This study constructs a reflective feedback model based on a pedagogical agent(PA)and explores its impact on students’problem-solving ability and cognitive load.A quasi-experimental design was used in the study,with ...This study constructs a reflective feedback model based on a pedagogical agent(PA)and explores its impact on students’problem-solving ability and cognitive load.A quasi-experimental design was used in the study,with 84 students from a middle school selected as the research subjects(44 in the experimental group and 40 in the control group).The experimental group used the reflective feedback model,while the control group used the factual feedback model.The results show that,compared with factual feedback,the reflective feedback model based on the pedagogical agent significantly improves students’problem-solving ability,especially at the action and thinking levels.In addition,this model effectively reduces students’cognitive load,especially in terms of internal and external load.展开更多
This study examines the current state of vocational education in Guizhou and its role in facilitating the export of Guizhou goods beyond regional boundaries, and explores various strategies for vocational education to...This study examines the current state of vocational education in Guizhou and its role in facilitating the export of Guizhou goods beyond regional boundaries, and explores various strategies for vocational education to contribute to rural revitalization, including the optimization of professional and curriculum systems, the deepening of industry-education integration and school-enterprise cooperation, the enhancement of brand development and marketing efforts, the strengthening of cross-border e-commerce and international cooperation capabilities, and the improvement of policy support and resource allocation systems. The findings aim to provide a theoretical foundation for Guizhou vocational education to support local economic development.展开更多
Monkeypox virus(MPXV),a member of the Orthopoxvirus genus,caused a large-scale global outbreak in 2022.Developing mouse models for MPXV infection is crucial for advancing research on vaccines and therapeutic intervent...Monkeypox virus(MPXV),a member of the Orthopoxvirus genus,caused a large-scale global outbreak in 2022.Developing mouse models for MPXV infection is crucial for advancing research on vaccines and therapeutic interventions.To address this,we conducted a comparative study on the susceptibility of six mouse strains—severe combined immune-deficiency(SCID),nude,genetically diabetic(db/db)and obese(ob/ob),C57BL/6J,and BALB/c—to MPXV infection.Mouse strains were infected with MPXV via intranasal inoculation,and body weight changes and mortality were monitored post-infection.Additionally,the tissue distribution of MPXV and the pathological changes in the lung tissues of the infected mice were evaluated.The results demonstrated that SCID and nude mice exhibited significant weight loss following MPXV infection,with 100%mortality observed in SCID mice,while no mortality occurred in nude mice.In contrast,the other mouse strains showed no significant weight loss or mortality.Notably,the viral load in the lung tissues of SCID and nude mice was the highest among the tested strains.Furthermore,we investigated the impact of different inoculation routes—intranasal(I.N.),intraperitoneal(I.P.),and intravenous(I.V.)—on the pathogenicity of MPXV in mice.The results revealed that the intravenous route induced more pronounced pathogenic effects compared to the intranasal and intraperitoneal routes.In summary,this study provides valuable insights into the development of MPXV-infected mouse models,offering a foundation for further research on MPXV pathogenesis and therapeutic drug development.展开更多
Microstructure and mechanical properties of aged Mg-10Gd-2Y-0.4Zr-0.4Ag alloy sheets prepared by different rolling routes were investigated.The results showed that the cross rolling aged(CRA)sheet possesses larger gra...Microstructure and mechanical properties of aged Mg-10Gd-2Y-0.4Zr-0.4Ag alloy sheets prepared by different rolling routes were investigated.The results showed that the cross rolling aged(CRA)sheet possesses larger grain size than unidirectional rolling aged(URA)sheet due to the occurrence of dynamic recovery during rolling which reduces the dislocation density and delays dynamic recrystallization(DRX).The URA sheet has basal texture and RD favored texture while CRA sheet has multiple-peak texture.Both sheets precipitate β'phase and CRA sheet exhibits a stronger aging response.The CRA sheet has higher yield strength and tensile strength than URA sheet,with reduced yield strength anisotropy but increased tensile strength anisotropy.Taking into account different strengthening mechanisms,although the finer grain size of URA sheet enhances grain boundary strengthening,CRA sheet is more responsive to aging,leading to superior aging-precipitated phase strengthening and consequently higher yield strength.展开更多
Due to the substantial and continuous growth of transportation demand in China,the existing highway capacity has become insufficient to meet the increasing traffic volume.The implementation of highway reconstruction a...Due to the substantial and continuous growth of transportation demand in China,the existing highway capacity has become insufficient to meet the increasing traffic volume.The implementation of highway reconstruction and expansion projects has gradually become a key measure to improve the service level of the road network and alleviate traffic congestion.Meanwhile,route design is a core aspect of highway reconstruction and expansion projects,and its scientific nature and quality can directly affect the safety,economy,and future operational efficiency of the highway.Therefore,this article provides a detailed analysis of the principles and requirements of route design for highway reconstruction and expansion projects.Additionally,it delves into the design process and key technologies applied in route design for these projects.展开更多
A dual-halide solid electrolyte,Li_(3)YCl_(3)Br_(3),was synthesized using a wet-chemistry route instead of the conventional mechanical ball-milling route.Li_(3)YCl_(3)Br_(3) exhibits an ion conductivity of 2.08 mS/cm ...A dual-halide solid electrolyte,Li_(3)YCl_(3)Br_(3),was synthesized using a wet-chemistry route instead of the conventional mechanical ball-milling route.Li_(3)YCl_(3)Br_(3) exhibits an ion conductivity of 2.08 mS/cm and an electro-chemical stability window of 3.8 V.Additionally,an all-solid-state lithium-ion battery using Li_(3)YCl_(3)Br_(3) and LiNi_(0.83)Co_(0.11)Mn_(0.06)O_(2)(NCM811)as the cathode material achieves a capacity retention of 93%after 200 cycles at 0.3C and maintains a specific capacity of 115 mA·h/g during 2C cycling.This exceptional performance is attributed to the high oxidative stability of Li_(3)YCl_(3)Br_(3) and the in-situ formation of Y_(2)O_(3) inert protective layer on the NCM811 surface under high voltage.Consequently,the study demonstrates the feasibility of a simple,cost-effective wet-chemistry route for synthesizing multi-component halides,highlighting its potential for large-scale production of halide solid electrolytes for practical applications.展开更多
Meta-heuristic evolutionary algorithms have become widely used for solving complex optimization problems.However,their effectiveness in real-world applications is often limited by the need for many evaluations,which c...Meta-heuristic evolutionary algorithms have become widely used for solving complex optimization problems.However,their effectiveness in real-world applications is often limited by the need for many evaluations,which can be both costly and time-consuming.This is especially true for large-scale transportation networks,where the size of the problem and the high computational cost can hinder the algorithm’s performance.To address these challenges,recent research has focused on using surrogate-assisted models.These models aim to reduce the number of expensive evaluations and improve the efficiency of solving time-consuming optimization problems.This paper presents a new two-layer Surrogate-Assisted Fish Migration Optimization(SA-FMO)algorithm designed to tackle high-dimensional and computationally heavy problems.The global surrogate model offers a good approximation of the entire problem space,while the local surrogate model focuses on refining the solution near the current best option,improving local optimization.To test the effectiveness of the SA-FMO algorithm,we first conduct experiments using six benchmark functions in a 50-dimensional space.We then apply the algorithm to optimize urban rail transit routes,focusing on the Train Routing Optimization problem.This aims to improve operational efficiency and vehicle turnover in situations with uneven passenger flow during transit disruptions.The results show that SA-FMO can effectively improve optimization outcomes in complex transportation scenarios.展开更多
Ecological barriers present significant challenges to bird migration by limiting the availability of stopover sites and shelters. The Qinghai-Tibet Plateau, a major migratory barrier located in higher latitude Central...Ecological barriers present significant challenges to bird migration by limiting the availability of stopover sites and shelters. The Qinghai-Tibet Plateau, a major migratory barrier located in higher latitude Central Asia, exerts a substantial influence on avian migration patterns. Species traversing such ecological barriers may adopt multiple optimal routes, which can contribute to the formation of migratory divides. From 2018 to 2021, the migration routes of 13 adult Common Cuckoos (Cuculus canorus) breeding in the north of the Qinghai-Tibet Plateau were tracked using satellite transmitters. We found Common Cuckoos have two primary migration routes: western and eastern, respectively following western and eastern edges of the Qinghai-Tibet plateau. The eastern and western routes are likely the optimal routes for the Central Asian Common Cuckoos population to navigate the Qinghai-Tibet Plateau. Furthermore, two individuals exhibited intermediate migration routes, suggesting attempted traverses of the Qinghai-Tibet Plateau, although neither completed the migration. These intermediate routes may indicate migratory behavior influenced by hybridization between eastern and western populations or migratory flexibility. Common Cuckoos exhibit significantly faster migration speed, flight speed, and shorter stopover durations during spring compared to autumn. The observed seasonal differences in migration behavior support birds following time-minimization strategies during spring migration. These results revealed the diverse migration routes of Common Cuckoos shaped by the Qinghai-Tibet Plateau and seasonal variation in migration patterns.展开更多
Advancements in artificial intelligence and big data technologies have led to the gradual emergence of intelligent ships,which are expected to dominate the future of maritime transportation.Supporting the navigation o...Advancements in artificial intelligence and big data technologies have led to the gradual emergence of intelligent ships,which are expected to dominate the future of maritime transportation.Supporting the navigation of intelligent ships,route planning technologies have developed many route planning algorithms that prioritize economy and safety.This paper conducts an in-depth study of algorithm efficiency for a route planning problem,proposing an intelligent ship route planning algorithm based on the adaptive step size Informed-RRT^(*).This algorithm can quickly plan a short route according to automatic obstacle avoidance and is suitable for planning the routes of intelligent ships.Results show that the adaptive step size Informed-RRT^(*) algorithm can shorten the optimal route length by approximately 13.05%while ensuring the running time of the planning algorithm and avoiding approximately 23.64%of redundant sampling nodes.The improved algorithm effectively circumvents unnecessary calculations and reduces a large amount of redundant sampling data,thus improving the efficiency of route planning.In a complex water environment,the unique adaptive step size mechanism enables this algorithm to prevent restricted search tree expansion,showing strong search ability and robustness,which is of practical significance for the development of intelligent ships.展开更多
The real-time path optimization for heterogeneous vehicle fleets in large-scale road networks presents significant challenges due to conflicting traffic demands and imbalanced resource allocation.While existing vehicl...The real-time path optimization for heterogeneous vehicle fleets in large-scale road networks presents significant challenges due to conflicting traffic demands and imbalanced resource allocation.While existing vehicleto-infrastructure coordination frameworks partially address congestion mitigation,they often neglect priority-aware optimization and exhibit algorithmic bias toward dominant vehicle classes—critical limitations in mixed-priority scenarios involving emergency vehicles.To bridge this gap,this study proposes a preference game-theoretic coordination framework with adaptive strategy transfer protocol,explicitly balancing system-wide efficiency(measured by network throughput)with priority vehicle rights protection(quantified via time-sensitive utility functions).The approach innovatively combines(1)a multi-vehicle dynamic routing model with quantifiable preference weights,and(2)a distributed Nash equilibrium solver updated using replicator sub-dynamic models.The framework was evaluated on an urban road network containing 25 intersections with mixed priority ratios(10%–30%of vehicles with priority access demand),and the framework showed consistent benefits on four benchmarks(Social routing algorithm,Shortest path algorithm,The comprehensive path optimisation model,The emergency vehicle timing collaborative evolution path optimization method)showed consistent benefits.Results showthat across different traffic demand configurations,the proposed method reduces the average vehicle traveling time by at least 365 s,increases the road network throughput by 48.61%,and effectively balances the road loads.This approach successfully meets the diverse traffic demands of various vehicle types while optimizing road resource allocations.The proposed coordination paradigm advances theoretical foundations for fairness-aware traffic optimization while offering implementable strategies for next-generation cooperative vehicle-road systems,particularly in smart city deployments requiring mixed-priority mobility guarantees.展开更多
Due to global warming and diminishing ice cover in Arctic regions,the northern sea route(NSR)has attracted increasing attention in recent years.Extreme cold temperatures and high wind speeds in Arctic regions present ...Due to global warming and diminishing ice cover in Arctic regions,the northern sea route(NSR)has attracted increasing attention in recent years.Extreme cold temperatures and high wind speeds in Arctic regions present substantial risks to vessels operating along the NSR.Consequently,analyzing extreme temperature and wind speed values along the NSR is essential for ensuring maritime operational safety in the region.This study analyzes wind and temperature data spanning 40 years,from 1981 to 2020,at four representative sites along the NSR for extreme value analysis.The average conditional exceedance rate(ACER)method and the Gumbel method are employed to estimate extreme wind speed and air temperature at these sites.Comparative analysis reveals that the ACER method provides higher accuracy and lower uncertainty in estimations.The predicted extreme wind speed for a 100-year return period is 30.36 m/s,with a minimum temperature of-56.66°C,varying across the four sites.Furthermore,the study presents extreme values corresponding to each return period,providing temperature extremes as a basis for guiding steel thickness specifications.These findings provide valuable reference for designing polar vessels and offshore structures,contributing to enhanced engineering standards for Arctic conditions.展开更多
To improve the efficiency of ship traffic in frequently traded sea areas and respond to the national“dual-carbon”strategy,a multi-objective ship route induction model is proposed.Considering the energy-saving and en...To improve the efficiency of ship traffic in frequently traded sea areas and respond to the national“dual-carbon”strategy,a multi-objective ship route induction model is proposed.Considering the energy-saving and environmental issues of ships,this study aims to improve the transportation efficiency of ships by providing a ship route induction method.Ship data from a certain bay during a defined period are collected,and an improved backpropagation neural network algorithm is used to forecast ship traffic.On the basis of the forecasted data and ship route induction objectives,dynamic programming of ship routes is performed.Experimental results show that the routes planned using this induction method reduce the combined cost by 17.55%compared with statically induced routes.This method has promising engineering applications in improving ship navigation efficiency,promoting energy conservation,and reducing emissions.展开更多
With the rapid development of low-altitude economy and unmanned aerial vehicles (UAVs) deployment technology, aerial-ground collaborative delivery (AGCD) is emerging as a novel mode of last-mile delivery, where the ve...With the rapid development of low-altitude economy and unmanned aerial vehicles (UAVs) deployment technology, aerial-ground collaborative delivery (AGCD) is emerging as a novel mode of last-mile delivery, where the vehicle and its onboard UAVs are utilized efficiently. Vehicles not only provide delivery services to customers but also function as mobile ware-houses and launch/recovery platforms for UAVs. This paper addresses the vehicle routing problem with UAVs considering time window and UAV multi-delivery (VRPU-TW&MD). A mixed integer linear programming (MILP) model is developed to mini-mize delivery costs while incorporating constraints related to UAV energy consumption. Subsequently, a micro-evolution aug-mented large neighborhood search (MEALNS) algorithm incor-porating adaptive large neighborhood search (ALNS) and micro-evolution mechanism is proposed. Numerical experiments demonstrate the effectiveness of both the model and algorithm in solving the VRPU-TW&MD. The impact of key parameters on delivery performance is explored by sensitivity analysis.展开更多
The rapid evolution of unmanned aerial vehicle(UAV)technology and autonomous capabilities has positioned UAV as promising last-mile delivery means.Vehicle and onboard UAV collaborative delivery is introduced as a nove...The rapid evolution of unmanned aerial vehicle(UAV)technology and autonomous capabilities has positioned UAV as promising last-mile delivery means.Vehicle and onboard UAV collaborative delivery is introduced as a novel delivery mode.Spatiotemporal collaboration,along with energy consumption with payload and wind conditions play important roles in delivery route planning.This paper introduces the traveling salesman problem with time window and onboard UAV(TSPTWOUAV)and emphasizes the consideration of real-world scenarios,focusing on time collaboration and energy consumption with wind and payload.To address this,a mixed integer linear programming(MILP)model is formulated to minimize the energy consumption costs of vehicle and UAV.Furthermore,an adaptive large neighborhood search(ALNS)algorithm is applied to identify high-quality solutions efficiently.The effectiveness of the proposed model and algorithm is validated through numerical tests on real geographic instances and sensitivity analysis of key parameters is conducted.展开更多
BACKGROUND Colorectal cancer(CRC)is a global health concern,with advanced-stage diagnoses contributing to poor prognoses.The efficacy of CRC screening has been well-established;nevertheless,a significant proportion of...BACKGROUND Colorectal cancer(CRC)is a global health concern,with advanced-stage diagnoses contributing to poor prognoses.The efficacy of CRC screening has been well-established;nevertheless,a significant proportion of patients remain unscreened,with>70%of cases diagnosed outside screening.Although identifying specific subgroups for whom CRC screening should be particularly recommended is crucial owing to limited resources,the association between the diagnostic routes and identification of these subgroups has been less appreciated.In the Japanese cancer registry,the diagnostic routes for groups discovered outside of screening are primarily categorized into those with comorbidities found during hospital visits and those with CRC-related symptoms.AIM To clarify the stage at CRC diagnosis based on diagnostic routes.METHODS We conducted a retrospective observational study using a cancer registry of patients with CRC between January 2016 and December 2019 at two hospitals.The diagnostic routes were primarily classified into three groups:Cancer screening,follow-up,and symptomatic.The early-stage was defined as Stages 0 or I.Multivariate and univariate logistic regressions were exploited to determine the odds of early-stage diagnosis in the symptomatic and cancer screening groups,referencing the follow-up group.The adjusted covariates were age,sex,and tumor location.RESULTS Of the 2083 patients,715(34.4%),1064(51.1%),and 304(14.6%)belonged to the follow-up,symptomatic,and cancer screening groups,respectively.Among the 2083 patients,CRCs diagnosed at an early stage were 57.3%(410 of 715),23.9%(254 of 1064),and 59.5%(181 of 304)in the follow-up,symptomatic,and cancer screening groups,respectively.The symptomatic group exhibited a lower likelihood of early-stage diagnosis than the follow-up group[P<0.001,adjusted odds ratio(aOR),0.23;95%confidence interval(95%CI):0.19-0.29].The likelihood of diagnosis at an early stage was similar between the follow-up and cancer screening groups(P=0.493,aOR for early-stage diagnosis in the cancer screening group vs follow-up group=1.11;95%CI=0.82-1.49).CONCLUSION CRCs detected during hospital visits for comorbidities were diagnosed earlier,similar to cancer screening.CRC screening should be recommended,particularly for patients without periodical hospital visits for comorbidities.展开更多
The ability to predict the anti-interference communications performance of unmanned aerial vehicle(UAV)data links is critical for intelligent route planning of UAVs in real combat scenarios.Previous research in this a...The ability to predict the anti-interference communications performance of unmanned aerial vehicle(UAV)data links is critical for intelligent route planning of UAVs in real combat scenarios.Previous research in this area has encountered several limitations:Classifiers exhibit low training efficiency,their precision is notably reduced when dealing with imbalanced samples,and they cannot be applied to the condition where the UAV’s flight altitude and the antenna bearing vary.This paper proposes the sequential Latin hypercube sampling(SLHS)-support vector machine(SVM)-AdaBoost algorithm,which enhances the training efficiency of the base classifier and circumvents local optima during the search process through SLHS optimization.Additionally,it mitigates the bottleneck of sample imbalance by adjusting the sample weight distribution using the AdaBoost algorithm.Through comparison,the modeling efficiency,prediction accuracy on the test set,and macro-averaged values of precision,recall,and F1-score for SLHS-SVM-AdaBoost are improved by 22.7%,5.7%,36.0%,25.0%,and 34.2%,respectively,compared with Grid-SVM.Additionally,these values are improved by 22.2%,2.1%,11.3%,2.8%,and 7.4%,respectively,compared with particle swarm optimization(PSO)-SVM-AdaBoost.Combining Latin hypercube sampling with the SLHS-SVM-AdaBoost algorithm,the classification prediction model of anti-interference performance of UAV data links,which took factors like three-dimensional position of UAV and antenna bearing into consideration,is established and used to assess the safety of the classical flying path and optimize the flying route.It was found that the risk of loss of communications could not be completely avoided by adjusting the flying altitude based on the classical path,whereas intelligent path planning based on the classification prediction model of anti-interference performance can realize complete avoidance of being interfered meanwhile reducing the route length by at least 2.3%,thus benefiting both safety and operation efficiency.展开更多
Demand Responsive Transit (DRT) responds to the dynamic users’ requests without any fixed routes and timetablesand determines the stop and the start according to the demands. This study explores the optimization of d...Demand Responsive Transit (DRT) responds to the dynamic users’ requests without any fixed routes and timetablesand determines the stop and the start according to the demands. This study explores the optimization of dynamicvehicle scheduling and real-time route planning in urban public transportation systems, with a focus on busservices. It addresses the limitations of current shared mobility routing algorithms, which are primarily designedfor simpler, single origin/destination scenarios, and do not meet the complex demands of bus transit systems. Theresearch introduces an route planning algorithm designed to dynamically accommodate passenger travel needsand enable real-time route modifications. Unlike traditional methods, this algorithm leverages a queue-based,multi-objective heuristic A∗ approach, offering a solution to the inflexibility and limited coverage of suburbanbus routes. Also, this study conducts a comparative analysis of the proposed algorithm with solutions based onGenetic Algorithm (GA) and Ant Colony Optimization Algorithm (ACO), focusing on calculation time, routelength, passenger waiting time, boarding time, and detour rate. The findings demonstrate that the proposedalgorithmsignificantly enhances route planning speed, achieving an 80–100-fold increase in efficiency over existingmodels, thereby supporting the real-time demands of Demand-Responsive Transportation (DRT) systems. Thestudy concludes that this algorithm not only optimizes route planning in bus transit but also presents a scalablesolution for improving urban mobility.展开更多
The emergence of beyond 5G networks has the potential for seamless and intelligent connectivity on a global scale.Network slicing is crucial in delivering services for different,demanding vertical applications in this...The emergence of beyond 5G networks has the potential for seamless and intelligent connectivity on a global scale.Network slicing is crucial in delivering services for different,demanding vertical applications in this context.Next-generation applications have time-sensitive requirements and depend on the most efficient routing path to ensure packets reach their intended destinations.However,the existing IP(Internet Protocol)over a multi-domain network faces challenges in enforcing network slicing due to minimal collaboration and information sharing among network operators.Conventional inter-domain routing methods,like Border Gateway Protocol(BGP),cannot make routing decisions based on performance,which frequently results in traffic flowing across congested paths that are never optimal.To address these issues,we propose CoopAI-Route,a multi-agent cooperative deep reinforcement learning(DRL)system utilizing hierarchical software-defined networks(SDN).This framework enforces network slicing in multi-domain networks and cooperative communication with various administrators to find performance-based routes in intra-and inter-domain.CoopAI-Route employs the Distributed Global Topology(DGT)algorithm to define inter-domain Quality of Service(QoS)paths.CoopAI-Route uses a DRL agent with a message-passing multi-agent Twin-Delayed Deep Deterministic Policy Gradient method to ensure optimal end-to-end routes adapted to the specific requirements of network slicing applications.Our evaluation demonstrates CoopAI-Route’s commendable performance in scalability,link failure handling,and adaptability to evolving topologies compared to state-of-the-art methods.展开更多
VOCs can exert great harm to both human and environment,and catalytic oxidation is believed to be an effective technique to eliminate these pollutants.In this paper,Ag-Mn bimetal catalysts with 10 wt.%of silver were s...VOCs can exert great harm to both human and environment,and catalytic oxidation is believed to be an effective technique to eliminate these pollutants.In this paper,Ag-Mn bimetal catalysts with 10 wt.%of silver were synthesized using doping,impregnation,and reduction methods respectively,and then they were applied to the catalytic oxidation of benzene.Through series of characterizations it showed that the loading of silver using reduction method significantly resulted in improved physico-chemical properties of manganese oxides,such as larger surface area and pore volume,higher proportion of surface Mn~(3+)and Mn~(4+),stronger reducibility and more active of surface oxygen species,which were all beneficial to its catalytic activity.As a result,the Ag-Mn catalysts synthesized by reduction method showed a lower T_(90)value(equals to the temperature at which 90%of initial benzene was removed)of 203℃.Besides,both the used and fresh Ag-Mn catalysts synthesized by reduction method showed preferable stability in this research.展开更多
基金023 Zhejiang Provincial Department of Education General Project:Research on an interdisciplinary teaching model to promote the development of computational thinking in the context of the new curriculum standards[Grant NO:Y202351596]Key Project of Zhejiang Provincial Education Science Planning:Research on an interdisciplinary teaching model to promote students’computational thinking from multiple analytical perspectives[Grant NO:2025SB103].
文摘This study constructs a reflective feedback model based on a pedagogical agent(PA)and explores its impact on students’problem-solving ability and cognitive load.A quasi-experimental design was used in the study,with 84 students from a middle school selected as the research subjects(44 in the experimental group and 40 in the control group).The experimental group used the reflective feedback model,while the control group used the factual feedback model.The results show that,compared with factual feedback,the reflective feedback model based on the pedagogical agent significantly improves students’problem-solving ability,especially at the action and thinking levels.In addition,this model effectively reduces students’cognitive load,especially in terms of internal and external load.
基金Supported by 2024 Planning Project of the China Vocational Education Association"Research and Practice on the Route of Guizhou Vocational Education in Serving the Export of Guizhou Goods Beyond Regional Boundaries in the Context of Rural Revitalization".
文摘This study examines the current state of vocational education in Guizhou and its role in facilitating the export of Guizhou goods beyond regional boundaries, and explores various strategies for vocational education to contribute to rural revitalization, including the optimization of professional and curriculum systems, the deepening of industry-education integration and school-enterprise cooperation, the enhancement of brand development and marketing efforts, the strengthening of cross-border e-commerce and international cooperation capabilities, and the improvement of policy support and resource allocation systems. The findings aim to provide a theoretical foundation for Guizhou vocational education to support local economic development.
基金financially supported by the National Key Research and Development Program of China(No.2023YFD1800403 and 2023YFD1800404)。
文摘Monkeypox virus(MPXV),a member of the Orthopoxvirus genus,caused a large-scale global outbreak in 2022.Developing mouse models for MPXV infection is crucial for advancing research on vaccines and therapeutic interventions.To address this,we conducted a comparative study on the susceptibility of six mouse strains—severe combined immune-deficiency(SCID),nude,genetically diabetic(db/db)and obese(ob/ob),C57BL/6J,and BALB/c—to MPXV infection.Mouse strains were infected with MPXV via intranasal inoculation,and body weight changes and mortality were monitored post-infection.Additionally,the tissue distribution of MPXV and the pathological changes in the lung tissues of the infected mice were evaluated.The results demonstrated that SCID and nude mice exhibited significant weight loss following MPXV infection,with 100%mortality observed in SCID mice,while no mortality occurred in nude mice.In contrast,the other mouse strains showed no significant weight loss or mortality.Notably,the viral load in the lung tissues of SCID and nude mice was the highest among the tested strains.Furthermore,we investigated the impact of different inoculation routes—intranasal(I.N.),intraperitoneal(I.P.),and intravenous(I.V.)—on the pathogenicity of MPXV in mice.The results revealed that the intravenous route induced more pronounced pathogenic effects compared to the intranasal and intraperitoneal routes.In summary,this study provides valuable insights into the development of MPXV-infected mouse models,offering a foundation for further research on MPXV pathogenesis and therapeutic drug development.
基金Project(2023GK2020)supported by the Key Research and Development Program of Hunan Province,China。
文摘Microstructure and mechanical properties of aged Mg-10Gd-2Y-0.4Zr-0.4Ag alloy sheets prepared by different rolling routes were investigated.The results showed that the cross rolling aged(CRA)sheet possesses larger grain size than unidirectional rolling aged(URA)sheet due to the occurrence of dynamic recovery during rolling which reduces the dislocation density and delays dynamic recrystallization(DRX).The URA sheet has basal texture and RD favored texture while CRA sheet has multiple-peak texture.Both sheets precipitate β'phase and CRA sheet exhibits a stronger aging response.The CRA sheet has higher yield strength and tensile strength than URA sheet,with reduced yield strength anisotropy but increased tensile strength anisotropy.Taking into account different strengthening mechanisms,although the finer grain size of URA sheet enhances grain boundary strengthening,CRA sheet is more responsive to aging,leading to superior aging-precipitated phase strengthening and consequently higher yield strength.
文摘Due to the substantial and continuous growth of transportation demand in China,the existing highway capacity has become insufficient to meet the increasing traffic volume.The implementation of highway reconstruction and expansion projects has gradually become a key measure to improve the service level of the road network and alleviate traffic congestion.Meanwhile,route design is a core aspect of highway reconstruction and expansion projects,and its scientific nature and quality can directly affect the safety,economy,and future operational efficiency of the highway.Therefore,this article provides a detailed analysis of the principles and requirements of route design for highway reconstruction and expansion projects.Additionally,it delves into the design process and key technologies applied in route design for these projects.
基金financially supported by Hunan Provincial Science and Technology Department,China(No.2021JJ10058)Key Research and Development Program of Hunan Province,China(No.2023GK2016)。
文摘A dual-halide solid electrolyte,Li_(3)YCl_(3)Br_(3),was synthesized using a wet-chemistry route instead of the conventional mechanical ball-milling route.Li_(3)YCl_(3)Br_(3) exhibits an ion conductivity of 2.08 mS/cm and an electro-chemical stability window of 3.8 V.Additionally,an all-solid-state lithium-ion battery using Li_(3)YCl_(3)Br_(3) and LiNi_(0.83)Co_(0.11)Mn_(0.06)O_(2)(NCM811)as the cathode material achieves a capacity retention of 93%after 200 cycles at 0.3C and maintains a specific capacity of 115 mA·h/g during 2C cycling.This exceptional performance is attributed to the high oxidative stability of Li_(3)YCl_(3)Br_(3) and the in-situ formation of Y_(2)O_(3) inert protective layer on the NCM811 surface under high voltage.Consequently,the study demonstrates the feasibility of a simple,cost-effective wet-chemistry route for synthesizing multi-component halides,highlighting its potential for large-scale production of halide solid electrolytes for practical applications.
基金supported by the National Natural Science Foundation of China(Project No.52172321,52102391)Sichuan Province Science and Technology Innovation Talent Project(2024JDRC0020)+1 种基金China Shenhua Energy Company Limited Technology Project(GJNY-22-7/2300-K1220053)Key science and technology projects in the transportation industry of the Ministry of Transport(2022-ZD7-132).
文摘Meta-heuristic evolutionary algorithms have become widely used for solving complex optimization problems.However,their effectiveness in real-world applications is often limited by the need for many evaluations,which can be both costly and time-consuming.This is especially true for large-scale transportation networks,where the size of the problem and the high computational cost can hinder the algorithm’s performance.To address these challenges,recent research has focused on using surrogate-assisted models.These models aim to reduce the number of expensive evaluations and improve the efficiency of solving time-consuming optimization problems.This paper presents a new two-layer Surrogate-Assisted Fish Migration Optimization(SA-FMO)algorithm designed to tackle high-dimensional and computationally heavy problems.The global surrogate model offers a good approximation of the entire problem space,while the local surrogate model focuses on refining the solution near the current best option,improving local optimization.To test the effectiveness of the SA-FMO algorithm,we first conduct experiments using six benchmark functions in a 50-dimensional space.We then apply the algorithm to optimize urban rail transit routes,focusing on the Train Routing Optimization problem.This aims to improve operational efficiency and vehicle turnover in situations with uneven passenger flow during transit disruptions.The results show that SA-FMO can effectively improve optimization outcomes in complex transportation scenarios.
基金supported by the National Natural Science Foundation of China(Grant No.31672296).
文摘Ecological barriers present significant challenges to bird migration by limiting the availability of stopover sites and shelters. The Qinghai-Tibet Plateau, a major migratory barrier located in higher latitude Central Asia, exerts a substantial influence on avian migration patterns. Species traversing such ecological barriers may adopt multiple optimal routes, which can contribute to the formation of migratory divides. From 2018 to 2021, the migration routes of 13 adult Common Cuckoos (Cuculus canorus) breeding in the north of the Qinghai-Tibet Plateau were tracked using satellite transmitters. We found Common Cuckoos have two primary migration routes: western and eastern, respectively following western and eastern edges of the Qinghai-Tibet plateau. The eastern and western routes are likely the optimal routes for the Central Asian Common Cuckoos population to navigate the Qinghai-Tibet Plateau. Furthermore, two individuals exhibited intermediate migration routes, suggesting attempted traverses of the Qinghai-Tibet Plateau, although neither completed the migration. These intermediate routes may indicate migratory behavior influenced by hybridization between eastern and western populations or migratory flexibility. Common Cuckoos exhibit significantly faster migration speed, flight speed, and shorter stopover durations during spring compared to autumn. The observed seasonal differences in migration behavior support birds following time-minimization strategies during spring migration. These results revealed the diverse migration routes of Common Cuckoos shaped by the Qinghai-Tibet Plateau and seasonal variation in migration patterns.
文摘Advancements in artificial intelligence and big data technologies have led to the gradual emergence of intelligent ships,which are expected to dominate the future of maritime transportation.Supporting the navigation of intelligent ships,route planning technologies have developed many route planning algorithms that prioritize economy and safety.This paper conducts an in-depth study of algorithm efficiency for a route planning problem,proposing an intelligent ship route planning algorithm based on the adaptive step size Informed-RRT^(*).This algorithm can quickly plan a short route according to automatic obstacle avoidance and is suitable for planning the routes of intelligent ships.Results show that the adaptive step size Informed-RRT^(*) algorithm can shorten the optimal route length by approximately 13.05%while ensuring the running time of the planning algorithm and avoiding approximately 23.64%of redundant sampling nodes.The improved algorithm effectively circumvents unnecessary calculations and reduces a large amount of redundant sampling data,thus improving the efficiency of route planning.In a complex water environment,the unique adaptive step size mechanism enables this algorithm to prevent restricted search tree expansion,showing strong search ability and robustness,which is of practical significance for the development of intelligent ships.
基金funded by the National Key Research and Development Program Project 2022YFB4300404.
文摘The real-time path optimization for heterogeneous vehicle fleets in large-scale road networks presents significant challenges due to conflicting traffic demands and imbalanced resource allocation.While existing vehicleto-infrastructure coordination frameworks partially address congestion mitigation,they often neglect priority-aware optimization and exhibit algorithmic bias toward dominant vehicle classes—critical limitations in mixed-priority scenarios involving emergency vehicles.To bridge this gap,this study proposes a preference game-theoretic coordination framework with adaptive strategy transfer protocol,explicitly balancing system-wide efficiency(measured by network throughput)with priority vehicle rights protection(quantified via time-sensitive utility functions).The approach innovatively combines(1)a multi-vehicle dynamic routing model with quantifiable preference weights,and(2)a distributed Nash equilibrium solver updated using replicator sub-dynamic models.The framework was evaluated on an urban road network containing 25 intersections with mixed priority ratios(10%–30%of vehicles with priority access demand),and the framework showed consistent benefits on four benchmarks(Social routing algorithm,Shortest path algorithm,The comprehensive path optimisation model,The emergency vehicle timing collaborative evolution path optimization method)showed consistent benefits.Results showthat across different traffic demand configurations,the proposed method reduces the average vehicle traveling time by at least 365 s,increases the road network throughput by 48.61%,and effectively balances the road loads.This approach successfully meets the diverse traffic demands of various vehicle types while optimizing road resource allocations.The proposed coordination paradigm advances theoretical foundations for fairness-aware traffic optimization while offering implementable strategies for next-generation cooperative vehicle-road systems,particularly in smart city deployments requiring mixed-priority mobility guarantees.
基金supported by the National Natural Science Foundation of China(Grant No.52201379)the Fundamental Research Funds for the Central Universities(Grant No.WUT:3120622898)+2 种基金State Key Laboratory of Structural Analysis,Optimization and CAE Software for Industrial Equipment,Dalian University of Technology(Grant No.GZ 231088)Shanghai Key Laboratory of Naval Architecture Engineering(Grant No.SE202305)funded by European Research Council project under the European Union’s Horizon 2020 research and innovation program(Grant No.TRUST CoG 2019864724).
文摘Due to global warming and diminishing ice cover in Arctic regions,the northern sea route(NSR)has attracted increasing attention in recent years.Extreme cold temperatures and high wind speeds in Arctic regions present substantial risks to vessels operating along the NSR.Consequently,analyzing extreme temperature and wind speed values along the NSR is essential for ensuring maritime operational safety in the region.This study analyzes wind and temperature data spanning 40 years,from 1981 to 2020,at four representative sites along the NSR for extreme value analysis.The average conditional exceedance rate(ACER)method and the Gumbel method are employed to estimate extreme wind speed and air temperature at these sites.Comparative analysis reveals that the ACER method provides higher accuracy and lower uncertainty in estimations.The predicted extreme wind speed for a 100-year return period is 30.36 m/s,with a minimum temperature of-56.66°C,varying across the four sites.Furthermore,the study presents extreme values corresponding to each return period,providing temperature extremes as a basis for guiding steel thickness specifications.These findings provide valuable reference for designing polar vessels and offshore structures,contributing to enhanced engineering standards for Arctic conditions.
基金Supported by the National Key R&D Program of China project (2017YFC0805309)the National Natural Science Foundation of China (60602020)。
文摘To improve the efficiency of ship traffic in frequently traded sea areas and respond to the national“dual-carbon”strategy,a multi-objective ship route induction model is proposed.Considering the energy-saving and environmental issues of ships,this study aims to improve the transportation efficiency of ships by providing a ship route induction method.Ship data from a certain bay during a defined period are collected,and an improved backpropagation neural network algorithm is used to forecast ship traffic.On the basis of the forecasted data and ship route induction objectives,dynamic programming of ship routes is performed.Experimental results show that the routes planned using this induction method reduce the combined cost by 17.55%compared with statically induced routes.This method has promising engineering applications in improving ship navigation efficiency,promoting energy conservation,and reducing emissions.
基金supported by the Fundamental Research Funds for the Central Universities(2024JBZX038)the National Natural Science Foundation of China(62076023).
文摘With the rapid development of low-altitude economy and unmanned aerial vehicles (UAVs) deployment technology, aerial-ground collaborative delivery (AGCD) is emerging as a novel mode of last-mile delivery, where the vehicle and its onboard UAVs are utilized efficiently. Vehicles not only provide delivery services to customers but also function as mobile ware-houses and launch/recovery platforms for UAVs. This paper addresses the vehicle routing problem with UAVs considering time window and UAV multi-delivery (VRPU-TW&MD). A mixed integer linear programming (MILP) model is developed to mini-mize delivery costs while incorporating constraints related to UAV energy consumption. Subsequently, a micro-evolution aug-mented large neighborhood search (MEALNS) algorithm incor-porating adaptive large neighborhood search (ALNS) and micro-evolution mechanism is proposed. Numerical experiments demonstrate the effectiveness of both the model and algorithm in solving the VRPU-TW&MD. The impact of key parameters on delivery performance is explored by sensitivity analysis.
基金Fundamental Research Funds for the Central Universities(2024JBZX038)National Natural Science F oundation of China(62076023)。
文摘The rapid evolution of unmanned aerial vehicle(UAV)technology and autonomous capabilities has positioned UAV as promising last-mile delivery means.Vehicle and onboard UAV collaborative delivery is introduced as a novel delivery mode.Spatiotemporal collaboration,along with energy consumption with payload and wind conditions play important roles in delivery route planning.This paper introduces the traveling salesman problem with time window and onboard UAV(TSPTWOUAV)and emphasizes the consideration of real-world scenarios,focusing on time collaboration and energy consumption with wind and payload.To address this,a mixed integer linear programming(MILP)model is formulated to minimize the energy consumption costs of vehicle and UAV.Furthermore,an adaptive large neighborhood search(ALNS)algorithm is applied to identify high-quality solutions efficiently.The effectiveness of the proposed model and algorithm is validated through numerical tests on real geographic instances and sensitivity analysis of key parameters is conducted.
基金the Foundation for Cancer Research supported by Kyoto Preventive Medical Center and the Japan Society for the Promotion of Science(JSPS)Grants-in-Aid KAKENHI,No.JP 22K21080.
文摘BACKGROUND Colorectal cancer(CRC)is a global health concern,with advanced-stage diagnoses contributing to poor prognoses.The efficacy of CRC screening has been well-established;nevertheless,a significant proportion of patients remain unscreened,with>70%of cases diagnosed outside screening.Although identifying specific subgroups for whom CRC screening should be particularly recommended is crucial owing to limited resources,the association between the diagnostic routes and identification of these subgroups has been less appreciated.In the Japanese cancer registry,the diagnostic routes for groups discovered outside of screening are primarily categorized into those with comorbidities found during hospital visits and those with CRC-related symptoms.AIM To clarify the stage at CRC diagnosis based on diagnostic routes.METHODS We conducted a retrospective observational study using a cancer registry of patients with CRC between January 2016 and December 2019 at two hospitals.The diagnostic routes were primarily classified into three groups:Cancer screening,follow-up,and symptomatic.The early-stage was defined as Stages 0 or I.Multivariate and univariate logistic regressions were exploited to determine the odds of early-stage diagnosis in the symptomatic and cancer screening groups,referencing the follow-up group.The adjusted covariates were age,sex,and tumor location.RESULTS Of the 2083 patients,715(34.4%),1064(51.1%),and 304(14.6%)belonged to the follow-up,symptomatic,and cancer screening groups,respectively.Among the 2083 patients,CRCs diagnosed at an early stage were 57.3%(410 of 715),23.9%(254 of 1064),and 59.5%(181 of 304)in the follow-up,symptomatic,and cancer screening groups,respectively.The symptomatic group exhibited a lower likelihood of early-stage diagnosis than the follow-up group[P<0.001,adjusted odds ratio(aOR),0.23;95%confidence interval(95%CI):0.19-0.29].The likelihood of diagnosis at an early stage was similar between the follow-up and cancer screening groups(P=0.493,aOR for early-stage diagnosis in the cancer screening group vs follow-up group=1.11;95%CI=0.82-1.49).CONCLUSION CRCs detected during hospital visits for comorbidities were diagnosed earlier,similar to cancer screening.CRC screening should be recommended,particularly for patients without periodical hospital visits for comorbidities.
文摘The ability to predict the anti-interference communications performance of unmanned aerial vehicle(UAV)data links is critical for intelligent route planning of UAVs in real combat scenarios.Previous research in this area has encountered several limitations:Classifiers exhibit low training efficiency,their precision is notably reduced when dealing with imbalanced samples,and they cannot be applied to the condition where the UAV’s flight altitude and the antenna bearing vary.This paper proposes the sequential Latin hypercube sampling(SLHS)-support vector machine(SVM)-AdaBoost algorithm,which enhances the training efficiency of the base classifier and circumvents local optima during the search process through SLHS optimization.Additionally,it mitigates the bottleneck of sample imbalance by adjusting the sample weight distribution using the AdaBoost algorithm.Through comparison,the modeling efficiency,prediction accuracy on the test set,and macro-averaged values of precision,recall,and F1-score for SLHS-SVM-AdaBoost are improved by 22.7%,5.7%,36.0%,25.0%,and 34.2%,respectively,compared with Grid-SVM.Additionally,these values are improved by 22.2%,2.1%,11.3%,2.8%,and 7.4%,respectively,compared with particle swarm optimization(PSO)-SVM-AdaBoost.Combining Latin hypercube sampling with the SLHS-SVM-AdaBoost algorithm,the classification prediction model of anti-interference performance of UAV data links,which took factors like three-dimensional position of UAV and antenna bearing into consideration,is established and used to assess the safety of the classical flying path and optimize the flying route.It was found that the risk of loss of communications could not be completely avoided by adjusting the flying altitude based on the classical path,whereas intelligent path planning based on the classification prediction model of anti-interference performance can realize complete avoidance of being interfered meanwhile reducing the route length by at least 2.3%,thus benefiting both safety and operation efficiency.
文摘Demand Responsive Transit (DRT) responds to the dynamic users’ requests without any fixed routes and timetablesand determines the stop and the start according to the demands. This study explores the optimization of dynamicvehicle scheduling and real-time route planning in urban public transportation systems, with a focus on busservices. It addresses the limitations of current shared mobility routing algorithms, which are primarily designedfor simpler, single origin/destination scenarios, and do not meet the complex demands of bus transit systems. Theresearch introduces an route planning algorithm designed to dynamically accommodate passenger travel needsand enable real-time route modifications. Unlike traditional methods, this algorithm leverages a queue-based,multi-objective heuristic A∗ approach, offering a solution to the inflexibility and limited coverage of suburbanbus routes. Also, this study conducts a comparative analysis of the proposed algorithm with solutions based onGenetic Algorithm (GA) and Ant Colony Optimization Algorithm (ACO), focusing on calculation time, routelength, passenger waiting time, boarding time, and detour rate. The findings demonstrate that the proposedalgorithmsignificantly enhances route planning speed, achieving an 80–100-fold increase in efficiency over existingmodels, thereby supporting the real-time demands of Demand-Responsive Transportation (DRT) systems. Thestudy concludes that this algorithm not only optimizes route planning in bus transit but also presents a scalablesolution for improving urban mobility.
文摘The emergence of beyond 5G networks has the potential for seamless and intelligent connectivity on a global scale.Network slicing is crucial in delivering services for different,demanding vertical applications in this context.Next-generation applications have time-sensitive requirements and depend on the most efficient routing path to ensure packets reach their intended destinations.However,the existing IP(Internet Protocol)over a multi-domain network faces challenges in enforcing network slicing due to minimal collaboration and information sharing among network operators.Conventional inter-domain routing methods,like Border Gateway Protocol(BGP),cannot make routing decisions based on performance,which frequently results in traffic flowing across congested paths that are never optimal.To address these issues,we propose CoopAI-Route,a multi-agent cooperative deep reinforcement learning(DRL)system utilizing hierarchical software-defined networks(SDN).This framework enforces network slicing in multi-domain networks and cooperative communication with various administrators to find performance-based routes in intra-and inter-domain.CoopAI-Route employs the Distributed Global Topology(DGT)algorithm to define inter-domain Quality of Service(QoS)paths.CoopAI-Route uses a DRL agent with a message-passing multi-agent Twin-Delayed Deep Deterministic Policy Gradient method to ensure optimal end-to-end routes adapted to the specific requirements of network slicing applications.Our evaluation demonstrates CoopAI-Route’s commendable performance in scalability,link failure handling,and adaptability to evolving topologies compared to state-of-the-art methods.
基金funded by the National Natural Science Foundation of China (No.22176123)the Natural Science Foundation of Xinjiang (No.2021D01C036)the National Undergraduate Innovation and Entre-preneurship of China (No.2021110755038)。
文摘VOCs can exert great harm to both human and environment,and catalytic oxidation is believed to be an effective technique to eliminate these pollutants.In this paper,Ag-Mn bimetal catalysts with 10 wt.%of silver were synthesized using doping,impregnation,and reduction methods respectively,and then they were applied to the catalytic oxidation of benzene.Through series of characterizations it showed that the loading of silver using reduction method significantly resulted in improved physico-chemical properties of manganese oxides,such as larger surface area and pore volume,higher proportion of surface Mn~(3+)and Mn~(4+),stronger reducibility and more active of surface oxygen species,which were all beneficial to its catalytic activity.As a result,the Ag-Mn catalysts synthesized by reduction method showed a lower T_(90)value(equals to the temperature at which 90%of initial benzene was removed)of 203℃.Besides,both the used and fresh Ag-Mn catalysts synthesized by reduction method showed preferable stability in this research.
