Energy-saving buildings(ESBs)are an emerging green technology that can significantly reduce building-associated cooling and heating energy consumption,catering to the desire for carbon neutrality and sustainable devel...Energy-saving buildings(ESBs)are an emerging green technology that can significantly reduce building-associated cooling and heating energy consumption,catering to the desire for carbon neutrality and sustainable development of society.Smart photovoltaic windows(SPWs)offer a promising platform for designing ESBs because they present the capability to regulate and harness solar energy.With frequent outbreaks of extreme weather all over the world,the achievement of exceptional energy-saving effect under different weather conditions is an inevitable trend for the development of ESBs but is hardly achieved via existing SPWs.Here,we substantially reduce the driving voltage of polymerdispersed liquid crystals(PDLCs)by 28.1%via molecular engineering while maintaining their high solar transmittance(T_(sol)=83.8%,transparent state)and solar modulating ability(ΔT_(sol)=80.5%).By the assembly of perovskite solar cell and a broadband thermal-managing unit encompassing the electrical-responsive PDLCs,transparent high-emissivity SiO_(2) passive radiation-cooling,and Ag low-emissivity layers possesses,we present a tri-band regulation and split-type SPW possessing superb energy-saving effect in all-season.The perovskite solar cell can produce the electric power to stimulate the electrical-responsive behavior of the PDLCs,endowing the SPWs zero-energy input solar energy regulating characteristic,and compensate the daily energy consumption needed for ESBs.Moreover,the scalable manufacturing technology holds a great potential for the real-world applications.展开更多
Joining dissimilar materials encounters significant engineering challenges due to the contrast in material properties that makes conventional welding not feasible.Magnetic Pulse Welding(MPW)offers a solidstate joining...Joining dissimilar materials encounters significant engineering challenges due to the contrast in material properties that makes conventional welding not feasible.Magnetic Pulse Welding(MPW)offers a solidstate joining technique that overcomes these issues by using impact to create strong bonds without melting the substrate materials.This study investigates the weldability of aluminum alloy Al-5754 with Al-7075 and MARS 380 steel,used in armouring solutions of defense systems,by the use of MPW.In this work,weldability windows are investigated by varying standoff distances between the coating material and its substrate(0.25-4.5 mm)and discharge energies(5-13 kJ)with both O-shape and U-shape inductors.Mechanical strength of the welded joints were assessed through single lap shear tests,identifying optimal welding parameters.Then,the velocity profiles of the flyer plates were measured using heterodyne velocimetry to understand the dynamics of the impact.Then,substructures assembled with the optimal welding conditions were subjected to ballistic testing using 7.62 mm×51 mm NATO and 9 mm×19 mm Parabellum munitions to evaluate the resilience of the welds under ballistic impact.The outcomes demonstrate that MPW effectively joins Al-5754 with both Al-7075 and MARS 380,producing robust welds capable of withstanding ballistic impacts under certain conditions.This research advances the application of MPW in lightweight ballistic protection of defense systems,contributing to the development of more resilient and lighter protective structures.展开更多
Preterm birth(PTB)is defined as delivery before 37 weeks of gestation.PTB is associated with increased cardiovascular risk,neurodevelopmental disorders,and other diseases in infancy,childhood,and adulthood[1].Globally...Preterm birth(PTB)is defined as delivery before 37 weeks of gestation.PTB is associated with increased cardiovascular risk,neurodevelopmental disorders,and other diseases in infancy,childhood,and adulthood[1].Globally,approximately 15 million PTB cases are reported annually,posing a huge burden on individual families and the community economy[2].In the context of climate warming,O_(3) pollution has continuously increased in many countries in recent years,including China;therefore,scientific communities and government agencies must strive to mitigate ozone pollution.展开更多
Persistent flows are defined as network flows that persist over multiple time intervals and continue to exhibit activity over extended periods,which are critical for identifying long-term behaviors and subtle security...Persistent flows are defined as network flows that persist over multiple time intervals and continue to exhibit activity over extended periods,which are critical for identifying long-term behaviors and subtle security threats.Programmable switches provide line-rate packet processing to meet the requirements of high-speed network environments,yet they are fundamentally limited in computational and memory resources.Accurate and memoryefficient persistent flow detection on programmable switches is therefore essential.However,existing approaches often rely on fixed-window sketches or multiple sketches instances,which either suffer from insufficient temporal precision or incur substantial memory overhead,making them ineffective on programmable switches.To address these challenges,we propose SP-Sketch,an innovative sliding-window-based sketch that leverages a probabilistic update mechanism to emulate slot expiration without maintaining multiple sketch instances.This innovative design significantly reduces memory consumption while preserving high detection accuracy across multiple time intervals.We provide rigorous theoretical analyses of the estimation errors,deriving precise error bounds for the proposed method,and validate our approach through comprehensive implementations on both P4 hardware switches(with Intel Tofino ASIC)and software switches(i.e.,BMv2).Experimental evaluations using real-world traffic traces demonstrate that SP-Sketch outperforms traditional methods,improving accuracy by up to 20%over baseline sliding window approaches and enhancing recall by 5%compared to non-sliding alternatives.Furthermore,SP-Sketch achieves a significant reduction in memory utilization,reducing memory consumption by up to 65%compared to traditional methods,while maintaining a robust capability to accurately track persistent flow behavior over extended time periods.展开更多
Memory is a cognitive process through which past experiences are encoded,stored,and retrieved,playing a crucial role in intelligent behavior.It is well established that the hippocampus continues to reactivate memories...Memory is a cognitive process through which past experiences are encoded,stored,and retrieved,playing a crucial role in intelligent behavior.It is well established that the hippocampus continues to reactivate memories for several days after learning,and this process primarily occurs during sleep[1,2].The prevailing view suggests that sharp-wave ripples(SWRs)during non-rapid eye movement(NREM)sleep serve as key electrophysiological signatures of memory replay[3,4].However,only a small portion of SWRs contain memory replay[5].The direct relationship among SWRs,memory replay,and memory consolidation remains an open question.Another unresolved issue is how the hippocampus simultaneously reactivates both new and old memories while preventing interference.展开更多
The deep convolutional neural network U-net has been introduced into adaptive subtraction, which is a critical step in effectively suppressing seismic multiples. The U-net approach has higher precision than the tradit...The deep convolutional neural network U-net has been introduced into adaptive subtraction, which is a critical step in effectively suppressing seismic multiples. The U-net approach has higher precision than the traditional linear regression approach. However, the existing 2D U-net approach with 2D data windows can not deal with elaborate discrepancies between the actual and simulated multiples along the gather direction. It may lead to erroneous preservation of primaries or generate obvious vestigial multiples, especially in complex media. To further enhance the multiple suppression accuracy, we present an adaptive subtraction approach utilizing 3D U-net architecture, which can adaptively separate primaries and multiples utilizing 3D windows. The utilization of 3D windows allows for enhanced depiction of spatial continuity and anisotropy of seismic events along the gather direction in comparison to 2D windows. The 3D U-net approach with 3D windows can more effectively preserve the continuity of primaries and manage the complex disparities between the actual and simulated multiples. The proposed 3D U-net approach exhibits 1 dB improvement in the signal-to-noise ratio compared to the 2D U-net approach, as observed in the synthesis data section, and exhibits more outstanding performance in the preservation of primaries and removal of residual multiples in both synthesis and reality data sections. Moreover, to expedite network training in our proposed 3D U-net approach we employ the transfer learning (TL) strategy by utilizing the network parameters of 3D U-net estimated in the preceding data segment as the initial network parameters of 3D U-net for the subsequent data segment. In the reality data section, the 3D U-net approach incorporating TL reduces the computational expense by 70% compared to the one without TL.展开更多
This paper addresses the Multi-Vehicle Routing Problem with Time Windows and Simultaneous Pickup and Delivery(MVRPTWSPD),aiming to optimize logistics distribution routes and minimize total costs.A vehicle routing opti...This paper addresses the Multi-Vehicle Routing Problem with Time Windows and Simultaneous Pickup and Delivery(MVRPTWSPD),aiming to optimize logistics distribution routes and minimize total costs.A vehicle routing optimization model is developed based on the operational requirements of the KS Logistics Center,focusing on minimizing vehicle dispatch,loading and unloading,operating,and time window penalty costs.The model incorporates constraints such as vehicle capacity,time windows,and travel distance,and is solved using a genetic algorithm to ensure optimal route planning.Through MATLAB simulations,34 customer points are analyzed,demonstrating that the simultaneous pickup and delivery model reduces total costs by 30.13%,increases vehicle loading rates by 20.04%,and decreases travel distance compared to delivery-only or pickup-only models.The results demonstrate the significant advantages of the simultaneous pickup and delivery mode in reducing logistics costs and improving vehicle utilization,offering valuable insights for enhancing the operational efficiency of the KS Logistics Center.展开更多
This year summarizes the experience of industrialization of vacuum glazing in the past twenty years.A series of technical difficulties have been solved to start the first global mass production of high-quality vacuum ...This year summarizes the experience of industrialization of vacuum glazing in the past twenty years.A series of technical difficulties have been solved to start the first global mass production of high-quality vacuum glass.High quality means high performance and long life which are interrelated.A mass production line must be able to achieve these two requirements if it is to produce vacuum glazing products that can be accepted by the society.With a U-value of 0.4 W/m²·K based on Low-E(low emissivity)with an emissivity of 0.03 the door is wide open for further solutions.Time,gradually to improve costs,maximizes output and develops innovative solutions of advanced window and façade systems combining complete new features like smart glasses,intelligent lamella systems in hybrid VG-IG solutions changing the building world towards“Energy plus Houses”.Market demand will rapidly increase with completely new options.Cost saving means to balance additional advantages for savings against system costs of window or façade elements.Due to promotion of energy saving and emission reduction,both,subjective and objective conditions for industrialization of vacuum glasses are perfect;the building world is waiting for it,since long.There is a lot to investigate and to gain for business success.展开更多
With the rapid development of intelligent navigation technology,efficient and safe path planning for mobile robots has become a core requirement.To address the challenges of complex dynamic environments,this paper pro...With the rapid development of intelligent navigation technology,efficient and safe path planning for mobile robots has become a core requirement.To address the challenges of complex dynamic environments,this paper proposes an intelligent path planning framework based on grid map modeling.First,an improved Safe and Smooth A*(SSA*)algorithm is employed for global path planning.By incorporating obstacle expansion and cornerpoint optimization,the proposed SSA*enhances the safety and smoothness of the planned path.Then,a Partitioned Dynamic Window Approach(PDWA)is integrated for local planning,which is triggered when dynamic or sudden static obstacles appear,enabling real-time obstacle avoidance and path adjustment.A unified objective function is constructed,considering path length,safety,and smoothness comprehensively.Multiple simulation experiments are conducted on typical port grid maps.The results demonstrate that the improved SSA*significantly reduces the number of expanded nodes and computation time in static environmentswhile generating smoother and safer paths.Meanwhile,the PDWA exhibits strong real-time performance and robustness in dynamic scenarios,achieving shorter paths and lower planning times compared to other graph search algorithms.The proposedmethodmaintains stable performance across maps of different scales and various port scenarios,verifying its practicality and potential for wider application.展开更多
The Vehicle Routing Problem with Time Windows(VRPTW)presents a significant challenge in combinatorial optimization,especially under real-world uncertainties such as variable travel times,service durations,and dynamic ...The Vehicle Routing Problem with Time Windows(VRPTW)presents a significant challenge in combinatorial optimization,especially under real-world uncertainties such as variable travel times,service durations,and dynamic customer demands.These uncertainties make traditional deterministic models inadequate,often leading to suboptimal or infeasible solutions.To address these challenges,this work proposes an adaptive hybrid metaheuristic that integrates Genetic Algorithms(GA)with Local Search(LS),while incorporating stochastic uncertainty modeling through probabilistic travel times.The proposed algorithm dynamically adjusts parameters—such as mutation rate and local search probability—based on real-time search performance.This adaptivity enhances the algorithm’s ability to balance exploration and exploitation during the optimization process.Travel time uncertainties are modeled using Gaussian noise,and solution robustness is evaluated through scenario-based simulations.We test our method on a set of benchmark problems from Solomon’s instance suite,comparing its performance under deterministic and stochastic conditions.Results show that the proposed hybrid approach achieves up to a 9%reduction in expected total travel time and a 40% reduction in time window violations compared to baseline methods,including classical GA and non-adaptive hybrids.Additionally,the algorithm demonstrates strong robustness,with lower solution variance across uncertainty scenarios,and converges faster than competing approaches.These findings highlight the method’s suitability for practical logistics applications such as last-mile delivery and real-time transportation planning,where uncertainty and service-level constraints are critical.The flexibility and effectiveness of the proposed framework make it a promising candidate for deployment in dynamic,uncertainty-aware supply chain environments.展开更多
Objective:To observe the efficacy and safety of TCM syndrome differentiation-guided herbal intervention for patients with five constitutions during the high-risk window period of acute exacerbation of chronic obstruct...Objective:To observe the efficacy and safety of TCM syndrome differentiation-guided herbal intervention for patients with five constitutions during the high-risk window period of acute exacerbation of chronic obstructive pulmonary disease(AECOPD)based on TCM constitution theory.Methods:A total of 300 AECOPD patients in the high-risk window period(54-66 cases for each constitution)were randomly divided into two groups(150 cases each).The control group received fluticasone furoate/umeclidinium/vilanterol inhalation therapy,while the experimental group was additionally given constitution-specific TCM decoctions(e.g.,Erchen Decoction combined with Sanzi Yangqin Decoction for Phlegm-Dampness constitution).The treatment course was 8 weeks with a 6-month follow-up.CAT score,TCM syndrome score,pulmonary function,6-minute walking distance(6MWD),and levels of CRP and IL-6 were observed.Recurrence and safety indicators were recorded.Results:After treatment,all indicators improved significantly in both groups(p<0.05),with the experimental group showing superior improvements in CAT score,TCM syndrome score,FEV1,6MWD,and inflammatory indicators(p<0.01).The recurrence rate was lower in the experimental group during follow-up(p<0.05).No severe adverse reactions or abnormalities in liver/kidney function were observed in either group.Conclusion:TCM syndrome differentiation treatment guided by constitution theory can improve symptoms,quality of life,and pulmonary function,reduce inflammatory levels and recurrence rate in AECOPD patients during the high-risk window period,with good safety.展开更多
基金supported by Natural Science Foundation of China(Grant No.52372076,52073081,52203322,5252200843)Ministry of Science and Technology of the People’s Republic of China(2023YFB3812800)Fundamental Research Funds for the Central Universities(FRF-TP-25-073)。
文摘Energy-saving buildings(ESBs)are an emerging green technology that can significantly reduce building-associated cooling and heating energy consumption,catering to the desire for carbon neutrality and sustainable development of society.Smart photovoltaic windows(SPWs)offer a promising platform for designing ESBs because they present the capability to regulate and harness solar energy.With frequent outbreaks of extreme weather all over the world,the achievement of exceptional energy-saving effect under different weather conditions is an inevitable trend for the development of ESBs but is hardly achieved via existing SPWs.Here,we substantially reduce the driving voltage of polymerdispersed liquid crystals(PDLCs)by 28.1%via molecular engineering while maintaining their high solar transmittance(T_(sol)=83.8%,transparent state)and solar modulating ability(ΔT_(sol)=80.5%).By the assembly of perovskite solar cell and a broadband thermal-managing unit encompassing the electrical-responsive PDLCs,transparent high-emissivity SiO_(2) passive radiation-cooling,and Ag low-emissivity layers possesses,we present a tri-band regulation and split-type SPW possessing superb energy-saving effect in all-season.The perovskite solar cell can produce the electric power to stimulate the electrical-responsive behavior of the PDLCs,endowing the SPWs zero-energy input solar energy regulating characteristic,and compensate the daily energy consumption needed for ESBs.Moreover,the scalable manufacturing technology holds a great potential for the real-world applications.
基金funded on the one hand by Agence de l'Innovation de Défense(AID)grant reference number 2021650044on the other hand by Ecole Centrale de Nantes。
文摘Joining dissimilar materials encounters significant engineering challenges due to the contrast in material properties that makes conventional welding not feasible.Magnetic Pulse Welding(MPW)offers a solidstate joining technique that overcomes these issues by using impact to create strong bonds without melting the substrate materials.This study investigates the weldability of aluminum alloy Al-5754 with Al-7075 and MARS 380 steel,used in armouring solutions of defense systems,by the use of MPW.In this work,weldability windows are investigated by varying standoff distances between the coating material and its substrate(0.25-4.5 mm)and discharge energies(5-13 kJ)with both O-shape and U-shape inductors.Mechanical strength of the welded joints were assessed through single lap shear tests,identifying optimal welding parameters.Then,the velocity profiles of the flyer plates were measured using heterodyne velocimetry to understand the dynamics of the impact.Then,substructures assembled with the optimal welding conditions were subjected to ballistic testing using 7.62 mm×51 mm NATO and 9 mm×19 mm Parabellum munitions to evaluate the resilience of the welds under ballistic impact.The outcomes demonstrate that MPW effectively joins Al-5754 with both Al-7075 and MARS 380,producing robust welds capable of withstanding ballistic impacts under certain conditions.This research advances the application of MPW in lightweight ballistic protection of defense systems,contributing to the development of more resilient and lighter protective structures.
基金supported by the Natural Science Foundation of Henan Province[grant number:242300420115]Key Scientific Research Projects in Universities of Henan Province[grant number:23A330006].
文摘Preterm birth(PTB)is defined as delivery before 37 weeks of gestation.PTB is associated with increased cardiovascular risk,neurodevelopmental disorders,and other diseases in infancy,childhood,and adulthood[1].Globally,approximately 15 million PTB cases are reported annually,posing a huge burden on individual families and the community economy[2].In the context of climate warming,O_(3) pollution has continuously increased in many countries in recent years,including China;therefore,scientific communities and government agencies must strive to mitigate ozone pollution.
基金supported by the National Undergraduate Innovation and Entrepreneurship Training Program of China(Project No.202510559076)at Jinan University,a nationwide initiative administered by the Ministry of Educationthe National Natural Science Foundation of China(NSFC)under Grant No.62172189.
文摘Persistent flows are defined as network flows that persist over multiple time intervals and continue to exhibit activity over extended periods,which are critical for identifying long-term behaviors and subtle security threats.Programmable switches provide line-rate packet processing to meet the requirements of high-speed network environments,yet they are fundamentally limited in computational and memory resources.Accurate and memoryefficient persistent flow detection on programmable switches is therefore essential.However,existing approaches often rely on fixed-window sketches or multiple sketches instances,which either suffer from insufficient temporal precision or incur substantial memory overhead,making them ineffective on programmable switches.To address these challenges,we propose SP-Sketch,an innovative sliding-window-based sketch that leverages a probabilistic update mechanism to emulate slot expiration without maintaining multiple sketch instances.This innovative design significantly reduces memory consumption while preserving high detection accuracy across multiple time intervals.We provide rigorous theoretical analyses of the estimation errors,deriving precise error bounds for the proposed method,and validate our approach through comprehensive implementations on both P4 hardware switches(with Intel Tofino ASIC)and software switches(i.e.,BMv2).Experimental evaluations using real-world traffic traces demonstrate that SP-Sketch outperforms traditional methods,improving accuracy by up to 20%over baseline sliding window approaches and enhancing recall by 5%compared to non-sliding alternatives.Furthermore,SP-Sketch achieves a significant reduction in memory utilization,reducing memory consumption by up to 65%compared to traditional methods,while maintaining a robust capability to accurately track persistent flow behavior over extended time periods.
基金supported by the National Natural Science Foundation of China(32371028,32300822,U24A20373,and 82071177)the Shanghai Rising-Star Program(24QA2704800)+2 种基金the Shanghai Jiao Tong University 2030 InitiativeShanghai Municipal Health Commission(202340046)the Fund for Excellent Young Scholars of Shanghai Ninth People's Hospital,Shanghai Jiao Tong University School of Medicine.
文摘Memory is a cognitive process through which past experiences are encoded,stored,and retrieved,playing a crucial role in intelligent behavior.It is well established that the hippocampus continues to reactivate memories for several days after learning,and this process primarily occurs during sleep[1,2].The prevailing view suggests that sharp-wave ripples(SWRs)during non-rapid eye movement(NREM)sleep serve as key electrophysiological signatures of memory replay[3,4].However,only a small portion of SWRs contain memory replay[5].The direct relationship among SWRs,memory replay,and memory consolidation remains an open question.Another unresolved issue is how the hippocampus simultaneously reactivates both new and old memories while preventing interference.
基金supported by National Natural Science Foundation of China(42364008,41804110)in part by Guizhou Provincial Basic Research Program(Natural Science)(ZK[2022]060)+1 种基金in part by China Postdoctoral Science Foundation(2022M723127)in part by Youth Innovation Team Project of Shandong Provincial Education Department(2022KJ141).
文摘The deep convolutional neural network U-net has been introduced into adaptive subtraction, which is a critical step in effectively suppressing seismic multiples. The U-net approach has higher precision than the traditional linear regression approach. However, the existing 2D U-net approach with 2D data windows can not deal with elaborate discrepancies between the actual and simulated multiples along the gather direction. It may lead to erroneous preservation of primaries or generate obvious vestigial multiples, especially in complex media. To further enhance the multiple suppression accuracy, we present an adaptive subtraction approach utilizing 3D U-net architecture, which can adaptively separate primaries and multiples utilizing 3D windows. The utilization of 3D windows allows for enhanced depiction of spatial continuity and anisotropy of seismic events along the gather direction in comparison to 2D windows. The 3D U-net approach with 3D windows can more effectively preserve the continuity of primaries and manage the complex disparities between the actual and simulated multiples. The proposed 3D U-net approach exhibits 1 dB improvement in the signal-to-noise ratio compared to the 2D U-net approach, as observed in the synthesis data section, and exhibits more outstanding performance in the preservation of primaries and removal of residual multiples in both synthesis and reality data sections. Moreover, to expedite network training in our proposed 3D U-net approach we employ the transfer learning (TL) strategy by utilizing the network parameters of 3D U-net estimated in the preceding data segment as the initial network parameters of 3D U-net for the subsequent data segment. In the reality data section, the 3D U-net approach incorporating TL reduces the computational expense by 70% compared to the one without TL.
文摘This paper addresses the Multi-Vehicle Routing Problem with Time Windows and Simultaneous Pickup and Delivery(MVRPTWSPD),aiming to optimize logistics distribution routes and minimize total costs.A vehicle routing optimization model is developed based on the operational requirements of the KS Logistics Center,focusing on minimizing vehicle dispatch,loading and unloading,operating,and time window penalty costs.The model incorporates constraints such as vehicle capacity,time windows,and travel distance,and is solved using a genetic algorithm to ensure optimal route planning.Through MATLAB simulations,34 customer points are analyzed,demonstrating that the simultaneous pickup and delivery model reduces total costs by 30.13%,increases vehicle loading rates by 20.04%,and decreases travel distance compared to delivery-only or pickup-only models.The results demonstrate the significant advantages of the simultaneous pickup and delivery mode in reducing logistics costs and improving vehicle utilization,offering valuable insights for enhancing the operational efficiency of the KS Logistics Center.
文摘This year summarizes the experience of industrialization of vacuum glazing in the past twenty years.A series of technical difficulties have been solved to start the first global mass production of high-quality vacuum glass.High quality means high performance and long life which are interrelated.A mass production line must be able to achieve these two requirements if it is to produce vacuum glazing products that can be accepted by the society.With a U-value of 0.4 W/m²·K based on Low-E(low emissivity)with an emissivity of 0.03 the door is wide open for further solutions.Time,gradually to improve costs,maximizes output and develops innovative solutions of advanced window and façade systems combining complete new features like smart glasses,intelligent lamella systems in hybrid VG-IG solutions changing the building world towards“Energy plus Houses”.Market demand will rapidly increase with completely new options.Cost saving means to balance additional advantages for savings against system costs of window or façade elements.Due to promotion of energy saving and emission reduction,both,subjective and objective conditions for industrialization of vacuum glasses are perfect;the building world is waiting for it,since long.There is a lot to investigate and to gain for business success.
文摘With the rapid development of intelligent navigation technology,efficient and safe path planning for mobile robots has become a core requirement.To address the challenges of complex dynamic environments,this paper proposes an intelligent path planning framework based on grid map modeling.First,an improved Safe and Smooth A*(SSA*)algorithm is employed for global path planning.By incorporating obstacle expansion and cornerpoint optimization,the proposed SSA*enhances the safety and smoothness of the planned path.Then,a Partitioned Dynamic Window Approach(PDWA)is integrated for local planning,which is triggered when dynamic or sudden static obstacles appear,enabling real-time obstacle avoidance and path adjustment.A unified objective function is constructed,considering path length,safety,and smoothness comprehensively.Multiple simulation experiments are conducted on typical port grid maps.The results demonstrate that the improved SSA*significantly reduces the number of expanded nodes and computation time in static environmentswhile generating smoother and safer paths.Meanwhile,the PDWA exhibits strong real-time performance and robustness in dynamic scenarios,achieving shorter paths and lower planning times compared to other graph search algorithms.The proposedmethodmaintains stable performance across maps of different scales and various port scenarios,verifying its practicality and potential for wider application.
文摘The Vehicle Routing Problem with Time Windows(VRPTW)presents a significant challenge in combinatorial optimization,especially under real-world uncertainties such as variable travel times,service durations,and dynamic customer demands.These uncertainties make traditional deterministic models inadequate,often leading to suboptimal or infeasible solutions.To address these challenges,this work proposes an adaptive hybrid metaheuristic that integrates Genetic Algorithms(GA)with Local Search(LS),while incorporating stochastic uncertainty modeling through probabilistic travel times.The proposed algorithm dynamically adjusts parameters—such as mutation rate and local search probability—based on real-time search performance.This adaptivity enhances the algorithm’s ability to balance exploration and exploitation during the optimization process.Travel time uncertainties are modeled using Gaussian noise,and solution robustness is evaluated through scenario-based simulations.We test our method on a set of benchmark problems from Solomon’s instance suite,comparing its performance under deterministic and stochastic conditions.Results show that the proposed hybrid approach achieves up to a 9%reduction in expected total travel time and a 40% reduction in time window violations compared to baseline methods,including classical GA and non-adaptive hybrids.Additionally,the algorithm demonstrates strong robustness,with lower solution variance across uncertainty scenarios,and converges faster than competing approaches.These findings highlight the method’s suitability for practical logistics applications such as last-mile delivery and real-time transportation planning,where uncertainty and service-level constraints are critical.The flexibility and effectiveness of the proposed framework make it a promising candidate for deployment in dynamic,uncertainty-aware supply chain environments.
基金Longquan Yi District Health Bureau Project(Project No.:WJKY2023009)。
文摘Objective:To observe the efficacy and safety of TCM syndrome differentiation-guided herbal intervention for patients with five constitutions during the high-risk window period of acute exacerbation of chronic obstructive pulmonary disease(AECOPD)based on TCM constitution theory.Methods:A total of 300 AECOPD patients in the high-risk window period(54-66 cases for each constitution)were randomly divided into two groups(150 cases each).The control group received fluticasone furoate/umeclidinium/vilanterol inhalation therapy,while the experimental group was additionally given constitution-specific TCM decoctions(e.g.,Erchen Decoction combined with Sanzi Yangqin Decoction for Phlegm-Dampness constitution).The treatment course was 8 weeks with a 6-month follow-up.CAT score,TCM syndrome score,pulmonary function,6-minute walking distance(6MWD),and levels of CRP and IL-6 were observed.Recurrence and safety indicators were recorded.Results:After treatment,all indicators improved significantly in both groups(p<0.05),with the experimental group showing superior improvements in CAT score,TCM syndrome score,FEV1,6MWD,and inflammatory indicators(p<0.01).The recurrence rate was lower in the experimental group during follow-up(p<0.05).No severe adverse reactions or abnormalities in liver/kidney function were observed in either group.Conclusion:TCM syndrome differentiation treatment guided by constitution theory can improve symptoms,quality of life,and pulmonary function,reduce inflammatory levels and recurrence rate in AECOPD patients during the high-risk window period,with good safety.
