This study examines the methods to plan the development of offshore oilfields over the years,which are used to support the decision-making on the development of offshore oilfields.About 100 papers are analysed and cat...This study examines the methods to plan the development of offshore oilfields over the years,which are used to support the decision-making on the development of offshore oilfields.About 100 papers are analysed and categorised into different groups of main early-stage decisions.The present study stands in contrast to the contributions of the operations research and system engineering review articles,on the one hand,and the petroleum engineering review articles,on the other.This is because it does not focus on one methodological approach,nor does it limit the literature analysis by offshore oilfield characteristics.Consequently,the present analysis may offer valuable insights,for instance,by identifying environmental planning decisions as a recent yet highly significant concern that is currently being imposed on decision-making process.Thus,it is evident that the incorporation of safety criteria within the technical-economic decision-making process for the design of production systems would be a crucial requirement at development phase.展开更多
Hierarchical Task Network(HTN)planning is a powerful technique in artificial intelligence for handling complex problems by decomposing them into hierarchical task structures.However,achieving optimal solutions in HTN ...Hierarchical Task Network(HTN)planning is a powerful technique in artificial intelligence for handling complex problems by decomposing them into hierarchical task structures.However,achieving optimal solutions in HTN planning remains a challenge,especially in scenarios where traditional search algorithms struggle to navigate the vast solution space efficiently.This research proposes a novel technique to enhance HTN planning by integrating the Ant Colony Optimization(ACO)algorithm into the refinement process.The Ant System algorithm,inspired by the foraging behavior of ants,is well-suited for addressing optimization problems by efficiently exploring solution spaces.By incorporating ACO into the refinement phase of HTN planning,the authors aim to leverage its adaptive nature and decentralized decision-making to improve plan generation.This paper involves the development of a hybrid strategy called ACO-HTN,which combines HTN planning with ACO-based plan selection.This technique enables the system to adaptively refine plans by guiding the search towards optimal solutions.To evaluate the effectiveness of the proposed technique,this paper conducts empirical experiments on various domains and benchmark datasets.Our results demonstrate that the ACO-HTN strategy enhances the efficiency and effectiveness of HTN planning,outperforming traditional methods in terms of solution quality and computational performance.展开更多
To improve the efficiency and accuracy of path planning for fan inspection tasks in thermal power plants,this paper proposes an intelligent inspection robot path planning scheme based on an improved A^(*)algorithm.The...To improve the efficiency and accuracy of path planning for fan inspection tasks in thermal power plants,this paper proposes an intelligent inspection robot path planning scheme based on an improved A^(*)algorithm.The inspection robot utilizes multiple sensors to monitor key parameters of the fans,such as vibration,noise,and bearing temperature,and upload the data to the monitoring center.The robot’s inspection path employs the improved A^(*)algorithm,incorporating obstacle penalty terms,path reconstruction,and smoothing optimization techniques,thereby achieving optimal path planning for the inspection robot in complex environments.Simulation results demonstrate that the improved A^(*)algorithm significantly outperforms the traditional A^(*)algorithm in terms of total path distance,smoothness,and detour rate,effectively improving the execution efficiency of inspection tasks.展开更多
Making plans is a good idea,but every one's schedule looks differe nt.You may have to talk about your plans before you're able to make some.It could sound like this:You ask,"Do you have plans this Friday ...Making plans is a good idea,but every one's schedule looks differe nt.You may have to talk about your plans before you're able to make some.It could sound like this:You ask,"Do you have plans this Friday night?"If the person already has plans,they may say,"I do.But I'm free on Saturday."If that day doesn't work for you,you can say,"I'm not available that day.How about Sunday after no on?"After you figure out the day and time,mark it on your calendar.展开更多
Robotic manipulators increasingly operate in complex three-dimensional workspaces where accuracy and strict limits on position,velocity,and acceleration must be satisfied.Conventional geometric planners emphasize path...Robotic manipulators increasingly operate in complex three-dimensional workspaces where accuracy and strict limits on position,velocity,and acceleration must be satisfied.Conventional geometric planners emphasize path smoothness but often ignore dynamic feasibility,motivating control-aware trajectory generation.This study presents a novel model predictive control(MPC)framework for three-dimensional trajectory planning of robotic manipulators that integrates second-order dynamic modeling and multi-objective parameter optimization.Unlike conventional interpolation techniques such as cubic splines,B-splines,and linear interpolation,which neglect physical constraints and system dynamics,the proposed method generates dynamically feasible trajectories by directly optimizing over acceleration inputs while minimizing both tracking error and control effort.A key innovation lies in the use of Pareto front analysis for tuning prediction horizon and sampling time,enabling a systematic balance between accuracy and motion smoothness.Comparative evaluation using simulated experiments demonstrates that the proposed MPC approach achieves a minimum mean absolute error(MAE)of 0.170 and reduces maximum acceleration to 0.0217,compared to 0.0385 in classical linear methods.The maximum deviation error was also reduced by approximately 27.4%relative to MPC configurations without tuned parameters.All experiments were conducted in a simulation environment,with computational times per control cycle consistently remaining below 20 milliseconds,indicating practical feasibility for real-time applications.Thiswork advances the state-of-the-art inMPC-based trajectory planning by offering a scalable and interpretable control architecture that meets physical constraints while optimizing motion efficiency,thus making it suitable for deployment in safety-critical robotic applications.展开更多
Climate change is increasingly affecting all aspects of protected areas management from changes of species ranges to visitor experiences.Due to these impacts,there is a need for managers to take more robust approaches...Climate change is increasingly affecting all aspects of protected areas management from changes of species ranges to visitor experiences.Due to these impacts,there is a need for managers to take more robust approaches to con-sidering the implications of climate change on the overall application and efficacy of protected areas management direction,including the achievement of the goals and objectives contained within management plans.Through a systematic and comprehensive content analysis approach,this study assesses the current extent to which climate change is considered in Canadian protected area management plans.Specifically,we evaluated 63 terrestrial protected area management plans against a set of climate robustness principles.Our content analysis revealed that climate change is currently not effectively factored into Canadian protected area management plans with an average climate robustness score of 18%.Climate robustness score was not found to be correlated with protected area size,International Union for the Conservation of Nature(IUCN)management classification,or jurisdictional authority.Certain climate robustness principles received higher scores across the management plans than oth-ers.For example,the principles of‘diverse knowledge sources’and‘addresses climate change’scored relatively highly whereas‘climate change vulnerability’and‘ecosystem integrity’received the lowest scores.The lack of integration of ecological integrity considerations in management plans was a particularly noteworthy deficiency considering that this guiding principle is the primary legislative objective of many national and sub-national protected areas in Canada.From this assessment,climate change needs to be more effectively and consistently integrated into protected area management plan development and coordinated across associated planning pro-cesses.We discuss the ways in which this can be achieved,for example,by integrating scenario planning into organizational management plan development processes.展开更多
BACKGROUND Hepatobiliary surgery is complex and requires a thorough understanding of the liver’s anatomy,biliary system,and vasculature.Traditional imaging methods such as computed tomography(CT)and magnetic resonanc...BACKGROUND Hepatobiliary surgery is complex and requires a thorough understanding of the liver’s anatomy,biliary system,and vasculature.Traditional imaging methods such as computed tomography(CT)and magnetic resonance imaging(MRI),although helpful,fail to provide three-dimensional(3D)relationships of these structures,which are critical for planning and executing complicated surgeries.AIM To explore the use of 3D imaging and virtual surgical planning(VSP)technologies to improve surgical accuracy,reduce complications,and enhance patient recovery in hepatobiliary surgeries.METHODS A comprehensive review of studies published between 2017 and 2024 was conducted through PubMed,Scopus,Google Scholar,and Web of Science.Studies selected focused on 3D imaging and VSP applications in hepatobiliary surgery,assessing surgical precision,complications,and patient outcomes.Thirty studies,including randomized controlled trials,cohort studies,and case reports,were included in the final analysis.RESULTS Various 3D imaging modalities,including multidetector CT,MRI,and 3D rotational angiography,provide high-resolution views of the liver’s vascular and biliary anatomy.VSP allows surgeons to simulate complex surgeries,improving preoperative planning and reducing complications like bleeding and bile leaks.Several studies have demonstrated improved surgical precision,reduced complications,and faster recovery times when 3D imaging and VSP were used in complex surgeries.CONCLUSION 3D imaging and VSP technologies significantly enhance the accuracy and outcomes of hepatobiliary surgeries by providing individualized preoperative planning.While promising,further research,particularly randomized controlled trials,is needed to standardize protocols and evaluate long-term efficacy.展开更多
ln order to improve the level of investment promotion and redouble effortsto enhance services,on February l9th,the 2025 Action Plan for StabilizingForeign lnvestment was released,proposing 20 measures in four aspects....ln order to improve the level of investment promotion and redouble effortsto enhance services,on February l9th,the 2025 Action Plan for StabilizingForeign lnvestment was released,proposing 20 measures in four aspects.Cur-rently,with increasing uncertainties in the external environment,China facesmultple difficulties and challenges in attracting foreign investment.展开更多
Spanish scholars decode China’s five-year planning as a strategic governance model that ensures long-term national development through continuity,popular participation,and adaptability,offering valuable insights for ...Spanish scholars decode China’s five-year planning as a strategic governance model that ensures long-term national development through continuity,popular participation,and adaptability,offering valuable insights for global governance.展开更多
Effective forest regeneration is essential for sustainable forestry practices.In Sweden,mechanical site preparation and manual planting is the dominating method,but sourcing labour for the physically demanding work is...Effective forest regeneration is essential for sustainable forestry practices.In Sweden,mechanical site preparation and manual planting is the dominating method,but sourcing labour for the physically demanding work is difficult.An autonomous scarifying and planting system(Autoplant)could meet the requirements of the forest industry and,for this,a tool for regeneration planning and routing is needed.The tool,Pathfinder,plans the regeneration and routes based on the harvested production(hpr)files,soil moisture and parent material maps,no-go areas(for culture or nature conservation),digital elevation models(DEM),and machine data(e.g.,working width,critical slope,time taken for different turn angles).The overall planting solution is either a set of capacity constrained routes or a continuous route and could be used for any planting machine as well as for traditional scarifiers as disc trenchers or mounders pulled by forwarders.Pathfinder was tested on eleven regeneration areas throughout Sweden,both with continuous routes and routes based on a carrying capacity of 1500 seedlings.The net operation area,species and seedling density suggestions were deemed relevant by expert judgement in the field.The routes provided by Pathfinder were compared with solutions given by two experienced drivers and a third solution based on the actual soil scarification at the site.Total driving distance did not differ significantly between the suggestions,but Pathfinder included less side-slope driving on steep slopes(≥27%or 15°)and medium slopes(15–27%).The chosen threshold value for steep slopes(where side-slope driving should be avoided)affects the routing,and a lower threshold means more turning and longer driving distance.Pathfinder is not only a tool for routing of planting machines,but also helps in planning of traditional regeneration by providing a more correct net area and tree species suggestions based on the growth of the previous stand.It also diminishes the risk of severe soil disturbance by excluding the wettest area in the planning.展开更多
Compared with single-domain unmanned swarms,cross-domain unmanned swarms continue to face new challenges in terms of platform performance and constraints.In this paper,a joint unmanned swarm target assignment and miss...Compared with single-domain unmanned swarms,cross-domain unmanned swarms continue to face new challenges in terms of platform performance and constraints.In this paper,a joint unmanned swarm target assignment and mission trajectory planning method is proposed to meet the requirements of cross-domain unmanned swarm mission planning.Firstly,the different performances of cross-domain heterogeneous platforms and mission requirements of targets are characterised by using a collection of operational resources.Secondly,an algorithmic framework for joint target assignment and mission trajectory planning is proposed,in which the initial planning of the trajectory is performed in the target assignment phase,while the trajectory is further optimised afterwards.Next,the estimation of the distribution algorithms is combined with the genetic algorithm to solve the objective function.Finally,the algorithm is numerically simulated by specific cases.Simulation results indicate that the proposed algorithm can perform effective task assignment and trajectory planning for cross-domain unmanned swarms.Furthermore,the solution performance of the hybrid estimation of distribution algorithm(EDA)-genetic algorithm(GA)algorithm is better than that of GA and EDA.展开更多
Based on the outcome-based education concept,the integrated teaching of professional courses for land space planning in the human geography and urban and rural planning majors was reformed and practiced.Focusing on th...Based on the outcome-based education concept,the integrated teaching of professional courses for land space planning in the human geography and urban and rural planning majors was reformed and practiced.Focusing on the fundamental task of“establishing morality and cultivating people,”the reform of the teaching mode was proposed to clarify the industry needs,revise and improve the training program and teaching syllabus,innovate the teaching mode,and optimize the practical teaching resources and conditions.A new“multi-dimensional,interactive,and three-dimensional”teaching mode was constructed,and the integrated teaching method of enterprise projects,professional internships,and scientific research training was innovated,realizing the talent training mechanism of“demand-driven and integration of industry and education.”展开更多
BACKGROUND Kidney transplantation is one of the most effective treatments for patients with end-stage renal disease.However,many regions face low deceased donor rates and limited ABO-compatible transplant availability...BACKGROUND Kidney transplantation is one of the most effective treatments for patients with end-stage renal disease.However,many regions face low deceased donor rates and limited ABO-compatible transplant availability,which increases reliance on living donors.These regional challenges necessitate the implementation of kidney paired donation(KPD)programs to overcome incompatibilities such as ABO mismatch or positive cross-matching,even when suitable and willing donors are available.AIM To evaluate the effectiveness of a single-center domino KPD model in both operational planning and clinical management processes and to assess its impact on clinical outcomes.METHODS Between April 2020 and January 2024,we retrospectively evaluated patients enrolled in our center’s domino kidney transplantation program.Donor-recipient pairs unable to proceed due to ABO incompatibility or positive cross-matching with their own living donors were included.Donors and recipients were assessed based on blood group compatibility,HLA tissue typing,and negative cross-match results.A specialized computer algorithm grouped patients into three-way,fourway,and five-way chains.All surgical procedures were performed on the same day at a single center.RESULTS A total of 169 kidney transplants were performed,forming 52 domino chains.These domino KPD transplants accounted for a notable proportion of our center’s overall transplant activity,which included both living donor kidney transplants and deceased donor transplants.Among these chains,the primary reasons for participation were ABO incompatibility(74%),positive cross-matching(10%),and the desire to improve HLA mismatch(16%).Improved HLA mismatch profiles and high graft survival(96%at 1 year,92%at 3 years)and patient survival(98%at 1 year,94%at 3 years)rates were observed,as well as low acute rejection episodes.CONCLUSION The single-center domino KPD model enhanced transplant opportunities for incompatible donor-recipient pairs while maintaining excellent clinical outcomes.By providing a framework that addresses regional challenges,improves operational efficiency,and optimizes clinical management,this model offers actionable insights to reduce waiting lists and improve patient outcomes.展开更多
China boasts over 10,000 native useful vascular plants(NUVPs),spanning eight families and serving twelve dis-tinct uses.Given the importance of NUVPs,widely-confirmed in-situ conservation policies,such as establishing...China boasts over 10,000 native useful vascular plants(NUVPs),spanning eight families and serving twelve dis-tinct uses.Given the importance of NUVPs,widely-confirmed in-situ conservation policies,such as establishing nature reserves,have been broadly implemented to protect them.However,the effectiveness of in-situ conser-vation efforts for NUVPs in China remains uncertain.Highlighting the importance of multi-family and multi-use plants,this research identified the spatial distribution pattern and diversity hotspots of NUVPs,evaluated the in-situ conservation effectiveness and provided the future conservation priority scheme.The results revealed that the spatial concentration of NUVPs is predominantly in the southwestern lowlands of China(<3,000 m),peaking around 109°E and 25°N.Importantly,diversity hotspots exhibited a significant spatial mismatch(over 80%)with the National Nature Reserve(NNR)network.Only about 17.7%and 13.3%of these hotspots are protected by NNR initiatives for endemic and nonendemic species,respectively.Additionally,the proposed Plants Conserva-tion Effectiveness Index(PCEI)proved more representative in addressing the two main crises faced by the studied species-species loss and human pressure,and found a decline in conservation effectiveness as the number of uses increased.Finally,future conservation priorities based on the PCEI highlight the Nanling Mountains,Heng-duan Mountains,Jiuwandashan,and Qilian Mountains as highly prioritized regions requiring focused efforts to address the impacts of climate change.Conversely,in sparsely distributed regions experiencing increasing human pressure,it is imperative to mitigate the expanding human footprint.展开更多
To meet the demand for intelligent and unmanned development in thermal power plants,an intelligent inspection system has been designed.This system efficiently performs inspection tasks and monitors the operational par...To meet the demand for intelligent and unmanned development in thermal power plants,an intelligent inspection system has been designed.This system efficiently performs inspection tasks and monitors the operational parameters of key equipment in real-time.The collected data is uploaded to the monitoring center,allowing operation and maintenance personnel to access equipment information promptly.Data analysis is used to provide fault warning and diagnosis for critical equipment.The system employs the Pure Pursuit algorithm,which effectively avoids obstacles and ensures path continuity and stability.Simulation results show that the Pure Pursuit algorithm significantly improves the navigation accuracy and task efficiency of the inspection robot,ensuring the reliability of thermal power plant inspections.展开更多
The environment of low-altitude urban airspace is complex and variable due to numerous obstacles,non-cooperative aircraft,and birds.Unmanned Aerial Vehicles(UAVs)leveraging environmental information to achieve three-d...The environment of low-altitude urban airspace is complex and variable due to numerous obstacles,non-cooperative aircraft,and birds.Unmanned Aerial Vehicles(UAVs)leveraging environmental information to achieve three-dimension collision-free trajectory planning is the prerequisite to ensure airspace security.However,the timely information of surrounding situation is difficult to acquire by UAVs,which further brings security risks.As a mature technology leveraged in traditional civil aviation,the Automatic Dependent Surveillance-Broadcast(ADS-B)realizes continuous surveillance of the information of aircraft.Consequently,we leverage ADS-B for surveillance and information broadcasting,and divide the aerial airspace into multiple sub-airspaces to improve flight safety in UAV trajectory planning.In detail,we propose the secure Sub-airSpaces Planning(SSP)algorithm and Particle Swarm Optimization Rapidly-exploring Random Trees(PSO-RRT)algorithm for the UAV trajectory planning in law-altitude airspace.The performance of the proposed algorithm is verified by simulations and the results show that SSP reduces both the maximum number of UAVs in the sub-airspace and the length of the trajectory,and PSO-RRT reduces the cost of UAV trajectory in the sub-airspace.展开更多
Non-contact debris removal methods are fuel-efficient in a single operation compared to contact-based strategies as spacecraft don’t need to match debris velocity.To comprehensively analyze this scheme,maneuvering sc...Non-contact debris removal methods are fuel-efficient in a single operation compared to contact-based strategies as spacecraft don’t need to match debris velocity.To comprehensively analyze this scheme,maneuvering schemes for maximum debris removal with minimum fuel consumption,including task assignment,sequence planning,and trajectory planning,must be formulated.The coupling between variables’dimensions and optimization results in task assignment poses challenges,as debris removal is repetitive and uncertain,leading to a vast search space.This paper proposes a novel Greedy Randomized Adaptive Search Procedure with Large Neighborhood and Crossover Mechanisms(GRASP-LNCM)to address this problem.The hybrid dynamic iteration mechanism improves computational efficiency and enhances the optimality of results.The model innovatively considers unsuccessful single removal by using a quantitative method to assess removal percentage.In addition,to improve the efficiency of sequence and trajectory planning,a Suboptimal Search Algorithm(SSA)based on the Lambert property and accelerated Multi-Revolution Lambert Problem(MRLP)solving strategy is established.Finally,a real Iridium-33 debris removal mission is studied.The simulation demonstrates that the proposed algorithm achieves state-of-the-art performance in several typical scenarios.Compared to the contact-based scheme,the new one is simpler,saving more fuel under certain conditions.展开更多
基金the Strategic Research Plan of the Centre for Marine Technology and Ocean Engineering(CENTEC),which is financed by the Portuguese Foundation for Science and Technology(Fundação para a Ciência e a Tecnologia FCT)under contract UIDB/UIDP/00134/2020.
文摘This study examines the methods to plan the development of offshore oilfields over the years,which are used to support the decision-making on the development of offshore oilfields.About 100 papers are analysed and categorised into different groups of main early-stage decisions.The present study stands in contrast to the contributions of the operations research and system engineering review articles,on the one hand,and the petroleum engineering review articles,on the other.This is because it does not focus on one methodological approach,nor does it limit the literature analysis by offshore oilfield characteristics.Consequently,the present analysis may offer valuable insights,for instance,by identifying environmental planning decisions as a recent yet highly significant concern that is currently being imposed on decision-making process.Thus,it is evident that the incorporation of safety criteria within the technical-economic decision-making process for the design of production systems would be a crucial requirement at development phase.
基金supported by the Ministry of Science and High Education of the Russian Federation by the grant 075-15-2022-1137supported by Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2025R323),Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘Hierarchical Task Network(HTN)planning is a powerful technique in artificial intelligence for handling complex problems by decomposing them into hierarchical task structures.However,achieving optimal solutions in HTN planning remains a challenge,especially in scenarios where traditional search algorithms struggle to navigate the vast solution space efficiently.This research proposes a novel technique to enhance HTN planning by integrating the Ant Colony Optimization(ACO)algorithm into the refinement process.The Ant System algorithm,inspired by the foraging behavior of ants,is well-suited for addressing optimization problems by efficiently exploring solution spaces.By incorporating ACO into the refinement phase of HTN planning,the authors aim to leverage its adaptive nature and decentralized decision-making to improve plan generation.This paper involves the development of a hybrid strategy called ACO-HTN,which combines HTN planning with ACO-based plan selection.This technique enables the system to adaptively refine plans by guiding the search towards optimal solutions.To evaluate the effectiveness of the proposed technique,this paper conducts empirical experiments on various domains and benchmark datasets.Our results demonstrate that the ACO-HTN strategy enhances the efficiency and effectiveness of HTN planning,outperforming traditional methods in terms of solution quality and computational performance.
文摘To improve the efficiency and accuracy of path planning for fan inspection tasks in thermal power plants,this paper proposes an intelligent inspection robot path planning scheme based on an improved A^(*)algorithm.The inspection robot utilizes multiple sensors to monitor key parameters of the fans,such as vibration,noise,and bearing temperature,and upload the data to the monitoring center.The robot’s inspection path employs the improved A^(*)algorithm,incorporating obstacle penalty terms,path reconstruction,and smoothing optimization techniques,thereby achieving optimal path planning for the inspection robot in complex environments.Simulation results demonstrate that the improved A^(*)algorithm significantly outperforms the traditional A^(*)algorithm in terms of total path distance,smoothness,and detour rate,effectively improving the execution efficiency of inspection tasks.
文摘Making plans is a good idea,but every one's schedule looks differe nt.You may have to talk about your plans before you're able to make some.It could sound like this:You ask,"Do you have plans this Friday night?"If the person already has plans,they may say,"I do.But I'm free on Saturday."If that day doesn't work for you,you can say,"I'm not available that day.How about Sunday after no on?"After you figure out the day and time,mark it on your calendar.
基金funded by the research project“BR24992947—Development of Robots,Scientific,Technical,and Software for Flexible Robotization and Industrial Automation(RPA)in Automotive Industrial Enterprises in Kazakhstan Using Artificial Intelligence”.
文摘Robotic manipulators increasingly operate in complex three-dimensional workspaces where accuracy and strict limits on position,velocity,and acceleration must be satisfied.Conventional geometric planners emphasize path smoothness but often ignore dynamic feasibility,motivating control-aware trajectory generation.This study presents a novel model predictive control(MPC)framework for three-dimensional trajectory planning of robotic manipulators that integrates second-order dynamic modeling and multi-objective parameter optimization.Unlike conventional interpolation techniques such as cubic splines,B-splines,and linear interpolation,which neglect physical constraints and system dynamics,the proposed method generates dynamically feasible trajectories by directly optimizing over acceleration inputs while minimizing both tracking error and control effort.A key innovation lies in the use of Pareto front analysis for tuning prediction horizon and sampling time,enabling a systematic balance between accuracy and motion smoothness.Comparative evaluation using simulated experiments demonstrates that the proposed MPC approach achieves a minimum mean absolute error(MAE)of 0.170 and reduces maximum acceleration to 0.0217,compared to 0.0385 in classical linear methods.The maximum deviation error was also reduced by approximately 27.4%relative to MPC configurations without tuned parameters.All experiments were conducted in a simulation environment,with computational times per control cycle consistently remaining below 20 milliseconds,indicating practical feasibility for real-time applications.Thiswork advances the state-of-the-art inMPC-based trajectory planning by offering a scalable and interpretable control architecture that meets physical constraints while optimizing motion efficiency,thus making it suitable for deployment in safety-critical robotic applications.
基金supported by the Government of the Northwest Territories in Canada and the John McMurry Research Chair in Environmental Geography at Wilfrid Laurier University.
文摘Climate change is increasingly affecting all aspects of protected areas management from changes of species ranges to visitor experiences.Due to these impacts,there is a need for managers to take more robust approaches to con-sidering the implications of climate change on the overall application and efficacy of protected areas management direction,including the achievement of the goals and objectives contained within management plans.Through a systematic and comprehensive content analysis approach,this study assesses the current extent to which climate change is considered in Canadian protected area management plans.Specifically,we evaluated 63 terrestrial protected area management plans against a set of climate robustness principles.Our content analysis revealed that climate change is currently not effectively factored into Canadian protected area management plans with an average climate robustness score of 18%.Climate robustness score was not found to be correlated with protected area size,International Union for the Conservation of Nature(IUCN)management classification,or jurisdictional authority.Certain climate robustness principles received higher scores across the management plans than oth-ers.For example,the principles of‘diverse knowledge sources’and‘addresses climate change’scored relatively highly whereas‘climate change vulnerability’and‘ecosystem integrity’received the lowest scores.The lack of integration of ecological integrity considerations in management plans was a particularly noteworthy deficiency considering that this guiding principle is the primary legislative objective of many national and sub-national protected areas in Canada.From this assessment,climate change needs to be more effectively and consistently integrated into protected area management plan development and coordinated across associated planning pro-cesses.We discuss the ways in which this can be achieved,for example,by integrating scenario planning into organizational management plan development processes.
文摘BACKGROUND Hepatobiliary surgery is complex and requires a thorough understanding of the liver’s anatomy,biliary system,and vasculature.Traditional imaging methods such as computed tomography(CT)and magnetic resonance imaging(MRI),although helpful,fail to provide three-dimensional(3D)relationships of these structures,which are critical for planning and executing complicated surgeries.AIM To explore the use of 3D imaging and virtual surgical planning(VSP)technologies to improve surgical accuracy,reduce complications,and enhance patient recovery in hepatobiliary surgeries.METHODS A comprehensive review of studies published between 2017 and 2024 was conducted through PubMed,Scopus,Google Scholar,and Web of Science.Studies selected focused on 3D imaging and VSP applications in hepatobiliary surgery,assessing surgical precision,complications,and patient outcomes.Thirty studies,including randomized controlled trials,cohort studies,and case reports,were included in the final analysis.RESULTS Various 3D imaging modalities,including multidetector CT,MRI,and 3D rotational angiography,provide high-resolution views of the liver’s vascular and biliary anatomy.VSP allows surgeons to simulate complex surgeries,improving preoperative planning and reducing complications like bleeding and bile leaks.Several studies have demonstrated improved surgical precision,reduced complications,and faster recovery times when 3D imaging and VSP were used in complex surgeries.CONCLUSION 3D imaging and VSP technologies significantly enhance the accuracy and outcomes of hepatobiliary surgeries by providing individualized preoperative planning.While promising,further research,particularly randomized controlled trials,is needed to standardize protocols and evaluate long-term efficacy.
文摘ln order to improve the level of investment promotion and redouble effortsto enhance services,on February l9th,the 2025 Action Plan for StabilizingForeign lnvestment was released,proposing 20 measures in four aspects.Cur-rently,with increasing uncertainties in the external environment,China facesmultple difficulties and challenges in attracting foreign investment.
文摘Spanish scholars decode China’s five-year planning as a strategic governance model that ensures long-term national development through continuity,popular participation,and adaptability,offering valuable insights for global governance.
基金funded by Vinnova,the Swedish Innovation Agency as a part of the Autoplant project(Dnr 2020-04202 and 2023-02747).
文摘Effective forest regeneration is essential for sustainable forestry practices.In Sweden,mechanical site preparation and manual planting is the dominating method,but sourcing labour for the physically demanding work is difficult.An autonomous scarifying and planting system(Autoplant)could meet the requirements of the forest industry and,for this,a tool for regeneration planning and routing is needed.The tool,Pathfinder,plans the regeneration and routes based on the harvested production(hpr)files,soil moisture and parent material maps,no-go areas(for culture or nature conservation),digital elevation models(DEM),and machine data(e.g.,working width,critical slope,time taken for different turn angles).The overall planting solution is either a set of capacity constrained routes or a continuous route and could be used for any planting machine as well as for traditional scarifiers as disc trenchers or mounders pulled by forwarders.Pathfinder was tested on eleven regeneration areas throughout Sweden,both with continuous routes and routes based on a carrying capacity of 1500 seedlings.The net operation area,species and seedling density suggestions were deemed relevant by expert judgement in the field.The routes provided by Pathfinder were compared with solutions given by two experienced drivers and a third solution based on the actual soil scarification at the site.Total driving distance did not differ significantly between the suggestions,but Pathfinder included less side-slope driving on steep slopes(≥27%or 15°)and medium slopes(15–27%).The chosen threshold value for steep slopes(where side-slope driving should be avoided)affects the routing,and a lower threshold means more turning and longer driving distance.Pathfinder is not only a tool for routing of planting machines,but also helps in planning of traditional regeneration by providing a more correct net area and tree species suggestions based on the growth of the previous stand.It also diminishes the risk of severe soil disturbance by excluding the wettest area in the planning.
文摘Compared with single-domain unmanned swarms,cross-domain unmanned swarms continue to face new challenges in terms of platform performance and constraints.In this paper,a joint unmanned swarm target assignment and mission trajectory planning method is proposed to meet the requirements of cross-domain unmanned swarm mission planning.Firstly,the different performances of cross-domain heterogeneous platforms and mission requirements of targets are characterised by using a collection of operational resources.Secondly,an algorithmic framework for joint target assignment and mission trajectory planning is proposed,in which the initial planning of the trajectory is performed in the target assignment phase,while the trajectory is further optimised afterwards.Next,the estimation of the distribution algorithms is combined with the genetic algorithm to solve the objective function.Finally,the algorithm is numerically simulated by specific cases.Simulation results indicate that the proposed algorithm can perform effective task assignment and trajectory planning for cross-domain unmanned swarms.Furthermore,the solution performance of the hybrid estimation of distribution algorithm(EDA)-genetic algorithm(GA)algorithm is better than that of GA and EDA.
文摘Based on the outcome-based education concept,the integrated teaching of professional courses for land space planning in the human geography and urban and rural planning majors was reformed and practiced.Focusing on the fundamental task of“establishing morality and cultivating people,”the reform of the teaching mode was proposed to clarify the industry needs,revise and improve the training program and teaching syllabus,innovate the teaching mode,and optimize the practical teaching resources and conditions.A new“multi-dimensional,interactive,and three-dimensional”teaching mode was constructed,and the integrated teaching method of enterprise projects,professional internships,and scientific research training was innovated,realizing the talent training mechanism of“demand-driven and integration of industry and education.”
文摘BACKGROUND Kidney transplantation is one of the most effective treatments for patients with end-stage renal disease.However,many regions face low deceased donor rates and limited ABO-compatible transplant availability,which increases reliance on living donors.These regional challenges necessitate the implementation of kidney paired donation(KPD)programs to overcome incompatibilities such as ABO mismatch or positive cross-matching,even when suitable and willing donors are available.AIM To evaluate the effectiveness of a single-center domino KPD model in both operational planning and clinical management processes and to assess its impact on clinical outcomes.METHODS Between April 2020 and January 2024,we retrospectively evaluated patients enrolled in our center’s domino kidney transplantation program.Donor-recipient pairs unable to proceed due to ABO incompatibility or positive cross-matching with their own living donors were included.Donors and recipients were assessed based on blood group compatibility,HLA tissue typing,and negative cross-match results.A specialized computer algorithm grouped patients into three-way,fourway,and five-way chains.All surgical procedures were performed on the same day at a single center.RESULTS A total of 169 kidney transplants were performed,forming 52 domino chains.These domino KPD transplants accounted for a notable proportion of our center’s overall transplant activity,which included both living donor kidney transplants and deceased donor transplants.Among these chains,the primary reasons for participation were ABO incompatibility(74%),positive cross-matching(10%),and the desire to improve HLA mismatch(16%).Improved HLA mismatch profiles and high graft survival(96%at 1 year,92%at 3 years)and patient survival(98%at 1 year,94%at 3 years)rates were observed,as well as low acute rejection episodes.CONCLUSION The single-center domino KPD model enhanced transplant opportunities for incompatible donor-recipient pairs while maintaining excellent clinical outcomes.By providing a framework that addresses regional challenges,improves operational efficiency,and optimizes clinical management,this model offers actionable insights to reduce waiting lists and improve patient outcomes.
基金supported by the National Natural Science Foundation of China(Grant No.42330205)the Open Fund of State Key Labora-tory of Remote Sensing Science and Beijing Engineering Research Center for Global Land Remote Sensing Products(Grant No.OF202206).
文摘China boasts over 10,000 native useful vascular plants(NUVPs),spanning eight families and serving twelve dis-tinct uses.Given the importance of NUVPs,widely-confirmed in-situ conservation policies,such as establishing nature reserves,have been broadly implemented to protect them.However,the effectiveness of in-situ conser-vation efforts for NUVPs in China remains uncertain.Highlighting the importance of multi-family and multi-use plants,this research identified the spatial distribution pattern and diversity hotspots of NUVPs,evaluated the in-situ conservation effectiveness and provided the future conservation priority scheme.The results revealed that the spatial concentration of NUVPs is predominantly in the southwestern lowlands of China(<3,000 m),peaking around 109°E and 25°N.Importantly,diversity hotspots exhibited a significant spatial mismatch(over 80%)with the National Nature Reserve(NNR)network.Only about 17.7%and 13.3%of these hotspots are protected by NNR initiatives for endemic and nonendemic species,respectively.Additionally,the proposed Plants Conserva-tion Effectiveness Index(PCEI)proved more representative in addressing the two main crises faced by the studied species-species loss and human pressure,and found a decline in conservation effectiveness as the number of uses increased.Finally,future conservation priorities based on the PCEI highlight the Nanling Mountains,Heng-duan Mountains,Jiuwandashan,and Qilian Mountains as highly prioritized regions requiring focused efforts to address the impacts of climate change.Conversely,in sparsely distributed regions experiencing increasing human pressure,it is imperative to mitigate the expanding human footprint.
文摘To meet the demand for intelligent and unmanned development in thermal power plants,an intelligent inspection system has been designed.This system efficiently performs inspection tasks and monitors the operational parameters of key equipment in real-time.The collected data is uploaded to the monitoring center,allowing operation and maintenance personnel to access equipment information promptly.Data analysis is used to provide fault warning and diagnosis for critical equipment.The system employs the Pure Pursuit algorithm,which effectively avoids obstacles and ensures path continuity and stability.Simulation results show that the Pure Pursuit algorithm significantly improves the navigation accuracy and task efficiency of the inspection robot,ensuring the reliability of thermal power plant inspections.
基金supported by the National Key R&D Program of China(No.2022YFB3104502)the National Natural Science Foundation of China(No.62301251)+2 种基金the Natural Science Foundation of Jiangsu Province of China under Project(No.BK20220883)the open research fund of National Mobile Communications Research Laboratory,Southeast University,China(No.2024D04)the Young Elite Scientists Sponsorship Program by CAST(No.2023QNRC001).
文摘The environment of low-altitude urban airspace is complex and variable due to numerous obstacles,non-cooperative aircraft,and birds.Unmanned Aerial Vehicles(UAVs)leveraging environmental information to achieve three-dimension collision-free trajectory planning is the prerequisite to ensure airspace security.However,the timely information of surrounding situation is difficult to acquire by UAVs,which further brings security risks.As a mature technology leveraged in traditional civil aviation,the Automatic Dependent Surveillance-Broadcast(ADS-B)realizes continuous surveillance of the information of aircraft.Consequently,we leverage ADS-B for surveillance and information broadcasting,and divide the aerial airspace into multiple sub-airspaces to improve flight safety in UAV trajectory planning.In detail,we propose the secure Sub-airSpaces Planning(SSP)algorithm and Particle Swarm Optimization Rapidly-exploring Random Trees(PSO-RRT)algorithm for the UAV trajectory planning in law-altitude airspace.The performance of the proposed algorithm is verified by simulations and the results show that SSP reduces both the maximum number of UAVs in the sub-airspace and the length of the trajectory,and PSO-RRT reduces the cost of UAV trajectory in the sub-airspace.
基金co-supported by the National Natural Science Foundation of China(Nos.U23B6001,62273118,12150008)the Fundamental Research Funds for the Central Universities,China(No.2023FRFK02043)+1 种基金the Natural Science Foundation of Heilongjiang Province,China(No.LH2022F023)China Aerospace Science and Technology Corporation Youth Talent Support Program.
文摘Non-contact debris removal methods are fuel-efficient in a single operation compared to contact-based strategies as spacecraft don’t need to match debris velocity.To comprehensively analyze this scheme,maneuvering schemes for maximum debris removal with minimum fuel consumption,including task assignment,sequence planning,and trajectory planning,must be formulated.The coupling between variables’dimensions and optimization results in task assignment poses challenges,as debris removal is repetitive and uncertain,leading to a vast search space.This paper proposes a novel Greedy Randomized Adaptive Search Procedure with Large Neighborhood and Crossover Mechanisms(GRASP-LNCM)to address this problem.The hybrid dynamic iteration mechanism improves computational efficiency and enhances the optimality of results.The model innovatively considers unsuccessful single removal by using a quantitative method to assess removal percentage.In addition,to improve the efficiency of sequence and trajectory planning,a Suboptimal Search Algorithm(SSA)based on the Lambert property and accelerated Multi-Revolution Lambert Problem(MRLP)solving strategy is established.Finally,a real Iridium-33 debris removal mission is studied.The simulation demonstrates that the proposed algorithm achieves state-of-the-art performance in several typical scenarios.Compared to the contact-based scheme,the new one is simpler,saving more fuel under certain conditions.
