详细分析BDS-3星座空间构型,从卫星可见性与天线指向性2个方面构建动态链路约束模型。通过两行轨道根数(two line elements,TLE)文件获取真实卫星轨道参数,并基于STK构建BDS-3星座,系统全面分析北斗星间链路拓扑特性。仿真结果对进一步...详细分析BDS-3星座空间构型,从卫星可见性与天线指向性2个方面构建动态链路约束模型。通过两行轨道根数(two line elements,TLE)文件获取真实卫星轨道参数,并基于STK构建BDS-3星座,系统全面分析北斗星间链路拓扑特性。仿真结果对进一步完成链路预算,实现星间自主定轨与时间同步具有重要指导意义。展开更多
In the Kigongo area of Mwanza Region,northwest Tanzania,fishmonger Neema Aisha remembers how the morning’s fresh catch would sour while she queued for the ferry,putting her business at risk.
Blockchain offers a promising solution to the security challenges faced by the Internet of Vehicles(IoV).However,due to the dynamic connectivity of IoV,blockchain based on a single-chain structure or Directed Acyclic ...Blockchain offers a promising solution to the security challenges faced by the Internet of Vehicles(IoV).However,due to the dynamic connectivity of IoV,blockchain based on a single-chain structure or Directed Acyclic Graph(DAG)structure often suffer from performance limitations.The DAG lattice structure is a novel blockchain model in which each node maintains its own account chain,and only the node itself is allowed to update it.This feature makes the DAG lattice structure particularly suitable for addressing the challenges in dynamically connected IoV environment.In this paper,we propose a blockchain architecture based on the DAG lattice structure,specifically designed for dynamically connected IoV.In the proposed system,nodes must obtain authorization from a trusted authority before joining,forming a permissioned blockchain.Each node is assigned an individual account chain,allowing vehicles with limited storage capacity to participate in the blockchain by storing transactions only from nearby vehicles’account chains.Every transmitted message is treated as a transaction and added to the blockchain,enablingmore efficient data transmission in a dynamic network environment.Areputation-based incentivemechanism is introduced to encourage nodes to behave normally.Experimental results demonstrate that the proposed architecture achieves better performance compared with traditional single-chain and DAG-based approaches in terms of average transmission delay and storage cost.展开更多
BACKGROUND Suicide constitutes the second leading cause of death among adolescents globally and represents a critical public health concern.The neural mechanisms underlying suicidal behavior in adolescents with major ...BACKGROUND Suicide constitutes the second leading cause of death among adolescents globally and represents a critical public health concern.The neural mechanisms underlying suicidal behavior in adolescents with major depressive disorder(MDD)remain poorly understood.Aberrant resting-state functional connectivity(rsFC)in the amygdala,a key region implicated in emotional regulation and threat detection,is strongly implicated in depression and suicidal behavior.AIM To investigate rsFC alterations between amygdala subregions and whole-brain networks in adolescent patients with depression and suicide attempts.METHODS Resting-state functional magnetic resonance imaging data were acquired from 32 adolescents with MDD and suicide attempts(sMDD)group,33 adolescents with MDD but without suicide attempts(nsMDD)group,and 34 demographically matched healthy control(HC)group,with the lateral and medial amygdala(MeA)defined as regions of interest.The rsFC patterns of amygdala subregions were compared across the three groups,and associations between aberrant rsFC values and clinical symptom severity scores were examined.RESULTS Compared with the nsMDD group,the sMDD group exhibited reduced rsFC between the right lateral amygdala(LA)and the right inferior occipital gyrus as well as the left middle occipital gyrus.Compared with the HC group,the abnormal brain regions of rsFC in the sMDD group and nsMDD group involve the parahippocampal gyrus(PHG)and fusiform gyrus.In the sMDD group,right MeA and right temporal pole:Superior temporal gyrus rsFC value negatively correlated with the Rosenberg Self-Esteem Scale scores(r=-0.409,P=0.025),while left LA and right PHG rsFC value positively correlated with the Adolescent Self-Rating Life Events Checklist interpersonal relationship scores(r=0.372,P=0.043).CONCLUSION Aberrant rsFC changes between amygdala subregions and these brain regions provide novel insights into the underlying neural mechanisms of suicide attempts in adolescents with MDD.展开更多
Autonomous connected vehicles(ACV)involve advanced control strategies to effectively balance safety,efficiency,energy consumption,and passenger comfort.This research introduces a deep reinforcement learning(DRL)-based...Autonomous connected vehicles(ACV)involve advanced control strategies to effectively balance safety,efficiency,energy consumption,and passenger comfort.This research introduces a deep reinforcement learning(DRL)-based car-following(CF)framework employing the Deep Deterministic Policy Gradient(DDPG)algorithm,which integrates a multi-objective reward function that balances the four goals while maintaining safe policy learning.Utilizing real-world driving data from the highD dataset,the proposed model learns adaptive speed control policies suitable for dynamic traffic scenarios.The performance of the DRL-based model is evaluated against a traditional model predictive control-adaptive cruise control(MPC-ACC)controller.Results show that theDRLmodel significantly enhances safety,achieving zero collisions and a higher average time-to-collision(TTC)of 8.45 s,compared to 5.67 s for MPC and 6.12 s for human drivers.For efficiency,the model demonstrates 89.2% headway compliance and maintains speed tracking errors below 1.2 m/s in 90% of cases.In terms of energy optimization,the proposed approach reduces fuel consumption by 5.4% relative to MPC.Additionally,it enhances passenger comfort by lowering jerk values by 65%,achieving 0.12 m/s3 vs.0.34 m/s3 for human drivers.A multi-objective reward function is integrated to ensure stable policy convergence while simultaneously balancing the four key performance metrics.Moreover,the findings underscore the potential of DRL in advancing autonomous vehicle control,offering a robust and sustainable solution for safer,more efficient,and more comfortable transportation systems.展开更多
This study proposes a new post-tensioned precast bridge column(PT-PBC)with a socket connection.Compared to conventional PBCs connected by PT tendons,the combination of the PT tendons with the socket connection can avo...This study proposes a new post-tensioned precast bridge column(PT-PBC)with a socket connection.Compared to conventional PBCs connected by PT tendons,the combination of the PT tendons with the socket connection can avoid tensioning the PT tendons on site,which further accelerates construction speed while improving construction quality and safety.In addition,compared to conventional PBCs with a socket connection,a rocking interface can avoid the formation of a plastic hinge in a column,which greatly alleviates seismic damage to that area.One specimen for quasi-static testing is used to validate the feasibility of this connection type.Subsequently,finite element models(FEM)are established to systematically predict the responses of the proposed columns under lateral cyclic loading.The accuracy of the FEM is verified through quasistatic testing.Next,the influences of the key design parameters of the PT-PBC,including the area ratio and prestress level of the PT tendons,the area ratio of energy dissipation(ED)steel rebars,and the total axial compression ratio on the seismic performances of PT-PBC are systematically investigated.The use of shape memory alloy(SMA)rods as energy dissipation devices and their performances also are investigated.The results show that increasing the area ratio and prestress level of PT tendons has an overall positive impact on the self-centering capacity of the column.The prestress level of PT tendons should be kept between 35%and 55%,depending on different conditions.The total compression axial ratio of the columns should be maintained between 0.3 and 0.4.Both ED steel rebars and SMA rods can boost the column’s energy dissipation capacity,while SMA rods can reduce residual deformation due to their inherent mechanical properties.展开更多
Background:Social connection is widely recognized as a protective determinant of health,yet its direct and indirect effects on mental health remain underexplored.This study examines the relationship between social con...Background:Social connection is widely recognized as a protective determinant of health,yet its direct and indirect effects on mental health remain underexplored.This study examines the relationship between social connection and mental health,focusing on the mediating role of quality of life(QoL)and the moderating effect of regional differences.Methods:We analyzed data from the 2019 Korean Community Health Survey,comprising 229,099 adults.Mental health was assessed through validated measures of depressive symptoms and psychological well-being.Social connection was measured using indicators of interpersonal ties and community participation,and QoL was assessed via self-reported health-related satisfaction across major life domains.Analytical procedures included mediation modeling and subgroup analyses by region,with significance levels set at p<0.05.Results:The results indicate that social connections are significantly associated with lower stress levels and reduced depressive symptoms,with QoL playing a critical mediating role.Notably,the indirect effect of social connection on mental health via QoL is stronger in rural areas compared to urban regions,highlighting the importance of social cohesion and community support in mental well-being.Among 203,567 adults,greater social participation was associated with lower subjective stress(total effect=−0.052,p<0.001)and fewer depressive symptoms(PHQ-9 total effect=−0.308,p<0.001).QoL significantly mediated these associations,with the strongest indirect pathways observed through usual activities(19.2%for stress;27.6%for depression)and mobility(24.4%for depression).Regional analysis showed stronger mediation in rural areas(up to 26.8%for stress and 32.6%for depression)than in urban areas(8–16%and 14.9–23%).Direct effects remained significant,indicating partial mediation.These findings highlight that social participation enhances mental health directly and indirectly through QoL,particularly in rural contexts.Conclusions:Social connection contributes to better mental health both directly and indirectly through improved QoL,with stronger effects observed in rural communities.These findings highlight the importance of fostering social cohesion and enhancing life quality as strategies for improving population mental health.Policy interventions should adopt context-sensitive approaches that account for regional differences in social resources and service availability.展开更多
Aiming at the problem of potential information noise introduced during the generation of ghost feature maps in GhostNet,this paper proposes a novel lightweight neural network model called ResghostNet.This model constr...Aiming at the problem of potential information noise introduced during the generation of ghost feature maps in GhostNet,this paper proposes a novel lightweight neural network model called ResghostNet.This model constructs the Resghost Module by combining residual connections and Adaptive-SE Blocks,which enhances the quality of generated feature maps through direct propagation of original input information and selection of important channels before cheap operations.Specifically,ResghostNet introduces residual connections on the basis of the Ghost Module to optimize the information flow,and designs a weight self-attention mechanism combined with SE blocks to enhance feature expression capabilities in cheap operations.Experimental results on the ImageNet dataset show that,compared to GhostNet,ResghostNet achieves higher accuracy while reducing the number of parameters by 52%.Although the computational complexity increases,by optimizing the usage strategy of GPU cachememory,themodel’s inference speed becomes faster.The ResghostNet is optimized in terms of classification accuracy and the number of model parameters,and shows great potential in edge computing devices.展开更多
The Wilczek–Zee connection(WZC)is a key concept in the study of topology of quantum systems.Here,we introduce the double Wilczek–Zee connection(DWZC)which naturally appears in the pure-state quantum geometric tensor...The Wilczek–Zee connection(WZC)is a key concept in the study of topology of quantum systems.Here,we introduce the double Wilczek–Zee connection(DWZC)which naturally appears in the pure-state quantum geometric tensor(QGT),another important concept in the field of quantum geometry.The DWZC is Hermitian with respect to the two integer indices,just like the original Hermitian WZC.Based on the symmetric logarithmic derivative operator,we propose a mixed-state quantum geometric tensor.Using the symmetric properties of the DWZC,we find that the real part of the QGT is connected to the real part of the DWZC and the square of eigenvalue differences of the density matrix,whereas the imaginary part can be given in terms of the imaginary part of the DWZC and the cube of the eigenvalue differences.For density matrices with full rank or no full rank,the QGT can be given in terms of real and imaginary parts of the DWZC.展开更多
Floodplain wetlands are invaluable ecosystems providing numerous ecological benefits,yet they face a global crisis necessitating sustainable preservation efforts.This study examines the depletion of floodplain wetland...Floodplain wetlands are invaluable ecosystems providing numerous ecological benefits,yet they face a global crisis necessitating sustainable preservation efforts.This study examines the depletion of floodplain wetlands within the Hastinapur Wildlife Sanctuary(HWLS)in Uttar Pradesh.Encroachment activities such as grazing,agriculture,and human settlements have fragmented and degraded critical wetland ecosystems.Additionally,irrigation projects,dam construction,and water diversion have disrupted natural water flow and availability.To assess wetland inundation in 2023,five classification techniques were employed:Random Forest(RF),Support Vector Machine(SVM),artificial neural network(ANN),Spectral Information Divergence(SID),and Maximum Likelihood Classifier(MLC).SVM emerged as the most precise method,as determined by kappa coefficient and index-based validation.Consequently,the SVM classifier was used to model wetland inundation areas from 1983 to 2023 and analyze spatiotemporal changes and fragmentation patterns.The findings revealed that the SVM clas-sifier accurately mapped 2023 wetland areas.The modeled time-series data demonstrated a 62.55%and 38.12%reduction in inundated wetland areas over the past 40 years in the pre-and post-monsoon periods,respectively.Fragmentation analysis indicated an 86.27%decrease in large core wetland areas in the pre-monsoon period,signifying severe habitat degradation.This rapid decline in wetlands within protected areas raises concerns about their ecological impacts.By linking wetland loss to global sustainability objectives,this study underscores the global urgency for strengthened wetland protection measures and highlights the need for integrating wetland conservation into broader sustainable development goals.Effective policies and adaptive management strategies are crucial for preserving these ecosystems and their vital services,which are essential for biodiversity,climate regulation,and human well-being.展开更多
The development of brain-computer interfaces(BCI)based on motor imagery(MI)has greatly improved patients’quality of life with movement disorders.The classification of upper limb MI has been widely studied and applied...The development of brain-computer interfaces(BCI)based on motor imagery(MI)has greatly improved patients’quality of life with movement disorders.The classification of upper limb MI has been widely studied and applied in many fields,including rehabilitation.However,the physiological representations of left and right lower limb movements are too close and activated deep in the cerebral cortex,making it difficult to distinguish their features.Therefore,classifying lower limbs motor imagery is more challenging.In this study,we propose a feature extraction method based on functional connectivity,which utilizes phase-locked values to construct a functional connectivity matrix as the features of the left and right legs,which can effectively avoid the problem of physiological representations of the left and right lower limbs being too close to each other during movement.In addition,considering the topology and the temporal characteristics of the electroencephalogram(EEG),we designed a temporal-spatial convolutional network(TSGCN)to capture the spatiotemporal information for classification.Experimental results show that the accuracy of the proposed method is higher than that of existing methods,achieving an average classification accuracy of 73.58%on the internal dataset.Finally,this study explains the network mechanism of left and right foot MI from the perspective of graph theoretic features and demonstrates the feasibility of decoding lower limb MI.展开更多
Traffic at urban intersections frequently encounters unexpected obstructions,resulting in congestion due to uncooperative and priority-based driving behavior.This paper presents an optimal right-turn coordination syst...Traffic at urban intersections frequently encounters unexpected obstructions,resulting in congestion due to uncooperative and priority-based driving behavior.This paper presents an optimal right-turn coordination system for Connected and Automated Vehicles(CAVs)at single-lane intersections,particularly in the context of left-hand side driving on roads.The goal is to facilitate smooth right turns for certain vehicles without creating bottlenecks.We consider that all approaching vehicles share relevant information through vehicular communications.The Intersection Coordination Unit(ICU)processes this information and communicates the optimal crossing or turning times to the vehicles.The primary objective of this coordination is to minimize overall traffic delays,which also helps improve the fuel consumption of vehicles.By considering information from upcoming vehicles at the intersection,the coordination system solves an optimization problem to determine the best timing for executing right turns,ultimately minimizing the total delay for all vehicles.The proposed coordination system is evaluated at a typical urban intersection,and its performance is compared to traditional traffic systems.Numerical simulation results indicate that the proposed coordination system significantly enhances the average traffic speed and fuel consumption compared to the traditional traffic system in various scenarios.展开更多
This study aims to explore the impact of fatigue induced by different limb exercises on cerebral cortical oxygenation levels and functional connectivity strength using functional near-infrared spectroscopy(fNIRS).Fati...This study aims to explore the impact of fatigue induced by different limb exercises on cerebral cortical oxygenation levels and functional connectivity strength using functional near-infrared spectroscopy(fNIRS).Fatigue was induced using an upper limb ergometer or a lower limb ergometer,with the load increasing gradually each minute.fNIRS covering the prefrontal cortex and motor cortex were used to collect data during the resting state,both before and after fatigue induction.A two-way ANOVA was conducted to examine differences in oxyhemoglobin(HbO_(2))and functional connectivity before and after fatigue induction in both groups,with the significance level set at 0.05.Exercise-induced fatigue in both the upper and lower limbs leads to a significant decrease in cerebral cortical oxygenation levels.Upper limb fatigue leads to a significant reduction in functional connectivity,there were significant decreases in connectivity within the motor cortex,between the motor cortex and frontal regions,and between the right ventrolateral prefrontal cortex and other frontal regions.Conversely,no significant changes were observed before and after lower limb fatigue.Future studies should focus on examining the extent to which how changes in the cerebral cortex,induced by exercise fatigue,are linked to exercise-and/or performance-related outcomes.展开更多
文摘详细分析BDS-3星座空间构型,从卫星可见性与天线指向性2个方面构建动态链路约束模型。通过两行轨道根数(two line elements,TLE)文件获取真实卫星轨道参数,并基于STK构建BDS-3星座,系统全面分析北斗星间链路拓扑特性。仿真结果对进一步完成链路预算,实现星间自主定轨与时间同步具有重要指导意义。
文摘In the Kigongo area of Mwanza Region,northwest Tanzania,fishmonger Neema Aisha remembers how the morning’s fresh catch would sour while she queued for the ferry,putting her business at risk.
基金funded in part by the Supported by Natural Science Foundation of Inner Mongolia Autonomous Region of China under Grants 2024QN06022 and 2023QN06008in part by the First-Class Discipline Research Special Project under Grant YLXKZX-NGD-015in part by the Inner Mongolia University of Technology Scientific Research Start-Up Project under Grant BS2024067.
文摘Blockchain offers a promising solution to the security challenges faced by the Internet of Vehicles(IoV).However,due to the dynamic connectivity of IoV,blockchain based on a single-chain structure or Directed Acyclic Graph(DAG)structure often suffer from performance limitations.The DAG lattice structure is a novel blockchain model in which each node maintains its own account chain,and only the node itself is allowed to update it.This feature makes the DAG lattice structure particularly suitable for addressing the challenges in dynamically connected IoV environment.In this paper,we propose a blockchain architecture based on the DAG lattice structure,specifically designed for dynamically connected IoV.In the proposed system,nodes must obtain authorization from a trusted authority before joining,forming a permissioned blockchain.Each node is assigned an individual account chain,allowing vehicles with limited storage capacity to participate in the blockchain by storing transactions only from nearby vehicles’account chains.Every transmitted message is treated as a transaction and added to the blockchain,enablingmore efficient data transmission in a dynamic network environment.Areputation-based incentivemechanism is introduced to encourage nodes to behave normally.Experimental results demonstrate that the proposed architecture achieves better performance compared with traditional single-chain and DAG-based approaches in terms of average transmission delay and storage cost.
基金Supported by Suzhou Clinical Medical Center for Mood Disorders,No.Szlcyxzx202109Suzhou Key Laboratory,No.SZS2024016Multicenter Clinical Research on Major Diseases in Suzhou,No.DZXYJ202413.
文摘BACKGROUND Suicide constitutes the second leading cause of death among adolescents globally and represents a critical public health concern.The neural mechanisms underlying suicidal behavior in adolescents with major depressive disorder(MDD)remain poorly understood.Aberrant resting-state functional connectivity(rsFC)in the amygdala,a key region implicated in emotional regulation and threat detection,is strongly implicated in depression and suicidal behavior.AIM To investigate rsFC alterations between amygdala subregions and whole-brain networks in adolescent patients with depression and suicide attempts.METHODS Resting-state functional magnetic resonance imaging data were acquired from 32 adolescents with MDD and suicide attempts(sMDD)group,33 adolescents with MDD but without suicide attempts(nsMDD)group,and 34 demographically matched healthy control(HC)group,with the lateral and medial amygdala(MeA)defined as regions of interest.The rsFC patterns of amygdala subregions were compared across the three groups,and associations between aberrant rsFC values and clinical symptom severity scores were examined.RESULTS Compared with the nsMDD group,the sMDD group exhibited reduced rsFC between the right lateral amygdala(LA)and the right inferior occipital gyrus as well as the left middle occipital gyrus.Compared with the HC group,the abnormal brain regions of rsFC in the sMDD group and nsMDD group involve the parahippocampal gyrus(PHG)and fusiform gyrus.In the sMDD group,right MeA and right temporal pole:Superior temporal gyrus rsFC value negatively correlated with the Rosenberg Self-Esteem Scale scores(r=-0.409,P=0.025),while left LA and right PHG rsFC value positively correlated with the Adolescent Self-Rating Life Events Checklist interpersonal relationship scores(r=0.372,P=0.043).CONCLUSION Aberrant rsFC changes between amygdala subregions and these brain regions provide novel insights into the underlying neural mechanisms of suicide attempts in adolescents with MDD.
基金the Hebei Province Science and Technology Plan Project(19221909D)rincess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2025R308),Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘Autonomous connected vehicles(ACV)involve advanced control strategies to effectively balance safety,efficiency,energy consumption,and passenger comfort.This research introduces a deep reinforcement learning(DRL)-based car-following(CF)framework employing the Deep Deterministic Policy Gradient(DDPG)algorithm,which integrates a multi-objective reward function that balances the four goals while maintaining safe policy learning.Utilizing real-world driving data from the highD dataset,the proposed model learns adaptive speed control policies suitable for dynamic traffic scenarios.The performance of the DRL-based model is evaluated against a traditional model predictive control-adaptive cruise control(MPC-ACC)controller.Results show that theDRLmodel significantly enhances safety,achieving zero collisions and a higher average time-to-collision(TTC)of 8.45 s,compared to 5.67 s for MPC and 6.12 s for human drivers.For efficiency,the model demonstrates 89.2% headway compliance and maintains speed tracking errors below 1.2 m/s in 90% of cases.In terms of energy optimization,the proposed approach reduces fuel consumption by 5.4% relative to MPC.Additionally,it enhances passenger comfort by lowering jerk values by 65%,achieving 0.12 m/s3 vs.0.34 m/s3 for human drivers.A multi-objective reward function is integrated to ensure stable policy convergence while simultaneously balancing the four key performance metrics.Moreover,the findings underscore the potential of DRL in advancing autonomous vehicle control,offering a robust and sustainable solution for safer,more efficient,and more comfortable transportation systems.
基金Natural Science Foundation of China under Grant No.52178449,the Beijing Natural Science Foundation under Grant No.8234060the Innovation Center of Beijing Association for Science and Technology。
文摘This study proposes a new post-tensioned precast bridge column(PT-PBC)with a socket connection.Compared to conventional PBCs connected by PT tendons,the combination of the PT tendons with the socket connection can avoid tensioning the PT tendons on site,which further accelerates construction speed while improving construction quality and safety.In addition,compared to conventional PBCs with a socket connection,a rocking interface can avoid the formation of a plastic hinge in a column,which greatly alleviates seismic damage to that area.One specimen for quasi-static testing is used to validate the feasibility of this connection type.Subsequently,finite element models(FEM)are established to systematically predict the responses of the proposed columns under lateral cyclic loading.The accuracy of the FEM is verified through quasistatic testing.Next,the influences of the key design parameters of the PT-PBC,including the area ratio and prestress level of the PT tendons,the area ratio of energy dissipation(ED)steel rebars,and the total axial compression ratio on the seismic performances of PT-PBC are systematically investigated.The use of shape memory alloy(SMA)rods as energy dissipation devices and their performances also are investigated.The results show that increasing the area ratio and prestress level of PT tendons has an overall positive impact on the self-centering capacity of the column.The prestress level of PT tendons should be kept between 35%and 55%,depending on different conditions.The total compression axial ratio of the columns should be maintained between 0.3 and 0.4.Both ED steel rebars and SMA rods can boost the column’s energy dissipation capacity,while SMA rods can reduce residual deformation due to their inherent mechanical properties.
基金supported by the“Regional Innovation System&Education(RISE)”through the Seoul RISE Center,funded by the Ministry of Education(MOE)and the Seoul Metropolitan Government.(2025-RISE-01-005-07).
文摘Background:Social connection is widely recognized as a protective determinant of health,yet its direct and indirect effects on mental health remain underexplored.This study examines the relationship between social connection and mental health,focusing on the mediating role of quality of life(QoL)and the moderating effect of regional differences.Methods:We analyzed data from the 2019 Korean Community Health Survey,comprising 229,099 adults.Mental health was assessed through validated measures of depressive symptoms and psychological well-being.Social connection was measured using indicators of interpersonal ties and community participation,and QoL was assessed via self-reported health-related satisfaction across major life domains.Analytical procedures included mediation modeling and subgroup analyses by region,with significance levels set at p<0.05.Results:The results indicate that social connections are significantly associated with lower stress levels and reduced depressive symptoms,with QoL playing a critical mediating role.Notably,the indirect effect of social connection on mental health via QoL is stronger in rural areas compared to urban regions,highlighting the importance of social cohesion and community support in mental well-being.Among 203,567 adults,greater social participation was associated with lower subjective stress(total effect=−0.052,p<0.001)and fewer depressive symptoms(PHQ-9 total effect=−0.308,p<0.001).QoL significantly mediated these associations,with the strongest indirect pathways observed through usual activities(19.2%for stress;27.6%for depression)and mobility(24.4%for depression).Regional analysis showed stronger mediation in rural areas(up to 26.8%for stress and 32.6%for depression)than in urban areas(8–16%and 14.9–23%).Direct effects remained significant,indicating partial mediation.These findings highlight that social participation enhances mental health directly and indirectly through QoL,particularly in rural contexts.Conclusions:Social connection contributes to better mental health both directly and indirectly through improved QoL,with stronger effects observed in rural communities.These findings highlight the importance of fostering social cohesion and enhancing life quality as strategies for improving population mental health.Policy interventions should adopt context-sensitive approaches that account for regional differences in social resources and service availability.
基金funded by Science and Technology Innovation Project grant No.ZZKY20222304.
文摘Aiming at the problem of potential information noise introduced during the generation of ghost feature maps in GhostNet,this paper proposes a novel lightweight neural network model called ResghostNet.This model constructs the Resghost Module by combining residual connections and Adaptive-SE Blocks,which enhances the quality of generated feature maps through direct propagation of original input information and selection of important channels before cheap operations.Specifically,ResghostNet introduces residual connections on the basis of the Ghost Module to optimize the information flow,and designs a weight self-attention mechanism combined with SE blocks to enhance feature expression capabilities in cheap operations.Experimental results on the ImageNet dataset show that,compared to GhostNet,ResghostNet achieves higher accuracy while reducing the number of parameters by 52%.Although the computational complexity increases,by optimizing the usage strategy of GPU cachememory,themodel’s inference speed becomes faster.The ResghostNet is optimized in terms of classification accuracy and the number of model parameters,and shows great potential in edge computing devices.
基金Project supported by Quantum Science and Technology–National Science and Technology Major Project(Grant No.2024ZD0301000)the National Natural Science Foundation of China(Grant No.12305031)+1 种基金the Hangzhou Joint Fund of the Natural Science Foundation of Zhejiang Province,China(Grant No.LHZSD24A050001)the Science Foundation of Zhejiang Sci-Tech University(Grant Nos.23062088Y and 23062153-Y)。
文摘The Wilczek–Zee connection(WZC)is a key concept in the study of topology of quantum systems.Here,we introduce the double Wilczek–Zee connection(DWZC)which naturally appears in the pure-state quantum geometric tensor(QGT),another important concept in the field of quantum geometry.The DWZC is Hermitian with respect to the two integer indices,just like the original Hermitian WZC.Based on the symmetric logarithmic derivative operator,we propose a mixed-state quantum geometric tensor.Using the symmetric properties of the DWZC,we find that the real part of the QGT is connected to the real part of the DWZC and the square of eigenvalue differences of the density matrix,whereas the imaginary part can be given in terms of the imaginary part of the DWZC and the cube of the eigenvalue differences.For density matrices with full rank or no full rank,the QGT can be given in terms of real and imaginary parts of the DWZC.
基金support through the“Trans-Disciplinary Research”Grant(No.R/Dev/IoE/TDRProjects/2023-24/61658),which played a crucial role in enabling this research endeavor.
文摘Floodplain wetlands are invaluable ecosystems providing numerous ecological benefits,yet they face a global crisis necessitating sustainable preservation efforts.This study examines the depletion of floodplain wetlands within the Hastinapur Wildlife Sanctuary(HWLS)in Uttar Pradesh.Encroachment activities such as grazing,agriculture,and human settlements have fragmented and degraded critical wetland ecosystems.Additionally,irrigation projects,dam construction,and water diversion have disrupted natural water flow and availability.To assess wetland inundation in 2023,five classification techniques were employed:Random Forest(RF),Support Vector Machine(SVM),artificial neural network(ANN),Spectral Information Divergence(SID),and Maximum Likelihood Classifier(MLC).SVM emerged as the most precise method,as determined by kappa coefficient and index-based validation.Consequently,the SVM classifier was used to model wetland inundation areas from 1983 to 2023 and analyze spatiotemporal changes and fragmentation patterns.The findings revealed that the SVM clas-sifier accurately mapped 2023 wetland areas.The modeled time-series data demonstrated a 62.55%and 38.12%reduction in inundated wetland areas over the past 40 years in the pre-and post-monsoon periods,respectively.Fragmentation analysis indicated an 86.27%decrease in large core wetland areas in the pre-monsoon period,signifying severe habitat degradation.This rapid decline in wetlands within protected areas raises concerns about their ecological impacts.By linking wetland loss to global sustainability objectives,this study underscores the global urgency for strengthened wetland protection measures and highlights the need for integrating wetland conservation into broader sustainable development goals.Effective policies and adaptive management strategies are crucial for preserving these ecosystems and their vital services,which are essential for biodiversity,climate regulation,and human well-being.
基金supported in part by the National Natural Science Foundation of China under Grant 62172368the Natural Science Foundation of Zhejiang Province under Grant LR22F020003.
文摘The development of brain-computer interfaces(BCI)based on motor imagery(MI)has greatly improved patients’quality of life with movement disorders.The classification of upper limb MI has been widely studied and applied in many fields,including rehabilitation.However,the physiological representations of left and right lower limb movements are too close and activated deep in the cerebral cortex,making it difficult to distinguish their features.Therefore,classifying lower limbs motor imagery is more challenging.In this study,we propose a feature extraction method based on functional connectivity,which utilizes phase-locked values to construct a functional connectivity matrix as the features of the left and right legs,which can effectively avoid the problem of physiological representations of the left and right lower limbs being too close to each other during movement.In addition,considering the topology and the temporal characteristics of the electroencephalogram(EEG),we designed a temporal-spatial convolutional network(TSGCN)to capture the spatiotemporal information for classification.Experimental results show that the accuracy of the proposed method is higher than that of existing methods,achieving an average classification accuracy of 73.58%on the internal dataset.Finally,this study explains the network mechanism of left and right foot MI from the perspective of graph theoretic features and demonstrates the feasibility of decoding lower limb MI.
基金supported by the Japan Society for the Promotion of Science(JSPS)Grants-in-Aid for Scientific Research(C)23K03898.
文摘Traffic at urban intersections frequently encounters unexpected obstructions,resulting in congestion due to uncooperative and priority-based driving behavior.This paper presents an optimal right-turn coordination system for Connected and Automated Vehicles(CAVs)at single-lane intersections,particularly in the context of left-hand side driving on roads.The goal is to facilitate smooth right turns for certain vehicles without creating bottlenecks.We consider that all approaching vehicles share relevant information through vehicular communications.The Intersection Coordination Unit(ICU)processes this information and communicates the optimal crossing or turning times to the vehicles.The primary objective of this coordination is to minimize overall traffic delays,which also helps improve the fuel consumption of vehicles.By considering information from upcoming vehicles at the intersection,the coordination system solves an optimization problem to determine the best timing for executing right turns,ultimately minimizing the total delay for all vehicles.The proposed coordination system is evaluated at a typical urban intersection,and its performance is compared to traditional traffic systems.Numerical simulation results indicate that the proposed coordination system significantly enhances the average traffic speed and fuel consumption compared to the traditional traffic system in various scenarios.
基金supported by National Natural Science Foundation of China[NO.11932013].
文摘This study aims to explore the impact of fatigue induced by different limb exercises on cerebral cortical oxygenation levels and functional connectivity strength using functional near-infrared spectroscopy(fNIRS).Fatigue was induced using an upper limb ergometer or a lower limb ergometer,with the load increasing gradually each minute.fNIRS covering the prefrontal cortex and motor cortex were used to collect data during the resting state,both before and after fatigue induction.A two-way ANOVA was conducted to examine differences in oxyhemoglobin(HbO_(2))and functional connectivity before and after fatigue induction in both groups,with the significance level set at 0.05.Exercise-induced fatigue in both the upper and lower limbs leads to a significant decrease in cerebral cortical oxygenation levels.Upper limb fatigue leads to a significant reduction in functional connectivity,there were significant decreases in connectivity within the motor cortex,between the motor cortex and frontal regions,and between the right ventrolateral prefrontal cortex and other frontal regions.Conversely,no significant changes were observed before and after lower limb fatigue.Future studies should focus on examining the extent to which how changes in the cerebral cortex,induced by exercise fatigue,are linked to exercise-and/or performance-related outcomes.
