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Ferritin nanocages for early theranostics of tumors via inflammation-enhanced active targeting

Science China(Life Sciences) 2022年第2期65卷 328-340页

作者： Bing Jiang Xiaohua Jia Tianjiao Ji Meng Zhou Jiuyang He Kun Wang Jie Tian Xiyun Yan Kelong Fan Nanozyme Medical Center School of Basic Medical SciencesZhengzhou UniversityZhengzhou 450001China CAS Engineering Laboratory for Nanozyme Key Laboratory of Protein and Peptide PharmaceuticalsInstitute of BiophysicsChinese Academy of SciencesBeijing 100101China Key Laboratory of Molecular Imaging of Chinese Academy of Sciences Institute of AutomationChinese Academy of SciencesBeijing 100190China CAS Key Laboratory for Biomedical Effects of Nanomaterials&Nanosafety CAS Center for Excellence in NanoscienceNational Center for Nanoscience and TechnologyBeijing 100190China Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of SciencesBeijing 100049China Beijing Advanced Innovation Center for Big Data-Based Precision Medicine School of MedicineBeihang UniversityBeijing 100191China

Engineered nanocarriers have been widely developed for tumor ***,the delivery of imaging probes or therapeutic drugs to the tumor pre-formation site for early and accurate detection and therapy remains a major ***,by using tailor-functionalized human H-ferritin(HFn),we developed a triple-modality nanoprobe IRdye800-M-HFn and achieved the early imaging of tumor cells before the formation of solid tumor ***,we developed an HFn-doxorubicin(Dox)drug delivery system by loading Dox into the HFn protein cage and achieved early-stage tumor *** intravenous injection of HFn nanoprobes enabled the imaging of tumor cells as early as two days after tumor implantation,and the triple-modality imaging techniques,namely,near-infrared fluorescence molecular imaging(NIR-FMI),magnetic resonance imaging(MRI),and photoacoustic imaging(PAI),ensured the accuracy of *** exploration indicated that HFn could specifically penetrate into pre-solid tumor sites by tumor-associated inflammation-mediated blood vessel leakage,followed by effective accumulation in tumor cells by the specific targeting property of HFn to transferrin receptor ***,the HFn-Dox drug delivery system delivered Dox into the tumor pre-formation site and effectively killed tumor cells at early ***800-M-HFn nanoprobes and HFn-Dox provide promising strategies for early-stage tumor diagnosis and constructive implications for early-stage tumor treatment.

关键词： ferritin nanocage early theranostics tumor-associated inflammation multimodality tumor imaging drug delivery

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A Region Enhanced Discrete Multi-Objective Fireworks Algorithm for Low-Carbon Vehicle Routing Problem

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Complex System Modeling and Simulation 2022年第2期2卷 142-155页

作者： Xiaoning Shen Jiaqi Lu Xuan You Liyan Song Zhongpei Ge Collaborative Innovation Center of Atmospheric Environment and Equipment Technology Jiangsu Key Laboratory of Big Data Analysis TechnologySchool of AutomationNanjing University of Information Science and TechnologyNanjing 210044China School of Automation Nanjing University of Information Science and TechnologyNanjing 210044China Institute of Trustworthy Autonomous Systems and also with the Guangdong Provincial Key Laboratory of Brain-Inspired Intelligent ComputationDepartment of Computer Science and EngineeringSouthern University of Science and TechnologyShenzhen 518055China

A constrained multi-objective optimization model for the low-carbon vehicle routing problem(VRP)is established.A carbon emission measurement method considering various practical factors is *** minimizes both the total carbon emissions and the longest time consumed by the sub-tours,subject to the limited number of available *** to the characteristics of the model,a region enhanced discrete multi-objective fireworks algorithm is proposed.A partial mapping explosion operator,a hybrid mutation for adjusting the sub-tours,and an objective-driven extending search are designed,which aim to improve the convergence,diversity,and spread of the non-dominated solutions produced by the algorithm,*** low-carbon VRP instances with different scales are used to verify the effectiveness of the new ***,comparison results with four state-of-the-art algorithms indicate that the proposed algorithm has better performance of convergence and distribution on the low-carbon *** provides a promising scalability to the problem size.

关键词： vehicle routing problem carbon emission multi-objective optimization fireworks algorithm region enhanced

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V2I Based Environment Perception for Autonomous Vehicles at Intersections

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China Communications 2021年第7期18卷 1-12页

作者： Xuting Duan Hang Jiang Daxin Tian Tianyuan Zou Jianshan Zhou Yue Cao Beijing Advanced Innovation Center for Big Data and Brain Computing Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems&Safety ControlSchool of Transportation Science and EngineeringBeihang UniversityBeijing 100191China School of Cyber Science and Engineering Wuhan UniversityWuhan 430072China

In recent years,autonomous driving technology has made good progress,but the noncooperative intelligence of vehicle for autonomous driving still has many technical bottlenecks when facing urban road autonomous driving challenges.V2I(Vehicle-to-Infrastructure)communication is a potential solution to enable cooperative intelligence of vehicles and *** this paper,the RGB-PVRCNN,an environment perception framework,is proposed to improve the environmental awareness of autonomous vehicles at intersections by leveraging V2I communication *** framework integrates vision feature based on *** normal distributions transform(NDT)point cloud registration algorithm is deployed both on onboard and roadside to obtain the position of the autonomous vehicles and to build the local map objects detected by roadside multi-sensor system are sent back to autonomous vehicles to enhance the perception ability of autonomous vehicles for benefiting path planning and traffic efficiency at the *** field-testing results show that our method can effectively extend the environmental perception ability and range of autonomous vehicles at the intersection and outperform the PointPillar algorithm and the VoxelRCNN algorithm in detection accuracy.

关键词： V2I environmental perception autonomous vehicles 3D objects detection

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BMDP:Blockchain-Based Multi-Cloud Storage data Provenance

BMDP:Blockchain-Based Multi-Cloud Storage Data Provenance

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International Conference on Computer Supported Cooperative Work in Design

作者： Feiyu Wang Jian-Tao Zhou Xu Guo College of Computer Science Inner Mongolia University Hohhot Inner Mongolia China Inner Mongolia Engineering Laboratory for Cloud Computing and Service Software Engineering Research Center of Ecological Big Data Ministry of Education National & Local Joint Engineering Research Center of Intelligent Information Processing Technology for Mongolian Inner Mongolia Key Laboratory of Social Computing and Data Processing Inner Mongolia Engineering Laboratory for Big Data Analysis Technology China

In a multi-cloud storage system, provenance data records all operations and ownership during its lifecycle, which is critical for data security and audibility. However, recording provenance data also poses some challenging security and storage issues. In this paper, we present a secure and efficient multi-cloud storage data source scheme, BMDP. We use blockchain technology to ensure the secure storage of provenance data and design a smart contract to utilize the provenance data to ensure the proper operation of the multi-cloud storage system. Finally, we analyze the scheme’s safety and do simulation experiments to show that the scheme has practicality.

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UAV-Assisted Joint Mobile Edge Computing and data Collection via Matching-Enabled Deep Reinforcement Learning

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IEEE Internet of Things Journal 2025年

作者： Wang, Boxiong Kang, Hui Li, Jiahui Sun, Geng Sun, Zemin Jilin University College of Computer Science and Technology Changchun130012 China Jilin University Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Changchun130012 China Nanyang Technological University College of Computing and Data Science 639798 Singapore

Unmanned aerial vehicle (UAV)-assisted mobile edge computing (MEC) and data collection (DC) have been popular research issues. Different from existing works that consider MEC and DC scenarios separately, this paper investigates a multi-UAV-assisted joint MEC-DC system. Specifically, we formulate a joint optimization problem to minimize the MEC latency and maximize the collected data volume. This problem can be classified as a non-convex mixed integer programming problem that exhibits long-term optimization and dynamics. Thus, we propose a deep reinforcement learning-based approach that jointly optimizes the UAV movement, user transmit power, and user association in real time to solve the problem efficiently. Specifically, we reformulate the optimization problem into an action space-reduced Markov decision process (MDP) and optimize the user association by using a two-phase matching-based association (TMA) strategy. Subsequently, we propose a soft actor-critic (SAC)-based approach that integrates the proposed TMA strategy (SAC-TMA) to solve the formulated joint optimization problem collaboratively. Simulation results demonstrate that the proposed SAC-TMA is able to coordinate the two subsystems and can effectively reduce the system latency and improve the data collection volume compared with other benchmark algorithms. © 2025 IEEE. All rights reserved,

关键词： Unmanned aerial vehicles (UAV)

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Research on Visualization Algorithm of Association Rules Based on Concept Lattice

Research on Visualization Algorithm of Association Rules Bas...

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2020 International Conference on Cyberspace Innovation of Advanced Technologies, CIAT 2020

作者： Shen, Xiajiong Bao, Lijie Zhang, Lei Institute of Data and Knowledge Engineering Henan University Kaifeng China Henan Key Laboratory of Big Data Analysis and Processing Henan University Kaifeng China

ISBN: (纸本)9781450387828

The traditional association rule representation method has no way to show the essential relationship between concepts and lacks understanding of the concept level. Concept lattice is a kind of data structure which can show the relationship between concepts, concept lattice also has unique advantages in the visualization and discovery of potential knowledge of association rules. In this paper, a visualization algorithm of association rules based on concept lattice is proposed. The algorithm visually displays the association rules extracted from concept lattice. Finally, this article combines the chronic disease record data of a certain hospital to analyze and visualize the association rules. The implementation results show that the visualization method has good effects in knowledge analysis and data display. © 2020 ACM.

关键词： Visualization

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Review of graph construction and graph learning in stock price prediction

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Procedia Computer Science 2022年 214卷 771-778页

作者： Yunong Wang Yi Qu Zhensong Chen Research Center on Fictitious Economy and Data Science Chinese Academy of Sciences Beijing 100190 China Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences Beijing 100190 China School of Management and Engineering Capital University of Economics and Business Beijing 100070 China

Precise prediction of stock prices leads to more profits and more effective risk prevention, which is of great significance to both investors and regulators. Recent years, various kinds of information not directly-relevant with stock prices have received more attention, such as texts, images or connections. These external information has the potential of reflecting or influencing fluctuations, and thus, given the utilization of advanced analyzing techniques, the forecasting performance of stock prices could be promoted substantially. For instance, graph neural network models have expanded into many other disciplines including stock price prediction, and exhibited impressive representation learning ability. However, in stock markets, well-defined graphs are rarely seen and how to formulate the graph structures needed remains a challenging problem. Towards this end, this article presents a comprehensive overview of graph construction and graph learning in stock price prediction, by reviewing the existing studies, summarizing its general paradigm, special cases and proposing possible prospects. Our research not only systematically reveals the feasible ways of constructing graphs in financial markets, but also provides insights for further implementations of graph learning models into stock prediction tasks.

关键词： Stock price prediction Graph construction Graph learning data structure

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Vision Transformer Based Hash Coding for Efficient Image and Audio Retrieval with Global and Local Equilibrium Distance Constraints

Vision Transformer Based Hash Coding for Efficient Image and...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Ye Liu Yan Pan Jian Yin School of Computer Science and Engineering Sun Yat-sen University Guangzhou China Guangdong Key Laboratory of Big Data Analysis and Processing Guangzhou China Artificial Intelligence and Big Data Department Lizhi Inc. Beijing & Guangzhou China School of Artificial Intelligence Sun Yat-sen University Zhuhai China

ISBN: (数字)9781665410205

ISBN: (纸本)9781665410212

With the application of efficient retrieval in information systems and retrieval augmented generation with vector database for large language models, hash coding algorithms have made progress in recent years. The rise of transformer technology in the field of deep learning has brought the possibility to further improve the effect of hash coding algorithms. We introduce the vision transformer framework to both images and audios, and propose a novel approach for the tasks of multi-label image retrieval and audio event retrieval. In the proposed hash coding model, global and local equilibrium distance constraints are integrated, so that the hash codes for images can be better obtained through the global hash centers and local similar samples. In order to realize end-to-end training and hash code generation for audios, we adopt the adapter of mel spectrogram, thus the proposed approach can be simply converted and applied to audio hash coding. Comparative experiments verify that better results can be achieved on multiple image and audio datasets.

关键词： Training Computer vision Image coding Codes Large language models Image retrieval Transformers Encoding Vectors Spectrogram

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Trim21 depletion alleviates bone loss in osteoporosis via activation of YAP1/β-catenin signaling

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Bone Research 2023年第4期11卷 819-833页

作者： Ri-Xu Liu Rong-He Gu Zhi-Peng Li Zhi-Quan Hao Qin-Xiao Hu Zhen-Yan Li Xiao-Gang Wang Wang Tang Xiao-He Wang Yu-Kai Zeng Zhen-Wei Li Qiu Dong Xiao-Feng Zhu Di Chen Ke-Wei Zhao Rong-Hua Zhang Zhen-Gang Zha Huan-Tian Zhang Department of Bone and Joint Surgery the First Affiliated Hospital of Jinan UniversityKey Laboratory of Regenerative Medicine of Ministry of EducationJinan UniversityGuangzhou 510630 GuangdongChina Department of Orthopedic and Spine Surgery The First Affiliated Hospital of Guangzhou Medical UniversityGuangzhou 510120 GuangdongChina School of Basic Medical Sciences of Guangxi Medical University the Fifth Affiliated Hospital of Guangxi Medical UniversityNanning 530022 GuangxiChina Key Laboratory of Big Data-Based Precision Medicine School of Engineering MedicineBeihang University100191 BeijingChina Guangdong Provincial Key Laboratory of Traditional Chinese Medicine Informatization College of PharmacyJinan UniversityGuangzhou 510630 GuangdongChina Research Center for Computer-aided Drug Discovery Shenzhen Institute of Advanced TechnologyChinese Academy of Sciences518005 ShenzhenChina Guangzhou Key Laboratory of Chinese Medicine Research on Prevention and Treatment of Osteoporosis the Third Affiliated Hospital of Guangzhou University of Chinese Medicine510375 GuangzhouChina

Despite the diverse roles of tripartite motif(Trim)-containing proteins in the regulation of autophagy,the innate immune response,and cell differentiation,their roles in skeletal diseases are largely *** recently demonstrated that Trim21 plays a crucial role in regulating osteoblast(OB)differentiation in ***,how Trim21 contributes to skeletal degenerative disorders,including osteoporosis,remains ***,human and mouse bone specimens were evaluated,and the results showed that Trim21 expression was significantly elevated in bone tissues obtained from osteoporosis ***,we found that global knockout of the Trim21 gene(KO,Trim2^(1-/-))resulted in higher bone mass compared to that of the control *** further demonstrated that loss of Trim21 promoted bone formation by enhancing the osteogenic differentiation of bone marrow mesenchymal stem cells(BMSCs)and elevating the activity of OBs;moreover,Trim21 depletion suppressed osteoclast(OC)formation of RAW264.7 *** addition,the differentiation of OCs from bone marrow-derived macrophages(BMMs)isolated from Trim21^(-/-)and Ctsk-cre;Trim21^(f/f)mice was largely compromised compared to that of the littermate control ***,YAP1/β-catenin signaling was identified and demonstrated to be required for the Trim21-mediated osteogenic differentiation of *** importantly,the loss of Trim21 prevented ovariectomy(OVX)-and lipopolysaccharide(LPS)-induced bone loss in vivo by orchestrating the coupling of OBs and OCs through YAP1 *** current study demonstrated that Trim21 is crucial for regulating OB-mediated bone formation and OC-mediated bone resorption,thereby providing a basis for exploring Trim21 as a novel dual-targeting approach for treating osteoporosis and pathological bone loss.

关键词： YAP1 osteoporosis depletion

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Flooded Cropland Mapping Based on GF-3 and Mapbox Imagery Using Semantic Segmentation: A Case Study of Typhoon Siamba in Western Guangdong in July 2022

Flooded Cropland Mapping Based on GF-3 and Mapbox Imagery Us...

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2022 International Conference on Geographic Information and Remote Sensing Technology, GIRST 2022

作者： Ku, Mengjun Jiang, Hao Li, Dan Wang, Chongyang Key Lab of Guangdong for Utilization of Remote Sensing and Geographical Information System Guangdong Open Laboratory of Geospatial Information Technology and Application Research Center of Guangdong Province for Engineering Technology Application of Remote Sensing Big Data Guangzhou Institute of Geography Guangdong Academy of Sciences Guangzhou510070 China Guangdong University of Technology Guangzhou China

ISBN: (纸本)9781510662186

Typhoon Siamba made landfall in Western Guangdong on July 2, 2022, causing great losses to crops in western Guangdong. Radar remote sensing can penetrate through clouds and fog, is suitable for identifying flooded areas before or after typhoons and in rainy weather. However, radar flooded waterbody mapping faces two major problems: distinguishing between flooded areas and natural waterbody, and the other is noise interference from confusing ground objects. Aiming at these problems, the study proposes a method of high-precision cropland information combined with waterbody identification. Based on GF-3 and Mapbox data, this paper first uses watershed semantic segmentation to extract initial waterbody, then uses SegFormer deep learning technology to identify cropland, finally realizes flooded cropland mapping based on cropland information. This study concluded that the affected cropland in Zhanjiang and Maoming City, Guangdong Province, China is 75.437 km2 and 31.175 km2 respectively. The cropland extraction accuracy and Intersection over Union (IoU) are 96.65% and 92.64% respectively. The study shows that flood monitoring combined with cropland identification information can effectively avoid noise interference and accurately extract the flood range, and achieve high-precision flooded cropland mapping. © 2023 SPIE.

关键词： Watersheds

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