgy and Materials 2024年第7期31卷 1659-1677页

作者： Yuchao Yan Zhu jin Hui Zhang Deren Yang State Key Laboratory of Silicon and Advanced Semiconductor Materials and School of Materials Science and Engineering Zhejiang UniversityHangzhou 310027China Zhejiang Provincial Key Laboratory of Power Semiconductor Materials and Devices ZJU-Hangzhou Global Scientific and Technological Innovation CenterHangzhou 311200China

In recent years,ultra-wide bandgap β-Ga_(2)O_(3) has emerged as a fascinating semiconductor material due to its great potential in power and photoelectric devices.In semiconductor industrial,thermal treatment has been widely utilized as a convenient and effective approach for substrate property modulation and device fabrication.Thus,a thorough summary of β-Ga_(2)O_(3) substrates and devices behaviors after high-temperature treatment should be significant.In this review,we present the recent advances in modulating properties of β-Ga_(2)O_(3) substrates by thermal treatment,which include three major applications:(ⅰ)tuning surface electrical properties,(ⅱ)modifying surface morphology,and(ⅲ)oxidating films.Meanwhile,regulating electrical contacts and handling with radiation damage and ion implantation have also been discussed in device fabrication.In each category,universal annealing conditions were speculated to figure out the corresponding problems,and some unsolved questions were proposed clearly.This review could construct a systematic thermal treatment strategy for various purposes and applications of β-Ga_(2)O_(3).

关键词： β-gallium oxide thermal treatment substrates devices

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A spaceborne advanced storage system for remote sensing microsatellites

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Frontiers of Information Technology & Electronic Engineering 2024年第4期25卷 600-615页

作者： Shilei TU Huiquan WANG Yue HUANG Zhonghe jin Micro-Satellite Research Center Zhejiang UniversityHangzhou 310027China Key Laboratory of Micro-Nano Satellite Research Zhejiang ProvinceHangzhou 310027China

With the development of satellite miniaturization and remote sensing,the establishment of microsatellite constellations is an inevitable trend.Due to their limited size,weight,and power,spaceborne storage systems with excellent scalability,performance,and reliability are still one of the technical bottlenecks of remote sensing microsatellites.Based on the commercial off-the-shelf field-programmable gate array and memory devices,a spaceborne advanced storage system(SASS)is proposed in this paper.This work provides a dynamic programming,queue scheduling multiple-input multiple-output cache technique and a high-speed,high-reliability NAND flash controller for multiple microsatellite payload data.Experimental results show that SASS has outstanding scalability with a maximum write rate of 2429 Mb/s and preserves at least 78.53%of the performance when a single NAND flash fails.The scheduling technique effectively shortens the data scheduling time,and the data remapping method of the NAND flash controller can reduce the retention error by at least 50.73%and the program disturbance error by at least 37.80%.

关键词： Microsatellite Spaceborne advanced storage system(SASS) Scalability Performance Reliability

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N-Heterocyclic carbene-catalyzed enantioselective(dynamic) kinetic resolutions and desymmetrizations

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Science China Chemistry 2024年第2期67卷 482-511页

作者： Yi Zhang Hui Cai Xiuhai Gan Zhichao jin National Key Laboratory of Green Pesticide Key Laboratory of Green Pesticide and Agricultural BioengineeringMinistry of EducationGuizhou UniversityHuaxi DistrictGuiyang550025China

N-heterocyclic carbene-catalyzed enantioselective kinetic resolutions,dynamic kinetic resolutions,and desymmetrization reactions are systematically reviewed.The content is organized according to the activation modes involved in these transformations.Future advances within this highly active research field are discussed from our perspectives on the topic.

关键词： N-heterocyclic carbene kinetic resolution dynamic kinetic resolution desymmetrization organocatalysis

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Research on modeling and self-excited vibration mechanism in magnetic levitation-collision interface coupling system

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Applied Mathematics and Mechanics(English Edition) 2024年第5期45卷 873-890页

作者： jinghu TANG Chaofeng LI jin ZHOU Zhiwei WU School of Mechanical Engineering&Automation Northeastern UniversityShenyang 110819China Key Laboratory of Vibration and Control of Aero-Propulsion Systems of Ministry of Education of China Northeastern UniversityShenyang 110819China School of Mechanical and Electrical Engineering Nanjing University of Aeronautics and AstronauticsNanjing 210016China

The modeling and self-excited vibration mechanism in the magnetic levitation-collision interface coupling system are investigated.The effects of the control and interface parameters on the system's stability are analyzed.The frequency range of self-excited vibrations is investigated from the energy point of view.The phenomenon of self-excited vibrations is elaborated with the phase trajectory.The corresponding control strategies are briefly analyzed with respect to the vibration mechanism.The results show that when the levitation objects collide with the mechanical interface,the system's vibration frequency becomes larger with the decrease in the collision gap;when the vibration frequency exceeds the critical frequency,the electromagnetic system continues to provide energy to the system,and the collision interface continuously dissipates energy so that the system enters the self-excited vibration state.

关键词： magnetic levitation coupling system self-excited vibration mechanical interface vibration frequency

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Constrained Multi-Objective Optimization With Deep Reinforcement Learning Assisted Operator Selection

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IEEE/CAA Journal of Automatica Sinica 2024年第4期11卷 919-931页

作者： Fei Ming Wenyin Gong Ling Wang Yaochu jin the School of Computer Science China University of GeosciencesWuhan 430074China the Department of Automation Tsinghua UniversityBeijing 100084China the Faculty of Technology Bielefeld UniversityNorth Rhine-Westphalia33619 BielefeldGermany

Solving constrained multi-objective optimization problems with evolutionary algorithms has attracted considerable attention.Various constrained multi-objective optimization evolutionary algorithms(CMOEAs)have been developed with the use of different algorithmic strategies,evolutionary operators,and constraint-handling techniques.The performance of CMOEAs may be heavily dependent on the operators used,however,it is usually difficult to select suitable operators for the problem at hand.Hence,improving operator selection is promising and necessary for CMOEAs.This work proposes an online operator selection framework assisted by Deep Reinforcement Learning.The dynamics of the population,including convergence,diversity,and feasibility,are regarded as the state;the candidate operators are considered as actions;and the improvement of the population state is treated as the reward.By using a Q-network to learn a policy to estimate the Q-values of all actions,the proposed approach can adaptively select an operator that maximizes the improvement of the population according to the current state and thereby improve the algorithmic performance.The framework is embedded into four popular CMOEAs and assessed on 42 benchmark problems.The experimental results reveal that the proposed Deep Reinforcement Learning-assisted operator selection significantly improves the performance of these CMOEAs and the resulting algorithm obtains better versatility compared to nine state-of-the-art CMOEAs.

关键词： Constrained multi-objective optimization deep Qlearning deep reinforcement learning(DRL) evolutionary algorithms evolutionary operator selection

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