In order to quickly and accurately locate the fault location of the distribution network and increase the stability of the distribution network,a fault recovery method based on multi-objective optimization algorithm i...In order to quickly and accurately locate the fault location of the distribution network and increase the stability of the distribution network,a fault recovery method based on multi-objective optimization algorithm is proposed.The optimization of the power distribution network fault system based on multiagent technology realizes fast recovery of multi-objective fault,solve the problem of network learning and parameter adjustment in the later stage of particle swarm optimization algorithm falling into the local extreme value dilemma,and realize the multi-dimensional nonlinear optimization of the main grid and the auxiliary grid.The system proposed in this study takes power distribution network as the goal,applies fuzzy probability algorithm,simplifies the calculation process,avoids local extreme value,and finally realizes the energy balance between each power grid.Simulation results show that the Multi-Agent Technology enjoys priority in restoring important load,shortening the recovery time of power grid balance,and reducing the overall line loss rate of power grid.Therefore,the power grid fault self-healing system can improve the safety and stability of the important power grid,and reduce the economic loss rate of the whole power grid.展开更多
Distributed Data Mining is expected to discover preciously unknown, implicit and valuable information from massive data set inherently distributed over a network. In recent years several approaches to distributed data...Distributed Data Mining is expected to discover preciously unknown, implicit and valuable information from massive data set inherently distributed over a network. In recent years several approaches to distributed data mining have been developed, but only a few of them make use of intelligent agents. This paper provides the reason for applying Multi-Agent Technology in Distributed Data Mining and presents a Distributed Data Mining System based on Multi-Agent Technology that deals with heterogeneity in such environment. Based on the advantages of both the CS model and agent-based model, the system is being able to address the specific concern of increasing scalability and enhancing performance.展开更多
Traditional ERP software system cannot efficiently su pport new management ideas such as BPR, DEM and virtual enterprise which emphasi zes that enterprise should be adjusted to market changes and business process ch a...Traditional ERP software system cannot efficiently su pport new management ideas such as BPR, DEM and virtual enterprise which emphasi zes that enterprise should be adjusted to market changes and business process ch ain and value chain should be integrated tightly. To solve these problems, this paper proposed the conception of Flexible ERP system. F-ERP is a self- adapti ve software system based on multi-agent technology. It developed the followin g kind of agents which are useful for F-ERP: business process agent, interf ace agent, data agent and decision and analysis agent. The F-ERP software syste m is an hierarchy system which is composed of data layer, system tools layer, bu siness application layer and business decision layer. It used component based de velopment mythology and complied with CORBA to development F-ERP. The F-ERP sy stem can support the new management ideas such as BPR, DEM and virtual enterpris e etc. By implementation of it, enterprise can improve its management and promot e its competence.展开更多
The genetic microarrays give to researchers a huge amount of data of many diseases represented by intensities of gene expression. In genomic medicine gene expression analysis is guided to find strategies for preventio...The genetic microarrays give to researchers a huge amount of data of many diseases represented by intensities of gene expression. In genomic medicine gene expression analysis is guided to find strategies for prevention and treatment of diseases with high rate of mortality like the different cancers. So, genomic medicine requires the use of complex information technology. The purpose of our paper is to present a multi-agent system developed in order to improve gene expression analysis with the automation of tasks about identification of genes involved in a cancer, and classification of tumors according to molecular biology. Agents that integrate the system, carry out reading files of intensity data of genes from microarrays, pre-processing of this information, and with machine learning methods make groups of genes involved in the process of a disease as well as the classification of samples that could propose new subtypes of tumors difficult to identify based on their morphology. Our results we prove that the multi-agent system requires a minimal intervention of user, and the agents generate knowledge that reduce the time and complexity of the work of prevention and diagnosis, and thus allow a more effective treatment of tumors.展开更多
The health monitoring for large-scale structures need to resolve a large number of difficulties,such as the data transmission and distributing information handling.To solve these problems,the technology of multi-agent...The health monitoring for large-scale structures need to resolve a large number of difficulties,such as the data transmission and distributing information handling.To solve these problems,the technology of multi-agent is a good candidate to be used in the field of structural health monitoring.A structural health monitoring system architecture based on multi-agent technology is proposed.The measurement system for aircraft airfoil is designed with FBG,strain gage,and corresponding signal processing circuit.The experiment to determine the location of the concentrate loading on the structure is carried on with the system combined with technologies of pattern recognition and multi-agent.The results show that the system can locate the concentrate loading of the aircraft airfoil at the accuracy of 91.2%.展开更多
The moment a media delegation from the Republic of the Congo arrived at the Othello Kitchenware Museum on 18 November 2025,they were greeted with a vivid show of Guangdong’s industrial strength.Standing before them w...The moment a media delegation from the Republic of the Congo arrived at the Othello Kitchenware Museum on 18 November 2025,they were greeted with a vivid show of Guangdong’s industrial strength.Standing before them was not a typical exhibition hall,but a building shaped like a gleaming stainless-steel cooking pot.展开更多
Background:With the rapid development of modern emerging technologies,the ethical dilemmas and social controversies triggered by scientific and technological activities have become increasingly prominent.How to guide ...Background:With the rapid development of modern emerging technologies,the ethical dilemmas and social controversies triggered by scientific and technological activities have become increasingly prominent.How to guide technology for good and prevent and control technological risks has become an important issue of global concern.Research on science and technology ethics is dedicated to integrating ethical theories into governance practices and constructing ethical models that adapt to the development of the times.Methods:This article systematically reviews the six core approaches of scientific and technological ethics thought,including technological autonomy and political philosophy criticism,responsibility ethics and intergenerational obligations,technological intermediation and the integration of life and the world,ethical principles and normative frameworks,participatory governance and ethical practice innovation,as well as domain-specific ethical norms,thereby constructing an ethical analysis framework applicable to medical technology risks.And cross-analysis was conducted by taking medical events such as gene editing and xenotransplantation as examples.Results:Research shows that a single ethical approach has limitations in addressing complex medical ethical challenges,while the six approaches are complementary and synergistic.By criticizing technological autonomy,establishing a responsibility ethics orientation,setting the bottom line of ethical principles,promoting participatory governance,formulating domain norms,and continuously reflecting on the intermediary nature of technology,a multi-level and dynamically adaptive governance system for scientific and technological ethics can be constructed.Conclusion:The key to addressing contemporary medical ethics challenges lies in the comprehensive application of science and technology ethics theories and the integration of ethical considerations throughout the entire process of scientific and technological research and development.In the future,a governance framework that adapts to the development of new technologies should be established to promote cross-cultural and cross-disciplinary ethical dialogue and public participation,ensuring that scientific and technological innovation always serves the dignity of human life and overall well-being.展开更多
Against the backdrop of integrated development between technical education and higher vocational education,the teaching of Chinese Medicine Processing Technology courses faces new opportunities and challenges.This pap...Against the backdrop of integrated development between technical education and higher vocational education,the teaching of Chinese Medicine Processing Technology courses faces new opportunities and challenges.This paper analyzes the existing problems in the current teaching of Chinese Medicine Processing Technology courses,discusses the necessity of reforming the teaching model under the context of integration,and proposes the construction of a"Dual-Capability Progression,Six-Dimensional Empowerment"teaching model.The aim is to enhance the teaching quality of Chinese Medicine Processing Technology courses and cultivate high-quality skilled talents in Chinese medicine processing who can meet industry demands.展开更多
Detecting biomarkers in body fluids by optical lateral flow immune assay(LFIA) technology provides rapid access to disease information for early diagnosis.LFIA is based on an antigen-antibody reaction and is rapidly b...Detecting biomarkers in body fluids by optical lateral flow immune assay(LFIA) technology provides rapid access to disease information for early diagnosis.LFIA is based on an antigen-antibody reaction and is rapidly becoming the preferred choice of physicians and patients for point-of-care testing due to its simplicity,cost-effectiveness,and rapid detection.Observing the optical signal change from the colloidal gold of the traditional LFIA strip has been widely applied for various biomarkers detection in body fluids.Despite the significant progress,rapid real-time detection of color changes in the colloidal gold by the naked eye still faces many limitations,such as large errors and the inability to quantify and accurately detect.New optical LFIA strip technology has emerged in recent years to extend its application scenarios for achieving quantitative detection such as fluorescence,afterglow,and chemiluminescence.Herein,we summarized the development of optical LFIA technology from single to hyphenated optical signals for biomarkers detection in body fluids from invasive and non-invasive sources.Moreover,the challenge and outlook of optical LFIA strip technology are highlighted to inspire the designing of next-generation diagnostic platforms.展开更多
The Sn−2Al filler metal was utilized to bond W90 tungsten heavy alloys by the ultrasonic-assisted coating technology in atmospheric environment at 250℃.The effects of ultrasonic power and ultrasonic time on microstru...The Sn−2Al filler metal was utilized to bond W90 tungsten heavy alloys by the ultrasonic-assisted coating technology in atmospheric environment at 250℃.The effects of ultrasonic power and ultrasonic time on microstructure and interfacial strength of Sn−2Al/W90 interface were investigated.The ultrasound improved the wettability of Sn−2Al filler metal on W90 surface.As the ultrasonic power increased and ultrasonic time increased,the size of Al phase in seam decreased.The maximum value of Sn−2Al/W90 interfacial strength reached 30.1 MPa.Based on the acoustic pressure simulation and bubble dynamics,the intensity of cavitation effect was proportional to ultrasonic power.The generated high temperature and high pressure by cavitation effect reached 83799.6 K and 1.26×10^(14) Pa,respectively.展开更多
Following the theory of Multi Agent System (MAS) and using series wound structure and shunt wound structure of Agents, the performance of Agent was improved to satisfy the need of satellite fault diagnosis, and a trid...Following the theory of Multi Agent System (MAS) and using series wound structure and shunt wound structure of Agents, the performance of Agent was improved to satisfy the need of satellite fault diagnosis, and a tridimensional MAS model of satellite fault diagnosis was thus established for the MAS based planar diagnosis system, which decentralizes the whole diagnosing task into subtasks to be performed by different functional Agents to make the complicated fault diagnosis very simple and the diagnosis system more intelligent. This method improved the reliability and accuracy of diagnosis and made the maintenance and upgrading of the satellite fault diagnosis system very easy as well.展开更多
This paper studies mainly how to make use of Multi- Agent technology to solve the complex problems which are caused by unsuitable coordination between protection and untimely action and protection fault activity in la...This paper studies mainly how to make use of Multi- Agent technology to solve the complex problems which are caused by unsuitable coordination between protection and untimely action and protection fault activity in large power system, and realizes timely the coordination among protections effectively in when losing some or all information. Thus it overcomes the difficult of solving single or shore range information, enhances correspond and coordination among the intelligent protect Agent, raises the stable and reliable property, and promotes the process of power network for large area.展开更多
Terahertz biotechnology has been increasingly applied in various biomedical fields and has especially shown great potential for application in brain sciences.In this article,we review the development of terahertz biot...Terahertz biotechnology has been increasingly applied in various biomedical fields and has especially shown great potential for application in brain sciences.In this article,we review the development of terahertz biotechnology and its applications in the field of neuropsychiatry.Available evidence indicates promising prospects for the use of terahertz spectroscopy and terahertz imaging techniques in the diagnosis of amyloid disease,cerebrovascular disease,glioma,psychiatric disease,traumatic brain injury,and myelin deficit.In vitro and animal experiments have also demonstrated the potential therapeutic value of terahertz technology in some neuropsychiatric diseases.Although the precise underlying mechanism of the interactions between terahertz electromagnetic waves and the biosystem is not yet fully understood,the research progress in this field shows great potential for biomedical noninvasive diagnostic and therapeutic applications.However,the biosafety of terahertz radiation requires further exploration regarding its two-sided efficacy in practical applications.This review demonstrates that terahertz biotechnology has the potential to be a promising method in the field of neuropsychiatry based on its unique advantages.展开更多
Cooperative multi-agent reinforcement learning(MARL)is a key technology for enabling cooperation in complex multi-agent systems.It has achieved remarkable progress in areas such as gaming,autonomous driving,and multi-...Cooperative multi-agent reinforcement learning(MARL)is a key technology for enabling cooperation in complex multi-agent systems.It has achieved remarkable progress in areas such as gaming,autonomous driving,and multi-robot control.Empowering cooperative MARL with multi-task decision-making capabilities is expected to further broaden its application scope.In multi-task scenarios,cooperative MARL algorithms need to address 3 types of multi-task problems:reward-related multi-task,arising from different reward functions;multi-domain multi-task,caused by differences in state and action spaces,state transition functions;and scalability-related multi-task,resulting from the dynamic variation in the number of agents.Most existing studies focus on scalability-related multitask problems.However,with the increasing integration between large language models(LLMs)and multi-agent systems,a growing number of LLM-based multi-agent systems have emerged,enabling more complex multi-task cooperation.This paper provides a comprehensive review of the latest advances in this field.By combining multi-task reinforcement learning with cooperative MARL,we categorize and analyze the 3 major types of multi-task problems under multi-agent settings,offering more fine-grained classifications and summarizing key insights for each.In addition,we summarize commonly used benchmarks and discuss future directions of research in this area,which hold promise for further enhancing the multi-task cooperation capabilities of multi-agent systems and expanding their practical applications in the real world.展开更多
Subgrade engineering is a fundamental aspect of infrastructure construction in China.As the primary structural element responsible for bearing and distributing traffic loads,the subgrade must not only withstand the su...Subgrade engineering is a fundamental aspect of infrastructure construction in China.As the primary structural element responsible for bearing and distributing traffic loads,the subgrade must not only withstand the substantial pressures exerted by vehicles,trains,and other forms of transportation,but also efficiently transfer these loads to the underlying foundation,ensuring the stability and longevity of the roadway.In recent years,advancements in subgrade engineering technology have propelled the industry towards smarter,greener,and more sustainable practices,particularly in the areas of intelligent monitoring,disaster management,and innovative construction methods.This paper reviews the application and methodologies of intelligent testing equipment,including cone penetration testing(CPT)devices,soil resistivity testers,and intelligent rebound testers,in subgrade engineering.It examines the operating principles,advantages,limitations,and application ranges of these tools in subgrade testing.Additionally,the paper evaluates the practical use of advanced equipment from both domestic and international perspectives,addressing the challenges encountered by various instruments in realworld applications.These devices enable precise,comprehensive testing and evaluation of subgrade conditions at different stages,providing real-time data analysis and intelligent early warnings.This supports effective subgrade health management and maintenance.As intelligent technologies continue to evolve and integrate,these tools will increasingly enhance the accuracy,efficiency,and sustainability of subgrade monitoring.展开更多
As artificial intelligence(AI)technology has continued to develop,its efficient data processing and pattern recognition capabilities have significantly improved the precision and speed of decision-making processes,and...As artificial intelligence(AI)technology has continued to develop,its efficient data processing and pattern recognition capabilities have significantly improved the precision and speed of decision-making processes,and it has been widely applied across various fields.In the field of astronomy,AI techniques have demonstrated unique advantages,particularly in the identification of pulsars and their candidates.AI is able to address the challenges of pulsar celestial body identification and classification because of its accuracy and efficiency.This paper systematically surveys commonly used AI models for pulsar candidate identification,analyzing and discussing the typical applications of machine learning,artificial neural networks,convolutional neural networks,and generative adversarial networks in candidate identification.Furthermore,it explores how th.e introduction of AI techniques not only enhances the efficiency and accuracy of pulsar identification but also provides new perspectives and tools for pulsar survey data processing,thus playing a significant role in advancing pulsar research and the field of astronomy.展开更多
This paper addresses the consensus problem of nonlinear multi-agent systems subject to external disturbances and uncertainties under denial-ofservice(DoS)attacks.Firstly,an observer-based state feedback control method...This paper addresses the consensus problem of nonlinear multi-agent systems subject to external disturbances and uncertainties under denial-ofservice(DoS)attacks.Firstly,an observer-based state feedback control method is employed to achieve secure control by estimating the system's state in real time.Secondly,by combining a memory-based adaptive eventtriggered mechanism with neural networks,the paper aims to approximate the nonlinear terms in the networked system and efficiently conserve system resources.Finally,based on a two-degree-of-freedom model of a vehicle affected by crosswinds,this paper constructs a multi-unmanned ground vehicle(Multi-UGV)system to validate the effectiveness of the proposed method.Simulation results show that the proposed control strategy can effectively handle external disturbances such as crosswinds in practical applications,ensuring the stability and reliable operation of the Multi-UGV system.展开更多
This paper investigates the challenges associated with Unmanned Aerial Vehicle (UAV) collaborative search and target tracking in dynamic and unknown environments characterized by limited field of view. The primary obj...This paper investigates the challenges associated with Unmanned Aerial Vehicle (UAV) collaborative search and target tracking in dynamic and unknown environments characterized by limited field of view. The primary objective is to explore the unknown environments to locate and track targets effectively. To address this problem, we propose a novel Multi-Agent Reinforcement Learning (MARL) method based on Graph Neural Network (GNN). Firstly, a method is introduced for encoding continuous-space multi-UAV problem data into spatial graphs which establish essential relationships among agents, obstacles, and targets. Secondly, a Graph AttenTion network (GAT) model is presented, which focuses exclusively on adjacent nodes, learns attention weights adaptively and allows agents to better process information in dynamic environments. Reward functions are specifically designed to tackle exploration challenges in environments with sparse rewards. By introducing a framework that integrates centralized training and distributed execution, the advancement of models is facilitated. Simulation results show that the proposed method outperforms the existing MARL method in search rate and tracking performance with less collisions. The experiments show that the proposed method can be extended to applications with a larger number of agents, which provides a potential solution to the challenging problem of multi-UAV autonomous tracking in dynamic unknown environments.展开更多
基金This work is supported by the project of Hebei power technology of state grid from 2018 to 2019:Research and application of real-time situation assessment and visualization(SZKJXM20170445).
文摘In order to quickly and accurately locate the fault location of the distribution network and increase the stability of the distribution network,a fault recovery method based on multi-objective optimization algorithm is proposed.The optimization of the power distribution network fault system based on multiagent technology realizes fast recovery of multi-objective fault,solve the problem of network learning and parameter adjustment in the later stage of particle swarm optimization algorithm falling into the local extreme value dilemma,and realize the multi-dimensional nonlinear optimization of the main grid and the auxiliary grid.The system proposed in this study takes power distribution network as the goal,applies fuzzy probability algorithm,simplifies the calculation process,avoids local extreme value,and finally realizes the energy balance between each power grid.Simulation results show that the Multi-Agent Technology enjoys priority in restoring important load,shortening the recovery time of power grid balance,and reducing the overall line loss rate of power grid.Therefore,the power grid fault self-healing system can improve the safety and stability of the important power grid,and reduce the economic loss rate of the whole power grid.
文摘Distributed Data Mining is expected to discover preciously unknown, implicit and valuable information from massive data set inherently distributed over a network. In recent years several approaches to distributed data mining have been developed, but only a few of them make use of intelligent agents. This paper provides the reason for applying Multi-Agent Technology in Distributed Data Mining and presents a Distributed Data Mining System based on Multi-Agent Technology that deals with heterogeneity in such environment. Based on the advantages of both the CS model and agent-based model, the system is being able to address the specific concern of increasing scalability and enhancing performance.
文摘Traditional ERP software system cannot efficiently su pport new management ideas such as BPR, DEM and virtual enterprise which emphasi zes that enterprise should be adjusted to market changes and business process ch ain and value chain should be integrated tightly. To solve these problems, this paper proposed the conception of Flexible ERP system. F-ERP is a self- adapti ve software system based on multi-agent technology. It developed the followin g kind of agents which are useful for F-ERP: business process agent, interf ace agent, data agent and decision and analysis agent. The F-ERP software syste m is an hierarchy system which is composed of data layer, system tools layer, bu siness application layer and business decision layer. It used component based de velopment mythology and complied with CORBA to development F-ERP. The F-ERP sy stem can support the new management ideas such as BPR, DEM and virtual enterpris e etc. By implementation of it, enterprise can improve its management and promot e its competence.
文摘The genetic microarrays give to researchers a huge amount of data of many diseases represented by intensities of gene expression. In genomic medicine gene expression analysis is guided to find strategies for prevention and treatment of diseases with high rate of mortality like the different cancers. So, genomic medicine requires the use of complex information technology. The purpose of our paper is to present a multi-agent system developed in order to improve gene expression analysis with the automation of tasks about identification of genes involved in a cancer, and classification of tumors according to molecular biology. Agents that integrate the system, carry out reading files of intensity data of genes from microarrays, pre-processing of this information, and with machine learning methods make groups of genes involved in the process of a disease as well as the classification of samples that could propose new subtypes of tumors difficult to identify based on their morphology. Our results we prove that the multi-agent system requires a minimal intervention of user, and the agents generate knowledge that reduce the time and complexity of the work of prevention and diagnosis, and thus allow a more effective treatment of tumors.
基金supported by the Key Program of the National Science Foundation of China(50830201)Aviation Research Foundation(20060952)+1 种基金the National High Technology Research and Development of China(2007AA03Z117)the Natural Science Foundation of Jiansu Province(08kjd560009)
文摘The health monitoring for large-scale structures need to resolve a large number of difficulties,such as the data transmission and distributing information handling.To solve these problems,the technology of multi-agent is a good candidate to be used in the field of structural health monitoring.A structural health monitoring system architecture based on multi-agent technology is proposed.The measurement system for aircraft airfoil is designed with FBG,strain gage,and corresponding signal processing circuit.The experiment to determine the location of the concentrate loading on the structure is carried on with the system combined with technologies of pattern recognition and multi-agent.The results show that the system can locate the concentrate loading of the aircraft airfoil at the accuracy of 91.2%.
文摘The moment a media delegation from the Republic of the Congo arrived at the Othello Kitchenware Museum on 18 November 2025,they were greeted with a vivid show of Guangdong’s industrial strength.Standing before them was not a typical exhibition hall,but a building shaped like a gleaming stainless-steel cooking pot.
基金supported by the National Key Research and Development Program(Grant No.2024YFA0917200)the Projects of the Chinese Center for Disease Control and Prevention(Grant No.BB2110240093)World Medical History under the Education Innovation Plan of the University of Science and Technology of China(Grant No.2024YCHX07).
文摘Background:With the rapid development of modern emerging technologies,the ethical dilemmas and social controversies triggered by scientific and technological activities have become increasingly prominent.How to guide technology for good and prevent and control technological risks has become an important issue of global concern.Research on science and technology ethics is dedicated to integrating ethical theories into governance practices and constructing ethical models that adapt to the development of the times.Methods:This article systematically reviews the six core approaches of scientific and technological ethics thought,including technological autonomy and political philosophy criticism,responsibility ethics and intergenerational obligations,technological intermediation and the integration of life and the world,ethical principles and normative frameworks,participatory governance and ethical practice innovation,as well as domain-specific ethical norms,thereby constructing an ethical analysis framework applicable to medical technology risks.And cross-analysis was conducted by taking medical events such as gene editing and xenotransplantation as examples.Results:Research shows that a single ethical approach has limitations in addressing complex medical ethical challenges,while the six approaches are complementary and synergistic.By criticizing technological autonomy,establishing a responsibility ethics orientation,setting the bottom line of ethical principles,promoting participatory governance,formulating domain norms,and continuously reflecting on the intermediary nature of technology,a multi-level and dynamically adaptive governance system for scientific and technological ethics can be constructed.Conclusion:The key to addressing contemporary medical ethics challenges lies in the comprehensive application of science and technology ethics theories and the integration of ethical considerations throughout the entire process of scientific and technological research and development.In the future,a governance framework that adapts to the development of new technologies should be established to promote cross-cultural and cross-disciplinary ethical dialogue and public participation,ensuring that scientific and technological innovation always serves the dignity of human life and overall well-being.
基金Supported by Scientific Research Fund Project of Yunnan Provincial Department of Education(2025J1950).
文摘Against the backdrop of integrated development between technical education and higher vocational education,the teaching of Chinese Medicine Processing Technology courses faces new opportunities and challenges.This paper analyzes the existing problems in the current teaching of Chinese Medicine Processing Technology courses,discusses the necessity of reforming the teaching model under the context of integration,and proposes the construction of a"Dual-Capability Progression,Six-Dimensional Empowerment"teaching model.The aim is to enhance the teaching quality of Chinese Medicine Processing Technology courses and cultivate high-quality skilled talents in Chinese medicine processing who can meet industry demands.
基金supported by the National Natural Science Foundation of China (Nos.22234005,22494632,22404081)the Natural Science Foundation of Jiangsu Province (Nos.BK20222015,BK20240534)。
文摘Detecting biomarkers in body fluids by optical lateral flow immune assay(LFIA) technology provides rapid access to disease information for early diagnosis.LFIA is based on an antigen-antibody reaction and is rapidly becoming the preferred choice of physicians and patients for point-of-care testing due to its simplicity,cost-effectiveness,and rapid detection.Observing the optical signal change from the colloidal gold of the traditional LFIA strip has been widely applied for various biomarkers detection in body fluids.Despite the significant progress,rapid real-time detection of color changes in the colloidal gold by the naked eye still faces many limitations,such as large errors and the inability to quantify and accurately detect.New optical LFIA strip technology has emerged in recent years to extend its application scenarios for achieving quantitative detection such as fluorescence,afterglow,and chemiluminescence.Herein,we summarized the development of optical LFIA technology from single to hyphenated optical signals for biomarkers detection in body fluids from invasive and non-invasive sources.Moreover,the challenge and outlook of optical LFIA strip technology are highlighted to inspire the designing of next-generation diagnostic platforms.
基金supported by the National Natural Science Foundation of China(Nos.52105330,52175307)the Natural Science Foundation of Shandong Province,China(No.ZR2023JQ021)。
文摘The Sn−2Al filler metal was utilized to bond W90 tungsten heavy alloys by the ultrasonic-assisted coating technology in atmospheric environment at 250℃.The effects of ultrasonic power and ultrasonic time on microstructure and interfacial strength of Sn−2Al/W90 interface were investigated.The ultrasound improved the wettability of Sn−2Al filler metal on W90 surface.As the ultrasonic power increased and ultrasonic time increased,the size of Al phase in seam decreased.The maximum value of Sn−2Al/W90 interfacial strength reached 30.1 MPa.Based on the acoustic pressure simulation and bubble dynamics,the intensity of cavitation effect was proportional to ultrasonic power.The generated high temperature and high pressure by cavitation effect reached 83799.6 K and 1.26×10^(14) Pa,respectively.
文摘Following the theory of Multi Agent System (MAS) and using series wound structure and shunt wound structure of Agents, the performance of Agent was improved to satisfy the need of satellite fault diagnosis, and a tridimensional MAS model of satellite fault diagnosis was thus established for the MAS based planar diagnosis system, which decentralizes the whole diagnosing task into subtasks to be performed by different functional Agents to make the complicated fault diagnosis very simple and the diagnosis system more intelligent. This method improved the reliability and accuracy of diagnosis and made the maintenance and upgrading of the satellite fault diagnosis system very easy as well.
基金Province natural science fund in Guangdong subsidizes item(05300167)
文摘This paper studies mainly how to make use of Multi- Agent technology to solve the complex problems which are caused by unsuitable coordination between protection and untimely action and protection fault activity in large power system, and realizes timely the coordination among protections effectively in when losing some or all information. Thus it overcomes the difficult of solving single or shore range information, enhances correspond and coordination among the intelligent protect Agent, raises the stable and reliable property, and promotes the process of power network for large area.
基金supported by grants from the National Key R&D Program of China,No.2017YFC0909200(to DC)the National Natural Science Foundation of China,No.62075225(to HZ)+1 种基金Zhejiang Provincial Medical Health Science and Technology Project,No.2023XY053(to ZP)Zhejiang Provincial Traditional Chinese Medical Science and Technology Project,No.2023ZL703(to ZP).
文摘Terahertz biotechnology has been increasingly applied in various biomedical fields and has especially shown great potential for application in brain sciences.In this article,we review the development of terahertz biotechnology and its applications in the field of neuropsychiatry.Available evidence indicates promising prospects for the use of terahertz spectroscopy and terahertz imaging techniques in the diagnosis of amyloid disease,cerebrovascular disease,glioma,psychiatric disease,traumatic brain injury,and myelin deficit.In vitro and animal experiments have also demonstrated the potential therapeutic value of terahertz technology in some neuropsychiatric diseases.Although the precise underlying mechanism of the interactions between terahertz electromagnetic waves and the biosystem is not yet fully understood,the research progress in this field shows great potential for biomedical noninvasive diagnostic and therapeutic applications.However,the biosafety of terahertz radiation requires further exploration regarding its two-sided efficacy in practical applications.This review demonstrates that terahertz biotechnology has the potential to be a promising method in the field of neuropsychiatry based on its unique advantages.
基金The National Natural Science Foundation of China(62136008,62293541)The Beijing Natural Science Foundation(4232056)The Beijing Nova Program(20240484514).
文摘Cooperative multi-agent reinforcement learning(MARL)is a key technology for enabling cooperation in complex multi-agent systems.It has achieved remarkable progress in areas such as gaming,autonomous driving,and multi-robot control.Empowering cooperative MARL with multi-task decision-making capabilities is expected to further broaden its application scope.In multi-task scenarios,cooperative MARL algorithms need to address 3 types of multi-task problems:reward-related multi-task,arising from different reward functions;multi-domain multi-task,caused by differences in state and action spaces,state transition functions;and scalability-related multi-task,resulting from the dynamic variation in the number of agents.Most existing studies focus on scalability-related multitask problems.However,with the increasing integration between large language models(LLMs)and multi-agent systems,a growing number of LLM-based multi-agent systems have emerged,enabling more complex multi-task cooperation.This paper provides a comprehensive review of the latest advances in this field.By combining multi-task reinforcement learning with cooperative MARL,we categorize and analyze the 3 major types of multi-task problems under multi-agent settings,offering more fine-grained classifications and summarizing key insights for each.In addition,we summarize commonly used benchmarks and discuss future directions of research in this area,which hold promise for further enhancing the multi-task cooperation capabilities of multi-agent systems and expanding their practical applications in the real world.
基金supported by the National Natural Science Foundation of China for Distinguished Young Scholars(Grant No.42225206)National Natural Science Foundation of China(42207180,42477209,42302320).
文摘Subgrade engineering is a fundamental aspect of infrastructure construction in China.As the primary structural element responsible for bearing and distributing traffic loads,the subgrade must not only withstand the substantial pressures exerted by vehicles,trains,and other forms of transportation,but also efficiently transfer these loads to the underlying foundation,ensuring the stability and longevity of the roadway.In recent years,advancements in subgrade engineering technology have propelled the industry towards smarter,greener,and more sustainable practices,particularly in the areas of intelligent monitoring,disaster management,and innovative construction methods.This paper reviews the application and methodologies of intelligent testing equipment,including cone penetration testing(CPT)devices,soil resistivity testers,and intelligent rebound testers,in subgrade engineering.It examines the operating principles,advantages,limitations,and application ranges of these tools in subgrade testing.Additionally,the paper evaluates the practical use of advanced equipment from both domestic and international perspectives,addressing the challenges encountered by various instruments in realworld applications.These devices enable precise,comprehensive testing and evaluation of subgrade conditions at different stages,providing real-time data analysis and intelligent early warnings.This supports effective subgrade health management and maintenance.As intelligent technologies continue to evolve and integrate,these tools will increasingly enhance the accuracy,efficiency,and sustainability of subgrade monitoring.
基金supported by the National Key R&D Program of China(2021YFC2203502 and 2022YFF0711502)the National Natural Science Foundation of China(NSFC)(12173077)+4 种基金the Tianshan Talent Project of Xinjiang Uygur Autonomous Region(2022TSYCCX0095 and 2023TSYCCX0112)the Scientific Instrument Developing Project of the Chinese Academy of Sciences(PTYQ2022YZZD01)China National Astronomical Data Center(NADC)the Operation,Maintenance and Upgrading Fund for Astronomical Telescopes and Facility Instruments,budgeted from the Ministry of Finance of China(MOF)and administrated by the Chinese Academy of Sciences(CAS)Natural Science Foundation of Xinjiang Uygur Autonomous Region(2022D01A360)。
文摘As artificial intelligence(AI)technology has continued to develop,its efficient data processing and pattern recognition capabilities have significantly improved the precision and speed of decision-making processes,and it has been widely applied across various fields.In the field of astronomy,AI techniques have demonstrated unique advantages,particularly in the identification of pulsars and their candidates.AI is able to address the challenges of pulsar celestial body identification and classification because of its accuracy and efficiency.This paper systematically surveys commonly used AI models for pulsar candidate identification,analyzing and discussing the typical applications of machine learning,artificial neural networks,convolutional neural networks,and generative adversarial networks in candidate identification.Furthermore,it explores how th.e introduction of AI techniques not only enhances the efficiency and accuracy of pulsar identification but also provides new perspectives and tools for pulsar survey data processing,thus playing a significant role in advancing pulsar research and the field of astronomy.
基金The National Natural Science Foundation of China(W2431048)The Science and Technology Research Program of Chongqing Municipal Education Commission,China(KJZDK202300807)The Chongqing Natural Science Foundation,China(CSTB2024NSCQQCXMX0052).
文摘This paper addresses the consensus problem of nonlinear multi-agent systems subject to external disturbances and uncertainties under denial-ofservice(DoS)attacks.Firstly,an observer-based state feedback control method is employed to achieve secure control by estimating the system's state in real time.Secondly,by combining a memory-based adaptive eventtriggered mechanism with neural networks,the paper aims to approximate the nonlinear terms in the networked system and efficiently conserve system resources.Finally,based on a two-degree-of-freedom model of a vehicle affected by crosswinds,this paper constructs a multi-unmanned ground vehicle(Multi-UGV)system to validate the effectiveness of the proposed method.Simulation results show that the proposed control strategy can effectively handle external disturbances such as crosswinds in practical applications,ensuring the stability and reliable operation of the Multi-UGV system.
基金supported by the National Natural Science Foundation of China(Nos.12272104,U22B2013).
文摘This paper investigates the challenges associated with Unmanned Aerial Vehicle (UAV) collaborative search and target tracking in dynamic and unknown environments characterized by limited field of view. The primary objective is to explore the unknown environments to locate and track targets effectively. To address this problem, we propose a novel Multi-Agent Reinforcement Learning (MARL) method based on Graph Neural Network (GNN). Firstly, a method is introduced for encoding continuous-space multi-UAV problem data into spatial graphs which establish essential relationships among agents, obstacles, and targets. Secondly, a Graph AttenTion network (GAT) model is presented, which focuses exclusively on adjacent nodes, learns attention weights adaptively and allows agents to better process information in dynamic environments. Reward functions are specifically designed to tackle exploration challenges in environments with sparse rewards. By introducing a framework that integrates centralized training and distributed execution, the advancement of models is facilitated. Simulation results show that the proposed method outperforms the existing MARL method in search rate and tracking performance with less collisions. The experiments show that the proposed method can be extended to applications with a larger number of agents, which provides a potential solution to the challenging problem of multi-UAV autonomous tracking in dynamic unknown environments.
