为提高有源电力滤波器(Active Power Filter, APF)的补偿性能,提出了一种基于双DSP的三电平APF控制器,改善了资源分配,主DSP负责负载电流采样、补偿电流采样、直流侧电压采样、谐波及无功补偿电流提取、电流跟踪控制运算、PWM波调制等工...为提高有源电力滤波器(Active Power Filter, APF)的补偿性能,提出了一种基于双DSP的三电平APF控制器,改善了资源分配,主DSP负责负载电流采样、补偿电流采样、直流侧电压采样、谐波及无功补偿电流提取、电流跟踪控制运算、PWM波调制等工作,辅DSP负责分担部分运算和信号采样,包括谐波运算、电网电压采样、触摸屏显示、断电数据存储等,2块DSP之间通过双端口随机存储器RAM通信;更加合理地分配了软件任务,提高了双DSP并行运算能力。并且在三电平APF实物中进行了验证,可实现开关频率20 kHz,电网电流畸变率可以从15%治理为2%,谐波滤除率达86.7%,具有良好的谐波滤除能力。展开更多
This study proposes a novel approach to optimizing individual work schedules for book digitization using mixed-integer programming (MIP). By leveraging the power of MIP solvers, we aimed to minimize the overall digiti...This study proposes a novel approach to optimizing individual work schedules for book digitization using mixed-integer programming (MIP). By leveraging the power of MIP solvers, we aimed to minimize the overall digitization time while considering various constraints and process dependencies. The book digitization process involves three key steps: cutting, scanning, and binding. Each step has specific requirements and limitations such as the number of pages that can be processed simultaneously and potential bottlenecks. To address these complexities, we formulate the problem as a one-machine job shop scheduling problem with additional constraints to capture the unique characteristics of book digitization. We conducted a series of experiments to evaluate the performance of our proposed approach. By comparing the optimized schedules with the baseline approach, we demonstrated significant reductions in the overall processing time. In addition, we analyzed the impact of different weighting schemes on the optimization results, highlighting the importance of identifying and prioritizing critical processes. Our findings suggest that MIP-based optimization can be a valuable tool for improving the efficiency of individual work schedules, even in seemingly simple tasks, such as book digitization. By carefully considering specific constraints and objectives, we can save time and leverage resources by carefully considering specific constraints and objectives.展开更多
The construction projects’ dynamic and interconnected nature requires a comprehensive understanding of complexity during pre-construction. Traditional tools such as Gantt charts, CPM, and PERT often overlook uncertai...The construction projects’ dynamic and interconnected nature requires a comprehensive understanding of complexity during pre-construction. Traditional tools such as Gantt charts, CPM, and PERT often overlook uncertainties. This study identifies 20 complexity factors through expert interviews and literature, categorising them into six groups. The Analytical Hierarchy Process evaluated the significance of different factors, establishing their corresponding weights to enhance adaptive project scheduling. A system dynamics (SD) model is developed and tested to evaluate the dynamic behaviour of identified complexity factors. The model simulates the impact of complexity on total project duration (TPD), revealing significant deviations from initial deterministic estimates. Data collection and analysis for reliability tests, including normality and Cronbach alpha, to validate the model’s components and expert feedback. Sensitivity analysis confirmed a positive relationship between complexity and project duration, with higher complexity levels resulting in increased TPD. This relationship highlights the inadequacy of static planning approaches and underscores the importance of addressing complexity dynamically. The study provides a framework for enhancing planning systems through system dynamics and recommends expanding the model to ensure broader applicability in diverse construction projects.展开更多
Objective:To understand the current situation of career planning awareness and readiness of freshman medical students with a background in digital medicine,and to provide references for optimizing the medical educatio...Objective:To understand the current situation of career planning awareness and readiness of freshman medical students with a background in digital medicine,and to provide references for optimizing the medical education system and career guidance.Methods:A cross-sectional study was conducted on freshman medical students at a university in Yunnan Province using questionnaire survey.Results:A total of 272 questionnaires were distributed and 264 valid questionnaires were returned,yielding an effective response rate of 97.10%.The average score of digital medical awareness of freshman medical students was(70.50±8.81),and 63.63%of the students had a high awareness(score≧70);The average score of career planning awareness and readiness of freshman medical students was(91.76±14.87),and 60.63%of students had high awareness and readiness(score≧90).Pearson correlation analysis showed that the total score of digital medical awareness was positively correlated with the total score of career planning awareness and readiness(r=0.13,P<0.05).Conclusion:Freshman medical students’career planning awareness and readiness are generally good,but their practical application of digital medical-related skills still needs improvement.It is suggested that schools strengthen the integration of interdisciplinary curriculum,introduce digital vocational training modules,and formulate differentiated guidance strategies for different majors to enhance students’professional competitiveness in the digital medical era.展开更多
Village revitalization is a major development strategy in China,where village planning plays as its critical component.Taking village planning of De’an County in Jiangxi Province as an example,this paper explored the...Village revitalization is a major development strategy in China,where village planning plays as its critical component.Taking village planning of De’an County in Jiangxi Province as an example,this paper explored the significant importance of village planning in promoting rural revitalization along with its corresponding promote mechanisms.Through in-depth research on the detailed situation of village planning and implementation in Jiangxi,this paper summarized that some challenges exist,including backward planning,poor planning consciousness,difficulties in planning implementation.Based on these findings,the paper analyzed the challenges of village land resource scarcity,village images lacking in uniqueness features,and insufficient rural infrastructure construction.Furthermore,it proposed strategies such as taking the lead in planning from the beginning,advancing practical implementation at a high level,adhering to bottom-line thinking,and coordinating high-quality rural land protection and development,applying strategies such as ecological and pleasant living,building villages suitable for living and working,and construction of beautiful countryside,aiming to provide valuable reference for related research fields.展开更多
Objective:This study aimed to explore the readiness for advance care planning(ACP)among older adults in Macao’s day service centers and investigate the influencing factors.Methods:A cross-sectional study was conducte...Objective:This study aimed to explore the readiness for advance care planning(ACP)among older adults in Macao’s day service centers and investigate the influencing factors.Methods:A cross-sectional study was conducted from October to December 2022 using a convenience sampling method.A total of 312 older adults were selected from 13 day service centers for older adults in Macao,China.The Advance Care Planning Acceptance Questionnaire and the Family Adaptation,Partnership,Growth,Affection,Resolve(APGAR)Scale were used to survey the older adults.Results:A total of 306 older adults completed the survey.The score for advance care planning readiness was 65.55±10.69,and 59.5%of participants(n=182)were willing to participate in ACP.The family function score was 7.24±2.51,while 70.3%of participants were from a highly functional family.The higher family function indicating a higher readiness for advance care planning(r=0.396,P<0.001).The multiple linear regression analysis indicated that the variables“age,”“knowledge of ACP,”“experience with ACP,”and“received resuscitation of yourself,relatives or friends”combined with“family function”can influence advance care planning readiness among older adults(R^(2)=0.317,F=27.898,P<0.001).Conclusions:Older adults in Macao’s day service centers were willing to engage in ACP.The importance of family involvement is highlighted in the ACP readiness.Health education and improved family communication are vital for promoting ACP,which ensures individuals receive care when they lack the capacity to make that choice.Additionally,healthcare professionals should enhance communication and education with older adults during the medical care process.展开更多
Legged robots have always been a focal point of research for scholars domestically and internationally.Compared to other types of robots,quadruped robots exhibit superior balance and stability,enabling them to adapt e...Legged robots have always been a focal point of research for scholars domestically and internationally.Compared to other types of robots,quadruped robots exhibit superior balance and stability,enabling them to adapt effectively to diverse environments and traverse rugged terrains.This makes them well-suited for applications such as search and rescue,exploration,and transportation,with strong environmental adaptability,high flexibility,and broad application prospects.This paper discusses the current state of research on quadruped robots in terms of development status,gait trajectory planning methods,motion control strategies,reinforcement learning applications,and control algorithm integration.It highlights advancements in modeling,optimization,control,and data-driven approaches.The study identifies the adoption of efficient gait planning algorithms,the integration of reinforcement learning-based control technologies,and data-driven methods as key directions for the development of quadruped robots.The aim is to provide theoretical references for researchers in the field of quadruped robotics.展开更多
Despite its immense potential,the application of digital twin technology in real industrial scenarios still faces numerous challenges.This study focuses on industrial assembly lines in sectors such as microelectronics...Despite its immense potential,the application of digital twin technology in real industrial scenarios still faces numerous challenges.This study focuses on industrial assembly lines in sectors such as microelectronics,pharmaceuticals,and food packaging,where precision and speed are paramount,applying digital twin technology to the robotic assembly process.The innovation of this research lies in the development of a digital twin architecture and system for Delta robots that is suitable for real industrial environments.Based on this system,a deep reinforcement learning algorithm for obstacle avoidance path planning in Delta robots has been developed,significantly enhancing learning efficiency through an improved intermediate reward mechanism.Experiments on communication and interaction between the digital twin system and the physical robot validate the effectiveness of this method.The system not only enhances the integration of digital twin technology,deep reinforcement learning and robotics,offering an efficient solution for path planning and target grasping inDelta robots,but also underscores the transformative potential of digital twin technology in intelligent manufacturing,with extensive applicability across diverse industrial domains.展开更多
The global demand for effective skin injury treatments has prompted the exploration of tissue engineering solutions.While three-dimensional(3D)bioprinting has shown promise,challenges persist with respect to achieving...The global demand for effective skin injury treatments has prompted the exploration of tissue engineering solutions.While three-dimensional(3D)bioprinting has shown promise,challenges persist with respect to achieving timely and compatible solutions to treat diverse skin injuries.In situ bioprinting has emerged as a key new technology,since it reduces risks during the implantation of printed scaffolds and demonstrates superior therapeutic effects.However,maintaining printing fidelity during in situ bioprinting remains a critical challenge,particularly with respect to model layering and path planning.This study proposes a novel optimization-based conformal path planning strategy for in situ bioprinting-based repair of complex skin injuries.This strategy employs constrained optimization to identify optimal waypoints on a point cloud-approximated curved surface,thereby ensuring a high degree of similarity between predesigned planar and surface-mapped 3D paths.Furthermore,this method is applicable for skin wound treatments,since it generates 3D-equidistant zigzag curves along surface tangents and enables multi-layer conformal path planning to facilitate the treatment of volumetric injuries.Furthermore,the proposed algorithm was found to be a feasible and effective treatment in a murine back injury model as well as in other complex models,thereby showcasing its potential to guide in situ bioprinting,enhance bioprinting fidelity,and facilitate improvement of clinical outcomes.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
An improved version of the sparse A^(*)algorithm is proposed to address the common issue of excessive expansion of nodes and failure to consider current ship status and parameters in traditional path planning algorith...An improved version of the sparse A^(*)algorithm is proposed to address the common issue of excessive expansion of nodes and failure to consider current ship status and parameters in traditional path planning algorithms.This algorithm considers factors such as initial position and orientation of the ship,safety range,and ship draft to determine the optimal obstacle-avoiding route from the current to the destination point for ship planning.A coordinate transformation algorithm is also applied to convert commonly used latitude and longitude coordinates of ship travel paths to easily utilized and analyzed Cartesian coordinates.The algorithm incorporates a hierarchical chart processing algorithm to handle multilayered chart data.Furthermore,the algorithm considers the impact of ship length on grid size and density when implementing chart gridification,adjusting the grid size and density accordingly based on ship length.Simulation results show that compared to traditional path planning algorithms,the sparse A^(*)algorithm reduces the average number of path points by 25%,decreases the average maximum storage node number by 17%,and raises the average path turning angle by approximately 10°,effectively improving the safety of ship planning paths.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
Rational distribution network planning optimizes power flow distribution,reduces grid stress,enhances voltage quality,promotes renewable energy utilization,and reduces costs.This study establishes a distribution netwo...Rational distribution network planning optimizes power flow distribution,reduces grid stress,enhances voltage quality,promotes renewable energy utilization,and reduces costs.This study establishes a distribution network planning model incorporating distributed wind turbines(DWT),distributed photovoltaics(DPV),and energy storage systems(ESS).K-means++is employed to partition the distribution network based on electrical distance.Considering the spatiotemporal correlation of distributed generation(DG)outputs in the same region,a joint output model of DWT and DPV is developed using the Frank-Copula.Due to the model’s high dimensionality,multiple constraints,and mixed-integer characteristics,bilevel programming theory is utilized to structure the model.The model is solved using a mixed-integer particle swarmoptimization algorithm(MIPSO)to determine the optimal location and capacity of DG and ESS integrated into the distribution network to achieve the best economic benefits and operation quality.The proposed bilevel planning method for distribution networks is validated through simulations on the modified IEEE 33-bus system.The results demonstrate significant improvements,with the proposedmethod reducing the annual comprehensive cost by 41.65%and 13.98%,respectively,compared to scenarios without DG and ESS or with only DG integration.Furthermore,it reduces the daily average voltage deviation by 24.35%and 10.24%and daily network losses by 55.72%and 35.71%.展开更多
文摘为提高有源电力滤波器(Active Power Filter, APF)的补偿性能,提出了一种基于双DSP的三电平APF控制器,改善了资源分配,主DSP负责负载电流采样、补偿电流采样、直流侧电压采样、谐波及无功补偿电流提取、电流跟踪控制运算、PWM波调制等工作,辅DSP负责分担部分运算和信号采样,包括谐波运算、电网电压采样、触摸屏显示、断电数据存储等,2块DSP之间通过双端口随机存储器RAM通信;更加合理地分配了软件任务,提高了双DSP并行运算能力。并且在三电平APF实物中进行了验证,可实现开关频率20 kHz,电网电流畸变率可以从15%治理为2%,谐波滤除率达86.7%,具有良好的谐波滤除能力。
文摘This study proposes a novel approach to optimizing individual work schedules for book digitization using mixed-integer programming (MIP). By leveraging the power of MIP solvers, we aimed to minimize the overall digitization time while considering various constraints and process dependencies. The book digitization process involves three key steps: cutting, scanning, and binding. Each step has specific requirements and limitations such as the number of pages that can be processed simultaneously and potential bottlenecks. To address these complexities, we formulate the problem as a one-machine job shop scheduling problem with additional constraints to capture the unique characteristics of book digitization. We conducted a series of experiments to evaluate the performance of our proposed approach. By comparing the optimized schedules with the baseline approach, we demonstrated significant reductions in the overall processing time. In addition, we analyzed the impact of different weighting schemes on the optimization results, highlighting the importance of identifying and prioritizing critical processes. Our findings suggest that MIP-based optimization can be a valuable tool for improving the efficiency of individual work schedules, even in seemingly simple tasks, such as book digitization. By carefully considering specific constraints and objectives, we can save time and leverage resources by carefully considering specific constraints and objectives.
文摘The construction projects’ dynamic and interconnected nature requires a comprehensive understanding of complexity during pre-construction. Traditional tools such as Gantt charts, CPM, and PERT often overlook uncertainties. This study identifies 20 complexity factors through expert interviews and literature, categorising them into six groups. The Analytical Hierarchy Process evaluated the significance of different factors, establishing their corresponding weights to enhance adaptive project scheduling. A system dynamics (SD) model is developed and tested to evaluate the dynamic behaviour of identified complexity factors. The model simulates the impact of complexity on total project duration (TPD), revealing significant deviations from initial deterministic estimates. Data collection and analysis for reliability tests, including normality and Cronbach alpha, to validate the model’s components and expert feedback. Sensitivity analysis confirmed a positive relationship between complexity and project duration, with higher complexity levels resulting in increased TPD. This relationship highlights the inadequacy of static planning approaches and underscores the importance of addressing complexity dynamically. The study provides a framework for enhancing planning systems through system dynamics and recommends expanding the model to ensure broader applicability in diverse construction projects.
文摘Objective:To understand the current situation of career planning awareness and readiness of freshman medical students with a background in digital medicine,and to provide references for optimizing the medical education system and career guidance.Methods:A cross-sectional study was conducted on freshman medical students at a university in Yunnan Province using questionnaire survey.Results:A total of 272 questionnaires were distributed and 264 valid questionnaires were returned,yielding an effective response rate of 97.10%.The average score of digital medical awareness of freshman medical students was(70.50±8.81),and 63.63%of the students had a high awareness(score≧70);The average score of career planning awareness and readiness of freshman medical students was(91.76±14.87),and 60.63%of students had high awareness and readiness(score≧90).Pearson correlation analysis showed that the total score of digital medical awareness was positively correlated with the total score of career planning awareness and readiness(r=0.13,P<0.05).Conclusion:Freshman medical students’career planning awareness and readiness are generally good,but their practical application of digital medical-related skills still needs improvement.It is suggested that schools strengthen the integration of interdisciplinary curriculum,introduce digital vocational training modules,and formulate differentiated guidance strategies for different majors to enhance students’professional competitiveness in the digital medical era.
文摘Village revitalization is a major development strategy in China,where village planning plays as its critical component.Taking village planning of De’an County in Jiangxi Province as an example,this paper explored the significant importance of village planning in promoting rural revitalization along with its corresponding promote mechanisms.Through in-depth research on the detailed situation of village planning and implementation in Jiangxi,this paper summarized that some challenges exist,including backward planning,poor planning consciousness,difficulties in planning implementation.Based on these findings,the paper analyzed the challenges of village land resource scarcity,village images lacking in uniqueness features,and insufficient rural infrastructure construction.Furthermore,it proposed strategies such as taking the lead in planning from the beginning,advancing practical implementation at a high level,adhering to bottom-line thinking,and coordinating high-quality rural land protection and development,applying strategies such as ecological and pleasant living,building villages suitable for living and working,and construction of beautiful countryside,aiming to provide valuable reference for related research fields.
文摘Objective:This study aimed to explore the readiness for advance care planning(ACP)among older adults in Macao’s day service centers and investigate the influencing factors.Methods:A cross-sectional study was conducted from October to December 2022 using a convenience sampling method.A total of 312 older adults were selected from 13 day service centers for older adults in Macao,China.The Advance Care Planning Acceptance Questionnaire and the Family Adaptation,Partnership,Growth,Affection,Resolve(APGAR)Scale were used to survey the older adults.Results:A total of 306 older adults completed the survey.The score for advance care planning readiness was 65.55±10.69,and 59.5%of participants(n=182)were willing to participate in ACP.The family function score was 7.24±2.51,while 70.3%of participants were from a highly functional family.The higher family function indicating a higher readiness for advance care planning(r=0.396,P<0.001).The multiple linear regression analysis indicated that the variables“age,”“knowledge of ACP,”“experience with ACP,”and“received resuscitation of yourself,relatives or friends”combined with“family function”can influence advance care planning readiness among older adults(R^(2)=0.317,F=27.898,P<0.001).Conclusions:Older adults in Macao’s day service centers were willing to engage in ACP.The importance of family involvement is highlighted in the ACP readiness.Health education and improved family communication are vital for promoting ACP,which ensures individuals receive care when they lack the capacity to make that choice.Additionally,healthcare professionals should enhance communication and education with older adults during the medical care process.
基金funded by the Natural Science Basis Research Plan in Shaanxi Province of China(Program No.2023-JC-QN-0659)General Specialized Scientific Research Program of the Shaanxi Provincial Department of Education(Program 23JK0349).
文摘Legged robots have always been a focal point of research for scholars domestically and internationally.Compared to other types of robots,quadruped robots exhibit superior balance and stability,enabling them to adapt effectively to diverse environments and traverse rugged terrains.This makes them well-suited for applications such as search and rescue,exploration,and transportation,with strong environmental adaptability,high flexibility,and broad application prospects.This paper discusses the current state of research on quadruped robots in terms of development status,gait trajectory planning methods,motion control strategies,reinforcement learning applications,and control algorithm integration.It highlights advancements in modeling,optimization,control,and data-driven approaches.The study identifies the adoption of efficient gait planning algorithms,the integration of reinforcement learning-based control technologies,and data-driven methods as key directions for the development of quadruped robots.The aim is to provide theoretical references for researchers in the field of quadruped robotics.
基金supported in part by the National Natural Science Foundation of China under Grants 62303098 and 62173073in part by China Postdoctoral Science Foundation under Grant 2022M720679+1 种基金in part by the Central University Basic Research Fund of China under Grant N2304021in part by the Liaoning Provincial Science and Technology Plan Project-Technology Innovation Guidance of the Science and Technology Department under Grant 2023JH1/10400011.
文摘Despite its immense potential,the application of digital twin technology in real industrial scenarios still faces numerous challenges.This study focuses on industrial assembly lines in sectors such as microelectronics,pharmaceuticals,and food packaging,where precision and speed are paramount,applying digital twin technology to the robotic assembly process.The innovation of this research lies in the development of a digital twin architecture and system for Delta robots that is suitable for real industrial environments.Based on this system,a deep reinforcement learning algorithm for obstacle avoidance path planning in Delta robots has been developed,significantly enhancing learning efficiency through an improved intermediate reward mechanism.Experiments on communication and interaction between the digital twin system and the physical robot validate the effectiveness of this method.The system not only enhances the integration of digital twin technology,deep reinforcement learning and robotics,offering an efficient solution for path planning and target grasping inDelta robots,but also underscores the transformative potential of digital twin technology in intelligent manufacturing,with extensive applicability across diverse industrial domains.
基金supported in part by the National Natural Science Foundation of China(Nos.52205532 and 624B2077)the National Key Research and Development Program of China(No.2023YFB4302003).
文摘The global demand for effective skin injury treatments has prompted the exploration of tissue engineering solutions.While three-dimensional(3D)bioprinting has shown promise,challenges persist with respect to achieving timely and compatible solutions to treat diverse skin injuries.In situ bioprinting has emerged as a key new technology,since it reduces risks during the implantation of printed scaffolds and demonstrates superior therapeutic effects.However,maintaining printing fidelity during in situ bioprinting remains a critical challenge,particularly with respect to model layering and path planning.This study proposes a novel optimization-based conformal path planning strategy for in situ bioprinting-based repair of complex skin injuries.This strategy employs constrained optimization to identify optimal waypoints on a point cloud-approximated curved surface,thereby ensuring a high degree of similarity between predesigned planar and surface-mapped 3D paths.Furthermore,this method is applicable for skin wound treatments,since it generates 3D-equidistant zigzag curves along surface tangents and enables multi-layer conformal path planning to facilitate the treatment of volumetric injuries.Furthermore,the proposed algorithm was found to be a feasible and effective treatment in a murine back injury model as well as in other complex models,thereby showcasing its potential to guide in situ bioprinting,enhance bioprinting fidelity,and facilitate improvement of clinical outcomes.
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 Tianjin University of Technology Graduate R esearch Innovation Project(YJ2281).
文摘An improved version of the sparse A^(*)algorithm is proposed to address the common issue of excessive expansion of nodes and failure to consider current ship status and parameters in traditional path planning algorithms.This algorithm considers factors such as initial position and orientation of the ship,safety range,and ship draft to determine the optimal obstacle-avoiding route from the current to the destination point for ship planning.A coordinate transformation algorithm is also applied to convert commonly used latitude and longitude coordinates of ship travel paths to easily utilized and analyzed Cartesian coordinates.The algorithm incorporates a hierarchical chart processing algorithm to handle multilayered chart data.Furthermore,the algorithm considers the impact of ship length on grid size and density when implementing chart gridification,adjusting the grid size and density accordingly based on ship length.Simulation results show that compared to traditional path planning algorithms,the sparse A^(*)algorithm reduces the average number of path points by 25%,decreases the average maximum storage node number by 17%,and raises the average path turning angle by approximately 10°,effectively improving the safety of ship planning paths.
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.
基金This research was funded by“Chunhui Program”Collaborative Scientific Research Project of the Ministry of Education of the People’s Republic of China(Project No.HZKY20220242)the S&T Program of Hebei(Project No.225676163GH).
文摘Rational distribution network planning optimizes power flow distribution,reduces grid stress,enhances voltage quality,promotes renewable energy utilization,and reduces costs.This study establishes a distribution network planning model incorporating distributed wind turbines(DWT),distributed photovoltaics(DPV),and energy storage systems(ESS).K-means++is employed to partition the distribution network based on electrical distance.Considering the spatiotemporal correlation of distributed generation(DG)outputs in the same region,a joint output model of DWT and DPV is developed using the Frank-Copula.Due to the model’s high dimensionality,multiple constraints,and mixed-integer characteristics,bilevel programming theory is utilized to structure the model.The model is solved using a mixed-integer particle swarmoptimization algorithm(MIPSO)to determine the optimal location and capacity of DG and ESS integrated into the distribution network to achieve the best economic benefits and operation quality.The proposed bilevel planning method for distribution networks is validated through simulations on the modified IEEE 33-bus system.The results demonstrate significant improvements,with the proposedmethod reducing the annual comprehensive cost by 41.65%and 13.98%,respectively,compared to scenarios without DG and ESS or with only DG integration.Furthermore,it reduces the daily average voltage deviation by 24.35%and 10.24%and daily network losses by 55.72%and 35.71%.
