In the context of global energy transition,traditional energy companies are confronting multiple pressures,including resource depletion,intensifying market competition,and elevated ESG standards,necessitating an urgen...In the context of global energy transition,traditional energy companies are confronting multiple pressures,including resource depletion,intensifying market competition,and elevated ESG standards,necessitating an urgent shift from the fossil fuel-centered“first curve”to a“second curve”characterized by renewable energy,digitalization,and green technologies.Drawing on second curve theory,dynamic capabilities theory,and ambidextrous innovation theory.展开更多
The Titanic sunk 113 years ago on April 14-15,after hitting an iceberg,with human error likely causing the ship to wander into those dangerous waters.Today,autonomous systems built on AI can help ships avoid such acci...The Titanic sunk 113 years ago on April 14-15,after hitting an iceberg,with human error likely causing the ship to wander into those dangerous waters.Today,autonomous systems built on AI can help ships avoid such accidents.But could such a system explain to the captain why it was controlling the ship in a certain way?展开更多
The impact of location services on people’s lives has grown significantly in the era of widespread smart device usage.Due to global navigation satellite system(GNSS)signal rejection,weak signal strength in indoor env...The impact of location services on people’s lives has grown significantly in the era of widespread smart device usage.Due to global navigation satellite system(GNSS)signal rejection,weak signal strength in indoor environments and radio signal interference caused by multiwall environments,which collectively lead to significant positioning errors,vision-based positioning has emerged as a crucial method in indoor positioning research.This paper introduces a scale hierarchical matching model to tackle challenges associated with large visual databases and high scene similarity,both of which will compromise matching accuracy and lead to prolonged positioning delays.The proposed model establishes an image feature database using GIST features and speeded up robust feature(SURF)in the offline stage.In the online stage,a positioning navigating algorithm is constructed based on Dijkstra’s path planning.Additionally,a corresponding Android application has been developed to facilitate visual positioning and navigation in indoor environments.Experimental results obtained in real indoor environments demonstrate that the proposed method significantly enhances positioning accuracy compared with similar algorithms,while effectively reducing time overhead.This improvement caters to the requirements for indoor positioning and navigation,thereby meeting user needs.展开更多
Today,autonomous mobile robots are widely used in all walks of life.Autonomous navigation,as a basic capability of robots,has become a research hotspot.Classical navigation techniques,which rely on pre-built maps,stru...Today,autonomous mobile robots are widely used in all walks of life.Autonomous navigation,as a basic capability of robots,has become a research hotspot.Classical navigation techniques,which rely on pre-built maps,struggle to cope with complex and dynamic environments.With the development of artificial intelligence,learning-based navigation technology have emerged.Instead of relying on pre-built maps,the agent perceives the environment and make decisions through visual observation,enabling end-to-end navigation.A key challenge is to enhance the generalization ability of the agent in unfamiliar environments.To tackle this challenge,it is necessary to endow the agent with spatial intelligence.Spatial intelligence refers to the ability of the agent to transform visual observations into insights,in-sights into understanding,and understanding into actions.To endow the agent with spatial intelligence,relevant research uses scene graph to represent the environment.We refer to this method as scene graph-based object goal navigation.In this paper,we concentrate on scene graph,offering formal description,computational framework of object goal navigation.We provide a comprehensive summary of the meth-ods for constructing and applying scene graph.Additionally,we present experimental evidence that highlights the critical role of scene graph in improving navigation success.This paper also delineates promising research directions,all aimed at sharpening the focus on scene graph.Overall,this paper shows how scene graph endows the agent with spatial intelligence,aiming to promote the importance of scene graph in the field of intelligent navigation.展开更多
The dynamic behavior of high-speed craft navigating through variable sea states plays a pivotal role in ensuring maritime safety.However,many existing simulation approaches rely on linear or overly simplified represen...The dynamic behavior of high-speed craft navigating through variable sea states plays a pivotal role in ensuring maritime safety.However,many existing simulation approaches rely on linear or overly simplified representations of the marine environment,thereby limiting the fidelity of motion predictions.This study explores the motion characteristics of a 4.5-t high-speed vessel by conducting fully coupled numerical simulations using the STAR-CCM+software.The analysis considers both calm and varying sea conditions,incorporating fluctuations in wave height,wavelength,and wind speed to reflect more realistic operating scenarios.Simulation results reveal that the vessel’s hydrodynamic response is highly sensitive to changes in sea state.As conditions deteriorate,the free surface becomes increasingly complex,with higher wave amplitudes and more pronounced interactions between the waves generated by the vessel and those imposed by the external environment.These effects lead to significant increases in roll,pitch,heave,and sway motions,thereby imposing greater demands on the vessel’s dynamic stability and operational safety.Furthermore,both hydrodynamic resistance and propulsive thrust exhibit notable dependence on sea state and vessel speed.Total resistance generally increases with rougher sea conditions,while thrust tends to rise with increasing forward speed.Under calm or mildly disturbed waters,a Froude number(Fr)of 0.5 appears to offer an optimal balance for initiating and controlling primary motions such as roll,pitch,heave,and sway.Conversely,in more challenging conditions-such as those represented by a Sea State 3-effective motion control is better achieved at a higher Froude number of approximately 1.0.展开更多
This paper introduces a new control strategy for heterogeneous multi-robots systems dedicated to industrial logistic setups. This control strategy is based on both distributed intelligence and machine learning and inv...This paper introduces a new control strategy for heterogeneous multi-robots systems dedicated to industrial logistic setups. This control strategy is based on both distributed intelligence and machine learning and involves three parts: the rigid formation controller, the perception system and the path planner. Our controller is event-based and thus its control-coordination strategy can be self-adaptive and applied to real dynamic environment. During the navigating process, the multi-robots system derives the environment model, performs the path planning process that guaranties both the transportation constraints and the obstacle avoidance. For the validation, both simulation and real robot experiments are performed. The results show that the developed control strategy can be well used for realistic logistics applications.展开更多
SEVEN years after the outbreak of the global financial crisis in 2008, the global economy is not yet quite out of the woods and, overall, recovery remains sluggish and not sufficiently robust. As the second largest ec...SEVEN years after the outbreak of the global financial crisis in 2008, the global economy is not yet quite out of the woods and, overall, recovery remains sluggish and not sufficiently robust. As the second largest economy in the world. China has also bidden a farewell to seemingly miraculous runaway economic expansion and seen its growth pace level offat 7 percent in the first half of this year, arousing extensive concerns over its long-term economic outlook.展开更多
Facing uncertainty in the global financiallandscape,the Annual Conference of Financial Street Forum 2025,running in Beijing from October 27 to 30,took on the theme Global Financial Development in an Era of Innovation,...Facing uncertainty in the global financiallandscape,the Annual Conference of Financial Street Forum 2025,running in Beijing from October 27 to 30,took on the theme Global Financial Development in an Era of Innovation,Transformation and Restructuring.展开更多
Unmanned aerial vehicles(UAVs),especially quadcopters,have become indispensable in numerous industrial and scientific applications due to their flexibility,lowcost,and capability to operate in dynamic environments.Thi...Unmanned aerial vehicles(UAVs),especially quadcopters,have become indispensable in numerous industrial and scientific applications due to their flexibility,lowcost,and capability to operate in dynamic environments.This paper presents a complete design and implementation of a compact autonomous quadcopter capable of trajectory tracking,object detection,precision landing,and real-time telemetry via long-range communication protocols.The system integrates an onboard flight controller running real-time sensor fusion algorithms,a vision-based detection system on a companion single-board computer,and a telemetry unit using Long Range(LoRa)communication.Extensive flight tests were conducted to validate the system’s stability,communication range,and autonomous capabilities.Potential applications in law enforcement,agriculture,search and rescue,and environmental monitoring are also discussed.展开更多
The satellite-based augmentation system(SBAS)provides differential and integrity augmentation services for life safety fields of aviation and navigation.However,the signal structure of SBAS is public,which incurs a ri...The satellite-based augmentation system(SBAS)provides differential and integrity augmentation services for life safety fields of aviation and navigation.However,the signal structure of SBAS is public,which incurs a risk of spoofing attacks.To improve the anti-spoofing capability of the SBAS,European Union and the United States conduct research on navigation message authentication,and promote the standardization of SBAS message authentication.For the development of Beidou satellite-based augmentation system(BDSBAS),this paper proposes navigation message authentication based on the Chinese commercial cryptographic standards.Firstly,this paper expounds the architecture and principles of the SBAS message authentication,and then carries out the design of timed efficient streaming losstolerant authentication scheme(TESLA)and elliptic curve digital signature algorithm(ECDSA)authentication schemes based on Chinese commercial cryptographic standards,message arrangement and the design of over-the-air rekeying(OTAR)message.Finally,this paper conducts a theoretical analysis of the time between authentications(TBA)and maximum authentication latency(MAL)for L5 TESLA-I and L5 ECDSA-Q,and further simulates the reception time of OTAR message,TBA and MAL from the aspects of OTAR message weight and demodulation error rate.The simulation results can provide theoretical supports for the standardization of BDSBAS message authentication.展开更多
The thoracic duct(TD),the largest lymphatic vessel in the human body,plays a critical role in returning lymph to the circulatory system.However,its dynamic,distensible nature and concealed anatomical location make int...The thoracic duct(TD),the largest lymphatic vessel in the human body,plays a critical role in returning lymph to the circulatory system.However,its dynamic,distensible nature and concealed anatomical location make intraoperative visualization critically challenging and increase the risk of injury.Real-time,high-resolution assessment of TD leaks remains an urgent clinical need.Here,we present a breakthrough molecular engineering strategy that leverages an intestinally lipophilic fluorescent formulation for dynamic in vivo TD imaging.Our rationally designed cyanine derivative IR790+,known for its rapid membrane permeability and endoplasmic reticulum(ER)targeting localization,demonstrates unprecedented chylomicron affinity,which subsequently transports the dye through the lymphatic system to the TD.Notably,dynamic,high-contrast intraoperative TD imaging is achieved from rat models to swine models.Administered orally as near-infrared(NIR)fluorescent contrast agent,this ultra-stable IR790+@oil formulation,engineered via flash nanoprecipitation,surpasses conventional counterparts by enabling non-invasive,real-time identification of TD.Intriguingly,this first-reported ER-targeting NIR formulation,delivered orally,represents a paradigm shift in fluorescence-guided surgery,significantly improving intraoperative accuracy.展开更多
Objectives:One of the most notable challenges in endoscopic procedures is maintaining correct orientation.Mental rotation exercise(MRE)has been suggested as a potential aid for improving orientation.However,there is a...Objectives:One of the most notable challenges in endoscopic procedures is maintaining correct orientation.Mental rotation exercise(MRE)has been suggested as a potential aid for improving orientation.However,there is a lack of research on designing MREs with varying difficultylevels for training purposes.Furthermore,few studies provide solid evidence linking MRE difficultylevels with cognitive load measurements.This study aims to address this gap by investigating the correlation between the MRE difficultylevels and participants’cognitive load,as measured by pupil dilation.Method:We recruited 33 participants to perform MREs on a computer equipped with a screen-mounted eye-tracker.The test consisted of 15 MREs,with the first10 relatively easy(traditional cube)and the next 5 more complex(invented molecule).The participants’eye movements during MREs were recorded.The participants’MRE scores and pupil dilation were obtained and compared between two MRE difficultylevels.Results:The participants who performed traditional cube MREs achieved significantlybetter MRE scores(0.77±0.11 vs.0.58±0.03,p<0.001)and lower pupil dilation(0.27±0.04 pixels vs.0.47±0.09 pixels,p<0.001)than did those who performed the invented molecule MREs.Moreover,there were significant negative correlations(r=0.62,p=0.015)between pupil dilation and MRE scores.Conclusions:The results revealed a significantnegative correlation between MRE scores and pupil dilation.The more challenging MRE questions led to worse MRE scores but increased pupil dilation.The MRE difficultylevels can be evaluated not only by the degrees or dimensions with which the objects were rotated but also by the participants’MRE scores and pupil dilation.The results of this study provide a basis for training orientation skills in endoscopy using MREs.By incorporating MREs with varying difficultylevels,customized training programs can be developed to enhance camera navigation in endoscopic and laparoscopic procedures.展开更多
Surgical navigation has evolved significantly through advances in augmented reality,virtual reality,and mixed reality,improving precision and safety across many clinical applications,including neurosurgery,maxillofaci...Surgical navigation has evolved significantly through advances in augmented reality,virtual reality,and mixed reality,improving precision and safety across many clinical applications,including neurosurgery,maxillofacial,spinal,and arthroplasty procedures.By integrating preoperative imaging with real-time intraoperative data,these systems provide dynamic guidance,reduce radiation exposure,and minimize tissue damage.Key challenges persist,including intraoperative registration accuracy,flexible tissue deformation,respiratory compensation,and real-time imaging quality.Emerging solutions include artificial intelligence-driven segmentation,deformation-field modeling,and hybrid registration techniques.Future developments will include lightweight,portable systems,improved non-rigid registration algorithms,and greater clinical adoption.Despite advances in rigid-tissue applications,soft-tissue navigation requires additional innovation to address motion variability and registration reliability,ultimately advancing minimally invasive surgery and precision medicine.展开更多
Background:Artificial intelligence(AI)-assisted threedimensional(3D)surgical platforms,integrated with augmented reality,have the potential to improve intraoperative anatomical recognition and provide surgeons with an...Background:Artificial intelligence(AI)-assisted threedimensional(3D)surgical platforms,integrated with augmented reality,have the potential to improve intraoperative anatomical recognition and provide surgeons with an immersive,dynamic operating environment during urooncological procedures.This review aims to examine the current applications of AI in robotic uro-oncology,with a particular focus on its role in facilitating intraoperative navigation during complex surgeries.Methods:A systematic literature search was performed across PubMed,the National Library of Medicine,MEDLINE,the Cochrane Central Register of Controlled Trials(CENTRAL),ClinicalTrials.gov,and Google Scholar to identify relevant studies published up to July 2025.The search strategy incorporated a predefined set of keywords,including AI,machine learning,radical prostatectomy(RP),robotic-assisted radical prostatectomy(RARP),robotassisted partial nephrectomy(RAPN),and robot-assisted radical cystectomy(RARC).Only clinical trials,full-text peer-reviewed publications,and original research articles were included.Studies were eligible for inclusion if they evaluated or described applications of AI in RARP,RAPN,or RARC.Results:Technological advancements have substantially transformed the field of uro-oncologic surgery.In particular,AI and AI-assisted intraoperative navigation in RARP demonstrate considerable potential to objectively assess surgical performance and predict clinical outcomes.In RAPN,the adoption of preoperative,interactive 3D virtualmodels for surgical planning has influenced surgical decisions,thus,enhanced precision in resection planning correlates with superior nephron-sparing outcomes and optimized selective clamping.AI applications in RARC,techniques such as augmented reality(AR)can overlay critical information on the surgical field,by facilitating navigation through complex anatomical planes and enhancing identification of critical structures.Conclusion:AI appears to enhance robotic uro-oncologic procedures by increasing operative precision and supporting individualised surgical treatment strategies.展开更多
Autonomous navigation is a key technology for unmanned motion platforms to perform their tasks smoothly.The current approaches for daytime polarization navigation have been extensively researched.However,the polarizat...Autonomous navigation is a key technology for unmanned motion platforms to perform their tasks smoothly.The current approaches for daytime polarization navigation have been extensively researched.However,the polarization light intensity is the fundamental information within the polarization image,and the light intensity at night is 6-8 orders of magnitude lower than that during the day,which increase the noise and the loss of local polarization information due to occlusion,resulting in a significant decrease in the polarization orientation accuracy.Aimed at the problem,a bio-inspired model is introduced to denoise and enhance weak nighttime polarization patterns.Further,to address the issue of outlier interference in the occluded environment during practical application,a fast-fitting method of the solar meridian based on the anti-symmetric distribution of the polarization angle adjusted by Proportional and Differential(PD)control is proposed.The experimental results show that the method proposed in this paper achieves a dynamic orientation error Root Mean Square Error(RMSE)of 0.7°in the weak polarization mode at night and in the presence of local occlusion.The proposed method has strong robustness under weak polarization occlusion at night,and the orientation accuracy is improved by 97%and 80%in comparison to the least squares method,which provides a new method for polarization navigation at night.This effectively improves the robustness and environmental applicability of the bionic polarization compass for nighttime applications.展开更多
Microelectromechanical systems(MEMS)technology has gained significant attention over the past decade for measuring inertial angular velocity.However,due to inherent complexity,MEMS gyroscopes typically feature up to t...Microelectromechanical systems(MEMS)technology has gained significant attention over the past decade for measuring inertial angular velocity.However,due to inherent complexity,MEMS gyroscopes typically feature up to ten times more parameters than traditional sensors,making selection a challenging task even for experts.This study addresses this challenge,focusing on defensive guidance,navigation,and control(GNC)systems where precise and reliable angular velocity measurement is critical to overall performance.A comprehensive mathematical model is introduced to encapsulate all key MEMS parameters,accompanied by discussions on calibration and Allan variance interpretation.For six leading MEMS gyroscope applications,namely inertial navigation,integrated navigation,autopilot systems,rotating projectiles,homing guidance,and north finding,the most critical parameters are identified,distinguishing suitable and unsuitable sensor choices.Special emphasis is placed on inertial navigation systems,where practical rules of thumb for error evaluation are derived using six degrees of freedom motion equations.Rigorous simulations demonstrate the influence of various sensor parameters through real-world case studies,including static navigation,multi-rotor attitude estimation,gimbal stabilization,and north finding via a turntable.This work aims to be a beacon for practitioners across diverse fields,empowering them to make more informed design decisions.展开更多
Unmanned Aerial Vehicle(UAV)plays a prominent role in various fields,and autonomous navigation is a crucial component of UAV intelligence.Deep Reinforcement Learning(DRL)has expanded the research avenues for addressin...Unmanned Aerial Vehicle(UAV)plays a prominent role in various fields,and autonomous navigation is a crucial component of UAV intelligence.Deep Reinforcement Learning(DRL)has expanded the research avenues for addressing challenges in autonomous navigation.Nonetheless,challenges persist,including getting stuck in local optima,consuming excessive computations during action space exploration,and neglecting deterministic experience.This paper proposes a noise-driven enhancement strategy.In accordance with the overall learning phases,a global noise control method is designed,while a differentiated local noise control method is developed by analyzing the exploration demands of four typical situations encountered by UAV during navigation.Both methods are integrated into a dual-model for noise control to regulate action space exploration.Furthermore,noise dual experience replay buffers are designed to optimize the rational utilization of both deterministic and noisy experience.In uncertain environments,based on the Twin Delay Deep Deterministic Policy Gradient(TD3)algorithm with Long Short-Term Memory(LSTM)network and Priority Experience Replay(PER),a Noise-Driven Enhancement Priority Memory TD3(NDE-PMTD3)is developed.We established a simulation environment to compare different algorithms,and the performance of the algorithms is analyzed in various scenarios.The training results indicate that the proposed algorithm accelerates the convergence speed and enhances the convergence stability.In test experiments,the proposed algorithm successfully and efficiently performs autonomous navigation tasks in diverse environments,demonstrating superior generalization results.展开更多
文摘In the context of global energy transition,traditional energy companies are confronting multiple pressures,including resource depletion,intensifying market competition,and elevated ESG standards,necessitating an urgent shift from the fossil fuel-centered“first curve”to a“second curve”characterized by renewable energy,digitalization,and green technologies.Drawing on second curve theory,dynamic capabilities theory,and ambidextrous innovation theory.
文摘The Titanic sunk 113 years ago on April 14-15,after hitting an iceberg,with human error likely causing the ship to wander into those dangerous waters.Today,autonomous systems built on AI can help ships avoid such accidents.But could such a system explain to the captain why it was controlling the ship in a certain way?
基金Supported by the National Natural Science Foundation of China(No.61971162,61771186)the Natural Science Foundation of Heilongjiang Province(No.PL2024F025)+1 种基金the Open Research Fund of National Mobile Communications Research Laboratory in Southeast University(No.2023D07)the Fundamental Scientific Research Funds of Heilongjiang Province(No.2022-KYYWF-1050).
文摘The impact of location services on people’s lives has grown significantly in the era of widespread smart device usage.Due to global navigation satellite system(GNSS)signal rejection,weak signal strength in indoor environments and radio signal interference caused by multiwall environments,which collectively lead to significant positioning errors,vision-based positioning has emerged as a crucial method in indoor positioning research.This paper introduces a scale hierarchical matching model to tackle challenges associated with large visual databases and high scene similarity,both of which will compromise matching accuracy and lead to prolonged positioning delays.The proposed model establishes an image feature database using GIST features and speeded up robust feature(SURF)in the offline stage.In the online stage,a positioning navigating algorithm is constructed based on Dijkstra’s path planning.Additionally,a corresponding Android application has been developed to facilitate visual positioning and navigation in indoor environments.Experimental results obtained in real indoor environments demonstrate that the proposed method significantly enhances positioning accuracy compared with similar algorithms,while effectively reducing time overhead.This improvement caters to the requirements for indoor positioning and navigation,thereby meeting user needs.
基金Supported by the Major Science and Technology Project of Hubei Province of China(2022AAA009)the Open Fund of Hubei Luojia Laboratory。
文摘Today,autonomous mobile robots are widely used in all walks of life.Autonomous navigation,as a basic capability of robots,has become a research hotspot.Classical navigation techniques,which rely on pre-built maps,struggle to cope with complex and dynamic environments.With the development of artificial intelligence,learning-based navigation technology have emerged.Instead of relying on pre-built maps,the agent perceives the environment and make decisions through visual observation,enabling end-to-end navigation.A key challenge is to enhance the generalization ability of the agent in unfamiliar environments.To tackle this challenge,it is necessary to endow the agent with spatial intelligence.Spatial intelligence refers to the ability of the agent to transform visual observations into insights,in-sights into understanding,and understanding into actions.To endow the agent with spatial intelligence,relevant research uses scene graph to represent the environment.We refer to this method as scene graph-based object goal navigation.In this paper,we concentrate on scene graph,offering formal description,computational framework of object goal navigation.We provide a comprehensive summary of the meth-ods for constructing and applying scene graph.Additionally,we present experimental evidence that highlights the critical role of scene graph in improving navigation success.This paper also delineates promising research directions,all aimed at sharpening the focus on scene graph.Overall,this paper shows how scene graph endows the agent with spatial intelligence,aiming to promote the importance of scene graph in the field of intelligent navigation.
基金funded by the National College Students Innovation and Entrepreneurship Training Program(202411646031)the Zhejiang Xinmiao Talents Program(2024R405A052)the SRIP Research Program of Ningbo University(2025SRIP1707).
文摘The dynamic behavior of high-speed craft navigating through variable sea states plays a pivotal role in ensuring maritime safety.However,many existing simulation approaches rely on linear or overly simplified representations of the marine environment,thereby limiting the fidelity of motion predictions.This study explores the motion characteristics of a 4.5-t high-speed vessel by conducting fully coupled numerical simulations using the STAR-CCM+software.The analysis considers both calm and varying sea conditions,incorporating fluctuations in wave height,wavelength,and wind speed to reflect more realistic operating scenarios.Simulation results reveal that the vessel’s hydrodynamic response is highly sensitive to changes in sea state.As conditions deteriorate,the free surface becomes increasingly complex,with higher wave amplitudes and more pronounced interactions between the waves generated by the vessel and those imposed by the external environment.These effects lead to significant increases in roll,pitch,heave,and sway motions,thereby imposing greater demands on the vessel’s dynamic stability and operational safety.Furthermore,both hydrodynamic resistance and propulsive thrust exhibit notable dependence on sea state and vessel speed.Total resistance generally increases with rougher sea conditions,while thrust tends to rise with increasing forward speed.Under calm or mildly disturbed waters,a Froude number(Fr)of 0.5 appears to offer an optimal balance for initiating and controlling primary motions such as roll,pitch,heave,and sway.Conversely,in more challenging conditions-such as those represented by a Sea State 3-effective motion control is better achieved at a higher Froude number of approximately 1.0.
文摘This paper introduces a new control strategy for heterogeneous multi-robots systems dedicated to industrial logistic setups. This control strategy is based on both distributed intelligence and machine learning and involves three parts: the rigid formation controller, the perception system and the path planner. Our controller is event-based and thus its control-coordination strategy can be self-adaptive and applied to real dynamic environment. During the navigating process, the multi-robots system derives the environment model, performs the path planning process that guaranties both the transportation constraints and the obstacle avoidance. For the validation, both simulation and real robot experiments are performed. The results show that the developed control strategy can be well used for realistic logistics applications.
文摘SEVEN years after the outbreak of the global financial crisis in 2008, the global economy is not yet quite out of the woods and, overall, recovery remains sluggish and not sufficiently robust. As the second largest economy in the world. China has also bidden a farewell to seemingly miraculous runaway economic expansion and seen its growth pace level offat 7 percent in the first half of this year, arousing extensive concerns over its long-term economic outlook.
文摘Facing uncertainty in the global financiallandscape,the Annual Conference of Financial Street Forum 2025,running in Beijing from October 27 to 30,took on the theme Global Financial Development in an Era of Innovation,Transformation and Restructuring.
文摘Unmanned aerial vehicles(UAVs),especially quadcopters,have become indispensable in numerous industrial and scientific applications due to their flexibility,lowcost,and capability to operate in dynamic environments.This paper presents a complete design and implementation of a compact autonomous quadcopter capable of trajectory tracking,object detection,precision landing,and real-time telemetry via long-range communication protocols.The system integrates an onboard flight controller running real-time sensor fusion algorithms,a vision-based detection system on a companion single-board computer,and a telemetry unit using Long Range(LoRa)communication.Extensive flight tests were conducted to validate the system’s stability,communication range,and autonomous capabilities.Potential applications in law enforcement,agriculture,search and rescue,and environmental monitoring are also discussed.
基金supported by National Natural Science Foundation of China:Space-based occultation detection with ground-based GNSS atmospheric horizontal gradient model(41904033).
文摘The satellite-based augmentation system(SBAS)provides differential and integrity augmentation services for life safety fields of aviation and navigation.However,the signal structure of SBAS is public,which incurs a risk of spoofing attacks.To improve the anti-spoofing capability of the SBAS,European Union and the United States conduct research on navigation message authentication,and promote the standardization of SBAS message authentication.For the development of Beidou satellite-based augmentation system(BDSBAS),this paper proposes navigation message authentication based on the Chinese commercial cryptographic standards.Firstly,this paper expounds the architecture and principles of the SBAS message authentication,and then carries out the design of timed efficient streaming losstolerant authentication scheme(TESLA)and elliptic curve digital signature algorithm(ECDSA)authentication schemes based on Chinese commercial cryptographic standards,message arrangement and the design of over-the-air rekeying(OTAR)message.Finally,this paper conducts a theoretical analysis of the time between authentications(TBA)and maximum authentication latency(MAL)for L5 TESLA-I and L5 ECDSA-Q,and further simulates the reception time of OTAR message,TBA and MAL from the aspects of OTAR message weight and demodulation error rate.The simulation results can provide theoretical supports for the standardization of BDSBAS message authentication.
基金supported by the National Natural Science Foundation of China(22225805,81400681,32394001,32121005)the Shanghai Science and Technology Innovation Action Plan(22Y11907200,23J21901600)the Innovation Program of Shanghai Municipal Education Commission,Shanghai Municipal Health Commission(2024ZZ2025)。
文摘The thoracic duct(TD),the largest lymphatic vessel in the human body,plays a critical role in returning lymph to the circulatory system.However,its dynamic,distensible nature and concealed anatomical location make intraoperative visualization critically challenging and increase the risk of injury.Real-time,high-resolution assessment of TD leaks remains an urgent clinical need.Here,we present a breakthrough molecular engineering strategy that leverages an intestinally lipophilic fluorescent formulation for dynamic in vivo TD imaging.Our rationally designed cyanine derivative IR790+,known for its rapid membrane permeability and endoplasmic reticulum(ER)targeting localization,demonstrates unprecedented chylomicron affinity,which subsequently transports the dye through the lymphatic system to the TD.Notably,dynamic,high-contrast intraoperative TD imaging is achieved from rat models to swine models.Administered orally as near-infrared(NIR)fluorescent contrast agent,this ultra-stable IR790+@oil formulation,engineered via flash nanoprecipitation,surpasses conventional counterparts by enabling non-invasive,real-time identification of TD.Intriguingly,this first-reported ER-targeting NIR formulation,delivered orally,represents a paradigm shift in fluorescence-guided surgery,significantly improving intraoperative accuracy.
文摘Objectives:One of the most notable challenges in endoscopic procedures is maintaining correct orientation.Mental rotation exercise(MRE)has been suggested as a potential aid for improving orientation.However,there is a lack of research on designing MREs with varying difficultylevels for training purposes.Furthermore,few studies provide solid evidence linking MRE difficultylevels with cognitive load measurements.This study aims to address this gap by investigating the correlation between the MRE difficultylevels and participants’cognitive load,as measured by pupil dilation.Method:We recruited 33 participants to perform MREs on a computer equipped with a screen-mounted eye-tracker.The test consisted of 15 MREs,with the first10 relatively easy(traditional cube)and the next 5 more complex(invented molecule).The participants’eye movements during MREs were recorded.The participants’MRE scores and pupil dilation were obtained and compared between two MRE difficultylevels.Results:The participants who performed traditional cube MREs achieved significantlybetter MRE scores(0.77±0.11 vs.0.58±0.03,p<0.001)and lower pupil dilation(0.27±0.04 pixels vs.0.47±0.09 pixels,p<0.001)than did those who performed the invented molecule MREs.Moreover,there were significant negative correlations(r=0.62,p=0.015)between pupil dilation and MRE scores.Conclusions:The results revealed a significantnegative correlation between MRE scores and pupil dilation.The more challenging MRE questions led to worse MRE scores but increased pupil dilation.The MRE difficultylevels can be evaluated not only by the degrees or dimensions with which the objects were rotated but also by the participants’MRE scores and pupil dilation.The results of this study provide a basis for training orientation skills in endoscopy using MREs.By incorporating MREs with varying difficultylevels,customized training programs can be developed to enhance camera navigation in endoscopic and laparoscopic procedures.
基金Supported by the National Natural Science Foundation of China(NSFC)under Grants 62025104,62422102,62331005,62301034,and U22A2052the Beijing Natural Science Foundation-Daxing Innovation Joint Fund(L256040).
文摘Surgical navigation has evolved significantly through advances in augmented reality,virtual reality,and mixed reality,improving precision and safety across many clinical applications,including neurosurgery,maxillofacial,spinal,and arthroplasty procedures.By integrating preoperative imaging with real-time intraoperative data,these systems provide dynamic guidance,reduce radiation exposure,and minimize tissue damage.Key challenges persist,including intraoperative registration accuracy,flexible tissue deformation,respiratory compensation,and real-time imaging quality.Emerging solutions include artificial intelligence-driven segmentation,deformation-field modeling,and hybrid registration techniques.Future developments will include lightweight,portable systems,improved non-rigid registration algorithms,and greater clinical adoption.Despite advances in rigid-tissue applications,soft-tissue navigation requires additional innovation to address motion variability and registration reliability,ultimately advancing minimally invasive surgery and precision medicine.
文摘Background:Artificial intelligence(AI)-assisted threedimensional(3D)surgical platforms,integrated with augmented reality,have the potential to improve intraoperative anatomical recognition and provide surgeons with an immersive,dynamic operating environment during urooncological procedures.This review aims to examine the current applications of AI in robotic uro-oncology,with a particular focus on its role in facilitating intraoperative navigation during complex surgeries.Methods:A systematic literature search was performed across PubMed,the National Library of Medicine,MEDLINE,the Cochrane Central Register of Controlled Trials(CENTRAL),ClinicalTrials.gov,and Google Scholar to identify relevant studies published up to July 2025.The search strategy incorporated a predefined set of keywords,including AI,machine learning,radical prostatectomy(RP),robotic-assisted radical prostatectomy(RARP),robotassisted partial nephrectomy(RAPN),and robot-assisted radical cystectomy(RARC).Only clinical trials,full-text peer-reviewed publications,and original research articles were included.Studies were eligible for inclusion if they evaluated or described applications of AI in RARP,RAPN,or RARC.Results:Technological advancements have substantially transformed the field of uro-oncologic surgery.In particular,AI and AI-assisted intraoperative navigation in RARP demonstrate considerable potential to objectively assess surgical performance and predict clinical outcomes.In RAPN,the adoption of preoperative,interactive 3D virtualmodels for surgical planning has influenced surgical decisions,thus,enhanced precision in resection planning correlates with superior nephron-sparing outcomes and optimized selective clamping.AI applications in RARC,techniques such as augmented reality(AR)can overlay critical information on the surgical field,by facilitating navigation through complex anatomical planes and enhancing identification of critical structures.Conclusion:AI appears to enhance robotic uro-oncologic procedures by increasing operative precision and supporting individualised surgical treatment strategies.
基金co-supported by the Excellent Youth Foundation of Shanxi Province,China(No.202103021222011)the Key Research and Development project of Shanxi Province of China(No.202202020101002)+3 种基金the Fundamental Research Program of Shanxi Province of China(No.202303021211150)the Aviation Science Foundation of China(No.2022Z0220U0002)the Graduate Education Innovation Plan Project of Shanxi Province,China(No.2023KY588)the Shanxi Province Key Laboratory of Quantum Sensing and Precision Measurement,China(No.201905D121001).
文摘Autonomous navigation is a key technology for unmanned motion platforms to perform their tasks smoothly.The current approaches for daytime polarization navigation have been extensively researched.However,the polarization light intensity is the fundamental information within the polarization image,and the light intensity at night is 6-8 orders of magnitude lower than that during the day,which increase the noise and the loss of local polarization information due to occlusion,resulting in a significant decrease in the polarization orientation accuracy.Aimed at the problem,a bio-inspired model is introduced to denoise and enhance weak nighttime polarization patterns.Further,to address the issue of outlier interference in the occluded environment during practical application,a fast-fitting method of the solar meridian based on the anti-symmetric distribution of the polarization angle adjusted by Proportional and Differential(PD)control is proposed.The experimental results show that the method proposed in this paper achieves a dynamic orientation error Root Mean Square Error(RMSE)of 0.7°in the weak polarization mode at night and in the presence of local occlusion.The proposed method has strong robustness under weak polarization occlusion at night,and the orientation accuracy is improved by 97%and 80%in comparison to the least squares method,which provides a new method for polarization navigation at night.This effectively improves the robustness and environmental applicability of the bionic polarization compass for nighttime applications.
文摘Microelectromechanical systems(MEMS)technology has gained significant attention over the past decade for measuring inertial angular velocity.However,due to inherent complexity,MEMS gyroscopes typically feature up to ten times more parameters than traditional sensors,making selection a challenging task even for experts.This study addresses this challenge,focusing on defensive guidance,navigation,and control(GNC)systems where precise and reliable angular velocity measurement is critical to overall performance.A comprehensive mathematical model is introduced to encapsulate all key MEMS parameters,accompanied by discussions on calibration and Allan variance interpretation.For six leading MEMS gyroscope applications,namely inertial navigation,integrated navigation,autopilot systems,rotating projectiles,homing guidance,and north finding,the most critical parameters are identified,distinguishing suitable and unsuitable sensor choices.Special emphasis is placed on inertial navigation systems,where practical rules of thumb for error evaluation are derived using six degrees of freedom motion equations.Rigorous simulations demonstrate the influence of various sensor parameters through real-world case studies,including static navigation,multi-rotor attitude estimation,gimbal stabilization,and north finding via a turntable.This work aims to be a beacon for practitioners across diverse fields,empowering them to make more informed design decisions.
基金the Collaborative Innovation Project of Shanghai,China for the financial support。
文摘Unmanned Aerial Vehicle(UAV)plays a prominent role in various fields,and autonomous navigation is a crucial component of UAV intelligence.Deep Reinforcement Learning(DRL)has expanded the research avenues for addressing challenges in autonomous navigation.Nonetheless,challenges persist,including getting stuck in local optima,consuming excessive computations during action space exploration,and neglecting deterministic experience.This paper proposes a noise-driven enhancement strategy.In accordance with the overall learning phases,a global noise control method is designed,while a differentiated local noise control method is developed by analyzing the exploration demands of four typical situations encountered by UAV during navigation.Both methods are integrated into a dual-model for noise control to regulate action space exploration.Furthermore,noise dual experience replay buffers are designed to optimize the rational utilization of both deterministic and noisy experience.In uncertain environments,based on the Twin Delay Deep Deterministic Policy Gradient(TD3)algorithm with Long Short-Term Memory(LSTM)network and Priority Experience Replay(PER),a Noise-Driven Enhancement Priority Memory TD3(NDE-PMTD3)is developed.We established a simulation environment to compare different algorithms,and the performance of the algorithms is analyzed in various scenarios.The training results indicate that the proposed algorithm accelerates the convergence speed and enhances the convergence stability.In test experiments,the proposed algorithm successfully and efficiently performs autonomous navigation tasks in diverse environments,demonstrating superior generalization results.
