Comprehensive Resilience Research Articles

Resilience assessment and recovery of airport departure flights under severe weather

In order to ensure the overall performance of the airport under severe weather, scientifically evaluate the resilience of the airport's flight operations, improve flight recovery capabilities, and alleviate the impact of severe weather effectively. This article first gives the definition of airport departure flight operation. Starting from the performance of the airport departure flight operation system, it analyzes flight departure delay time, total departure delay time, departure flight normality rate and departure airport flight operation system comprehensive resilience index four indicators to evaluate the resilience changes of the system under severe weather conditions; put forward the concept of the performance recovery strategy of the airport departure flight operation system, and established the corresponding resilience model, and used the genetic algorithm to optimize the sequence of the delayed departure flights; finally, take the "721" heavy rain event in Beijing Capital International Airport in 2012 as an example to analyze the data, obtain the performance index and resilience index of the Capital Airport under the influence of heavy rain, and use the optimized departure flight schedule to compare and analyze the changes in airport departure flight operating system performance and resilience level. The results indicate that: under the influence of heavy rain, the comprehensive resilience index of the airport departure flight operation system decreased from 0.4573 to 0.0628 , and increased to 0.2223 after the rainstorm decreased; after the flight optimization and sequencing was carried out in the recovery stage of the airport departure flight operation performance, the total number of departure flights decreased. The delay time is reduced by 24.85%, the airport performance recovery speed is increased by 13.89%after optimization, and the minimum resilience index of the optimized airport departure flight operation system is increased by 13.38%, and under the same heavy rain, the system performance is given priority to restore to the initial state, indicating that the evaluation Indicators are valid.

Association of Resilience-Related Life Experiences on Variability on Age of Onset in Dominantly Inherited Alzheimer Disease.

It remains unknown whether the associations between protective lifestyles and sporadic dementia risk reported in observational studies also affect age at symptom onset (AAO) in autosomal dominant Alzheimer disease (ADAD) with predominant genetic influences. We investigated the associations between resilience-related life experiences and interindividual AAO variability in ADAD. We performed a longitudinal and confirmatory analysis of the Dominantly Inherited Alzheimer Network prospective observational cohort (January 2009-June 2018, follow-up duration 2.13 ± 2.22 years), involving clinical, CSF, and lifestyle/behavioral assessments. We performed a 2-pronged comprehensive resilience assessment in each cohort. Cohort 1, incorporating the general resilience definition (cognitive maintenance [Clinical Dementia Rating = 0] despite high pathology), included carriers during the periods of significant CSFp-tau181 variability and grouped into resilience/resistance outcome bins according to the dichotomous pathologic and cognitive statuses, subcategorized by the estimated years from expected symptom onset (EYO). Cohort 2, focused on ADAD-specific genetically determined time frame characterizing the onset predictability, included asymptomatic participants with available preclinical lifestyle data and AAO outcomes and grouped into delayed or earlier AAO relative to the parental AAO. Associations of cognitive, CSFp-tau181, and lifestyle/behavioral predictors with binary outcomes were investigated using logistic regression. Of 320 carriers (age 38.19 ± 10.94 years, female 56.25%), cohort 1 included 218 participants (39.00 ± 9.37 years, 57.34%) and cohort 2 included 28 participants (43.34 ± 7.40 years, 71.43%). In cohort 1, 218 carriers after -20 EYO, when the interindividual variability (SD) of CSFp-tau181 first became more than twice greater in carriers than in noncarriers, were grouped into low-risk control (asymptomatic, low pathology, n = 103), high-resilience (asymptomatic despite high pathology, n = 60), low-resilience (symptomatic despite low pathology, n = 15), and susceptible control (symptomatic, high pathology, n = 40) groups. Multivariable predictors of high resilience, controlling for age and depression, included higher conscientiousness (odds ratio 1.051 [95% CI 1.016-1.086], p = 0.004), openness to experience (1.068 [1.005-1.135], p = 0.03) (vs. susceptible controls), and agreeableness (1.082 [1.015-1.153], p = 0.02) (vs. low resilience). From 1 to 3 years before parental AAO (cohort 2), the multivariable predictor of delayed AAO, controlling for CSFp-tau181, was higher conscientiousness (0.916 [0.845-0.994], p = 0.036). Among the cognitively and socially integrated life experiences associated with resilience, measures of conscientiousness were useful indicators for evaluating resilience and predicting future dementia onset in late preclinical ADAD.

Оценка жизнестойкости сельских сообществ Ненецкого автономного округа

The concept of resilience is applied to complex social systems to describe the ability of a territory (or settlement) or local community to recover from external shocks. In this context, resilience complements the concept of sustainable development by revealing the mechanisms that enable systems to regenerate during crises. In recent decades, various approaches for assessing urban resilience, including that of Arctic cities in high-risk zones, have been developed in scientific literature. However, a comprehensive methodology for assessing the resilience of Arctic rural communities has not yet been fully developed or tested. The goal of this article is to assess the resilience of several rural communities in the Nenets Autonomous Okrug (NAO), followed by their comparison and classification. Drawing on Russian researchers' experience in measuring the resilience of Arctic cities, the authors propose their own methodology for assessing the resilience of Arctic rural communities. This methodology involves measuring 11 resilience indicators, which are aggregated into a comprehensive resilience index (R-index). The R-index enables the ranking of Arctic rural communities by their resilience levels. In the course of the study, all surveyed rural communities were classified into four groups based on R-index values: 1) isolated communities with low resilience; 2) vulnerable communities prone to external shocks; 3) administrative centers of rural municipalities with moderate resilience; 4) large and stable rural communities. The primary differentiating factors among these communities include geographical location, transport links and logistics, the structure of local economies, and demographic resources. Overall, Arctic rural communities exhibit a high level of social capital. The novelty of this study lies in its application of the community resilience concept to Arctic rural areas, contributing to a deeper understanding of the factors that shape their development potential. Future research should expand the geographical scope of the study and conduct larger surveys to improve the accuracy and reliability of rural community resilience assessments.

On the non-resiliency of subsequence reduced resilient consensus in multiagent networks

This paper studies resilient distributed consensus in networks lacking the structural robustness necessary for achieving consensus in the presence of misbehaving agents. Existing resilient consensus solutions, including widely adapted weighted mean subsequence reduced (WMSR) resilient consensus algorithm, present robustness conditions guaranteeing consensus among normal agents. However, when the graph is less robust than required, they only inform that agents fail to achieve consensus and do not evaluate the network performance comprehensively in such non-ideal scenarios. To address this limitation, we analyze the performance of resilient consensus in non-ideal situations by introducing the concept of non-convergent nodes. These nodes/agents cannot achieve consensus with any arbitrary agent due to the presence of misbehaving agents in the network. This notion enables ordering graphs that lack required robustness and facilitates the assessment of partial performance. Additionally, we demonstrate that among graphs with the same level of robustness (measured by their (r,s)-robustness), the number of non-convergent nodes varies significantly, indicating differing degrees of non-resilience. We also present numerical evaluation of results. Our approach quantifies the network performance under sub-optimal robustness conditions and offers a comprehensive resilience perspective.

Comprehensive Resilience Assessment Framework for Water Distribution Networks

A novel comprehensive resilience assessment framework for drinking water systems is proposed integrating different resilience perspectives (i.e., robustness, autonomy, flexibility, reliability, preparedness and recovery), oriented by objectives, criteria and metrics, applicable at the tactical level. The resilience assessment framework is applied to a Portuguese real water distribution network, enabling the evaluation of the system’s resilience. The infrastructure dimension is the main contributor to the low resilience results, particularly in terms of infrastructural robustness, as the infrastructure has exceeded the average service life and has low rehabilitation rates. In terms of autonomy, the system highly depends on external water and energy sources. Regarding the service dimension, most of the drinking water available is used for non-potable uses (e.g., irrigation), without alternative sources. The detailed diagnosis identified network area R6 as the priority area. Assets rehabilitation, increasing storage capacity, finding alternative water and energy sources, and minimizing non-potable uses are relevant improvement measures that promote the reinforcement of the system’s resilience. The resilience assessment framework is a very useful tool for the daily and tactical management of drinking water systems.

Comprehensive resilience assessment of bridge networks using ensemble learning method

The assessment of seismic resilience in bridge networks holds significant importance for urban disaster prevention and mitigation efforts. Unlike individual bridges, there has been limited efficiency in assessing bridge networks. A seismic resilience assessment methodology for bridge networks using ensemble learning methods is proposed in this paper. Initially, a comprehensive resilience index is proposed, integrating both structural and functional aspects of bridge networks. Using 3 ensemble learning methods, 9 parameters related to network structure and traffic characteristics are chosen as input variables for predicting the seismic resilience index. Finite element models of 18 bridges are constructed and combined to generate 3500 sets of virtual bridge networks for model training. The predictive accuracy of models trained using the 3 ensemble methods exceeds 89 %, and the expected values of peak ground acceleration (PGA) and functional loss rate are the most influential features. The methodology offers insights into the application of ensemble learning for bridge network seismic resilience assessment.

Research on the Socio-Spatial Resilience Evaluation and Evolution of the Central Area of Beijing in Transitional China

In recent decades, the increasing threats of global climate change, natural disasters, and epidemics have brought extensive attention to resilience theory. However, most studies focus on the physical aspects of cities, overlooking the significance of the social perspective. This study addresses this gap by using social areas as the core spatial unit for analysis. By constructing a scientific indicator system and employing the set pair analysis method, this study comprehensively evaluates the multidimensional resilience levels of Beijing’s central area during its transitional period (1990–2020). The findings reveal that socio-spatial divisions, which emphasize the network structure of social relations and the dynamic changes in social spaces, are more suitable than traditional administrative divisions as fundamental units for resilience assessment. During Beijing’s transitional period, the comprehensive resilience of the central area and all social areas steadily increased, although social capital resilience faced the challenges of loss and slow recovery. Social areas with a unique internal connection, such as those based on ethnicity, exhibited more positive social capital resilience development. Additionally, social areas with lower population diversity and greater homogeneity tended to have higher comprehensive resilience and a more positive trend in social capital resilience development, whereas highly heterogeneous social areas faced significant constraints in resilience development. These findings may provide valuable insights for cities and communities to enhance their capacity to address future uncertainties and assist policymakers in making informed governance decisions.

Study on Rural Classification and Resilience Evaluation Based on PSR Model: A Case Study of Lvshunkou District, Dalian City, China

When implementing a rural revitalization strategy, it is of great significance to understand how to identify potential risks in different types of villages and how to achieve resilience governance. In this paper, a rural classification evaluation method is proposed from the perspective of resilience. The stress–state–response model and the TOPSIS method were used to analyze the resilience risks in different types of villages in Lvshunkou District. The results showed that the comprehensive resilience of rural areas in Lvshunkou District has the spatial distribution characteristics of “high center and low wings”, and the spatial differences of each resilience subsystem are different: the pressure resilience subsystem shows a trend of “increasing step by step” from the coast to the inland, the state resilience subsystem shows a trend of “decreasing step by step from the center to the two wings”, and the response resilience subsystem shows a trend of “blocky aggregation and balanced distribution”. This paper further proposes systematic reconstruction strategies for rural resilience related to the four aspects of rural space, industry, ecology, and governance, providing development ideas for measuring rural resilience indicators in Lvshunkou District and realizing long-term governance in different types of villages.

Criticality assessment and cascading effects: impacts of COVID-19 disruptions in public transport on marginalized groups in Dortmund, Germany, São Paulo, Brazil, and Cape Town, South Africa

The COVID-19 pandemic has underscored the interconnectedness of critical infrastructure systems and their profound impact on marginalized communities. This study investigates the cascading effects of reduced mobility and infrastructure disruptions caused by COVID-19 response strategies on marginalized households across three diverse urban settings: Dortmund, São Paulo, and Cape Town. Employing a criticality assessment, we examine disruptions in healthcare, food and nutrition, social work, education, and childcare sectors, highlighting interdependencies and their implications for marginalized communities. Our findings reveal that disruptions in one sector, such as public transportation, can trigger adverse consequences across interconnected systems, amplifying vulnerabilities and exacerbating social inequalities. Furthermore, limited digital accessibility compounds these challenges, particularly for marginalized groups who may lack access to necessary technologies or digital literacy skills. Addressing these disparities in digital access is crucial for ensuring equitable access to essential services and support networks, especially in times of crisis. The study underscores the importance of mobility and accessibility in addressing systemic vulnerabilities and advocates for comprehensive resilience strategies that prioritize the needs of marginalized communities. Recommendations for policymakers, urban planners, and community stakeholders are provided to enhance infrastructure resilience and mitigate the indirect effects of disruptions on marginalized groups. The study contributes to a deeper understanding of cascading effects within critical infrastructure networks and informs future research and policy initiatives aimed at building resilient communities in an interconnected world.

Predictive resilience assessment of road networks based on dynamic multi-granularity graph neural network

Due to the influence of global climate anomalies, abnormal weather conditions such as heavy rainfall have become more frequent in recent years, posing a significant threat to the operation of transportation systems. An effective assessment of the resilience of the transportation system before and during heavy rain can alert the transportation department to take necessary emergency actions. However, existing methods for assessing the rainfall resilience of transportation networks mostly suffer from the following problems: (1) Simulation methods for modeling rainfall impacts lack realism; (2) After-the-fact evaluations of resilience cannot offer advance warning prior to or during a heavy rain event. To address above problems, we present a novel resilience assessment methodology for evaluating the resilience of road networks in real-time during heavy rainfall scenarios. In this methodology, we propose the temporal decomposition-based dynamic multi-granularity graph neural network (TD2MG2NN) for long-term traffic speed forecasting, providing a perspective on the future evolution of traffic states for accurate resilience assessment. In addition, we construct a composite traffic resilience indicator, designed to comprehensively reflect changes in the spatial–temporal resilience of the transportation system during heavy rain. Experimental results on four publicly real datasets indicate that the prediction performance of TD2MG2NN outperforms state-of-the-art models. The assessment results for the transportation road network in California demonstrate that the comprehensive resilience indicator is superior to single functional resilience indicator and the real-time methodology for evaluating resilience can accurately depict and predict the operation of the road network system under heavy rainfall scenarios.

Integrating flood and earthquake resilience: a framework for assessing urban community resilience against multiple hazards

Floods and earthquakes are the most common natural disasters, causing significant damage and casualties in urban communities. Although academic research has focused on assessing cities' ability to withstand these natural disasters, there is a lack of established frameworks for evaluating resilience against multiple hazards. This research integrates the earthquake and flood resilience indicators to create a comprehensive resilience assessment framework. This study integrated seismic and flood resilience indicators and categorized them into 27 clusters. It also used the DEMATEL (Decision-Making Trial and Evaluation Laboratory) method to determine the significance of clusters and prioritize them. This research identified 13 cause clusters and 14 effect clusters of indicators for seismic and flood resilience. The ‘response capacity’ cluster has the most impact on seismic and flood resilience, while the ‘transportation and accessibility’ cluster is the most affected cluster. This article presents a framework for evaluating flood and seismic resilience and makes suggestions for future research.

A Social-Ecological Systems Perspective on Working toward Resilience in Nature-Based Tourism Planning

ABSTRACT Integration of resilience thinking and systems approaches with nature-based tourism (NBT) planning to address the uncertainties and the dynamic complexities of the twenty-first century. It highlights the inadequacy of conventional planning methods to address the challenges faced by NBT, emphasizing the need for adaptive management and sustainable development practices. The study proposes a comprehensive resilience framework that includes three foundational elements: governance flexibility, a culture of learning, and financial support for resilience initiatives. Additionally, it outlines six actionable strategies to enhance resilience in NBT planning, such as acknowledging inherent turbulence, embracing systems thinking, and fostering adaptive pathways. Through a synthesis of classical and contemporary literature, this manuscript contributes novel insights and practical guidance for incorporating resilience into NBT planning, offering a path forward for sustaining tourism in the face of global disruptions and local challenges.

Understanding Resilience – a Conceptual Framework

Abstract Nowadays we face a shift of paradigm from risk management to resilience management. Resilience is a complex concept that has become not just a “buzzword”, but also a meta-concept used in fields as far apart as biology, psychology, environmental studies, system-of-systems engineering and more. In this regard, the authors conducted fundamental research (mainly a literature review of a selection of open-source papers) to increase awareness towards the conceptual elements related to resilience. There were defined three resilience-related concepts: engineering resilience, organizational resilience and socioecological resilience. Afterwards, the main characteristics of resilient systems were highlighted. Nevertheless, the authors described a possible organizational resilience framework. The 6 suggested and detailed steps are: the comprehensive resilience analysis encompassing existing or new methodologies – audit, defining and fleshing out needed strategies, the actual design of measures to be implemented, the implementation phase of the previously designed measures, the monitoring step, and the evaluation phase of the success of the various implemented measures. The main limitation of the present research is the lack of validation of the proposed methodology.

Electrical resilience assessment of a building operating at low voltage

Resilience is becoming increasingly important in power systems, microgrids (MG) and buildings. It evaluates their performance against disruptive events. The approaches mainly correspond to high-impact, low-probability events such as natural disasters and intentional attacks affecting the electrical systems infrastructure. However, resilience can encompass medium and low-impact events such as minor civil structural accidents, light faults and supply disturbances. Some resilience assessment advances are in buildings at the low-voltage (LV) level. They include vulnerability to natural disasters, reliability of supply, and service quality. These works usually use approaches independent of each other, leaving a gap between their relationship and interpretation. Therefore, there is a need to consolidate a resilience assessment strategy to guide the analysis of vulnerabilities and strengths in the same direction. This paper proposes a comprehensive approach to evaluate electrical resilience for buildings. It compiles quantitative strategies for studying electrical resilience, focusing on LV systems. It proposes a methodology for integrating the electrical system infrastructure's vulnerability, the supply's continuity and the voltage service's quality. Implementing this approach in a university building equipped with smart metering demonstrates the effectiveness of the proposed methodology for assessing electrical resilience. The results show a comprehensive resilience analysis and the possibility of extending the methodology to MG and LV distribution networks.

A study on the spatial and temporal evolution patterns of water resource–ecology–social economy composite system resilience in the Huaihe River Basin

ABSTRACT Water resources are important supporting elements in the ecological environment and socio-economic system of sustainable development. The purpose of this study is to evaluate the comprehensive resilience level of the water resources–ecology–socioeconomic system against external disturbances in the Anhui and Shandong sections of the Huaihe River Basin. The comprehensive index system is constructed with the characteristic dimensions of resistance, resilience, and adaptability. Use the game theory combination weighting-VIKOR method to quantify the resilience level, and use the kernel density analysis and Markov chain to explore the spatial and temporal evolution characteristics and transition probability. The results show that (1) the resilience index of the composite system in the Huaihe River Basin shows an increasing trend, and the resilience level of the Anhui section is generally higher than that of the Shandong section. (2) The resilience level gradually evolved into the spatial distribution characteristics of high in the west and low in the east, high in the south and low in the north during the study period. (3) The resilience grade has strong robustness, and the probability of transferring to the higher grade is greater than that of transferring to the lower grade.

Resilience Assessment of Historical and Cultural Cities from the Perspective of Urban Complex Adaptive Systems

Due to the increasingly complex global climatic environment and the rapid development of China’s urban construction, China’s historical and cultural cities are experiencing an external impact as well as internal fragility. Representing the capacity of the urban system to address impact and pressure, resilience can effectively guarantee the sustainable development of historical and cultural cities. A scientific and reasonable resilience assessment system can guide the resilience construction of historical and cultural cities in an effort to effectively counter the impact and pressure they face. Therefore, it is necessary to research the resilience of historical and cultural cities. On the basis of the complex adaptive system (CAS), and by applying multiple assessment indicators, this paper established a resilience assessment system for China’s historical and cultural cities, comprising 38 indicators in six dimensions, to analyze the characteristics and the influencing mechanisms of the resilience of the historical and cultural cities and to reveal the inherent logic underlying their complex presentation. Using six historical and cultural cities in east China as an example, the study applied the assessment system to assess and analyze the different resilience levels of the cities. The comprehensive resilience of Changzhou City obtained the highest score at 0.64, indicating a higher degree of resilience; the scores of Yantai City, Huzhou City, and Nantong City were 0.59, 0.54, and 0.50, respectively, representing moderate degrees of resilience; the scores of Zhongshan City and Quzhou City were 0.44 and 0.40, respectively, exhibiting a lower degree of resilience. Moreover, the factors that result in an unbalanced development of urban resilience were explored from the perspectives of economy, system, and culture. The paper contains some significance in guiding the development of the resilience of historical and cultural cities.

Conceptualizing heat vulnerability: equity-centered approaches for comprehensive resilience in a changing climate

Conceptualizing heat vulnerability: equity-centered approaches for comprehensive resilience in a changing climate

Typologies of secondary school student academic resilience in science with classroom and school context predictors

ABSTRACT The education system strives to help students from low-income families achieve academic success. Academic resilience is related to not only individuals but also classrooms and schools. This study aimed to construct a comprehensive resilience model in science domains that presents the image of resilient students and describes the mechanisms by which they arise. This goal was achieved through a parametric multilevel latent profile analysis with level 1 and level 2 covariates. Latent profile indicators included variables reflecting motivation, subjective well-being, and engagement in science of secondary school students. Variables related to science classroom and school contexts constituted the levels 1 and 2 covariates. We used secondary data from Japan and Macao (China) collected in the 2015 Programme of International Student Assessment (PISA). The sample sizes were 1594 and 1114, respectively. We identified three resilience levels among students. The emergence of resilient students benefited from science classroom discipline, teacher-directed instruction, inquiry-based teaching, adjusting instruction, and teacher support. In Japan, the most robust predictor was inquiry-based teaching, while in Macao, it was teacher-directed instruction. Therefore, science teachers play a crucial role in building students’ resilience. It also suggests that a small class decreases the likelihood of students entering the high-level resilience group.

A comprehensive resilience evaluation method for power distribution systems based on weighted Page-Rank algorithm

Resilience evaluation plays a critical role in the decarbonized development of modern power distribution systems since it objectively assesses how the distribution system performs in the face of stochastic renewable generation, increasing load demand, and promising to cut carbon emissions. This study proposed a comprehensive resilience evaluation method for regional distribution systems. The proposed resilience evaluation system comprises three sub-groups: performance, economy, and connections. To improve the objectivity of the proposed evaluation method, the weighting factors are calculated based on the Analytic Hierarchy Process (AHP) and weighted Page-ranking algorithm, respectively. Specifically, AHP is adopted to calculate the weighting factors for different metrics. At the same time, the original Page-ranking algorithm is improved according to the importance of the buses and then used to calculate the weighting factors for different buses within the same metric. The proposed method is applied to a real-world distribution network in China. Numerical results show that the proposed method can objectively evaluate the overall resilience level of the distribution network, including the source side, the network, and the load side. The evaluation results can help the decision-makers to make resilience enhancement in an economical and targeted way.

Zoning strategies for ecological restoration in the karst region of Guangdong province, China: a perspective from the “social-ecological system”

Ecological restoration holds great significance in addressing environmental degradation and rock desertification in karst areas. Zoning strategy is a fundamental task in understanding the interrelationship between human-environment to foster sustainable development. We explore “social-ecological” system and conduct a case study on the karst region in Guangdong Province, China. An evaluation framework consists of “development pressure”, “sensitivity status”, and “resilience potential” was established. The results show that: regions with high pressure of development are predominantly located in high-density urban areas. The generally distribution of the comprehensive status index exhibits significant spatial heterogeneity. Regions with low sensitivity are found on the eastern and western sides of the study area. The comprehensive resilience values are largely influenced by per capita energy-saving and environmental protection expenditures. The restoration zones mainly concentrated in the contiguous regions of the northwestern and southern parts, covering more than half of the total area. The conservation zones are more numerous and primarily situated in the northern and eastern parts. By integrating socio-economic and ecological factors, this study proposes ecological restoration strategies for specific zones. It helps for improve development issues arising from complex interactions between human-environment, facilitating the implementation of restoration practices.