In this paper, the multi-agent systems(MASs) typically with heterogeneous unknown nonlinearities and nonidentical unknown control coefficients are studied. Although the model information of MASs is coarse, the leader-...In this paper, the multi-agent systems(MASs) typically with heterogeneous unknown nonlinearities and nonidentical unknown control coefficients are studied. Although the model information of MASs is coarse, the leader-following consensus is still pursued, with a prescribed performance and zero consensus errors. Leveraging a powerful funnel control strategy, a fully distributed and completely relative-state-dependent protocol is designed. Distinctively, the time-varying function characterizing the performance boundary is introduced, not only to construct the funnel gains but also as an indispensable part of the protocol,enhancing the control ability and enabling the consensus errors to converge to zero(rather than a residual set). Remark that when control directions are unknown, coexisting with inherent system nonlinearities, it is essential to incorporate an additional compensation mechanism while imposing a hierarchical structure of communication topology for the control design and analysis. Simulation examples are given to illustrate the effectiveness of the theoretical results.展开更多
In this paper we make use of a special procedure on the repro ducing kernel space to give an expansion theorem for the function with two unkno wns and a surface approximation formula. The error of the surface posses...In this paper we make use of a special procedure on the repro ducing kernel space to give an expansion theorem for the function with two unkno wns and a surface approximation formula. The error of the surface possesses mono tonically decreasing and uniformly convergent characteristics in the sense of t he norm on the space.展开更多
This paper investigates the challenges associated with Unmanned Aerial Vehicle (UAV) collaborative search and target tracking in dynamic and unknown environments characterized by limited field of view. The primary obj...This paper investigates the challenges associated with Unmanned Aerial Vehicle (UAV) collaborative search and target tracking in dynamic and unknown environments characterized by limited field of view. The primary objective is to explore the unknown environments to locate and track targets effectively. To address this problem, we propose a novel Multi-Agent Reinforcement Learning (MARL) method based on Graph Neural Network (GNN). Firstly, a method is introduced for encoding continuous-space multi-UAV problem data into spatial graphs which establish essential relationships among agents, obstacles, and targets. Secondly, a Graph AttenTion network (GAT) model is presented, which focuses exclusively on adjacent nodes, learns attention weights adaptively and allows agents to better process information in dynamic environments. Reward functions are specifically designed to tackle exploration challenges in environments with sparse rewards. By introducing a framework that integrates centralized training and distributed execution, the advancement of models is facilitated. Simulation results show that the proposed method outperforms the existing MARL method in search rate and tracking performance with less collisions. The experiments show that the proposed method can be extended to applications with a larger number of agents, which provides a potential solution to the challenging problem of multi-UAV autonomous tracking in dynamic unknown environments.展开更多
HONO is a critical precursor of•OH,but its sources are controversial due to its complex formation mechanism.This study conducted comprehensive observations in Zhengzhou from April 26 to May 11,2022.Low NO_(x)concentra...HONO is a critical precursor of•OH,but its sources are controversial due to its complex formation mechanism.This study conducted comprehensive observations in Zhengzhou from April 26 to May 11,2022.Low NO_(x)concentrations were observed during the Covid epidemic period(EP)(10.4±3.0 ppb),compared to the pre-epidemic period(PEP)(12.5±3.8 ppb).The mean HONO concentration during EP(0.53±0.34 ppb)was 0.09 ppb lower than that during PEP(0.62±0.53 ppb).The decrease in HONO concentration during EP came mainly at night due to the reduction in the direct emission(P_(emi))(0.03 ppb/hr),the homogeneous reaction between•OHandNO(P_(OH+NO))(0.02 ppb/hr),and the heterogeneous conversion of NO_(2)on the ground(0.01 ppb/hr).Notably,there was no significant change in daytime HONO concentration.The daytime HONO budget indicated that the primary HONO sources during PEP were the nitrate photolysis(P_(nitrate)),followed by the P_(OH+NO),Pemi,the photo-enhanced reaction of NO_(2)on the ground(P_(ground+hv))and aerosol surface(Paerosol+hv).The primary HONO sources were Pnitrate,POH+NO,P_(emi),and_(Paerosol+hv)during EP,respectively.The missing source has a high correlation with solar radiation,there might be other photo-related HONO sources or the contributions of photosensitized reactions were underestimated.In the extremely underestimated cases,HONO production rates fromthe P_(nitrate),P_(ground+hv),and Paerosol+hv increased by 0.17,0.10,and 0.10 ppb/hr during PEP,0.23,0.13,and 0.16 ppb/hr during EP,and P_(nitrate)was still the primary source during both PEP and EP.展开更多
Based on the finite difference discretization of partial differential equations, we propose a kind of semi-implicit θ-schemes of incremental unknowns type for the heat equation with time-dependent coefficients. The s...Based on the finite difference discretization of partial differential equations, we propose a kind of semi-implicit θ-schemes of incremental unknowns type for the heat equation with time-dependent coefficients. The stability of the new schemes is carefully studied. Some new types of conditions give better stability when θ is closed to 1/2 even if we have variable coefficients.展开更多
The first-ever synthesis of the unknown furo[2,3:4,5]pyrimido[1,2-b]indazole skeleton was demonstrated based on the undiscovered tetra-functionalization of enaminones,with simple substrates and reaction conditions.The...The first-ever synthesis of the unknown furo[2,3:4,5]pyrimido[1,2-b]indazole skeleton was demonstrated based on the undiscovered tetra-functionalization of enaminones,with simple substrates and reaction conditions.The key to realizing this process lies in the multiple trapping of the in situ generated ketenimine cation by the 3-aminoindazole,which results in the formation of four new chemical bonds and two new rings in one pot.Moreover,the products of this new reaction were found to exhibit aggregationinduced emission(AIE)without modification.展开更多
BACKGROUND Fever of unknown origin(FUO)remains a diagnostic challenge and was originally defined in 1961.Its classic criteria include fever≥38.3°C(≥101°F)on multiple occasions,fever lasting three weeks or ...BACKGROUND Fever of unknown origin(FUO)remains a diagnostic challenge and was originally defined in 1961.Its classic criteria include fever≥38.3°C(≥101°F)on multiple occasions,fever lasting three weeks or longer,and a diagnosis after one week of inpatient evaluation.However,these criteria may not fully encompass the varied clinical presentations seen in resource-limited settings such as India.The adaptation of FUO definitions to local healthcare contexts is crucial for enhancing diagnostic accuracy and optimizing patient outcomes.AIM To investigate the applicability of revised FUO criteria in a tertiary care setting in India.METHODS This longitudinal-exploratory study at All India Institute of Medical Sciences Rishikesh(January 2018–December 2022)analyzed 228 adult patients with fever≥99.1°F lasting over three days.Patients diagnosed within three days of admission were excluded.Data were collected retrospectively and prospectively using predefined FUO definitions based on durations of nondiagnosis(3-21 days,>21 days),temperature ranges(99.1°F-100.9°F,≥101°F),and hospitalization durations(3-7 days,>7 days).Descriptive statistics and comparative tests(Fisher's exact test,χ2 test)evaluated outcomes across definitions.RESULTS Among the proposed FUO definitions,Definition B(fever lasting 3-21 days,temperatures between 99.1°F-100.9°F,hospitalization>7 days)predominated(40.8%),while only 2.2%met the classical criteria.Notably,36.5%of Definition B patients remained undiagnosed after 7-10 days,despite 94%undergoing diagnostic workups within 21 days.Infection emerged as the leading etiology across definitions,without significant variation in outcomes or mortality during hospitalization(χ2=27.937,P=0.142).CONCLUSION Adapting FUO criteria to local contexts improves diagnostic accuracy and treatment.Definition B(40.8%prevalence)showed practical utility,with higher mortality in patients discharged on empirical'Anti-tuberculosis therapy'.展开更多
The autonomous landing guidance of fixed-wing aircraft in unknown structured scenes presents a substantial technological challenge,particularly regarding the effectiveness of solutions for monocular visual relative po...The autonomous landing guidance of fixed-wing aircraft in unknown structured scenes presents a substantial technological challenge,particularly regarding the effectiveness of solutions for monocular visual relative pose estimation.This study proposes a novel airborne monocular visual estimation method based on structured scene features to address this challenge.First,a multitask neural network model is established for segmentation,depth estimation,and slope estimation on monocular images.And a monocular image comprehensive three-dimensional information metric is designed,encompassing length,span,flatness,and slope information.Subsequently,structured edge features are leveraged to filter candidate landing regions adaptively.By leveraging the three-dimensional information metric,the optimal landing region is accurately and efficiently identified.Finally,sparse two-dimensional key point is used to parameterize the optimal landing region for the first time and a high-precision relative pose estimation is achieved.Additional measurement information is introduced to provide the autonomous landing guidance information between the aircraft and the optimal landing region.Experimental results obtained from both synthetic and real data demonstrate the effectiveness of the proposed method in monocular pose estimation for autonomous aircraft landing guidance in unknown structured scenes.展开更多
This paper discusses the design of event-triggered output-feedback controller for a class of nonlinear time-delay systems with multiple uncertainties. In sharp contrast to previous works, the considered systems posses...This paper discusses the design of event-triggered output-feedback controller for a class of nonlinear time-delay systems with multiple uncertainties. In sharp contrast to previous works, the considered systems possess two important characteristics: (i) The uncertain nonlinear terms meet the linearly unmeasurable-states dependent growth with the growth rate being an unknown function of the input and output. (ii) There exist input matching uncertainty and unknown measurement sensitivity. By introducing a single dynamic gain and employing a cleverly devised event-triggering mechanism (ETM), we design a new gain-based event-triggered output-feedback controller, which globally regulates all states of the considered systems and maintains global boundedness of the closed-loop system. Furthermore, the estimation of input matching uncertainty achieves convergence towards its actual value, and Zeno behavior does not happen. Two simulation examples including a practical one show that the proposed approach is effective.展开更多
BACKGROUND Nosocomial fever of unknown origin(nFUO)is a frequent and challenging diagnostic entity,encompassing diverse infectious and non-infectious etiologies.Timely identification is crucial,yet evidence on the dia...BACKGROUND Nosocomial fever of unknown origin(nFUO)is a frequent and challenging diagnostic entity,encompassing diverse infectious and non-infectious etiologies.Timely identification is crucial,yet evidence on the diagnostic accuracy of commonly employed sepsis screening tools and biomarkers remains sparse.We hypothesized that these tools and biomarkers measured at fever onset could distinguish infectious from non-infectious causes of nFUO in critically ill adults.AIM To evaluate the diagnostic utility of sepsis tools and biomarkers in identifying infectious causes of nFUO.METHODS This prospective observational study included patients admitted to the Acute Care Emergency Medicine Unit,Postgraduate Institute of Medical Education and Research,Chandigarh,India(July 2023 to December 2024).nFUO was defined by Durack and Street criteria.Diagnostic performance of sepsis screening tools(systemic inflammatory response syndrome,Sequential Organ Failure Assessment,quick Sequential Organ Failure Assessment,National Early Warning Score,and Modified Early Warning Score)and biomarkers[procalcitonin(PCT),C-reactive protein(CRP)]at fever onset was assessed using receiver operating characteristic curve analysis.RESULTS Of 80 cases(mean age 42.9±16.5 years;80% male),42.5% had infectious causes,38.7% non-infectious,and 18.8% remained undiagnosed.Pneumonia(26.2%)and bloodstream infections(11.2%)were the most common infectious etiologies,while central fever and thrombophlebitis(each 7.5%)were predominant among non-infectious causes.Sepsis tools showed poor diagnostic accuracy,with area under the receiver operating characteristic curve(AUC)values close to 0.5.PCT demonstrated modest performance(AUC=0.61;optimal cut-off:0.85μg/L),while CRP was paradoxically higher in non-infectious cases(AUC=0.45).Overall mortality was 20% and was highest among undiagnosed patients(33.3%).Fever duration and hospitalization length were significantly greater in infectious cases.CONCLUSION Sepsis tools,PCT,and CRP have limited utility in identifying infectious causes of nFUO in critically ill adults and should not solely guide initial decision-making.展开更多
BACKGROUND Leuconostoc garlicum is commonly found in fermented foods and very few infected patients have been reported,who typically present symptoms such as fever and fatigue.Conventional clinical examinations often ...BACKGROUND Leuconostoc garlicum is commonly found in fermented foods and very few infected patients have been reported,who typically present symptoms such as fever and fatigue.Conventional clinical examinations often struggle to identify this bacterium,and routine anti-infective treatments are generally ineffective.Both diagnostic challenges and therapeutic limitations pose significant difficulties for clinicians.CASE SUMMARY We report a patient ultimately diagnosed with Leuconostoc garlicum infection.The primary manifestations included persistent fever,cough and fatigue.These symptoms lasted for 2 months.He received anti-infective treatment at a community hospital,but this was ineffective.After inquiring about the patient's medical history and conducting a physical examination,the patient underwent laboratory tests.Complete blood count tests revealed that the patient had a high proportion of neutrophils,C-reactive protein level was 235.9 mg/L,erythrocyte sedimentation rate was 67 mm/h,respiratory pathogen testing was negative,and he was then thought to have an infectious disease.However,conventional anti-infective treatments were ineffective.After excluding infectious neurological diseases,urologic diseases and digestive problems,we ultimately focused our attention on the lungs.A lung computed tomography scan indicated pulmonary inflammation.Bronchoalveolar lavage fluid for next-generation sequencing suggested lung infection with Leuconostoc garlicum.The patient's symptoms gradually improved following treatment with piperacillin tazobactam and linezolid.During the follow-up period,the patient's temperature remained normal.CONCLUSION For patients with suspected bacterial infection and experiencing fever,conventional anti-infective treatment can be ineffective in controlling their symptoms,and an infection due to rare bacteria or drug-resistant bacteria should be considered.Next-generation sequencing enables rapid and precise identification of infection-related pathogens in febrile patients.展开更多
With the emergence of new attack techniques,traffic classifiers usually fail to maintain the expected performance in real-world network environments.In order to have sufficient generalizability to deal with unknown ma...With the emergence of new attack techniques,traffic classifiers usually fail to maintain the expected performance in real-world network environments.In order to have sufficient generalizability to deal with unknown malicious samples,they require a large number of new samples for retraining.Considering the cost of data collection and labeling,data augmentation is an ideal solution.We propose an optimized noise-based traffic data augmentation system,ONTDAS.The system uses a gradient-based searching algorithm and an improved Bayesian optimizer to obtain optimized noise.The noise is injected into the original samples for data augmentation.Then,an improved bagging algorithm is used to integrate all the base traffic classifiers trained on noised datasets.The experiments verify ONTDAS on 6 types of base classifiers and 4 publicly available datasets respectively.The results show that ONTDAS can effectively enhance the traffic classifiers’performance and significantly improve their generalizability on unknown malicious samples.The system can also alleviate dataset imbalance.Moreover,the performance of ONTDAS is significantly superior to the existing data augmentation methods mentioned.展开更多
Hydraulic-electric systems are widely utilized in various applications.However,over time,these systems may encounter random faults such as loose cables,ambient environmental noise,or sensor aging,leading to inaccurate...Hydraulic-electric systems are widely utilized in various applications.However,over time,these systems may encounter random faults such as loose cables,ambient environmental noise,or sensor aging,leading to inaccurate sensor readings.These faults may result in system instability or compromise safety.In this paper,we propose a fault compensation control system to mitigate the effects of sensor faults and ensure system safety.Specifically,we utilize the pressure sensor within the system to implement the control process and evaluate performance based on the piston position.First,we develop a mathematical model to identify optimal parameters for the fault estimation model based on the Lyapunov stability principle.Next,we design an unknown input observer that estimates the state vector and detects pressure sensor faults using a linear matrix inequality optimization algorithm.The estimated pressure faults are incorporated into the fault compensation control system to counteract their effects via a fault residual coefficient.The discrepancy between the feedback state and the estimated state determines this coefficient.We assess the piston position’s performance through pressure control to evaluate the proposed model’s effectiveness.Finally,the system simulation results are analyzed to validate the efficiency of the proposed model.When a pressure sensor fault occurs,the proposed approach effectively minimizes position control errors,enhancing overall system stability.When a pressure sensor fault occurs,the proposed model compensates for the fault to mitigate the impact of pressure problem,thereby enhancing the position control quality of the EHA system.The fault compensation method ensures over 90%system performance,with its effectiveness becoming more evident under pressure sensor faults.展开更多
This paper studies motor joint control of a 4-degree-of-freedom(DoF)robotic manipulator using learning-based Adaptive Dynamic Programming(ADP)approach.The manipulator’s dynamics are modelled as an open-loop 4-link se...This paper studies motor joint control of a 4-degree-of-freedom(DoF)robotic manipulator using learning-based Adaptive Dynamic Programming(ADP)approach.The manipulator’s dynamics are modelled as an open-loop 4-link serial kinematic chain with 4 Degrees of Freedom(DoF).Decentralised optimal controllers are designed for each link using ADP approach based on a set of cost matrices and data collected from exploration trajectories.The proposed control strategy employs an off-line,off-policy iterative approach to derive four optimal control policies,one for each joint,under exploration strategies.The objective of the controller is to control the position of each joint.Simulation and experimental results show that four independent optimal controllers are found,each under similar exploration strategies,and the proposed ADP approach successfully yields optimal linear control policies despite the presence of these complexities.The experimental results conducted on the Quanser Qarm robotic platform demonstrate the effectiveness of the proposed ADP controllers in handling significant dynamic nonlinearities,such as actuation limitations,output saturation,and filter delays.展开更多
A spontaneous splenic rupture is one of the rarest encounters in our field. It is a potentially fatal condition if not diagnosed early and treated promptly. Moreover, several preexisting diseases contribute to the occ...A spontaneous splenic rupture is one of the rarest encounters in our field. It is a potentially fatal condition if not diagnosed early and treated promptly. Moreover, several preexisting diseases contribute to the occurrence of spontaneous splenic rupture, which includes hematological disease, infectious, malignancy, and immune-compromised disease. In our case, we report a 37-year-old male with a known case of diabetes mellitus who presented with generalized abdominal pain and was diagnosed with spontaneous splenic rupture. He was treated with splenic artery embolization and discharged with a good outcome. Despite the rarity of the disease, it is important to keep it in mind when a patient presents to you with abdominal pain.展开更多
There are all kinds of unknown and known signals in the actual electromagnetic environment,which hinders the development of practical cognitive radio applications.However,most existing signal recognition models are di...There are all kinds of unknown and known signals in the actual electromagnetic environment,which hinders the development of practical cognitive radio applications.However,most existing signal recognition models are difficult to discover unknown signals while recognizing known ones.In this paper,a compact manifold mixup feature-based open-set recognition approach(OR-CMMF)is proposed to address the above problem.First,the proposed approach utilizes the center loss to constrain decision boundaries so that it obtains the compact latent signal feature representations and extends the low-confidence feature space.Second,the latent signal feature representations are used to construct synthetic representations as substitutes for unknown categories of signals.Then,these constructed representations can occupy the extended low-confidence space.Finally,the proposed approach applies the distillation loss to adjust the decision boundaries between the known categories signals and the constructed unknown categories substitutes so that it accurately discovers unknown signals.The OR-CMMF approach outperformed other state-of-the-art open-set recognition methods in comprehensive recognition performance and running time,as demonstrated by simulation experiments on two public datasets RML2016.10a and ORACLE.展开更多
This paper introduces a novel chattering-free terminal sliding mode control(SMC)strategy to address chaotic behavior in permanent magnet synchronous generators(PMSG)for offshore wind turbine systems.By integrating an ...This paper introduces a novel chattering-free terminal sliding mode control(SMC)strategy to address chaotic behavior in permanent magnet synchronous generators(PMSG)for offshore wind turbine systems.By integrating an adaptive exponential reaching law with a continuous barrier function,the proposed approach eliminates chattering and ensures robust performance under model uncertainties.The methodology combines adaptive SMC with dynamic switching to estimate and compensates for unknown uncertainties,providing smooth and stable control.Finally,the performance and effectiveness of the proposed approach are compared with those of a previous study.展开更多
This paper investigates the problem of dynamic event-triggered control for a class of large-scale nonlinear systems.In particular,both neutral delays and unknown backlash-like hysteresis are considered.This requires t...This paper investigates the problem of dynamic event-triggered control for a class of large-scale nonlinear systems.In particular,both neutral delays and unknown backlash-like hysteresis are considered.This requires to integrate a compensation mechanism into the event-triggered control architecture.To this end,dynamic gain and adaptive control techniques are introduced to address the effects of neutral delays,unknown hysteresis and parameter uncertainties simultaneously.By introducing a non-negative internal dynamic variable,a dynamic event-triggered controller is designed using the hyperbolic tangent function to reduce the communication burden.By means of the Lyapunov–Krasovskii method,it is demonstrated that all signals of the closed-loop system are globally bounded and eventually converge to a tunable bounded region.Moreover,the Zeno behavior is avoided.Finally,a simulation example is presented to verify the validity of the control scheme.展开更多
Over the past few decades, numerous adaptive Kalman filters(AKFs) have been proposed. However, achieving online estimation with both high estimation accuracy and fast convergence speed is challenging, especially when ...Over the past few decades, numerous adaptive Kalman filters(AKFs) have been proposed. However, achieving online estimation with both high estimation accuracy and fast convergence speed is challenging, especially when both the process noise and measurement noise covariance matrices are relatively inaccurate. Maximum likelihood estimation(MLE) possesses the potential to achieve this goal, since its theoretical accuracy is guaranteed by asymptotic optimality and the convergence speed is fast due to weak dependence on accurate state estimation.Unfortunately, the maximum likelihood cost function is so intricate that the existing MLE methods can only simply ignore all historical measurement information to achieve online estimation,which cannot adequately realize the potential of MLE. In order to design online MLE-based AKFs with high estimation accuracy and fast convergence speed, an online exploratory MLE approach is proposed, based on which a mini-batch coordinate descent noise covariance matrix estimation framework is developed. In this framework, the maximum likelihood cost function is simplified for online estimation with fewer and simpler terms which are selected in a mini-batch and calculated with a backtracking method. This maximum likelihood cost function is sidestepped and solved by exploring possible estimated noise covariance matrices adaptively while the historical measurement information is adequately utilized. Furthermore, four specific algorithms are derived under this framework to meet different practical requirements in terms of convergence speed, estimation accuracy,and calculation load. Abundant simulations and experiments are carried out to verify the validity and superiority of the proposed algorithms as compared with existing state-of-the-art AKFs.展开更多
Enhancing the stability and performance of practical control systems in the presence of nonlinearity,time delay,and uncertainty remains a significant challenge.Particularly,a class of strict-feedback nonlinear uncerta...Enhancing the stability and performance of practical control systems in the presence of nonlinearity,time delay,and uncertainty remains a significant challenge.Particularly,a class of strict-feedback nonlinear uncertain systems characterized by unknown control directions and time-varying input delay lacks comprehensive solutions.In this paper,we propose an observerbased adaptive tracking controller to address this gap.Neural networks are utilized to handle uncertainty,and a unique coordinate transformation is employed to untangle the coupling between input delay and unknown control directions.Subsequently,a new auxiliary signal counters the impact of time-varying input delay,while a Nussbaum function is introduced to solve the problem of unknown control directions.The leverage of an advanced dynamic surface control technique avoids the“complexity explosion”and reduces boundary layer errors.Synthesizing these techniques ensures that all the closed-loop signals are semi-globally uniformly ultimately bounded(SGUUB),and the tracking error converges to a small region around the origin by selecting suitable parameters.Simulation examples are provided to demonstrate the feasibility of the proposed approach.展开更多
基金supported in part by the National Natural Science Foundation of China(61821004,62033007)Major Fundamental Research Program of Shandong Province(ZR2023ZD37)
文摘In this paper, the multi-agent systems(MASs) typically with heterogeneous unknown nonlinearities and nonidentical unknown control coefficients are studied. Although the model information of MASs is coarse, the leader-following consensus is still pursued, with a prescribed performance and zero consensus errors. Leveraging a powerful funnel control strategy, a fully distributed and completely relative-state-dependent protocol is designed. Distinctively, the time-varying function characterizing the performance boundary is introduced, not only to construct the funnel gains but also as an indispensable part of the protocol,enhancing the control ability and enabling the consensus errors to converge to zero(rather than a residual set). Remark that when control directions are unknown, coexisting with inherent system nonlinearities, it is essential to incorporate an additional compensation mechanism while imposing a hierarchical structure of communication topology for the control design and analysis. Simulation examples are given to illustrate the effectiveness of the theoretical results.
文摘In this paper we make use of a special procedure on the repro ducing kernel space to give an expansion theorem for the function with two unkno wns and a surface approximation formula. The error of the surface possesses mono tonically decreasing and uniformly convergent characteristics in the sense of t he norm on the space.
基金supported by the National Natural Science Foundation of China(Nos.12272104,U22B2013).
文摘This paper investigates the challenges associated with Unmanned Aerial Vehicle (UAV) collaborative search and target tracking in dynamic and unknown environments characterized by limited field of view. The primary objective is to explore the unknown environments to locate and track targets effectively. To address this problem, we propose a novel Multi-Agent Reinforcement Learning (MARL) method based on Graph Neural Network (GNN). Firstly, a method is introduced for encoding continuous-space multi-UAV problem data into spatial graphs which establish essential relationships among agents, obstacles, and targets. Secondly, a Graph AttenTion network (GAT) model is presented, which focuses exclusively on adjacent nodes, learns attention weights adaptively and allows agents to better process information in dynamic environments. Reward functions are specifically designed to tackle exploration challenges in environments with sparse rewards. By introducing a framework that integrates centralized training and distributed execution, the advancement of models is facilitated. Simulation results show that the proposed method outperforms the existing MARL method in search rate and tracking performance with less collisions. The experiments show that the proposed method can be extended to applications with a larger number of agents, which provides a potential solution to the challenging problem of multi-UAV autonomous tracking in dynamic unknown environments.
基金supported by China Postdoctoral Science Foundation(2023M733220)Zhengzhou PM_(2.5)and O_(3)Collaborative Control and Monitoring Project(20220347A)the National Key Research and Development Program of China(No.2017YFC0212403).
文摘HONO is a critical precursor of•OH,but its sources are controversial due to its complex formation mechanism.This study conducted comprehensive observations in Zhengzhou from April 26 to May 11,2022.Low NO_(x)concentrations were observed during the Covid epidemic period(EP)(10.4±3.0 ppb),compared to the pre-epidemic period(PEP)(12.5±3.8 ppb).The mean HONO concentration during EP(0.53±0.34 ppb)was 0.09 ppb lower than that during PEP(0.62±0.53 ppb).The decrease in HONO concentration during EP came mainly at night due to the reduction in the direct emission(P_(emi))(0.03 ppb/hr),the homogeneous reaction between•OHandNO(P_(OH+NO))(0.02 ppb/hr),and the heterogeneous conversion of NO_(2)on the ground(0.01 ppb/hr).Notably,there was no significant change in daytime HONO concentration.The daytime HONO budget indicated that the primary HONO sources during PEP were the nitrate photolysis(P_(nitrate)),followed by the P_(OH+NO),Pemi,the photo-enhanced reaction of NO_(2)on the ground(P_(ground+hv))and aerosol surface(Paerosol+hv).The primary HONO sources were Pnitrate,POH+NO,P_(emi),and_(Paerosol+hv)during EP,respectively.The missing source has a high correlation with solar radiation,there might be other photo-related HONO sources or the contributions of photosensitized reactions were underestimated.In the extremely underestimated cases,HONO production rates fromthe P_(nitrate),P_(ground+hv),and Paerosol+hv increased by 0.17,0.10,and 0.10 ppb/hr during PEP,0.23,0.13,and 0.16 ppb/hr during EP,and P_(nitrate)was still the primary source during both PEP and EP.
基金This project is partially supported by Natural Science Foundation of Gansu Province under Grant 3ZS041-A25-011 by National Natural Science Foundation under Grant 10471056.
文摘Based on the finite difference discretization of partial differential equations, we propose a kind of semi-implicit θ-schemes of incremental unknowns type for the heat equation with time-dependent coefficients. The stability of the new schemes is carefully studied. Some new types of conditions give better stability when θ is closed to 1/2 even if we have variable coefficients.
基金supported by the National Natural Science Foundation of China(Nos.21971080,22171098)supported by Chengdu Guibao Science&Technology Co.,Ltd.This work was also supported by the 111 Project(No.B17019)。
文摘The first-ever synthesis of the unknown furo[2,3:4,5]pyrimido[1,2-b]indazole skeleton was demonstrated based on the undiscovered tetra-functionalization of enaminones,with simple substrates and reaction conditions.The key to realizing this process lies in the multiple trapping of the in situ generated ketenimine cation by the 3-aminoindazole,which results in the formation of four new chemical bonds and two new rings in one pot.Moreover,the products of this new reaction were found to exhibit aggregationinduced emission(AIE)without modification.
文摘BACKGROUND Fever of unknown origin(FUO)remains a diagnostic challenge and was originally defined in 1961.Its classic criteria include fever≥38.3°C(≥101°F)on multiple occasions,fever lasting three weeks or longer,and a diagnosis after one week of inpatient evaluation.However,these criteria may not fully encompass the varied clinical presentations seen in resource-limited settings such as India.The adaptation of FUO definitions to local healthcare contexts is crucial for enhancing diagnostic accuracy and optimizing patient outcomes.AIM To investigate the applicability of revised FUO criteria in a tertiary care setting in India.METHODS This longitudinal-exploratory study at All India Institute of Medical Sciences Rishikesh(January 2018–December 2022)analyzed 228 adult patients with fever≥99.1°F lasting over three days.Patients diagnosed within three days of admission were excluded.Data were collected retrospectively and prospectively using predefined FUO definitions based on durations of nondiagnosis(3-21 days,>21 days),temperature ranges(99.1°F-100.9°F,≥101°F),and hospitalization durations(3-7 days,>7 days).Descriptive statistics and comparative tests(Fisher's exact test,χ2 test)evaluated outcomes across definitions.RESULTS Among the proposed FUO definitions,Definition B(fever lasting 3-21 days,temperatures between 99.1°F-100.9°F,hospitalization>7 days)predominated(40.8%),while only 2.2%met the classical criteria.Notably,36.5%of Definition B patients remained undiagnosed after 7-10 days,despite 94%undergoing diagnostic workups within 21 days.Infection emerged as the leading etiology across definitions,without significant variation in outcomes or mortality during hospitalization(χ2=27.937,P=0.142).CONCLUSION Adapting FUO criteria to local contexts improves diagnostic accuracy and treatment.Definition B(40.8%prevalence)showed practical utility,with higher mortality in patients discharged on empirical'Anti-tuberculosis therapy'.
基金co-supported by the Science and Technology Innovation Program of Hunan Province,China(No.2023RC3023)the National Natural Science Foundation of China(No.12272404)。
文摘The autonomous landing guidance of fixed-wing aircraft in unknown structured scenes presents a substantial technological challenge,particularly regarding the effectiveness of solutions for monocular visual relative pose estimation.This study proposes a novel airborne monocular visual estimation method based on structured scene features to address this challenge.First,a multitask neural network model is established for segmentation,depth estimation,and slope estimation on monocular images.And a monocular image comprehensive three-dimensional information metric is designed,encompassing length,span,flatness,and slope information.Subsequently,structured edge features are leveraged to filter candidate landing regions adaptively.By leveraging the three-dimensional information metric,the optimal landing region is accurately and efficiently identified.Finally,sparse two-dimensional key point is used to parameterize the optimal landing region for the first time and a high-precision relative pose estimation is achieved.Additional measurement information is introduced to provide the autonomous landing guidance information between the aircraft and the optimal landing region.Experimental results obtained from both synthetic and real data demonstrate the effectiveness of the proposed method in monocular pose estimation for autonomous aircraft landing guidance in unknown structured scenes.
基金supported by the fund of Beijing Municipal Commission of Education(KM202210017001 and 22019821001)the Natural Science Foundation of Henan Province(222300420253).
文摘This paper discusses the design of event-triggered output-feedback controller for a class of nonlinear time-delay systems with multiple uncertainties. In sharp contrast to previous works, the considered systems possess two important characteristics: (i) The uncertain nonlinear terms meet the linearly unmeasurable-states dependent growth with the growth rate being an unknown function of the input and output. (ii) There exist input matching uncertainty and unknown measurement sensitivity. By introducing a single dynamic gain and employing a cleverly devised event-triggering mechanism (ETM), we design a new gain-based event-triggered output-feedback controller, which globally regulates all states of the considered systems and maintains global boundedness of the closed-loop system. Furthermore, the estimation of input matching uncertainty achieves convergence towards its actual value, and Zeno behavior does not happen. Two simulation examples including a practical one show that the proposed approach is effective.
文摘BACKGROUND Nosocomial fever of unknown origin(nFUO)is a frequent and challenging diagnostic entity,encompassing diverse infectious and non-infectious etiologies.Timely identification is crucial,yet evidence on the diagnostic accuracy of commonly employed sepsis screening tools and biomarkers remains sparse.We hypothesized that these tools and biomarkers measured at fever onset could distinguish infectious from non-infectious causes of nFUO in critically ill adults.AIM To evaluate the diagnostic utility of sepsis tools and biomarkers in identifying infectious causes of nFUO.METHODS This prospective observational study included patients admitted to the Acute Care Emergency Medicine Unit,Postgraduate Institute of Medical Education and Research,Chandigarh,India(July 2023 to December 2024).nFUO was defined by Durack and Street criteria.Diagnostic performance of sepsis screening tools(systemic inflammatory response syndrome,Sequential Organ Failure Assessment,quick Sequential Organ Failure Assessment,National Early Warning Score,and Modified Early Warning Score)and biomarkers[procalcitonin(PCT),C-reactive protein(CRP)]at fever onset was assessed using receiver operating characteristic curve analysis.RESULTS Of 80 cases(mean age 42.9±16.5 years;80% male),42.5% had infectious causes,38.7% non-infectious,and 18.8% remained undiagnosed.Pneumonia(26.2%)and bloodstream infections(11.2%)were the most common infectious etiologies,while central fever and thrombophlebitis(each 7.5%)were predominant among non-infectious causes.Sepsis tools showed poor diagnostic accuracy,with area under the receiver operating characteristic curve(AUC)values close to 0.5.PCT demonstrated modest performance(AUC=0.61;optimal cut-off:0.85μg/L),while CRP was paradoxically higher in non-infectious cases(AUC=0.45).Overall mortality was 20% and was highest among undiagnosed patients(33.3%).Fever duration and hospitalization length were significantly greater in infectious cases.CONCLUSION Sepsis tools,PCT,and CRP have limited utility in identifying infectious causes of nFUO in critically ill adults and should not solely guide initial decision-making.
文摘BACKGROUND Leuconostoc garlicum is commonly found in fermented foods and very few infected patients have been reported,who typically present symptoms such as fever and fatigue.Conventional clinical examinations often struggle to identify this bacterium,and routine anti-infective treatments are generally ineffective.Both diagnostic challenges and therapeutic limitations pose significant difficulties for clinicians.CASE SUMMARY We report a patient ultimately diagnosed with Leuconostoc garlicum infection.The primary manifestations included persistent fever,cough and fatigue.These symptoms lasted for 2 months.He received anti-infective treatment at a community hospital,but this was ineffective.After inquiring about the patient's medical history and conducting a physical examination,the patient underwent laboratory tests.Complete blood count tests revealed that the patient had a high proportion of neutrophils,C-reactive protein level was 235.9 mg/L,erythrocyte sedimentation rate was 67 mm/h,respiratory pathogen testing was negative,and he was then thought to have an infectious disease.However,conventional anti-infective treatments were ineffective.After excluding infectious neurological diseases,urologic diseases and digestive problems,we ultimately focused our attention on the lungs.A lung computed tomography scan indicated pulmonary inflammation.Bronchoalveolar lavage fluid for next-generation sequencing suggested lung infection with Leuconostoc garlicum.The patient's symptoms gradually improved following treatment with piperacillin tazobactam and linezolid.During the follow-up period,the patient's temperature remained normal.CONCLUSION For patients with suspected bacterial infection and experiencing fever,conventional anti-infective treatment can be ineffective in controlling their symptoms,and an infection due to rare bacteria or drug-resistant bacteria should be considered.Next-generation sequencing enables rapid and precise identification of infection-related pathogens in febrile patients.
基金supported in part by the National Key Research and Development Program of China(No.2022YFB4500800)the National Science Foundation of China(No.42071431).
文摘With the emergence of new attack techniques,traffic classifiers usually fail to maintain the expected performance in real-world network environments.In order to have sufficient generalizability to deal with unknown malicious samples,they require a large number of new samples for retraining.Considering the cost of data collection and labeling,data augmentation is an ideal solution.We propose an optimized noise-based traffic data augmentation system,ONTDAS.The system uses a gradient-based searching algorithm and an improved Bayesian optimizer to obtain optimized noise.The noise is injected into the original samples for data augmentation.Then,an improved bagging algorithm is used to integrate all the base traffic classifiers trained on noised datasets.The experiments verify ONTDAS on 6 types of base classifiers and 4 publicly available datasets respectively.The results show that ONTDAS can effectively enhance the traffic classifiers’performance and significantly improve their generalizability on unknown malicious samples.The system can also alleviate dataset imbalance.Moreover,the performance of ONTDAS is significantly superior to the existing data augmentation methods mentioned.
基金supported by Nguyen Tat Thanh University,Ho Chi Minh City,Vietnam,provided with the facilities required to carry out this work.
文摘Hydraulic-electric systems are widely utilized in various applications.However,over time,these systems may encounter random faults such as loose cables,ambient environmental noise,or sensor aging,leading to inaccurate sensor readings.These faults may result in system instability or compromise safety.In this paper,we propose a fault compensation control system to mitigate the effects of sensor faults and ensure system safety.Specifically,we utilize the pressure sensor within the system to implement the control process and evaluate performance based on the piston position.First,we develop a mathematical model to identify optimal parameters for the fault estimation model based on the Lyapunov stability principle.Next,we design an unknown input observer that estimates the state vector and detects pressure sensor faults using a linear matrix inequality optimization algorithm.The estimated pressure faults are incorporated into the fault compensation control system to counteract their effects via a fault residual coefficient.The discrepancy between the feedback state and the estimated state determines this coefficient.We assess the piston position’s performance through pressure control to evaluate the proposed model’s effectiveness.Finally,the system simulation results are analyzed to validate the efficiency of the proposed model.When a pressure sensor fault occurs,the proposed approach effectively minimizes position control errors,enhancing overall system stability.When a pressure sensor fault occurs,the proposed model compensates for the fault to mitigate the impact of pressure problem,thereby enhancing the position control quality of the EHA system.The fault compensation method ensures over 90%system performance,with its effectiveness becoming more evident under pressure sensor faults.
基金supported by the DEEPCOBOT project under Grant 306640/O70 funded by the Research Council of Norway.
文摘This paper studies motor joint control of a 4-degree-of-freedom(DoF)robotic manipulator using learning-based Adaptive Dynamic Programming(ADP)approach.The manipulator’s dynamics are modelled as an open-loop 4-link serial kinematic chain with 4 Degrees of Freedom(DoF).Decentralised optimal controllers are designed for each link using ADP approach based on a set of cost matrices and data collected from exploration trajectories.The proposed control strategy employs an off-line,off-policy iterative approach to derive four optimal control policies,one for each joint,under exploration strategies.The objective of the controller is to control the position of each joint.Simulation and experimental results show that four independent optimal controllers are found,each under similar exploration strategies,and the proposed ADP approach successfully yields optimal linear control policies despite the presence of these complexities.The experimental results conducted on the Quanser Qarm robotic platform demonstrate the effectiveness of the proposed ADP controllers in handling significant dynamic nonlinearities,such as actuation limitations,output saturation,and filter delays.
文摘A spontaneous splenic rupture is one of the rarest encounters in our field. It is a potentially fatal condition if not diagnosed early and treated promptly. Moreover, several preexisting diseases contribute to the occurrence of spontaneous splenic rupture, which includes hematological disease, infectious, malignancy, and immune-compromised disease. In our case, we report a 37-year-old male with a known case of diabetes mellitus who presented with generalized abdominal pain and was diagnosed with spontaneous splenic rupture. He was treated with splenic artery embolization and discharged with a good outcome. Despite the rarity of the disease, it is important to keep it in mind when a patient presents to you with abdominal pain.
基金fully supported by National Natural Science Foundation of China(61871422)Natural Science Foundation of Sichuan Province(2023NSFSC1422)Central Universities of South west Minzu University(ZYN2022032)。
文摘There are all kinds of unknown and known signals in the actual electromagnetic environment,which hinders the development of practical cognitive radio applications.However,most existing signal recognition models are difficult to discover unknown signals while recognizing known ones.In this paper,a compact manifold mixup feature-based open-set recognition approach(OR-CMMF)is proposed to address the above problem.First,the proposed approach utilizes the center loss to constrain decision boundaries so that it obtains the compact latent signal feature representations and extends the low-confidence feature space.Second,the latent signal feature representations are used to construct synthetic representations as substitutes for unknown categories of signals.Then,these constructed representations can occupy the extended low-confidence space.Finally,the proposed approach applies the distillation loss to adjust the decision boundaries between the known categories signals and the constructed unknown categories substitutes so that it accurately discovers unknown signals.The OR-CMMF approach outperformed other state-of-the-art open-set recognition methods in comprehensive recognition performance and running time,as demonstrated by simulation experiments on two public datasets RML2016.10a and ORACLE.
文摘This paper introduces a novel chattering-free terminal sliding mode control(SMC)strategy to address chaotic behavior in permanent magnet synchronous generators(PMSG)for offshore wind turbine systems.By integrating an adaptive exponential reaching law with a continuous barrier function,the proposed approach eliminates chattering and ensures robust performance under model uncertainties.The methodology combines adaptive SMC with dynamic switching to estimate and compensates for unknown uncertainties,providing smooth and stable control.Finally,the performance and effectiveness of the proposed approach are compared with those of a previous study.
基金supported by the National Natural Science Foundation of China under Grant 62073190the Science Center Program of National Natural Science Foundation of China under Grant 62188101.
文摘This paper investigates the problem of dynamic event-triggered control for a class of large-scale nonlinear systems.In particular,both neutral delays and unknown backlash-like hysteresis are considered.This requires to integrate a compensation mechanism into the event-triggered control architecture.To this end,dynamic gain and adaptive control techniques are introduced to address the effects of neutral delays,unknown hysteresis and parameter uncertainties simultaneously.By introducing a non-negative internal dynamic variable,a dynamic event-triggered controller is designed using the hyperbolic tangent function to reduce the communication burden.By means of the Lyapunov–Krasovskii method,it is demonstrated that all signals of the closed-loop system are globally bounded and eventually converge to a tunable bounded region.Moreover,the Zeno behavior is avoided.Finally,a simulation example is presented to verify the validity of the control scheme.
基金supported in part by the National Key Research and Development Program of China(2023YFB3906403)the National Natural Science Foundation of China(62373118,62173105)the Natural Science Foundation of Heilongjiang Province of China(ZD2023F002)
文摘Over the past few decades, numerous adaptive Kalman filters(AKFs) have been proposed. However, achieving online estimation with both high estimation accuracy and fast convergence speed is challenging, especially when both the process noise and measurement noise covariance matrices are relatively inaccurate. Maximum likelihood estimation(MLE) possesses the potential to achieve this goal, since its theoretical accuracy is guaranteed by asymptotic optimality and the convergence speed is fast due to weak dependence on accurate state estimation.Unfortunately, the maximum likelihood cost function is so intricate that the existing MLE methods can only simply ignore all historical measurement information to achieve online estimation,which cannot adequately realize the potential of MLE. In order to design online MLE-based AKFs with high estimation accuracy and fast convergence speed, an online exploratory MLE approach is proposed, based on which a mini-batch coordinate descent noise covariance matrix estimation framework is developed. In this framework, the maximum likelihood cost function is simplified for online estimation with fewer and simpler terms which are selected in a mini-batch and calculated with a backtracking method. This maximum likelihood cost function is sidestepped and solved by exploring possible estimated noise covariance matrices adaptively while the historical measurement information is adequately utilized. Furthermore, four specific algorithms are derived under this framework to meet different practical requirements in terms of convergence speed, estimation accuracy,and calculation load. Abundant simulations and experiments are carried out to verify the validity and superiority of the proposed algorithms as compared with existing state-of-the-art AKFs.
基金National Natural Science Foundation of China(62373102)Jiangsu Natural Science Foundation(BK20221455)Anhui Provincial Key Research and Development Project(2022i01020013)。
文摘Enhancing the stability and performance of practical control systems in the presence of nonlinearity,time delay,and uncertainty remains a significant challenge.Particularly,a class of strict-feedback nonlinear uncertain systems characterized by unknown control directions and time-varying input delay lacks comprehensive solutions.In this paper,we propose an observerbased adaptive tracking controller to address this gap.Neural networks are utilized to handle uncertainty,and a unique coordinate transformation is employed to untangle the coupling between input delay and unknown control directions.Subsequently,a new auxiliary signal counters the impact of time-varying input delay,while a Nussbaum function is introduced to solve the problem of unknown control directions.The leverage of an advanced dynamic surface control technique avoids the“complexity explosion”and reduces boundary layer errors.Synthesizing these techniques ensures that all the closed-loop signals are semi-globally uniformly ultimately bounded(SGUUB),and the tracking error converges to a small region around the origin by selecting suitable parameters.Simulation examples are provided to demonstrate the feasibility of the proposed approach.
