Traffic-related fine and ultrafine particle exposures of professional drivers and illness : An opportunity to better link exposure science and epidemiology to address an occupational hazard?

Exposures to traffic-related air pollution (TRAP) can be particularly high in transport microenvironments (i.e. in and around vehicles) despite the short durations typically spent there. There is a mounting body of evidence that suggests that this is especially true for fine (b2.5 μm) and ultrafine (b100 nm, UF) particles. Professional drivers, who spend extended periods of time in transport microenvironments due to their job, may incur exposures markedly higher than already elevated non-occupational exposures. Numerous epidemiological studies have shown a raised incidence of adverse health outcomes among professional drivers, and exposure to TRAP has been suggested as one of the possible causal factors. Despite this, data describing the range and determinants of occupational exposures to fine and UF particles are largely conspicuous in their absence. Such information could strengthen attempts to define the aetiology of professional drivers' illnesses as it relates to traffic combustion-derived particles. In this article, we suggest that the drivers' occupational fine and UF particle exposures are an exemplar case where opportunities exist to better link exposure science and epidemiology in addressing questions of causality. The nature of the hazard is first introduced, followed by an overview of the health effects attributable to exposures typical of transport microenvironments. Basic determinants of exposure and reduction strategies are also described, and finally the state of knowledge is briefly summarised along with an outline of the main unanswered questions in the topic area.

Increasing disaster resilience of people and property through fostering collaboration in coastal high hazard zones

As evidenced with the 2011 floods the state of Queensland in Australia is quite vulnerable to this kind of disaster. Climate change will increase the frequency and magnitude of such events and will have a variety of other impacts. To deal with these governments at all levels need to be prepared and work together. Since most of the population of the state is located in the coastal areas and these areas are more vulnerable to the impacts of climate change this paper examines climate change adaptation efforts in coastal Queensland. The paper is part of a more comprehensive project which looks at the critical linkages between land use and transport planning in coastal Queensland, especially in light of increased frequencies of cyclonic activity and other impacts associated with climate change. The aim is improving coordination between local and state government in addressing land use and transport planning in coastal high hazard areas. By increasing the ability of local governments and state agencies to coordinate planning activities, we can help adapt to impacts of climate change. Towards that end, we will look at the ways that these groups currently interact, especially with regard to issues involving uncertainty related to climate change impacts. Through surveys and interviews of Queensland coastal local governments and state level planning agencies on how they coordinate their planning activities at different levels as well as how much they take into account the linkage of transportation and land use we aim to identify the weaknesses of the current planning system in responding to the challenges of climate change adaptation. The project will identify opportunities for improving the ways we plan and coordinate planning, and make recommendations to improve resilience in advance of disasters so as to help speed up recovery when they occur.

The effect of injury diagnosis on expected Postconcussion Syndrome (PCS) symptom reporting and illness perception

Objective: To determine if systematic variation of diagnostic terminology (i.e. concussion, minor head injury [MHI], mild traumatic brain injury [mTBI]) following a standardized injury description produced different expected symptoms and illness perceptions. We hypothesized that worse outcomes would be expected of mTBI, compared to other diagnoses, and that MHI would be perceived as worse than concussion. Method:108 volunteers were randomly allocated to conditions in which they read a vignette describing a motor vehicle accident-related mTBI followed by: a diagnosis of mTBI (n=27), MHI (n=24), concussion (n=31); or, no diagnosis (n=26). All groups rated: a) event ‘undesirability’; b) illness perception, and; c) expected Postconcussion Syndrome (PCS) and Posttraumatic Stress Disorder (PTSD) symptoms six months post injury. Results: On average, more PCS symptomatology was expected following mTBI compared to other diagnoses, but this difference was not statistically significant. There was a statistically significant group effect on undesirability (mTBI>concussion & MHI), PTSD symptomatology (mTBI & no diagnosis>concussion), and negative illness perception (mTBI & no diagnosis>concussion). Conclusion: In general, diagnostic terminology did not affect anticipated PCS symptoms six months post injury, but other outcomes were affected. Given that these diagnostic terms are used interchangeably, this study suggests that changing terminology can influence known contributors to poor mTBI outcome.

The prevalence and perception of pain amongst hospital in-patients

The aim of this paper is to describe the prevalence and perceptions of pain and pain management amongst hospital in-patients. A cross-sectional descriptive survey of 205 patients was conducted. Presence and severity of pain was assessed using verbal descriptor and visual analogue scales, and perceptions of pain were assessed using multi-item scales. Although the severity of pain reported was consistent across age groups and clinical areas, women in the study sample were significantly more likely to report high levels of pain than men. Differences in how men and women communicate their pain were observed, with women indicating that they were less willing to ask for help with their pain. Results suggest that pain continues to be an important problem for a large number of men and women in hospital, and that the experience of pain impacts negatively upon their well-being. Gender differences in the experience of and response to pain remain important considerations for clinical nurses who have major responsibilities for the management of pain in hospitalized patients.

Asset health prediction using the explicit hazard model

The ability to estimate the asset reliability and the probability of failure is critical to reducing maintenance costs, operation downtime, and safety hazards. Predicting the survival time and the probability of failure in future time is an indispensable requirement in prognostics and asset health management. In traditional reliability models, the lifetime of an asset is estimated using failure event data, alone; however, statistically sufficient failure event data are often difficult to attain in real-life situations due to poor data management, effective preventive maintenance, and the small population of identical assets in use. Condition indicators and operating environment indicators are two types of covariate data that are normally obtained in addition to failure event and suspended data. These data contain significant information about the state and health of an asset. Condition indicators reflect the level of degradation of assets while operating environment indicators accelerate or decelerate the lifetime of assets. When these data are available, an alternative approach to the traditional reliability analysis is the modelling of condition indicators and operating environment indicators and their failure-generating mechanisms using a covariate-based hazard model. The literature review indicates that a number of covariate-based hazard models have been developed. All of these existing covariate-based hazard models were developed based on the principle theory of the Proportional Hazard Model (PHM). However, most of these models have not attracted much attention in the field of machinery prognostics. Moreover, due to the prominence of PHM, attempts at developing alternative models, to some extent, have been stifled, although a number of alternative models to PHM have been suggested. The existing covariate-based hazard models neglect to fully utilise three types of asset health information (including failure event data (i.e. observed and/or suspended), condition data, and operating environment data) into a model to have more effective hazard and reliability predictions. In addition, current research shows that condition indicators and operating environment indicators have different characteristics and they are non-homogeneous covariate data. Condition indicators act as response variables (or dependent variables) whereas operating environment indicators act as explanatory variables (or independent variables). However, these non-homogenous covariate data were modelled in the same way for hazard prediction in the existing covariate-based hazard models. The related and yet more imperative question is how both of these indicators should be effectively modelled and integrated into the covariate-based hazard model. This work presents a new approach for addressing the aforementioned challenges. The new covariate-based hazard model, which termed as Explicit Hazard Model (EHM), explicitly and effectively incorporates all three available asset health information into the modelling of hazard and reliability predictions and also drives the relationship between actual asset health and condition measurements as well as operating environment measurements. The theoretical development of the model and its parameter estimation method are demonstrated in this work. EHM assumes that the baseline hazard is a function of the both time and condition indicators. Condition indicators provide information about the health condition of an asset; therefore they update and reform the baseline hazard of EHM according to the health state of asset at given time t. Some examples of condition indicators are the vibration of rotating machinery, the level of metal particles in engine oil analysis, and wear in a component, to name but a few. Operating environment indicators in this model are failure accelerators and/or decelerators that are included in the covariate function of EHM and may increase or decrease the value of the hazard from the baseline hazard. These indicators caused by the environment in which an asset operates, and that have not been explicitly identified by the condition indicators (e.g. Loads, environmental stresses, and other dynamically changing environment factors). While the effects of operating environment indicators could be nought in EHM; condition indicators could emerge because these indicators are observed and measured as long as an asset is operational and survived. EHM has several advantages over the existing covariate-based hazard models. One is this model utilises three different sources of asset health data (i.e. population characteristics, condition indicators, and operating environment indicators) to effectively predict hazard and reliability. Another is that EHM explicitly investigates the relationship between condition and operating environment indicators associated with the hazard of an asset. Furthermore, the proportionality assumption, which most of the covariate-based hazard models suffer from it, does not exist in EHM. According to the sample size of failure/suspension times, EHM is extended into two forms: semi-parametric and non-parametric. The semi-parametric EHM assumes a specified lifetime distribution (i.e. Weibull distribution) in the form of the baseline hazard. However, for more industry applications, due to sparse failure event data of assets, the analysis of such data often involves complex distributional shapes about which little is known. Therefore, to avoid the restrictive assumption of the semi-parametric EHM about assuming a specified lifetime distribution for failure event histories, the non-parametric EHM, which is a distribution free model, has been developed. The development of EHM into two forms is another merit of the model. A case study was conducted using laboratory experiment data to validate the practicality of the both semi-parametric and non-parametric EHMs. The performance of the newly-developed models is appraised using the comparison amongst the estimated results of these models and the other existing covariate-based hazard models. The comparison results demonstrated that both the semi-parametric and non-parametric EHMs outperform the existing covariate-based hazard models. Future research directions regarding to the new parameter estimation method in the case of time-dependent effects of covariates and missing data, application of EHM in both repairable and non-repairable systems using field data, and a decision support model in which linked to the estimated reliability results, are also identified.

Active text perception for mobile robots

Our everyday environment is full of text but this rich source of information remains largely inaccessible to mobile robots. In this paper we describe an active text spotting system that uses a small number of wide angle views to locate putative text in the environment and then foveates and zooms onto that text in order to improve the reliability of text recognition. We present extensive experimental results obtained with a pan/tilt/zoom camera and a ROS-based mobile robot operating in an indoor environment.

Hazard based models for freeway traffic incident duration

Assessing and prioritising cost-effective strategies to mitigate the impacts of traffic incidents and accidents on non-recurrent congestion on major roads represents a significant challenge for road network managers. This research examines the influence of numerous factors associated with incidents of various types on their duration. It presents a comprehensive traffic incident data mining and analysis by developing an incident duration model based on twelve months of incident data obtained from the Australian freeway network. Parametric accelerated failure time (AFT) survival models of incident duration were developed, including log-logistic, lognormal, and Weibul-considering both fixed and random parameters, as well as a Weibull model with gamma heterogeneity. The Weibull AFT models with random parameters were appropriate for modelling incident duration arising from crashes and hazards. A Weibull model with gamma heterogeneity was most suitable for modelling incident duration of stationary vehicles. Significant variables affecting incident duration include characteristics of the incidents (severity, type, towing requirements, etc.), and location, time of day, and traffic characteristics of the incident. Moreover, the findings reveal no significant effects of infrastructure and weather on incident duration. A significant and unique contribution of this paper is that the durations of each type of incident are uniquely different and respond to different factors. The results of this study are useful for traffic incident management agencies to implement strategies to reduce incident duration, leading to reduced congestion, secondary incidents, and the associated human and economic losses.

Perception of Brownfield Sites : Myth or Reality?

The scarcity of large parcels of land in well-serviced areas is one motivator for redeveloping industrial or commercial property that is abandoned or underused and often environmentally contaminated – so-called brownfield land. Poor industrial waste disposal practices caused by industrial activities including gas works, factories, railway land and waste tips have contributed to many instances of contaminated land identified as brownfield sites. It is estimated there are between 10,000 and 160,000 brownfield sites in Australia, with Queensland accounting for around 4000 of these.

Principals, Teachers, and Student's Perception of the Information and Communication Technology in Kuwait Secondary Schools (Rhetoric and reality)

ICT integration has been advocated to provide opportunities to improve students’ achievement and engagement through transforming the educational setting. A valuable tool that contributes in enhancing and developing students’ cognitive skills for lifelong learning, ICT integration has introduced a new educational philosophy, shifting the role of students into a more central position in the pedagogical processes. Kuwait, as with many other countries, has recently planned ICT integration to develop its citizen’s capacities. This study sought to capture the principals’, teachers’, and students’ perceptions of ICT integration in pedagogical activities, as well as how ICT is being used for learning and teaching activities in three ICT leading Kuwaiti secondary schools. Interviews with principals, teachers, and students were conducted, along with an open-ended questionnaire for the teachers, researcher observations, and document analysis. The findings revealed that ICT integration in Kuwait needed to be reinforced to accomplish the ICT integration objectives. A call for further support for teachers, and a reconsideration of the ICT integration strategies were also recommended.

Assessing the overuse of antibiotics in children with URTIs in Saudi Arabia : development of the parental perception on antibiotics scale (PAPA scale)

Background: Antibiotic overuse is influenced by several factors that can only be measured using a valid and reliable psychosocial measurement instrument. This study aims to establish translation and early stage validation of an instrument recently developed by this research team to measure factors influencing the overuse of antibiotics in children with upper respiratory tract infections in Saudi Arabia. Method: The content evaluation panel was composed of area experts approached using the Delphi Technique. Experts were provided with the questionnaires iteratively, on a three-round basis until consensus on the relevance of items was reached independently. Translation was achieved by adapting Brislin’s model of translation. Results: After going through the iterative process with the experts, consensus was reached to 58 items (including demographics). Experts also pointed out some issues related to ambiguity and redundancy in some items. A final Arabic version was produced from the translation process. Conclusion: This study produced preliminary validation of the developed instrument from the experts’ contributions. Then, the instrument was translated from English to Arabic. The instrument will undergo further validation steps in the future, such as construct validity.

Assessing the overuse of antibiotics in children in Saudi Arabia : validation of the parental perception on antibiotics scale (PAPA scale)

Background Antibiotics overuse is a global public health issue influenced by several factors, of which some are parent-related psychosocial factors that can only be measured using valid and reliable psychosocial measurement instruments. The PAPA scale was developed to measure these factors and the content validity of this instrument was assessed. Aim This study further validated the recently developed instrument in terms of (1) face validity and (2) construct validity including: deciding the number and nature of factors, and item selection. Methods Questionnaires were self-administered to parents of children between the ages of 0 and 12 years old. Parents were conveniently recruited from schools’ parental meetings in the Eastern Province, Saudi Arabia. Face validity was assessed with regards to questionnaire clarity and unambiguity. Construct validity and item selection processes were conducted using Exploratory factor analysis. Results Parallel analysis and Exploratory factor analysis using principal axis factoring produced six factors in the developed instrument: knowledge and beliefs, behaviours, sources of information, adherence, awareness about antibiotics resistance, and parents’ perception regarding doctors’ prescribing behaviours. Reliability was assessed (Cronbach’s alpha = 0.78) which demonstrates the instrument as being reliable. Conclusion The ‘factors’ produced in this study coincide with the constructs contextually identified in the development phase of other instruments used to study antibiotic use. However, no other study considering perceptions of antibiotic use had gone beyond content validation of such instruments. This study is the first to constructively validate the factors underlying perceptions regarding antibiotic use in any population and in parents in particular.

Regional characteristics, opportunity perception and entrepreneurial activities

This paper seeks to better understand the link between regional characteristics and individual entrepreneurship. We combine individual-level GEM data for Western Germany with regional-level data, using multi-level analysis to test our hypotheses. We find no direct link between regional knowledge creation, the economic context and an entrepreneurial culture on the one side and individual business start-up intentions and start-up activity on the other side. However our findings point to the importance of an indirect effect of regional characteristics as knowledge creation, the economic context and an entrepreneurial culture have an effect on the individual perception of founding opportunities which in turn predicted start-up intentions and activity.

The impact of legislation on divorce : a hazard function approach

The paper examines the impact of the introduction of no-fault divorce legislation in Australia. The approach used is rather novel, a hazard model of the divorce rate is estimated with the role of legislation captured via a time-varying covariate. The paper concludes that contrary to US empirical evidence, no-fault divorce legislation appears to have had a positive impact upon the divorce rate in Australia.