Objective:Sepsis exhibits remarkable heterogeneity in disease progression trajectories,and accurate identificationof distinct trajectory-based phenotypes is critical for implementing personalized therapeutic strategie...Objective:Sepsis exhibits remarkable heterogeneity in disease progression trajectories,and accurate identificationof distinct trajectory-based phenotypes is critical for implementing personalized therapeutic strategies and prognostic assessment.However,trajectory clustering analysis of time-series clinical data poses substantial methodological challenges for researchers.This study provides a comprehensive tutorial framework demonstrating six trajectory modeling approaches integrated with proteomic analysis to guide researchers in identifying sepsis subtypes after laparoscopic surgery.Methods:This study employs simulated longitudinal data from 300 septic patients after laparoscopic surgery to demonstrate six trajectory modeling methods(group-based trajectory modeling,latent growth mixture modeling,latent transition analysis,time-varying effect modeling,K-means for longitudinal data,agglomerative hierarchical clustering)for identifying associations between predefinedsequential organ failure assessment trajectories and 25 proteomic biomarkers.Clustering performance was evaluated via multiple metrics,and a biomarker discovery pipeline integrating principal component analysis,random forests,feature selection,and receiver operating characteristic analysis was developed.Results:The six methods demonstrated varying performance in identifying trajectory structures,with each approach exhibiting distinct analytical characteristics.The performance metrics revealed differences across methods,which may inform context-specificmethod selection and interpretation strategies.Conclusion:This study illustrates practical implementations of trajectory modeling approaches under controlled conditions,facilitating informed method selection for clinical researchers.The inclusion of complete R code and integrated proteomics workflows offers a reproducible analytical framework connecting temporal pattern recognition to biomarker discovery.Beyond sepsis,this pipeline-oriented approach may be adapted to diverse clinical scenarios requiring longitudinal disease characterization and precision medicine applications.The comparative analysis reveals that each method has distinct strengths,providing a practical guide for clinical researchers in selecting appropriate methods based on their specificstudy goals and data characteristics.展开更多
The generation of synthetic trajectories has become essential in various fields for analyzing complex movement patterns.However,the use of real-world trajectory data poses significant privacy risks,such as location re...The generation of synthetic trajectories has become essential in various fields for analyzing complex movement patterns.However,the use of real-world trajectory data poses significant privacy risks,such as location reidentification and correlation attacks.To address these challenges,privacy-preserving trajectory generation methods are critical for applications relying on sensitive location data.This paper introduces DPIL-Traj,an advanced framework designed to generate synthetic trajectories while achieving a superior balance between data utility and privacy preservation.Firstly,the framework incorporates Differential Privacy Clustering,which anonymizes trajectory data by applying differential privacy techniques that add noise,ensuring the protection of sensitive user information.Secondly,Imitation Learning is used to replicate decision-making behaviors observed in real-world trajectories.By learning from expert trajectories,this component generates synthetic data that closely mimics real-world decision-making processes while optimizing the quality of the generated trajectories.Finally,Markov-based Trajectory Generation is employed to capture and maintain the inherent temporal dynamics of movement patterns.Extensive experiments conducted on the GeoLife trajectory dataset show that DPIL-Traj improves utility performance by an average of 19.85%,and in terms of privacy performance by an average of 12.51%,compared to state-of-the-art approaches.Ablation studies further reveal that DP clustering effectively safeguards privacy,imitation learning enhances utility under noise,and the Markov module strengthens temporal coherence.展开更多
Scalable simulation leveraging real-world data plays an essential role in advancing autonomous driving,owing to its efficiency and applicability in both training and evaluating algorithms.Consequently,there has been i...Scalable simulation leveraging real-world data plays an essential role in advancing autonomous driving,owing to its efficiency and applicability in both training and evaluating algorithms.Consequently,there has been increasing attention on generating highly realistic and consistent driving videos,particularly those involving viewpoint changes guided by the control commands or trajectories of ego vehicles.However,current reconstruction approaches,such as Neural Radiance Fields and 3D Gaussian Splatting,frequently suffer from limited generalization and depend on substantial input data.Meanwhile,2D generative models,though capable of producing unknown scenes,still have room for improvement in terms of coherence and visual realism.To overcome these challenges,we introduce GenScene,a world model that synthesizes front-view driving videos conditioned on trajectories.A new temporal module is presented to improve video consistency by extracting the global context of each frame,calculating relationships of frames using these global representations,and fusing frame contexts accordingly.Moreover,we propose an innovative attention mechanism that computes relations of pixels within each frame and pixels in the corresponding window range of the initial frame.Extensive experiments show that our approach surpasses various state-of-the-art models in driving video generation,and the introduced modules contribute significantly to model performance.This work establishes a new paradigm for goal-oriented video synthesis in autonomous driving,which facilitates on-demand simulation to expedite algorithm development.展开更多
In the field of intelligent air combat,real-time and accurate recognition of within-visual-range(WVR)maneuver actions serves as the foundational cornerstone for constructing autonomous decision-making systems.However,...In the field of intelligent air combat,real-time and accurate recognition of within-visual-range(WVR)maneuver actions serves as the foundational cornerstone for constructing autonomous decision-making systems.However,existing methods face two major challenges:traditional feature engineering suffers from insufficient effective dimensionality in the feature space due to kinematic coupling,making it difficult to distinguish essential differences between maneuvers,while end-to-end deep learning models lack controllability in implicit feature learning and fail to model high-order long-range temporal dependencies.This paper proposes a trajectory feature pre-extraction method based on a Long-range Masked Autoencoder(LMAE),incorporating three key innovations:(1)Random Fragment High-ratio Masking(RFH-Mask),which enforces the model to learn long-range temporal correlations by masking 80%of trajectory data while retaining continuous fragments;(2)Kalman Filter-Guided Objective Function(KFG-OF),integrating trajectory continuity constraints to align the feature space with kinematic principles;and(3)Two-stage Decoupled Architecture,enabling efficient and controllable feature learning through unsupervised pre-training and frozen-feature transfer.Experimental results demonstrate that LMAE significantly improves the average recognition accuracy for 20-class maneuvers compared to traditional end-to-end models,while significantly accelerating convergence speed.The contributions of this work lie in:introducing high-masking-rate autoencoders into low-informationdensity trajectory analysis,proposing a feature engineering framework with enhanced controllability and efficiency,and providing a novel technical pathway for intelligent air combat decision-making systems.展开更多
The environment of low-altitude urban airspace is complex and variable due to numerous obstacles,non-cooperative aircraft,and birds.Unmanned Aerial Vehicles(UAVs)leveraging environmental information to achieve three-d...The environment of low-altitude urban airspace is complex and variable due to numerous obstacles,non-cooperative aircraft,and birds.Unmanned Aerial Vehicles(UAVs)leveraging environmental information to achieve three-dimension collision-free trajectory planning is the prerequisite to ensure airspace security.However,the timely information of surrounding situation is difficult to acquire by UAVs,which further brings security risks.As a mature technology leveraged in traditional civil aviation,the Automatic Dependent Surveillance-Broadcast(ADS-B)realizes continuous surveillance of the information of aircraft.Consequently,we leverage ADS-B for surveillance and information broadcasting,and divide the aerial airspace into multiple sub-airspaces to improve flight safety in UAV trajectory planning.In detail,we propose the secure Sub-airSpaces Planning(SSP)algorithm and Particle Swarm Optimization Rapidly-exploring Random Trees(PSO-RRT)algorithm for the UAV trajectory planning in law-altitude airspace.The performance of the proposed algorithm is verified by simulations and the results show that SSP reduces both the maximum number of UAVs in the sub-airspace and the length of the trajectory,and PSO-RRT reduces the cost of UAV trajectory in the sub-airspace.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
In this paper,we investigate a multi-UAV aided NOMA communication system,where multiple UAV-mounted aerial base stations are employed to serve ground users in the downlink NOMA communication,and each UAV serves its as...In this paper,we investigate a multi-UAV aided NOMA communication system,where multiple UAV-mounted aerial base stations are employed to serve ground users in the downlink NOMA communication,and each UAV serves its associated users on its own bandwidth.We aim at maximizing the overall common throughput in a finite time period.Such a problem is a typical mixed integer nonlinear problem,which involves both continuous-variable and combinatorial optimizations.To efficiently solve this problem,we propose a two-layer algorithm,which separately tackles continuous-variable and combinatorial optimization.Specifically,in the inner layer given one user association scheme,subproblems of bandwidth allocation,power allocation and trajectory design are solved based on alternating optimization.In the outer layer,a small number of candidate user association schemes are generated from an initial scheme and the best solution can be determined by comparing all the candidate schemes.In particular,a clustering algorithm based on K-means is applied to produce all candidate user association schemes,the successive convex optimization technique is adopted in the power allocation subproblem and a logistic function approximation approach is employed in the trajectory design subproblem.Simulation results show that the proposed NOMA scheme outperforms three baseline schemes in downlink common throughput,including one solution proposed in an existing literature.展开更多
This paper studies the tracking control problem for stratospheric airships with userspecified performance.Dealing with the infinite gain phenomenon in the prescribed-time stability,a new stability criterion with bound...This paper studies the tracking control problem for stratospheric airships with userspecified performance.Dealing with the infinite gain phenomenon in the prescribed-time stability,a new stability criterion with bounded gain is proposed by using a new time-varying scaling function.Moreover,a same-side performance function and a novel barrier Lyapunov function are incorporated into the control algorithm,which can compress the feasible domain of tracking error to minimize the overshoot and solve the difficult in tracking error not converging to zero simultaneously.The proposed scheme guarantees the airship capable of operating autonomously with satisfactory transient performance and tracking accuracy,where the performance parameters can be designed artificially and link to the physical process directly.Finally,the effectiveness of the proposed control scheme is verified by theoretical analysis and numerical simulation.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
Objective We aimed to investigate the patterns of fasting blood glucose(FBG)trajectories and analyze the relationship between various occupational hazard factors and FBG trajectories in male steelworkers.Methods The s...Objective We aimed to investigate the patterns of fasting blood glucose(FBG)trajectories and analyze the relationship between various occupational hazard factors and FBG trajectories in male steelworkers.Methods The study cohort included 3,728 workers who met the selection criteria for the Tanggang Occupational Cohort(TGOC)between 2017 and 2022.A group-based trajectory model was used to identify the FBG trajectories.Environmental risk scores(ERS)were constructed using regression coefficients from the occupational hazard model as weights.Univariate and multivariate logistic regression analyses were performed to explore the effects of occupational hazard factors using the ERS on FBG trajectories.Results FBG trajectories were categorized into three groups.An association was observed between high temperature,noise exposure,and FBG trajectory(P<0.05).Using the first quartile group of ERS1 as a reference,the fourth quartile group of ERS1 had an increased risk of medium and high FBG by 1.90and 2.21 times,respectively(odds ratio[OR]=1.90,95%confidence interval[CI]:1.17–3.10;OR=2.21,95%CI:1.09–4.45).Conclusion An association was observed between occupational hazards based on ERS and FBG trajectories.The risk of FBG trajectory levels increase with an increase in ERS.展开更多
1Introduction To date,in model-based gait-planning methods,the dynamics of the center of mass(COM)of bipedal robots have been analyzed by establishing their linear inverted pendulum model(LIPM)or extended forms(Owaki ...1Introduction To date,in model-based gait-planning methods,the dynamics of the center of mass(COM)of bipedal robots have been analyzed by establishing their linear inverted pendulum model(LIPM)or extended forms(Owaki et al.,2010;Englsberger et al.,2015;Xie et al.,2020).With regard to model-based gait-generation methods for uphill and downhill terrain,Kuo(2007)simulated human gait using an inverted pendulum,which provided a circular trajectory for the COM rather than a horizontal trajectory.He found that a horizontal COM trajectory consumed more muscle energy.Massah et al.(2012)utilized a 3D LIPM and the concept of zero moment point(ZMP).They developed a trajectory planner using the semi-elliptical motion equations of an NAO humanoid robot and simulated walking on various sloped terrains using the Webots platform.展开更多
BACKGROUND The atherogenic index of plasma(AIP)has been shown to be positively correlated with cardiovascular disease in previous studies.However,it is unclear whether elderly people with long-term high AIP levels are...BACKGROUND The atherogenic index of plasma(AIP)has been shown to be positively correlated with cardiovascular disease in previous studies.However,it is unclear whether elderly people with long-term high AIP levels are more likely to develop coronary heart disease(CHD).Therefore,the aim of this study was to investigate the relationship between AIP trajectory and CHD incidence in elderly people.METHODS 19,194 participants aged≥60 years who had three AIP measurements between 2018 and 2020 were included in this study.AIP was defined as log10(triglyceride/high-density lipoprotein cholesterol).The group-based trajectory model was used to identify different trajectory patterns of AIP from 2018 to 2020.Cox proportional hazards models were used to estimate the hazard ratio(HR)with 95%CI of CHD events between different trajectory groups from 2020 to 2023.RESULTS Three different trajectory patterns were identified through group-based trajectory model:the low-level group(n=7410,mean AIP:-0.25 to-0.17),the medium-level group(n=9981,mean AIP:0.02-0.08),and the high-level group(n=1803,mean AIP:0.38-0.42).During a mean follow-up of 2.65 years,a total of 1391 participants developed CHD.After adjusting for potential confounders,compared with the participants in the low-level group,the HR with 95%CI of the medium-level group and the high-level group were estimated to be 1.24(1.10-1.40)and 1.43(1.19-1.73),respectively.These findings remained consistent in subgroup analyses and sensitivity analyses.CONCLUSIONS There was a significant correlation between persistent high AIP level and increased CHD risk in the elderly.This suggests that monitoring the long-term changes in AIP is helpful to identify individuals at high CHD risk in elderly people.展开更多
1. Background Driven by ongoing economic expansion and low-altitude aviation development, the global air transportation industry has experienced significant growth in recent decades, resulting in increasing airspace c...1. Background Driven by ongoing economic expansion and low-altitude aviation development, the global air transportation industry has experienced significant growth in recent decades, resulting in increasing airspace complexity, and considerable challenges for Air Traffic Control(ATC). As the fundamental technique of the ATC system, Flight Trajectory Prediction(FTP) forecasts future traffic dynamics to support critical applications(such as conflict detection), and also serves as a cornerstone for future Trajectory-based Operations(TBO).展开更多
Aimed at the demand of contingency return at any time during the near-moon phase in the manned lunar landing missions,a fast calculation method for three-impulse contingency return trajectories is proposed.Firstly,a t...Aimed at the demand of contingency return at any time during the near-moon phase in the manned lunar landing missions,a fast calculation method for three-impulse contingency return trajectories is proposed.Firstly,a three-impulse contingency return trajectory scheme is presented by combining the Lambert transfer and maneuver at the special point.Secondly,a calculation model of three-impulse contingency return trajectories is established.Then,fast calculation methods are proposed by adopting the high-order Taylor expansion of differential algebra in the twobody trajectory dynamics model and perturbed trajectory dynamics model.Finally,the performance of the proposed methods is verified by numerical simulation.The results indicate that the fast calculation method of two-body trajectory has higher calculation efficiency compared to the semi-analytical calculation method under a certain accuracy condition.Due to its high efficiency,the characteristics of the three-impulse contingency return trajectories under different contingency scenarios are further analyzed expeditiously.These findings can be used for the design of contingency return trajectories in future manned lunar landing missions.展开更多
Objective:To preliminarily construct and apply a longitudinal trajectory model for the prognosis of intracerebral hemorrhage(ICH)based on blood urea nitrogen(BUN)characteristics.Methods:Clinical data from 320 ICH pati...Objective:To preliminarily construct and apply a longitudinal trajectory model for the prognosis of intracerebral hemorrhage(ICH)based on blood urea nitrogen(BUN)characteristics.Methods:Clinical data from 320 ICH patients admitted to our hospital between 2020 and 2024 were collected,including demographic information,National Institutes of Health Stroke Scale(NIHSS)scores at admission,dynamic changes in BUN levels during treatment,and 30-day survival outcomes.A latent class growth model(LCGM)was first used for preliminary modeling,followed by a latent growth mixture modeling(GMM)approach to determine the final model.Three classes of BUN trajectories for ICH prognosis were identified,and latent classes were established.GMM modeling was then performed on these latent classes,considering linear,quadratic,and cubic polynomial forms;six GMM models were constructed and individuals were assigned to latent trajectory groups for validation.Results:LCGM analysis ultimately identified three dynamic BUN trajectory groups:Sustained low-level group(76 cases,23.8%):BUN remained stable between 3.1-9.0 mmol/L,with the highest 30-day survival rate(98.7%).Fluctuating-declining group(222 cases,69.4%):BUN initially increased and then slowly decreased(peak at day 3:15.2 mmol/L),with a 30-day mortality of 8.1%(18/222),higher than the sustained low-level group.Sustained high-level group(22 cases,6.9%):BUN mean>9.0 mmol/L,with a 30-day mortality of 41.7%(P=0.000).GMM model fitting showed that the cubic polynomial GMM model was optimal(AIC=6754.474,BIC=6852.450,Entropy=0.905).Incorporating gender,age,and BMI as covariates revealed significant effects for gender(Estimate=0.045,-0.011,P=0.000,0.000).The AUC for predicting 30-day mortality was 0.88(sensitivity 82.8%,specificity 77.9%),which increased to 0.89 when combined with admission NIHSS scores.Conclusion:The LCGM+GMM model based on dynamic BUN trajectories effectively distinguishes prognostic subgroups in ICH patients.Patients with persistently elevated or fluctuating-rising BUN levels have a significantly higher mortality risk compared to those with sustained low levels.This model provides a new quantitative tool for early identification of high-risk patients and poor prognoses.展开更多
BACKGROUND Neck pain,a primary symptom of cervical spondylosis,affects patients'physical and mental health,reducing their quality of life.Pain and emotional state interact;however,their longitudinal interrelations...BACKGROUND Neck pain,a primary symptom of cervical spondylosis,affects patients'physical and mental health,reducing their quality of life.Pain and emotional state interact;however,their longitudinal interrelationship remains unclear.In this study,we applied a dual-trajectory model to assess how neck pain and emotional state evolve together over time and how clinical interventions,particularly acupuncture,influence these trajectories.AIM To investigate the longitudinal relationship between neck pain and emotional state in patients with cervical spondylosis.METHODS This prospective cohort study included 472 patients with cervical spondylosis from eight Chinese hospitals.Participants received acupuncture or medication and were followed up at baseline,and at 1,2,4,6,and 8 weeks.Neck pain and emotional distress were assessed using the Northwick Park Neck Pain Questionnaire(NPQ)and the affective subscale of the Short-Form McGill Pain Questionnaire(SF-MPQ),respectively.Group-based trajectory models and dual trajectory analysis were used to identify and correlate pain-emotion trajectories.Multivariate logistic regression identified predictors of group membership.RESULTS Three trajectory groups were identified for NPQ and SF-MPQ scores(low,medium,and high).Higher NPQ trajectory was associated with older age(OR=1.058,P<0.001)and was significantly reduced by acupuncture(OR=0.382,P<0.001).Similarly,acupuncture lowered the odds of high SF-MPQ trajectory membership(OR=0.336,P<0.001),while age increased it(OR=1.037,P<0.001).Dual-trajectory analysis revealed bidirectional associations:69.1%of patients with low NPQ had low SF-MPQ scores,and 42.6%of patients with high SF-MPQ also had high NPQ scores.Gender was a predictor for medium SF-MPQ trajectory(OR=1.629,P=0.094).Occupation and education levels differed significantly across the trajectory groups(P<0.05).CONCLUSION Over time,neck pain and emotional distress are closely associated in patients with cervical spondylosis.Acupuncture alleviates both outcomes significantly,while age is a risk factor.Integrated approaches to pain and emotional management are encouraged.展开更多
To evaluate the heat performance of the lifting-body entry vehicle during the hypersonic gliding phase,entry flight heat tests involving the determination of the maximum peak-heat-flux entry trajectory with complex co...To evaluate the heat performance of the lifting-body entry vehicle during the hypersonic gliding phase,entry flight heat tests involving the determination of the maximum peak-heat-flux entry trajectory with complex constraints are essential.A significant obstacle is the uncertainty of passage time or energy states of the maximum peak entry heat flux point and waypoints.This paper showcases an endeavour to leverage disjunctive programming and combinatorial theory for the max-max type(maximum peak-heat-flux)Entry Trajectory Optimization(ETO)problems with complex constraints such as dynamic pressure,normal load,waypoints,and no-fly zones.The concept of a"generalized waypoint"is introduced,and the maximum peak-heat-flux point is regarded as a"generalized waypoint".Through the application of propositional calculus rules,the derivation of generalized waypoints incorporating various physical quantities and magnitudes such as heat flux density,longitude,and latitude is actualized in one disjunctive normal form,enabling resolution via a unified method.Consequently,a novel method based on combinatorial prior rules is proposed,utilizing Successive Mixed-Integer Nonlinear Programming(SMINLP)to optimize various heat entry test flight trajectories.Numerical experiments are provided to show the computational accuracy,stability,and adaptability of the proposed method in solving maxmax type entry optimal control problems.展开更多
Cohort studies are important epidemiological methods to investigate associations between environmental factors,individual characteristics,and disease or other health outcomes.As a paradigm of cohort studies,the Framin...Cohort studies are important epidemiological methods to investigate associations between environmental factors,individual characteristics,and disease or other health outcomes.As a paradigm of cohort studies,the Framingham Heart Study(FHS)is the longest-running cardiovascular epidemiological study,starting in 1948.展开更多
In this study,it is aimed to develop a generic model which calculates the trajectory of the ejection seat from the jet aircraft,by taking into account the parameters that will affect the seat movement such as the seat...In this study,it is aimed to develop a generic model which calculates the trajectory of the ejection seat from the jet aircraft,by taking into account the parameters that will affect the seat movement such as the seat’s launch speed,ejection direction,ejection angle,altitude of the aircraft,distance/height from the aircraft rudder and canopy,pilot and ejection seat weight.With the model algorithm proposed,the ejection seat trajectory model was developed on MATLAB.The ejection seat trajectory model is based on point mass trajectory mathematical model.In this study,an analytical study of the problem has been made for modeling the flight trajectory of the ejection seat after it has been ejected.Past studies were used as a basis for validation and simulation.By writing a generic MATLAB code,a user interface was developed and presented to the user as a module.This generic code that has been developed could be used for simulations by users in the future by revising it in accordance with their own job descriptions.展开更多
Addressing the issue that flight plans between Chinese city pairs typically rely on a single route,lacking alternative paths and posing challenges in responding to emergencies,this study employs the“quantile-inflecti...Addressing the issue that flight plans between Chinese city pairs typically rely on a single route,lacking alternative paths and posing challenges in responding to emergencies,this study employs the“quantile-inflection point method”to analyze specific deviation trajectories,determine deviation thresholds,and identify commonly used deviation paths.By combining multiple similarity metrics,including Euclidean distance,Hausdorff distance,and sector edit distance,with the density-based spatial clustering of applications with noise(DBSCAN)algorithm,the study clusters deviation trajectories to construct a multi-option trajectory set for city pairs.A case study of 23578 flight trajectories between the Guangzhou airport cluster and the Shanghai airport cluster demonstrates the effectiveness of the proposed framework.Experimental results show that sector edit distance achieves superior clustering performance compared to Euclidean and Hausdorff distances,with higher silhouette coefficients and lower Davies⁃Bouldin indices,ensuring better intra-cluster compactness and inter-cluster separation.Based on clustering results,19 representative trajectory options are identified,covering both nominal and deviation paths,which significantly enhance route diversity and reflect actual flight practices.This provides a practical basis for optimizing flight paths and scheduling,enhancing the flexibility of route selection for flights between city pairs.展开更多
基金funding from the China National Key Research and Development Program(No.2023YFC3603104)the National Natural Science Foundation of China(Nos.82472243 and 82272180)+6 种基金the Fundamental Research Funds for the Central Universities(No.226-2025-00024)the Huadong Medicine Joint Funds of the Zhejiang Provincial Natural Science Foundation of China(No.LHDMD24H150001)the Key Research&Development Project of Zhejiang Province(No.2024C03240)a collaborative scientific project co-established by the Science and Technology Department of the National Administration of Traditional Chinese Medicine and the Zhejiang Provincial Administration of Traditional Chinese Medicine(No.GZY-ZJ-KJ-24082)he General Health Science and Technology Program of Zhejiang Province(No.2024KY1099)the Project of Zhejiang University Longquan Innovation Center(No.ZJDXLQCXZCJBGS2024016)Wu Jieping Medical Foundation Special Research Grant(No.320.6750.2024-23-07).
文摘Objective:Sepsis exhibits remarkable heterogeneity in disease progression trajectories,and accurate identificationof distinct trajectory-based phenotypes is critical for implementing personalized therapeutic strategies and prognostic assessment.However,trajectory clustering analysis of time-series clinical data poses substantial methodological challenges for researchers.This study provides a comprehensive tutorial framework demonstrating six trajectory modeling approaches integrated with proteomic analysis to guide researchers in identifying sepsis subtypes after laparoscopic surgery.Methods:This study employs simulated longitudinal data from 300 septic patients after laparoscopic surgery to demonstrate six trajectory modeling methods(group-based trajectory modeling,latent growth mixture modeling,latent transition analysis,time-varying effect modeling,K-means for longitudinal data,agglomerative hierarchical clustering)for identifying associations between predefinedsequential organ failure assessment trajectories and 25 proteomic biomarkers.Clustering performance was evaluated via multiple metrics,and a biomarker discovery pipeline integrating principal component analysis,random forests,feature selection,and receiver operating characteristic analysis was developed.Results:The six methods demonstrated varying performance in identifying trajectory structures,with each approach exhibiting distinct analytical characteristics.The performance metrics revealed differences across methods,which may inform context-specificmethod selection and interpretation strategies.Conclusion:This study illustrates practical implementations of trajectory modeling approaches under controlled conditions,facilitating informed method selection for clinical researchers.The inclusion of complete R code and integrated proteomics workflows offers a reproducible analytical framework connecting temporal pattern recognition to biomarker discovery.Beyond sepsis,this pipeline-oriented approach may be adapted to diverse clinical scenarios requiring longitudinal disease characterization and precision medicine applications.The comparative analysis reveals that each method has distinct strengths,providing a practical guide for clinical researchers in selecting appropriate methods based on their specificstudy goals and data characteristics.
基金supported by the Natural Science Foundation of Fujian Province of China(2025J01380)National Natural Science Foundation of China(No.62471139)+3 种基金the Major Health Research Project of Fujian Province(2021ZD01001)Fujian Provincial Units Special Funds for Education and Research(2022639)Fujian University of Technology Research Start-up Fund(GY-S24002)Fujian Research and Training Grants for Young and Middle-aged Leaders in Healthcare(GY-H-24179).
文摘The generation of synthetic trajectories has become essential in various fields for analyzing complex movement patterns.However,the use of real-world trajectory data poses significant privacy risks,such as location reidentification and correlation attacks.To address these challenges,privacy-preserving trajectory generation methods are critical for applications relying on sensitive location data.This paper introduces DPIL-Traj,an advanced framework designed to generate synthetic trajectories while achieving a superior balance between data utility and privacy preservation.Firstly,the framework incorporates Differential Privacy Clustering,which anonymizes trajectory data by applying differential privacy techniques that add noise,ensuring the protection of sensitive user information.Secondly,Imitation Learning is used to replicate decision-making behaviors observed in real-world trajectories.By learning from expert trajectories,this component generates synthetic data that closely mimics real-world decision-making processes while optimizing the quality of the generated trajectories.Finally,Markov-based Trajectory Generation is employed to capture and maintain the inherent temporal dynamics of movement patterns.Extensive experiments conducted on the GeoLife trajectory dataset show that DPIL-Traj improves utility performance by an average of 19.85%,and in terms of privacy performance by an average of 12.51%,compared to state-of-the-art approaches.Ablation studies further reveal that DP clustering effectively safeguards privacy,imitation learning enhances utility under noise,and the Markov module strengthens temporal coherence.
基金supported by the Cultivation Program for Major Scientific Research Projects of Harbin Institute of Technology(ZDXMPY20180109).
文摘Scalable simulation leveraging real-world data plays an essential role in advancing autonomous driving,owing to its efficiency and applicability in both training and evaluating algorithms.Consequently,there has been increasing attention on generating highly realistic and consistent driving videos,particularly those involving viewpoint changes guided by the control commands or trajectories of ego vehicles.However,current reconstruction approaches,such as Neural Radiance Fields and 3D Gaussian Splatting,frequently suffer from limited generalization and depend on substantial input data.Meanwhile,2D generative models,though capable of producing unknown scenes,still have room for improvement in terms of coherence and visual realism.To overcome these challenges,we introduce GenScene,a world model that synthesizes front-view driving videos conditioned on trajectories.A new temporal module is presented to improve video consistency by extracting the global context of each frame,calculating relationships of frames using these global representations,and fusing frame contexts accordingly.Moreover,we propose an innovative attention mechanism that computes relations of pixels within each frame and pixels in the corresponding window range of the initial frame.Extensive experiments show that our approach surpasses various state-of-the-art models in driving video generation,and the introduced modules contribute significantly to model performance.This work establishes a new paradigm for goal-oriented video synthesis in autonomous driving,which facilitates on-demand simulation to expedite algorithm development.
文摘In the field of intelligent air combat,real-time and accurate recognition of within-visual-range(WVR)maneuver actions serves as the foundational cornerstone for constructing autonomous decision-making systems.However,existing methods face two major challenges:traditional feature engineering suffers from insufficient effective dimensionality in the feature space due to kinematic coupling,making it difficult to distinguish essential differences between maneuvers,while end-to-end deep learning models lack controllability in implicit feature learning and fail to model high-order long-range temporal dependencies.This paper proposes a trajectory feature pre-extraction method based on a Long-range Masked Autoencoder(LMAE),incorporating three key innovations:(1)Random Fragment High-ratio Masking(RFH-Mask),which enforces the model to learn long-range temporal correlations by masking 80%of trajectory data while retaining continuous fragments;(2)Kalman Filter-Guided Objective Function(KFG-OF),integrating trajectory continuity constraints to align the feature space with kinematic principles;and(3)Two-stage Decoupled Architecture,enabling efficient and controllable feature learning through unsupervised pre-training and frozen-feature transfer.Experimental results demonstrate that LMAE significantly improves the average recognition accuracy for 20-class maneuvers compared to traditional end-to-end models,while significantly accelerating convergence speed.The contributions of this work lie in:introducing high-masking-rate autoencoders into low-informationdensity trajectory analysis,proposing a feature engineering framework with enhanced controllability and efficiency,and providing a novel technical pathway for intelligent air combat decision-making systems.
基金supported by the National Key R&D Program of China(No.2022YFB3104502)the National Natural Science Foundation of China(No.62301251)+2 种基金the Natural Science Foundation of Jiangsu Province of China under Project(No.BK20220883)the open research fund of National Mobile Communications Research Laboratory,Southeast University,China(No.2024D04)the Young Elite Scientists Sponsorship Program by CAST(No.2023QNRC001).
文摘The environment of low-altitude urban airspace is complex and variable due to numerous obstacles,non-cooperative aircraft,and birds.Unmanned Aerial Vehicles(UAVs)leveraging environmental information to achieve three-dimension collision-free trajectory planning is the prerequisite to ensure airspace security.However,the timely information of surrounding situation is difficult to acquire by UAVs,which further brings security risks.As a mature technology leveraged in traditional civil aviation,the Automatic Dependent Surveillance-Broadcast(ADS-B)realizes continuous surveillance of the information of aircraft.Consequently,we leverage ADS-B for surveillance and information broadcasting,and divide the aerial airspace into multiple sub-airspaces to improve flight safety in UAV trajectory planning.In detail,we propose the secure Sub-airSpaces Planning(SSP)algorithm and Particle Swarm Optimization Rapidly-exploring Random Trees(PSO-RRT)algorithm for the UAV trajectory planning in law-altitude airspace.The performance of the proposed algorithm is verified by simulations and the results show that SSP reduces both the maximum number of UAVs in the sub-airspace and the length of the trajectory,and PSO-RRT reduces the cost of UAV trajectory in the sub-airspace.
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 Beijing Natural Science Fund–Haidian Original Innovation Joint Fund(L232040 and L232045).
文摘In this paper,we investigate a multi-UAV aided NOMA communication system,where multiple UAV-mounted aerial base stations are employed to serve ground users in the downlink NOMA communication,and each UAV serves its associated users on its own bandwidth.We aim at maximizing the overall common throughput in a finite time period.Such a problem is a typical mixed integer nonlinear problem,which involves both continuous-variable and combinatorial optimizations.To efficiently solve this problem,we propose a two-layer algorithm,which separately tackles continuous-variable and combinatorial optimization.Specifically,in the inner layer given one user association scheme,subproblems of bandwidth allocation,power allocation and trajectory design are solved based on alternating optimization.In the outer layer,a small number of candidate user association schemes are generated from an initial scheme and the best solution can be determined by comparing all the candidate schemes.In particular,a clustering algorithm based on K-means is applied to produce all candidate user association schemes,the successive convex optimization technique is adopted in the power allocation subproblem and a logistic function approximation approach is employed in the trajectory design subproblem.Simulation results show that the proposed NOMA scheme outperforms three baseline schemes in downlink common throughput,including one solution proposed in an existing literature.
基金supported by the National Natural Science Foundation of China(Nos.51775021,52302511)the Fundamental Research Funds for the Central Universities,China(Nos.501JCGG2024129003,501JCGG2024129005,501JCGG2024129006),the Fundamental Research Funds for the Central Universities,China(No.YWF-24-JC-09)the National Key Research and Development Program of China(No.2018YFC1506401)。
文摘This paper studies the tracking control problem for stratospheric airships with userspecified performance.Dealing with the infinite gain phenomenon in the prescribed-time stability,a new stability criterion with bounded gain is proposed by using a new time-varying scaling function.Moreover,a same-side performance function and a novel barrier Lyapunov function are incorporated into the control algorithm,which can compress the feasible domain of tracking error to minimize the overshoot and solve the difficult in tracking error not converging to zero simultaneously.The proposed scheme guarantees the airship capable of operating autonomously with satisfactory transient performance and tracking accuracy,where the performance parameters can be designed artificially and link to the physical process directly.Finally,the effectiveness of the proposed control scheme is verified by theoretical analysis and numerical simulation.
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 Key Research and Development Program of the Ministry of Science and Technology of China(grant number:2016YF0900605)the Key Research and Development Program of Hebei Province(grant number:192777129D)+1 种基金the Joint Fund for Iron and Steel of the Natural Science Foundation of Hebei Province(grant number:H2016209058)the National Natural Science Foundation for Regional Joint Fund of China(grant number:U22A20364)。
文摘Objective We aimed to investigate the patterns of fasting blood glucose(FBG)trajectories and analyze the relationship between various occupational hazard factors and FBG trajectories in male steelworkers.Methods The study cohort included 3,728 workers who met the selection criteria for the Tanggang Occupational Cohort(TGOC)between 2017 and 2022.A group-based trajectory model was used to identify the FBG trajectories.Environmental risk scores(ERS)were constructed using regression coefficients from the occupational hazard model as weights.Univariate and multivariate logistic regression analyses were performed to explore the effects of occupational hazard factors using the ERS on FBG trajectories.Results FBG trajectories were categorized into three groups.An association was observed between high temperature,noise exposure,and FBG trajectory(P<0.05).Using the first quartile group of ERS1 as a reference,the fourth quartile group of ERS1 had an increased risk of medium and high FBG by 1.90and 2.21 times,respectively(odds ratio[OR]=1.90,95%confidence interval[CI]:1.17–3.10;OR=2.21,95%CI:1.09–4.45).Conclusion An association was observed between occupational hazards based on ERS and FBG trajectories.The risk of FBG trajectory levels increase with an increase in ERS.
基金supported by the National Natural Science Foundation of China(No.12332023)the Zhejiang Provincial Natural Science Foundation of China(No.LY23E050010).
文摘1Introduction To date,in model-based gait-planning methods,the dynamics of the center of mass(COM)of bipedal robots have been analyzed by establishing their linear inverted pendulum model(LIPM)or extended forms(Owaki et al.,2010;Englsberger et al.,2015;Xie et al.,2020).With regard to model-based gait-generation methods for uphill and downhill terrain,Kuo(2007)simulated human gait using an inverted pendulum,which provided a circular trajectory for the COM rather than a horizontal trajectory.He found that a horizontal COM trajectory consumed more muscle energy.Massah et al.(2012)utilized a 3D LIPM and the concept of zero moment point(ZMP).They developed a trajectory planner using the semi-elliptical motion equations of an NAO humanoid robot and simulated walking on various sloped terrains using the Webots platform.
基金supported by the National Key Research and Development Program of China(2017YFC1307705).
文摘BACKGROUND The atherogenic index of plasma(AIP)has been shown to be positively correlated with cardiovascular disease in previous studies.However,it is unclear whether elderly people with long-term high AIP levels are more likely to develop coronary heart disease(CHD).Therefore,the aim of this study was to investigate the relationship between AIP trajectory and CHD incidence in elderly people.METHODS 19,194 participants aged≥60 years who had three AIP measurements between 2018 and 2020 were included in this study.AIP was defined as log10(triglyceride/high-density lipoprotein cholesterol).The group-based trajectory model was used to identify different trajectory patterns of AIP from 2018 to 2020.Cox proportional hazards models were used to estimate the hazard ratio(HR)with 95%CI of CHD events between different trajectory groups from 2020 to 2023.RESULTS Three different trajectory patterns were identified through group-based trajectory model:the low-level group(n=7410,mean AIP:-0.25 to-0.17),the medium-level group(n=9981,mean AIP:0.02-0.08),and the high-level group(n=1803,mean AIP:0.38-0.42).During a mean follow-up of 2.65 years,a total of 1391 participants developed CHD.After adjusting for potential confounders,compared with the participants in the low-level group,the HR with 95%CI of the medium-level group and the high-level group were estimated to be 1.24(1.10-1.40)and 1.43(1.19-1.73),respectively.These findings remained consistent in subgroup analyses and sensitivity analyses.CONCLUSIONS There was a significant correlation between persistent high AIP level and increased CHD risk in the elderly.This suggests that monitoring the long-term changes in AIP is helpful to identify individuals at high CHD risk in elderly people.
文摘1. Background Driven by ongoing economic expansion and low-altitude aviation development, the global air transportation industry has experienced significant growth in recent decades, resulting in increasing airspace complexity, and considerable challenges for Air Traffic Control(ATC). As the fundamental technique of the ATC system, Flight Trajectory Prediction(FTP) forecasts future traffic dynamics to support critical applications(such as conflict detection), and also serves as a cornerstone for future Trajectory-based Operations(TBO).
基金co-supported by the National Natural Science Foundation of China(No.12072365)the Technology Innovation Team of Manned Space Engineering,China。
文摘Aimed at the demand of contingency return at any time during the near-moon phase in the manned lunar landing missions,a fast calculation method for three-impulse contingency return trajectories is proposed.Firstly,a three-impulse contingency return trajectory scheme is presented by combining the Lambert transfer and maneuver at the special point.Secondly,a calculation model of three-impulse contingency return trajectories is established.Then,fast calculation methods are proposed by adopting the high-order Taylor expansion of differential algebra in the twobody trajectory dynamics model and perturbed trajectory dynamics model.Finally,the performance of the proposed methods is verified by numerical simulation.The results indicate that the fast calculation method of two-body trajectory has higher calculation efficiency compared to the semi-analytical calculation method under a certain accuracy condition.Due to its high efficiency,the characteristics of the three-impulse contingency return trajectories under different contingency scenarios are further analyzed expeditiously.These findings can be used for the design of contingency return trajectories in future manned lunar landing missions.
文摘Objective:To preliminarily construct and apply a longitudinal trajectory model for the prognosis of intracerebral hemorrhage(ICH)based on blood urea nitrogen(BUN)characteristics.Methods:Clinical data from 320 ICH patients admitted to our hospital between 2020 and 2024 were collected,including demographic information,National Institutes of Health Stroke Scale(NIHSS)scores at admission,dynamic changes in BUN levels during treatment,and 30-day survival outcomes.A latent class growth model(LCGM)was first used for preliminary modeling,followed by a latent growth mixture modeling(GMM)approach to determine the final model.Three classes of BUN trajectories for ICH prognosis were identified,and latent classes were established.GMM modeling was then performed on these latent classes,considering linear,quadratic,and cubic polynomial forms;six GMM models were constructed and individuals were assigned to latent trajectory groups for validation.Results:LCGM analysis ultimately identified three dynamic BUN trajectory groups:Sustained low-level group(76 cases,23.8%):BUN remained stable between 3.1-9.0 mmol/L,with the highest 30-day survival rate(98.7%).Fluctuating-declining group(222 cases,69.4%):BUN initially increased and then slowly decreased(peak at day 3:15.2 mmol/L),with a 30-day mortality of 8.1%(18/222),higher than the sustained low-level group.Sustained high-level group(22 cases,6.9%):BUN mean>9.0 mmol/L,with a 30-day mortality of 41.7%(P=0.000).GMM model fitting showed that the cubic polynomial GMM model was optimal(AIC=6754.474,BIC=6852.450,Entropy=0.905).Incorporating gender,age,and BMI as covariates revealed significant effects for gender(Estimate=0.045,-0.011,P=0.000,0.000).The AUC for predicting 30-day mortality was 0.88(sensitivity 82.8%,specificity 77.9%),which increased to 0.89 when combined with admission NIHSS scores.Conclusion:The LCGM+GMM model based on dynamic BUN trajectories effectively distinguishes prognostic subgroups in ICH patients.Patients with persistently elevated or fluctuating-rising BUN levels have a significantly higher mortality risk compared to those with sustained low levels.This model provides a new quantitative tool for early identification of high-risk patients and poor prognoses.
基金Supported by 2022 Chinese Medicine Scientific Research Project of Hebei Administration of Traditional Chinese Medicine,No.20221572025 Annual Scientific Research Project of Higher Education Institutions in Hebei Province,No.QN2025654.
文摘BACKGROUND Neck pain,a primary symptom of cervical spondylosis,affects patients'physical and mental health,reducing their quality of life.Pain and emotional state interact;however,their longitudinal interrelationship remains unclear.In this study,we applied a dual-trajectory model to assess how neck pain and emotional state evolve together over time and how clinical interventions,particularly acupuncture,influence these trajectories.AIM To investigate the longitudinal relationship between neck pain and emotional state in patients with cervical spondylosis.METHODS This prospective cohort study included 472 patients with cervical spondylosis from eight Chinese hospitals.Participants received acupuncture or medication and were followed up at baseline,and at 1,2,4,6,and 8 weeks.Neck pain and emotional distress were assessed using the Northwick Park Neck Pain Questionnaire(NPQ)and the affective subscale of the Short-Form McGill Pain Questionnaire(SF-MPQ),respectively.Group-based trajectory models and dual trajectory analysis were used to identify and correlate pain-emotion trajectories.Multivariate logistic regression identified predictors of group membership.RESULTS Three trajectory groups were identified for NPQ and SF-MPQ scores(low,medium,and high).Higher NPQ trajectory was associated with older age(OR=1.058,P<0.001)and was significantly reduced by acupuncture(OR=0.382,P<0.001).Similarly,acupuncture lowered the odds of high SF-MPQ trajectory membership(OR=0.336,P<0.001),while age increased it(OR=1.037,P<0.001).Dual-trajectory analysis revealed bidirectional associations:69.1%of patients with low NPQ had low SF-MPQ scores,and 42.6%of patients with high SF-MPQ also had high NPQ scores.Gender was a predictor for medium SF-MPQ trajectory(OR=1.629,P=0.094).Occupation and education levels differed significantly across the trajectory groups(P<0.05).CONCLUSION Over time,neck pain and emotional distress are closely associated in patients with cervical spondylosis.Acupuncture alleviates both outcomes significantly,while age is a risk factor.Integrated approaches to pain and emotional management are encouraged.
基金funded by the Key Laboratory of Cross-Domain Flight Interdisciplinary Technology,China(No.2024-KF02201)the National Natural Science Foundation of China(No.61973326)。
文摘To evaluate the heat performance of the lifting-body entry vehicle during the hypersonic gliding phase,entry flight heat tests involving the determination of the maximum peak-heat-flux entry trajectory with complex constraints are essential.A significant obstacle is the uncertainty of passage time or energy states of the maximum peak entry heat flux point and waypoints.This paper showcases an endeavour to leverage disjunctive programming and combinatorial theory for the max-max type(maximum peak-heat-flux)Entry Trajectory Optimization(ETO)problems with complex constraints such as dynamic pressure,normal load,waypoints,and no-fly zones.The concept of a"generalized waypoint"is introduced,and the maximum peak-heat-flux point is regarded as a"generalized waypoint".Through the application of propositional calculus rules,the derivation of generalized waypoints incorporating various physical quantities and magnitudes such as heat flux density,longitude,and latitude is actualized in one disjunctive normal form,enabling resolution via a unified method.Consequently,a novel method based on combinatorial prior rules is proposed,utilizing Successive Mixed-Integer Nonlinear Programming(SMINLP)to optimize various heat entry test flight trajectories.Numerical experiments are provided to show the computational accuracy,stability,and adaptability of the proposed method in solving maxmax type entry optimal control problems.
文摘Cohort studies are important epidemiological methods to investigate associations between environmental factors,individual characteristics,and disease or other health outcomes.As a paradigm of cohort studies,the Framingham Heart Study(FHS)is the longest-running cardiovascular epidemiological study,starting in 1948.
文摘In this study,it is aimed to develop a generic model which calculates the trajectory of the ejection seat from the jet aircraft,by taking into account the parameters that will affect the seat movement such as the seat’s launch speed,ejection direction,ejection angle,altitude of the aircraft,distance/height from the aircraft rudder and canopy,pilot and ejection seat weight.With the model algorithm proposed,the ejection seat trajectory model was developed on MATLAB.The ejection seat trajectory model is based on point mass trajectory mathematical model.In this study,an analytical study of the problem has been made for modeling the flight trajectory of the ejection seat after it has been ejected.Past studies were used as a basis for validation and simulation.By writing a generic MATLAB code,a user interface was developed and presented to the user as a module.This generic code that has been developed could be used for simulations by users in the future by revising it in accordance with their own job descriptions.
基金supported in part by Boeing Company and Nanjing University of Aeronautics and Astronautics(NUAA)through the Research on Decision Support Technology of Air Traffic Operation Management in Convective Weather under Project 2022-GT-129in part by the Postgraduate Research and Practice Innovation Program of NUAA(No.xcxjh20240709)。
文摘Addressing the issue that flight plans between Chinese city pairs typically rely on a single route,lacking alternative paths and posing challenges in responding to emergencies,this study employs the“quantile-inflection point method”to analyze specific deviation trajectories,determine deviation thresholds,and identify commonly used deviation paths.By combining multiple similarity metrics,including Euclidean distance,Hausdorff distance,and sector edit distance,with the density-based spatial clustering of applications with noise(DBSCAN)algorithm,the study clusters deviation trajectories to construct a multi-option trajectory set for city pairs.A case study of 23578 flight trajectories between the Guangzhou airport cluster and the Shanghai airport cluster demonstrates the effectiveness of the proposed framework.Experimental results show that sector edit distance achieves superior clustering performance compared to Euclidean and Hausdorff distances,with higher silhouette coefficients and lower Davies⁃Bouldin indices,ensuring better intra-cluster compactness and inter-cluster separation.Based on clustering results,19 representative trajectory options are identified,covering both nominal and deviation paths,which significantly enhance route diversity and reflect actual flight practices.This provides a practical basis for optimizing flight paths and scheduling,enhancing the flexibility of route selection for flights between city pairs.
