Optimization problems are prevalent in various fields of science and engineering,with several real-world applications characterized by high dimensionality and complex search landscapes.Starfish optimization algorithm(...Optimization problems are prevalent in various fields of science and engineering,with several real-world applications characterized by high dimensionality and complex search landscapes.Starfish optimization algorithm(SFOA)is a recently optimizer inspired by swarm intelligence,which is effective for numerical optimization,but it may encounter premature and local convergence for complex optimization problems.To address these challenges,this paper proposes the multi-strategy enhanced crested porcupine-starfish optimization algorithm(MCPSFOA).The core innovation of MCPSFOA lies in employing a hybrid strategy to improve SFOA,which integrates the exploratory mechanisms of SFOA with the diverse search capacity of the Crested Porcupine Optimizer(CPO).This synergy enhances MCPSFOA’s ability to navigate complex and multimodal search spaces.To further prevent premature convergence,MCPSFOA incorporates Lévy flight,leveraging its characteristic long and short jump patterns to enable large-scale exploration and escape from local optima.Subsequently,Gaussian mutation is applied for precise solution tuning,introducing controlled perturbations that enhance accuracy and mitigate the risk of insufficient exploitation.Notably,the population diversity enhancement mechanism periodically identifies and resets stagnant individuals,thereby consistently revitalizing population variety throughout the optimization process.MCPSFOA is rigorously evaluated on 24 classical benchmark functions(including high-dimensional cases),the CEC2017 suite,and the CEC2022 suite.MCPSFOA achieves superior overall performance with Friedman mean ranks of 2.208,2.310 and 2.417 on these benchmark functions,outperforming 11 state-of-the-art algorithms.Furthermore,the practical applicability of MCPSFOA is confirmed through its successful application to five engineering optimization cases,where it also yields excellent results.In conclusion,MCPSFOA is not only a highly effective and reliable optimizer for benchmark functions,but also a practical tool for solving real-world optimization problems.展开更多
Variable-fidelity(VF)surrogate models have received increasing attention in engineering design optimization as they can approximate expensive high-fidelity(HF)simulations with reduced computational power.A key challen...Variable-fidelity(VF)surrogate models have received increasing attention in engineering design optimization as they can approximate expensive high-fidelity(HF)simulations with reduced computational power.A key challenge to building a VF model is devising an adaptive model updating strategy that jointly selects additional low-fidelity(LF)and/or HF samples.The additional samples must enhance the model accuracy while maximizing the computational efficiency.We propose ISMA-VFEEI,a global optimization framework that integrates an Improved Slime-Mould Algorithm(ISMA)and a Variable-Fidelity Expected Extension Improvement(VFEEI)learning function to construct a VF surrogate model efficiently.First,A cost-aware VFEEI function guides the adaptive LF/HF sampling by explicitly incorporating evaluation cost and existing sample proximity.Second,ISMA is employed to solve the resulting non-convex optimization problem and identify global optimal infill points for model enhancement.The efficacy of ISMA-VFEEI is demonstrated through six numerical benchmarks and one real-world engineering case study.The engineering case study of a high-speed railway Electric Multiple Unit(EMU),the optimization objective of a sanding device attained a minimum value of 1.546 using only 20 HF evaluations,outperforming all the compared methods.展开更多
Optimal sizing and allocation of distributed generators(DGs)have become essential computational challenges in improving the performance,efficiency,and reliability of electrical distribution networks.Despite extensive ...Optimal sizing and allocation of distributed generators(DGs)have become essential computational challenges in improving the performance,efficiency,and reliability of electrical distribution networks.Despite extensive research,existing approaches often face algorithmic limitations such as slow convergence,premature stagnation in local minima,or suboptimal accuracy in determining optimal DG placement and capacity.This study presents a comprehensive scientometric and systematic review of global research focused on computer-based modelling and algorithmic optimization for renewable DG sizing and placement.It integrates both quantitative and qualitative analyses of the scholarly landscape,mapping influential research domains,co-authorship structures,the articles’citation networks,keyword clusters,and international collaboration patterns.Moreover,the study classifies and evaluates the most prominent objective functions,key computational models and optimization algorithms,DG technologies,and strategic approaches employed in the field.The findings reveal that advanced algorithmic frameworks substantially enhance network stability,minimize real power losses,and improve voltage profiles under various operational constraints.This review serves as a foundational resource for researchers and practitioners,highlighting emerging algorithmic trends,modelling innovations,and data-driven methodologies that can guide future development of intelligent,optimization-based DG integration strategies in smart distribution systems.展开更多
In this paper,an adaptive cubic regularisation algorithm based on affine scaling methods(ARCBASM)is proposed for solving nonlinear equality constrained programming with nonnegative constraints on variables.From the op...In this paper,an adaptive cubic regularisation algorithm based on affine scaling methods(ARCBASM)is proposed for solving nonlinear equality constrained programming with nonnegative constraints on variables.From the optimality conditions of the problem,we introduce appropriate affine matrix and construct an affine scaling ARC subproblem with linearized constraints.Composite step methods and reduced Hessian methods are applied to tackle the linearized constraints.As a result,a standard unconstrained ARC subproblem is deduced and its solution can supply sufficient decrease.The fraction to the boundary rule maintains the strict feasibility(for nonnegative constraints on variables)of every iteration point.Reflection techniques are employed to prevent the iterations from approaching zero too early.Under mild assumptions,global convergence of the algorithm is analysed.Preliminary numerical results are reported.展开更多
In this paper,we consider the fourth-order parabolic equation with p(x)Laplacian and variable exponent source ut+∆^(2)u−div(|■u|^(p(x)−2■u))=|u|^(q(x))−1u.By applying potential well method,we obtain global existence...In this paper,we consider the fourth-order parabolic equation with p(x)Laplacian and variable exponent source ut+∆^(2)u−div(|■u|^(p(x)−2■u))=|u|^(q(x))−1u.By applying potential well method,we obtain global existence,asymptotic behavior and blow-up of solutions with initial energy J(u_(0))≤d.Moreover,we estimate the upper bound of the blow-up time for J(u_(0))≤0.展开更多
The Global Governance Initiative(GGI)is another important public good that China has provided for the international community,following the Global Development Initiative,the Global Security Initiative,and the Global C...The Global Governance Initiative(GGI)is another important public good that China has provided for the international community,following the Global Development Initiative,the Global Security Initiative,and the Global Civilization Initiative.As a sub-field of global governance,global climate governance has hitherto progressed slowly,exhibiting growing deficits in discourse,institutions,and actions.The governance paradigm is in desperate need of revamping,especially under the guidance of an innovative initiative.At the conceptual level,the GGI has gone beyond the Western governance discourse by outlining the institutional starting point,foundations of legitimacy,action orientations,ultimate goals,and practical support for good global climate governance through its five core concepts.At the practical level,the spillover effects of China's achievements in climate governance and the collective rise of the Global South have created favorable conditions,domestically and internationally,for the GGI to lead the way forward toward good global climate governance.However,the fact that the international political and economic order remains unjust and inequitable indicates that this will inevitably be a long-term process replete with rivalries in the pursuit of breakthroughs.展开更多
In recent years, the overall strength of Western developed countries, led by the United States, has declined relatively, resulting in a trend of decentralization. This has posed severe challenges to the traditional gl...In recent years, the overall strength of Western developed countries, led by the United States, has declined relatively, resulting in a trend of decentralization. This has posed severe challenges to the traditional global governance system with regard to trade, security, and multilateral cooperation. However, this trend also provides a historical opportunity to transform the global governance system into one that is more inclusive and equitable. This can be seen in the reconstruction of value priorities, the adjustment of governance focus, the reform of governance mechanisms, and the promotion of new mechanisms. Only by adhering to openness and inclusiveness and balancing rights and responsibilities can we build a future governance order that conforms to the common interests of all humanity.展开更多
Refractory metals,including tungsten(W),tantalum(Ta),molybdenum(Mo),and niobium(Nb),play a vital role in industries,such as nuclear energy and aerospace,owing to their exceptional melting temperatures,thermal durabili...Refractory metals,including tungsten(W),tantalum(Ta),molybdenum(Mo),and niobium(Nb),play a vital role in industries,such as nuclear energy and aerospace,owing to their exceptional melting temperatures,thermal durability,and corrosion resistance.These metals have body-centered cubic crystal structure,characterized by limited slip systems and impeded dislocation motion,resulting in significant low-temperature brittleness,which poses challenges for the conventional processing.Additive manufacturing technique provides an innovative approach,enabling the production of intricate parts without molds,which significantly improves the efficiency of material usage.This review provides a comprehensive overview of the advancements in additive manufacturing techniques for the production of refractory metals,such as W,Ta,Mo,and Nb,particularly the laser powder bed fusion.In this review,the influence mechanisms of key process parameters(laser power,scan strategy,and powder characteristics)on the evolution of material microstructure,the formation of metallurgical defects,and mechanical properties were discussed.Generally,optimizing powder characteristics,such as sphericity,implementing substrate preheating,and formulating alloying strategies can significantly improve the densification and crack resistance of manufactured parts.Meanwhile,strictly controlling the oxygen impurity content and optimizing the energy density input are also the key factors to achieve the simultaneous improvement in strength and ductility of refractory metals.Although additive manufacturing technique provides an innovative solution for processing refractory metals,critical issues,such as residual stress control,microstructure and performance anisotropy,and process stability,still need to be addressed.This review not only provides a theoretical basis for the additive manufacturing of high-performance refractory metals,but also proposes forward-looking directions for their industrial application.展开更多
Aiming to solve the steering instability and hysteresis of agricultural robots in the process of movement,a fusion PID control method of particle swarm optimization(PSO)and genetic algorithm(GA)was proposed.The fusion...Aiming to solve the steering instability and hysteresis of agricultural robots in the process of movement,a fusion PID control method of particle swarm optimization(PSO)and genetic algorithm(GA)was proposed.The fusion algorithm took advantage of the fast optimization ability of PSO to optimize the population screening link of GA.The Simulink simulation results showed that the convergence of the fitness function of the fusion algorithm was accelerated,the system response adjustment time was reduced,and the overshoot was almost zero.Then the algorithm was applied to the steering test of agricultural robot in various scenes.After modeling the steering system of agricultural robot,the steering test results in the unloaded suspended state showed that the PID control based on fusion algorithm reduced the rise time,response adjustment time and overshoot of the system,and improved the response speed and stability of the system,compared with the artificial trial and error PID control and the PID control based on GA.The actual road steering test results showed that the PID control response rise time based on the fusion algorithm was the shortest,about 4.43 s.When the target pulse number was set to 100,the actual mean value in the steady-state regulation stage was about 102.9,which was the closest to the target value among the three control methods,and the overshoot was reduced at the same time.The steering test results under various scene states showed that the PID control based on the proposed fusion algorithm had good anti-interference ability,it can adapt to the changes of environment and load and improve the performance of the control system.It was effective in the steering control of agricultural robot.This method can provide a reference for the precise steering control of other robots.展开更多
Optimization algorithms are crucial for solving NP-hard problems in engineering and computational sciences.Metaheuristic algorithms,in particular,have proven highly effective in complex optimization scenarios characte...Optimization algorithms are crucial for solving NP-hard problems in engineering and computational sciences.Metaheuristic algorithms,in particular,have proven highly effective in complex optimization scenarios characterized by high dimensionality and intricate variable relationships.The Mountain Gazelle Optimizer(MGO)is notably effective but struggles to balance local search refinement and global space exploration,often leading to premature convergence and entrapment in local optima.This paper presents the Improved MGO(IMGO),which integrates three synergistic enhancements:dynamic chaos mapping using piecewise chaotic sequences to boost explo-ration diversity;Opposition-Based Learning(OBL)with adaptive,diversity-driven activation to speed up convergence;and structural refinements to the position update mechanisms to enhance exploitation.The IMGO underwent a comprehensive evaluation using 52 standardised benchmark functions and seven engineering optimization problems.Benchmark evaluations showed that IMGO achieved the highest rank in best solution quality for 31 functions,the highest rank in mean performance for 18 functions,and the highest rank in worst-case performance for 14 functions among 11 competing algorithms.Statistical validation using Wilcoxon signed-rank tests confirmed that IMGO outperformed individual competitors across 16 to 50 functions,depending on the algorithm.At the same time,Friedman ranking analysis placed IMGO with an average rank of 4.15,compared to the baseline MGO’s 4.38,establishing the best overall performance.The evaluation of engineering problems revealed consistent improvements,including an optimal cost of 1.6896 for the welded beam design vs.MGO’s 1.7249,a minimum cost of 5885.33 for the pressure vessel design vs.MGO’s 6300,and a minimum weight of 2964.52 kg for the speed reducer design vs.MGO’s 2990.00 kg.Ablation studies identified OBL as the strongest individual contributor,whereas complete integration achieved superior performance through synergistic interactions among components.Computational complexity analysis established an O(T×N×5×f(P))time complexity,representing a 1.25×increase in fitness evaluation relative to the baseline MGO,validating the favorable accuracy-efficiency trade-offs for practical optimization applications.展开更多
The onset,cessation,and length of the rainy season are crucial for global water resources,agricultural practices,and food security.However,the response of precipitation seasonality to global warming remains uncertain....The onset,cessation,and length of the rainy season are crucial for global water resources,agricultural practices,and food security.However,the response of precipitation seasonality to global warming remains uncertain.In this study,we analyze how global warming levels(GWLs)of 1.5℃ and 2℃ could affect the timing of rainfall onset(RODs),rainfall cessation(RCDs),and the overall duration of the rainy season(LRS)over global land monsoon(GLM)regions using simulations from CMIP6 under the SSP2-4.5 and SSP5-8.5 scenarios.With high model consensus,our results reveal that RODs are projected to occur later over Southern Africa,North Africa,and South America,but earlier over South Asia and Australia,in a warmer climate.The projected early RODs in Australia are more pronounced at the 2℃ GWL under SSP5-8.5.On the other hand,early RCDs are projected over South America and East Asia,while late RCDs are projected over North Africa,with high inter-model agreement.These changes are associated with a future decrease in LRS in most GLM regions.Additionally,we found that continuous warming over 1.5℃ will further reduce the length of the rainy season,especially over the South America,North Africa,and Southern Africa monsoon regions.The findings underscore the urgent need to mitigate global warming.展开更多
As we enter the year 2026,the international system continues to receive shocks from Donald Trump,arguably the 21st century’s most disruptive US leader.His return to the White House in 2025 coincided with the 80th ann...As we enter the year 2026,the international system continues to receive shocks from Donald Trump,arguably the 21st century’s most disruptive US leader.His return to the White House in 2025 coincided with the 80th anniversary of the defeat of fascism and the establishment of the United Nations,the multilateral platform that carried the world’s hope for peace,restraint and collective security.The coincidence was unsettling.A world order designed to limit power now confronts a moment in which power is exercised openly,transactionally and unapologetically.展开更多
On September 1,2025,Chinese President Xi Jinping solemnly proposed the Global Governance Initiative(GGI)at the“Shanghai Cooperation Organization Plus”meeting,answering a question posed by the times:what kind of glob...On September 1,2025,Chinese President Xi Jinping solemnly proposed the Global Governance Initiative(GGI)at the“Shanghai Cooperation Organization Plus”meeting,answering a question posed by the times:what kind of global governance system to build and how to reform and improve global governance.The GGI is committed to sovereign equality,the international rule of law,multilateralism,the people-centered approach,and real results,offering China's wisdom and solutions for building a more just and equitable global governance system.On the journey ahead,China will hold high the banner of a community with a shared future for humanity and advance the GGI through multiple measures,effectively strengthening and improving global governance.展开更多
Optimization is the key to obtaining efficient utilization of resources in structural design.Due to the complex nature of truss systems,this study presents a method based on metaheuristic modelling that minimises stru...Optimization is the key to obtaining efficient utilization of resources in structural design.Due to the complex nature of truss systems,this study presents a method based on metaheuristic modelling that minimises structural weight under stress and frequency constraints.Two new algorithms,the Red Kite Optimization Algorithm(ROA)and Secretary Bird Optimization Algorithm(SBOA),are utilized on five benchmark trusses with 10,18,37,72,and 200-bar trusses.Both algorithms are evaluated against benchmarks in the literature.The results indicate that SBOA always reaches a lighter optimal.Designs with reducing structural weight ranging from 0.02%to 0.15%compared to ROA,and up to 6%–8%as compared to conventional algorithms.In addition,SBOA can achieve 15%–20%faster convergence speed and 10%–18%reduction in computational time with a smaller standard deviation over independent runs,which demonstrates its robustness and reliability.It is indicated that the adaptive exploration mechanism of SBOA,especially its Levy flight–based search strategy,can obviously improve optimization performance for low-and high-dimensional trusses.The research has implications in the context of promoting bio-inspired optimization techniques by demonstrating the viability of SBOA,a reliable model for large-scale structural design that provides significant enhancements in performance and convergence behavior.展开更多
During 13 to 16 January 2026,with 148 participating nations,rising global relevance and a marked increase in visitor quality,Heimtextil 2026 stood for stability and reliability in a volatile market environment.Once ag...During 13 to 16 January 2026,with 148 participating nations,rising global relevance and a marked increase in visitor quality,Heimtextil 2026 stood for stability and reliability in a volatile market environment.Once again,3,000 exhibitors from across the globe placed their trust in the industry’s central platform in Frankfurt,presenting current collections,materials and textile solutions for holistic interior design to approximately 47,000 buyers.Under the motto“Lead the Change”,Heimtextil brought evolving market dynamics,Artificial Intelligence(AI)and new business opportunities to life.The focus was on progressive design approaches,visionary talents,functional textiles and new hospitality concepts shaping the future of interior design.A tangible sense of confidence and a clear commitment to Heimtextil as a strong industry partner resonated throughout the exhibition halls.展开更多
China’s shipbuilding industry maintained the world’s largest market share in terms of three major indicators for the 16th consecutive year in 2025,according to data released by the Ministry of Industry and Informati...China’s shipbuilding industry maintained the world’s largest market share in terms of three major indicators for the 16th consecutive year in 2025,according to data released by the Ministry of Industry and Information Technology on 1 February.展开更多
Background:Investigators from low-,middle-,and high-income countries representing 6 continents contributed to the development of the Global Adolescent and Child Physical Activity Questionnaire(GAC-PAQ).The GAC-PAQ is ...Background:Investigators from low-,middle-,and high-income countries representing 6 continents contributed to the development of the Global Adolescent and Child Physical Activity Questionnaire(GAC-PAQ).The GAC-PAQ is designed to assess physical activity(PA)across all key domains(i.e.,school,chores,work/volunteering,transport,free time,outdoor time).It aimed to address multiple gaps in global PA surveillance(e.g.,omission of important PA domains,insufficient cultural adaptation,underrepresentation of rural areas in questionnaire validation studies).The purpose of this study was to assess the content validity of the GAC-PAQ among PA experts,8-to 17-year-olds,and one of their parents/guardians,and to discuss changes made to the questionnaire based on participants'feedback.Methods:Sixty-two experts in PA measurement and/or surveillance from 24 countries completed an online survey that included both closed-and open-ended questions about the content validity of the GAC-PAQ.The proportion of experts who agreed or strongly agreed with the items was calculated.Child-parent/guardian dyads from 15 countries(n=250;10-40 per country)participated in a structured cognitive interview to assess the clarity of the questions and response options,and they were encouraged to provide suggestions to improve clarity and facilitate completion of the questionnaire.Participating countries are:Aotearoa New Zealand,Brazil,Canada,China,Colombia,Czech Republic,India,Malawi,Mexico,Nepal,Nigeria,Spain,Sweden,Thailand,and the United Arab Emirates.Interviews were conducted in 13 different languages and structured by PA domain.Generic images were included to help participants in answering questions about PA intensity.Results:Expert agreement with the items for each domain exceeded 75%,and their qualitative feedback was used to revise the questionnaire before cognitive interviews.In general,participants found the questionnaire to be comprehensive.Adolescents(12-17 years)found it easier than children(8-11 years)to answer the questions.Several children struggled to answer questions about the duration and intensity of activities and/or concepts related to travel modes,active trips,and organized activities.Many parents/guardians were unsure about the frequency,duration,and intensity of their children's or adolescents'PA at school and/or recommended using more culturally relevant and appropriate images.Some participants misunderstood the concept of activities that“make you stronger”(intended to assess resistance activities)and/or struggled to differentiate between work,volunteering,and chores.Conclusion:Participants'feedback was used to develop a revised,simplified,and culturally adapted GAC-PAQ,which will be pilot-tested in all15 countries in an App that will include country-specific images and narration in local languages.Further research is needed to assess the reliability and validity of the revised GAC-PAQ.展开更多
This study investigates the impact of vegetation-climate feedback on the global land monsoon system during the Last Interglacial(LIG,127000 years BP)and the mid-Holocene(MH,6000 years BP)using the earth system model E...This study investigates the impact of vegetation-climate feedback on the global land monsoon system during the Last Interglacial(LIG,127000 years BP)and the mid-Holocene(MH,6000 years BP)using the earth system model EC-Earth3.Our findings indicate that vegetation changes significantly influence the global monsoon area and precipitation patterns,especially in the North African and Indian monsoon regions.The North African monsoon region experienced the most substantial increase in vegetation during both the LIG and MH,resulting in significant increases in monsoonal precipitation by 9.8%and 6.0%,respectively.The vegetation feedback also intensified the Saharan Heat Low,strengthened monsoonal flows,and enhanced precipitation over the North African monsoon region.In contrast,the Indian monsoon region exhibited divergent responses to vegetation changes.During the LIG,precipitation in the Indian monsoon region decreased by 2.2%,while it increased by 1.6%during the MH.These differences highlight the complex and region-specific impacts of vegetation feedback on monsoon systems.Overall,this study demonstrates that vegetation feedback exerts distinct influences on the global monsoon during the MH and LIG.These findings highlight the importance of considering vegetation-climate feedback in understanding past monsoon variability and in predicting future climate change impacts on monsoon systems.展开更多
To help university students know more about standards,and attract them to par ticipate in s tandardization ac tivities,the International Standardization Youth Star Competition was initiated by the International Standa...To help university students know more about standards,and attract them to par ticipate in s tandardization ac tivities,the International Standardization Youth Star Competition was initiated by the International Standardization Outstanding Contribution Award Foundation(ISOCAF)in 2023,and has been held since then for three consecutive years in China.The 2025 Competition attracted 236 teams nationwide who demonstrated great enthusiasm for engaging in the standardization undertaking.The SPECIAL REPORT column presents the series reports on the competition,which is expected to inspire more young minds to step forward,innovate with purpose,and shape a future where standards unite ambition with impact.展开更多
Experts and officials shared their insights on poverty reduction cooperation and sustainable development during the 2025 International Seminar on Global Poverty Reduction Partnerships.
基金supported by the National Natural Science Foundation of China(Grant No.12402139,No.52368070)supported by Hainan Provincial Natural Science Foundation of China(Grant No.524QN223)+3 种基金Scientific Research Startup Foundation of Hainan University(Grant No.RZ2300002710)State Key Laboratory of Structural Analysis,Optimization and CAE Software for Industrial Equipment,Dalian University of Technology(Grant No.GZ24107)the Horizontal Research Project(Grant No.HD-KYH-2024022)Innovative Research Projects for Postgraduate Students in Hainan Province(Grant No.Hys2025-217).
文摘Optimization problems are prevalent in various fields of science and engineering,with several real-world applications characterized by high dimensionality and complex search landscapes.Starfish optimization algorithm(SFOA)is a recently optimizer inspired by swarm intelligence,which is effective for numerical optimization,but it may encounter premature and local convergence for complex optimization problems.To address these challenges,this paper proposes the multi-strategy enhanced crested porcupine-starfish optimization algorithm(MCPSFOA).The core innovation of MCPSFOA lies in employing a hybrid strategy to improve SFOA,which integrates the exploratory mechanisms of SFOA with the diverse search capacity of the Crested Porcupine Optimizer(CPO).This synergy enhances MCPSFOA’s ability to navigate complex and multimodal search spaces.To further prevent premature convergence,MCPSFOA incorporates Lévy flight,leveraging its characteristic long and short jump patterns to enable large-scale exploration and escape from local optima.Subsequently,Gaussian mutation is applied for precise solution tuning,introducing controlled perturbations that enhance accuracy and mitigate the risk of insufficient exploitation.Notably,the population diversity enhancement mechanism periodically identifies and resets stagnant individuals,thereby consistently revitalizing population variety throughout the optimization process.MCPSFOA is rigorously evaluated on 24 classical benchmark functions(including high-dimensional cases),the CEC2017 suite,and the CEC2022 suite.MCPSFOA achieves superior overall performance with Friedman mean ranks of 2.208,2.310 and 2.417 on these benchmark functions,outperforming 11 state-of-the-art algorithms.Furthermore,the practical applicability of MCPSFOA is confirmed through its successful application to five engineering optimization cases,where it also yields excellent results.In conclusion,MCPSFOA is not only a highly effective and reliable optimizer for benchmark functions,but also a practical tool for solving real-world optimization problems.
基金funded by National Natural Science Foundation of China(grant No.52405255)Special Program of Huzhou(grant No.2023GZ05)+1 种基金Projects of Huzhou Science and Technology Correspondent(grant No.2023KT76)Guangdong Basic and Applied Basic Research Foundation(grant No.2025A1515010487)。
文摘Variable-fidelity(VF)surrogate models have received increasing attention in engineering design optimization as they can approximate expensive high-fidelity(HF)simulations with reduced computational power.A key challenge to building a VF model is devising an adaptive model updating strategy that jointly selects additional low-fidelity(LF)and/or HF samples.The additional samples must enhance the model accuracy while maximizing the computational efficiency.We propose ISMA-VFEEI,a global optimization framework that integrates an Improved Slime-Mould Algorithm(ISMA)and a Variable-Fidelity Expected Extension Improvement(VFEEI)learning function to construct a VF surrogate model efficiently.First,A cost-aware VFEEI function guides the adaptive LF/HF sampling by explicitly incorporating evaluation cost and existing sample proximity.Second,ISMA is employed to solve the resulting non-convex optimization problem and identify global optimal infill points for model enhancement.The efficacy of ISMA-VFEEI is demonstrated through six numerical benchmarks and one real-world engineering case study.The engineering case study of a high-speed railway Electric Multiple Unit(EMU),the optimization objective of a sanding device attained a minimum value of 1.546 using only 20 HF evaluations,outperforming all the compared methods.
基金supported and funded by the Deanship of Scientific Research at Imam Mohammad Ibn Saud Islamic University(IMSIU)(grant number:IMSIU-DDRSP2503)。
文摘Optimal sizing and allocation of distributed generators(DGs)have become essential computational challenges in improving the performance,efficiency,and reliability of electrical distribution networks.Despite extensive research,existing approaches often face algorithmic limitations such as slow convergence,premature stagnation in local minima,or suboptimal accuracy in determining optimal DG placement and capacity.This study presents a comprehensive scientometric and systematic review of global research focused on computer-based modelling and algorithmic optimization for renewable DG sizing and placement.It integrates both quantitative and qualitative analyses of the scholarly landscape,mapping influential research domains,co-authorship structures,the articles’citation networks,keyword clusters,and international collaboration patterns.Moreover,the study classifies and evaluates the most prominent objective functions,key computational models and optimization algorithms,DG technologies,and strategic approaches employed in the field.The findings reveal that advanced algorithmic frameworks substantially enhance network stability,minimize real power losses,and improve voltage profiles under various operational constraints.This review serves as a foundational resource for researchers and practitioners,highlighting emerging algorithmic trends,modelling innovations,and data-driven methodologies that can guide future development of intelligent,optimization-based DG integration strategies in smart distribution systems.
基金Supported by the National Natural Science Foundation of China(12071133)Natural Science Foundation of Henan Province(252300421993)Key Scientific Research Project of Higher Education Institutions in Henan Province(25B110005)。
文摘In this paper,an adaptive cubic regularisation algorithm based on affine scaling methods(ARCBASM)is proposed for solving nonlinear equality constrained programming with nonnegative constraints on variables.From the optimality conditions of the problem,we introduce appropriate affine matrix and construct an affine scaling ARC subproblem with linearized constraints.Composite step methods and reduced Hessian methods are applied to tackle the linearized constraints.As a result,a standard unconstrained ARC subproblem is deduced and its solution can supply sufficient decrease.The fraction to the boundary rule maintains the strict feasibility(for nonnegative constraints on variables)of every iteration point.Reflection techniques are employed to prevent the iterations from approaching zero too early.Under mild assumptions,global convergence of the algorithm is analysed.Preliminary numerical results are reported.
基金Supported by NSFC(No.12101482)the Natural Science Foundation of Shaanxi Province,China(No.2018JQ1052)。
文摘In this paper,we consider the fourth-order parabolic equation with p(x)Laplacian and variable exponent source ut+∆^(2)u−div(|■u|^(p(x)−2■u))=|u|^(q(x))−1u.By applying potential well method,we obtain global existence,asymptotic behavior and blow-up of solutions with initial energy J(u_(0))≤d.Moreover,we estimate the upper bound of the blow-up time for J(u_(0))≤0.
基金2024 Shaanxi Provincial Social Science Fund Annual Project titled"Research on Chinese Modernization from the Perspective of Overseas Studies on the Communist Party of China"(Project Number:2024B002)a 2024 key project of Xi'an Jiaotong University for studying and expounding Xi Jinping Thought on Culture titled"Research on the World Implications of a New Model for Human Advancement"(Project Number:SKZX2024003)funded by the"Top Young Talents Project"(TZ0275)of Shaanxi Province's second batch of"Special Support Program for High-Level Talents"(Philosophy,Social Sciences,Culture,and Arts).
文摘The Global Governance Initiative(GGI)is another important public good that China has provided for the international community,following the Global Development Initiative,the Global Security Initiative,and the Global Civilization Initiative.As a sub-field of global governance,global climate governance has hitherto progressed slowly,exhibiting growing deficits in discourse,institutions,and actions.The governance paradigm is in desperate need of revamping,especially under the guidance of an innovative initiative.At the conceptual level,the GGI has gone beyond the Western governance discourse by outlining the institutional starting point,foundations of legitimacy,action orientations,ultimate goals,and practical support for good global climate governance through its five core concepts.At the practical level,the spillover effects of China's achievements in climate governance and the collective rise of the Global South have created favorable conditions,domestically and internationally,for the GGI to lead the way forward toward good global climate governance.However,the fact that the international political and economic order remains unjust and inequitable indicates that this will inevitably be a long-term process replete with rivalries in the pursuit of breakthroughs.
文摘In recent years, the overall strength of Western developed countries, led by the United States, has declined relatively, resulting in a trend of decentralization. This has posed severe challenges to the traditional global governance system with regard to trade, security, and multilateral cooperation. However, this trend also provides a historical opportunity to transform the global governance system into one that is more inclusive and equitable. This can be seen in the reconstruction of value priorities, the adjustment of governance focus, the reform of governance mechanisms, and the promotion of new mechanisms. Only by adhering to openness and inclusiveness and balancing rights and responsibilities can we build a future governance order that conforms to the common interests of all humanity.
基金National MCF Energy R&D Program(2024YFE03260300)。
文摘Refractory metals,including tungsten(W),tantalum(Ta),molybdenum(Mo),and niobium(Nb),play a vital role in industries,such as nuclear energy and aerospace,owing to their exceptional melting temperatures,thermal durability,and corrosion resistance.These metals have body-centered cubic crystal structure,characterized by limited slip systems and impeded dislocation motion,resulting in significant low-temperature brittleness,which poses challenges for the conventional processing.Additive manufacturing technique provides an innovative approach,enabling the production of intricate parts without molds,which significantly improves the efficiency of material usage.This review provides a comprehensive overview of the advancements in additive manufacturing techniques for the production of refractory metals,such as W,Ta,Mo,and Nb,particularly the laser powder bed fusion.In this review,the influence mechanisms of key process parameters(laser power,scan strategy,and powder characteristics)on the evolution of material microstructure,the formation of metallurgical defects,and mechanical properties were discussed.Generally,optimizing powder characteristics,such as sphericity,implementing substrate preheating,and formulating alloying strategies can significantly improve the densification and crack resistance of manufactured parts.Meanwhile,strictly controlling the oxygen impurity content and optimizing the energy density input are also the key factors to achieve the simultaneous improvement in strength and ductility of refractory metals.Although additive manufacturing technique provides an innovative solution for processing refractory metals,critical issues,such as residual stress control,microstructure and performance anisotropy,and process stability,still need to be addressed.This review not only provides a theoretical basis for the additive manufacturing of high-performance refractory metals,but also proposes forward-looking directions for their industrial application.
文摘Aiming to solve the steering instability and hysteresis of agricultural robots in the process of movement,a fusion PID control method of particle swarm optimization(PSO)and genetic algorithm(GA)was proposed.The fusion algorithm took advantage of the fast optimization ability of PSO to optimize the population screening link of GA.The Simulink simulation results showed that the convergence of the fitness function of the fusion algorithm was accelerated,the system response adjustment time was reduced,and the overshoot was almost zero.Then the algorithm was applied to the steering test of agricultural robot in various scenes.After modeling the steering system of agricultural robot,the steering test results in the unloaded suspended state showed that the PID control based on fusion algorithm reduced the rise time,response adjustment time and overshoot of the system,and improved the response speed and stability of the system,compared with the artificial trial and error PID control and the PID control based on GA.The actual road steering test results showed that the PID control response rise time based on the fusion algorithm was the shortest,about 4.43 s.When the target pulse number was set to 100,the actual mean value in the steady-state regulation stage was about 102.9,which was the closest to the target value among the three control methods,and the overshoot was reduced at the same time.The steering test results under various scene states showed that the PID control based on the proposed fusion algorithm had good anti-interference ability,it can adapt to the changes of environment and load and improve the performance of the control system.It was effective in the steering control of agricultural robot.This method can provide a reference for the precise steering control of other robots.
文摘Optimization algorithms are crucial for solving NP-hard problems in engineering and computational sciences.Metaheuristic algorithms,in particular,have proven highly effective in complex optimization scenarios characterized by high dimensionality and intricate variable relationships.The Mountain Gazelle Optimizer(MGO)is notably effective but struggles to balance local search refinement and global space exploration,often leading to premature convergence and entrapment in local optima.This paper presents the Improved MGO(IMGO),which integrates three synergistic enhancements:dynamic chaos mapping using piecewise chaotic sequences to boost explo-ration diversity;Opposition-Based Learning(OBL)with adaptive,diversity-driven activation to speed up convergence;and structural refinements to the position update mechanisms to enhance exploitation.The IMGO underwent a comprehensive evaluation using 52 standardised benchmark functions and seven engineering optimization problems.Benchmark evaluations showed that IMGO achieved the highest rank in best solution quality for 31 functions,the highest rank in mean performance for 18 functions,and the highest rank in worst-case performance for 14 functions among 11 competing algorithms.Statistical validation using Wilcoxon signed-rank tests confirmed that IMGO outperformed individual competitors across 16 to 50 functions,depending on the algorithm.At the same time,Friedman ranking analysis placed IMGO with an average rank of 4.15,compared to the baseline MGO’s 4.38,establishing the best overall performance.The evaluation of engineering problems revealed consistent improvements,including an optimal cost of 1.6896 for the welded beam design vs.MGO’s 1.7249,a minimum cost of 5885.33 for the pressure vessel design vs.MGO’s 6300,and a minimum weight of 2964.52 kg for the speed reducer design vs.MGO’s 2990.00 kg.Ablation studies identified OBL as the strongest individual contributor,whereas complete integration achieved superior performance through synergistic interactions among components.Computational complexity analysis established an O(T×N×5×f(P))time complexity,representing a 1.25×increase in fitness evaluation relative to the baseline MGO,validating the favorable accuracy-efficiency trade-offs for practical optimization applications.
基金supported by the Australian Research Council(Grant No.CE230100012)。
文摘The onset,cessation,and length of the rainy season are crucial for global water resources,agricultural practices,and food security.However,the response of precipitation seasonality to global warming remains uncertain.In this study,we analyze how global warming levels(GWLs)of 1.5℃ and 2℃ could affect the timing of rainfall onset(RODs),rainfall cessation(RCDs),and the overall duration of the rainy season(LRS)over global land monsoon(GLM)regions using simulations from CMIP6 under the SSP2-4.5 and SSP5-8.5 scenarios.With high model consensus,our results reveal that RODs are projected to occur later over Southern Africa,North Africa,and South America,but earlier over South Asia and Australia,in a warmer climate.The projected early RODs in Australia are more pronounced at the 2℃ GWL under SSP5-8.5.On the other hand,early RCDs are projected over South America and East Asia,while late RCDs are projected over North Africa,with high inter-model agreement.These changes are associated with a future decrease in LRS in most GLM regions.Additionally,we found that continuous warming over 1.5℃ will further reduce the length of the rainy season,especially over the South America,North Africa,and Southern Africa monsoon regions.The findings underscore the urgent need to mitigate global warming.
文摘As we enter the year 2026,the international system continues to receive shocks from Donald Trump,arguably the 21st century’s most disruptive US leader.His return to the White House in 2025 coincided with the 80th anniversary of the defeat of fascism and the establishment of the United Nations,the multilateral platform that carried the world’s hope for peace,restraint and collective security.The coincidence was unsettling.A world order designed to limit power now confronts a moment in which power is exercised openly,transactionally and unapologetically.
文摘On September 1,2025,Chinese President Xi Jinping solemnly proposed the Global Governance Initiative(GGI)at the“Shanghai Cooperation Organization Plus”meeting,answering a question posed by the times:what kind of global governance system to build and how to reform and improve global governance.The GGI is committed to sovereign equality,the international rule of law,multilateralism,the people-centered approach,and real results,offering China's wisdom and solutions for building a more just and equitable global governance system.On the journey ahead,China will hold high the banner of a community with a shared future for humanity and advance the GGI through multiple measures,effectively strengthening and improving global governance.
文摘Optimization is the key to obtaining efficient utilization of resources in structural design.Due to the complex nature of truss systems,this study presents a method based on metaheuristic modelling that minimises structural weight under stress and frequency constraints.Two new algorithms,the Red Kite Optimization Algorithm(ROA)and Secretary Bird Optimization Algorithm(SBOA),are utilized on five benchmark trusses with 10,18,37,72,and 200-bar trusses.Both algorithms are evaluated against benchmarks in the literature.The results indicate that SBOA always reaches a lighter optimal.Designs with reducing structural weight ranging from 0.02%to 0.15%compared to ROA,and up to 6%–8%as compared to conventional algorithms.In addition,SBOA can achieve 15%–20%faster convergence speed and 10%–18%reduction in computational time with a smaller standard deviation over independent runs,which demonstrates its robustness and reliability.It is indicated that the adaptive exploration mechanism of SBOA,especially its Levy flight–based search strategy,can obviously improve optimization performance for low-and high-dimensional trusses.The research has implications in the context of promoting bio-inspired optimization techniques by demonstrating the viability of SBOA,a reliable model for large-scale structural design that provides significant enhancements in performance and convergence behavior.
文摘During 13 to 16 January 2026,with 148 participating nations,rising global relevance and a marked increase in visitor quality,Heimtextil 2026 stood for stability and reliability in a volatile market environment.Once again,3,000 exhibitors from across the globe placed their trust in the industry’s central platform in Frankfurt,presenting current collections,materials and textile solutions for holistic interior design to approximately 47,000 buyers.Under the motto“Lead the Change”,Heimtextil brought evolving market dynamics,Artificial Intelligence(AI)and new business opportunities to life.The focus was on progressive design approaches,visionary talents,functional textiles and new hospitality concepts shaping the future of interior design.A tangible sense of confidence and a clear commitment to Heimtextil as a strong industry partner resonated throughout the exhibition halls.
文摘China’s shipbuilding industry maintained the world’s largest market share in terms of three major indicators for the 16th consecutive year in 2025,according to data released by the Ministry of Industry and Information Technology on 1 February.
基金supported by a Project Grant(Grant No.PJT183705)an Early Career Investigator Prize(Grant No.ECP 184184)from the Canadian Institutes of Health Research+7 种基金a Prentice Institute Research Affiliate Fund Grant from the Prentice Institute for Global Population and Economy(Grant No.G00004116)a Te Herenga Waka Victoria University of Wellington Division of Science Health Engineering Architecture and Design Innovation Faculty Strategic Research Grant(Grant No.FSRG-SHEADI-10724)The Thailand Physical Activity Knowledge Development Centre(TPAK)/Thai Health Promotion Foundation provided funding for the cognitive interviews and pilot study in Thailand(Grant No.66-P1-0473)The University Pablo de Olavide provided a scholarship for 2 undergraduate students working on the project(codes PPI2207 and PPI2308)In the Czech Republicthe study was supported by Palacky University IGA(Grant No.IGA_FTK_2023_017)supported by the Division of Intramural Research at the National Institute on Minority Health and Health Disparities of the National Institutes of Healthsupported by the Key Project of the National Philosophy and Social Science Foundation of China(23&ZD197)。
文摘Background:Investigators from low-,middle-,and high-income countries representing 6 continents contributed to the development of the Global Adolescent and Child Physical Activity Questionnaire(GAC-PAQ).The GAC-PAQ is designed to assess physical activity(PA)across all key domains(i.e.,school,chores,work/volunteering,transport,free time,outdoor time).It aimed to address multiple gaps in global PA surveillance(e.g.,omission of important PA domains,insufficient cultural adaptation,underrepresentation of rural areas in questionnaire validation studies).The purpose of this study was to assess the content validity of the GAC-PAQ among PA experts,8-to 17-year-olds,and one of their parents/guardians,and to discuss changes made to the questionnaire based on participants'feedback.Methods:Sixty-two experts in PA measurement and/or surveillance from 24 countries completed an online survey that included both closed-and open-ended questions about the content validity of the GAC-PAQ.The proportion of experts who agreed or strongly agreed with the items was calculated.Child-parent/guardian dyads from 15 countries(n=250;10-40 per country)participated in a structured cognitive interview to assess the clarity of the questions and response options,and they were encouraged to provide suggestions to improve clarity and facilitate completion of the questionnaire.Participating countries are:Aotearoa New Zealand,Brazil,Canada,China,Colombia,Czech Republic,India,Malawi,Mexico,Nepal,Nigeria,Spain,Sweden,Thailand,and the United Arab Emirates.Interviews were conducted in 13 different languages and structured by PA domain.Generic images were included to help participants in answering questions about PA intensity.Results:Expert agreement with the items for each domain exceeded 75%,and their qualitative feedback was used to revise the questionnaire before cognitive interviews.In general,participants found the questionnaire to be comprehensive.Adolescents(12-17 years)found it easier than children(8-11 years)to answer the questions.Several children struggled to answer questions about the duration and intensity of activities and/or concepts related to travel modes,active trips,and organized activities.Many parents/guardians were unsure about the frequency,duration,and intensity of their children's or adolescents'PA at school and/or recommended using more culturally relevant and appropriate images.Some participants misunderstood the concept of activities that“make you stronger”(intended to assess resistance activities)and/or struggled to differentiate between work,volunteering,and chores.Conclusion:Participants'feedback was used to develop a revised,simplified,and culturally adapted GAC-PAQ,which will be pilot-tested in all15 countries in an App that will include country-specific images and narration in local languages.Further research is needed to assess the reliability and validity of the revised GAC-PAQ.
基金supported by the Swedish Research Council(Vetenskapsradet,Grant No.202203129)the Project of Youth Science and Technology Fund of Gansu Province(Grant No.24JRRA439)partially funded by the Swedish Research Council(Vetenskapsradet,Grant No.2022-06725)。
文摘This study investigates the impact of vegetation-climate feedback on the global land monsoon system during the Last Interglacial(LIG,127000 years BP)and the mid-Holocene(MH,6000 years BP)using the earth system model EC-Earth3.Our findings indicate that vegetation changes significantly influence the global monsoon area and precipitation patterns,especially in the North African and Indian monsoon regions.The North African monsoon region experienced the most substantial increase in vegetation during both the LIG and MH,resulting in significant increases in monsoonal precipitation by 9.8%and 6.0%,respectively.The vegetation feedback also intensified the Saharan Heat Low,strengthened monsoonal flows,and enhanced precipitation over the North African monsoon region.In contrast,the Indian monsoon region exhibited divergent responses to vegetation changes.During the LIG,precipitation in the Indian monsoon region decreased by 2.2%,while it increased by 1.6%during the MH.These differences highlight the complex and region-specific impacts of vegetation feedback on monsoon systems.Overall,this study demonstrates that vegetation feedback exerts distinct influences on the global monsoon during the MH and LIG.These findings highlight the importance of considering vegetation-climate feedback in understanding past monsoon variability and in predicting future climate change impacts on monsoon systems.
文摘To help university students know more about standards,and attract them to par ticipate in s tandardization ac tivities,the International Standardization Youth Star Competition was initiated by the International Standardization Outstanding Contribution Award Foundation(ISOCAF)in 2023,and has been held since then for three consecutive years in China.The 2025 Competition attracted 236 teams nationwide who demonstrated great enthusiasm for engaging in the standardization undertaking.The SPECIAL REPORT column presents the series reports on the competition,which is expected to inspire more young minds to step forward,innovate with purpose,and shape a future where standards unite ambition with impact.
文摘Experts and officials shared their insights on poverty reduction cooperation and sustainable development during the 2025 International Seminar on Global Poverty Reduction Partnerships.
