In the era of intelligent media,the interaction between teachers and students in higher education is undergoing a profound transformation.The model has shifted from one-way transmission to multi-agent,two-way collabor...In the era of intelligent media,the interaction between teachers and students in higher education is undergoing a profound transformation.The model has shifted from one-way transmission to multi-agent,two-way collaboration involving“teacher-student-AI(artificial intelligence)”.Interaction depth moves from surface Q&A to deep thought engagement,supported by instant,precise feedback and a blended virtual-physical space.New forms such as data-driven personalized interaction and immersive collaborative learning have emerged.However,this evolution brings significant challenges:over-reliance on technology may weaken cognitive autonomy;virtual interaction risks emotional detachment and trust erosion;ethical concerns like algorithmic bias and data privacy arise;teachers’roles become blurred;and evaluation systems lag behind technological advances.Future pathways should position AI as a supportive tool while upholding human centrality.Strengthening emotional connection through online-offline blending,reforming assessment to value process and growth,and empowering teachers as digitally literate“learning guides”and“emotional connectors”are key to building a healthy,sustainable interactive ecosystem.展开更多
In the modern higher education music curriculum system,the teacher-student interaction mode is a key factor affecting the effectiveness of piano teaching.However,the current teacher-student interaction mode in piano t...In the modern higher education music curriculum system,the teacher-student interaction mode is a key factor affecting the effectiveness of piano teaching.However,the current teacher-student interaction mode in piano teaching still has limitations,such as one-way transmission and a lack of personalized feedback.Based on constructivist learning theory and social interaction theory,combined with information technology,this paper explores the optimization strategy of interaction mode in the piano teaching process of normal universities.This study adopts classroom observation and interview methods to analyze the impact of different interaction modes on students’piano learning effectiveness,learning engagement,and autonomous learning ability.The research results show that the constructivist interactive teaching mode supported by information technology can significantly enhance students’interest in learning and playing skills,optimize the classroom teaching atmosphere,and promote the improvement of their comprehensive literacy.展开更多
To address the challenges of multi-scale differences,complex background interference,and unstable small target positioning in visual inspection of power towers,the existing methods still face issues such as insufficie...To address the challenges of multi-scale differences,complex background interference,and unstable small target positioning in visual inspection of power towers,the existing methods still face issues such as insufficient feature interaction and unstable confidence estimation,which lead to performance degradation in complex backgrounds and occlusion conditions.This paper proposes a precise inspection method for key power tower components using autonomous drone positioning.To this end,this paper makes three key improvements to the you only look once version 11(YOLOv11)framework.First,it constructs C3k2-adaptive multi-receptive field block(C3k2-AMRB),combining multiple dilated convolutions with a reparameterization mechanism to significantly expand the receptive field and enhance multi-scale feature extraction.Second,it designs a hierarchical wavelet interaction unit(HWIU),which leverages high-and low-frequency decomposition and reconstruction of wavelet transform(WT)to achieve cross-scale semantic alignment,enhancing feature discriminability in complex backgrounds.Third,it proposes a distribution-aware confidence refinement head(DACR-Head),which adaptively calibrates classification confidence based on the statistical characteristics of the predicted bounding-box corner distribution,improving the localization stability and accuracy of small targets.Experiments on the inspection of power line assets dataset(InsPLAD)dataset show that the integrated approach achieves a component detection accuracy at intersection over union(IoU)=0.5(CDA_(50))of 88.3%and a component detection robustness(CDR_(50:95))of 69.8%,respectively,improvements of 4.4%and 7.0%over the baseline.展开更多
Coronavirus disease 2019(COVID-19)has caused a global pandemic impacting over 200 countries/regions and more than 200 million patients worldwide.Among the infected patients,there is a high prevalence of COVID-19-relat...Coronavirus disease 2019(COVID-19)has caused a global pandemic impacting over 200 countries/regions and more than 200 million patients worldwide.Among the infected patients,there is a high prevalence of COVID-19-related cardiovascular injuries.However,the specific mechanisms linking cardiovascular damage and COVID-19 remain unclear.The COVID-19 pandemic also has exacerbated the mental health burden of humans.Considering the close association between neuroimmune interactions and cardiovascular disease,this review assessed the complex pathophysiological mechanisms connecting neuroimmune interactions and cardiovascular disease.It was revealed that the mental health burden might be a pivotal accomplice causing COVID-19-associated cardiovascular damage.Specifically,the proinflammatory status of patients with a terrible mood state is closely related to overdrive of the hypothalamus-pituitary-adrenal(HPA)axis,sympathovagal imbalance,and endothelial dysfunction,which lead to an increased risk of developing cardiovascular injury during COVID-19.Therefore,during the prevention and treatment of cardiovascular complications in COVID-19 patients,particular attention should be given to relieve the mental health burden of these patients.展开更多
This paper describes the design and evaluation of a user interface for a remotely supervised autonomous agricultural sprayer. The interface was designed to help the remote supervisor to instruct the autonomous sprayer...This paper describes the design and evaluation of a user interface for a remotely supervised autonomous agricultural sprayer. The interface was designed to help the remote supervisor to instruct the autonomous sprayer to commence operation, monitor the status of the sprayer and its operation in the field, and intervene when needed (i.e., to stop or shut down). Design principles and guidelines were carefully selected to help develop a human-centered automation interface. Evaluation of the interface using a combination of heuristic, cognitive walkthrough, and user testing techniques revealed several strengths of the design as well as areas that needed further improvement. Overall, this paper provides guidelines that will assist other researchers to develop an ergonomic user interface for a fully autonomous agricultural machine.展开更多
With the development of mobile technologies,mobile learning has become a trend and a necessary means in the e-learning environment.E-learners' autonomous learning processes can also be facilitated through the adop...With the development of mobile technologies,mobile learning has become a trend and a necessary means in the e-learning environment.E-learners' autonomous learning processes can also be facilitated through the adoption of various mobile learning tools.Mobile learning tools can be classified into different types according to their different features and functions.Mobile learning devices,mobile learning software,mobile learning resources,and mobile learning services are the four types of learning tools suggested in the paper.Different mobile learning tools are proven to be able to fulfill different needs of autonomous learning.展开更多
Embodied intelligence is redefining policing On the first day of 2026 chunyun,a period of high mobility associated with the Chinese New Year,the city of Jingzhou in Hubei Province welcomed new participants in road saf...Embodied intelligence is redefining policing On the first day of 2026 chunyun,a period of high mobility associated with the Chinese New Year,the city of Jingzhou in Hubei Province welcomed new participants in road safety:police robots capable of moving autonomously and interacting with passengers.Deployed on a trial basis on 2 February,these robots quickly demonstrated their usefulness in various urban settings.展开更多
Interactive autonomous driving is an evolving research domain that demands an autonomous vehicle(AV)to exhibit adaptability to new environments,cognizance of surrounding traffic conditions,and proficient decision-maki...Interactive autonomous driving is an evolving research domain that demands an autonomous vehicle(AV)to exhibit adaptability to new environments,cognizance of surrounding traffic conditions,and proficient decision-making ability in complex human-dominated scenarios to guarantee safe navigation and promote social compatibility.This paper reviews the diverse methodologies utilized in interactive driving for AVs.Various techniques will be investigated for their unique contributions and capabilities in developing AV systems,such as long short-term memory(LSTM),transformer,artificial potential field(APF),game theory,reinforcement learning(RL)/deep reinforcement learning(DRL),and partially observable Markov decision processes(POMDP),among others.Recent advancements based on these methodologies are summarized to elucidate their application rationale in interactive driving scenarios.The strengths and challenges inherent to each approach within the context of interactive driving are further assessed.Additionally,the resolution of these challenges is explored through integrating different methods.Therefore,a comparative analysis offers crucial perspectives for advancing autonomous driving technologies.This review exclusively focuses on the interactions between AVs and human-driven vehicles(HDVs).展开更多
文摘In the era of intelligent media,the interaction between teachers and students in higher education is undergoing a profound transformation.The model has shifted from one-way transmission to multi-agent,two-way collaboration involving“teacher-student-AI(artificial intelligence)”.Interaction depth moves from surface Q&A to deep thought engagement,supported by instant,precise feedback and a blended virtual-physical space.New forms such as data-driven personalized interaction and immersive collaborative learning have emerged.However,this evolution brings significant challenges:over-reliance on technology may weaken cognitive autonomy;virtual interaction risks emotional detachment and trust erosion;ethical concerns like algorithmic bias and data privacy arise;teachers’roles become blurred;and evaluation systems lag behind technological advances.Future pathways should position AI as a supportive tool while upholding human centrality.Strengthening emotional connection through online-offline blending,reforming assessment to value process and growth,and empowering teachers as digitally literate“learning guides”and“emotional connectors”are key to building a healthy,sustainable interactive ecosystem.
文摘In the modern higher education music curriculum system,the teacher-student interaction mode is a key factor affecting the effectiveness of piano teaching.However,the current teacher-student interaction mode in piano teaching still has limitations,such as one-way transmission and a lack of personalized feedback.Based on constructivist learning theory and social interaction theory,combined with information technology,this paper explores the optimization strategy of interaction mode in the piano teaching process of normal universities.This study adopts classroom observation and interview methods to analyze the impact of different interaction modes on students’piano learning effectiveness,learning engagement,and autonomous learning ability.The research results show that the constructivist interactive teaching mode supported by information technology can significantly enhance students’interest in learning and playing skills,optimize the classroom teaching atmosphere,and promote the improvement of their comprehensive literacy.
基金supported by the National Natural Science Foundation of China(No.61702347)Hebei Academy of Sciences Basic Research Operating Fund Project(No.2025PF21)。
文摘To address the challenges of multi-scale differences,complex background interference,and unstable small target positioning in visual inspection of power towers,the existing methods still face issues such as insufficient feature interaction and unstable confidence estimation,which lead to performance degradation in complex backgrounds and occlusion conditions.This paper proposes a precise inspection method for key power tower components using autonomous drone positioning.To this end,this paper makes three key improvements to the you only look once version 11(YOLOv11)framework.First,it constructs C3k2-adaptive multi-receptive field block(C3k2-AMRB),combining multiple dilated convolutions with a reparameterization mechanism to significantly expand the receptive field and enhance multi-scale feature extraction.Second,it designs a hierarchical wavelet interaction unit(HWIU),which leverages high-and low-frequency decomposition and reconstruction of wavelet transform(WT)to achieve cross-scale semantic alignment,enhancing feature discriminability in complex backgrounds.Third,it proposes a distribution-aware confidence refinement head(DACR-Head),which adaptively calibrates classification confidence based on the statistical characteristics of the predicted bounding-box corner distribution,improving the localization stability and accuracy of small targets.Experiments on the inspection of power line assets dataset(InsPLAD)dataset show that the integrated approach achieves a component detection accuracy at intersection over union(IoU)=0.5(CDA_(50))of 88.3%and a component detection robustness(CDR_(50:95))of 69.8%,respectively,improvements of 4.4%and 7.0%over the baseline.
基金the National Natural Science Foundation of China(No.81570427 and No.81974039).
文摘Coronavirus disease 2019(COVID-19)has caused a global pandemic impacting over 200 countries/regions and more than 200 million patients worldwide.Among the infected patients,there is a high prevalence of COVID-19-related cardiovascular injuries.However,the specific mechanisms linking cardiovascular damage and COVID-19 remain unclear.The COVID-19 pandemic also has exacerbated the mental health burden of humans.Considering the close association between neuroimmune interactions and cardiovascular disease,this review assessed the complex pathophysiological mechanisms connecting neuroimmune interactions and cardiovascular disease.It was revealed that the mental health burden might be a pivotal accomplice causing COVID-19-associated cardiovascular damage.Specifically,the proinflammatory status of patients with a terrible mood state is closely related to overdrive of the hypothalamus-pituitary-adrenal(HPA)axis,sympathovagal imbalance,and endothelial dysfunction,which lead to an increased risk of developing cardiovascular injury during COVID-19.Therefore,during the prevention and treatment of cardiovascular complications in COVID-19 patients,particular attention should be given to relieve the mental health burden of these patients.
文摘This paper describes the design and evaluation of a user interface for a remotely supervised autonomous agricultural sprayer. The interface was designed to help the remote supervisor to instruct the autonomous sprayer to commence operation, monitor the status of the sprayer and its operation in the field, and intervene when needed (i.e., to stop or shut down). Design principles and guidelines were carefully selected to help develop a human-centered automation interface. Evaluation of the interface using a combination of heuristic, cognitive walkthrough, and user testing techniques revealed several strengths of the design as well as areas that needed further improvement. Overall, this paper provides guidelines that will assist other researchers to develop an ergonomic user interface for a fully autonomous agricultural machine.
基金Beijing Higher Education Young Elite Teacher Project,China(No.YETP0471)
文摘With the development of mobile technologies,mobile learning has become a trend and a necessary means in the e-learning environment.E-learners' autonomous learning processes can also be facilitated through the adoption of various mobile learning tools.Mobile learning tools can be classified into different types according to their different features and functions.Mobile learning devices,mobile learning software,mobile learning resources,and mobile learning services are the four types of learning tools suggested in the paper.Different mobile learning tools are proven to be able to fulfill different needs of autonomous learning.
文摘Embodied intelligence is redefining policing On the first day of 2026 chunyun,a period of high mobility associated with the Chinese New Year,the city of Jingzhou in Hubei Province welcomed new participants in road safety:police robots capable of moving autonomously and interacting with passengers.Deployed on a trial basis on 2 February,these robots quickly demonstrated their usefulness in various urban settings.
基金partially supported by the Texas Tech University Graduate School Fellowship.
文摘Interactive autonomous driving is an evolving research domain that demands an autonomous vehicle(AV)to exhibit adaptability to new environments,cognizance of surrounding traffic conditions,and proficient decision-making ability in complex human-dominated scenarios to guarantee safe navigation and promote social compatibility.This paper reviews the diverse methodologies utilized in interactive driving for AVs.Various techniques will be investigated for their unique contributions and capabilities in developing AV systems,such as long short-term memory(LSTM),transformer,artificial potential field(APF),game theory,reinforcement learning(RL)/deep reinforcement learning(DRL),and partially observable Markov decision processes(POMDP),among others.Recent advancements based on these methodologies are summarized to elucidate their application rationale in interactive driving scenarios.The strengths and challenges inherent to each approach within the context of interactive driving are further assessed.Additionally,the resolution of these challenges is explored through integrating different methods.Therefore,a comparative analysis offers crucial perspectives for advancing autonomous driving technologies.This review exclusively focuses on the interactions between AVs and human-driven vehicles(HDVs).
