ACE research vignette 029 : Can entrepreneurship be taught?

This series of research vignettes is aimed at sharing current and interesting research findings from our team of international Entrepreneurship researchers. This vignette, written by Professor Per Davidsson, examines the evidence on whether entrepreneurship education and training leads to more entrepreneurial action and success.

Final : report assessing risk and variation in maintenance and rehabilitation costs for road network

This report presents the results of research projects conducted by The Australian Cooperative Research Centre for Construction Innovation, Queensland University of Technology, RMIT University, Queensland Government Department of Main Roads and Queensland Department of Public Works. The research projects aimed at developing a methodology for assessing variation and risk in investment in road network, including the application of the method in assessing road network performance and maintenance and rehabilitation costs for short- and long-term future investment.

Report : review of the literature : maintenance and rehabilitation costs for roads (Risk-based Analysis)

Realistic estimates of short- and long-term (strategic) budgets for maintenance and rehabilitation of road assessment management should consider the stochastic characteristics of asset conditions of the road networks so that the overall variability of road asset data conditions is taken into account. The probability theory has been used for assessing life-cycle costs for bridge infrastructures by Kong and Frangopol (2003), Zayed et.al. (2002), Kong and Frangopol (2003), Liu and Frangopol (2004), Noortwijk and Frangopol (2004), Novick (1993). Salem 2003 cited the importance of the collection and analysis of existing data on total costs for all life-cycle phases of existing infrastructure, including bridges, road etc., and the use of realistic methods for calculating the probable useful life of these infrastructures (Salem et. al. 2003). Zayed et. al. (2002) reported conflicting results in life-cycle cost analysis using deterministic and stochastic methods. Frangopol et. al. 2001 suggested that additional research was required to develop better life-cycle models and tools to quantify risks, and benefits associated with infrastructures. It is evident from the review of the literature that there is very limited information on the methodology that uses the stochastic characteristics of asset condition data for assessing budgets/costs for road maintenance and rehabilitation (Abaza 2002, Salem et. al. 2003, Zhao, et. al. 2004). Due to this limited information in the research literature, this report will describe and summarise the methodologies presented by each publication and also suggest a methodology for the current research project funded under the Cooperative Research Centre for Construction Innovation CRC CI project no 2003-029-C.

Report : development of a methodology for assessing variation in maintenance and rehabilitation costs

In the previous research CRC CI 2001-010-C “Investment Decision Framework for Infrastructure Asset Management”, a method for assessing variation in cost estimates for road maintenance and rehabilitation was developed. The variability of pavement strength collected from a 92km national highway was used in the analysis to demonstrate the concept. Further analysis was conducted to identify critical input parameters that significantly affect the prediction of road deterioration. In addition to pavement strength, rut depth, annual traffic loading and initial roughness were found to be critical input parameters for road deterioration. This report presents a method developed to incorporate other critical parameters in the analysis, such as unit costs, which are suspected to contribute to a certain degree to cost estimate variation. Thus, the variability of unit costs will be incorporated in this analysis. Bruce Highway located in the tropical east coast of Queensland has been identified to be the network for the analysis. This report presents a step by step methodology for assessing variation in road maintenance and rehabilitation cost estimates.

Report : stochastic analysis of road asset data for maintenance cost prediction

Reliable budget/cost estimates for road maintenance and rehabilitation are subjected to uncertainties and variability in road asset condition and characteristics of road users. The CRC CI research project 2003-029-C ‘Maintenance Cost Prediction for Road’ developed a method for assessing variation and reliability in budget/cost estimates for road maintenance and rehabilitation. The method is based on probability-based reliable theory and statistical method. The next stage of the current project is to apply the developed method to predict maintenance/rehabilitation budgets/costs of large networks for strategic investment. The first task is to assess the variability of road data. This report presents initial results of the analysis in assessing the variability of road data. A case study of the analysis for dry non reactive soil is presented to demonstrate the concept in analysing the variability of road data for large road networks. In assessing the variability of road data, large road networks were categorised into categories with common characteristics according to soil and climatic conditions, pavement conditions, pavement types, surface types and annual average daily traffic. The probability distributions, statistical means, and standard deviation values of asset conditions and annual average daily traffic for each type were quantified. The probability distributions and the statistical information obtained in this analysis will be used to asset the variation and reliability in budget/cost estimates in later stage. Generally, we usually used mean values of asset data of each category as input values for investment analysis. The variability of asset data in each category is not taken into account. This analysis method demonstrated that it can be used for practical application taking into account the variability of road data in analysing large road networks for maintenance/rehabilitation investment analysis.

Identification of critical input variables for risk-based cost estimates for road maintenance and rehabilitation

An estimation of costs for maintenance and rehabilitation is subject to variation due to the uncertainties of input parameters. This paper presents the results of an analysis to identify input parameters that affect the prediction of variation in road deterioration. Road data obtained from 1688 km of a national highway located in the tropical northeast of Queensland in Australia were used in the analysis. Data were analysed using a probability-based method, the Monte Carlo simulation technique and HDM-4’s roughness prediction model. The results of the analysis indicated that among the input parameters the variability of pavement strength, rut depth, annual equivalent axle load and initial roughness affected the variability of the predicted roughness. The second part of the paper presents an analysis to assess the variation in cost estimates due to the variability of the overall identified critical input parameters.

On-road ultrafine particle concentration in the M5 East road tunnel, Sydney, Australia

The human health effects following exposure to ultrafine (<100nm) particles (UFPs) produced by fuel combustion, while not completely understood, are generally regarded as detrimental. Road tunnels have emerged as locations where maximum exposure to these particles may occur for the vehicle occupants using them. This study aimed to quantify and investigate the determinants of UFP concentrations in the 4km twin-bore (eastbound and westbound) M5 East tunnel in Sydney, Australia. Sampling was undertaken using a condensation particle counter (CPC) mounted in a vehicle traversing both tunnel bores at various times of day from May through July, 2006. Supplementary measurements were conducted in February, 2008. Over three hundred transects of the tunnel were performed, and these were distributed evenly between the bores. Additional comparative measurements were conducted on a mixed route comprising major roads and shorter tunnels, all within Sydney. Individual trip average UFP concentrations in the M5 East tunnel bores ranged from 5.53 × 104 p cm-3 to 5.95 × 106 p cm-3. Data were sorted by hour of capture, and hourly median trip average (HMA) UFP concentrations ranged from 7.81 × 104 p cm-3 to 1.73 × 106 p cm-3. Hourly median UFP concentrations measured on the mixed route were between 3.71 × 104 p cm-3 and 1.55 × 105 p cm-3. Hourly heavy diesel vehicle (HDV) traffic volume was a very good determinant of UFP concentration in the eastbound tunnel bore (R2 = 0.87), but much less so in the westbound bore (R2 = 0.26). In both bores, the volume of passenger vehicles (i.e. unleaded gasoline-powered vehicles) was a significantly poorer determinant of particle concentration. When compared with similar studies reported previously, the measurements described here were among the highest recorded concentrations, which further highlights the contribution road tunnels may make to the overall UFP exposure of vehicle occupants.

Preliminary Results from Exercise for Health : A Breast Cancer Recovery Project [Abstract]

The Exercise for Health program is a telephone-delivered exercise intervention for women with breast cancer (BC) living in regional Queensland. The effect of the program is being evaluated in the context of a randomised controlled trial. Consenting, newly diagnosed BC patients, treated in one of 8 regional Queensland hospitals, were randomly allocated to telephone-based exercise counselling (EC) or usual care (UC) at 6-weeks post-surgery. EC participants received an exercise workbook and 16 calls from an exercise physiologist over 8 months. Physical activity levels (PA) (Active Australia & CHAMPS), quality-of-life (FACTB+4), upper-body function (DASH) and fatigue (FACIT-Fatigue) were assessed at baseline (4-6 weeks post-surgery), 6- and 12-months post-surgery. Preliminary analyses of available 6-month data were conducted using t-tests and repeated measures ANCOVAs. Participating women (n=143; EC n=73, UC n=70) were aged 53±9 years and 30% met PA guidelines at baseline. Up to two thirds of the women received adjuvant therapy during the first 6 months following surgery. Greater improvements (mean change+SD) occurred for the EC vs UC group in weekly sessions of walking (1.83±4.3 vs -0.5±5.5, p=0.029) moderate-vigorous PA (5.0±6.5 vs -1.1±6.1, p=0.005) and strength training (1.9±2.9 vs -0.5±4.2 p<0.001), and in upper-body function, reflected by lower log-transformed disability scores (-0.34±0.44 vs -0.17±0.28, p=0.038). More EC than UC participants met PA guidelines at 6 months (46.3% vs 32.7%). Preliminary findings from this ongoing trial suggest that the telephone is a feasible and effective medium for delivering exercise counselling to newly diagnosed BC patients living in regional areas.

Influences of age and mechanical stability on volume, microstructure, and mineralization of the fracture callus during bone healing : Is osteoclast activity the key to age-related impaired healing?

Earlier studies have shown that the influence of fixation stability on bone healing diminishes with advanced age. The goal of this study was to unravel the relationship between mechanical stimulus and age on callus competence at a tissue level. Using 3D in vitro micro-computed tomography derived metrics, 2D in vivo radiography, and histology, we investigated the influences of age and varying fixation stability on callus size, geometry, microstructure, composition, remodeling, and vascularity. Compared were four groups with a 1.5-mm osteotomy gap in the femora of Sprague–Dawley rats: Young rigid (YR), Young semirigid (YSR), Old rigid (OR), Old semirigid (OSR). Hypothesis was that calcified callus microstructure and composition is impaired due to the influence of advanced age, and these individuals would show a reduced response to fixation stabilities. Semirigid fixations resulted in a larger ΔCSA (Callus cross-sectional area) compared to rigid groups. In vitro μCT analysis at 6 weeks postmortem showed callus bridging scores in younger animals to be superior than their older counterparts (pb0.01). Younger animals showed (i) larger callus strut thickness (pb0.001), (ii) lower perforation in struts (pb0.01), and (iii) higher mineralization of callus struts (pb0.001). Callus mineralization was reduced in young animals with semirigid fracture fixation but remained unaffected in the aged group. While stability had an influence, age showed none on callus size and geometry of callus. With no differences observed in relative osteoid areas in the callus ROI, old as well as semirigid fixated animals showed a higher osteoclast count (pb0.05). Blood vessel density was reduced in animals with semirigid fixation (pb0.05). In conclusion, in vivo monitoring indicated delayed callus maturation in aged individuals. Callus bridging and callus competence (microstructure and mineralization) were impaired in individuals with an advanced age. This matched with increased bone resorption due to higher osteoclast numbers. Varying fixator configurations in older individuals did not alter the dominant effect of advanced age on callus tissue mineralization, unlike in their younger counterparts. Age-associated influences appeared independent from stability. This study illustrates the dominating role of osteoclastic activity in age-related impaired healing, while demonstrating the optimization of fixation parameters such as stiffness appeared to be less effective in influencing healing in aged individuals.

Adaptive Bayesian compound designs for dose finding studies

We consider the problem of how to efficiently and safely design dose finding studies. Both current and novel utility functions are explored using Bayesian adaptive design methodology for the estimation of a maximum tolerated dose (MTD). In particular, we explore widely adopted approaches such as the continual reassessment method and minimizing the variance of the estimate of an MTD. New utility functions are constructed in the Bayesian framework and are evaluated against current approaches. To reduce computing time, importance sampling is implemented to re-weight posterior samples thus avoiding the need to draw samples using Markov chain Monte Carlo techniques. Further, as such studies are generally first-in-man, the safety of patients is paramount. We therefore explore methods for the incorporation of safety considerations into utility functions to ensure that only safe and well-predicted doses are administered. The amalgamation of Bayesian methodology, adaptive design and compound utility functions is termed adaptive Bayesian compound design (ABCD). The performance of this amalgamation of methodology is investigated via the simulation of dose finding studies. The paper concludes with a discussion of results and extensions that could be included into our approach.