Enhancing the resilience of critical infrastructure(CI)systems has become a focal point of national and inter-national policies.However,the formulation of resilience enhancement strategies often requires component-(i....Enhancing the resilience of critical infrastructure(CI)systems has become a focal point of national and inter-national policies.However,the formulation of resilience enhancement strategies often requires component-(i.e.asset-)level prioritization,which entails many complexities.Acknowledging the complex and interdependent nature of infrastructure systems,this paper aims to aid researchers,practitioners and policy-makers by pre-senting a review of the relative literature and current state-of-the-art,and by identifying future research op-portunities to improve the applicability and operationalizability of CI component identification and prioritization methods.Theoretical and practical applications are reviewed for definitions,analysis and modelling approaches regarding the resilience of interdependent infrastructure systems.A detailed review of infrastructure criticality definitions,component criticality assessment and prioritization frameworks,from scientific,policy and other documents,is presented.A discussion on social justice and equity dimensions therein is included,which have the potential to greatly influence decisions and should always be incorporated in infrastructure planning and in-vestment discussions.The findings of this review are discussed in terms of applicability and operationalizability.Key recommendations for future research include:(i)developing quantification frameworks for CI component criticality based on formal definitions and multiple criteria,(ii)incorporating the entire resilience cycle of CI in component prioritization,(iii)accounting for the socio-technical nature of CI systems by integrating social di-mensions and their wider operating environment and(iv)developing comprehensive model validation,cali-bration and uncertainty analysis frameworks.展开更多
Habitat loss driven by land-use change is a major factor shaping the dynamics of urban bird community structures.However,the potential mechanisms by which the spatial configuration and composition of blue-green infras...Habitat loss driven by land-use change is a major factor shaping the dynamics of urban bird community structures.However,the potential mechanisms by which the spatial configuration and composition of blue-green infrastructure,recognized as biodiversity hotspots in urban landscapes,influence urban bird beta diversity remain insufficiently understood.This study was conducted in the built-up area of Yinchuan,an internationally recognized wetland city in Northwest China.From December 2023 to June 2024,we systematically surveyed bird communities during both the breeding and wintering periods across 29 blue-green space mosaics.We quantified taxonomic,functional,and phylogenetic beta diversity,along with their turnover component and nestedness-resultant component,based on both pairwise beta diversity and multiple-site beta diversity.We further assessed the relative importance of landscape variables and spatial geographic distance in shaping beta diversity patterns and used hierarchical modeling of species communities(HMSC)to explore the responses of bird occurrence and functional traits to landscape variables.Our results revealed that species turnover was the dominant driver of taxonomic,functional,and phylogenetic beta diversity.Seasonal differences were observed in the effects of spatial geographic distance and landscape structure on beta diversity and its components,with landscape variables showing higher explanatory power than geographic isolation.In the breeding period,landscape diversity and waterbody area had positive effects on bird occurrence,whereas in the wintering period,most landscape features—except for landscape diversity—exerted neutral or negative influences.Regarding functional traits,we found that reproductive traits,flight ability,and foraging characteristics responded significantly to landscape structure,and that some small-bodied species active in aerial and canopy layers were more adaptable to habitat fragmentation.This study provides novel insights into the assembly processes and driving mechanisms of urban bird communities and offers scientific support for the notion that designing and maintaining blue-green infrastructure can contribute to urban biodiversity conservation.展开更多
The year 2026 marks the 70th anniversary of the establishment of diplomatic relations between China and African countries.It also marks the launch of the China-Africa Year of People-to-People Exchanges.At this pivotal...The year 2026 marks the 70th anniversary of the establishment of diplomatic relations between China and African countries.It also marks the launch of the China-Africa Year of People-to-People Exchanges.At this pivotal juncture linking past achievements with future development,Wang Yi,member of the Political Bureau of the Communist Party of China Central Committee and foreign minister,continued the longstanding diplomatic tradition under which the Chinese foreign minister makes Africa the destination of the first overseas visit of the year,a practice upheld for 36 consecutive years,underscoring the stability,continuity and sincerity of China’s policy towards Africa.展开更多
The evolution of cities into digitally managed environments requires computational systems that can operate in real time while supporting predictive and adaptive infrastructure management.Earlier approaches have often...The evolution of cities into digitally managed environments requires computational systems that can operate in real time while supporting predictive and adaptive infrastructure management.Earlier approaches have often advanced one dimension—such as Internet of Things(IoT)-based data acquisition,Artificial Intelligence(AI)-driven analytics,or digital twin visualization—without fully integrating these strands into a single operational loop.As a result,many existing solutions encounter bottlenecks in responsiveness,interoperability,and scalability,while also leaving concerns about data privacy unresolved.This research introduces a hybrid AI–IoT–Digital Twin framework that combines continuous sensing,distributed intelligence,and simulation-based decision support.The design incorporates multi-source sensor data,lightweight edge inference through Convolutional Neural Networks(CNN)and Long ShortTerm Memory(LSTM)models,and federated learning enhanced with secure aggregation and differential privacy to maintain confidentiality.A digital twin layer extends these capabilities by simulating city assets such as traffic flows and water networks,generating what-if scenarios,and issuing actionable control signals.Complementary modules,including model compression and synchronization protocols,are embedded to ensure reliability in bandwidth-constrained and heterogeneous urban environments.The framework is validated in two urban domains:traffic management,where it adapts signal cycles based on real-time congestion patterns,and pipeline monitoring,where it anticipates leaks through pressure and vibration data.Experimental results show a 28%reduction in response time,a 35%decrease in maintenance costs,and a marked reduction in false positives relative to conventional baselines.The architecture also demonstrates stability across 50+edge devices under federated training and resilience to uneven node participation.The proposed system provides a scalable and privacy-aware foundation for predictive urban infrastructure management.By closing the loop between sensing,learning,and control,it reduces operator dependence,enhances resource efficiency,and supports transparent governance models for emerging smart cities.展开更多
Structural Health Monitoring(SHM)plays a critical role in ensuring the safety,integrity,longevity and economic efficiency of civil infrastructures.The field has undergone a profound transformation over the last few de...Structural Health Monitoring(SHM)plays a critical role in ensuring the safety,integrity,longevity and economic efficiency of civil infrastructures.The field has undergone a profound transformation over the last few decades,evolving from traditional methods—often reliant on visual inspections—to data-driven intelligent systems.This review paper analyzes this historical trajectory,beginning with the approaches that relied on modal parameters as primary damage indicators.The advent of advanced sensor technologies and increased computational power brings a significant change,making Machine Learning(ML)a viable and powerful tool for damage assessment.More recently,Deep Learning(DL)has emerged as a paradigm shift,allowing for more automated processing of large data sets(such as the structural vibration signals and other types of sensors)with excellent performance and accuracy,often surpassing previous methods.This paper systematically reviews these technological milestones—from traditional vibration-based methods to the current state-of-the-art in deep learning.Finally,it critically examines emerging trends—such as Digital Twins and Transformer-based architectures—and discusses future research directions that will shape the next generation of SHM systems for civil engineering.展开更多
As the frontier of multidimensional transportation systems,urban air mobility(UAM)is receiving increasing attention from international organizations,governments,and stakeholders in industry and academia owing to its h...As the frontier of multidimensional transportation systems,urban air mobility(UAM)is receiving increasing attention from international organizations,governments,and stakeholders in industry and academia owing to its high efficiency,low carbon footprint,and operational flexibility.Vertical take-off and landing(VTOL)infrastructure is the core facility that enables UAM and is therefore essential for its safe,efficient,and large-scale commercial implementation.However,the key technologies for establishing low-altitude VTOL infrastructure are still nascent,and government,industry,and academia have yet to harmonize the corresponding construction,management,and operation standards.To address this gap,we herein systematically review the related progress and trends,comprehensively surveying the key technologies of establishing VTOL infrastructure serving unmanned aerial vehicles(UAVs)and electric VTOL aircraft from three complementary perspectives of ground-side,airspace-side,and communication,navigation,surveillance,and information services.In the light of future UAM operations characterized by diverse vehicle types and dense air traffic,we propose a conceptual design for a public multioperator VTOL site to provide constructive insights into the sustainable growth of the low-altitude economy.展开更多
The national grid and other life-sustaining critical infrastructures face an unprecedented threat from prolonged blackouts,which could last over a year and pose a severe risk to national security.Whether caused by phy...The national grid and other life-sustaining critical infrastructures face an unprecedented threat from prolonged blackouts,which could last over a year and pose a severe risk to national security.Whether caused by physical attacks,EMP(electromagnetic pulse)events,or cyberattacks,such disruptions could cripple essential services like water supply,healthcare,communication,and transportation.Research indicates that an attack on just nine key substations could result in a coast-to-coast blackout lasting up to 18 months,leading to economic collapse,civil unrest,and a breakdown of public order.This paper explores the key vulnerabilities of the grid,the potential impacts of prolonged blackouts,and the role of AI(artificial intelligence)and ML(machine learning)in mitigating these threats.AI-driven cybersecurity measures,predictive maintenance,automated threat response,and EMP resilience strategies are discussed as essential solutions to bolster grid security.Policy recommendations emphasize the need for hardened infrastructure,enhanced cybersecurity,redundant power systems,and AI-based grid management to ensure national resilience.Without proactive measures,the nation remains exposed to a catastrophic power grid failure that could have dire consequences for society and the economy.展开更多
Over the past few years,major investments have been directed toward building new railway lines and upgrading existing ones.Many of these lines include critical infrastructure where operational and safety conditions mu...Over the past few years,major investments have been directed toward building new railway lines and upgrading existing ones.Many of these lines include critical infrastructure where operational and safety conditions must be carefully considered throughout their life cycle.Recent advancements in science and technology have enabled more effective structural monitoring of railway systems,largely driven by the adoption of intelligent strategies for inspection,maintenance,monitoring,and risk management.Research continues to expand and deepen the knowledge in this area;however,it remains a challenging field due to factors such as the complexity of railway systems,the high cost of implementation,and the need for reliable long-term data.展开更多
The efficient transportation of goods is vital for the economic growth of communities,making developing and maintaining seaport infrastructure an essential component of the marine transportation system.Given their geo...The efficient transportation of goods is vital for the economic growth of communities,making developing and maintaining seaport infrastructure an essential component of the marine transportation system.Given their geographic locations,ports are consistently at risk from natural hazards,making the resilience of port infrastructure an essential goal.Despite considerable progress in resilience research,there remains a gap in methods tailored explicitly to assessing port resilience,particularly under extreme wind events.Current approaches often do not capture the full complexity of port systems,as they tend to focus on isolated aspects,such as structural resilience.This paper introduces the PORT Resilience Framework,addressing these gaps by evaluating resilience through a comprehensive list of indicators gathered from various legitimate sources.The indicators are then organized under four comprehensive resilience dimensions:Physical Infrastructure,ICT(i.e.,Information and Communication Technology)and Equipment;Organization and Business Management;Resources and Economic Development;and Territory,Environment,and Stakeholders.This classification is summarized under the acronym"PORT."This paper also introduces a method for aggregating resilience indicators by considering their performance before and after a specific hazard,transforming the data into a quantifiable Loss of Resilience index.The approach is applied to a case study,assessing the resilience of a real Terminal against wind action using real data sourced from the port management.The case study analysis revealed that human resources and quay operations were the most critical factors affecting recovery,with insufficient staffing leading to prolonged recovery periods.The study further demonstrated that post-disruption activity surges,captured by different serviceability function methodologies,often created operational bottlenecks,challenging the port's overall recovery.展开更多
As offshore wind infrastructure becomes more important to global efforts to reduce carbon emissions,it is becoming more important to connect lifecycle cost management with circular economy(CE)principles.When looking a...As offshore wind infrastructure becomes more important to global efforts to reduce carbon emissions,it is becoming more important to connect lifecycle cost management with circular economy(CE)principles.When looking at the long-term costs of infrastructure,traditional lifecycle cost models often fail to account for residual value recovery,material circularity,or environmental externalities.This study creates a unified analytical framework that adds CE strategies to lifecycle cost modelling for offshore wind systems,such as turbines,substructures,moorings,and floating platforms.The method uses multi-objective optimization and system dynamics simulation along with net present value(NPV)modelling,material flow analysis,and carbonadjusted cost accounting.We modelled project-level datasets over 25 years to look at the trade-offs between economic and environmental factors in both linear and circular lifecycle scenarios.We use Python,MATLAB,and OpenLCA to look at key metrics like the Material Circularity Indicator(MCI),estimates of residual value,and internalized carbon costs.The results show that circular infrastructure strategies greatly lower lifecycle costs while also increasing material recovery and carbon efficiency.Scenario simulations showed that CE-based configurations could cut costs by up to 18%and emissions over the life of the product by 22%.Regression and sensitivity analyses showed that MCI,CAPEX,and circular design strategies are good at predicting residual value and long-term economic performance.This study adds a new,evidence-based model for making decisions about infrastructure that takes into account financial,environmental,and material circularity.展开更多
Scientific and technological advancements are rapidly transforming underground engineering,shifting from labor-intensive,time-consuming methods to automated,real-time systems.This timely and comprehensive review cover...Scientific and technological advancements are rapidly transforming underground engineering,shifting from labor-intensive,time-consuming methods to automated,real-time systems.This timely and comprehensive review covers in-situ testing,intelligent monitoring,and geophysical testing methods,highlighting fundamental principles,testing apparatuses,data processing techniques,and engineering applications.The state-of-the-art summary emphasizes not only cutting-edge innovations for complex and harsh environments but also the transformative role of artificial intelligence and machine learning in data interpretations.The integration of big data and advanced algorithms is particularly impactful,enabling the identification,prediction,and mitigation of potential risks in underground projects.Key aspects of the discussion include detection capabilities,method integration,and data convergence of intelligent technologies to drive enhanced safety,operational efficiency,and predictive reliability.The review also examines future trends in intelligent technologies,emphasizing unified platforms that combine multiple methods,real-time data,and predictive analytics.These advancements are shaping the evolution of underground construction and maintenance,aiming for risk-free,high-efficiency underground engineering.展开更多
Marine infrastructure is increasingly vulnerable to harsh environmental conditions that accelerate the degradation of traditional materials such as Portland cement concrete and carbon steel.This review systematically ...Marine infrastructure is increasingly vulnerable to harsh environmental conditions that accelerate the degradation of traditional materials such as Portland cement concrete and carbon steel.This review systematically investigates recent advancements in sustainable alternatives,including geopolymer concrete,engineered innovacementitious composites(ECC),bio-concrete,fiber-reinforced polymers(FRPs),and bamboo,stainless steel,and steel-CFRP hybrid bars.Each material is evaluated based on marine durability,mechanical performance,environmental impact,and cost feasibility using life cycle assessment,durability modelling,and a multi-criteria decisionsupport framework.The results reveal that geopolymer concrete and FRP reinforcement’s exhibit superior corrosion resistance and environmental benefits,while ECC and steel-CFRP composites offer structural resilience with moderate environmental trade-offs.However,challenges remain in long-term performance validation,standardization,and market integration.The review concludes that a combined approach involving innovative materials,computational tools,and sustainability assessment is essential for advancing marine infrastructure.Outlook recommendations include focused field studies,development of regulatory guidelines,and interdisciplinary collaboration to drive the practical adoption of eco-efficient materials in coastal and offshore construction.展开更多
In this work,we present a parallel implementation of radiation hydrodynamics coupled with particle transport,utilizing software infrastructure JASMIN(J Adaptive Structured Meshes applications INfrastructure)which enca...In this work,we present a parallel implementation of radiation hydrodynamics coupled with particle transport,utilizing software infrastructure JASMIN(J Adaptive Structured Meshes applications INfrastructure)which encapsulates high-performance technology for the numerical simulation of complex applications.Two serial codes,radiation hydrodynamics RH2D and particle transport Sn2D,have been integrated into RHSn2D on JASMIN infrastructure,which can efficiently use thousands of processors to simulate the complex multi-physics phenomena.Moreover,the non-conforming processors strategy has ensured RHSn2D against the serious load imbalance between radiation hydrodynamics and particle transport for large scale parallel simulations.Numerical results show that RHSn2D achieves a parallel efficiency of 17.1%using 90720 cells on 8192 processors compared with 256 processors in the same problem.展开更多
Structural health monitoring technology uses advanced sensors to collect structural state data in real time,evaluate its integrity and residual life,and make maintenance decisions accordingly.The key of structural hea...Structural health monitoring technology uses advanced sensors to collect structural state data in real time,evaluate its integrity and residual life,and make maintenance decisions accordingly.The key of structural health monitoring is to obtain structural data accurately.With the development of new sensor technology,sensors and data acquisition devices for structural health monitoring are constantly emerging,and the performance of these devices is developing rapidly.The latest developments of fiber optic sensors,piezoelectric material sensors and self-diagnostic sensors for structural health monitoring are summarized.The basic working principle of each sensor and its application in structural health monitoring are introduced,and the challenges and opportunities faced by sensors in structural health monitoring are prospected.展开更多
Quantifying material use in infrastructure development and analyzing its relationship with economic growth is essential for enhancing resource efficiency and steering regional resource management toward sustainable de...Quantifying material use in infrastructure development and analyzing its relationship with economic growth is essential for enhancing resource efficiency and steering regional resource management toward sustainable development.This study systematically assessed infrastructure related material use in 30 provinces,autonomous regions,and municipalities in China during 1978-2022.The result indicated that material stock has experienced significant growth,increasing from 16.91×10^(9)t in 1978 to 103.60×10^(9)t in 2022,with an average annual growth rate of 4.20%.However,from 1978 to 2015,material input followed a strong upward trend but saturated after 2015.At the national level,material input peaked in 2015,after which it began to decline.The central region reached its peak earlier in 2013,while the eastern and western regions peaked in 2015.Using a decoupling analysis framework,this study revealed that nationally,the elasticity value between material stock and gross domestic product(GDP)remained near or above 1.0,reflecting continued reliance on stock accumulation.Regionally,the elasticity value between material stock and GDP has increased in the central and western regions during 1978-2022,whereas elasticity value between material stock and GDP in the eastern region showed a slower growth rate but still struggled to achieve absolute decoupling.Moreover,the elasticity value between material input and GDP has declined at the national level,presenting a relative decoupling,with some regions already achieving absolute decoupling.The eastern region was closer to absolute decoupling,while the central and western regions,though still intensive in material input,exhibited faster declines in elasticity.Accelerating the transition from linear to circular economy is an essential step for China to achieve absolute decoupling and long-term sustainability.Finally,this research recommends promoting the adoption of renewable energy,driving industrial upgrading,implementing compact urban design,and extending the lifespan of infrastructure to reduce material dependency and achieve sustainable infrastructure transformation at the national level.展开更多
This research conducted a systematic study on the processes of migration of energy-related pollutants caused by nanoparticles in marine sediments,as well as their impacts on the durability of offshore infrastructure.W...This research conducted a systematic study on the processes of migration of energy-related pollutants caused by nanoparticles in marine sediments,as well as their impacts on the durability of offshore infrastructure.While focused on representative nanoparticles(nano-TiO_(2),nano-Fe_(3)O_(4),and carbon nanotubes)and select energy pollutants,experimental data showed these materials greatly enhanced the movement of pollutants,increasing migration distances from 1.6 to 2.9 times.The carbon nanotubes possessed the greatest carrying effect,increasing the phenanthrene migration distance by 286 percent.The study determined surface properties of nanoparticles,pH of the liquid environment,ionic concentration,and organic matter level as major elements impacting pollutant mobility.Laboratory simulations,while controlled and reproducible,necessarily simplified the complex dynamics of real marine environments.Nanoparticle-sorbate systems were found to be effective in enhancing the deterioration rate of materials used in offshore constructions,with CNTPAHs composites causing carbon steel to corrode by 183% more than if PAHs were used without the composites.This change in corrosion behaviour was shown in other tests to be caused by a change in dynamics of the corrosion products'structural constituents and the various electrochemical properties present on the surface of the material.Samples of concrete showed a spend of 90 days in the composite system resulted in a 26.8% decrease in compressive strength compared to control conditions which had only a 15.3%.Therefore,taking into account the results,strategies were formulated to ensure durability for offshore infrastructure including surface modified anticorrosion coatings,surveillance and alert systems,and integrated protective systems.Future field validation studies are needed to verify these laboratory findings under actual marine conditions.This study helps to comprehend the behaviour of nanoparticles in intricate marine ecosystems,providing support for the sustainable advancement of offshore infrastructure and the protection of the marine environment.展开更多
The increasing frequency and severity of natural disasters,exacerbated by global warming,necessitate novel solutions to strengthen the resilience of Critical Infrastructure Systems(CISs).Recent research reveals the si...The increasing frequency and severity of natural disasters,exacerbated by global warming,necessitate novel solutions to strengthen the resilience of Critical Infrastructure Systems(CISs).Recent research reveals the sig-nificant potential of natural language processing(NLP)to analyze unstructured human language during disasters,thereby facilitating the uncovering of disruptions and providing situational awareness supporting various aspects of resilience regarding CISs.Despite this potential,few studies have systematically mapped the global research on NLP applications with respect to supporting various aspects of resilience of CISs.This paper contributes to the body of knowledge by presenting a review of current knowledge using the scientometric review technique.Using 231 bibliographic records from the Scopus and Web of Science core collections,we identify five key research areas where researchers have used NLP to support the resilience of CISs during natural disasters,including sentiment analysis,crisis informatics,data and knowledge visualization,disaster impacts,and content analysis.Furthermore,we map the utility of NLP in the identified research focus with respect to four aspects of resilience(i.e.,preparedness,absorption,recovery,and adaptability)and present various common techniques used and potential future research directions.This review highlights that NLP has the potential to become a supplementary data source to support the resilience of CISs.The results of this study serve as an introductory-level guide designed to help scholars and practitioners unlock the potential of NLP for strengthening the resilience of CISs against natural disasters.展开更多
On 13 December 2024,liquefied natural gas(LNG)company Venture Global LNG(Arlington,VA,USA)commenced commercial production of the super-chilled fuel at its partially completed Plaquemines LNG export terminal in Louisia...On 13 December 2024,liquefied natural gas(LNG)company Venture Global LNG(Arlington,VA,USA)commenced commercial production of the super-chilled fuel at its partially completed Plaquemines LNG export terminal in Louisiana(Fig.1)[1].In terms of dollars invested,the 21 billion USD plant is the fourth largest infrastructure project in the world[2].Venture Global initially expected the terminal to produce and ship 20 million tonnes of LNG annually[3].An 18 billion USD expansion of the terminal approved in February 2025 will bring its maximum annual produc-tion capacity to 45 million tonnes[4].When fully operational in 2027,the facility,located in Plaquemines Parish on the Mississippi River about 32 km south of New Orleans,will be among the largest in the world,further contributing to the US position as the world’s biggest LNG exporter[1].展开更多
Since its inception,the Belt and Road Initiative(BRI)has emerged as a global platform for international cooperation,with infrastructure connectivity at its core.Infrastructure,often referred to as the“lifeblood”of e...Since its inception,the Belt and Road Initiative(BRI)has emerged as a global platform for international cooperation,with infrastructure connectivity at its core.Infrastructure,often referred to as the“lifeblood”of economic and social development,plays a pivotal role in breaking bottlenecks,bridging regional gaps,and driving inclusive growth-particularly in developing regions where inadequate infrastructure has long hindered progress.展开更多
The NIST Cybersecurity Framework (NIST CSF) serves as a voluntary guideline aimed at helping organizations, tiny and medium-sized enterprises (SMEs), and critical infrastructure operators, effectively manage cyber ris...The NIST Cybersecurity Framework (NIST CSF) serves as a voluntary guideline aimed at helping organizations, tiny and medium-sized enterprises (SMEs), and critical infrastructure operators, effectively manage cyber risks. Although comprehensive, the complexity of the NIST CSF can be overwhelming, especially for those lacking extensive cybersecurity resources. Current implementation tools often cater to larger companies, neglecting the specific needs of SMEs, which can be vulnerable to cyber threats. To address this gap, our research proposes a user-friendly, open-source web platform designed to simplify the implementation of the NIST CSF. This platform enables organizations to assess their risk exposure and continuously monitor their cybersecurity maturity through tailored recommendations based on their unique profiles. Our methodology includes a literature review of existing tools and standards, followed by a description of the platform’s design and architecture. Initial tests with SMEs in Burkina Faso reveal a concerning cybersecurity maturity level, indicating the urgent need for improved strategies based on our findings. By offering an intuitive interface and cross-platform accessibility, this solution aims to empower organizations to enhance their cybersecurity resilience in an evolving threat landscape. The article concludes with discussions on the practical implications and future enhancements of the tool.展开更多
基金supported by the European Union’s Horizon 2020 research and innovation programme under grant agreement No.101037424.
文摘Enhancing the resilience of critical infrastructure(CI)systems has become a focal point of national and inter-national policies.However,the formulation of resilience enhancement strategies often requires component-(i.e.asset-)level prioritization,which entails many complexities.Acknowledging the complex and interdependent nature of infrastructure systems,this paper aims to aid researchers,practitioners and policy-makers by pre-senting a review of the relative literature and current state-of-the-art,and by identifying future research op-portunities to improve the applicability and operationalizability of CI component identification and prioritization methods.Theoretical and practical applications are reviewed for definitions,analysis and modelling approaches regarding the resilience of interdependent infrastructure systems.A detailed review of infrastructure criticality definitions,component criticality assessment and prioritization frameworks,from scientific,policy and other documents,is presented.A discussion on social justice and equity dimensions therein is included,which have the potential to greatly influence decisions and should always be incorporated in infrastructure planning and in-vestment discussions.The findings of this review are discussed in terms of applicability and operationalizability.Key recommendations for future research include:(i)developing quantification frameworks for CI component criticality based on formal definitions and multiple criteria,(ii)incorporating the entire resilience cycle of CI in component prioritization,(iii)accounting for the socio-technical nature of CI systems by integrating social di-mensions and their wider operating environment and(iv)developing comprehensive model validation,cali-bration and uncertainty analysis frameworks.
基金supported by the National Natural Science Foundation of China(32401409)the Central Government’s Special Fund for National Key Protected Wildlife Conservation Projects in Yinchuan City(HXCG-ZC2023148,XZ-2024-16)。
文摘Habitat loss driven by land-use change is a major factor shaping the dynamics of urban bird community structures.However,the potential mechanisms by which the spatial configuration and composition of blue-green infrastructure,recognized as biodiversity hotspots in urban landscapes,influence urban bird beta diversity remain insufficiently understood.This study was conducted in the built-up area of Yinchuan,an internationally recognized wetland city in Northwest China.From December 2023 to June 2024,we systematically surveyed bird communities during both the breeding and wintering periods across 29 blue-green space mosaics.We quantified taxonomic,functional,and phylogenetic beta diversity,along with their turnover component and nestedness-resultant component,based on both pairwise beta diversity and multiple-site beta diversity.We further assessed the relative importance of landscape variables and spatial geographic distance in shaping beta diversity patterns and used hierarchical modeling of species communities(HMSC)to explore the responses of bird occurrence and functional traits to landscape variables.Our results revealed that species turnover was the dominant driver of taxonomic,functional,and phylogenetic beta diversity.Seasonal differences were observed in the effects of spatial geographic distance and landscape structure on beta diversity and its components,with landscape variables showing higher explanatory power than geographic isolation.In the breeding period,landscape diversity and waterbody area had positive effects on bird occurrence,whereas in the wintering period,most landscape features—except for landscape diversity—exerted neutral or negative influences.Regarding functional traits,we found that reproductive traits,flight ability,and foraging characteristics responded significantly to landscape structure,and that some small-bodied species active in aerial and canopy layers were more adaptable to habitat fragmentation.This study provides novel insights into the assembly processes and driving mechanisms of urban bird communities and offers scientific support for the notion that designing and maintaining blue-green infrastructure can contribute to urban biodiversity conservation.
文摘The year 2026 marks the 70th anniversary of the establishment of diplomatic relations between China and African countries.It also marks the launch of the China-Africa Year of People-to-People Exchanges.At this pivotal juncture linking past achievements with future development,Wang Yi,member of the Political Bureau of the Communist Party of China Central Committee and foreign minister,continued the longstanding diplomatic tradition under which the Chinese foreign minister makes Africa the destination of the first overseas visit of the year,a practice upheld for 36 consecutive years,underscoring the stability,continuity and sincerity of China’s policy towards Africa.
基金The researchers would like to thank the Deanship of Graduate Studies and Scientific Research at Qassim University for financial support(QU-APC-2025)。
文摘The evolution of cities into digitally managed environments requires computational systems that can operate in real time while supporting predictive and adaptive infrastructure management.Earlier approaches have often advanced one dimension—such as Internet of Things(IoT)-based data acquisition,Artificial Intelligence(AI)-driven analytics,or digital twin visualization—without fully integrating these strands into a single operational loop.As a result,many existing solutions encounter bottlenecks in responsiveness,interoperability,and scalability,while also leaving concerns about data privacy unresolved.This research introduces a hybrid AI–IoT–Digital Twin framework that combines continuous sensing,distributed intelligence,and simulation-based decision support.The design incorporates multi-source sensor data,lightweight edge inference through Convolutional Neural Networks(CNN)and Long ShortTerm Memory(LSTM)models,and federated learning enhanced with secure aggregation and differential privacy to maintain confidentiality.A digital twin layer extends these capabilities by simulating city assets such as traffic flows and water networks,generating what-if scenarios,and issuing actionable control signals.Complementary modules,including model compression and synchronization protocols,are embedded to ensure reliability in bandwidth-constrained and heterogeneous urban environments.The framework is validated in two urban domains:traffic management,where it adapts signal cycles based on real-time congestion patterns,and pipeline monitoring,where it anticipates leaks through pressure and vibration data.Experimental results show a 28%reduction in response time,a 35%decrease in maintenance costs,and a marked reduction in false positives relative to conventional baselines.The architecture also demonstrates stability across 50+edge devices under federated training and resilience to uneven node participation.The proposed system provides a scalable and privacy-aware foundation for predictive urban infrastructure management.By closing the loop between sensing,learning,and control,it reduces operator dependence,enhances resource efficiency,and supports transparent governance models for emerging smart cities.
基金The authors would like to thank CNPq(Conselho Nacional de Desenvolvimento Científico e Tecnológico)—grants 407256/2022-9,303550/2025-2,402533/2023-2 and 303982/2022-5FAPEMIG(Fundação de AmparoàPesquisa do Estado de Minas Gerais)—grants APQ-00032-24 and APD-01113-25 for their financial support.
文摘Structural Health Monitoring(SHM)plays a critical role in ensuring the safety,integrity,longevity and economic efficiency of civil infrastructures.The field has undergone a profound transformation over the last few decades,evolving from traditional methods—often reliant on visual inspections—to data-driven intelligent systems.This review paper analyzes this historical trajectory,beginning with the approaches that relied on modal parameters as primary damage indicators.The advent of advanced sensor technologies and increased computational power brings a significant change,making Machine Learning(ML)a viable and powerful tool for damage assessment.More recently,Deep Learning(DL)has emerged as a paradigm shift,allowing for more automated processing of large data sets(such as the structural vibration signals and other types of sensors)with excellent performance and accuracy,often surpassing previous methods.This paper systematically reviews these technological milestones—from traditional vibration-based methods to the current state-of-the-art in deep learning.Finally,it critically examines emerging trends—such as Digital Twins and Transformer-based architectures—and discusses future research directions that will shape the next generation of SHM systems for civil engineering.
基金supported by the National Natural Science Foundation of China(No.U2333214).
文摘As the frontier of multidimensional transportation systems,urban air mobility(UAM)is receiving increasing attention from international organizations,governments,and stakeholders in industry and academia owing to its high efficiency,low carbon footprint,and operational flexibility.Vertical take-off and landing(VTOL)infrastructure is the core facility that enables UAM and is therefore essential for its safe,efficient,and large-scale commercial implementation.However,the key technologies for establishing low-altitude VTOL infrastructure are still nascent,and government,industry,and academia have yet to harmonize the corresponding construction,management,and operation standards.To address this gap,we herein systematically review the related progress and trends,comprehensively surveying the key technologies of establishing VTOL infrastructure serving unmanned aerial vehicles(UAVs)and electric VTOL aircraft from three complementary perspectives of ground-side,airspace-side,and communication,navigation,surveillance,and information services.In the light of future UAM operations characterized by diverse vehicle types and dense air traffic,we propose a conceptual design for a public multioperator VTOL site to provide constructive insights into the sustainable growth of the low-altitude economy.
文摘The national grid and other life-sustaining critical infrastructures face an unprecedented threat from prolonged blackouts,which could last over a year and pose a severe risk to national security.Whether caused by physical attacks,EMP(electromagnetic pulse)events,or cyberattacks,such disruptions could cripple essential services like water supply,healthcare,communication,and transportation.Research indicates that an attack on just nine key substations could result in a coast-to-coast blackout lasting up to 18 months,leading to economic collapse,civil unrest,and a breakdown of public order.This paper explores the key vulnerabilities of the grid,the potential impacts of prolonged blackouts,and the role of AI(artificial intelligence)and ML(machine learning)in mitigating these threats.AI-driven cybersecurity measures,predictive maintenance,automated threat response,and EMP resilience strategies are discussed as essential solutions to bolster grid security.Policy recommendations emphasize the need for hardened infrastructure,enhanced cybersecurity,redundant power systems,and AI-based grid management to ensure national resilience.Without proactive measures,the nation remains exposed to a catastrophic power grid failure that could have dire consequences for society and the economy.
文摘Over the past few years,major investments have been directed toward building new railway lines and upgrading existing ones.Many of these lines include critical infrastructure where operational and safety conditions must be carefully considered throughout their life cycle.Recent advancements in science and technology have enabled more effective structural monitoring of railway systems,largely driven by the adoption of intelligent strategies for inspection,maintenance,monitoring,and risk management.Research continues to expand and deepen the knowledge in this area;however,it remains a challenging field due to factors such as the complexity of railway systems,the high cost of implementation,and the need for reliable long-term data.
文摘The efficient transportation of goods is vital for the economic growth of communities,making developing and maintaining seaport infrastructure an essential component of the marine transportation system.Given their geographic locations,ports are consistently at risk from natural hazards,making the resilience of port infrastructure an essential goal.Despite considerable progress in resilience research,there remains a gap in methods tailored explicitly to assessing port resilience,particularly under extreme wind events.Current approaches often do not capture the full complexity of port systems,as they tend to focus on isolated aspects,such as structural resilience.This paper introduces the PORT Resilience Framework,addressing these gaps by evaluating resilience through a comprehensive list of indicators gathered from various legitimate sources.The indicators are then organized under four comprehensive resilience dimensions:Physical Infrastructure,ICT(i.e.,Information and Communication Technology)and Equipment;Organization and Business Management;Resources and Economic Development;and Territory,Environment,and Stakeholders.This classification is summarized under the acronym"PORT."This paper also introduces a method for aggregating resilience indicators by considering their performance before and after a specific hazard,transforming the data into a quantifiable Loss of Resilience index.The approach is applied to a case study,assessing the resilience of a real Terminal against wind action using real data sourced from the port management.The case study analysis revealed that human resources and quay operations were the most critical factors affecting recovery,with insufficient staffing leading to prolonged recovery periods.The study further demonstrated that post-disruption activity surges,captured by different serviceability function methodologies,often created operational bottlenecks,challenging the port's overall recovery.
文摘As offshore wind infrastructure becomes more important to global efforts to reduce carbon emissions,it is becoming more important to connect lifecycle cost management with circular economy(CE)principles.When looking at the long-term costs of infrastructure,traditional lifecycle cost models often fail to account for residual value recovery,material circularity,or environmental externalities.This study creates a unified analytical framework that adds CE strategies to lifecycle cost modelling for offshore wind systems,such as turbines,substructures,moorings,and floating platforms.The method uses multi-objective optimization and system dynamics simulation along with net present value(NPV)modelling,material flow analysis,and carbonadjusted cost accounting.We modelled project-level datasets over 25 years to look at the trade-offs between economic and environmental factors in both linear and circular lifecycle scenarios.We use Python,MATLAB,and OpenLCA to look at key metrics like the Material Circularity Indicator(MCI),estimates of residual value,and internalized carbon costs.The results show that circular infrastructure strategies greatly lower lifecycle costs while also increasing material recovery and carbon efficiency.Scenario simulations showed that CE-based configurations could cut costs by up to 18%and emissions over the life of the product by 22%.Regression and sensitivity analyses showed that MCI,CAPEX,and circular design strategies are good at predicting residual value and long-term economic performance.This study adds a new,evidence-based model for making decisions about infrastructure that takes into account financial,environmental,and material circularity.
基金supported by Ministry of Education of Singapore,under Academic Research Fund Tier 1(Grant Number RG143/23).
文摘Scientific and technological advancements are rapidly transforming underground engineering,shifting from labor-intensive,time-consuming methods to automated,real-time systems.This timely and comprehensive review covers in-situ testing,intelligent monitoring,and geophysical testing methods,highlighting fundamental principles,testing apparatuses,data processing techniques,and engineering applications.The state-of-the-art summary emphasizes not only cutting-edge innovations for complex and harsh environments but also the transformative role of artificial intelligence and machine learning in data interpretations.The integration of big data and advanced algorithms is particularly impactful,enabling the identification,prediction,and mitigation of potential risks in underground projects.Key aspects of the discussion include detection capabilities,method integration,and data convergence of intelligent technologies to drive enhanced safety,operational efficiency,and predictive reliability.The review also examines future trends in intelligent technologies,emphasizing unified platforms that combine multiple methods,real-time data,and predictive analytics.These advancements are shaping the evolution of underground construction and maintenance,aiming for risk-free,high-efficiency underground engineering.
文摘Marine infrastructure is increasingly vulnerable to harsh environmental conditions that accelerate the degradation of traditional materials such as Portland cement concrete and carbon steel.This review systematically investigates recent advancements in sustainable alternatives,including geopolymer concrete,engineered innovacementitious composites(ECC),bio-concrete,fiber-reinforced polymers(FRPs),and bamboo,stainless steel,and steel-CFRP hybrid bars.Each material is evaluated based on marine durability,mechanical performance,environmental impact,and cost feasibility using life cycle assessment,durability modelling,and a multi-criteria decisionsupport framework.The results reveal that geopolymer concrete and FRP reinforcement’s exhibit superior corrosion resistance and environmental benefits,while ECC and steel-CFRP composites offer structural resilience with moderate environmental trade-offs.However,challenges remain in long-term performance validation,standardization,and market integration.The review concludes that a combined approach involving innovative materials,computational tools,and sustainability assessment is essential for advancing marine infrastructure.Outlook recommendations include focused field studies,development of regulatory guidelines,and interdisciplinary collaboration to drive the practical adoption of eco-efficient materials in coastal and offshore construction.
基金National Natural Science Foundation of China(12471367)。
文摘In this work,we present a parallel implementation of radiation hydrodynamics coupled with particle transport,utilizing software infrastructure JASMIN(J Adaptive Structured Meshes applications INfrastructure)which encapsulates high-performance technology for the numerical simulation of complex applications.Two serial codes,radiation hydrodynamics RH2D and particle transport Sn2D,have been integrated into RHSn2D on JASMIN infrastructure,which can efficiently use thousands of processors to simulate the complex multi-physics phenomena.Moreover,the non-conforming processors strategy has ensured RHSn2D against the serious load imbalance between radiation hydrodynamics and particle transport for large scale parallel simulations.Numerical results show that RHSn2D achieves a parallel efficiency of 17.1%using 90720 cells on 8192 processors compared with 256 processors in the same problem.
文摘Structural health monitoring technology uses advanced sensors to collect structural state data in real time,evaluate its integrity and residual life,and make maintenance decisions accordingly.The key of structural health monitoring is to obtain structural data accurately.With the development of new sensor technology,sensors and data acquisition devices for structural health monitoring are constantly emerging,and the performance of these devices is developing rapidly.The latest developments of fiber optic sensors,piezoelectric material sensors and self-diagnostic sensors for structural health monitoring are summarized.The basic working principle of each sensor and its application in structural health monitoring are introduced,and the challenges and opportunities faced by sensors in structural health monitoring are prospected.
基金supported by the Shanghai Committee of Science and Technology Fund(22ZR1419300)the Academic Year 2025 Ritsumeikan Asia Pacific University Academic Research Subsidy(Grants-in-Aid Reapplication Type).
文摘Quantifying material use in infrastructure development and analyzing its relationship with economic growth is essential for enhancing resource efficiency and steering regional resource management toward sustainable development.This study systematically assessed infrastructure related material use in 30 provinces,autonomous regions,and municipalities in China during 1978-2022.The result indicated that material stock has experienced significant growth,increasing from 16.91×10^(9)t in 1978 to 103.60×10^(9)t in 2022,with an average annual growth rate of 4.20%.However,from 1978 to 2015,material input followed a strong upward trend but saturated after 2015.At the national level,material input peaked in 2015,after which it began to decline.The central region reached its peak earlier in 2013,while the eastern and western regions peaked in 2015.Using a decoupling analysis framework,this study revealed that nationally,the elasticity value between material stock and gross domestic product(GDP)remained near or above 1.0,reflecting continued reliance on stock accumulation.Regionally,the elasticity value between material stock and GDP has increased in the central and western regions during 1978-2022,whereas elasticity value between material stock and GDP in the eastern region showed a slower growth rate but still struggled to achieve absolute decoupling.Moreover,the elasticity value between material input and GDP has declined at the national level,presenting a relative decoupling,with some regions already achieving absolute decoupling.The eastern region was closer to absolute decoupling,while the central and western regions,though still intensive in material input,exhibited faster declines in elasticity.Accelerating the transition from linear to circular economy is an essential step for China to achieve absolute decoupling and long-term sustainability.Finally,this research recommends promoting the adoption of renewable energy,driving industrial upgrading,implementing compact urban design,and extending the lifespan of infrastructure to reduce material dependency and achieve sustainable infrastructure transformation at the national level.
文摘This research conducted a systematic study on the processes of migration of energy-related pollutants caused by nanoparticles in marine sediments,as well as their impacts on the durability of offshore infrastructure.While focused on representative nanoparticles(nano-TiO_(2),nano-Fe_(3)O_(4),and carbon nanotubes)and select energy pollutants,experimental data showed these materials greatly enhanced the movement of pollutants,increasing migration distances from 1.6 to 2.9 times.The carbon nanotubes possessed the greatest carrying effect,increasing the phenanthrene migration distance by 286 percent.The study determined surface properties of nanoparticles,pH of the liquid environment,ionic concentration,and organic matter level as major elements impacting pollutant mobility.Laboratory simulations,while controlled and reproducible,necessarily simplified the complex dynamics of real marine environments.Nanoparticle-sorbate systems were found to be effective in enhancing the deterioration rate of materials used in offshore constructions,with CNTPAHs composites causing carbon steel to corrode by 183% more than if PAHs were used without the composites.This change in corrosion behaviour was shown in other tests to be caused by a change in dynamics of the corrosion products'structural constituents and the various electrochemical properties present on the surface of the material.Samples of concrete showed a spend of 90 days in the composite system resulted in a 26.8% decrease in compressive strength compared to control conditions which had only a 15.3%.Therefore,taking into account the results,strategies were formulated to ensure durability for offshore infrastructure including surface modified anticorrosion coatings,surveillance and alert systems,and integrated protective systems.Future field validation studies are needed to verify these laboratory findings under actual marine conditions.This study helps to comprehend the behaviour of nanoparticles in intricate marine ecosystems,providing support for the sustainable advancement of offshore infrastructure and the protection of the marine environment.
基金financial support from the National Science Foundation(NSF)EPSCoR R.I.I.Track-2 Program,awarded under the NSF grant number 2119691.
文摘The increasing frequency and severity of natural disasters,exacerbated by global warming,necessitate novel solutions to strengthen the resilience of Critical Infrastructure Systems(CISs).Recent research reveals the sig-nificant potential of natural language processing(NLP)to analyze unstructured human language during disasters,thereby facilitating the uncovering of disruptions and providing situational awareness supporting various aspects of resilience regarding CISs.Despite this potential,few studies have systematically mapped the global research on NLP applications with respect to supporting various aspects of resilience of CISs.This paper contributes to the body of knowledge by presenting a review of current knowledge using the scientometric review technique.Using 231 bibliographic records from the Scopus and Web of Science core collections,we identify five key research areas where researchers have used NLP to support the resilience of CISs during natural disasters,including sentiment analysis,crisis informatics,data and knowledge visualization,disaster impacts,and content analysis.Furthermore,we map the utility of NLP in the identified research focus with respect to four aspects of resilience(i.e.,preparedness,absorption,recovery,and adaptability)and present various common techniques used and potential future research directions.This review highlights that NLP has the potential to become a supplementary data source to support the resilience of CISs.The results of this study serve as an introductory-level guide designed to help scholars and practitioners unlock the potential of NLP for strengthening the resilience of CISs against natural disasters.
文摘On 13 December 2024,liquefied natural gas(LNG)company Venture Global LNG(Arlington,VA,USA)commenced commercial production of the super-chilled fuel at its partially completed Plaquemines LNG export terminal in Louisiana(Fig.1)[1].In terms of dollars invested,the 21 billion USD plant is the fourth largest infrastructure project in the world[2].Venture Global initially expected the terminal to produce and ship 20 million tonnes of LNG annually[3].An 18 billion USD expansion of the terminal approved in February 2025 will bring its maximum annual produc-tion capacity to 45 million tonnes[4].When fully operational in 2027,the facility,located in Plaquemines Parish on the Mississippi River about 32 km south of New Orleans,will be among the largest in the world,further contributing to the US position as the world’s biggest LNG exporter[1].
文摘Since its inception,the Belt and Road Initiative(BRI)has emerged as a global platform for international cooperation,with infrastructure connectivity at its core.Infrastructure,often referred to as the“lifeblood”of economic and social development,plays a pivotal role in breaking bottlenecks,bridging regional gaps,and driving inclusive growth-particularly in developing regions where inadequate infrastructure has long hindered progress.
文摘The NIST Cybersecurity Framework (NIST CSF) serves as a voluntary guideline aimed at helping organizations, tiny and medium-sized enterprises (SMEs), and critical infrastructure operators, effectively manage cyber risks. Although comprehensive, the complexity of the NIST CSF can be overwhelming, especially for those lacking extensive cybersecurity resources. Current implementation tools often cater to larger companies, neglecting the specific needs of SMEs, which can be vulnerable to cyber threats. To address this gap, our research proposes a user-friendly, open-source web platform designed to simplify the implementation of the NIST CSF. This platform enables organizations to assess their risk exposure and continuously monitor their cybersecurity maturity through tailored recommendations based on their unique profiles. Our methodology includes a literature review of existing tools and standards, followed by a description of the platform’s design and architecture. Initial tests with SMEs in Burkina Faso reveal a concerning cybersecurity maturity level, indicating the urgent need for improved strategies based on our findings. By offering an intuitive interface and cross-platform accessibility, this solution aims to empower organizations to enhance their cybersecurity resilience in an evolving threat landscape. The article concludes with discussions on the practical implications and future enhancements of the tool.
