Evaluation Of Resilience Research Articles

An Evaluation of Resilience as a Protective Factor for Mental Health Among Sexual and Gender Minority Young People.

Purpose: Sexual and gender minority (SGM) individuals often face minority stressors that negatively affect their mental health, making it important to identify protective factors against the adverse psychological effects of minority stress. We investigated the potential protective effect of trait resilience in SGM individuals assigned female at birth (SGM-AFAB), who are understudied despite being at particularly high risk for mental health problems. Methods: As part of an ongoing longitudinal cohort study, 452 SGM-AFAB young people (age 16-31 years) completed measures of resilience, minority stressors (victimization, microaggressions, internalized heterosexism, and cisgenderism), and mental health (depression, anxiety, suicidal ideation) in 2017-2018. Moderating effects of resilience on associations between the minority stressors and mental health outcomes were tested using regression analyses. Results: Resilience attenuated the positive associations of microaggressions with both depression and anxiety and of internalized cisgenderism with depression (in transgender and gender-diverse participants), suggesting protective effects. Resilience did not moderate any other associations. Conclusion: These findings suggest that resilience serves as a protective factor against depressive and anxiety symptoms following experiences of microaggressions and against depressive symptoms following internalized cisgenderism among diverse SGM-AFAB individuals. These results underscore the importance of identifying factors that bolster resilience and developing intervention strategies aimed at promoting resilience within SGM-AFAB individuals, especially following experiences of microaggressions and internalized cisgenderism.

A novel multi-criteria decision making method to evaluate green innovation ecosystem resilience

Green innovation ecosystem resilience evaluation is crucial for ensuring sustainable development in dynamic environments. By comprehensively assessing resilience, it helps identify risks and facilitate effective responses, thus promoting sustainable development. To effectively evaluate the resilience of green innovation ecosystems, this paper proposes a model based on the interval-valued intuitionistic fuzzy multi-criteria decision-making (MCDM) method, designed to support decision-makers (DMs) in resilience evaluation. In this model, we improve the Criteria Importance Through Intercriteria Correlation (CRITIC) method by introducing Spearman's correlation coefficient to more accurately determine the objective weights of various indicators based on their interrelationships. Furthermore, we propose an Interval-Valued Intuitionistic Fuzzy Hybrid Average Aggregation (IVIFHAA) operator, which considers both the subjective and objective weight order for aggregating expert evaluation results. Additionally, a scoring function is introduced to generate ranked evaluation results. We also establish a resilience evaluation criteria system covering interconnectivity, sustainability, and diversity within green innovation ecosystems to assist DMs in resilience evaluation. Finally, to validate this method, we apply it to assess the resilience of regional green innovation ecosystems and compare it with other methods. The results demonstrate that the improved operator effectively reduces information loss and improves evaluation efficiency, while the improved CRITIC method handles outliers during the evaluation process.

Digital retailing practices for triggering physical retailers’ bounce-back and bounce-forward performance against a great shock: evidence from the COVID-19 pandemic

This paper explores the mapping from specific digitalization practices to specific resilient performance against a great shock. Based on an adapted structure–conduct–performance framework, this paper hypothesizes by theoretically analyzing how the pre-shock establishment of digital retailing practices could trigger physical retailers’ bounce-back and bounce-forward performance against the COVID-19 crisis. Using a difference-in-differences strategy, the hypotheses are examined with a sample including 549 observations of 50 Chinese listed retailers from the first quarter of 2018 to the third quarter of 2020. The empirical results mainly indicate the following binary findings. First, regardless of the differences in triggering bounce-back performance, different digital retailing practices are found to be effective in triggering physical retailers’ bounce-forward performance against the COVID-19 crisis. This somewhat addresses the concern about the temporality of digitalization-enabled resilience by revealing the generality across digital retailing practices in the sense of triggering resilient performance. Second, it is shown that physical retailers’ bounce-back performance at a specific stage of the COVID-19 crisis could only be triggered by digital retailing practices that coincidentally apply to the shock-induced market structure changes at the stage. The results emphasize each digitalization practice’s individuality in triggering resilient performance. This justifies the non-negligibility of the direct mapping from specific digitalization practices to specific resilient performance in digitalization-enabled resilience evaluation.

Impacts of Missing Data Imputation on Resilience Evaluation for Water Distribution System

Impacts of Missing Data Imputation on Resilience Evaluation for Water Distribution System

Exploring an adaptive management model for “status-optimization-regulation” of mining city in transition: A case study of Huangshi, China

Mining cities face the challenges of ecological transformation and sustainable development after mineral depletion. Thus, ecological space optimization and adaptive management are pivotal after ecological restoration project, but easily neglected. Taking Huangshi in Hubei Province as an example, a top-down adaptive management model for regional mining ecological space integrating status-optimization-regulation (SOR) was established based on land system resilience (LSR) evaluation, circuit theory, complex network model and community discovery algorithm. The results showed that i) As the LSR increased, the land use structure shifted from non-ecological zones to forest and cropland, indicating that balancing agriculture and forest protection was crucial for increasing LSR in Huangshi. i) The ecological networks (ENs) of Huangshi had an irregular fishnet pattern, with densely intricate corridors in the south and broader, sparser ones in the north, and numerous ecological barriers near the mining area. Furthermore, the distribution of ecological sources and corridors displayed complementarity and hierarchy. iii) The optimized ENs exhibited higher connectivity and efficiency under disturbance, reducing corridor redundancy and migration costs. iv) The ENs clusters were classified into five types based on ecological connectivity: ecological buffer zone, priority restoration zone, moderate restoration zone, natural restoration zone, and moderate development zone, and tailored ecological regulatory strategies were proposed. The findings provide practice-oriented guidance for the sustainable development of mining cities, and offer a direct approach to support conscious, clear, and coherent adaptive management of ecological restoration in rapidly changing environments.

Resilience evaluation of memristor based PUF against machine learning attacks

Physical unclonable functions (PUFs) have emerged as a favorable hardware security primitive, they exploit the process variations to provide unique signatures or secret keys amidst other critical cryptographic applications. CMOS-based PUFs are the most popular type, they generate unique bit strings using process variations in semiconductor fabrication. However, most existing CMOS PUFs are found to be vulnerable to modeling attacks based on machine learning (ML) algorithms. Memristors leveraging nanotechnology fabrication processes and highly nonlinear behavior became an interesting alternative to the existing CMOS-based PUF technology, introducing cryptographic and resilient random outputs. Memristor-based PUFs are emerging due to the inherent randomness at both the memristor level due to the cycle-to-cycle (C2C) programming variation of the device and the fabrication process level such as the cross-sectional area and variations. Our study focuses on building a machine learning analysis and attack framework of tools on Cu/HfO2-x/p++Si\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$Cu/HfO_{2-x}/p^{++}Si$$\\end{document} memristor-based PUF (MR-PUF). Our objective is to test the resiliency of the security margins of the presented PUF using machine learning analysis tools, on-top of holistic NIST cryptographic randomness testing initially provided, to provide a high level of certainty in predicting the randomness output of the verified Memrister-based PUF. Our main contribution is a holistic study that focuses on attacking the randomness output resiliency based on building randomness predictors using Logistic Regression (LR), Support Vector Machine (SVM), Gaussian Mixture Models (GMM), K-means, K-means++\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$++$$\\end{document}, Random Forest, XGBoost and LSTM, within efficient time, and data complexity. Our results yield low accuracy and ROC results of within 0.49-0.52\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$0.49-0.52$$\\end{document} and 0.49-0.52\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$0.49-0.52$$\\end{document} respectively, indicating failure in predicting random data demonstrates efficient randomness prediction resiliency of the MR-PUF. The efficient time and data complexities of these attacks illustrated in this study are yielded to be linear and quadratic resulting in attack execution time in seconds and 5032 training samples combined with 2157 testing samples to verify the randomness of PUF.

A Global Resilience Analysis-Based Benchmark Framework for Comparing Reliability Surrogate Measures of Water Distribution Systems

Various reliability surrogate measures have emerged over the last three decades to design water distribution systems. However, existing comparative studies cannot assess surrogate measures from the resilience perspective considering the dynamic absorption–recovery process imposed by pipe failures. In this work, we propose a novel benchmark framework based on the global resilience analysis to examine surrogate measures’ performance. Surrogate measures were compared via the stress–strain curve derived from the global resilience analysis under extended period simulation. In particular, we identify the comparable stress range to articulate the differences among surrogate measures and significantly reduce the computational burden. Then, we develop the normalized resilience score (NRS) to evaluate the quality of solutions to network design. Five well-known measures are compared for the multiobjective design of two benchmark networks. Results show that the Network Resilience Index achieves 2.5% to 10.1% better NRSs than the mean NRSs over five surrogate measures, implying that both nodal surplus energy and pipe diameter uniformity greatly impact the network system’s resilience. The uniformity of pipe diameters is more significant than the uniformity of flow rate. Our findings contribute to the design of new and better surrogate measures for network resilience evaluation.

Clustering of Basic Educational Resources and Urban Resilience Development in the Central Region of China—An Empirical Study Based on POI Data

This paper presents an urban resilience evaluation index system and evaluation on the clustering of educational resources based on the data of 80 prefecture-level cities in China’s central region in 2012, 2016, and 2020. The results reveal a rising trend of urban resilience in the central region of China, with the provincial capital cities exhibiting the highest levels of resilience. Educational resources are clustered in urban areas of provincial capital cities and other prefectural-level cities. Furthermore, clustering of educational resources has a significant impact on urban resilience. Policy factors play a significant role in moderating the relationship between educational resource clustering and urban resilience in large cities; however, this moderating role is not significant in small cities. These findings have significant implications for the optimal allocation of educational resources, promotion of urban resilience, and advancement of social equity.

Resilience assessment of FPSO leakage emergency response based on quantitative FRAM

FPSO production process is prone to leakage, and failure to respond promptly and effectively will lead to accident escalation and serious consequences. However, traditional safety assessment methods cannot handle the nonlinear relationships between human, technology, and organization in emergency response process. This study proposes a quantitative FRAM to evaluate the emergency response resilience of FPSO leakage. This method establishes a resilience evaluation framework including three tiers: function, ability, and system, which can quantify system resilience based on the variability of function. First, identify basic functions according to the four stages of monitoring, response, learning and anticipation in the emergency response process, and establish the FRAM model of FPSO leakage emergency response. Then, the quantitative FRAM and Monte Carlo simulation are combined to calculate the variabilities of functions under different operating conditions. Finally, based on the simulation results, the variabilities of basic functions are aggregated and statistically analyzed to quantify system resilience. The implementation process of this method is illustrated by a case study. The influence of different factors on the system resilience is analyzed by setting various operation scenarios, and critical functions are identified by sensitivity analysis, which can provide reference for improving system resilience and ensuring FPSO safety production.

Spatiotemporal evolution and influencing factors of flood resilience in Beibu Gulf Urban Agglomeration

In the context of global climate change and rapid urbanization, enhancing flood resilience is essential for mitigating urban flood risk. However, few studies have conducted long-term, cross-scale dynamic evaluations of flood resilience and analyzed its influencing factors and mechanisms. Taking the Beibu Gulf urban agglomeration as the study area, a long-term, cross-scale dynamic evaluation index system based on the “Robustness-Resistance-Recovery” (3Rs) framework were adopted to assess the spatiotemporal evolution of flood resilience from 2000 to 2020. Furthermore, the optimal parameters-based geographical detector model is employed to identify the key influencing factors and mechanisms. The results reveal that pre-flood robustness is lower in coastal areas and higher in inland regions. In the during-flood stage, cities with greater comprehensive power exhibit stronger resistance. Post-flood recovery is higher in city centers and marginal mountainous areas, while coastal and inland low-lying regions show lower recovery. The flood resilience of urban agglomerations has improved in recent years, largely due to the enhancement of urban flood control infrastructure and healthcare capacity. However, disparities between cities persist. From 2000 to 2020, economic factors have been the primary drivers of improved flood resilience, while ecological factors have gained increasing importance over the past decade. These findings provide valuable insights for flood prevention, mitigation, and resilience management in urban agglomerations. The proposed dynamic evaluation index system offers a reference framework for evaluating flood resilience in other regions.

Intelligent vs. Cultural: Research on the Path to Improve the Resilience of Urban and Rural Community Governance Based on the AHP-FCE Model

Community resilience is a core component of grassroots governance modernization, and community resilience shows different characteristics depending on the type of community. Existing research on community resilience mainly uses direct questionnaire data, relatively ignoring the differences in weights of various dimensions. Different categories of community resilience components play different roles in community resilience. Based on this, the study cited the logic of the AHP-FCE model and added objective data based on empowering resilience, thus making up for the model's shortcomings while giving full play to the model's advantages. The quantitative analysis of 353 questionnaires from five urban districts and five rural communities in the sample city was based on the community resilience evaluation model. In the current process of community resilience construction, there are typical problems of a lack of cultural resilience in urban community resilience construction and a need for more intelligent resilience in rural community resilience construction. The key to future community resilience construction is reconciling the relationship between cultural and intellectual resilience to solve the problem of targeting deviation in urban communities and rural community resilience construction. It is necessary to adhere to the spirit of "long-term construction" to build the cultural resilience of urban communities, implement the path of "digital empowerment" to make the intelligent resilience of rural communities, and adhere to the standard of "complete redundancy" to form an urban and rural community resilience governance mechanism gradually, and then Move towards more resilient urban and rural community governance and help realize the modernization of grassroots governance.

Resiliency Evaluation of Sheltering in a Net-zero Energy House During Summer Power Outage

This study examines the growing issue of power outages caused by natural disasters and proposes the use of net-zero energy houses (ZEH) as a safe alternative to traditional shelters. A ZEH, equipped with an independent energy system, can maintain essential living standards such as thermal comfort and 24-hour air conditioning during a summer power outage, reducing the risk of heatstroke. The research tested a ZEH in Japan, confirming its ability to support critical household appliances like refrigerators, lighting, and water heaters for up to 72 hours. This demonstrates the ZEH's potential for offering safe, comfortable shelter during emergencies while addressing problems like poor sanitation and lack of privacy found in typical shelters. The experimental ZEH is located in Shizuoka, Japan, is a steel structure, and has a floor area of 110.94 m2 and overall heat transmission coefficient (UA) of 0.48 W/m2ཥK. The ZEH was equipped with a 5.1 kW photovoltaic system and 5.6/11.2 kWh storage battery (BT), which produced an output of up to 2.0/4.0 kVA. A ZEH with a 5.6 kWh BT can provide for ventilation and living/dining room/kitchen air conditioning (AC), refrigerator, television, lighting, mobile phone charging, rice cooker, microwave, electric kettle, and heat pump water heater during a 72-h power outage. The ZEH with a 11.2 kWh BT can also provide bedroom AC and high-load home appliances for lunch and dinner, in addition to a 5.6 kWh BT. The use of AC in a self-supporting circuit maintained the thermal environment at a low heat stroke risk.

Electricity supply resiliency evaluation by a hybrid renewable energy system for a petrochemical plant: Frameworks and quantitative assessment methodologies

The escalation of harm inflicted upon energy systems, has spurred the investigation of energy system resilience. In this regard, the measurement of resilience capacity can serve as a valuable metric for assessing the energy system's ability to withstand a variety of events that may result in potential adverse outcomes. For renewable energy systems, the measurement of resilience is imperative due to the inherent unpredictability and unreliability in their nature. Often, resilience studies lack the comprehensiveness required to fully comprehend the intricate interdependencies within integrated hybrid renewable energy systems. This research delineates the essential factors required to facilitate a comprehensive understanding and advancement in the quantification of such integrated systems in small-scale. Pardis Petrochemical Company, located in Asalouyeh city, Iran, has been chosen as case study. Four distinct configurations of hybrid renewable energy systems—comprising Photovoltaic panels, Photovoltaic panels + Wind Turbines, Photovoltaic panels + Wave energy converters, and Photovoltaic panels + Wind Turbines + Wave energy converters— connected to grid, have been developed. These configurations are the result of a multi-objective optimization process, considering the following metrics: the cost of electricity (as an economic metric), CO2 emissions (as an environmental metric), loss of power supply probability (as a reliability metric), and exergy efficiency (as a technical metric). Subsequently, a methodological framework for multicriteria decision support is introduced. This framework is constructed based on primary resilience dimensions, namely: “resist,” “restabilize,” “technology,” and “withstand” serve as a tool for measuring the resiliency of the optimized configurations. The findings indicate that the Photovoltaic panels + Wind Turbines + Wave Energy Converters configuration is as the most resilient system among the studied alternatives.

Performance evaluation of supply chain resilience in epidemic crises: an extension of network non-parametric methodology

Performance evaluation of supply chain resilience in epidemic crises: an extension of network non-parametric methodology

Differential Evaluation of Ecological Resilience in 45 Cities along the Yangtze River in China: A New Multidimensional Analysis Framework

The rapid pace of urbanization and global climate change necessitates a thorough assessment of urban ecological resilience to cultivate sustainable regional ecosystem development. Cities along the Yangtze River face an intensifying conflict between ecological preservation and socio-economic growth. Analyzing the ecological resilience of these urban centers is essential for achieving equilibrium in regional urban ecosystems. This study proposes a “system process space” attribute analysis framework, taking into account urban development processes, ecosystem structure, and resilience evolution stages. Utilizing data from 45 Yangtze River cities, we establish a “Driver, Pressure, State, Impact, and Response” (DPSIR) evaluation index system to evaluate changes in ecological resilience levels and evolution trends from 2011 to 2022. Our findings indicate that: (1) The ecological resilience index of Yangtze River cities increased from 0.177 to 0.307 between 2011 and 2022, progressing through three phases: ecological resilience construction, rapid development, and stable development. (2) At the city level, ecological resilience along the Yangtze River exhibits uneven development characteristics. Upstream cities display a significant “stepped” pattern, midstream cities exhibit a significant “Matthew effect”, and downstream cities present a pyramid-shaped pattern. While regional differences in ecological resilience persist, overall polarization is gradually decreasing, intercity connections are strengthening, and there is a growing focus on coordinated regional development. (3) The spatial distribution of ecological resilience in Yangtze River cities demonstrates both continuity and evolution, generally forming a “core-edge” clustered pattern. Based on these findings, we recommend enhancing inter-city cooperation and connectivity, addressing imbalances in urban ecological resilience, and promoting high-quality ecological resilience development along the Yangtze River through tailored development strategies for each city.

Ecological Flood Resilience Index (EFRI) to Assess the Urban Pluvial Flood Resilience of Blue-Green infrastructure: A case from a southwestern coastal city of India

Urban pluvial flood resilience planning must account for the ecological capacity to absorb, adapt, and transform with floods. Research on flood resilience indices highlights resilience as a normative condition, characterized by the return to equilibrium or the recovery time. However, the socio-ecological approach, including adaptive, absorptive, and transformative capacities is often overlooked, and the determinants of these capacities are underexplored. The present study addresses this gap by proposing an impact-based composite index to measure the flood resilience of urban Blue-Green Infrastructure (BGI). An eight-step procedure was used for the composite index construction. Statistical correlation and regression analysis established indicator appropriateness, and Principal Component Analysis (PCA) was used for weighing and aggregation. The Ecological Flood Resilience Index (EFRI) was developed and applied to the city of Kochi, India to assess the ability of existing urban BGI to temporarily store, infiltrate, and delay runoff, indicating the capacity of the system to withstand urban flooding. The index was validated using crowd-based data followed by sensitivity analysis. The EFRI Map outlines that the highly urbanized low resilient central areas, marked by poor vegetation and disrupted natural drainage contribute to flooding in various parts of the city. A comprehensive analysis of the 37 % regions of the city that falls within ‘very low’ to ‘extremely low’ resilience is essential to understand the critical factors in flood resilient spatial planning. The proposed composite index is significant for its novelty and theoretical clarity in resilience evaluations, promoting a shift from risk-based to resilience approaches in urban flood management.

Evaluating resilience and enhancing strategies for old urban communities amidst epidemic challenges

Epidemic outbreaks pose significant risks to sustainable urban development, underscoring the critical need to bolster the resilience of old communities, key to urban epidemic prevention. This study introduces a resilience evaluation system tailored for these communities, employs a cloud model-based fuzzy comprehensive evaluation (FCE) method, and selects Fuzhou City for a case study. It evaluates the resilience of three communities, Qixingjing Xincun (A), the Provincial Forestry Department's dormitory (B), and Wufeng Lanting community (C) across five dimensions. By employing system dynamics (SD) model, the study examines the interplay and impact mechanisms of resilience indicators, predicts trends and future developments, and proposes strategies to enhance resilience. Results indicate that: (1) community B exhibits the highest resilience, followed by A and C, validating the FCE method's efficacy; (2) resilience across all dimensions is on the rise, with no signs of plateauing observed; (3) enhancements in resilience are notably impactful in facility (A3), spatial (A1), environmental (A2) and resident resilience (A5) are extremely close to each other in terms of their impacts, while governance resilience (A4) exhibits minimal changes. Offering insightful contributions to the resilience study of old urban communities, this study serves as a guide for future practice in improving public safety and promoting urban development, and insights into universal urban challenges and resilience strategies.

Bidirectional evaluation and differentiation analysis of marine economic resilience in China

With the continuous improvement of the marine economy, the role of marine economic resilience is becoming ever more prominent. This study evaluates China’s marine economic resilience based on a bidirectional evaluation index system, and analyzes spatiotemporal characteristics and regional differences. The results show that: (1) marine economic resilience is increasing in the system object dimension and the resilience attribute dimension in China. Strengthening the protection of marine resources and the environment is important for improving marine economic resilience; (2) the development of marine economic resilience among 11 coastal provinces is unbalanced, forming a three-polar pattern with Shandong as the core in the north, Shanghai as the core in the east, and Guangdong as the core in the south; (3) the difference between the northern marine economic circle and the southern marine economic circle is the main reason for the overall difference.

Solution for time-dependent resilience in the presence of gradual deterioration of performance

In this paper, a closed-form method is developed for the evaluation of time-dependent resilience (so named as it is a function of the service time of interest) of an aging object (e.g., a structure or system). These structures and systems often suffer from the deterioration of performances in a harsh service environment, causing the decline of serviceability. They are thus expected to be sufficiently resilient during their service lives, i.e., to have the ability to withstand disruptions to their performances. The proposed method takes into account the uncertainty associated with the performance deterioration process, the availability of resources that support the performance recovery, and the impact of a changing environment. The accuracy and improved efficiency of the proposed method are demonstrated through three examples. It is also shown through sensitivity analysis that the impact of a changing environment, and the availability of recovery-supporting resources play an essential role in the time-dependent resilience. The proposed resilience method can also be used to efficiently guide the design of new structures that meet predefined resilience goals.

Resilience evaluation of active and passive redundancy using carbon-hydrogen-oxygen symbiosis network – An integrated and post-design analysis

Carbon-hydrogen-oxygen symbiosis network, which is an eco-industrial park design method, along with atomic targeting provides a different avenue to approach effluents whereby effluents from industries could be gathered and redistributed to the respective interceptors to produce products. Resilience of an eco-industrial park is of particular interest due to the fluctuating economy whereby commitment of participants would be into question due to downturn in the economy. Resilience index provides a metric to evaluate the resilience of an eco-industrial park by assigning a value between 0 and 1. Resilience of an eco-industrial park could be improved by either having active redundancy such as extra process lines or oversizing the process lines. However, passive redundancy such as storage and buffer tanks also play a role in improving resilience of an eco-industrial park. This work aims to develop a method for resilience evaluation of a carbon-hydrogen-oxygen symbiosis network as well as comparing active and passive redundancy in resilience improvement of an eco-industrial park. Besides, the resilience metric is also incorporated into the carbon-hydrogen-oxygen symbiosis network model to compare the differences between post-design and integrated approach. The results obtained showed that while incorporation of both active and passive redundancy on all species would maximise the resilience index, partial combination of both could achieve a similar result. Besides, post-design and integrated approach would yield similar resilience index when interceptors of carbon-hydrogen-oxygen symbiosis network is limited. When more degrees of freedom are given to the number of interceptors, the results of post-design would not differ much. On the other hand, the results from integrated approach would select extra interceptors. Primarily, species which have not been compensated in the network would be selected to allow for redirection of flow when disruption occurs.