Crisis response planning in tunnel and road networks

Critical road infrastructure (such as tunnels and overpasses) is of major significance to society and constitutes major components of interdependent, ‘systems and networks’. Failure in critical components of these wide area infrastructure systems can often result in cascading disturbances with secondary and tertiary impacts - some of which may become initiating sources of failure in their own right, triggering further systems failures across wider networks. Perrow1) considered the impact of our increasing use of technology in high-risk fields, analysing the implications on everyday life and argued that designers of these types of infrastructure systems cannot predict every possible failure scenario nor create perfect contingency plans for operators. Challenges exist for transport system operators in the conceptualisation and implementation of response and subsequent recovery planning for significant events. Disturbances can vary from reduced traffic flow causing traffic congestion throughout the local road network(s) and subsequent possible loss of income to businesses and industry to a major incident causing loss of life or complete loss of an asset. Many organisations and institutions, despite increasing recognition of the effects of crisis events, are not adequately prepared to manage crises2). It is argued that operators of land transport infrastructure are in a similar category of readiness given the recent instances of failures in road tunnels. These unexpected infrastructure failures, and their ultimately identified causes, suggest there is significant room for improvement. As a result, risk profiles for road transport systems are often complex due to the human behaviours and the inter-mix of technical and organisational components and the managerial coverage needed for the socio-technical components and the physical infrastructure. In this sense, the span of managerial oversight may require new approaches to asset management that combines the notion of risk and continuity management. This paper examines challenges in the planning of response and recovery practices of owner/operators of transport systems (above and below ground) in Australia covering: • Ageing or established infrastructure; and • New-build infrastructure. With reference to relevant international contexts this paper seeks to suggest options for enhancing the planning and practice for crisis response in these transport networks and as a result support the resilience of Critical Infrastructure.

A critical analysis of crisis escalation models : understanding stages and severity in infrastructure disturbance

A range of authors from the risk management, crisis management, and crisis communications literature have proposed different models as a means of understanding components of crisis. A generic component of these sources has focused on preparedness practices before disturbance events and response practices during events. This paper provides a critical analysis of three key explanatory models of how crises escalate highlighting the strengths and limitations of each approach. The paper introduces an optimised conceptual model utilising components from the previous work under the four phases of pre-event, response, recovery, and post-event. Within these four phases, a ten step process is introduced that can enhance understanding of the progression of distinct stages of disturbance for different types of events. This crisis evolution framework is examined as a means to provide clarity and applicability to a range of infrastructure failure contexts and provide a path for further empirical investigation in this area.

Screening in early childhood for risk of later mental health problems : a longitudinal study

Depression in childhood or adolescence is associated with increased rates of depression in adulthood. Does this justify efforts to detect (and treat) those with symptoms of depression in early childhood or adolescence? The aim of this study was to determine how well symptoms of anxiety/depression (A-D) in early childhood and adolescence predict adult mental health. The study sample is taken from a population-based prospective birth cohort study. Of the 8556 mothers initially approached to participate 8458 agreed, of whom 7223 mothers gave birth to a live singleton baby. Children were screened using modified Child Behaviour Checklist (CBCL) scales for internalizing and total problems (T-P) at age 5 and the CBCL and Youth Self Report (YSR) A-D subscale and T-P scale at age 14. At age 21, a sub-sample of 2563 young adults in this cohort were administered the CIDI-Auto. Results indicated that screening at age 5 would detect few later cases of significant mental ill-health. Using a cut-point of 20% for internalizing at child age 5 years the CBCL had sensitivities of only 25% and 18% for major depression and anxiety disorders at 21 years, respectively. At age 14, the YSR generally performed a little better than the CBCL as a screening instrument, but neither performed at a satisfactory level. Of the children who were categorised as having YSR A-D at 14 years 30% and 37% met DSM-IV criteria for major depression and anxiety disorders, respectively, at age 21. Our findings challenge an existing movement encouraging the detection and treatment of those with symptoms of mental illness in early childhood.

Validating a screening tool for mental health and substance use risk in an Indigenous prison population

Introduction and Aims: The Indigenous Risk Impact Screen (IRIS) is a validated culturally appropriate and widely used tool in the community for assessing substance use and mental disorder. This research aimed to assess the utility of this tool in an Indigenous prison population. Design and Methods: The study used data collected from a cross-sectional study of mental health among indigenous inmates in Queensland custodial centres (n=395, 84% male). Participants were administered a modified version of the IRIS, and ICD-10 diagnoses of substance use, depressive and anxiety disorders obtained using the Composite International Diagnostic Interview (CIDI). The concurrent validity of the modified IRIS was assessed against those of the CIDI. Results: 312 people screened as high risk for a substance use disorder and 179 were high risk for mental problems. 73% of males and 88% of females were diagnosed with a mental disorder. The IRIS was an effective screener for substance use disorders, with high sensitivity (Se) of 94% and low specificity (Sp) of 33%. The screener was less effective in identifying depression (Se 82%, Sp 59%) and anxiety (Se 68%, Sp 60%). Discussion: The IRIS is the first culturally appropriate screening instrument to be validated for the risk of drug and alcohol and mental disorder among Indigenous adults in custody. Conclusions: This study demonstrated that the IRIS is a valid tool for screening of alcohol and drug use risk among an incarcerated Indigenous population. The IRIS could offer an opportunity to improve the identification, treatment and health outcomes for incarcerated Indigenous adults.

PCV13 Perceptions of health during pregnancy increase the risk of cardiovascular disease

OBJECTIVES: To examine the prospective association between perception of health during pregnancy and cardiovascular risk factor of mothers 21 years after the index pregnancy. METHODS: Data used were from the Mater University Study of Pregnancy (MUSP), a community- based prospective birth ohort study begun in Brisbane, Australia, in 1983. Logistic regression analyses were conducted. RESULTS: Data were available for 3692 women. Women who perceived themselves as not having a straight forward pregnancy had twice the odds (adjusted OR 2.0, 95% CI 1.1-3.8) of being diagnosed with heart disease 21 years after the indexpregnancyascomparedtowomenwith a straight forward pregnancy. Apart from that, women who had complications (other than serious pregnancy complications) during the pregnancy were also at30%increased odds (adjustedOR 1.3, 95% CI 1.0-1.6) of having hypertension 21 years later. CONCLUSIONS: As a whole, our study suggests that pregnant women who perceived that they had complications and did not have a straight forward pregnancy are likely to experience poorer cardiovascular outcomes 21 years after the pregnancy.

Re-framing infrastructure investment decision-making processes : a preliminary scoping study for urban flood risk management in Jakarta, Indonesia

Jakarta, Indonesia’s chronic housing shortage poses multiple challenges for contemporary policy-makers. While it may be in the city’s interest to increase the availability of housing, there is limited land to do so. Market pressures, in tandem with government’s desire for housing availability, demand consideration of even marginal lands, such as those within floodplains, for development. Increasingly, planning for a flood resilient Jakarta is complicated by a number of factors, including: the city is highly urbanized and land use data is limited; flood management is technically complex, creating potential barriers to engagement for both decision-makers and the public; inherent uncertainty exists throughout modelling efforts, central to management; and risk and liability for infrastructure investments is unclear. These obstacles require localized watershed-level participatory planning to address risks of flooding where possible and reduce the likelihood that informal settlements occur in areas of extreme risk. This paper presents a preliminary scoping study for determination of an effective participatory planning method to encourage more resilient development. First, the scoping study provides background relevant to the challenges faced in planning for contemporary Jakarta. Second, the study examines the current use of decision-support tools, such as Geographic Information Systems (GIS), in planning for Jakarta. Existing capacity in the use of GIS allows for consideration of the use of an emerging method of community consultation - Multi-Criteria Decision-Making (MCDM) support systems infused with geospatial information - to aid in engagement with the public and improve decision-making outcomes. While these methods have been used in Australia to promote stakeholder engagement in urban intensification, the planned research will be an early introduction of the method to Indonesia. As a consequence of this intervention, it is expected that planning activities will result in a more resilient city, capable of engaging with disaster risk management in a more effective manner.

Letter : anxiety score as a risk factor for radial artery vasospasm during radial interventions : a pilot study

I read with interest the article in Angiology that determined the role of anxiety level on radial artery spasm during transradial coronary angiography.1 As the importance of conducting more randomised controlled trials using anxiolytics to define the relation between anxiety and vasospasm was noted by the authors, I offer the following insights for investigators to consider when conducting such research. While previous research has already identified that moderate procedural sedation and opioid analgesia reduces the incidence of vasospasm,2 the identification of risk factors in the present study is hypothesis generating as to how outcomes might be even further improved. It is possible that selectively applying either even more intensive sedation and analgesia or complementary non-pharmacological stress-reducing therapies, such as music therapy or visualisation and attentive behaviour, to patients ‘at-risk’ of vasospasm (women and those with high levels of anxiety prior to the procedure) might lead to even better patient outcomes...

Universal active and reactive power control of electronically interfaced distributed generation sources in virtual power plants operating in gridconnected and islanding modes

The control paradigms of the distributed generation (DG) sources in the smart grid are realised by either utilising virtual power plant (VPP) or by employing MicroGrid structures. Both VPP and MicroGrid are presented with the problem of control of power flow between their comprising DG sources. This study depicts this issue for VPP and proposes a novel and improved universal active and reactive power flow controllers for three-phase pulse width modulated voltage source inverters (PWM-VSI) operating in the VPP environment. The proposed controller takes into account all cases of R-X relationship, thus allowing it to function in systems operating at high, medium (MV) and low-voltage (LV) levels. Also proposed control scheme for the first time in an inverter control takes into account the capacitance of the transmission line which is an important factor to accurately represent medium length transmission lines. This allows the proposed control scheme to be applied in VPP structures, where DG sources can operate at MV LV levels over a short/medium length transmission line. The authors also conducted small signal stability analysis of the proposed controller and compared it against the small signal study of the existing controllers.

A data mining driven crash risk profiling method for road asset management

This thesis takes a new data mining approach for analyzing road/crash data by developing models for the whole road network and generating a crash risk profile. Roads with an elevated crash risk due to road surface friction deficit are identified. The regression tree model, predicting road segment crash rate, is applied in a novel deployment coined regression tree extrapolation that produces a skid resistance/crash rate curve. Using extrapolation allows the method to be applied across the network and cope with the high proportion of missing road surface friction values. This risk profiling method can be applied in other domains.

A multi-objective optimization approach for coordinating available transfer capability with risk control

In the electricity market environment, coordination of system reliability and economics of a power system is of great significance in determining the available transfer capability (ATC). In addition, the risks associated with uncertainties should be properly addressed in the ATC determination process for risk-benefit maximization. Against this background, it is necessary that the ATC be optimally allocated and utilized within relative security constraints. First of all, the non-sequential Monte Carlo stimulation is employed to derive the probability density distribution of ATC of designated areas incorporating uncertainty factors. Second, on the basis of that, a multi-objective optimization model is formulated to determine the multi-area ATC so as to maximize the risk-benefits. Then, the solution to the developed model is achieved by the fast non-dominated sorting (NSGA-II) algorithm, which could decrease the risk caused by uncertainties while coordinating the ATCs of different areas. Finally, the IEEE 118-bus test system is served for demonstrating the essential features of the developed model and employed algorithm.

Reducing the Risk of Alcohol and Other Drugs in Construction : An Australian Assessment

There is increasing concern about the impact of employees’ alcohol and other drug (AOD) consumption on workplace safety, particularly within the construction industry. No known study has scientifically evaluated the relationship between the use of drugs and alcohol and safety impacts in construction, and there has been only limited adoption of nationally coordinated strategies, supported by employers and employees to render it socially unacceptable to arrive at a construction workplace with impaired judgment from AODs. This research aims to scientifically evaluate the use of AODs within the Australian construction industry in order to reduce the potential resulting safety and performance impacts and engender a cultural change in the workforce. Using the Alcohol Use Disorders Identification Test (AUDIT), the study will adopt both quantitative and qualitative methods to evaluate the extent of general AOD use in the industry. Results indicate that a proportion of the construction sector may be at risk of hazardous alcohol consumption. A total of 286 respondents (58%) scored above the cut-off score for risky alcohol use with 43 respondents (15%) scoring in the significantly ‘at risk’ category. Other drug use was also identified as a major issue that must be addressed. Results support the need for evidence-based, preventative educational initiatives that are tailored specifically to the construction industry.

Towards engaged consumption : new sources of inspiration for eco-feedback design

Eco-feedback interventions are capable of producing reductions in household energy consumption. Yet less is known about exactly how this reduction is achieved, how to maximise user engagement, or how to effectively translate engagement into energy saving. This paper discusses design opportunities for eco-feedback systems through observations of domestic energy use in both Western and rural developing world contexts. Drawing on case studies from these two contexts including 21 empirical interviews, we present an alternative framework for human-resource interaction, highlighting design opportunities for a transition towards more engaged and sustainable energy consumption among users.

Segmentation of cone-beam CT using a hidden Markov random field with informative priors

Purpose: Flat-detector, cone-beam computed tomography (CBCT) has enormous potential to improve the accuracy of treatment delivery in image-guided radiotherapy (IGRT). To assist radiotherapists in interpreting these images, we use a Bayesian statistical model to label each voxel according to its tissue type. Methods: The rich sources of prior information in IGRT are incorporated into a hidden Markov random field (MRF) model of the 3D image lattice. Tissue densities in the reference CT scan are estimated using inverse regression and then rescaled to approximate the corresponding CBCT intensity values. The treatment planning contours are combined with published studies of physiological variability to produce a spatial prior distribution for changes in the size, shape and position of the tumour volume and organs at risk (OAR). The voxel labels are estimated using the iterated conditional modes (ICM) algorithm. Results: The accuracy of the method has been evaluated using 27 CBCT scans of an electron density phantom (CIRS, Inc. model 062). The mean voxel-wise misclassification rate was 6.2%, with Dice similarity coefficient of 0.73 for liver, muscle, breast and adipose tissue. Conclusions: By incorporating prior information, we are able to successfully segment CBCT images. This could be a viable approach for automated, online image analysis in radiotherapy.

A data mining driven risk profiling method for road asset management

Road surface skid resistance has been shown to have a strong relationship to road crash risk, however, applying the current method of using investigatory levels to identify crash prone roads is problematic as they may fail in identifying risky roads outside of the norm. The proposed method analyses a complex and formerly impenetrable volume of data from roads and crashes using data mining. This method rapidly identifies roads with elevated crash-rate, potentially due to skid resistance deficit, for investigation. A hypothetical skid resistance/crash risk curve is developed for each road segment, driven by the model deployed in a novel regression tree extrapolation method. The method potentially solves the problem of missing skid resistance values which occurs during network-wide crash analysis, and allows risk assessment of the major proportion of roads without skid resistance values.