Alcohol and other drugs in the Australian construction industry : a pathway for safety focused cultural change

Background: Anecdotal evidence from the infrastructure and building sectors highlights issues of alcohol and other drugs (AODs) and its association with safety risk on construction sites. Currently, there is no clear evidence on the prevalence and risk of AOD use among Australian construction workers and there is limited evidential guidance regarding how to effectively address such an issue. Aims: The current 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. A nationally consistent and collaborative approach across the workforce will be adopted. Methods: A national assessment of the use of AODs was conducted in participating organisations across three states. The World Health Organisation’s Alcohol Use Disorders Identification Test (AUDIT) was used to measure alcohol use. Illicit drug use, ‘readiness to change’, impediments to reducing impairment, feasibility of proposed interventions, and employee attitudes and knowledge regarding AOD was also measured through a combination of survey items and interviews. Through an educative approach and consultation with employers, employees, union groups and leaders in applied AOD research, this assessment was used to inform and support cultural change management of AOD use in the industry. Results: Results (n=494) indicate that as in the general population, a proportion of those sampled in the construction sector may be at risk of hazardous alcohol consumption. A total of 286 respondents (58%) scored above the cut-off cumulative score for risky or hazardous alcohol use. Other drug use was also identified as a major issue. Interview responses and input from all project partners is presented within a guiding principle framework for cultural change. Conclusions: Results support the need for evidence-based, comprehensive and tailored responses in the workplace. This paper will discuss the final results in the context of facilitating cultural change in the construction industry.

The influence of temperature and introduction point on the detection of Rhyzopertha dominica in stored grain

The presence of insect pests in grain storages throughout the supply chain is a significant problem for farmers, grain handlers, and distributors world-wide. Insect monitoring and sampling programmes are used in the stored grains industry for the detection and estimation of pest populations. At the low pest densities dictated by economic and commercial requirements, the accuracy of both detection and abundance estimates can be influenced by variations in the spatial structure of pest populations over short distances. Geostatistical analysis of Rhyzopertha dominica populations in 2 and 3 dimensions showed that insect numbers were positively correlated over short (0.5 cm) distances, and negatively correlated over longer (.10 cm) distances. At 35 C, insects were located significantly further from the grain surface than at 25 and 30 C. Dispersion metrics showed statistically significant aggregation in all cases. The observed heterogeneous spatial distribution of R. dominica may also be influenced by factors such as the site of initial infestation and disturbance during handling. To account for these additional factors, I significantly extended a simulation model that incorporates both pest growth and movement through a typical stored-grain supply chain. By incorporating the effects of abundance, initial infestation site, grain handling, and treatment on pest spatial distribution, I developed a supply chain model incorporating estimates of pest spatial distribution. This was used to examine several scenarios representative of grain movement through a supply chain, and determine the influence of infestation location and grain disturbance on the sampling intensity required to detect pest infestations at various infestation rates. This study has investigated the effects of temperature, infestation point, and grain handling on the spatial distribution and detection of R. dominica. The proportion of grain infested was found to be dependent upon abundance, initial pest location, and grain handling. Simulation modelling indicated that accounting for these factors when developing sampling strategies for stored grain has the potential to significantly reduce sampling costs while simultaneously improving detection rate, resulting in reduced storage and pest management cost while improving grain quality.

Quantitative and qualitative assessment of the regenerative potential of osteoblasts versus bone marrow derived mesenchymal stem cells in the reconstruction of critical sized segmental tibial bone defects in a large animal model

This thesis is about the use of different cells for bone tissue engineering. The cells were used in combination with a novel biomaterial in a large tibial bone defects in a sheep model. Furthermore this study developed a novel cell delivery procedure for bone tissue engineering. This novel procedure of cell delivery could overcome the current problems of cell-based tissue engineering and serve as a baseline for the translation of novel concepts into clinical application.

Prolegomenon to the study of the concepts of maturity and maturity model : from Black Horse to White Knight?

This paper takes its root in a trivial observation: management approaches are unable to provide relevant guidelines to cope with uncertainty, and trust of our modern worlds. Thus, managers are looking for reducing uncertainty through information’s supported decision-making, sustained by ex-ante rationalization. They strive to achieve best possible solution, stability, predictability, and control of “future”. Hence, they turn to a plethora of “prescriptive panaceas”, and “management fads” to bring simple solutions through best practices. However, these solutions are ineffective. They address only one part of a system (e.g. an organization) instead of the whole. They miss the interactions and interdependencies with other parts leading to “suboptimization”. Further classical cause-effects investigations and researches are not very helpful to this regard. Where do we go from there? In this conversation, we want to challenge the assumptions supporting the traditional management approaches and shed some lights on the problem of management discourse fad using the concept of maturity and maturity models in the context of temporary organizations as support for reflexion. Global economy is characterized by use and development of standards and compliance to standards as a practice is said to enable better decision-making by managers in uncertainty, control complexity, and higher performance. Amongst the plethora of standards, organizational maturity and maturity models hold a specific place due to general belief in organizational performance as dependent variable of (business) processes continuous improvement, grounded on a kind of evolutionary metaphor. Our intention is neither to offer a new “evidence based management fad” for practitioners, nor to suggest research gap to scholars. Rather, we want to open an assumption-challenging conversation with regards to main stream approaches (neo-classical economics and organization theory), turning “our eyes away from the blinding light of eternal certitude towards the refracted world of turbid finitude” (Long, 2002, p. 44) generating what Bernstein has named “Cartesian Anxiety” (Bernstein, 1983, p. 18), and revisit the conceptualization of maturity and maturity models. We rely on conventions theory and a systemic-discursive perspective. These two lenses have both information & communication and self-producing systems as common threads. Furthermore the narrative approach is well suited to explore complex way of thinking about organizational phenomena as complex systems. This approach is relevant with our object of curiosity, i.e. the concept of maturity and maturity models, as maturity models (as standards) are discourses and systems of regulations. The main contribution of this conversation is that we suggest moving from a neo-classical “theory of the game” aiming at making the complex world simpler in playing the game, to a “theory of the rules of the game”, aiming at influencing and challenging the rules of the game constitutive of maturity models – conventions, governing systems – making compatible individual calculation and social context, and possible the coordination of relationships and cooperation between agents with or potentially divergent interests and values. A second contribution is the reconceptualization of maturity as structural coupling between conventions, rather than as an independent variable leading to organizational performance.

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.

Econometric Modelling with Time Series : Specification, Estimation and Testing

This book provides a general framework for specifying, estimating, and testing time series econometric models. Special emphasis is given to estimation by maximum likelihood, but other methods are also discussed, including quasi-maximum likelihood estimation, generalized method of moments estimation, nonparametric estimation, and estimation by simulation. An important advantage of adopting the principle of maximum likelihood as the unifying framework for the book is that many of the estimators and test statistics proposed in econometrics can be derived within a likelihood framework, thereby providing a coherent vehicle for understanding their properties and interrelationships. In contrast to many existing econometric textbooks, which deal mainly with the theoretical properties of estimators and test statistics through a theorem-proof presentation, this book squarely addresses implementation to provide direct conduits between the theory and applied work.

Equal employment opportunity and its links to the participation of women in the construction industry : the case of Australia

Australia is currently experiencing a resources boom and jobs in the male dominated fields of construction and engineering are at a premium. Employment in the construction industry, historically and today, is overwhelmingly male and, with an ageing population this predominately older male workforce will be retiring in greater numbers in the coming decade. Despite more that 25 years of anti- discrimination legislation and equal opportunity legislation these industries still employ few women in operational roles. This paper investigates the issue of the low representation of women in the construction industry. Our investigation involves the analysis of 95 organisation progress reports on the equal opportunity strategic programs in the construction industry. Findings indicate that this industry is not engaging with equal employment opportunity programs and further that equity outcomes for women in the industry are not evident.

An Artificial Neutral Network (ANN) model for predicting biodiesel kinetic viscosity as a function of temperature and chemical compositions

An Artificial Neural Network (ANN) is a computational modeling tool which has found extensive acceptance in many disciplines for modeling complex real world problems. An ANN can model problems through learning by example, rather than by fully understanding the detailed characteristics and physics of the system. In the present study, the accuracy and predictive power of an ANN was evaluated in predicting kinetic viscosity of biodiesels over a wide range of temperatures typically encountered in diesel engine operation. In this model, temperature and chemical composition of biodiesel were used as input variables. In order to obtain the necessary data for model development, the chemical composition and temperature dependent fuel properties of ten different types of biodiesels were measured experimentally using laboratory standard testing equipments following internationally recognized testing procedures. The Neural Networks Toolbox of MatLab R2012a software was used to train, validate and simulate the ANN model on a personal computer. The network architecture was optimised following a trial and error method to obtain the best prediction of the kinematic viscosity. The predictive performance of the model was determined by calculating the absolute fraction of variance (R2), root mean squared (RMS) and maximum average error percentage (MAEP) between predicted and experimental results. This study found that ANN is highly accurate in predicting the viscosity of biodiesel and demonstrates the ability of the ANN model to find a meaningful relationship between biodiesel chemical composition and fuel properties at different temperature levels. Therefore the model developed in this study can be a useful tool in accurately predict biodiesel fuel properties instead of undertaking costly and time consuming experimental tests.

Spatially-explicit modelling of grassland classes - an improved method of integrating a climate-based classification model with interpolated climate surfaces

Spatially-explicit modelling of grassland classes is important to site-specific planning for improving grassland and environmental management over large areas. In this study, a climate-based grassland classification model, the Comprehensive and Sequential Classification System (CSCS) was integrated with spatially interpolated climate data to classify grassland in Gansu province, China. The study area is characterized by complex topographic features imposed by plateaus, high mountains, basins and deserts. To improve the quality of the interpolated climate data and the quality of the spatial classification over this complex topography, three linear regression methods, namely an analytic method based on multiple regression and residues (AMMRR), a modification of the AMMRR method through adding the effect of slope and aspect to the interpolation analysis (M-AMMRR) and a method which replaces the IDW approach for residue interpolation in M-AMMRR with an ordinary kriging approach (I-AMMRR), for interpolating climate variables were evaluated. The interpolation outcomes from the best interpolation method were then used in the CSCS model to classify the grassland in the study area. Climate variables interpolated included the annual cumulative temperature and annual total precipitation. The results indicated that the AMMRR and M-AMMRR methods generated acceptable climate surfaces but the best model fit and cross validation result were achieved by the I-AMMRR method. Twenty-six grassland classes were classified for the study area. The four grassland vegetation classes that covered more than half of the total study area were "cool temperate-arid temperate zonal semi-desert", "cool temperate-humid forest steppe and deciduous broad-leaved forest", "temperate-extra-arid temperate zonal desert", and "frigid per-humid rain tundra and alpine meadow". The vegetation classification map generated in this study provides spatial information on the locations and extents of the different grassland classes. This information can be used to facilitate government agencies' decision-making in land-use planning and environmental management, and for vegetation and biodiversity conservation. The information can also be used to assist land managers in the estimation of safe carrying capacities which will help to prevent overgrazing and land degradation.

Design, characterisation and in vivo testing of a new, adjustable stiffness, external fixator for the rat femur

Very little is known about the infl uence of the mechanical environment on the healing of large segmental defects. This partly reflects the lack of standardised, well characterised technologies to enable such studies. Here we report the design, construction and characterisation of a novel external fixator for use in conjunction with rat femoral defects. This device not only imposes a predetermined axial stiffness on the lesion, but also enables the stiffness to be changed during the healing process. The main frame of the fi xator consists of polyethylethylketone with titanium alloy mounting pins. The stiffness of the fi xator is determined by interchangeable connection elements of different thicknesses. Fixators were shown to stabilise 5 mm femoral defects in rats in vivo for at least 8 weeks during unrestricted cage activity. No distortion or infections, including pin infections, were noted. The healing process was simulated in vitro by inserting into a 5 mm femoral defect, materials whose Young’s moduli approximated those of the different tissues present in regenerating bone. These studies confirmed that, although the external fixator is the major determinant of axial stiffness during the early phase of healing, the regenerate within the lesion subsequently dominates this property. There is much clinical interest in altering the mechanics of the defect to enhance bone healing. Our data suggest that, if alteration of the mechanical environment is to be used to modulate the healing of large segmental defects, this needs to be performed before the tissue properties become dominant.

The Interaction of lean and building information modeling in construction

Lean construction and building information modeling (BIM) are quite different initiatives, but both are having profound impacts on the construction industry. A rigorous analysis of the myriad specific interactions between them indicates that a synergy exists which, if properly understood in theoretical terms, can be exploited to improve construction processes beyond the degree to which it might be improved by application of either of these paradigms independently. Using a matrix that juxtaposes BIM functionalities with prescriptive lean construction principles, 56 interactions have been identified, all but four of which represent constructive interaction. Although evidence for the majority of these has been found, the matrix is not considered complete but rather a framework for research to explore the degree of validity of the interactions. Construction executives, managers, designers, and developers of information technology systems for construction can also benefit from the framework as an aid to recognizing the potential synergies when planning their lean and BIM adoption strategies.

CTCombine : rotating and combining CT data with an accurate detector model to simulate radiotherapy portal imaging at non-zero beam angles

Established Monte Carlo user codes BEAMnrc and DOSXYZnrc permit the accurate and straightforward simulation of radiotherapy experiments and treatments delivered from multiple beam angles. However, when an electronic portal imaging detector (EPID) is included in these simulations, treatment delivery from non-zero beam angles becomes problematic. This study introduces CTCombine, a purpose-built code for rotating selected CT data volumes, converting CT numbers to mass densities, combining the results with model EPIDs and writing output in a form which can easily be read and used by the dose calculation code DOSXYZnrc...

Beyond the barriers : road construction safety issues from the office and the roadside

Conceptually, the management of safety at roadworks can be seen in a three level framework. At the regulatory level, roadworks operate at the interface between the work environment, governed by workplace health and safety regulations, and the road environment, which is subject to road traffic regulations and practices. At the organizational level, national, state and local governments plan and purchase road construction and maintenance which are then delivered in-house or tendered out to large construction companies who often subcontract multiple smaller companies to supply services and labor. At the operational level, roadworks are difficult to isolate from the general public, hindering effective occupational health and safety controls. This study, from the State of Queensland, Australia, examines how well this tripartite framework functions. It includes reviews of organizational policy and procedures documents; interviews with 24 subject matter experts from various road construction and maintenance organizations, and on-site interviews with 66 road construction personnel. The study identified several factors influencing the translation of safety policies into practice including the cost of safety measures in the context of competitive tendering, lack of firm evidence of the effectiveness of safety measures, and pressures to minimize disruption to the travelling public.

Assessing uncertainty in pollutant wash-off modelling via model validation

Stormwater pollution is linked to stream ecosystem degradation. In predicting stormwater pollution, various types of modelling techniques are adopted. The accuracy of predictions provided by these models depends on the data quality, appropriate estimation of model parameters, and the validation undertaken. It is well understood that available water quality datasets in urban areas span only relatively short time scales unlike water quantity data, which limits the applicability of the developed models in engineering and ecological assessment of urban waterways. This paper presents the application of leave-one-out (LOO) and Monte Carlo cross validation (MCCV) procedures in a Monte Carlo framework for the validation and estimation of uncertainty associated with pollutant wash-off when models are developed using a limited dataset. It was found that the application of MCCV is likely to result in a more realistic measure of model coefficients than LOO. Most importantly, MCCV and LOO were found to be effective in model validation when dealing with a small sample size which hinders detailed model validation and can undermine the effectiveness of stormwater quality management strategies.

A tag-based personalized item recommendation system using tensor modeling and topic model approaches

This research falls in the area of enhancing the quality of tag-based item recommendation systems. It aims to achieve this by employing a multi-dimensional user profile approach and by analyzing the semantic aspects of tags. Tag-based recommender systems have two characteristics that need to be carefully studied in order to build a reliable system. Firstly, the multi-dimensional correlation, called as tag assignment , should be appropriately modelled in order to create the user profiles [1]. Secondly, the semantics behind the tags should be considered properly as the flexibility with their design can cause semantic problems such as synonymy and polysemy [2]. This research proposes to address these two challenges for building a tag-based item recommendation system by employing tensor modeling as the multi-dimensional user profile approach, and the topic model as the semantic analysis approach. The first objective is to optimize the tensor model reconstruction and to improve the model performance in generating quality rec-ommendation. A novel Tensor-based Recommendation using Probabilistic Ranking (TRPR) method [3] has been developed. Results show this method to be scalable for large datasets and outperforming the benchmarking methods in terms of accuracy. The memory efficient loop implements the n-mode block-striped (matrix) product for tensor reconstruction as an approximation of the initial tensor. The probabilistic ranking calculates the probabil-ity of users to select candidate items using their tag preference list based on the entries generated from the reconstructed tensor. The second objective is to analyse the tag semantics and utilize the outcome in building the tensor model. This research proposes to investigate the problem using topic model approach to keep the tags nature as the “social vocabulary” [4]. For the tag assignment data, topics can be generated from the occurrences of tags given for an item. However there is only limited amount of tags availa-ble to represent items as collection of topics, since an item might have only been tagged by using several tags. Consequently, the generated topics might not able to represent the items appropriately. Furthermore, given that each tag can belong to any topics with various probability scores, the occurrence of tags cannot simply be mapped by the topics to build the tensor model. A standard weighting technique will not appropriately calculate the value of tagging activity since it will define the context of an item using a tag instead of a topic.