Resilient Time-Varying Formation-Tracking of Multi-UAV Systems Against Composite Attacks: A Two-Layered Framework

This paper studies the countermeasure design problems of distributed resilient time-varying formation-tracking control for multi-UAV systems with single-way communications against composite attacks,including denial-of-services(DoS)attacks,false-data injection attacks,camouflage attacks,and actuation attacks(AAs).Inspired by the concept of digital twin,a new two-layered protocol equipped with a safe and private twin layer(TL)is proposed,which decouples the above problems into the defense scheme against DoS attacks on the TL and the defense scheme against AAs on the cyber-physical layer.First,a topologyrepairing strategy against frequency-constrained DoS attacks is implemented via a Zeno-free event-triggered estimation scheme,which saves communication resources considerably.The upper bound of the reaction time needed to launch the repaired topology after the occurrence of DoS attacks is calculated.Second,a decentralized adaptive and chattering-relief controller against potentially unbounded AAs is designed.Moreover,this novel adaptive controller can achieve uniformly ultimately bounded convergence,whose error bound can be given explicitly.The practicability and validity of this new two-layered protocol are shown via a simulation example and a UAV swarm experiment equipped with both Ultra-WideBand and WiFi communication channels.

Compounding effects of human activities and climatic changes on coexistence of oasis-desert ecosystems:Prioritizing resilient decision-making for a riskier world

Water-salt balance is critical for the stable coexistence of salt-affected and groundwater-fed oasis-desert ecosystems. Yet, a comprehensive investigation of how soil salinization and groundwater degradation threaten the coexistence of oasis-desert ecosystems is still scarce, especially under the compounding effects of human activities and climatic changes. Here, we assessed the impacts of irrigated agriculture on hydrological regimes in oasisdesert systems, investigated the spatio-temporal variations of soil salinization in irrigated cropland, and evaluated the implications of the interplays of soil salinization and groundwater degradation on the coexistence of oasis-desert ecosystems in northwestern China, based on meaningful modelling approaches and comprehensive measurements over 1995–2020. The results showed that the irrigation return flow coefficient decreased sharply from 0.21 ± 0.09 in the traditional irrigation period to 0.09 ± 0.01 in the water-saving irrigation period. The continuous drop in groundwater tables and significant degradation of groundwater quality are occurring throughout this watershed. The eco-environmental flows are reaching to their limit with watershed closures(i.e.,the drainage from the oasis region into the desert region is being weakened or even eliminated), although these progressions were largely hidden by regional precipitation and streamflow variability. The process of salt migration and accumulation across different landscapes in oasis-desert system is being reshaped, and soil salinization in water-saving agricultural irrigated lands is accelerating with a regional average annual growth rate of18%. The vegetation in this watershed is degrading, and anthropogenic disturbance accelerates this trend. Our results highlight that environmental stress adaptation strategies must account for resilience maintenance to avoid accelerating catastrophic transitions in oasis-desert ecosystems. Determining the optimal oasis scales and formulating the best irrigation management plans are effective and resilient decision-making ways to maintain the coexistence relationship of oasis-desert ecosystem in drylands.

Resilient performance of self-centering hybrid rocking walls with curved interface under pseudo-static loading

Frame and rocking wall(FRW)structures have excellent resilient performance during earthquakes.However,the concrete at interfacial corners of rocking walls(RWs)is easily crushed due to local extreme compression during the rocking process.An innovative RW with a curved interface is proposed to prevent interfacial corners from producing local damage,enhancing its earthquake resilient performance(ERP).The precast wall panel with a curved interface is assembled into an integral self-centering hybrid rocking wall(SCRW)by two post-tensioned unbonded prestressed tendons.Moreover,two ordinary energy dissipation steel rebars and two shear reinforcements are arranged to increase the energy dissipation capacity and lateral resistance.Two SCRW specimens and one monolithic reinforced concrete(RC)shear wall(SW)were tested under pseudo-static loading to compare the ERPs of the proposed SCRW and the SW,focusing on studying the effect of the curved interface on the SCRW.The key resilient performance of rocking effects,failure modes,and hysteretic properties of the SCRW were explored.The results show that nonlinear deformations of the SCRW are concentrated along the interface between the SCRW and the foundation,avoiding damage within the SCRW.The restoring force provided by the prestressed tendons can effectively realize self-centering capacity with small residual deformation,and the resilient performance of the SCRW is better than that of monolithic SW.In addition,the curved interface of the SCRW makes the rocking center change and move inward,partially relieving the stress concentration and crush of concrete.The rocking range of the rocking center is about 41.4%of the width of the SCRW.

Regularity analysis of resilient modulus for hot-mix asphalt with large temperature fluctuations

To evaluate the regularity of resilient modulus for hot-mix asphalt(HMA)under large temperature fluctuations,back propagation(BP)neural network technology was used to analyze the continuous change of HMA resilient modulus.Firstly,based on the abundant data,the training model of HMA resilient modulus was established by using BP neural network technology.Subsequently,BP neural network prediction and regression analysis were performed,and the prediction model of HMA resilient modulus at different temperatures(50C to 60C)was obtained,which fully considered multi-factor and nonlinearity.Finally,the fitted theoretical model can be used to evaluate the HMA performance under the condition of large temperature fluctuations,and the rationality of theoretical model was verified by taking Harbin region as an example.It was found that the relationship between HMA resilient modulus and temperatures can be described by inverse tangent function.And the key parameters of theoretical model can be used to evaluate the continuous change characteristics of HMA resilient modulus with large temperature fluctuations.The results can further improve the HMA performance evaluation system and have certain theoretical value.

Grassland-type ecosystem stability in China differs under the influence of drought and wet events

Ecological stability is a core issue in ecological research and holds significant implications forhumanity. The increased frequency and intensity of drought and wet climate events resulting from climatechange pose a major threat to global ecological stability. Variations in stability among different ecosystemshave been confirmed, but it remains unclear whether there are differences in stability within the sameterrestrial vegetation ecosystem under the influence of climate events in different directions and intensities.China's grassland ecosystem includes most grassland types and is a good choice for studying this issue.This study used the Standardized Precipitation Evapotranspiration Index-12 (SPEI-12) to identify thedirections and intensities of different types of climate events, and based on Normalized DifferenceVegetation Index (NDVI), calculated the resistance and resilience of different grassland types for 30consecutive years from 1990 to 2019 (resistance and resilience are important indicators to measurestability). Based on a traditional regression model, standardized methods were integrated to analyze theimpacts of the intensity and duration of drought and wet events on vegetation stability. The resultsshowed that meadow steppe exhibited the highest stability, while alpine steppe and desert steppe had thelowest overall stability. The stability of typical steppe, alpine meadow, temperate meadow was at anintermediate level. Regarding the impact of the duration and intensity of climate events on vegetationecosystem stability for the same grassland type, the resilience of desert steppe during drought was mainlyaffected by the duration. In contrast, the impact of intensity was not significant. However, alpine steppewas mainly affected by intensity in wet environments, and duration had no significant impact. Ourconclusions can provide decision support for the future grassland ecosystem governance.

Optimal decision-making method for equipment maintenance to enhance the resilience of power digital twin system under extreme disaster

Digital twins and the physical assets of electric power systems face the potential risk of data loss and monitoring failures owing to catastrophic events,causing surveillance and energy loss.This study aims to refine maintenance strategies for the monitoring of an electric power digital twin system post disasters.Initially,the research delineates the physical electric power system along with its digital counterpart and post-disaster restoration processes.Subsequently,it delves into communication and data processing mechanisms,specifically focusing on central data processing(CDP),communication routers(CRs),and phasor measurement units(PMUs),to re-establish an equipment recovery model based on these data transmission methodologies.Furthermore,it introduces a mathematical optimization model designed to enhance the digital twin system’s post-disaster monitoring efficacy by employing the branch-and-bound method for its resolution.The efficacy of the proposed model was corroborated by analyzing an IEEE-14 system.The findings suggest that the proposed branch-and-bound algorithm significantly augments the observational capabilities of a power system with limited resources,thereby bolstering its stability and emergency response mechanisms.

Exploring social-ecological system resilience in South China Karst:Quantification,interaction and policy implication

China’s Grain to Green Program(GTGP),which is one of the largest payments for ecosystem services(PES)in the world,has made significant ecological improvements to the environment.However,current understanding of its outcomes on the social-ecological system(SES)remains limited.Therefore,taking the South China Karst as an example,a SES resilience evaluation index system was constructed followed by an exploratory spatial analysis,root mean square error,and Self-Organizing Feature Map to clarify the spatiotemporal changes and relationship of SES resilience,achieve the zoning of SES resilience and provide restoration measures.The results showed an upward trend in social resilience from 2000 to 2020,especially its subsystem of social development.Regional ecological resilience was stable,owing to a slightly declined ecosystem services and increased landscape pattern.Spatially,nearly half of the counties exhibited a distribution mismatch in SES resilience.There was an obvious inverted U-shaped relationship of SES resilience,indicating a clear threshold effect,and the constraint relation-ship of SES resilience eased over time,demonstrating the effectiveness of the ecological restoration program.GTGP played a positive role in reducing regional SES trade-off,but this positive effect was limited,reflecting the limitations of overemphasizing the conversion from farmland to forest and grassland.Regional SES resilience can be divided into four clusters,which were the key optimization zone for social system,the SES resilience safety zone,the key restoration zone for SES resilience,and the key optimization zone for ecological system.Adaptive adjustments for the GTGP in these zones should be taken to achieve maximum SES benefits in the future.

Resilience-driven cooperative reconfiguration strategy for unmanned weapon system-of-systems

As the unmanned weap system-of systems(UWSoS)becomes complex,the inevitable uncertain interference gradu-ally increases,which leads to a strong emphasis on the resilience of UWSoS.Hence,this paper presents a resilience-driven cooperative reconfiguration strategy to enhance the resilience of UWSoS.First,a unified resilience-driven coopera-tive reconfiguration strategy framework is designed to guide the UWSoS resilience enhancement.Subsequently,a cooperative reconfiguration strategy algorithm is proposed to identify the optimal cooperative reconfiguration sequence,combining the cooperative pair resilience contribution index(CPRCI)and coop-erative pair importance index(CPII).At last,the effectiveness and superiority of the proposed algorithm are demonstrated through various attack scenario simulations that include differ-ent attack modes and intensities.The analysis results can pro-vide a reference for decision-makers to manage UWSoS.

Resilience Augmentation in Unmanned Weapon Systems via Multi-Layer Attention Graph Convolutional Neural Networks

The collective Unmanned Weapon System-of-Systems(UWSOS)network represents a fundamental element in modern warfare,characterized by a diverse array of unmanned combat platforms interconnected through hetero-geneous network architectures.Despite its strategic importance,the UWSOS network is highly susceptible to hostile infiltrations,which significantly impede its battlefield recovery capabilities.Existing methods to enhance network resilience predominantly focus on basic graph relationships,neglecting the crucial higher-order dependencies among nodes necessary for capturing multi-hop meta-paths within the UWSOS.To address these limitations,we propose the Enhanced-Resilience Multi-Layer Attention Graph Convolutional Network(E-MAGCN),designed to augment the adaptability of UWSOS.Our approach employs BERT for extracting semantic insights from nodes and edges,thereby refining feature representations by leveraging various node and edge categories.Additionally,E-MAGCN integrates a regularization-based multi-layer attention mechanism and a semantic node fusion algo-rithm within the Graph Convolutional Network(GCN)framework.Through extensive simulation experiments,our model demonstrates an enhancement in resilience performance ranging from 1.2% to 7% over existing algorithms.

A Novel Defender-Attacker-Defender Model for Resilient Distributed Generator Planning with Network Reconfiguration and Demand Response

To improve the resilience of a distribution system against extreme weather,a fuel-based distributed generator(DG)allocation model is proposed in this study.In this model,the DGs are placed at the planning stage.When an extreme event occurs,the controllable generators form temporary microgrids(MGs)to restore the load maximally.Simultaneously,a demand response program(DRP)mitigates the imbalance between the power supply and demand during extreme events.To cope with the fault uncertainty,a robust optimization(RO)method is applied to reduce the long-term investment and short-term operation costs.The optimization is formulated as a tri-level defenderattacker-defender(DAD)framework.At the first level,decision-makers work out the DG allocation scheme;at the second level,the attacker finds the optimal attack strategy with maximum damage;and at the third level,restoration measures,namely distribution network reconfiguration(DNR)and demand response are performed.The problem is solved by the nested column and constraint generation(NC&CG)method and the model is validated using an IEEE 33-node system.Case studies validate the effectiveness and superiority of the proposed model according to the enhanced resilience and reduced cost.

Spatio-temporal Evaluation of Multi-scale Cultivated Land System Resilience in Black Soil Region from 2000 to 2019:A Case Study of Liaoning Province,Northeast China

It is of great significance to systematically analyze the cultivated land system resilience(CLSR) for the black soil protection and national food security.The CLSR is impacted by planting structure adjustment and cultivated land quality decline,posing major hidden dangers to food security.It is urgent to evaluate the CLSR at multiple spatio-temporal scales.This study took Liaoning Province in the black soil region of Northeast China as an example.Based on the resilience theory,this study constructed the CLSR evaluation system from the input-feedback perspective at the provincial-scale and the city-scale,and used the rank-sum ratio comprehensive evaluation method(RSR) to analyze the key influencing factors of CLSR in Liaoning Province and its 14 cities from 2000 to 2019.The results showed that:1) the time series changes of CLSR at the provincial-scale and the city-scale in Liaoning Province were similar,both showing an increasing trend.2) The CLSR in Liaoning Province presented a spatial pattern of ‘high in the west and low in the east’ at the city-scale.3) There were seven and six main influencing factors of CLSR at the provincial-scale and the city-scale,respectively.In addition to the net income per capita of rural households,other influencing factors of CLSR were different at the provincial-scale and the city-scale.The feedback factors were dominant at the provincial-scale,and the input factors and feedback factors were dominant at the city-scale.The results could provide a reference for the utilization of black soil and draw on the experience of regional agricultural planning and adjustment.

Threshold-Based Software-Defined Networking(SDN)Solution for Healthcare Systems against Intrusion Attacks

The healthcare sector holds valuable and sensitive data.The amount of this data and the need to handle,exchange,and protect it,has been increasing at a fast pace.Due to their nature,software-defined networks(SDNs)are widely used in healthcare systems,as they ensure effective resource utilization,safety,great network management,and monitoring.In this sector,due to the value of thedata,SDNs faceamajor challengeposed byawide range of attacks,such as distributed denial of service(DDoS)and probe attacks.These attacks reduce network performance,causing the degradation of different key performance indicators(KPIs)or,in the worst cases,a network failure which can threaten human lives.This can be significant,especially with the current expansion of portable healthcare that supports mobile and wireless devices for what is called mobile health,or m-health.In this study,we examine the effectiveness of using SDNs for defense against DDoS,as well as their effects on different network KPIs under various scenarios.We propose a threshold-based DDoS classifier(TBDC)technique to classify DDoS attacks in healthcare SDNs,aiming to block traffic considered a hazard in the form of a DDoS attack.We then evaluate the accuracy and performance of the proposed TBDC approach.Our technique shows outstanding performance,increasing the mean throughput by 190.3%,reducing the mean delay by 95%,and reducing packet loss by 99.7%relative to normal,with DDoS attack traffic.

Resilience-Oriented Load Restoration Method and Repair Strategies for Regional Integrated Electricity-Natural Gas System

The rising frequency of extreme disaster events seriously threatens the safe and secure operation of the regional integrated electricity-natural gas system(RIENGS).With the growing level of coupling between electric and natural gas systems,it is critical to enhance the load restoration capability of both systems.This paper proposes a coordinated optimization strategy for resilience-enhanced RIENGS load restoration and repair scheduling and transforms it into a mixed integer second-order cone programming(MISOCP)model.The proposed model considers the distribution network reconfiguration and the coordinated repair strategy between the two systems,minimizing the total system load loss cost and repair time.In addition,a bi-directional gas flow model is used to describe the natural gas system,which can provide the RIENGS with more flexibility for load restoration during natural gas system failure.Finally,the effectiveness of the proposed approach is verified by conducting case studies on the test systems RIENGS E13-G7 and RIENGS E123-G20.

Renewal Needs and Solutions for Urban Old Communities under the Guidance of Resilient Security

The renewal strategy guided by resilient security aims to enhance the community’s resistance and resilience to natural disasters and other emergency situations,ensuring that the community can quickly restore normal functions in the face of shocks.By enhancing the resilience of the community,residents’sense of security and satisfaction can be improved,while promoting the long-term stability and prosperity of the city.Using methods such as literature review,case analysis,and demand investigation,this paper investigates the needs and strategies for the renewal of urban old communities,and explores the demand analysis and solutions for the renewal of urban old communities under the guidance of resilient security.This paper aims to address the lack of resilience in old communities caused by outdated construction,aging infrastructure,and insufficient public services,as well as how to improve the adaptability,resilience,and transformation ability of communities through renovation and transformation.

Modelling of the variation of granular base materials resilient modulus with material characteristics and humidity conditions

This study aims to quantify the susceptibility of granular materials used in pavements to changes in moisture content and propose a correlation model to incorporate this susceptibility into seasonal analyses.The fines content and the percentage of fractured coarse aggregates were identified as direct indicators of the resilient modulus susceptibility to changes in water content.The results showed that the percentage of fractured coarse aggregates particles(FR)has a more significant impact on the resilient modulus(Er)of crushed granular materials used in pavement construction than the combined indicator of the fines content and sample volumetrics(nf).Crushed granular materials with a higher percentage of fractured coarse aggregates are relatively insensitive to changes in the degree of saturation,but become more sensitive as the fine fraction porosity decreases.An adjusted model was proposed based on the existing formulation,but considers a complex parameter to describe and adjust the sensitivity of base granular materials to variations in moisture content with respect to fabrication charac-teristics,fines content and volumetric properties.The model shows that the variation of Er values is below10%for fully crushed granular materials.However,it reaches approximately±12%for materials with 75%of crushed coarse aggregates andþ40%and-25%for materials with FR=50%.This model could help select good ag-gregates characteristics and adjust grain-size distribution for environments where significant moisture content variations can occur in the pavement system,such as in the Province of Quebec(Canada).As it is based on pa-rameters that can be easily determined or estimated,it also represents a valuable tool for detailed design and analysis that can consider material characteristics.

Principles for Designing New Types of Housing for a Strong and Resilient Local Economy in the Republic of Congo

The Congolese population is organised into households, which are thus headed by a chief who ensures the social well-being, development and integration into working life of the individuals in his charge. This study examines the functional principles of new housing design as an instrument for transforming the (current) failing economy into a strong and resilient one. Accordingly, a literature review of the practice of designing and building housing in human settlements in the Congo revealed the state of the art on this subject. An analysis of the existing housing stock from a demographic, social and economic point of view made it possible to identify the most common household sizes and numbers, as well as the lifestyle processes that determine the need for developed space. To this end, the experimental method was used to propose configuration plans for various new types of dwelling. To this end, the study highlighted the link between people’s standard of living and the effectiveness of their involvement in the local economy. To achieve the aims of the National Development Plan (NDP), particular attention must be paid to solving the housing problem. The existing housing stock actively contributes to the problems associated with unemployment and insecurity. Functional principles for the design of new types of housing have been developed. Four model types are proposed in line with the demographic structure of the population, their socio-economic characteristics and their lifestyle.

Artificial Intelligence Based on Resilient Leadership in the Health Sector-A Secondary Publication

At present,it is impossible to deny the existence of artificial intelligence in various areas of social life,understood as the simulation of expert human intelligence from computer processes that involve learning,reasoning,and self-correction,its benefits to the medical field,in particular,are innumerable,but their incorporation into health systems has been gradual for many reasons.According to the above,this research analyzed artificial intelligence based on resilient leadership in the health sector,for which qualitative research was carried out with a documentary-bibliographic design with printed and electronic documentary sources with theoretical contributions fromÁvila,Mayer,and Quesada[1],Morgan[2],Villa[3],and Finol[4],among others.It is highlighted that resilient leadership has become a strategic factor in all organizations,since times of uncertainty and changes lead institutions to properly manage the incorporation of technologies specifically AI,achieving in this way that the centers and professionals in the field of health assume the needs of the contexts and the innovations of the same.It is concluded that resilient leadership will allow artificial intelligence in the health sector to generate higher levels of learning and adaptability to the transformations that are necessary,whose resistance would make its application difficult and in the long run it will leave behind professionals who refuse to assume the contributions of these innovative techniques in medical practice.

A Resilient Control Strategy for Cyber-Physical Systems Subject to Denial of Service Attacks:A Leader-Follower Set-Theoretic Approach

Multi-agent systems are usually equipped with open communication infrastructures to improve interactions efficiency,reliability and sustainability.Although technologically costeffective,this makes them vulnerable to cyber-attacks with potentially catastrophic consequences.To this end,we present a novel control architecture capable to deal with the distributed constrained regulation problem in the presence of time-delay attacks on the agents’communication infrastructure.The basic idea consists of orchestrating the interconnected cyber-physical system as a leader-follower configuration so that adequate control actions are computed to isolate the attacked unit before it compromises the system operations.Simulations on a multi-area power system confirm that the proposed control scheme can reconfigure the leader-follower structure in response to denial ofservice(DoS)attacks.

Coronavirus disease 2019 (COVID-19) pandemic: how countries shouldbuild more resilient health systems for preparedness and response

Objective: A resilient health system plays a crucial role in pandemic preparedness and response. Althoughthe World Health Organization (WHO) has required all states parties to strengthen core capacities to respondto public health emergencies under the International Health Regulations (2005), the actions of most countriesto combating coronavirus disease 2019 (COVID-19) has showed that they are not well-prepared. This crosssectionalstudy aimed to examine the health system resilience of selected countries and analyze their strategiesand measures in response to the COVID-19 pandemic.Methods: This study selected five countries including the Iran, Japan, Republic of Korea (South Korea), the U.K.,and the U.S., based on the severity of the national epidemic, the geographical location, and the developmentlevel. Cumulative number of death cases derived from WHO COVID-19 dashboard was used to measure theseverity of the impact of the pandemic in each country;WHO State Parties Self-Assessment Annual Reporting (SPAR)Scores and Global Health Security (GHS) Index were applied to measure the national health system resilience;and research articles and press materials were summarized to identify the strategies and measures adopted bycountries during response to COVID-19. This study applied the resilient health systems framework to analyzehealth system resilience in the selected countries from five dimensions, including awareness, diversity, selfregulation,integration and adaptation.Results: The SPAR Scores and GHS Index of the four developed countries, Japan, South Korea, the U.K. and theU.S. were above the global and regional averages;the SPAR Scores of Iran were above the global average whilethe GHI Index lain below the global average. In terms of response strategies, Japan, the U.K. and the U.S. investedmore health resources in the treatment of severe patients, while South Korea and Iran had adopted a strategyof extensive testing and identification of suspected patients. In terms of specific measures, all the five countriesadopted measures such as restrictions on entry and international travel, closure of schools and industries,lockdown and quarantine. Nevertheless, the effectiveness of implementing these measures varied acrosscountries, based on the response strategies.Conclusion: Although SPAR Scores and GHS Index have evaluated the national core capacities for preparednessand response, the actions to cope with the COVID-19 pandemic has revealed the fact that most countries stilldo not build resilient health systems in response to public health emergencies. Health system strengtheningand health security efforts should be pursued in tandem, as part of the same mutually reinforcing approach todeveloping resilient health systems.

Resilient and Safe Platooning Control of Connected Automated Vehicles Against Intermittent Denial-of-Service Attacks

Connected automated vehicles(CAVs)serve as a promising enabler for future intelligent transportation systems because of their capabilities in improving traffic efficiency and driving safety,and reducing fuel consumption and vehicle emissions.A fundamental issue in CAVs is platooning control that empowers a convoy of CAVs to be cooperatively maneuvered with desired longitudinal spacings and identical velocities on roads.This paper addresses the issue of resilient and safe platooning control of CAVs subject to intermittent denial-of-service(DoS)attacks that disrupt vehicle-to-vehicle communications.First,a heterogeneous and uncertain vehicle longitudinal dynamic model is presented to accommodate a variety of uncertainties,including diverse vehicle masses and engine inertial delays,unknown and nonlinear resistance forces,and a dynamic platoon leader.Then,a resilient and safe distributed longitudinal platooning control law is constructed with an aim to preserve simultaneous individual vehicle stability,attack resilience,platoon safety and scalability.Furthermore,a numerically efficient offline design algorithm for determining the desired platoon control law is developed,under which the platoon resilience against DoS attacks can be maximized but the anticipated stability,safety and scalability requirements remain preserved.Finally,extensive numerical experiments are provided to substantiate the efficacy of the proposed platooning method.