Pipeline renewal decision support : a case study using LinEAR in a water pipeline network

This paper presents a case study for the application of a Linear Engineering Asset Renewal decision support software tool (LinEAR) at a water distribution network in Australia. This case study examines how the LinEAR can assist water utilities to minimise their total pipeline management cost, to make a long-term budget based on mathematically predicted expenditure, and to present calculated evidence for supporting their expenditure requirements. The outcomes from the study on pipeline renewal decision support demonstrate that LinEAR can help water utilities to improve the decision process and save renewal costs over a long-term by providing an optimum renewal schedules. This software can help organisation to accumulate technical knowledge and prediction future impact of the decision using what-if analysis.

A non-linear interface element model for thin layer high adhesive mortared masonry

A nonlinear interface element modelling method is formulated for the prediction of deformation and failure of high adhesive thin layer polymer mortared masonry exhibiting failure of units and mortar. Plastic flow vectors are explicitly integrated within the implicit finite element framework instead of relying on predictor–corrector like approaches. The method is calibrated using experimental data from uniaxial compression, shear triplet and flexural beam tests. The model is validated using a thin layer mortared masonry shear wall, whose experimental datasets are reported in the literature and is used to examine the behaviour of thin layer mortared masonry under biaxial loading.

Rapid analysis of GSTM1, GSTT1 and GSTP1 polymorphisms using real-time polymerase chain reaction

Polymorphisms of glutathione transferases (GST) are important genetic determinants of susceptibility to environmental carcinogens (Rebbeck, 1997). The GSTs are a multigene family of dimeric enzymes involved in detoxification, and, in a few cases, the bioactivation of a variety of xenobiotics (Hayes et al., 1995). The cytosolic GST enzyme family consists of four major classes of enzymes, referred to as alpha, mu, pi and theta. Several members of this family (for example, GSTM1, GSTT1 and GSTP1) are polymorphic in human populations (Wormhoudt et al., 1999). Molecular epidemiology studies have examined the role of GST polymorphisms as susceptibility factors for environmentally and/or occupationally induced cancers (Wormhoudt et al., 1999). In particular, case-control studies showed a relationship between the GSTM1 null genotype and the development of cancer in association with smoking habits, which has been shown for cancers of the respiratory and gastrointestinal tracts as well as other cancer types (Miller et al., 1997). Only a few molecular epidemiological studies addressed the role of GSTT1 and GSTP1 polymorphisms in cancer susceptibility. Since GSTP1 is a key player in biotransformation/bioactivation of benzo(a)pyrene, GSTP1 may be even more important than GSTM1 in the prevention of tobacco-induced cancers (Harries et al., 1997; Harris et al., 1998). To date, this relationship has not been sufficiently addressed in humans. Comprehensive molecular epidemiological studies may add to the current knowledge of the role of GST polymorphisms in cancer susceptibility and extent of the knowledge gained from approaches that used phenotyping, such as GSTM1 activity as it relates to trans-stilbene oxide, or polymerase chain reaction (PCR) based genotyping of polymorphic isoenzymes (Bell et al., 1993; Pemble et al., 1994; Harries et al., 1997).

Supply chain regulation to protect the occupational health and safety of vulnerable workers

The last two decades have witnessed a fragmentation of previously integrated systems of production and service delivery with the advent of boundary-less, networked and porous organisational forms. This trend has been associated with the growth of outsourcing and increased use of contingent workers. One consequence of these changes is the development of production/service delivery systems based on complex national and international networks of multi-tiered subcontracting increasingly labelled as supply chains. A growing body of research indicates that subcontracting and contingent work arrangements affect design and decision-making processes in ways that can seriously undermine occupational health and safety (OHS). Elaborate supply chains also present a regulatory challenge because legal responsibility for OHS is diffused amongst a wider array of parties, targeting key decision-makers is more difficult, and government agencies encounter greater logistical difficulties trying to safeguard contingent workers. In a number of industries these problems have prompted new forms of regulatory intervention, including mechanisms for sheeting legal responsibility to the top of supply chains, contractual tracking devices and increasing industry, union and community involvement in enforcement. After describing the problems just alluded to this paper examines recent efforts to regulate supply chains to safeguard OHS in the United Kingdom and Australia.

Thrust allocation with linear constrained quadratic cost function

In this paper, a method of thrust allocation based on a linearly constrained quadratic cost function capable of handling rotating azimuths is presented. The problem formulation accounts for magnitude and rate constraints on both thruster forces and azimuth angles. The advantage of this formulation is that the solution can be found with a finite number of iterations for each time step. Experiments with a model ship are used to validate the thrust allocation system.

kmth price sealed-bid auctions with general independent values and equilibrium linear mark-ups

A generalised bidding model is developed to calculate a bidder’s expected profit and auctioners expected revenue/payment for both a General Independent Value and Independent Private Value (IPV) kmth price sealed-bid auction (where the mth bidder wins at the kth bid payment) using a linear (affine) mark-up function. The Common Value (CV) assumption, and highbid and lowbid symmetric and asymmetric First Price Auctions and Second Price Auctions are included as special cases. The optimal n bidder symmetric analytical results are then provided for the uniform IPV and CV models in equilibrium. Final comments concern implications, the assumptions involved and prospects for further research.

Understanding Uncertainties in Non-Linear Population Trajectories: A Bayesian Semi-Parametric Hierarchical Approach to Large-Scale Surveys of Coral Cover

Recently, attempts to improve decision making in species management have focussed on uncertainties associated with modelling temporal fluctuations in populations. Reducing model uncertainty is challenging; while larger samples improve estimation of species trajectories and reduce statistical errors, they typically amplify variability in observed trajectories. In particular, traditional modelling approaches aimed at estimating population trajectories usually do not account well for nonlinearities and uncertainties associated with multi-scale observations characteristic of large spatio-temporal surveys. We present a Bayesian semi-parametric hierarchical model for simultaneously quantifying uncertainties associated with model structure and parameters, and scale-specific variability over time. We estimate uncertainty across a four-tiered spatial hierarchy of coral cover from the Great Barrier Reef. Coral variability is well described; however, our results show that, in the absence of additional model specifications, conclusions regarding coral trajectories become highly uncertain when considering multiple reefs, suggesting that management should focus more at the scale of individual reefs. The approach presented facilitates the description and estimation of population trajectories and associated uncertainties when variability cannot be attributed to specific causes and origins. We argue that our model can unlock value contained in large-scale datasets, provide guidance for understanding sources of uncertainty, and support better informed decision making

Strategic supply chain management factors influencing agribusiness innovation utilization

Purpose – The purpose of this paper is to examine empirically, an industry development paradox, using embryonic literature in the area of strategic supply chain management, together with innovation management literature. This study seeks to understand how, forming strategic supply chain relationships, and developing strategic supply chain capability, influences beneficial supply chain outcomes expected from utilizing industry-led innovation, in the form of electronic business solutions using the internet, in the Australian beef industry. Findings should add valuable insights to both academics and practitioners in the fields of supply chain innovation management and strategic supply chain management, and expand knowledge to current literature. Design/methodology/approach – This is a quantitative study comparing innovative and non-innovative supply chain operatives in the Australian beef industry, through factor analysis and structural equation modeling using PAWS Statistical V18 and AMOS V18 to analyze survey data from 412 respondents from the Australian beef supply chain. Findings – Key findings are that both innovative and non-innovative supply chain operators attribute supply chain synchronization as only a minor indicator of strategic supply chain capability, contrary to the literature; and they also indicate strategic supply chain capability has a minor influence in achieving beneficial outcomes from utilizing industry-led innovation. These results suggest a lack of coordination between supply chain operatives in the industry. They also suggest a lack of understanding of the benefits of developing a strategic supply chain management competence, particularly in relation to innovation agendas, and provides valuable insights as to why an industry paradox exists in terms of the level of investment in industry-led innovation, vs the level of corresponding benefit achieved. Research limitations/implications – Results are not generalized due to the single agribusiness industry studied and the single research method employed. However, this provides opportunity for further agribusiness studies in this area and also studies using alternate methods, such as qualitative, in-depth analysis of these factors and their relationships, which may confirm results or produce different results. Further, this study empirically extends existing theoretical contributions and insights into the roles of strategic supply chain management and innovation management in improving supply chain and ultimately industry performance while providing practical insights to supply chain practitioners in this and other similar agribusiness industries. Practical implications – These findings confirm results from a 2007 research (Ketchen et al., 2007) which suggests supply chain practice and teachings need to take a strategic direction in the twenty-first century. To date, competence in supply chain management has built up from functional and process orientations rather than from a strategic perspective. This study confirms that there is a need for more generalists that can integrate with various disciplines, particularly those who can understand and implement strategic supply chain management. Social implications – Possible social implications accrue through the development of responsible government policy in terms of industry supply chains. Strategic supply chain management and supply chain innovation management have impacts to the social fabric of nations through the sustainability of their industries, especially agribusiness industries which deal with food safety and security. If supply chains are now the competitive weapon of nations then funding innovation and managing their supply chain competitiveness in global markets requires a strategic approach from everyone, not just the industry participants. Originality/value – This is original empirical research, seeking to add value to embryonic and important developing literature concerned with adopting a strategic approach to supply chain management. It also seeks to add to existing literature in the area of innovation management, particularly through greater understanding of the implications of nations developing industry-wide, industry-led innovation agendas, and their ramifications to industry supply chains.

Characterization of acyl chain position in unsaturated phosphatidylcholines using differential mobility-mass spectrometry

Glycerophospholipids (GPs) that differ in the relative position of the two fatty acyl chains on the glycerol backbone (i.e., sn-positional isomers) can have distinct physicochemical properties. The unambiguous assignment of acyl chain position to an individual GP represents a significant analytical challenge. Here we describe a workflow where phosphatidylcholines (PCs) are subjected to ESI for characterization by a combination of differential mobility spectrometry and MS (DMS-MS). When infused as a mixture, ions formed from silver adduction of each phospholipid isomer {e.g., [PC (16:0/18:1) + Ag]+ and [PC (18:1/16:0) + Ag]+} are transmitted through the DMS device at discrete compensation voltages. Varying their relative amounts allows facile and unambiguous assignment of the sn-positions of the fatty acyl chains for each isomer. Integration of the well-resolved ion populations provides a rapid method (< 3 min) for relative quantification of these lipid isomers. The DMS-MS results show excellent agreement with established, but time-consuming, enzymatic approaches and also provide superior accuracy to methods that rely on MS alone. The advantages of this DMS-MS method in identification and quantification of GP isomer populations is demonstrated by direct analysis of complex biological extracts without any prior fractionation.

Identifying weak linear features with the "coalescing shortest path image transform"

The detection of line-like features in images finds many applications in microanalysis. Actin fibers, microtubules, neurites, pilis, DNA, and other biological structures all come up as tenuous curved lines in microscopy images. A reliable tracing method that preserves the integrity and details of these structures is particularly important for quantitative analyses. We have developed a new image transform called the "Coalescing Shortest Path Image Transform" with very encouraging properties. Our scheme efficiently combines information from an extensive collection of shortest paths in the image to delineate even very weak linear features. © Copyright Microscopy Society of America 2011.

Models of protein linear molecular motors for dynamic nanodevices

Protein molecular motors are natural nano-machines that convert the chemical energy from the hydrolysis of adenosine triphosphate into mechanical work. These efficient machines are central to many biological processes, including cellular motion, muscle contraction and cell division. The remarkable energetic efficiency of the protein molecular motors coupled with their nano-scale has prompted an increasing number of studies focusing on their integration in hybrid micro- and nanodevices, in particular using linear molecular motors. The translation of these tentative devices into technologically and economically feasible ones requires an engineering, design-orientated approach based on a structured formalism, preferably mathematical. This contribution reviews the present state of the art in the modelling of protein linear molecular motors, as relevant to the future design-orientated development of hybrid dynamic nanodevices. © 2009 The Royal Society of Chemistry.