In this paper,an online midcourse guidance method for intercepting high-speed maneuvering targets is proposed.Firstly,the affine system is used to build a dynamic model and analyze the state constraints.The midcourse ...In this paper,an online midcourse guidance method for intercepting high-speed maneuvering targets is proposed.Firstly,the affine system is used to build a dynamic model and analyze the state constraints.The midcourse guidance problem is transformed into a continuous time optimization problem.Secondly,the problem is transformed into a discrete convex programming problem by affine control variable relaxation,Gaussian pseudospectral discretization and constraints linearization.Then,the off-line midcourse guidance trajectory is generated before midcourse guidance.It is used as the initial reference trajectory for online correction of midcourse guidance.An online guidance framework is used to eliminate the error caused by calculation of guidance instruction time.And the design of discrete points decreases with flight time to improve the solving efficiency.In addition,it is proposed that the terminal guidance capture is used innovatively space to judge the success of midcourse guidance.Numerical simulation shows the feasibility and effectiveness of the proposed method.展开更多
Project construction and development are an impor-tant part of future army designs.In today’s world,intelligent war-fare and joint operations have become the dominant develop-ments in warfare,so the construction and ...Project construction and development are an impor-tant part of future army designs.In today’s world,intelligent war-fare and joint operations have become the dominant develop-ments in warfare,so the construction and development of the army need top-down,top-level design,and comprehensive plan-ning.The traditional project development model is no longer suf-ficient to meet the army’s complex capability requirements.Projects in various fields need to be developed and coordinated to form a joint force and improve the army’s combat effective-ness.At the same time,when a program consists of large-scale project data,the effectiveness of the traditional,precise mathe-matical planning method is greatly reduced because it is time-consuming,costly,and impractical.To solve above problems,this paper proposes a multi-stage program optimization model based on a heterogeneous network and hybrid genetic algo-rithm and verifies the effectiveness and feasibility of the model and algorithm through an example.The results show that the hybrid algorithm proposed in this paper is better than the exist-ing meta-heuristic algorithm.展开更多
Because of an unfortunate mistake during the production of this article,the Acknowledgements have been omitted.The Acknowledgements are added as follows:Sasan YAZDANI would like to thank the Scientific and Technologic...Because of an unfortunate mistake during the production of this article,the Acknowledgements have been omitted.The Acknowledgements are added as follows:Sasan YAZDANI would like to thank the Scientific and Technological Research Council of Turkey(TÜB˙ITAK)for receiving financial support for this work through the 2221 Fellowship Program for Visiting Scientists and Scientists on Sabbatical Leave(Grant ID:E 21514107-115.02-228864).Sasan YAZDANI also expresses his gratitude to Sahand University of Technology for granting him sabbatical leave to facilitate the completion of this research.展开更多
The electricity-hydrogen integrated energy system(EH-IES)enables synergistic operation of electricity,heat,and hydrogen subsystems,supporting renewable energy integration and efficient multi-energy utilization in futu...The electricity-hydrogen integrated energy system(EH-IES)enables synergistic operation of electricity,heat,and hydrogen subsystems,supporting renewable energy integration and efficient multi-energy utilization in future low carbon societies.However,uncertainties from renewable energy and load variability threaten system safety and economy.Conventional chance-constrained programming(CCP)ensures reliable operation by limiting risk.However,increasing source-load uncertainties that can render CCP models infeasible and exacerbate operational risks.To address this,this paper proposes a risk-adjustable chance-constrained goal programming(RACCGP)model,integrating CCP and goal programming to balance risk and cost based on system risk assessment.An intelligent nonlinear goal programming method based on the state transition algorithm(STA)is developed,along with an improved discretized step transformation,to handle model nonlinearity and enhance computational efficiency.Experimental results show that the proposed model reduces costs while controlling risk compared to traditional CCP,and the solution method outperforms average sample sampling in efficiency and solution quality.展开更多
International freedom of the air(traffic rights)is a key resource for airlines to carry out international air transport business.An efficient and reasonable traffic right resource allocation within a country between a...International freedom of the air(traffic rights)is a key resource for airlines to carry out international air transport business.An efficient and reasonable traffic right resource allocation within a country between airlines can affect the quality of a country’s participation in international air transport.In this paper,a multi-objective mixed-integer programming model for traffic rights resource allocation is developed to minimize passenger travel mileages and maximize the number of traffic rights resources allocated to hub airports and competitive carriers.A hybrid heuristic algorithm combining the genetic algorithm and the variable neighborhood search is devised to solve the model.The results show that the optimal allocation scheme aligns with the principle of fairness,indicating that the proposed model can play a certain guiding role in and provide an innovative perspective on traffic rights resource allocation in various countries.展开更多
In the field of calculating the attack area of air-to-air missiles in modern air combat scenarios,the limitations of existing research,including real-time calculation,accuracy efficiency trade-off,and the absence of t...In the field of calculating the attack area of air-to-air missiles in modern air combat scenarios,the limitations of existing research,including real-time calculation,accuracy efficiency trade-off,and the absence of the three-dimensional attack area model,restrict their practical applications.To address these issues,an improved backtracking algorithm is proposed to improve calculation efficiency.A significant reduction in solution time and maintenance of accuracy in the three-dimensional attack area are achieved by using the proposed algorithm.Furthermore,the age-layered population structure genetic programming(ALPS-GP)algorithm is introduced to determine an analytical polynomial model of the three-dimensional attack area,considering real-time requirements.The accuracy of the polynomial model is enhanced through the coefficient correction using an improved gradient descent algorithm.The study reveals a remarkable combination of high accuracy and efficient real-time computation,with a mean error of 91.89 m using the analytical polynomial model of the three-dimensional attack area solved in just 10^(-4)s,thus meeting the requirements of real-time combat scenarios.展开更多
Complex multi-area collaborative coverage path planning in dynamic environments poses a significant challenge for multi-fixed-wing UAVs(multi-UAV).This study establishes a comprehensive framework that incorporates UAV...Complex multi-area collaborative coverage path planning in dynamic environments poses a significant challenge for multi-fixed-wing UAVs(multi-UAV).This study establishes a comprehensive framework that incorporates UAV capabilities,terrain,complex areas,and mission dynamics.A novel dynamic collaborative path planning algorithm is introduced,designed to ensure complete coverage of designated areas.This algorithm meticulously optimizes the operation,entry,and transition paths for each UAV,while also establishing evaluation metrics to refine coverage sequences for each area.Additionally,a three-dimensional path is computed utilizing an altitude descent method,effectively integrating twodimensional coverage paths with altitude constraints.The efficacy of the proposed approach is validated through digital simulations and mixed-reality semi-physical experiments across a variety of dynamic scenarios,including both single-area and multi-area coverage by multi-UAV.Results show that the coverage paths generated by this method significantly reduce both computation time and path length,providing a reliable solution for dynamic multi-UAV mission planning in semi-physical environments.展开更多
As commercial drone delivery becomes increasingly popular,the extension of the vehicle routing problem with drones(VRPD)is emerging as an optimization problem of inter-ests.This paper studies a variant of VRPD in mult...As commercial drone delivery becomes increasingly popular,the extension of the vehicle routing problem with drones(VRPD)is emerging as an optimization problem of inter-ests.This paper studies a variant of VRPD in multi-trip and multi-drop(VRP-mmD).The problem aims at making schedules for the trucks and drones such that the total travel time is minimized.This paper formulate the problem with a mixed integer program-ming model and propose a two-phase algorithm,i.e.,a parallel route construction heuristic(PRCH)for the first phase and an adaptive neighbor searching heuristic(ANSH)for the second phase.The PRCH generates an initial solution by con-currently assigning as many nodes as possible to the truck–drone pair to progressively reduce the waiting time at the rendezvous node in the first phase.Then the ANSH improves the initial solution by adaptively exploring the neighborhoods in the second phase.Numerical tests on some benchmark data are conducted to verify the performance of the algorithm.The results show that the proposed algorithm can found better solu-tions than some state-of-the-art methods for all instances.More-over,an extensive analysis highlights the stability of the pro-posed algorithm.展开更多
The rapid evolution of unmanned aerial vehicle(UAV)technology and autonomous capabilities has positioned UAV as promising last-mile delivery means.Vehicle and onboard UAV collaborative delivery is introduced as a nove...The rapid evolution of unmanned aerial vehicle(UAV)technology and autonomous capabilities has positioned UAV as promising last-mile delivery means.Vehicle and onboard UAV collaborative delivery is introduced as a novel delivery mode.Spatiotemporal collaboration,along with energy consumption with payload and wind conditions play important roles in delivery route planning.This paper introduces the traveling salesman problem with time window and onboard UAV(TSPTWOUAV)and emphasizes the consideration of real-world scenarios,focusing on time collaboration and energy consumption with wind and payload.To address this,a mixed integer linear programming(MILP)model is formulated to minimize the energy consumption costs of vehicle and UAV.Furthermore,an adaptive large neighborhood search(ALNS)algorithm is applied to identify high-quality solutions efficiently.The effectiveness of the proposed model and algorithm is validated through numerical tests on real geographic instances and sensitivity analysis of key parameters is conducted.展开更多
Taiji-2 project is the second step of Taiji program,which is to verify the required technology for Taiji-3 mission.The feasibility study of Taiji-2 is successfully finished,and some of the main progress is introduced ...Taiji-2 project is the second step of Taiji program,which is to verify the required technology for Taiji-3 mission.The feasibility study of Taiji-2 is successfully finished,and some of the main progress is introduced here.展开更多
Mechanobiology is a rapidly growing field that has expanded significantly over the past 40 years.There have been great examples of mechanobiology research on the cardiovascular,musculoskeletal,and respiratory systems....Mechanobiology is a rapidly growing field that has expanded significantly over the past 40 years.There have been great examples of mechanobiology research on the cardiovascular,musculoskeletal,and respiratory systems.The field has evolved from the system level to the organ and tissue levels,and down to the cellular and molecular levels,benefiting from scientific progress and technological developments in molecular and cell biology,biomaterials,imaging techniques,and computational tools.Additionally,the interdisciplinary integration of mechanobiology with cell engineering,tissue engineering,and drug delivery has led to promising mechanomedicine applications in both therapeutics and diagnostics.Here,I will discuss two examples at the molecular and cellular levels:(1)mechanical regulation of epigenomics for cell reprogramming,and(2)engineering the mechanical properties of artificial antigen-presenting cells(APCs)for immune cell modulation and cancer therapy.Cell memory of its identity is determined by the epigenetic state of the cells.However,how cells control the epigenetic state and thus cell fate is not well understood,and how mechanical factors such as surface topography,cell morphology,mechanical properties of the extracellular matrix(ECM),and the mechanical deformation of cells regulate the epigenetic state is not clear.In an early study,we showed that biophysical cues,in the form of parallel microgrooves on the surface of cell-adhesive substrates,can replace the effects of small-molecule epigenetic modifiers and significantly improve reprogramming efficiency from fibroblasts to induced pluripotent stem cells.The mechanism relies on the mechanomodulation of the cells’epigenetic state through the activity of histone deacetylase and H3 methyltransferase.We also showed that microtopography promotes a mesenchymal-to-epithelial transition in adult fibroblasts.Nanofibrous scaffolds with aligned fiber orientation produce effects similar to those produced by microgrooves,suggesting that changes in cell morphology may be responsible for the modulation of the epigenetic state.The effects of micro/nanopatterned surfaces may be related to the reduction of intracellular tension and cell adhesion.Indeed,the reduction of actin cytoskeletal tension or cell adhesion at the early phase of reprogramming suppresses the expression of mesenchymal genes,promotes a more open chromatin structure,and significantly enhances the efficiency of induced neuronal(i N)conversion.Specifically,the reduction of intracellular tension or cell adhesion not only modulates global epigenetic marks but also decreases DNA methylation and heterochromatin marks while increasing euchromatin marks at the promoter of neuronal genes,thus enhancing the accessibility for gene activation.Finally,micro-and nano-topographic surfaces that reduce cell adhesion enhance i N reprogramming.These novel findings suggest that the actin cytoskeleton and focal adhesions play an important role in epigenetic regulation for cell fate determination,which may lead to biomaterialbased approaches for more effective cell reprogramming.In addition,matrix stiffness also regulates cell reprogramming,which acts as a biphasic regulator of the epigenetic state and fibroblast-to-neuron conversion efficiency,maximized at an intermediate stiffness of 20 k Pa.ATAC sequencing analysis shows the same trend of chromatin accessibility to neuronal genes at these stiffness levels.Concurrently,we observe peak levels of histone acetylation and histone acetyltransferase(HAT)activity in the nucleus on 20 k Pa matrices,and inhibiting HAT activity abolishes matrix stiffness effects.G-actin and cofilin,the co-transporters shuttling HAT into the nucleus,rise with decreasing matrix stiffness;however,reduced importin-9 on soft matrices limits nuclear transport.These two factors result in a biphasic regulation of HAT transport into the nucleus,which is directly demonstrated on matrices with dynamically tunable stiffness.Furthermore,we find that the regulation of the epigenetic state by the viscoelastic matrix is more pronounced on softermatrices.Cells on viscoelastic matrices exhibit larger nuclei,increased nuclear lamina ruffling,loosely organized chromatin,and faster chromatin dynamics compared to those on elastic matrices.These changes are accompanied by a global increase in euchromatic marks and a local increase in chromatin accessibility at the cis-regulatory elements associated with neuronal and pluripotent genes.Consequently,viscoelastic matrices enhance the efficiency of reprogramming fibroblasts into neurons and induced pluripotent stem cells,respectively.Together,our findings demonstrate the key roles of matrix viscoelasticity in regulating the epigenetic state and uncover a new mechanism of biophysical regulation of chromatin and cell reprogramming,with implications for designing smart materials to engineer cell fate.The viscoelasticity of biomaterials not only regulates cell adhesion and the epigenetic state but also modulates other ligand-receptor interactions such as T cell receptor activation.We developed a scalable microfluidic platform to fabricate synthetic viscoelastic activating cells(Syn VACs)with programmable mechanical and chemical properties.We demonstrated that the viscoelastic nature of Syn VACs significantly impacts T cell functionality.Compared to rigid or elastic microspheres,Syn VACs greatly enhance human T cell expansion with drastic CD8+T cell generation while suppressing regulatory T cell formation,resulting in enhanced tumor-killing capability.Notably,expanding chimeric antigen receptor(CAR)-T cells with Syn VACs achieves approximately 90%CAR transduction efficiency and leads to a six-fold increase in T memory stem cells.These engineered CAR-T cells exhibit superior efficacy in eliminating tumor cells,not only in a human lymphoma mouse model but also in a solid tumor xenograft mouse model of ovarian cancer.Additionally,Syn VAC-expanded CAR-T cells persist for longer periods in vivo to suppress tumor growth and recurrence.These findings underscore the crucial role of mechanical signals in T cell engineering and highlight the potential of the Syn VAC platform in CAR-T therapy and broad immunoengineering applications.These examples of mechanical regulation of cells not only unravel the underlying mechanisms of mechanotransduction in various cells,but also have tremendous potential to translate into therapeutic applications.展开更多
In 2024,the Chinese Meridian Project(CMP)completed its construction,deploying 282 instruments across 31 stations.This achievement not only provides a robust foundation but also serves as a reference template for the I...In 2024,the Chinese Meridian Project(CMP)completed its construction,deploying 282 instruments across 31 stations.This achievement not only provides a robust foundation but also serves as a reference template for the International Meridian Circle Program(IMCP).The IMCP aims to integrate and establish a comprehensive network of ground-based monitoring stations designed to track the propagation of space weather events from the Sun to Earth.Additionally,it monitors various disturbances generated within the Earth system that impact geospace.Over the past two years,significant progress has been made on the IMCP.In particular,the second phase of construction for the China-Brazil Joint Laboratory for Space Weather has been completed,and the North Pole and Southeast Asia networks are under active construction.The 2024 IMCP joint observation campaign was successfully conducted.To facilitate these developments,the scientific program committee of IMCP was established,following the success of 2023 IMCP workshop and the space weather school,which was co-hosted with the Asia-Pacific Space Cooperation Organization(APSCO)and sponsored by Chinese Academy of Sciences(CAS)and Scientific Committee on Solar-Terrestrial Physics(SCOSTEP).Preparations are now underway for the 2024 workshop in collaboration with the National Institute for Space Research(INPE)in Brazil.展开更多
This paper aims to explore the ability of genetic programming(GP)to achieve the intelligent prediction of tunnelling-induced building deformation considering the multifactor impact.A total of 1099 groups of data obtai...This paper aims to explore the ability of genetic programming(GP)to achieve the intelligent prediction of tunnelling-induced building deformation considering the multifactor impact.A total of 1099 groups of data obtained from 22 geotechnical centrifuge tests are used for model development and analysis using GP.Tunnel volume loss,building eccentricity,soil density,building transverse width,building shear stiffness and building load are selected as the inputs,and shear distortion is selected as the output.Results suggest that the proposed intelligent prediction model is capable of providing a reasonable and accurate prediction of framed building shear distortion due to tunnel construction with realistic conditions,highlighting the important roles of shear stiffness of framed buildings and the pressure beneath the foundation on structural deformation.It has been proven that the proposed model is efficient and feasible to analyze relevant engineering problems by parametric analysis and comparative analysis.The findings demonstrate the great potential of GP approaches in predicting building distortion caused by tunnelling.The proposed equation can be used for the quick and intelligent prediction of tunnelling induced building deformation,providing valuable guidance for the practical design and risk assessment of urban tunnel construction projects.展开更多
文摘In this paper,an online midcourse guidance method for intercepting high-speed maneuvering targets is proposed.Firstly,the affine system is used to build a dynamic model and analyze the state constraints.The midcourse guidance problem is transformed into a continuous time optimization problem.Secondly,the problem is transformed into a discrete convex programming problem by affine control variable relaxation,Gaussian pseudospectral discretization and constraints linearization.Then,the off-line midcourse guidance trajectory is generated before midcourse guidance.It is used as the initial reference trajectory for online correction of midcourse guidance.An online guidance framework is used to eliminate the error caused by calculation of guidance instruction time.And the design of discrete points decreases with flight time to improve the solving efficiency.In addition,it is proposed that the terminal guidance capture is used innovatively space to judge the success of midcourse guidance.Numerical simulation shows the feasibility and effectiveness of the proposed method.
基金supported by the National Natural Science Foundation of China(724701189072431011).
文摘Project construction and development are an impor-tant part of future army designs.In today’s world,intelligent war-fare and joint operations have become the dominant develop-ments in warfare,so the construction and development of the army need top-down,top-level design,and comprehensive plan-ning.The traditional project development model is no longer suf-ficient to meet the army’s complex capability requirements.Projects in various fields need to be developed and coordinated to form a joint force and improve the army’s combat effective-ness.At the same time,when a program consists of large-scale project data,the effectiveness of the traditional,precise mathe-matical planning method is greatly reduced because it is time-consuming,costly,and impractical.To solve above problems,this paper proposes a multi-stage program optimization model based on a heterogeneous network and hybrid genetic algo-rithm and verifies the effectiveness and feasibility of the model and algorithm through an example.The results show that the hybrid algorithm proposed in this paper is better than the exist-ing meta-heuristic algorithm.
文摘Because of an unfortunate mistake during the production of this article,the Acknowledgements have been omitted.The Acknowledgements are added as follows:Sasan YAZDANI would like to thank the Scientific and Technological Research Council of Turkey(TÜB˙ITAK)for receiving financial support for this work through the 2221 Fellowship Program for Visiting Scientists and Scientists on Sabbatical Leave(Grant ID:E 21514107-115.02-228864).Sasan YAZDANI also expresses his gratitude to Sahand University of Technology for granting him sabbatical leave to facilitate the completion of this research.
基金Project(2022YFC2904502)supported by the National Key Research and Development Program of ChinaProject(62273357)supported by the National Natural Science Foundation of China。
文摘The electricity-hydrogen integrated energy system(EH-IES)enables synergistic operation of electricity,heat,and hydrogen subsystems,supporting renewable energy integration and efficient multi-energy utilization in future low carbon societies.However,uncertainties from renewable energy and load variability threaten system safety and economy.Conventional chance-constrained programming(CCP)ensures reliable operation by limiting risk.However,increasing source-load uncertainties that can render CCP models infeasible and exacerbate operational risks.To address this,this paper proposes a risk-adjustable chance-constrained goal programming(RACCGP)model,integrating CCP and goal programming to balance risk and cost based on system risk assessment.An intelligent nonlinear goal programming method based on the state transition algorithm(STA)is developed,along with an improved discretized step transformation,to handle model nonlinearity and enhance computational efficiency.Experimental results show that the proposed model reduces costs while controlling risk compared to traditional CCP,and the solution method outperforms average sample sampling in efficiency and solution quality.
基金supported by the National Natural Science Foundation of Chinathe Civil Aviation Administration of China (U2333206).
文摘International freedom of the air(traffic rights)is a key resource for airlines to carry out international air transport business.An efficient and reasonable traffic right resource allocation within a country between airlines can affect the quality of a country’s participation in international air transport.In this paper,a multi-objective mixed-integer programming model for traffic rights resource allocation is developed to minimize passenger travel mileages and maximize the number of traffic rights resources allocated to hub airports and competitive carriers.A hybrid heuristic algorithm combining the genetic algorithm and the variable neighborhood search is devised to solve the model.The results show that the optimal allocation scheme aligns with the principle of fairness,indicating that the proposed model can play a certain guiding role in and provide an innovative perspective on traffic rights resource allocation in various countries.
基金National Natural Science Foundation of China(62373187)Forward-looking Layout Special Projects(ILA220591A22)。
文摘In the field of calculating the attack area of air-to-air missiles in modern air combat scenarios,the limitations of existing research,including real-time calculation,accuracy efficiency trade-off,and the absence of the three-dimensional attack area model,restrict their practical applications.To address these issues,an improved backtracking algorithm is proposed to improve calculation efficiency.A significant reduction in solution time and maintenance of accuracy in the three-dimensional attack area are achieved by using the proposed algorithm.Furthermore,the age-layered population structure genetic programming(ALPS-GP)algorithm is introduced to determine an analytical polynomial model of the three-dimensional attack area,considering real-time requirements.The accuracy of the polynomial model is enhanced through the coefficient correction using an improved gradient descent algorithm.The study reveals a remarkable combination of high accuracy and efficient real-time computation,with a mean error of 91.89 m using the analytical polynomial model of the three-dimensional attack area solved in just 10^(-4)s,thus meeting the requirements of real-time combat scenarios.
基金National Natural Science Foundation of China(Grant No.52472417)to provide fund for conducting experiments.
文摘Complex multi-area collaborative coverage path planning in dynamic environments poses a significant challenge for multi-fixed-wing UAVs(multi-UAV).This study establishes a comprehensive framework that incorporates UAV capabilities,terrain,complex areas,and mission dynamics.A novel dynamic collaborative path planning algorithm is introduced,designed to ensure complete coverage of designated areas.This algorithm meticulously optimizes the operation,entry,and transition paths for each UAV,while also establishing evaluation metrics to refine coverage sequences for each area.Additionally,a three-dimensional path is computed utilizing an altitude descent method,effectively integrating twodimensional coverage paths with altitude constraints.The efficacy of the proposed approach is validated through digital simulations and mixed-reality semi-physical experiments across a variety of dynamic scenarios,including both single-area and multi-area coverage by multi-UAV.Results show that the coverage paths generated by this method significantly reduce both computation time and path length,providing a reliable solution for dynamic multi-UAV mission planning in semi-physical environments.
文摘As commercial drone delivery becomes increasingly popular,the extension of the vehicle routing problem with drones(VRPD)is emerging as an optimization problem of inter-ests.This paper studies a variant of VRPD in multi-trip and multi-drop(VRP-mmD).The problem aims at making schedules for the trucks and drones such that the total travel time is minimized.This paper formulate the problem with a mixed integer program-ming model and propose a two-phase algorithm,i.e.,a parallel route construction heuristic(PRCH)for the first phase and an adaptive neighbor searching heuristic(ANSH)for the second phase.The PRCH generates an initial solution by con-currently assigning as many nodes as possible to the truck–drone pair to progressively reduce the waiting time at the rendezvous node in the first phase.Then the ANSH improves the initial solution by adaptively exploring the neighborhoods in the second phase.Numerical tests on some benchmark data are conducted to verify the performance of the algorithm.The results show that the proposed algorithm can found better solu-tions than some state-of-the-art methods for all instances.More-over,an extensive analysis highlights the stability of the pro-posed algorithm.
基金Fundamental Research Funds for the Central Universities(2024JBZX038)National Natural Science F oundation of China(62076023)。
文摘The rapid evolution of unmanned aerial vehicle(UAV)technology and autonomous capabilities has positioned UAV as promising last-mile delivery means.Vehicle and onboard UAV collaborative delivery is introduced as a novel delivery mode.Spatiotemporal collaboration,along with energy consumption with payload and wind conditions play important roles in delivery route planning.This paper introduces the traveling salesman problem with time window and onboard UAV(TSPTWOUAV)and emphasizes the consideration of real-world scenarios,focusing on time collaboration and energy consumption with wind and payload.To address this,a mixed integer linear programming(MILP)model is formulated to minimize the energy consumption costs of vehicle and UAV.Furthermore,an adaptive large neighborhood search(ALNS)algorithm is applied to identify high-quality solutions efficiently.The effectiveness of the proposed model and algorithm is validated through numerical tests on real geographic instances and sensitivity analysis of key parameters is conducted.
基金Supported by the Strategic Priority Research Program of the Chinese Academy of Sciences(XDA15021100)the National Natural Science Foundation of China(12147103)the Fundamental Research Funds for the Central Universities。
文摘Taiji-2 project is the second step of Taiji program,which is to verify the required technology for Taiji-3 mission.The feasibility study of Taiji-2 is successfully finished,and some of the main progress is introduced here.
文摘Mechanobiology is a rapidly growing field that has expanded significantly over the past 40 years.There have been great examples of mechanobiology research on the cardiovascular,musculoskeletal,and respiratory systems.The field has evolved from the system level to the organ and tissue levels,and down to the cellular and molecular levels,benefiting from scientific progress and technological developments in molecular and cell biology,biomaterials,imaging techniques,and computational tools.Additionally,the interdisciplinary integration of mechanobiology with cell engineering,tissue engineering,and drug delivery has led to promising mechanomedicine applications in both therapeutics and diagnostics.Here,I will discuss two examples at the molecular and cellular levels:(1)mechanical regulation of epigenomics for cell reprogramming,and(2)engineering the mechanical properties of artificial antigen-presenting cells(APCs)for immune cell modulation and cancer therapy.Cell memory of its identity is determined by the epigenetic state of the cells.However,how cells control the epigenetic state and thus cell fate is not well understood,and how mechanical factors such as surface topography,cell morphology,mechanical properties of the extracellular matrix(ECM),and the mechanical deformation of cells regulate the epigenetic state is not clear.In an early study,we showed that biophysical cues,in the form of parallel microgrooves on the surface of cell-adhesive substrates,can replace the effects of small-molecule epigenetic modifiers and significantly improve reprogramming efficiency from fibroblasts to induced pluripotent stem cells.The mechanism relies on the mechanomodulation of the cells’epigenetic state through the activity of histone deacetylase and H3 methyltransferase.We also showed that microtopography promotes a mesenchymal-to-epithelial transition in adult fibroblasts.Nanofibrous scaffolds with aligned fiber orientation produce effects similar to those produced by microgrooves,suggesting that changes in cell morphology may be responsible for the modulation of the epigenetic state.The effects of micro/nanopatterned surfaces may be related to the reduction of intracellular tension and cell adhesion.Indeed,the reduction of actin cytoskeletal tension or cell adhesion at the early phase of reprogramming suppresses the expression of mesenchymal genes,promotes a more open chromatin structure,and significantly enhances the efficiency of induced neuronal(i N)conversion.Specifically,the reduction of intracellular tension or cell adhesion not only modulates global epigenetic marks but also decreases DNA methylation and heterochromatin marks while increasing euchromatin marks at the promoter of neuronal genes,thus enhancing the accessibility for gene activation.Finally,micro-and nano-topographic surfaces that reduce cell adhesion enhance i N reprogramming.These novel findings suggest that the actin cytoskeleton and focal adhesions play an important role in epigenetic regulation for cell fate determination,which may lead to biomaterialbased approaches for more effective cell reprogramming.In addition,matrix stiffness also regulates cell reprogramming,which acts as a biphasic regulator of the epigenetic state and fibroblast-to-neuron conversion efficiency,maximized at an intermediate stiffness of 20 k Pa.ATAC sequencing analysis shows the same trend of chromatin accessibility to neuronal genes at these stiffness levels.Concurrently,we observe peak levels of histone acetylation and histone acetyltransferase(HAT)activity in the nucleus on 20 k Pa matrices,and inhibiting HAT activity abolishes matrix stiffness effects.G-actin and cofilin,the co-transporters shuttling HAT into the nucleus,rise with decreasing matrix stiffness;however,reduced importin-9 on soft matrices limits nuclear transport.These two factors result in a biphasic regulation of HAT transport into the nucleus,which is directly demonstrated on matrices with dynamically tunable stiffness.Furthermore,we find that the regulation of the epigenetic state by the viscoelastic matrix is more pronounced on softermatrices.Cells on viscoelastic matrices exhibit larger nuclei,increased nuclear lamina ruffling,loosely organized chromatin,and faster chromatin dynamics compared to those on elastic matrices.These changes are accompanied by a global increase in euchromatic marks and a local increase in chromatin accessibility at the cis-regulatory elements associated with neuronal and pluripotent genes.Consequently,viscoelastic matrices enhance the efficiency of reprogramming fibroblasts into neurons and induced pluripotent stem cells,respectively.Together,our findings demonstrate the key roles of matrix viscoelasticity in regulating the epigenetic state and uncover a new mechanism of biophysical regulation of chromatin and cell reprogramming,with implications for designing smart materials to engineer cell fate.The viscoelasticity of biomaterials not only regulates cell adhesion and the epigenetic state but also modulates other ligand-receptor interactions such as T cell receptor activation.We developed a scalable microfluidic platform to fabricate synthetic viscoelastic activating cells(Syn VACs)with programmable mechanical and chemical properties.We demonstrated that the viscoelastic nature of Syn VACs significantly impacts T cell functionality.Compared to rigid or elastic microspheres,Syn VACs greatly enhance human T cell expansion with drastic CD8+T cell generation while suppressing regulatory T cell formation,resulting in enhanced tumor-killing capability.Notably,expanding chimeric antigen receptor(CAR)-T cells with Syn VACs achieves approximately 90%CAR transduction efficiency and leads to a six-fold increase in T memory stem cells.These engineered CAR-T cells exhibit superior efficacy in eliminating tumor cells,not only in a human lymphoma mouse model but also in a solid tumor xenograft mouse model of ovarian cancer.Additionally,Syn VAC-expanded CAR-T cells persist for longer periods in vivo to suppress tumor growth and recurrence.These findings underscore the crucial role of mechanical signals in T cell engineering and highlight the potential of the Syn VAC platform in CAR-T therapy and broad immunoengineering applications.These examples of mechanical regulation of cells not only unravel the underlying mechanisms of mechanotransduction in various cells,but also have tremendous potential to translate into therapeutic applications.
基金Supported by International Meridian Circle Program Headquarters,China-Brazil Joint Laboratory for Space Weather(Y42347A99S)。
文摘In 2024,the Chinese Meridian Project(CMP)completed its construction,deploying 282 instruments across 31 stations.This achievement not only provides a robust foundation but also serves as a reference template for the International Meridian Circle Program(IMCP).The IMCP aims to integrate and establish a comprehensive network of ground-based monitoring stations designed to track the propagation of space weather events from the Sun to Earth.Additionally,it monitors various disturbances generated within the Earth system that impact geospace.Over the past two years,significant progress has been made on the IMCP.In particular,the second phase of construction for the China-Brazil Joint Laboratory for Space Weather has been completed,and the North Pole and Southeast Asia networks are under active construction.The 2024 IMCP joint observation campaign was successfully conducted.To facilitate these developments,the scientific program committee of IMCP was established,following the success of 2023 IMCP workshop and the space weather school,which was co-hosted with the Asia-Pacific Space Cooperation Organization(APSCO)and sponsored by Chinese Academy of Sciences(CAS)and Scientific Committee on Solar-Terrestrial Physics(SCOSTEP).Preparations are now underway for the 2024 workshop in collaboration with the National Institute for Space Research(INPE)in Brazil.
基金Projects(52108364,52278398)supported by the National Natural Science Foundation of ChinaProject(211179)supported by the Royal Society,UK+1 种基金Project(22CX06051A)supported by the Independent Innovation Research Plan Project of China University of Petroleum(East China)Project(ZR2023QE004)supported by the Shandong Provincial Natural Science Foundation,China。
文摘This paper aims to explore the ability of genetic programming(GP)to achieve the intelligent prediction of tunnelling-induced building deformation considering the multifactor impact.A total of 1099 groups of data obtained from 22 geotechnical centrifuge tests are used for model development and analysis using GP.Tunnel volume loss,building eccentricity,soil density,building transverse width,building shear stiffness and building load are selected as the inputs,and shear distortion is selected as the output.Results suggest that the proposed intelligent prediction model is capable of providing a reasonable and accurate prediction of framed building shear distortion due to tunnel construction with realistic conditions,highlighting the important roles of shear stiffness of framed buildings and the pressure beneath the foundation on structural deformation.It has been proven that the proposed model is efficient and feasible to analyze relevant engineering problems by parametric analysis and comparative analysis.The findings demonstrate the great potential of GP approaches in predicting building distortion caused by tunnelling.The proposed equation can be used for the quick and intelligent prediction of tunnelling induced building deformation,providing valuable guidance for the practical design and risk assessment of urban tunnel construction projects.
