In order to minimize the project duration of resourceconstrained project scheduling problem( RCPSP), a gene expression programming-based scheduling rule( GEP-SR) method is proposed to automatically discover and select...In order to minimize the project duration of resourceconstrained project scheduling problem( RCPSP), a gene expression programming-based scheduling rule( GEP-SR) method is proposed to automatically discover and select the effective scheduling rules( SRs) which are constructed using the project status and attributes of the activities. SRs are represented by the chromosomes of GEP, and an improved parallel schedule generation scheme( IPSGS) is used to transform the SRs into explicit schedules. The framework of GEP-SR for RCPSP is designed,and the effectiveness of the GEP-SR approach is demonstrated by comparing with other methods on the same instances.展开更多
A memetic algorithm （MA） for a multi-mode resourceconstrained project scheduling problem （MRCPSP） is proposed. We use a new fitness function and two very effective local search procedures in the proposed MA. The f...A memetic algorithm （MA） for a multi-mode resourceconstrained project scheduling problem （MRCPSP） is proposed. We use a new fitness function and two very effective local search procedures in the proposed MA. The fitness function makes use of a mechanism called ＂strategic oscillation＂ to make the search process have a higher probability to visit solutions around a ＂feasible boundary＂. One of the local search procedures aims at improving the lower bound of project makespan to be less than a known upper bound, and another aims at improving a solution of an MRCPSP instance accepting infeasible solutions based on the new fitness function in the search process. A detailed computational experiment is set up using instances from the problem instance library PSPLIB. Computational results show that the proposed MA is very competitive with the state-of-the-art algorithms. The MA obtains improved solutions for one instance of set J30.展开更多
An improved differential evolution（IDE）algorithm that adopts a novel mutation strategy to speed up the convergence rate is introduced to solve the resource-constrained project scheduling problem（RCPSP）with the obj...An improved differential evolution（IDE）algorithm that adopts a novel mutation strategy to speed up the convergence rate is introduced to solve the resource-constrained project scheduling problem（RCPSP）with the objective of minimizing project duration Activities priorities for scheduling are represented by individual vectors and a senal scheme is utilized to transform the individual-represented priorities to a feasible schedule according to the precedence and resource constraints so as to be evaluated.To investigate the performance of the IDE-based approach for the RCPSP,it is compared against the meta-heuristic methods of hybrid genetic algorithm（HGA）,particle swarm optimization（PSO） and several well selected heuristics.The results show that the proposed scheduling method is better than general heuristic rules and is able to obtain the same optimal result as the HGA and PSO approaches but more efficient than the two algorithms.展开更多
To solve the resource-constrained project scheduling problem(RCPSP),a hybrid ant colony optimization(HACO)approach is presented.To improve the quality of the schedules,the HACO is incorporated with an extended double ...To solve the resource-constrained project scheduling problem(RCPSP),a hybrid ant colony optimization(HACO)approach is presented.To improve the quality of the schedules,the HACO is incorporated with an extended double justification in which the activity splitting is applied to predict whether the schedule could be improved.The HACO is tested on the set of large benchmark problems from the project scheduling problem library(PSPLIB).The computational result shows that the proposed algo-rithm can improve the quality of the schedules efficiently.展开更多
This paper introduces a hybrid evolutionary algorithm for the resource-constrained project scheduling problem (RCPSP). Given an RCPSP instance, the algorithm identifies the problem structure and selects a suitable dec...This paper introduces a hybrid evolutionary algorithm for the resource-constrained project scheduling problem (RCPSP). Given an RCPSP instance, the algorithm identifies the problem structure and selects a suitable decoding scheme. Then a multi-pass biased sampling method followed up by a multi-local search is used to generate a diverse and good quality initial population. The population then evolves through modified order-based recombination and mutation operators to perform exploration for promising solutions within the entire region. Mutation is performed only if the current population has converged or the produced offspring by recombination operator is too similar to one of his parents. Finally the algorithm performs an intensified local search on the best solution found in the evolutionary stage. Computational experiments using standard instances indicate that the proposed algorithm works well in both computational time and solution quality.展开更多
This paper presents a new method to solve the resource-constrained project scheduling problem for software development. In this method,activity duration times are described as fuzzy variables and resource-constrained ...This paper presents a new method to solve the resource-constrained project scheduling problem for software development. In this method,activity duration times are described as fuzzy variables and resource-constrained software project scheduling problems are described as fuzzy programming models. First,how to model the software project scheduling problem under the fuzzy environment conditions is proposed. Second,in order to satisfy the different requirements of decision-making,two novel fuzzy project scheduling models,expected cost model and credibility maximization model,are suggested. Third,a hybrid intelligent algorithm integrated by genetic algorithm and fuzzy simulation is designed to solve the above two fuzzy programming models. Numerical experiments illustrate the effectiveness of the hybrid intelligent algorithm.展开更多
This paper presents a new genetic algorithm for the resource-constrained project scheduling problem(RCPSP).The algorithm employs a standardized random key(SRK) vector representation with an additional gene that determ...This paper presents a new genetic algorithm for the resource-constrained project scheduling problem(RCPSP).The algorithm employs a standardized random key(SRK) vector representation with an additional gene that determines whether the serial or parallel schedule generation scheme(SGS) is to be used as the decoding procedure.The iterative forward-backward improvement as the local search procedure is applied upon all generated solutions to schedule the project three times and obtain an SRK vector,which is rese...展开更多
Offshore engineering construction projects are large and complex,having the characteristics of multiple execution modes andmultiple resource constraints.Their complex internal scheduling processes can be regarded as r...Offshore engineering construction projects are large and complex,having the characteristics of multiple execution modes andmultiple resource constraints.Their complex internal scheduling processes can be regarded as resourceconstrained project scheduling problems(RCPSPs).To solve RCPSP problems in offshore engineering construction more rapidly,a hybrid genetic algorithmwas established.To solve the defects of genetic algorithms,which easily fall into the local optimal solution,a local search operation was added to a genetic algorithm to defend the offspring after crossover/mutation.Then,an elitist strategy and adaptive operators were adopted to protect the generated optimal solutions,reduce the computation time and avoid premature convergence.A calibrated function method was used to cater to the roulette rules,and appropriate rules for encoding,decoding and crossover/mutation were designed.Finally,a simple network was designed and validated using the case study of a real offshore project.The performance of the genetic algorithmand a simulated annealing algorithmwas compared to validate the feasibility and effectiveness of the approach.展开更多
In this paper we formulate a bi-criteria search strategy of a heuristic learning algorithm for solving multiple resource-constrained project scheduling problems. The heuristic solves problems in two phases. In the pre...In this paper we formulate a bi-criteria search strategy of a heuristic learning algorithm for solving multiple resource-constrained project scheduling problems. The heuristic solves problems in two phases. In the pre-processing phase, the algorithm estimates distance between a state and the goal state and measures complexity of problem instances. In the search phase, the algorithm uses estimates of the pre-processing phase to further estimate distances to the goal state. The search continues in a stepwise generation of a series of intermediate states through search path evaluation process with backtracking. Developments of intermediate states are exclusively based on a bi-criteria new state selection technique where we consider resource utilization and duration estimate to the goal state. We also propose a variable weighting technique based on initial problem complexity measures. Introducing this technique allows the algorithm to efficiently solve complex project scheduling problems. A numerical example illustrates the algorithm and performance is evaluated by extensive experimentation with various problem parameters. Computational results indicate significance of the algorithm in terms of solution quality and computational performance.展开更多
To solve the resource-constrained multiple project scheduling problem(RCMPSP) more effectively,a method based on timed colored Petri net(TCPN) was proposed.In this methodology,firstly a novel mapping mechanism between...To solve the resource-constrained multiple project scheduling problem(RCMPSP) more effectively,a method based on timed colored Petri net(TCPN) was proposed.In this methodology,firstly a novel mapping mechanism between traditional network diagram such as CPM(critical path method)/PERT(program evaluation and review technique) and TCPN was presented.Then a primary TCPN(PTCPN) for solving RCMPSP was modeled based on the proposed mapping mechanism.Meanwhile,the object PTCPN was used to simulate the multiple projects scheduling and to find the approximately optimal value of RCMPSP.Finally,the performance of the proposed approach for solving RCMPSP was validated by executing a mould manufacturing example.展开更多
Dependency Structure Matrix （DSM） is a successful and powerful tool for representing and analyzing dependencies between the items, but for external influencing factors it cannot charge effectively. This paper sets t...Dependency Structure Matrix （DSM） is a successful and powerful tool for representing and analyzing dependencies between the items, but for external influencing factors it cannot charge effectively. This paper sets the stage for connecting the activities and resources, which not only considers information flow but also resources constrains.We first introduce the DSM to represent the degree of overlapping between the activities in a project. Then we present the Extended DSM combined former DSM and resource factors to calculate the project duration. Finally, the practical significance of the Extended DSM is confirmed by an illustrative example.展开更多
This paper deals with the problem of project scheduling subject to multiple execution modes with non-renewable resources, and a model that handles some of monetary issues in real world applications.The objective is to...This paper deals with the problem of project scheduling subject to multiple execution modes with non-renewable resources, and a model that handles some of monetary issues in real world applications.The objective is to schedule the activities to maximize the expected net present value(NPV) of the project, taking into account the activity costs, the activity durations, and the cash flows generated by successfully completing an activity.Owing to the combinatorial nature of this problem, the current study develops a hybrid of branch-and-bound procedure and memetic algorithm to enhance both mode assignment and activity scheduling.Modifications for the makespan minimization problem have been made through a set of benchmark problem instances.Algorithmic performance is rated on the maximization of the project NPV and computational results show that the two-phase hybrid metaheuristic performs competitively for all instances of different problem sizes.展开更多
China and Laos are close neighbors with a long-standing friendship.Since the early 2000s,China has supported Laos'economic and social development through wide-ranging cooperation projects,all guided by the vision ...China and Laos are close neighbors with a long-standing friendship.Since the early 2000s,China has supported Laos'economic and social development through wide-ranging cooperation projects,all guided by the vision of a community with a shared future.As this vision takes deeper root,many aid projects have moved from blueprint to reality,delivering tangible benefits across towns and villages and improving the lives of ordinary Lao people while further strengthening bilateral ties.展开更多
Projections of future urban land change are essential for a range of sustainability assessments,including those related to biodiversity loss,carbon emissions,and agricultural land conversion.However,to what extent and...Projections of future urban land change are essential for a range of sustainability assessments,including those related to biodiversity loss,carbon emissions,and agricultural land conversion.However,to what extent and where current projections agree or disagree remains unknown.Here,we systematically compare existing global projections that are consistent with the Shared Socioeconomic Pathways.We find that the total global urban land area is expected to increase by 112%between 2020 and 2100(averaged across all projections),with a coefficient of variation of 0.81.This variation is mostly caused by the selection of the underlying drivers that are included in the different models.Regionally,the highest average growth rates are found in sub-Saharan Africa(+679%to+730%),while this region also has the highest variation across projections(coefficient of variation ranging from 2.02 to 2.18).When ranking scenarios within a study from the highest to the lowest projected increase in urban land,rankings are relatively similar for regions in the Global North,but not for regions in the Global South.The large disagreement across projections can lead to high uncertainties in assessments of future urban land change impacts,which can undermine the effectiveness of long-term planning,policymaking,and resource management decisions.展开更多
This study provides potential climate projections for Central Asia(CA)based on multi-regional climate model(RCM)outputs from the Coordinated Regional Climate Downscaling Experiment for Central Asia(CORDEX-CAII).Despit...This study provides potential climate projections for Central Asia(CA)based on multi-regional climate model(RCM)outputs from the Coordinated Regional Climate Downscaling Experiment for Central Asia(CORDEX-CAII).Despite some systematic biases,all RCMs effectively capture the main features of observed temperature and precipitation means and extremes over CA,with notable variations in model performance due to differences in the driving global climate models and the RCMs themselves.Overall,REMO consistently outperforms ALARO in simulating temperature-related indices,and ALARO-0 provides more accurate simulations for precipitation-related indices,and the multimodel ensemble(MME)tends to outperform individual RCMs.Under the representative concentration pathway(RCP)scenarios of RCP2.6 and RCP8.5,the MME results indicate a clear warming trend across CA for all temperature-related indices,except for the diurnal temperature range,with annual temperatures projected to increase by 0.15℃/10 yr and 0.53℃/10 yr,respectively.Both scenarios exhibit similar spatial distributions in projected annual precipitation,characterized by peak increases of~0.2 mm per day in northern CA.The number of consecutive dry days is projected to slightly increase under RCP8.5,while it is expected to slightly decrease under RCP2.6.This study improves our understanding of the applicability of RCMs in CA and provides reliable projections of future climate change.展开更多
当下,小学英语板块教学存在活动形式单一化、探究活动浅表化等问题,综合育人价值未能完全发挥。为改变这一现状,文章以人教版英语(PEP)四年级上册Unit 1“Helping at home”的“Project:Make a poster of a happy family”为例,以项目...当下,小学英语板块教学存在活动形式单一化、探究活动浅表化等问题,综合育人价值未能完全发挥。为改变这一现状,文章以人教版英语(PEP)四年级上册Unit 1“Helping at home”的“Project:Make a poster of a happy family”为例,以项目化学习为支架,围绕项目设计、过程实施、评价反馈、成果展示等维度探究有效教学策略,旨在优化Project板块的教学模式,引导学生在项目化学习中提升语言运用能力和综合实践能力。展开更多
Climate models are essential for understanding past,present,and future changes in atmospheric circulation,with circulation modes providing key sources of seasonal predictability and prediction uncertainties for both g...Climate models are essential for understanding past,present,and future changes in atmospheric circulation,with circulation modes providing key sources of seasonal predictability and prediction uncertainties for both global and regional climates.This study assesses the performance of models participating in phase 6 of the Coupled Model Intercomparison Project in simulating interannual variability modes of Northern Hemisphere 500-hPa geopotential height during winter and summer,distinguishing predictable(potentially predictable on seasonal or longer timescales)and unpredictable(intraseasonal and essentially unpredictable at long range)components,using reanalysis data and a variance decomposition method.Although most models effectively capture unpredictable modes in reanalysis,their ability to reproduce dominant predictable modes-specifically the Pacific-North American pattern,Arctic Oscillation,and Western Pacific Oscillation in winter,and the East Atlantic and North Atlantic Oscillations in summer-varies notably.An optimal ensemble is identified to distinguish(a)predictable-external modes,dominated by external forcing,and(b)predictable-internal modes,associated with slow internal variability,during the historical period(1950-2014)and the SSP5-8.5 scenario(2036-2100).Under increased radiative forcing,the leading winter/summer predictable-external mode exhibits a more uniform spatial distribution,remarkably larger trend and annual variance,and enhanced height-sea surface temperature(SST)covariance under SSP5-8.5 compared to historical conditions.The dominant winter/summer predictable-internal modes also exhibit increased variance and height-SST covariance under SSP5-8.5,along with localized changes in spatial configuration.Minimal changes are observed in spatial distribution or variance for dominant winter/summer unpredictable modes under SSP5-8.5.This study,from a predictive perspective,deepens our understanding of model uncertainties and projected changes in circulations.展开更多
Accurate fission cross-sectional data for actinide nuclides are critical for nuclear energy,astrophysics,and defense applications.Traditional detectors,such as fission chambers,face limitations in achieving sub-3% unc...Accurate fission cross-sectional data for actinide nuclides are critical for nuclear energy,astrophysics,and defense applications.Traditional detectors,such as fission chambers,face limitations in achieving sub-3% uncertainty owing to particle identification challenges and dynamic range constraints.The time projection chamber(TPC)can record both the energy deposition dE/dx and the three-dimensional track of an event,providing the ability to identify particles and fission fragments.Based on this characteristic,we developed a novel TPC,INPC-TPC,featuring a symmetrical dual-chamber structure and gas electron multiplier(GEM)-based readout technology.The dual-chamber design isolates fission fragments and recoils protons,thereby reducing the dynamic range requirements of a single chamber,whereas the GEM ensures high spatial resolution and stable gain.Experiments conducted at the Chinese Spallation Neutron Source(CSNS)Back-n white neutron beamline validated the performance of the proposed detector.The INPC-TPC demonstrated effective fission fragment identification through particle energy-length correlation measurements and accurately measured the neutron beam spot size with a diameter relative error of<2%.The results highlight the capability of the system to achieve high-precision measurements of neutroninduced fission cross sections,particularly for ^(235)U and ^(238)U.展开更多
基金The Spring Plan of Ministry of Education,China(No.Z2012017)
文摘In order to minimize the project duration of resourceconstrained project scheduling problem( RCPSP), a gene expression programming-based scheduling rule( GEP-SR) method is proposed to automatically discover and select the effective scheduling rules( SRs) which are constructed using the project status and attributes of the activities. SRs are represented by the chromosomes of GEP, and an improved parallel schedule generation scheme( IPSGS) is used to transform the SRs into explicit schedules. The framework of GEP-SR for RCPSP is designed,and the effectiveness of the GEP-SR approach is demonstrated by comparing with other methods on the same instances.
基金supported by the National Natural Science Foundation of China(71171038)
文摘A memetic algorithm （MA） for a multi-mode resourceconstrained project scheduling problem （MRCPSP） is proposed. We use a new fitness function and two very effective local search procedures in the proposed MA. The fitness function makes use of a mechanism called ＂strategic oscillation＂ to make the search process have a higher probability to visit solutions around a ＂feasible boundary＂. One of the local search procedures aims at improving the lower bound of project makespan to be less than a known upper bound, and another aims at improving a solution of an MRCPSP instance accepting infeasible solutions based on the new fitness function in the search process. A detailed computational experiment is set up using instances from the problem instance library PSPLIB. Computational results show that the proposed MA is very competitive with the state-of-the-art algorithms. The MA obtains improved solutions for one instance of set J30.
基金supported by the National Natural Science Foundation of China(6083500460775047+4 种基金60974048)the National High Technology Research and Development Program of China(863 Program)(2007AA0422442008AA04Z214)the Natural Science Foundation of Hunan Province(09JJ9012)Scientific Research Fund of Hunan Provincial Education Department(08C337)
文摘An improved differential evolution（IDE）algorithm that adopts a novel mutation strategy to speed up the convergence rate is introduced to solve the resource-constrained project scheduling problem（RCPSP）with the objective of minimizing project duration Activities priorities for scheduling are represented by individual vectors and a senal scheme is utilized to transform the individual-represented priorities to a feasible schedule according to the precedence and resource constraints so as to be evaluated.To investigate the performance of the IDE-based approach for the RCPSP,it is compared against the meta-heuristic methods of hybrid genetic algorithm（HGA）,particle swarm optimization（PSO） and several well selected heuristics.The results show that the proposed scheduling method is better than general heuristic rules and is able to obtain the same optimal result as the HGA and PSO approaches but more efficient than the two algorithms.
基金supported by Liaoning BaiQianWan Talents Program(20071866-25)
文摘To solve the resource-constrained project scheduling problem(RCPSP),a hybrid ant colony optimization(HACO)approach is presented.To improve the quality of the schedules,the HACO is incorporated with an extended double justification in which the activity splitting is applied to predict whether the schedule could be improved.The HACO is tested on the set of large benchmark problems from the project scheduling problem library(PSPLIB).The computational result shows that the proposed algo-rithm can improve the quality of the schedules efficiently.
文摘This paper introduces a hybrid evolutionary algorithm for the resource-constrained project scheduling problem (RCPSP). Given an RCPSP instance, the algorithm identifies the problem structure and selects a suitable decoding scheme. Then a multi-pass biased sampling method followed up by a multi-local search is used to generate a diverse and good quality initial population. The population then evolves through modified order-based recombination and mutation operators to perform exploration for promising solutions within the entire region. Mutation is performed only if the current population has converged or the produced offspring by recombination operator is too similar to one of his parents. Finally the algorithm performs an intensified local search on the best solution found in the evolutionary stage. Computational experiments using standard instances indicate that the proposed algorithm works well in both computational time and solution quality.
基金Supported by the National Natural Science Foundation of China (60975050)the Specialized Research Fund for the Doctoral Program of Higher Education of China (20070486081)
文摘This paper presents a new method to solve the resource-constrained project scheduling problem for software development. In this method,activity duration times are described as fuzzy variables and resource-constrained software project scheduling problems are described as fuzzy programming models. First,how to model the software project scheduling problem under the fuzzy environment conditions is proposed. Second,in order to satisfy the different requirements of decision-making,two novel fuzzy project scheduling models,expected cost model and credibility maximization model,are suggested. Third,a hybrid intelligent algorithm integrated by genetic algorithm and fuzzy simulation is designed to solve the above two fuzzy programming models. Numerical experiments illustrate the effectiveness of the hybrid intelligent algorithm.
文摘This paper presents a new genetic algorithm for the resource-constrained project scheduling problem(RCPSP).The algorithm employs a standardized random key(SRK) vector representation with an additional gene that determines whether the serial or parallel schedule generation scheme(SGS) is to be used as the decoding procedure.The iterative forward-backward improvement as the local search procedure is applied upon all generated solutions to schedule the project three times and obtain an SRK vector,which is rese...
基金funded by the Ministry of Industry and Information Technology of the People’s Republic of China(Nos.[2018]473,[2019]331).
文摘Offshore engineering construction projects are large and complex,having the characteristics of multiple execution modes andmultiple resource constraints.Their complex internal scheduling processes can be regarded as resourceconstrained project scheduling problems(RCPSPs).To solve RCPSP problems in offshore engineering construction more rapidly,a hybrid genetic algorithmwas established.To solve the defects of genetic algorithms,which easily fall into the local optimal solution,a local search operation was added to a genetic algorithm to defend the offspring after crossover/mutation.Then,an elitist strategy and adaptive operators were adopted to protect the generated optimal solutions,reduce the computation time and avoid premature convergence.A calibrated function method was used to cater to the roulette rules,and appropriate rules for encoding,decoding and crossover/mutation were designed.Finally,a simple network was designed and validated using the case study of a real offshore project.The performance of the genetic algorithmand a simulated annealing algorithmwas compared to validate the feasibility and effectiveness of the approach.
文摘In this paper we formulate a bi-criteria search strategy of a heuristic learning algorithm for solving multiple resource-constrained project scheduling problems. The heuristic solves problems in two phases. In the pre-processing phase, the algorithm estimates distance between a state and the goal state and measures complexity of problem instances. In the search phase, the algorithm uses estimates of the pre-processing phase to further estimate distances to the goal state. The search continues in a stepwise generation of a series of intermediate states through search path evaluation process with backtracking. Developments of intermediate states are exclusively based on a bi-criteria new state selection technique where we consider resource utilization and duration estimate to the goal state. We also propose a variable weighting technique based on initial problem complexity measures. Introducing this technique allows the algorithm to efficiently solve complex project scheduling problems. A numerical example illustrates the algorithm and performance is evaluated by extensive experimentation with various problem parameters. Computational results indicate significance of the algorithm in terms of solution quality and computational performance.
文摘To solve the resource-constrained multiple project scheduling problem(RCMPSP) more effectively,a method based on timed colored Petri net(TCPN) was proposed.In this methodology,firstly a novel mapping mechanism between traditional network diagram such as CPM(critical path method)/PERT(program evaluation and review technique) and TCPN was presented.Then a primary TCPN(PTCPN) for solving RCMPSP was modeled based on the proposed mapping mechanism.Meanwhile,the object PTCPN was used to simulate the multiple projects scheduling and to find the approximately optimal value of RCMPSP.Finally,the performance of the proposed approach for solving RCMPSP was validated by executing a mould manufacturing example.
基金supported by the National Natural Science Foundation of China under Grant No.71172123the Aviation Science Fund under Grant No.2012ZG53083the Soft Science Foundation of Shaanxi Province and the funds of NPU for Humanities and social sciences and management revilization under Grant No.RW201105
文摘Dependency Structure Matrix （DSM） is a successful and powerful tool for representing and analyzing dependencies between the items, but for external influencing factors it cannot charge effectively. This paper sets the stage for connecting the activities and resources, which not only considers information flow but also resources constrains.We first introduce the DSM to represent the degree of overlapping between the activities in a project. Then we present the Extended DSM combined former DSM and resource factors to calculate the project duration. Finally, the practical significance of the Extended DSM is confirmed by an illustrative example.
文摘This paper deals with the problem of project scheduling subject to multiple execution modes with non-renewable resources, and a model that handles some of monetary issues in real world applications.The objective is to schedule the activities to maximize the expected net present value(NPV) of the project, taking into account the activity costs, the activity durations, and the cash flows generated by successfully completing an activity.Owing to the combinatorial nature of this problem, the current study develops a hybrid of branch-and-bound procedure and memetic algorithm to enhance both mode assignment and activity scheduling.Modifications for the makespan minimization problem have been made through a set of benchmark problem instances.Algorithmic performance is rated on the maximization of the project NPV and computational results show that the two-phase hybrid metaheuristic performs competitively for all instances of different problem sizes.
基金supported by the Yunnan Provincial Philosophy and Social Science Planning Projectthe Yunnan Academy of Social Sciences。
文摘China and Laos are close neighbors with a long-standing friendship.Since the early 2000s,China has supported Laos'economic and social development through wide-ranging cooperation projects,all guided by the vision of a community with a shared future.As this vision takes deeper root,many aid projects have moved from blueprint to reality,delivering tangible benefits across towns and villages and improving the lives of ordinary Lao people while further strengthening bilateral ties.
基金supported by the Netherlands Organization for Scientific Research NWO in the form of a VIDI grant(Grant No.VI.Vidi.198.008).
文摘Projections of future urban land change are essential for a range of sustainability assessments,including those related to biodiversity loss,carbon emissions,and agricultural land conversion.However,to what extent and where current projections agree or disagree remains unknown.Here,we systematically compare existing global projections that are consistent with the Shared Socioeconomic Pathways.We find that the total global urban land area is expected to increase by 112%between 2020 and 2100(averaged across all projections),with a coefficient of variation of 0.81.This variation is mostly caused by the selection of the underlying drivers that are included in the different models.Regionally,the highest average growth rates are found in sub-Saharan Africa(+679%to+730%),while this region also has the highest variation across projections(coefficient of variation ranging from 2.02 to 2.18).When ranking scenarios within a study from the highest to the lowest projected increase in urban land,rankings are relatively similar for regions in the Global North,but not for regions in the Global South.The large disagreement across projections can lead to high uncertainties in assessments of future urban land change impacts,which can undermine the effectiveness of long-term planning,policymaking,and resource management decisions.
基金jointly supported by the Second Tibetan Plateau Scientific Expedition and Research Program[grant number 2019QZKK0103]the National Natural Science Foundation of China[grant number 42293294]the China Meteorological Administration Climate Change Special Program[grant number QBZ202303]。
文摘This study provides potential climate projections for Central Asia(CA)based on multi-regional climate model(RCM)outputs from the Coordinated Regional Climate Downscaling Experiment for Central Asia(CORDEX-CAII).Despite some systematic biases,all RCMs effectively capture the main features of observed temperature and precipitation means and extremes over CA,with notable variations in model performance due to differences in the driving global climate models and the RCMs themselves.Overall,REMO consistently outperforms ALARO in simulating temperature-related indices,and ALARO-0 provides more accurate simulations for precipitation-related indices,and the multimodel ensemble(MME)tends to outperform individual RCMs.Under the representative concentration pathway(RCP)scenarios of RCP2.6 and RCP8.5,the MME results indicate a clear warming trend across CA for all temperature-related indices,except for the diurnal temperature range,with annual temperatures projected to increase by 0.15℃/10 yr and 0.53℃/10 yr,respectively.Both scenarios exhibit similar spatial distributions in projected annual precipitation,characterized by peak increases of~0.2 mm per day in northern CA.The number of consecutive dry days is projected to slightly increase under RCP8.5,while it is expected to slightly decrease under RCP2.6.This study improves our understanding of the applicability of RCMs in CA and provides reliable projections of future climate change.
文摘当下,小学英语板块教学存在活动形式单一化、探究活动浅表化等问题,综合育人价值未能完全发挥。为改变这一现状,文章以人教版英语(PEP)四年级上册Unit 1“Helping at home”的“Project:Make a poster of a happy family”为例,以项目化学习为支架,围绕项目设计、过程实施、评价反馈、成果展示等维度探究有效教学策略,旨在优化Project板块的教学模式,引导学生在项目化学习中提升语言运用能力和综合实践能力。
基金supported by the National Natural Science Foundation of China(Grant Nos.U2342210 and 42275043)the National Institute of Natural Hazards,Ministry of Emergency Management of China(Grant Nos.J2223806,ZDJ2024-25 and ZDJ2025-34)。
文摘Climate models are essential for understanding past,present,and future changes in atmospheric circulation,with circulation modes providing key sources of seasonal predictability and prediction uncertainties for both global and regional climates.This study assesses the performance of models participating in phase 6 of the Coupled Model Intercomparison Project in simulating interannual variability modes of Northern Hemisphere 500-hPa geopotential height during winter and summer,distinguishing predictable(potentially predictable on seasonal or longer timescales)and unpredictable(intraseasonal and essentially unpredictable at long range)components,using reanalysis data and a variance decomposition method.Although most models effectively capture unpredictable modes in reanalysis,their ability to reproduce dominant predictable modes-specifically the Pacific-North American pattern,Arctic Oscillation,and Western Pacific Oscillation in winter,and the East Atlantic and North Atlantic Oscillations in summer-varies notably.An optimal ensemble is identified to distinguish(a)predictable-external modes,dominated by external forcing,and(b)predictable-internal modes,associated with slow internal variability,during the historical period(1950-2014)and the SSP5-8.5 scenario(2036-2100).Under increased radiative forcing,the leading winter/summer predictable-external mode exhibits a more uniform spatial distribution,remarkably larger trend and annual variance,and enhanced height-sea surface temperature(SST)covariance under SSP5-8.5 compared to historical conditions.The dominant winter/summer predictable-internal modes also exhibit increased variance and height-SST covariance under SSP5-8.5,along with localized changes in spatial configuration.Minimal changes are observed in spatial distribution or variance for dominant winter/summer unpredictable modes under SSP5-8.5.This study,from a predictive perspective,deepens our understanding of model uncertainties and projected changes in circulations.
基金supported by the auspices of the Youth Doctoral Talent Incubation Program of the Second Affiliated Hospital of Army Medical University(No.2024YQB060)。
文摘Accurate fission cross-sectional data for actinide nuclides are critical for nuclear energy,astrophysics,and defense applications.Traditional detectors,such as fission chambers,face limitations in achieving sub-3% uncertainty owing to particle identification challenges and dynamic range constraints.The time projection chamber(TPC)can record both the energy deposition dE/dx and the three-dimensional track of an event,providing the ability to identify particles and fission fragments.Based on this characteristic,we developed a novel TPC,INPC-TPC,featuring a symmetrical dual-chamber structure and gas electron multiplier(GEM)-based readout technology.The dual-chamber design isolates fission fragments and recoils protons,thereby reducing the dynamic range requirements of a single chamber,whereas the GEM ensures high spatial resolution and stable gain.Experiments conducted at the Chinese Spallation Neutron Source(CSNS)Back-n white neutron beamline validated the performance of the proposed detector.The INPC-TPC demonstrated effective fission fragment identification through particle energy-length correlation measurements and accurately measured the neutron beam spot size with a diameter relative error of<2%.The results highlight the capability of the system to achieve high-precision measurements of neutroninduced fission cross sections,particularly for ^(235)U and ^(238)U.
