Flight behavior analysis provides the fundamental basis for the future development of air traffic management(ATM).The characteristics of aircraft behavior are inherently reflected in their flight trajectories,impactin...Flight behavior analysis provides the fundamental basis for the future development of air traffic management(ATM).The characteristics of aircraft behavior are inherently reflected in their flight trajectories,impacting flight efficiency and safety levels.However,existing research largely addresses inefficient or abnormal trajectories from a single perspective,with an absence of a unified evaluation standard.This paper introduces a method for analyzing flight deviation behavior based on automatic dependent surveillance-broadcast(ADS-B)data,defining novel metrics of trajectory redundancy and trajectory deviation.An adaptive detection algorithm is developed to capture diverse deviation patterns.Results reveal that higher trajectory redundancy is linked to lower operational efficiency,while trajectory deviation effectively identify stepped descents,holding patterns,detours,and other behaviors.The approach offers data-driven support for anomaly detection,performance evaluation and air traffic management,with substantial significance for civil aviation applications.展开更多
The coupling effects among the flow field,temperature distribution and structural deformation in a turbine cannot be ignored,particularly during flight cycles when the turbine experiences varied operational states.Rel...The coupling effects among the flow field,temperature distribution and structural deformation in a turbine cannot be ignored,particularly during flight cycles when the turbine experiences varied operational states.Relying solely on steady-state solutions cannot predict the detrimental effects caused by hysteresis.Consequently,this paper employs a quasi-steady-state fluid-thermalstructure multidisciplinary coupling solution method,integrating transient solid heat conduction with steady-state flow field and static structural deformation solutions.After conducting a numerical simulation of a three-dimensional,five-stage,low-pressure turbine air system,the following conclusions are drawn:when boundary conditions attain high-power states through processes that are numerically identical but in opposite directions,slight variations in solid deformation significantly impact the flow field;when boundary conditions attain high-power states through processes that are directionally consistent but have different numerical values,the influence of the boundary condition change rate on the flow field surpasses that of solid deformation.In terms of turbine design parameters,a large difference in stage-reaction between adjacent stages at the lower radius of the turbine can lead to significant changes in the disc cavity flow field during flight cycles.The difference in the stage-reaction of 0.23 at 10%blade height in adjacent stages may induce severe gas ingress in the stator disc cavity.Thus,it is crucial to minimize this difference and to appropriately extend the duration of the deceleration phase to ensure the turbine's safe operation.展开更多
With the expanding applications of unmanned aerial vehicles(UAVs),precise flight evaluation has emerged as a critical enabler for efficient path planning,directly impacting operational performance and safety.Tradition...With the expanding applications of unmanned aerial vehicles(UAVs),precise flight evaluation has emerged as a critical enabler for efficient path planning,directly impacting operational performance and safety.Traditional path planning algorithms typically combine Dubins curves with local optimization to minimize trajectory length under 3D spatial constraints.However,these methods often overlook the correlation between pilot control quality and UAV flight dynamics,limiting their adaptability in complex scenarios.In this paper,we propose an intelligent flight evaluation model specifically designed to enhancemulti-waypoint trajectory optimization algorithms.Our model leverages a decision tree to integrate attitude parameters and trajectory matching metrics,establishing a quantitative link between pilot control quality and UAV flight states.Experimental results demonstrate that the proposed model not only accurately assesses pilot performance across diverse skill levels but also improves the optimality of generated trajectories.When integrated with our path planning algorithm,it efficiently produces optimal trajectories while strictly adhering to UAV flight constraints.This integrated framework highlights significant potential for real-time UAV training,performance assessment,and adaptive mission planning applications.展开更多
Purpose:The purpose of this study was to examine the associations between adherence to the 24-Hour Movement Guidelines and all-cause and cause-specific mortality in a large Spanish prospective cohort.Methods:We analyz...Purpose:The purpose of this study was to examine the associations between adherence to the 24-Hour Movement Guidelines and all-cause and cause-specific mortality in a large Spanish prospective cohort.Methods:We analyzed data from 14,288 participants of the Seguimiento Universidad de Navarra(SUN)Project,followed for a mean of 12.8 years(mean baseline age=38.3 years;60.1%women).Data were collected at baseline and through biennial follow-up questionnaires(up to 10 waves,depending on year of entry).The participants self-reported 24-h movement behaviors at baseline and were categorized based on the number of guidelines met(0-3).Behaviors were assessed at baseline only;changes in adherence during follow-up were not accounted for.Cox proportional hazards models were used to estimate hazard ratios(HRs)for all-cause and cause-specific mortality,adjusting for sociodemographic,lifestyle,and clinical covariates.Results:Meeting a greater number of 24-Hour Movement Guidelines at baseline was associated with a progressively lower risk of all-cause mortality.Compared with those meeting none,the multivariable-adjusted HRs were 0.52(95%confidence interval(95%CI):0.33-0.82)for meeting 1 guideline,0.47(95%CI:0.30-0.73)for meeting 2 guidelines,and 0.44(95%CI:0.28-0.71)for meeting all 3 guidelines.Only adherence to the physical activity guidelines was independently associated with a significantly lower mortality risk(HR=0.70;95%CI:0.55-0.89).A reduced risk was also observed for cancer and other-cause mortality among those meeting 2 or more guidelines.Conclusion:Adherence to the 24-Hour Movement Guidelines at baseline,particularly physical activity,was associated with a lower risk of mortality.Promoting an integrated approach to movement behaviors may be an effective strategy for improving population health and longevity.展开更多
Objectives:24-h movement behaviors(24-HMB),encompassing physical activity,sedentary behavior,and sleep duration,are increasingly regarded as interrelated and important factors for mental health.However,evidence on the...Objectives:24-h movement behaviors(24-HMB),encompassing physical activity,sedentary behavior,and sleep duration,are increasingly regarded as interrelated and important factors for mental health.However,evidence on the comprehensive association of these behaviors with mental health in adults with diabetes in developing countries remains scarce.This study examined the association between 24-HMB guidelines and psychological health among adults with diabetes in developing countries.Methods:Data were retrieved from the World Health Organization’s study on Global Aging and Adult Health Survey dataset.Adults(N=1905)diagnosed with diabetes from five low-and middle-income countries were included.The exposure of interest was adherence to 24-HMB guidelines,depression,cognition,and quality of life(QoL).Multiple logistic and multiple linear regression analyses were used to examine the association between meeting 24-HMB guidelines and depression,cognition,and QoL,respectively.Results:This cross-sectional study revealed that 28.61%complied with all three 24-HMB guidelines.Diabetic patients who met more numbers of 24-HMB guidelines had lower depression risk(OR=0.74,95%CI:0.61 to 0.91,p=0.004),greater cognition(β=0.42,95%CI:0.25 to 0.60,p<0.001),and QoL(β=1.30,95%CI:1.04 to 1.55,p<0.001)with the non-compliant population.For specific combinations,meeting all three guidelines were significantly associated with lower odds of depression,improved cognitive function,and enhanced QoL(all p<0.001).Conclusion:These findings support that meeting 24-HMB guidelines in a single or combined movement behaviors was significantly related to reduced risk of depression,enhanced cognitive function,and improved QoL among individuals with diabetes.展开更多
Background:Health benefits have been reported for many physical activity(PA)interventions for improving fundamental movement skills(FMS)and cognitive function(CF),but the most effective type of PA interventions for em...Background:Health benefits have been reported for many physical activity(PA)interventions for improving fundamental movement skills(FMS)and cognitive function(CF),but the most effective type of PA interventions for emhancing FMS and CF in early childhood remain unknown.Thus,the study aimed to determine the effects of PA interventions in enhancing FMS and CF among young children and to establish the optimal types of PA interventions.Methods:Six electronic databases(PubMed,OVID,SPORTDiscus,Scopus,Web of Science,and Cochrane)were searched for studies from inception to March 17,2024.Randomized controlled trials(RCTs)were included in this study if they reported outcomes related to FMS,CF,or both associated with PA interventions.Effect sizes were calculated and performed as Hedges'g.The hierarchy of competing interventions was established using the surface under the cumulative ranking curve(SUCRA).Risk of bias was independently assessed using the Cochrane Riskof-Bias 2.Results:This analysis included 38 studies with 5237 young children,with sample sizes ranging from 32 to 897 participants.The types of PA interventions analyzed included active play/free play/unstructured PA(AP),general structured PA(GSPA),FMS-targeted PA programs(FMSprograms),cognitively-engaging PA programs(CPA),multilevel PA interventions(MPA),and exergaming.PA interventions had a large,pooled effect size for total FMS(g=0.96;95%CI:0.45-1.46;p<0.01;I^(2)=94%).For CF,a small-to-moderate pooled effect size was found(g=0.39;95%CI:0.18-0.60;p<0.01;I^(2)=88%).PA interventions longer than 3 months showed fewer benefits for FMS(p<0.01).The network meta-analysis showed that FMS-programs(standardized mean difference((SMD)=1.55,95%CI:0.98-2.11,SUCRA=98.3%)and GSPA(SMD=0.94,95%CI:0.05-1.85,SUCRA=69.8%)significantly improved total FMS compared to AP.For locomotor skills(LMS),exergaming ranked highest(SUCRA=79.3%),followed by FMS-programs(75.9%)and GSPA(61.6%).However,despite its top ranking,exergaming's effect estimate was not statistically significant(SMD=1.38,95%CI:-0.08 to 2.85).For object control skills(OCS),exergaming again ranked highest(SUCRA=91.9%)and showed the largest significant effect(SMD=2.38,95%CI:0.96-3.80),followed by FMS-programs(SUCRA=78.5%)and GSPA(SUCRA=53.7%).FMS-programs,GSPA,MPA,and UC also significantly improved OCS compared to AP.While no significant differences were observed across PA interventions for most CF domains,exergaming had a significant positive effect on working memory(SMD=1.41,95%CI:0.07-2.75).The certainty of evidence varied from low to moderate.Conclusion:These findings emphasize the importance of PA interventions in improving FMS and CF in early childhood.FMS-programs and GSPA appear to be the most effective approaches for enhancing total FMS,while exergaming showed the highest ranking for LMS and OCS,with a significant impact on OCS but uncertainty in LMS improvements.Additionally,exergaming had a positive effect on working memory,suggesting its potential cognitive benefits.展开更多
Lateral movement represents the most covert and critical phase of Advanced Persistent Threats(APTs),and its detection still faces two primary challenges:sample scarcity and“cold start”of new entities.To address thes...Lateral movement represents the most covert and critical phase of Advanced Persistent Threats(APTs),and its detection still faces two primary challenges:sample scarcity and“cold start”of new entities.To address these challenges,we propose an Uncertainty-Driven Graph Embedding-Enhanced Lateral Movement Detection framework(UGEA-LMD).First,the framework employs event-level incremental encoding on a continuous-time graph to capture fine-grained behavioral evolution,enabling newly appearing nodes to retain temporal contextual awareness even in the absence of historical interactions and thereby fundamentally mitigating the cold-start problem.Second,in the embedding space,we model the dependency structure among feature dimensions using a Gaussian copula to quantify the uncertainty distribution,and generate augmented samples with consistent structural and semantic properties through adaptive sampling,thus expanding the representation space of sparse samples and enhancing the model’s generalization under sparse sample conditions.Unlike static graph methods that cannot model temporal dependencies or data augmentation techniques that depend on predefined structures,UGEA-LMD offers both superior temporaldynamic modeling and structural generalization.Experimental results on the large-scale LANL log dataset demonstrate that,under the transductive setting,UGEA-LMD achieves an AUC of 0.9254;even when 10%of nodes or edges are withheld during training,UGEA-LMD significantly outperforms baseline methods on metrics such as recall and AUC,confirming its robustness and generalization capability in sparse-sample and cold-start scenarios.展开更多
Efficient multiple unmanned aerial vehicles(UAVs)path planning is crucial for improving mission completion efficiency in UAV operations.However,during the actual flight of UAVs,the flight time between nodes is always ...Efficient multiple unmanned aerial vehicles(UAVs)path planning is crucial for improving mission completion efficiency in UAV operations.However,during the actual flight of UAVs,the flight time between nodes is always influenced by external factors,making the original path planning solution ineffective.In this paper,the multi-depot multi-UAV path planning problem with uncertain flight time is modeled as a robust optimization model with a budget uncertainty set.Then,the robust optimization model is transformed into a mixed integer linear programming model by the strong duality theorem,which makes the problem easy to solve.To effectively solve large-scale instances,a simulated annealing algorithm with a robust feasibility check(SA-RFC)is developed.The numerical experiment shows that the SA-RFC can find high-quality solutions within a few seconds.Moreover,the effect of the task location distribution,depot counts,and variations in robustness parameters on the robust optimization solution is analyzed by using Monte Carlo experiments.The results demonstrate that the proposed robust model can effectively reduce the risk of the UAV failing to return to the depot without significantly compromising the profit.展开更多
To examine the effect of sleep deprivation （SD） on eye movement be- havior in flight task, four subjects who were skilled in flight simulator participated in the experiment, which were asked to perform a level fligh...To examine the effect of sleep deprivation （SD） on eye movement be- havior in flight task, four subjects who were skilled in flight simulator participated in the experiment, which were asked to perform a level flight task in a flight simulator. Eye movement data and flight performance data were measured at the following hours： 11：00, 15：00, 04：00, 11：00, 15：00. The subjects workload and fatigue were assessed with the method of national aeronautics and space administration-task load index （NASA-TLX） and rating of perceived exertion （RPE）. Eye movement indices of average pupil area, av- erage saceade amplitude and average saccade velocity decreased during the 32 h of SD and they all showed significantly change in the final SD while the index of average fixa- tion time increased in the final SD. Flight performance deteriorated during the 32 h of SD, but not significantly. The feeling of fatigue and workload reported by subjects both increased during the 32 h of SD. Daily rhythm effects on the measured indices were also found, there were a obviously change at the hour of 04：00. 32 h of SD has obvious effect on eye movement behaviors which have close relation to fatigue because of SD. The eye movement measurement can be served as a tool to continually monitor fatigue online.展开更多
Unmanned aerial vehicle light detection and ranging(UAV–LiDAR)is a new method for collecting understory terrain data.The high estimation accuracy of understory terrain is crucial for accurate tree height measurement ...Unmanned aerial vehicle light detection and ranging(UAV–LiDAR)is a new method for collecting understory terrain data.The high estimation accuracy of understory terrain is crucial for accurate tree height measurement and forest resource surveys.The UAV–LiDAR flight altitude and forest canopy cover significantly impact the accuracy of understory terrain estimation.However,since no research examined their combined effects,we aimed to investigate this relationship.This will help optimize UAV–LiDAR flight parameters for understory terrain estimation and forest surveys across various canopy cover.This study analyzed the impacts of three flight altitudes and three canopy cover on the estimation accuracy of understory terrain.The results showed that when canopy cover exceeded a specific value,UAV–LiDAR flight altitudes significantly affected understory terrain estimation.Given a forest canopy cover,the reduction in ground point coverage increased significantly as the flight altitude increased;given a flight altitude,the higher the canopy cover,the more significant the reduction in ground point coverage.In forests with a canopy cover≥0.9,there were substantial differences in the accuracies of understory digital elevation models(DEMs)generated using UAV–LiDAR at different flight altitudes.For forests with a canopy cover<0.9,the mean absolute error(MAE)of understory DEMs from UAV–LiDAR at different flight altitudes was≤0.17 m and the root mean square error(RMSE)was≤0.24 m.However,for forests with a canopy cover≥0.9,the UAV–LiDAR flight altitude significantly affected the accuracy of understory DEMs.At the same flight altitude,the MAE and RMSE of the estimated elevation for forests with a canopy cover≥0.9 were approximately twice those of the estimated elevation for forests with a canopy cover<0.9.In forests with low canopy cover,it is possible to improve data collection efficiency by selecting a higher flight altitude.However,UAV–LiDAR flight altitudes significantly affected understory terrain estimation in forests with high canopy cover,it is essential to adopt terrain-following flight modes,reduce flight altitudes,and maintain a consistent flight altitude during longterm monitoring in high canopy cover forests.展开更多
Generating dynamically feasible trajectory for fixed-wing Unmanned Aerial Vehicles(UAVs)in dense obstacle environments remains computationally intractable.This paper proposes a Safe Flight Corridor constrained Sequent...Generating dynamically feasible trajectory for fixed-wing Unmanned Aerial Vehicles(UAVs)in dense obstacle environments remains computationally intractable.This paper proposes a Safe Flight Corridor constrained Sequential Convex Programming(SFC-SCP)to improve the computation efficiency and reliability of trajectory generation.SFC-SCP combines the front-end convex polyhedron SFC construction and back-end SCP-based trajectory optimization.A Sparse A^(*)Search(SAS)driven SFC construction method is designed to efficiently generate polyhedron SFC according to the geometric relation among obstacles and collision-free waypoints.Via transforming the nonconvex obstacle-avoidance constraints to linear inequality constraints,SFC can mitigate infeasibility of trajectory planning and reduce computation complexity.Then,SCP casts the nonlinear trajectory optimization subject to SFC into convex programming subproblems to decrease the problem complexity.In addition,a convex optimizer based on interior point method is customized,where the search direction is calculated via successive elimination to further improve efficiency.Simulation experiments on dense obstacle scenarios show that SFC-SCP can generate dynamically feasible safe trajectory rapidly.Comparative studies with state-of-the-art SCP-based methods demonstrate the efficiency and reliability merits of SFC-SCP.Besides,the customized convex optimizer outperforms off-the-shelf optimizers in terms of computation time.展开更多
Dear Editor,Space flight(SF)is substantially increasing at present.The emergence of commercial suborbital SF,such as the Virgin Galactic with VSS Unity and VMS Eve spacecraft,is extending to civilians,being previously...Dear Editor,Space flight(SF)is substantially increasing at present.The emergence of commercial suborbital SF,such as the Virgin Galactic with VSS Unity and VMS Eve spacecraft,is extending to civilians,being previously confined to military and/or professional astronauts only.This new evidence offers additional opportunities for better characterizing the impact that the transition from Earth’s 1G to microgravity in space could have on the astronauts’health while comparing well-trained subjects such as the latt er to space newcomers[1].展开更多
With the advent of the next-generation Air Traffic Control(ATC)system,there is growing interest in using Artificial Intelligence(AI)techniques to enhance Situation Awareness(SA)for ATC Controllers(ATCOs),i.e.,Intellig...With the advent of the next-generation Air Traffic Control(ATC)system,there is growing interest in using Artificial Intelligence(AI)techniques to enhance Situation Awareness(SA)for ATC Controllers(ATCOs),i.e.,Intelligent SA(ISA).However,the existing AI-based SA approaches often rely on unimodal data and lack a comprehensive description and benchmark of the ISA tasks utilizing multi-modal data for real-time ATC environments.To address this gap,by analyzing the situation awareness procedure of the ATCOs,the ISA task is refined to the processing of the two primary elements,i.e.,spoken instructions and flight trajectories.Subsequently,the ISA is further formulated into Controlling Intent Understanding(CIU)and Flight Trajectory Prediction(FTP)tasks.For the CIU task,an innovative automatic speech recognition and understanding framework is designed to extract the controlling intent from unstructured and continuous ATC communications.For the FTP task,the single-and multi-horizon FTP approaches are investigated to support the high-precision prediction of the situation evolution.A total of 32 unimodal/multi-modal advanced methods with extensive evaluation metrics are introduced to conduct the benchmarks on the real-world multi-modal ATC situation dataset.Experimental results demonstrate the effectiveness of AI-based techniques in enhancing ISA for the ATC environment.展开更多
Corticotomy is a clinical procedure to accelerate orthodontic tooth movement characterized by the regional acceleratory phenomenon(RAP).Despite its therapeutic effects,the surgical risk and unclear mechanism hamper th...Corticotomy is a clinical procedure to accelerate orthodontic tooth movement characterized by the regional acceleratory phenomenon(RAP).Despite its therapeutic effects,the surgical risk and unclear mechanism hamper the clinical application.Numerous evidences support macrophages as the key immune cells during bone remodeling.Our study discovered that the monocyte-derived macrophages primarily exhibited a pro-inflammatory phenotype that dominated bone remodeling in corticotomy by CX3CR1CreERT2;R26GFP lineage tracing system.Fluorescence staining,flow cytometry analysis,and western blot determined the significantly enhanced expression of binding immunoglobulin protein(BiP)and emphasized the activation of sensor activating transcription factor 6(ATF6)in macrophages.Then,we verified that macrophage specific ATF6 deletion(ATF6f/f;CX3CR1CreERT2 mice)decreased the proportion of pro-inflammatory macrophages and therefore blocked the acceleration effect of corticotomy.In contrast,macrophage ATF6 overexpression exaggerated the acceleration of orthodontic tooth movement.In vitro experiments also proved that higher proportion of pro-inflammatory macrophages was positively correlated with higher expression of ATF6.At the mechanism level,RNA-seq and CUT&Tag analysis demonstrated that ATF6 modulated the macrophage-orchestrated inflammation through interacting with Tnfαpromotor and augmenting its transcription.Additionally,molecular docking simulation and dual-luciferase reporter system indicated the possible binding sites outside of the traditional endoplasmic reticulum-stress response element(ERSE).Taken together,ATF6 may aggravate orthodontic bone remodeling by promoting Tnfαtranscription in macrophages,suggesting that ATF6 may represent a promising therapeutic target for non-invasive accelerated orthodontics.展开更多
Accurate measurement of helicopter rotor motion parameters(flap,lead-lag,torsion,and azimuth angles)is essential for rotor blade design,helicopter dynamics modeling,and flight safety and health monitoring.However,the ...Accurate measurement of helicopter rotor motion parameters(flap,lead-lag,torsion,and azimuth angles)is essential for rotor blade design,helicopter dynamics modeling,and flight safety and health monitoring.However,the existing methods face challenges in testing equipment installation,calibration,and data transmission,resulting in limited reports on real-time in-flight measurements of blade motion parameters.This paper proposes a non-contact optoelectronic method based on two-dimensional position-sensitive detectors for in-flight measurement and a ground calibration system to obtain real-time rotor motion parameters during helicopter flight.The proposed method establishes the time evolution relationship of rotor motion parameters and verifies the performance of the in-flight measurement system regarding measurement resolution and accuracy through the construction of a blade motion posture experimental platform.The proposed method has been applied to the flight measurement of a medium-sized single-rotor helicopter,and the obtained results have been compared with theoretical analysis outcomes.Furthermore,this paper examines the characteristics of blade motion parameters during flight and discusses the challenges and potential solutions for measuring rotor motion parameters during helicopter flight using the proposed method.展开更多
A novel block–particle discrete-element simulation method that matches the double medium of overlying rock(OLR)and loose layer(LSL)in coal mining is developed in this study.This method achieves the collaborative fail...A novel block–particle discrete-element simulation method that matches the double medium of overlying rock(OLR)and loose layer(LSL)in coal mining is developed in this study.This method achieves the collaborative failure characteristics of mining damage under the conduction of double media between the OLR and LSL by combining the self-weight stress loading of the LSL and the breakage morphology of the bedrock top.Based on this,the conduction law of high-strength mining damage in the double medium in a western mining area is simulated and analyzed.The combining effect of the OLR breakage morphology and LSL characteristics on the surface-subsidence characteristics is analyzed and verified based on on-site measurements.The results indicate that the OLR is guided by the“double-control layer and thick-soft rock buffer layer”and shows“grouping subsidence”,whereas the surface forms collaborative subsidence with the thick-soft rock buffer layer.In the ultra-full mining stage,the surface presents an“asymmetric inverted trapezoidal”subsidence trough shape.The simulation results agree well the on-site measurements in terms of the surface-subsidence and bedrock-subsidence coefficients.The proposed simulation method provides a scientific approach for investigating the micro-conduction mechanism of mining damage under the effect of high-strength mining in western mining areas.It will benefit future investigations pertaining to the characteristics of OLR breakage and surface subsidence under conditions such as LSL thickness and proportion.展开更多
基金supported in part by the National Key Research and Development Program of China(No.2023YFB4302903)the Fundamental Research Funds for the Central Universities(No.210525001464)。
文摘Flight behavior analysis provides the fundamental basis for the future development of air traffic management(ATM).The characteristics of aircraft behavior are inherently reflected in their flight trajectories,impacting flight efficiency and safety levels.However,existing research largely addresses inefficient or abnormal trajectories from a single perspective,with an absence of a unified evaluation standard.This paper introduces a method for analyzing flight deviation behavior based on automatic dependent surveillance-broadcast(ADS-B)data,defining novel metrics of trajectory redundancy and trajectory deviation.An adaptive detection algorithm is developed to capture diverse deviation patterns.Results reveal that higher trajectory redundancy is linked to lower operational efficiency,while trajectory deviation effectively identify stepped descents,holding patterns,detours,and other behaviors.The approach offers data-driven support for anomaly detection,performance evaluation and air traffic management,with substantial significance for civil aviation applications.
基金supported by the National Science and Tech-nology Major Project,China(No.J2019-II-0012-0032)。
文摘The coupling effects among the flow field,temperature distribution and structural deformation in a turbine cannot be ignored,particularly during flight cycles when the turbine experiences varied operational states.Relying solely on steady-state solutions cannot predict the detrimental effects caused by hysteresis.Consequently,this paper employs a quasi-steady-state fluid-thermalstructure multidisciplinary coupling solution method,integrating transient solid heat conduction with steady-state flow field and static structural deformation solutions.After conducting a numerical simulation of a three-dimensional,five-stage,low-pressure turbine air system,the following conclusions are drawn:when boundary conditions attain high-power states through processes that are numerically identical but in opposite directions,slight variations in solid deformation significantly impact the flow field;when boundary conditions attain high-power states through processes that are directionally consistent but have different numerical values,the influence of the boundary condition change rate on the flow field surpasses that of solid deformation.In terms of turbine design parameters,a large difference in stage-reaction between adjacent stages at the lower radius of the turbine can lead to significant changes in the disc cavity flow field during flight cycles.The difference in the stage-reaction of 0.23 at 10%blade height in adjacent stages may induce severe gas ingress in the stator disc cavity.Thus,it is crucial to minimize this difference and to appropriately extend the duration of the deceleration phase to ensure the turbine's safe operation.
基金funded in part by the Fundamental Research Funds for the Central Universities under Grant NS2023052in part by the Natural Science Foundation of Jiangsu Province of China under Grants No.BK20231439 and No.BK20222012.
文摘With the expanding applications of unmanned aerial vehicles(UAVs),precise flight evaluation has emerged as a critical enabler for efficient path planning,directly impacting operational performance and safety.Traditional path planning algorithms typically combine Dubins curves with local optimization to minimize trajectory length under 3D spatial constraints.However,these methods often overlook the correlation between pilot control quality and UAV flight dynamics,limiting their adaptability in complex scenarios.In this paper,we propose an intelligent flight evaluation model specifically designed to enhancemulti-waypoint trajectory optimization algorithms.Our model leverages a decision tree to integrate attitude parameters and trajectory matching metrics,establishing a quantitative link between pilot control quality and UAV flight states.Experimental results demonstrate that the proposed model not only accurately assesses pilot performance across diverse skill levels but also improves the optimality of generated trajectories.When integrated with our path planning algorithm,it efficiently produces optimal trajectories while strictly adhering to UAV flight constraints.This integrated framework highlights significant potential for real-time UAV training,performance assessment,and adaptive mission planning applications.
文摘Purpose:The purpose of this study was to examine the associations between adherence to the 24-Hour Movement Guidelines and all-cause and cause-specific mortality in a large Spanish prospective cohort.Methods:We analyzed data from 14,288 participants of the Seguimiento Universidad de Navarra(SUN)Project,followed for a mean of 12.8 years(mean baseline age=38.3 years;60.1%women).Data were collected at baseline and through biennial follow-up questionnaires(up to 10 waves,depending on year of entry).The participants self-reported 24-h movement behaviors at baseline and were categorized based on the number of guidelines met(0-3).Behaviors were assessed at baseline only;changes in adherence during follow-up were not accounted for.Cox proportional hazards models were used to estimate hazard ratios(HRs)for all-cause and cause-specific mortality,adjusting for sociodemographic,lifestyle,and clinical covariates.Results:Meeting a greater number of 24-Hour Movement Guidelines at baseline was associated with a progressively lower risk of all-cause mortality.Compared with those meeting none,the multivariable-adjusted HRs were 0.52(95%confidence interval(95%CI):0.33-0.82)for meeting 1 guideline,0.47(95%CI:0.30-0.73)for meeting 2 guidelines,and 0.44(95%CI:0.28-0.71)for meeting all 3 guidelines.Only adherence to the physical activity guidelines was independently associated with a significantly lower mortality risk(HR=0.70;95%CI:0.55-0.89).A reduced risk was also observed for cancer and other-cause mortality among those meeting 2 or more guidelines.Conclusion:Adherence to the 24-Hour Movement Guidelines at baseline,particularly physical activity,was associated with a lower risk of mortality.Promoting an integrated approach to movement behaviors may be an effective strategy for improving population health and longevity.
文摘Objectives:24-h movement behaviors(24-HMB),encompassing physical activity,sedentary behavior,and sleep duration,are increasingly regarded as interrelated and important factors for mental health.However,evidence on the comprehensive association of these behaviors with mental health in adults with diabetes in developing countries remains scarce.This study examined the association between 24-HMB guidelines and psychological health among adults with diabetes in developing countries.Methods:Data were retrieved from the World Health Organization’s study on Global Aging and Adult Health Survey dataset.Adults(N=1905)diagnosed with diabetes from five low-and middle-income countries were included.The exposure of interest was adherence to 24-HMB guidelines,depression,cognition,and quality of life(QoL).Multiple logistic and multiple linear regression analyses were used to examine the association between meeting 24-HMB guidelines and depression,cognition,and QoL,respectively.Results:This cross-sectional study revealed that 28.61%complied with all three 24-HMB guidelines.Diabetic patients who met more numbers of 24-HMB guidelines had lower depression risk(OR=0.74,95%CI:0.61 to 0.91,p=0.004),greater cognition(β=0.42,95%CI:0.25 to 0.60,p<0.001),and QoL(β=1.30,95%CI:1.04 to 1.55,p<0.001)with the non-compliant population.For specific combinations,meeting all three guidelines were significantly associated with lower odds of depression,improved cognitive function,and enhanced QoL(all p<0.001).Conclusion:These findings support that meeting 24-HMB guidelines in a single or combined movement behaviors was significantly related to reduced risk of depression,enhanced cognitive function,and improved QoL among individuals with diabetes.
文摘Background:Health benefits have been reported for many physical activity(PA)interventions for improving fundamental movement skills(FMS)and cognitive function(CF),but the most effective type of PA interventions for emhancing FMS and CF in early childhood remain unknown.Thus,the study aimed to determine the effects of PA interventions in enhancing FMS and CF among young children and to establish the optimal types of PA interventions.Methods:Six electronic databases(PubMed,OVID,SPORTDiscus,Scopus,Web of Science,and Cochrane)were searched for studies from inception to March 17,2024.Randomized controlled trials(RCTs)were included in this study if they reported outcomes related to FMS,CF,or both associated with PA interventions.Effect sizes were calculated and performed as Hedges'g.The hierarchy of competing interventions was established using the surface under the cumulative ranking curve(SUCRA).Risk of bias was independently assessed using the Cochrane Riskof-Bias 2.Results:This analysis included 38 studies with 5237 young children,with sample sizes ranging from 32 to 897 participants.The types of PA interventions analyzed included active play/free play/unstructured PA(AP),general structured PA(GSPA),FMS-targeted PA programs(FMSprograms),cognitively-engaging PA programs(CPA),multilevel PA interventions(MPA),and exergaming.PA interventions had a large,pooled effect size for total FMS(g=0.96;95%CI:0.45-1.46;p<0.01;I^(2)=94%).For CF,a small-to-moderate pooled effect size was found(g=0.39;95%CI:0.18-0.60;p<0.01;I^(2)=88%).PA interventions longer than 3 months showed fewer benefits for FMS(p<0.01).The network meta-analysis showed that FMS-programs(standardized mean difference((SMD)=1.55,95%CI:0.98-2.11,SUCRA=98.3%)and GSPA(SMD=0.94,95%CI:0.05-1.85,SUCRA=69.8%)significantly improved total FMS compared to AP.For locomotor skills(LMS),exergaming ranked highest(SUCRA=79.3%),followed by FMS-programs(75.9%)and GSPA(61.6%).However,despite its top ranking,exergaming's effect estimate was not statistically significant(SMD=1.38,95%CI:-0.08 to 2.85).For object control skills(OCS),exergaming again ranked highest(SUCRA=91.9%)and showed the largest significant effect(SMD=2.38,95%CI:0.96-3.80),followed by FMS-programs(SUCRA=78.5%)and GSPA(SUCRA=53.7%).FMS-programs,GSPA,MPA,and UC also significantly improved OCS compared to AP.While no significant differences were observed across PA interventions for most CF domains,exergaming had a significant positive effect on working memory(SMD=1.41,95%CI:0.07-2.75).The certainty of evidence varied from low to moderate.Conclusion:These findings emphasize the importance of PA interventions in improving FMS and CF in early childhood.FMS-programs and GSPA appear to be the most effective approaches for enhancing total FMS,while exergaming showed the highest ranking for LMS and OCS,with a significant impact on OCS but uncertainty in LMS improvements.Additionally,exergaming had a positive effect on working memory,suggesting its potential cognitive benefits.
基金supported by the Zhongyuan University of Technology Discipline Backbone Teacher Support Program Project(No.GG202417)the Key Research and Development Program of Henan under Grant 251111212000.
文摘Lateral movement represents the most covert and critical phase of Advanced Persistent Threats(APTs),and its detection still faces two primary challenges:sample scarcity and“cold start”of new entities.To address these challenges,we propose an Uncertainty-Driven Graph Embedding-Enhanced Lateral Movement Detection framework(UGEA-LMD).First,the framework employs event-level incremental encoding on a continuous-time graph to capture fine-grained behavioral evolution,enabling newly appearing nodes to retain temporal contextual awareness even in the absence of historical interactions and thereby fundamentally mitigating the cold-start problem.Second,in the embedding space,we model the dependency structure among feature dimensions using a Gaussian copula to quantify the uncertainty distribution,and generate augmented samples with consistent structural and semantic properties through adaptive sampling,thus expanding the representation space of sparse samples and enhancing the model’s generalization under sparse sample conditions.Unlike static graph methods that cannot model temporal dependencies or data augmentation techniques that depend on predefined structures,UGEA-LMD offers both superior temporaldynamic modeling and structural generalization.Experimental results on the large-scale LANL log dataset demonstrate that,under the transductive setting,UGEA-LMD achieves an AUC of 0.9254;even when 10%of nodes or edges are withheld during training,UGEA-LMD significantly outperforms baseline methods on metrics such as recall and AUC,confirming its robustness and generalization capability in sparse-sample and cold-start scenarios.
基金supported by the National Natural Science Foundation of China(72571094,72271076,71871079)。
文摘Efficient multiple unmanned aerial vehicles(UAVs)path planning is crucial for improving mission completion efficiency in UAV operations.However,during the actual flight of UAVs,the flight time between nodes is always influenced by external factors,making the original path planning solution ineffective.In this paper,the multi-depot multi-UAV path planning problem with uncertain flight time is modeled as a robust optimization model with a budget uncertainty set.Then,the robust optimization model is transformed into a mixed integer linear programming model by the strong duality theorem,which makes the problem easy to solve.To effectively solve large-scale instances,a simulated annealing algorithm with a robust feasibility check(SA-RFC)is developed.The numerical experiment shows that the SA-RFC can find high-quality solutions within a few seconds.Moreover,the effect of the task location distribution,depot counts,and variations in robustness parameters on the robust optimization solution is analyzed by using Monte Carlo experiments.The results demonstrate that the proposed robust model can effectively reduce the risk of the UAV failing to return to the depot without significantly compromising the profit.
基金Aviation Science Foundation of Chinagrant number:20115551025
文摘To examine the effect of sleep deprivation （SD） on eye movement be- havior in flight task, four subjects who were skilled in flight simulator participated in the experiment, which were asked to perform a level flight task in a flight simulator. Eye movement data and flight performance data were measured at the following hours： 11：00, 15：00, 04：00, 11：00, 15：00. The subjects workload and fatigue were assessed with the method of national aeronautics and space administration-task load index （NASA-TLX） and rating of perceived exertion （RPE）. Eye movement indices of average pupil area, av- erage saceade amplitude and average saccade velocity decreased during the 32 h of SD and they all showed significantly change in the final SD while the index of average fixa- tion time increased in the final SD. Flight performance deteriorated during the 32 h of SD, but not significantly. The feeling of fatigue and workload reported by subjects both increased during the 32 h of SD. Daily rhythm effects on the measured indices were also found, there were a obviously change at the hour of 04：00. 32 h of SD has obvious effect on eye movement behaviors which have close relation to fatigue because of SD. The eye movement measurement can be served as a tool to continually monitor fatigue online.
基金supported by the National Natural Science Foundation of China(No.32271876)the Research on Key Technologies of Intelligent Monitoring and Carbon Sink Metering of Forest Resources in Fujian Province(No.2022FKJ03)the Science and Technology Innovation Project of Fujian Agriculture and Forestry University(No.KFB23172A,KFB23173A).
文摘Unmanned aerial vehicle light detection and ranging(UAV–LiDAR)is a new method for collecting understory terrain data.The high estimation accuracy of understory terrain is crucial for accurate tree height measurement and forest resource surveys.The UAV–LiDAR flight altitude and forest canopy cover significantly impact the accuracy of understory terrain estimation.However,since no research examined their combined effects,we aimed to investigate this relationship.This will help optimize UAV–LiDAR flight parameters for understory terrain estimation and forest surveys across various canopy cover.This study analyzed the impacts of three flight altitudes and three canopy cover on the estimation accuracy of understory terrain.The results showed that when canopy cover exceeded a specific value,UAV–LiDAR flight altitudes significantly affected understory terrain estimation.Given a forest canopy cover,the reduction in ground point coverage increased significantly as the flight altitude increased;given a flight altitude,the higher the canopy cover,the more significant the reduction in ground point coverage.In forests with a canopy cover≥0.9,there were substantial differences in the accuracies of understory digital elevation models(DEMs)generated using UAV–LiDAR at different flight altitudes.For forests with a canopy cover<0.9,the mean absolute error(MAE)of understory DEMs from UAV–LiDAR at different flight altitudes was≤0.17 m and the root mean square error(RMSE)was≤0.24 m.However,for forests with a canopy cover≥0.9,the UAV–LiDAR flight altitude significantly affected the accuracy of understory DEMs.At the same flight altitude,the MAE and RMSE of the estimated elevation for forests with a canopy cover≥0.9 were approximately twice those of the estimated elevation for forests with a canopy cover<0.9.In forests with low canopy cover,it is possible to improve data collection efficiency by selecting a higher flight altitude.However,UAV–LiDAR flight altitudes significantly affected understory terrain estimation in forests with high canopy cover,it is essential to adopt terrain-following flight modes,reduce flight altitudes,and maintain a consistent flight altitude during longterm monitoring in high canopy cover forests.
基金supported by the National Natural Science Foundation of China(No.62203256)。
文摘Generating dynamically feasible trajectory for fixed-wing Unmanned Aerial Vehicles(UAVs)in dense obstacle environments remains computationally intractable.This paper proposes a Safe Flight Corridor constrained Sequential Convex Programming(SFC-SCP)to improve the computation efficiency and reliability of trajectory generation.SFC-SCP combines the front-end convex polyhedron SFC construction and back-end SCP-based trajectory optimization.A Sparse A^(*)Search(SAS)driven SFC construction method is designed to efficiently generate polyhedron SFC according to the geometric relation among obstacles and collision-free waypoints.Via transforming the nonconvex obstacle-avoidance constraints to linear inequality constraints,SFC can mitigate infeasibility of trajectory planning and reduce computation complexity.Then,SCP casts the nonlinear trajectory optimization subject to SFC into convex programming subproblems to decrease the problem complexity.In addition,a convex optimizer based on interior point method is customized,where the search direction is calculated via successive elimination to further improve efficiency.Simulation experiments on dense obstacle scenarios show that SFC-SCP can generate dynamically feasible safe trajectory rapidly.Comparative studies with state-of-the-art SCP-based methods demonstrate the efficiency and reliability merits of SFC-SCP.Besides,the customized convex optimizer outperforms off-the-shelf optimizers in terms of computation time.
基金supported by the Hyperbaric Med School of the Department of Biomedical Sciences at the University of Padova,the Italian Air Force,and the Institute of Clinical Physiology(Milan)-National Research Council(IFC-CNR).
文摘Dear Editor,Space flight(SF)is substantially increasing at present.The emergence of commercial suborbital SF,such as the Virgin Galactic with VSS Unity and VMS Eve spacecraft,is extending to civilians,being previously confined to military and/or professional astronauts only.This new evidence offers additional opportunities for better characterizing the impact that the transition from Earth’s 1G to microgravity in space could have on the astronauts’health while comparing well-trained subjects such as the latt er to space newcomers[1].
基金supported by the National Natural Science Foundation of China(Nos.62371323,62401380,U2433217,U2333209,and U20A20161)Natural Science Foundation of Sichuan Province,China(Nos.2025ZNSFSC1476)+2 种基金Sichuan Science and Technology Program,China(Nos.2024YFG0010 and 2024ZDZX0046)the Institutional Research Fund from Sichuan University(Nos.2024SCUQJTX030)the Open Fund of Key Laboratory of Flight Techniques and Flight Safety,CAAC(Nos.GY2024-01A).
文摘With the advent of the next-generation Air Traffic Control(ATC)system,there is growing interest in using Artificial Intelligence(AI)techniques to enhance Situation Awareness(SA)for ATC Controllers(ATCOs),i.e.,Intelligent SA(ISA).However,the existing AI-based SA approaches often rely on unimodal data and lack a comprehensive description and benchmark of the ISA tasks utilizing multi-modal data for real-time ATC environments.To address this gap,by analyzing the situation awareness procedure of the ATCOs,the ISA task is refined to the processing of the two primary elements,i.e.,spoken instructions and flight trajectories.Subsequently,the ISA is further formulated into Controlling Intent Understanding(CIU)and Flight Trajectory Prediction(FTP)tasks.For the CIU task,an innovative automatic speech recognition and understanding framework is designed to extract the controlling intent from unstructured and continuous ATC communications.For the FTP task,the single-and multi-horizon FTP approaches are investigated to support the high-precision prediction of the situation evolution.A total of 32 unimodal/multi-modal advanced methods with extensive evaluation metrics are introduced to conduct the benchmarks on the real-world multi-modal ATC situation dataset.Experimental results demonstrate the effectiveness of AI-based techniques in enhancing ISA for the ATC environment.
基金supported by the National Natural Science Foundation of China(82071143,82371000,82270361)Key Research and Development Program of Jiangsu Province(BE2022795)+2 种基金the Postgraduate Research&Practice Innovation Program of Jiangsu Province(KYCX22_1801)the Jiangsu Province Capability Improvement Project through the Science,Technology and Education-Jiangsu Provincial Research Hospital Cultivation Unit(YJXYYJSDW4)Jiangsu Provincial Medical Innovation Center(CXZX202227).
文摘Corticotomy is a clinical procedure to accelerate orthodontic tooth movement characterized by the regional acceleratory phenomenon(RAP).Despite its therapeutic effects,the surgical risk and unclear mechanism hamper the clinical application.Numerous evidences support macrophages as the key immune cells during bone remodeling.Our study discovered that the monocyte-derived macrophages primarily exhibited a pro-inflammatory phenotype that dominated bone remodeling in corticotomy by CX3CR1CreERT2;R26GFP lineage tracing system.Fluorescence staining,flow cytometry analysis,and western blot determined the significantly enhanced expression of binding immunoglobulin protein(BiP)and emphasized the activation of sensor activating transcription factor 6(ATF6)in macrophages.Then,we verified that macrophage specific ATF6 deletion(ATF6f/f;CX3CR1CreERT2 mice)decreased the proportion of pro-inflammatory macrophages and therefore blocked the acceleration effect of corticotomy.In contrast,macrophage ATF6 overexpression exaggerated the acceleration of orthodontic tooth movement.In vitro experiments also proved that higher proportion of pro-inflammatory macrophages was positively correlated with higher expression of ATF6.At the mechanism level,RNA-seq and CUT&Tag analysis demonstrated that ATF6 modulated the macrophage-orchestrated inflammation through interacting with Tnfαpromotor and augmenting its transcription.Additionally,molecular docking simulation and dual-luciferase reporter system indicated the possible binding sites outside of the traditional endoplasmic reticulum-stress response element(ERSE).Taken together,ATF6 may aggravate orthodontic bone remodeling by promoting Tnfαtranscription in macrophages,suggesting that ATF6 may represent a promising therapeutic target for non-invasive accelerated orthodontics.
基金the funding provided by the National Helicopter Development Project of China。
文摘Accurate measurement of helicopter rotor motion parameters(flap,lead-lag,torsion,and azimuth angles)is essential for rotor blade design,helicopter dynamics modeling,and flight safety and health monitoring.However,the existing methods face challenges in testing equipment installation,calibration,and data transmission,resulting in limited reports on real-time in-flight measurements of blade motion parameters.This paper proposes a non-contact optoelectronic method based on two-dimensional position-sensitive detectors for in-flight measurement and a ground calibration system to obtain real-time rotor motion parameters during helicopter flight.The proposed method establishes the time evolution relationship of rotor motion parameters and verifies the performance of the in-flight measurement system regarding measurement resolution and accuracy through the construction of a blade motion posture experimental platform.The proposed method has been applied to the flight measurement of a medium-sized single-rotor helicopter,and the obtained results have been compared with theoretical analysis outcomes.Furthermore,this paper examines the characteristics of blade motion parameters during flight and discusses the challenges and potential solutions for measuring rotor motion parameters during helicopter flight using the proposed method.
基金support for this work is provided by the National Key R&D Program of China(2023YFC3012101)the National Natural Science Foundation of China(52474161)the Fundamental Research Funds for the Central Universities(2024ZKPYNY01).
文摘A novel block–particle discrete-element simulation method that matches the double medium of overlying rock(OLR)and loose layer(LSL)in coal mining is developed in this study.This method achieves the collaborative failure characteristics of mining damage under the conduction of double media between the OLR and LSL by combining the self-weight stress loading of the LSL and the breakage morphology of the bedrock top.Based on this,the conduction law of high-strength mining damage in the double medium in a western mining area is simulated and analyzed.The combining effect of the OLR breakage morphology and LSL characteristics on the surface-subsidence characteristics is analyzed and verified based on on-site measurements.The results indicate that the OLR is guided by the“double-control layer and thick-soft rock buffer layer”and shows“grouping subsidence”,whereas the surface forms collaborative subsidence with the thick-soft rock buffer layer.In the ultra-full mining stage,the surface presents an“asymmetric inverted trapezoidal”subsidence trough shape.The simulation results agree well the on-site measurements in terms of the surface-subsidence and bedrock-subsidence coefficients.The proposed simulation method provides a scientific approach for investigating the micro-conduction mechanism of mining damage under the effect of high-strength mining in western mining areas.It will benefit future investigations pertaining to the characteristics of OLR breakage and surface subsidence under conditions such as LSL thickness and proportion.
