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
The advent of sixth-generation(6G)networks introduces unprecedented challenges in achieving seamless connectivity,ultra-low latency,and efficient resource management in highly dynamic environments.Although fifth-gener...The advent of sixth-generation(6G)networks introduces unprecedented challenges in achieving seamless connectivity,ultra-low latency,and efficient resource management in highly dynamic environments.Although fifth-generation(5G)networks transformed mobile broadband and machine-type communications at massive scales,their properties of scaling,interference management,and latency remain a limitation in dense high mobility settings.To overcome these limitations,artificial intelligence(AI)and unmanned aerial vehicles(UAVs)have emerged as potential solutions to develop versatile,dynamic,and energy-efficient communication systems.The study proposes an AI-based UAV architecture that utilizes cooperative reinforcement learning(CoRL)to manage an autonomous network.The UAVs collaborate by sharing local observations and real-time state exchanges to optimize user connectivity,movement directions,allocate power,and resource distribution.Unlike conventional centralized or autonomous methods,CoRL involves joint state sharing and conflict-sensitive reward shaping,which ensures fair coverage,less interference,and enhanced adaptability in a dynamic urban environment.Simulations conducted in smart city scenarios with 10 UAVs and 50 ground users demonstrate that the proposed CoRL-based UAV system increases user coverage by up to 10%,achieves convergence 40%faster,and reduces latency and energy consumption by 30%compared with centralized and decentralized baselines.Furthermore,the distributed nature of the algorithm ensures scalability and flexibility,making it well-suited for future large-scale 6G deployments.The results highlighted that AI-enabled UAV systems enhance connectivity,support ultra-reliable low-latency communications(URLLC),and improve 6G network efficiency.Future work will extend the framework with adaptive modulation,beamforming-aware positioning,and real-world testbed deployment.展开更多
Spartina alterniflora invasions seriously threaten the structure and functions of coastal wetlands in China.In this study,the Suaeda salsa community in the Yellow River Estuary wetland was monitored using long-term La...Spartina alterniflora invasions seriously threaten the structure and functions of coastal wetlands in China.In this study,the Suaeda salsa community in the Yellow River Estuary wetland was monitored using long-term Landsat satellite images acquired from 1997 to 2020 to quantify the impact of changes in hydrological connectivity induced by S.alterniflora on neighboring vegetation com-munities.The results showed that S.alterniflora rapidly expanded in the estuary area at a rate of 4.91 km^(2)/yr from 2010 to 2020.At the same time,the hydrological connectivity of the area and the distribution of S.salsa changed significantly.Small tidal creeks dominated the S.alterniflora landscape.The number of tidal creeks increased significantly,but their average length decreased and they tended to develop in a horizontal tree-like pattern.Affected by the changes in hydrological connectivity due to the S.alterniflora invasion,the area of S.salsa decreased by 41.1%,and the degree of landscape fragmentation increased from 1997 to 2020.Variations in the Largest Patch Index(LPI)indicated that the S.alterniflora landscape had become the dominant landscape type in the Yellow River Estuary.The res-ults of standard deviation ellipse(SDE)and Pearson’s correlation analyses indicated that a well-developed hydrological connectivity could promote the maintenance of the S.salsa landscape.The degradation of most S.salsa communities is caused by the influence of S.alterniflora on the morphological characteristics of the hydrological connectivity of tidal creek systems.展开更多
Pavement condition monitoring and its timely maintenance is necessary to ensure the safety and quality of the roadway infrastructure. The International Roughness Index (IRI) is a commonly used measure to quantify road...Pavement condition monitoring and its timely maintenance is necessary to ensure the safety and quality of the roadway infrastructure. The International Roughness Index (IRI) is a commonly used measure to quantify road surface roughness and is a critical input to asset management. In Indiana, the IRI statistic contributes to roughly half of the pavement quality index computation used for asset management. Most agencies inventory IRI once a year, however, pavement conditions vary much more frequently. The objective of this paper is to develop a framework using crowdsourced connected vehicle data to identify and detect temporal changes in IRI. Over 3 billion connected vehicle records in Indiana were analyzed across 30 months between 2022 and 2024 to understand the spatiotemporal variations in roughness. Annual comparisons across all major interstates in Indiana showed the miles of interstates classified as “Good” decreased from 1896 to 1661 miles between 2022 and 2024. The miles of interstate classified as “Needs Maintenance” increased from 82 to 120 miles. A detailed case study showing monthly and daily changes of estimated IRI on I-65 are presented along with supporting dashcam images. Although the crowdsourced IRI estimates are not as robust as traditional specialized pavement profilers, they can be obtained on a monthly, weekly, or even daily basis. The paper concludes by suggesting a combination of frequent crowdsourced IRI and commercially available dashcam imagery of roadway can provide an agile and responsive mechanism for agencies to implement pavement asset management programs that can complement existing annual programs.展开更多
During oilfield development,a comprehensive model for assessing inter-well connectivity and connected volume within reservoirs is crucial.Traditional capacitance(TC)models,widely used in inter-well data analysis,face ...During oilfield development,a comprehensive model for assessing inter-well connectivity and connected volume within reservoirs is crucial.Traditional capacitance(TC)models,widely used in inter-well data analysis,face challenges when dealing with rapidly changing reservoir conditions over time.Additionally,TC models struggle with complex,random noise primarily caused by measurement errors in production and injection rates.To address these challenges,this study introduces a dynamic capacitance(SV-DC)model based on state variables.By integrating the extended Kalman filter(EKF)algorithm,the SV-DC model provides more flexible predictions of inter-well connectivity and time-lag efficiency compared to the TC model.The robustness of the SV-DC model is verified by comparing relative errors between preset and calculated values through Monte Carlo simulations.Sensitivity analysis was performed to compare the model performance with the benchmark,using the Qinhuangdao Oilfield as a case study.The results show that the SV-DC model accurately predicts water breakthrough times.Increases in the liquid production index and water cut in two typical wells indicate the development time of ineffective circulation channels,further confirming the accuracy and reliability of the model.The SV-DC model offers significant advantages in addressing complex,dynamic oilfield production scenarios and serves as a valuable tool for the efficient and precise planning and management of future oilfield developments.展开更多
With the development of fast communication technology between ego vehicle and other traffic participants,and automated driving technology,there is a big potential in the improvement of energy efficiency of hybrid elec...With the development of fast communication technology between ego vehicle and other traffic participants,and automated driving technology,there is a big potential in the improvement of energy efficiency of hybrid electric vehicles(HEVs).Moreover,the terrain along the driving route is a non-ignorable factor for energy efficiency of HEV running on the hilly streets.This paper proposes a look-ahead horizon-based optimal energy management strategy to jointly improve the efficiencies of powertrain and vehicle for connected and automated HEVs on the road with slope.Firstly,a rule-based framework is developed to guarantee the success of automated driving in the traffic scenario.Then a constrained optimal control problem is formulated to minimize the fuel consumption and the electricity consumption under the satisfaction of inter-vehicular distance constraint between ego vehicle and preceding vehicle.Both speed planning and torque split of hybrid powertrain are provided by the proposed approach.Moreover,the preceding vehicle speed in the look-ahead horizon is predicted by extreme learning machine with real-time data obtained from communication of vehicle-to-everything.The optimal solution is derived through the Pontryagin’s maximum principle.Finally,to verify the effectiveness of the proposed algorithm,a traffic-in-the-loop powertrain platform with data from real world traffic environment is built.It is found that the fuel economy for the proposed energy management strategy improves in average 17.0%in scenarios of different traffic densities,compared to the energy management strategy without prediction of preceding vehicle speed.展开更多
January 30,Geneva,Switzerland&online As we step into a pivotal moment in the journey toward universal and meaningful connectivity,the Partner2Connect(P2C)Annual Meeting promises to be a transformative gathering of...January 30,Geneva,Switzerland&online As we step into a pivotal moment in the journey toward universal and meaningful connectivity,the Partner2Connect(P2C)Annual Meeting promises to be a transformative gathering of global leaders,innovators,and changemakers.This year’s programme reflects the dynamic and evolving spirit of P2C,offering engaging discussions,interactive sessions,and valuable networking opportunities.Together,we will not only celebrate our collective achievements but also confront the challenges that remain—ensuring that progress toward digital inclusion is sustainable and equitable.展开更多
With the acceleration of urbanization,prefabricated bridges have become a significant choice for transportation infrastructure construction due to their environmental friendliness,efficiency,and reliable quality.Howev...With the acceleration of urbanization,prefabricated bridges have become a significant choice for transportation infrastructure construction due to their environmental friendliness,efficiency,and reliable quality.However,existing connection technologies still face shortcomings in construction efficiency,seismic performance,and cost control.This paper summarizes the process characteristics of commonly used connection technologies such as socket connections,grouted sleeve connections and corrugated pipe connections,and analyzes their seismic capacity and mechanical performance.In response to existing issues,two new technologies—separated steel connection and multi-chamber steel tube concrete connection—are proposed,and their comprehensive performance and economic efficiency are analyzed.The new connection technologies outperform traditional methods in construction efficiency,economic efficiency,and structural stability,with more reasonable force distribution,clearer load transfer paths,and significantly reduced overall costs.Existing technologies,such as socket connections,perform well in seismic performance but are complex to construct;grouted sleeve connections are mature in technology,but the quality of grouting is difficult to inspect.The separated steel connection and multi-chamber steel tube concrete connection technologies offer significant advantages.With the increasing demands for energy conservation and emission reduction,coupled with the rising labor costs,prefabricated bridge piers are undoubtedly poised to become one of the preferred technologies for bridge construction in China in the future.Therefore,in light of the current research landscape,this paper concludes by offering a forward-looking perspective on the development directions of connection methods for prefabricated bridge piers and identifying key areas for future research.展开更多
A borderless art form,film shoulders a mission of sharing culture and fostering emotional bonds.In the relationship between China and Thailand,cinema has long served as a vital cultural bridge,uniting the hearts and m...A borderless art form,film shoulders a mission of sharing culture and fostering emotional bonds.In the relationship between China and Thailand,cinema has long served as a vital cultural bridge,uniting the hearts and minds of the two peoples.From the screening of Chinese films in Thailand to the deepening collaboration within the film industry,the history of bilateral cinematic exchange not only showcases the unique value of film as a cultural medium but also reflects the resilience and vitality of grassroots cultural interactions amid a complex international landscape.This shared history,marked by both challenges and triumphs,has laid a solid foundation for future cultural cooperation,becoming a memorable chapter in the narrative of China-Thailand relations.展开更多
Infrastructure and energy are two important areas for African countries to achieve sustainable development,as well as are among the priorities in the African Union’s Agenda 2063,the continent’s ambitious development...Infrastructure and energy are two important areas for African countries to achieve sustainable development,as well as are among the priorities in the African Union’s Agenda 2063,the continent’s ambitious development blueprint.In February,Lerato Mataboge was elected as the African Union Commissioner for Infrastructure and Energy.She is a global policy and trade and investment facilitation expert and was the deputy director general in the South African Department of Trade,Industry and Competition when she was elected.展开更多
Connective tissue is a dynamic structure that reacts to environmental cues to maintain homeostasis,including mechanical properties.Mechanical load influences extracellular matrix(ECM)—cell interactions and modulates ...Connective tissue is a dynamic structure that reacts to environmental cues to maintain homeostasis,including mechanical properties.Mechanical load influences extracellular matrix(ECM)—cell interactions and modulates cellular behavior.Mechano-regulation processes involve matrix modification and cell activation to preserve tissue function.The ECM remodeling is crucial for force transmission.Cytoskeleton components are involved in force sensing and transmission,affecting cellular adhesion,motility,and gene expression.Proper mechanical loading helps to maintain tissue health,while imbalances may lead to pathological processes.Active and passive movement,including manual mobilization,improves connective tissue elasticity,promotes ECM-cell homeostasis,and reduces fibrosis.In rehabilitation,understanding mechanical-regulation processes is necessary for ameliorating and developing treatments aimed at preserving tissue elasticity and preventing fibrosis.In this commentary,we aim to globally describe the biological processes involved in mechanical force transmission in connective tissue as support for translational studies and clinical applications in the rehabilitation field.展开更多
Background The heterogeneity of depression limits the treatment outcomes of intermittent theta burst stimulation(iTBS)and hinders the identification of predictive factors.This study investigated functional network con...Background The heterogeneity of depression limits the treatment outcomes of intermittent theta burst stimulation(iTBS)and hinders the identification of predictive factors.This study investigated functional network connectivity and predictors of iTBS treatment outcomes in adolescents and young adults with depression.Aim This study aimed to identify default mode network(DMN)-based connectivity patterns associated with varying iTBS treatment outcomes in depression.Methods Data from a randomised controlled trial of iTBS in depression(n=82)were analysed using a data-driven approach to classify homogeneous subgroups based on the DMN.Connectivity subgroups were compared on depressive symptoms and cognitive function at pretreatment and post-treatment.Furthermore,the predictive significance of baseline inflammatory cytokines on post-treatment outcomes was evaluated.Results Two distinct subgroups were identified.Subgroup 1 exhibited high heterogeneity and greater centrality in the posterior cingulate cortex and retrosplenial cortex,while subgroup 2 showed more homogeneous connectivity patterns and greater centrality in the temporoparietal junction and posterior inferior parietal lobule.No main effect for subgroup,treatment or subgroup×treatment interaction was revealed in the improvement of depressive symptoms.A significant subgroup×treatment interaction related to symbol coding improvement was detected(F=5.22,p=0.026).Within subgroup 1,the active group showed significantly greater improvement in symbol coding compared with the sham group(t=2.30,p=0.028),while baseline levels of interleukin-6 and C-reactive protein emerged as significant indicators for predicting improvements in symbolic coding(R2=0.35,RMSE(root-mean-square error)=5.72,p=0.013).Subgroup 2 showed no significant findings in terms of cognitive improvement or inflammatory cytokines predictions.展开更多
Decision-making of connected and automated vehicles(CAV)includes a sequence of driving maneuvers that improve safety and efficiency,characterized by complex scenarios,strong uncertainty,and high real-time requirements...Decision-making of connected and automated vehicles(CAV)includes a sequence of driving maneuvers that improve safety and efficiency,characterized by complex scenarios,strong uncertainty,and high real-time requirements.Deep reinforcement learning(DRL)exhibits excellent capability of real-time decision-making and adaptability to complex scenarios,and generalization abilities.However,it is arduous to guarantee complete driving safety and efficiency under the constraints of training samples and costs.This paper proposes a Mixture of Expert method(MoE)based on Soft Actor-Critic(SAC),where the upper-level discriminator dynamically decides whether to activate the lower-level DRL expert or the heuristic expert based on the features of the input state.To further enhance the performance of the DRL expert,a buffer zone is introduced in the reward function,preemptively applying penalties before insecure situations occur.In order to minimize collision and off-road rates,the Intelligent Driver Model(IDM)and Minimizing Overall Braking Induced by Lane changes(MOBIL)strategy are designed by heuristic experts.Finally,tested in typical simulation scenarios,MOE shows a 13.75%improvement in driving efficiency compared with the traditional DRL method with continuous action space.It ensures high safety with zero collision and zero off-road rates while maintaining high adaptability.展开更多
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 the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(RS-2025-00559546)supported by the IITP(Institute of Information&Coummunications Technology Planning&Evaluation)-ITRC(Information Technology Research Center)grant funded by the Korea government(Ministry of Science and ICT)(IITP-2025-RS-2023-00259004).
文摘The advent of sixth-generation(6G)networks introduces unprecedented challenges in achieving seamless connectivity,ultra-low latency,and efficient resource management in highly dynamic environments.Although fifth-generation(5G)networks transformed mobile broadband and machine-type communications at massive scales,their properties of scaling,interference management,and latency remain a limitation in dense high mobility settings.To overcome these limitations,artificial intelligence(AI)and unmanned aerial vehicles(UAVs)have emerged as potential solutions to develop versatile,dynamic,and energy-efficient communication systems.The study proposes an AI-based UAV architecture that utilizes cooperative reinforcement learning(CoRL)to manage an autonomous network.The UAVs collaborate by sharing local observations and real-time state exchanges to optimize user connectivity,movement directions,allocate power,and resource distribution.Unlike conventional centralized or autonomous methods,CoRL involves joint state sharing and conflict-sensitive reward shaping,which ensures fair coverage,less interference,and enhanced adaptability in a dynamic urban environment.Simulations conducted in smart city scenarios with 10 UAVs and 50 ground users demonstrate that the proposed CoRL-based UAV system increases user coverage by up to 10%,achieves convergence 40%faster,and reduces latency and energy consumption by 30%compared with centralized and decentralized baselines.Furthermore,the distributed nature of the algorithm ensures scalability and flexibility,making it well-suited for future large-scale 6G deployments.The results highlighted that AI-enabled UAV systems enhance connectivity,support ultra-reliable low-latency communications(URLLC),and improve 6G network efficiency.Future work will extend the framework with adaptive modulation,beamforming-aware positioning,and real-world testbed deployment.
基金Under the auspices of Key Program of the National Natural Science Foundation of China(No.U2006215,U1806218)the National Key R&D Program of China(No.2017YFC0505902)。
文摘Spartina alterniflora invasions seriously threaten the structure and functions of coastal wetlands in China.In this study,the Suaeda salsa community in the Yellow River Estuary wetland was monitored using long-term Landsat satellite images acquired from 1997 to 2020 to quantify the impact of changes in hydrological connectivity induced by S.alterniflora on neighboring vegetation com-munities.The results showed that S.alterniflora rapidly expanded in the estuary area at a rate of 4.91 km^(2)/yr from 2010 to 2020.At the same time,the hydrological connectivity of the area and the distribution of S.salsa changed significantly.Small tidal creeks dominated the S.alterniflora landscape.The number of tidal creeks increased significantly,but their average length decreased and they tended to develop in a horizontal tree-like pattern.Affected by the changes in hydrological connectivity due to the S.alterniflora invasion,the area of S.salsa decreased by 41.1%,and the degree of landscape fragmentation increased from 1997 to 2020.Variations in the Largest Patch Index(LPI)indicated that the S.alterniflora landscape had become the dominant landscape type in the Yellow River Estuary.The res-ults of standard deviation ellipse(SDE)and Pearson’s correlation analyses indicated that a well-developed hydrological connectivity could promote the maintenance of the S.salsa landscape.The degradation of most S.salsa communities is caused by the influence of S.alterniflora on the morphological characteristics of the hydrological connectivity of tidal creek systems.
文摘Pavement condition monitoring and its timely maintenance is necessary to ensure the safety and quality of the roadway infrastructure. The International Roughness Index (IRI) is a commonly used measure to quantify road surface roughness and is a critical input to asset management. In Indiana, the IRI statistic contributes to roughly half of the pavement quality index computation used for asset management. Most agencies inventory IRI once a year, however, pavement conditions vary much more frequently. The objective of this paper is to develop a framework using crowdsourced connected vehicle data to identify and detect temporal changes in IRI. Over 3 billion connected vehicle records in Indiana were analyzed across 30 months between 2022 and 2024 to understand the spatiotemporal variations in roughness. Annual comparisons across all major interstates in Indiana showed the miles of interstates classified as “Good” decreased from 1896 to 1661 miles between 2022 and 2024. The miles of interstate classified as “Needs Maintenance” increased from 82 to 120 miles. A detailed case study showing monthly and daily changes of estimated IRI on I-65 are presented along with supporting dashcam images. Although the crowdsourced IRI estimates are not as robust as traditional specialized pavement profilers, they can be obtained on a monthly, weekly, or even daily basis. The paper concludes by suggesting a combination of frequent crowdsourced IRI and commercially available dashcam imagery of roadway can provide an agile and responsive mechanism for agencies to implement pavement asset management programs that can complement existing annual programs.
基金the National Natural Science Foundation of China(Grant No.52374051)the Joint Fund for Enterprise Innovation and Development of NSFC(Grant No.U24B2037).
文摘During oilfield development,a comprehensive model for assessing inter-well connectivity and connected volume within reservoirs is crucial.Traditional capacitance(TC)models,widely used in inter-well data analysis,face challenges when dealing with rapidly changing reservoir conditions over time.Additionally,TC models struggle with complex,random noise primarily caused by measurement errors in production and injection rates.To address these challenges,this study introduces a dynamic capacitance(SV-DC)model based on state variables.By integrating the extended Kalman filter(EKF)algorithm,the SV-DC model provides more flexible predictions of inter-well connectivity and time-lag efficiency compared to the TC model.The robustness of the SV-DC model is verified by comparing relative errors between preset and calculated values through Monte Carlo simulations.Sensitivity analysis was performed to compare the model performance with the benchmark,using the Qinhuangdao Oilfield as a case study.The results show that the SV-DC model accurately predicts water breakthrough times.Increases in the liquid production index and water cut in two typical wells indicate the development time of ineffective circulation channels,further confirming the accuracy and reliability of the model.The SV-DC model offers significant advantages in addressing complex,dynamic oilfield production scenarios and serves as a valuable tool for the efficient and precise planning and management of future oilfield developments.
文摘With the development of fast communication technology between ego vehicle and other traffic participants,and automated driving technology,there is a big potential in the improvement of energy efficiency of hybrid electric vehicles(HEVs).Moreover,the terrain along the driving route is a non-ignorable factor for energy efficiency of HEV running on the hilly streets.This paper proposes a look-ahead horizon-based optimal energy management strategy to jointly improve the efficiencies of powertrain and vehicle for connected and automated HEVs on the road with slope.Firstly,a rule-based framework is developed to guarantee the success of automated driving in the traffic scenario.Then a constrained optimal control problem is formulated to minimize the fuel consumption and the electricity consumption under the satisfaction of inter-vehicular distance constraint between ego vehicle and preceding vehicle.Both speed planning and torque split of hybrid powertrain are provided by the proposed approach.Moreover,the preceding vehicle speed in the look-ahead horizon is predicted by extreme learning machine with real-time data obtained from communication of vehicle-to-everything.The optimal solution is derived through the Pontryagin’s maximum principle.Finally,to verify the effectiveness of the proposed algorithm,a traffic-in-the-loop powertrain platform with data from real world traffic environment is built.It is found that the fuel economy for the proposed energy management strategy improves in average 17.0%in scenarios of different traffic densities,compared to the energy management strategy without prediction of preceding vehicle speed.
文摘January 30,Geneva,Switzerland&online As we step into a pivotal moment in the journey toward universal and meaningful connectivity,the Partner2Connect(P2C)Annual Meeting promises to be a transformative gathering of global leaders,innovators,and changemakers.This year’s programme reflects the dynamic and evolving spirit of P2C,offering engaging discussions,interactive sessions,and valuable networking opportunities.Together,we will not only celebrate our collective achievements but also confront the challenges that remain—ensuring that progress toward digital inclusion is sustainable and equitable.
基金supported by Prevention the Fundamental Research Funds for the Central Universities“Study on the general joint of prefabricated high-pier columns”(ZY20230218)Science and Technology Innovation Program for Postgraduate students in IDP subsidized by Fundamental Research Funds for the Central Universities“Research on seismic performance of prefabricated bridge piers with embedded separated steel connections”(ZY20250316).
文摘With the acceleration of urbanization,prefabricated bridges have become a significant choice for transportation infrastructure construction due to their environmental friendliness,efficiency,and reliable quality.However,existing connection technologies still face shortcomings in construction efficiency,seismic performance,and cost control.This paper summarizes the process characteristics of commonly used connection technologies such as socket connections,grouted sleeve connections and corrugated pipe connections,and analyzes their seismic capacity and mechanical performance.In response to existing issues,two new technologies—separated steel connection and multi-chamber steel tube concrete connection—are proposed,and their comprehensive performance and economic efficiency are analyzed.The new connection technologies outperform traditional methods in construction efficiency,economic efficiency,and structural stability,with more reasonable force distribution,clearer load transfer paths,and significantly reduced overall costs.Existing technologies,such as socket connections,perform well in seismic performance but are complex to construct;grouted sleeve connections are mature in technology,but the quality of grouting is difficult to inspect.The separated steel connection and multi-chamber steel tube concrete connection technologies offer significant advantages.With the increasing demands for energy conservation and emission reduction,coupled with the rising labor costs,prefabricated bridge piers are undoubtedly poised to become one of the preferred technologies for bridge construction in China in the future.Therefore,in light of the current research landscape,this paper concludes by offering a forward-looking perspective on the development directions of connection methods for prefabricated bridge piers and identifying key areas for future research.
基金supported by the Fundamental Research Funds for the Central Universities(No.2022JJ037).
文摘A borderless art form,film shoulders a mission of sharing culture and fostering emotional bonds.In the relationship between China and Thailand,cinema has long served as a vital cultural bridge,uniting the hearts and minds of the two peoples.From the screening of Chinese films in Thailand to the deepening collaboration within the film industry,the history of bilateral cinematic exchange not only showcases the unique value of film as a cultural medium but also reflects the resilience and vitality of grassroots cultural interactions amid a complex international landscape.This shared history,marked by both challenges and triumphs,has laid a solid foundation for future cultural cooperation,becoming a memorable chapter in the narrative of China-Thailand relations.
文摘Infrastructure and energy are two important areas for African countries to achieve sustainable development,as well as are among the priorities in the African Union’s Agenda 2063,the continent’s ambitious development blueprint.In February,Lerato Mataboge was elected as the African Union Commissioner for Infrastructure and Energy.She is a global policy and trade and investment facilitation expert and was the deputy director general in the South African Department of Trade,Industry and Competition when she was elected.
文摘Connective tissue is a dynamic structure that reacts to environmental cues to maintain homeostasis,including mechanical properties.Mechanical load influences extracellular matrix(ECM)—cell interactions and modulates cellular behavior.Mechano-regulation processes involve matrix modification and cell activation to preserve tissue function.The ECM remodeling is crucial for force transmission.Cytoskeleton components are involved in force sensing and transmission,affecting cellular adhesion,motility,and gene expression.Proper mechanical loading helps to maintain tissue health,while imbalances may lead to pathological processes.Active and passive movement,including manual mobilization,improves connective tissue elasticity,promotes ECM-cell homeostasis,and reduces fibrosis.In rehabilitation,understanding mechanical-regulation processes is necessary for ameliorating and developing treatments aimed at preserving tissue elasticity and preventing fibrosis.In this commentary,we aim to globally describe the biological processes involved in mechanical force transmission in connective tissue as support for translational studies and clinical applications in the rehabilitation field.
基金supported by the Guangzhou Municipal Key Discipline in Medicine(2021-2023)the Guangzhou High-level Clinical Key Specialty,the Guangzhou Research-oriented Hospital,the Innovative Clinical Technique of Guangzhou(2024-2026)+6 种基金the Guangdong Basic and Applied Basic Research Foundation(grant number 2022A1515011567,2020A1515110565)the Guangzhou Science,Technology Planning Project(grant number 202201010714,202103000032)the National Natural Science Foundation of China(grant number 82471546)the Guangdong College Students Innovation and Entrepreneurship Training Project(grant number S202310570038)the Guangzhou Health Science and Technology Project(grant number 20231A010038)the Guangzhou Traditional Chinese Medicine and Integrated Traditional Chinese and Western Medicine Technology Project(grant number:20232A010013)the Science and Technology Plan Project of Guangzhou(2023A03J0842).
文摘Background The heterogeneity of depression limits the treatment outcomes of intermittent theta burst stimulation(iTBS)and hinders the identification of predictive factors.This study investigated functional network connectivity and predictors of iTBS treatment outcomes in adolescents and young adults with depression.Aim This study aimed to identify default mode network(DMN)-based connectivity patterns associated with varying iTBS treatment outcomes in depression.Methods Data from a randomised controlled trial of iTBS in depression(n=82)were analysed using a data-driven approach to classify homogeneous subgroups based on the DMN.Connectivity subgroups were compared on depressive symptoms and cognitive function at pretreatment and post-treatment.Furthermore,the predictive significance of baseline inflammatory cytokines on post-treatment outcomes was evaluated.Results Two distinct subgroups were identified.Subgroup 1 exhibited high heterogeneity and greater centrality in the posterior cingulate cortex and retrosplenial cortex,while subgroup 2 showed more homogeneous connectivity patterns and greater centrality in the temporoparietal junction and posterior inferior parietal lobule.No main effect for subgroup,treatment or subgroup×treatment interaction was revealed in the improvement of depressive symptoms.A significant subgroup×treatment interaction related to symbol coding improvement was detected(F=5.22,p=0.026).Within subgroup 1,the active group showed significantly greater improvement in symbol coding compared with the sham group(t=2.30,p=0.028),while baseline levels of interleukin-6 and C-reactive protein emerged as significant indicators for predicting improvements in symbolic coding(R2=0.35,RMSE(root-mean-square error)=5.72,p=0.013).Subgroup 2 showed no significant findings in terms of cognitive improvement or inflammatory cytokines predictions.
基金Supported by National Key R&D Program of China(Grant No.2022YFB2503203)National Natural Science Foundation of China(Grant No.U1964206).
文摘Decision-making of connected and automated vehicles(CAV)includes a sequence of driving maneuvers that improve safety and efficiency,characterized by complex scenarios,strong uncertainty,and high real-time requirements.Deep reinforcement learning(DRL)exhibits excellent capability of real-time decision-making and adaptability to complex scenarios,and generalization abilities.However,it is arduous to guarantee complete driving safety and efficiency under the constraints of training samples and costs.This paper proposes a Mixture of Expert method(MoE)based on Soft Actor-Critic(SAC),where the upper-level discriminator dynamically decides whether to activate the lower-level DRL expert or the heuristic expert based on the features of the input state.To further enhance the performance of the DRL expert,a buffer zone is introduced in the reward function,preemptively applying penalties before insecure situations occur.In order to minimize collision and off-road rates,the Intelligent Driver Model(IDM)and Minimizing Overall Braking Induced by Lane changes(MOBIL)strategy are designed by heuristic experts.Finally,tested in typical simulation scenarios,MOE shows a 13.75%improvement in driving efficiency compared with the traditional DRL method with continuous action space.It ensures high safety with zero collision and zero off-road rates while maintaining high adaptability.
