Framework for assessing the influence of critical infrastructure interdependencies in post-disaster reconstruction management

Due to ever increasing climate instability, the number of natural disasters affecting society and communities is expected to increase globally in the future, which will result in a growing number of casualties and damage to property and infrastructure. Such damage poses crucial challenges for recovery of interdependent critical infrastructures. Post-disaster reconstruction is a complex undertaking as it is not only closely linked to the well-being and essential functioning of society, but also requires a large financial commitment. Management of critical infrastructure during post-disaster recovery needs to be underpinned by a holistic recognition that the recovery of each individual infrastructure system (e.g. energy, water, transport and information and communication technology) can be affected by the interdependencies that exist between these different systems. A fundamental characteristic of these interdependencies is that failure of one critical infrastructure system can result in the failure of other interdependent infrastructures, leading to a cascade of failures, which can impede post-disaster recovery and delay the subsequent reconstruction process. Consequently, there is a critical need for developing a holistic strategy to assess the influence of infrastructure interdependencies, and for incorporating these interdependencies into a post-disaster recovery strategy. This paper discusses four key dimensions of interdependencies that need to be considered in a post-disaster reconstruction planning. Using key concepts and sub-concepts derived from the notion of interdependency, the paper examines how critical infrastructure interdependencies affect the recovery processes of damaged infrastructures.

Inter-organisational characteristics of resilience in a post-disaster recovery context

During post-disaster recovery, an infrastructure system may be subject to a number of disturbances originating from several other interdependent infrastructures. These disturbances might result in a series of system failures, thereby having immediate impact on societal living conditions. The inability to detect signs of disturbance from one infrastructure during recovery might cause significant disruptive effects on other infrastructure via the interconnection that exist among them. In such circumstances, it clearly appears that critical infrastructures' interdependencies affect the recovery of each individual infrastructure, as well as those of other interdependent infrastructure systems. This is why infrastructure resilience needs to be improved in function of those interdependencies, particularly during the recovery period to avoid the occurrence of a ‘disaster of disaster’ scenario. Viewed from this perspective, resilience is achieved through an inter-organisational collaboration between the different organisations involved in the reconstruction of interdependent infrastructure systems. This paper suggests that to some extent, the existing degree of interconnectedness between these infrastructure systems can also be found in their resilience ability during post-disaster recovery. For instance, without a resilient energy system, a large-scale power outage could affect simultaneously all the interdependent infrastructures after a disaster. Thus, breaking down the silos of resilience would be the first step in minimizing the risks of disaster failures from one infrastructure to cascade or escalate to other interconnected systems.

Engineering Phenomenography

This chapter extends the phenomenographical research method by arguing the merits of engineering the outcome space from these investigations to effectively communicate the outcomes to an audience in technology-based discipline areas. Variations discovered from the phenomenographical study are blended with pre and post tests and a frequency distribution. Outcomes are then represented in a visual statistical manner to suit the specific target audience. This chapter provides useful insights that will be of interest to researchers wishing to present findings from qualitative research methods, and particularly the outcomes of phenomenographic investigations, to an audience in technology-based discipline areas.

Public space design of knowledge and innovation spaces: Learnings from Kelvin Grove Urban Village, Brisbane

The era of knowledge-based urban development has led to an unprecedented increase in mobility of people and the subsequent growth in new typologies of agglomerated enclaves of knowledge such as knowledge and innovation spaces. Within this context, a new role has been assigned to contemporary public spaces to attract and retain the mobile knowledge workforce by creating a sense of place. This paper investigates place making in the globalized knowledge economy, which develops a sense of permanence spatio-temporally to knowledge workers displaying a set of particular characteristics and simultaneously is process-dependent getting developed by the internal and external flows and contributing substantially in the development of the broader context it stands in relation with. The paper reviews the literature and highlights observations from Kelvin Grove Urban Village, located in Australia’s new world city Brisbane, to understand the application of urban design as a vehicle to create and sustain place making in knowledge and innovation spaces. This research seeks to analyze the modified permeable typology of public spaces that makes knowledge and innovation spaces more viable and adaptive as per the changing needs of the contemporary globalized knowledge society.

Community participation in post-disaster reconstruction

When a community already torn by a prolonged war is subsequently subjected to being hit by a natural disaster, the combined impact of such disasters can be extremely devastating. Affected communities often face enormous challenges during the long-term reconstruction, mainly due to the lack of a viable community involvement process. In post-war settings, affected communities are often conceived as being disabled and are hardly ever consulted when reconstruction projects are instigated. This lack of community involvement often leads to poor project planning, decreased community support and an unsustainable completed project. The impact of war, coupled with the tensions created by the poor housing provisions, often hinder the affected residents from integrating permanently into their home communities. This paper identifies a number of fundamental factors that act as barriers to community participation in reconstruction projects. The paper is based on a statistical analysis of a questionnaire survey administered in 2012 in Afghanistan.

Populations of models, experimental designs and coverage of parameter space by Latin Hypercube and Orthogonal Sampling

In this paper we have used simulations to make a conjecture about the coverage of a t-dimensional subspace of a d-dimensional parameter space of size n when performing k trials of Latin Hypercube sampling. This takes the form P(k,n,d,t) = 1 - e^(-k/n^(t-1)). We suggest that this coverage formula is independent of d and this allows us to make connections between building Populations of Models and Experimental Designs. We also show that Orthogonal sampling is superior to Latin Hypercube sampling in terms of allowing a more uniform coverage of the t-dimensional subspace at the sub-block size level. These ideas have particular relevance when attempting to perform uncertainty quantification and sensitivity analyses.

The influence of critical infrastructure interdependencies on post-disaster reconstruction: Elements of infrastructure interdependency that impede the post-disaster recovery effort

The importance of developing effective disaster management strategies has significantly grown as the world continues to be confronted with unprecedented disastrous events. Factors such as climate instability, recent urbanization along with rapid population growth in many cities around the world have unwittingly exacerbated the risks of potential disasters, leaving a large number of people and infrastructure exposed to new forms of threats from natural disasters such as flooding, cyclones, and earthquakes. With disasters on the rise, effective recovery planning of the built environment is becoming imperative as it is not only closely related to the well-being and essential functioning of society, but it also requires significant financial commitment. In the built environment context, post-disaster reconstruction focuses essentially on the repair and reconstruction of physical infrastructures. The reconstruction and rehabilitation efforts are generally performed in the form of collaborative partnerships that involve multiple organisations, enabling the restoration of interdependencies that exist between infrastructure systems such as energy, water (including wastewater), transport, and telecommunication systems. These interdependencies are major determinants of vulnerabilities and risks encountered by critical infrastructures and therefore have significant implications for post-disaster recovery. When disrupted by natural disasters, such interdependencies have the potential to promote the propagation of failures between critical infrastructures at various levels, and thus can have dire consequences on reconstruction activities. This paper outlines the results of a pilot study on how elements of infrastructure interdependencies have the potential to impede the post-disaster recovery effort. Using a set of unstructured interview questionnaires, plausible arguments provided by seven respondents revealed that during post-disaster recovery, critical infrastructures are mutually dependent on each other’s uninterrupted availability, both physically and through a host of information and communication technologies. Major disruption to their physical and cyber interdependencies could lead to cascading failures, which could delay the recovery effort. Thus, the existing interrelationship between critical infrastructures requires that the entire interconnected network be considered when managing reconstruction activities during the post-disaster recovery period.

Organisational belongingness mediates the relationship between sources of stress and post-trauma outcomes in fire-fighters

Previous research with emergency service workers has examined the relationship between operational and organisational stress and negative indicators of mental health, and generally found that organisational stress is more strongly related to pathology than operational stress. The current study aimed to create and test a model predicting both posttraumatic stress disorder (PTSD) symptoms and posttraumatic growth (PTG) simultaneously in a sample of fire-fighters (N = 250). The results found that the model demonstrated good fit for the data. In contrast to previous research operational stress was directly related to PTSD symptoms, while organisational stress was not. Organisational stress was indirectly related to PTG, through the mediating role of organisational belongingness. This research identified organisational belongingness as a good target for psychosocial interventions aimed at promoting positive adaptation following the experience of trauma in emergency services.

Territoriality and the regulation of public space in Favela Morro da Formiga, Rio de Janeiro

Public space in many communities around the world has been identified as over-regulated and devoid of social vibrancy. This research contributed new knowledge regarding the way local residents territorialise and take ownership of streets and open areas in a favela, or informal settlement, in Rio De Janeiro, Brazil. Findings showed that public spaces were only partly activated by spatial pattern or structure. User agency also played a significant role, despite recent regulatory and policing interventions in the favela. This may have important implications for new communities where design could allow for more flexible usage and thereby enhance social vibrancy.

Fourier spectral methods for fractional-in-space reaction-diffusion equations

Fractional differential equations are becoming increasingly used as a powerful modelling approach for understanding the many aspects of nonlocality and spatial heterogeneity. However, the numerical approximation of these models is demanding and imposes a number of computational constraints. In this paper, we introduce Fourier spectral methods as an attractive and easy-to-code alternative for the integration of fractional-in-space reaction-diffusion equations described by the fractional Laplacian in bounded rectangular domains ofRn. The main advantages of the proposed schemes is that they yield a fully diagonal representation of the fractional operator, with increased accuracy and efficiency when compared to low-order counterparts, and a completely straightforward extension to two and three spatial dimensions. Our approach is illustrated by solving several problems of practical interest, including the fractional Allen–Cahn, FitzHugh–Nagumo and Gray–Scott models, together with an analysis of the properties of these systems in terms of the fractional power of the underlying Laplacian operator.

Estimates on the coverage of parameter space using populations of models

In this paper we provide estimates for the coverage of parameter space when using Latin Hypercube Sampling, which forms the basis of building so-called populations of models. The estimates are obtained using combinatorial counting arguments to determine how many trials, k, are needed in order to obtain specified parameter space coverage for a given value of the discretisation size n. In the case of two dimensions, we show that if the ratio (Ø) of trials to discretisation size is greater than 1, then as n becomes moderately large the fractional coverage behaves as 1-exp-ø. We compare these estimates with simulation results obtained from an implementation of Latin Hypercube Sampling using MATLAB.

Numerical analysis of a new space-time variable fractional order advection-dispersion equation

Many physical processes appear to exhibit fractional order behavior that may vary with time and/or space. The continuum of order in the fractional calculus allows the order of the fractional operator to be considered as a variable. In this paper, we consider a new space–time variable fractional order advection–dispersion equation on a finite domain. The equation is obtained from the standard advection–dispersion equation by replacing the first-order time derivative by Coimbra’s variable fractional derivative of order α(x)∈(0,1]α(x)∈(0,1], and the first-order and second-order space derivatives by the Riemann–Liouville derivatives of order γ(x,t)∈(0,1]γ(x,t)∈(0,1] and β(x,t)∈(1,2]β(x,t)∈(1,2], respectively. We propose an implicit Euler approximation for the equation and investigate the stability and convergence of the approximation. Finally, numerical examples are provided to show that the implicit Euler approximation is computationally efficient.

Post-transcriptional regulation in the nucleus and cytoplasm: study of mean time to threshold (MTT) and narrow escape problem

Messenger RNAs (mRNAs) can be repressed and degraded by small non-coding RNA molecules. In this paper, we formulate a coarsegrained Markov-chain description of the post-transcriptional regulation of mRNAs by either small interfering RNAs (siRNAs) or microRNAs (miRNAs). We calculate the probability of an mRNA escaping from its domain before it is repressed by siRNAs/miRNAs via cal- culation of the mean time to threshold: when the number of bound siRNAs/miRNAs exceeds a certain threshold value, the mRNA is irreversibly repressed. In some cases,the analysis can be reduced to counting certain paths in a reduced Markov model. We obtain explicit expressions when the small RNA bind irreversibly to the mRNA and we also discuss the reversible binding case. We apply our models to the study of RNA interference in the nucleus, examining the probability of mRNAs escaping via small nuclear pores before being degraded by siRNAs. Using the same modelling framework, we further investigate the effect of small, decoy RNAs (decoys) on the process of post-transcriptional regulation, by studying regulation of the tumor suppressor gene, PTEN : decoys are able to block binding sites on PTEN mRNAs, thereby educing the number of sites available to siRNAs/miRNAs and helping to protect it from repression. We calculate the probability of a cytoplasmic PTEN mRNA translocating to the endoplasmic reticulum before being repressed by miRNAs. We support our results with stochastic simulations

The impact of orbital errors on the estimation of satellite clock errors and PPP

Precise satellite orbit and clocks are essential for providing high accuracy real-time PPP (Precise Point Positioning) service. However, by treating the predicted orbits as fixed, the orbital errors may be partially assimilated by the estimated satellite clock and hence impact the positioning solutions. This paper presents the impact analysis of errors in radial and tangential orbital components on the estimation of satellite clocks and PPP through theoretical study and experimental evaluation. The relationship between the compensation of the orbital errors by the satellite clocks and the satellite-station geometry is discussed in details. Based on the satellite clocks estimated with regional station networks of different sizes (∼100, ∼300, ∼500 and ∼700 km in radius), results indicated that the orbital errors compensated by the satellite clock estimates reduce as the size of the network increases. An interesting regional PPP mode based on the broadcast ephemeris and the corresponding estimated satellite clocks is proposed and evaluated through the numerical study. The impact of orbital errors in the broadcast ephemeris has shown to be negligible for PPP users in a regional network of a radius of ∼300 km, with positioning RMS of about 1.4, 1.4 and 3.7 cm for east, north and up component in the post-mission kinematic mode, comparable with 1.3, 1.3 and 3.6 cm using the precise orbits and the corresponding estimated clocks. Compared with the DGPS and RTK positioning, only the estimated satellite clocks are needed to be disseminated to PPP users for this approach. It can significantly alleviate the communication burdens and therefore can be beneficial to the real time applications.

Missing in space: An evaluation of imputation methods for missing data in spatial analysis of risk factors for type II diabetes

Background Spatial analysis is increasingly important for identifying modifiable geographic risk factors for disease. However, spatial health data from surveys are often incomplete, ranging from missing data for only a few variables, to missing data for many variables. For spatial analyses of health outcomes, selection of an appropriate imputation method is critical in order to produce the most accurate inferences. Methods We present a cross-validation approach to select between three imputation methods for health survey data with correlated lifestyle covariates, using as a case study, type II diabetes mellitus (DM II) risk across 71 Queensland Local Government Areas (LGAs). We compare the accuracy of mean imputation to imputation using multivariate normal and conditional autoregressive prior distributions. Results Choice of imputation method depends upon the application and is not necessarily the most complex method. Mean imputation was selected as the most accurate method in this application. Conclusions Selecting an appropriate imputation method for health survey data, after accounting for spatial correlation and correlation between covariates, allows more complete analysis of geographic risk factors for disease with more confidence in the results to inform public policy decision-making.