Analysis of build-up of heavy metals and volatile organics on urban roads in Gold Coast, Australia

Urban water quality can be significantly impaired by the build-up of pollutants such as heavy metals and volatile organics on urban road surfaces due to vehicular traffic. Any control strategy for the mitigation of traffic related build-up of heavy metals and volatile organic pollutants should be based on the knowledge of their build-up processes. In the study discussed in this paper, the outcomes of a detailed experiment investigation into build-up processes of heavy metals and volatile organics are presented. It was found that traffic parameters such as average daily traffic, volume over capacity ratio and surface texture depth had similar strong correlations with the build-up of heavy metals and volatile organics. Multicriteria decision analyses revealed that the 1 - 74 um particulate fraction of total suspended solids (TSS) could be regarded as a surrogate indicator for particulate heavy metals in build-up and this same fraction of total organic carbon could be regarded as a surrogate indicator for particulate volatile organics build-up. In terms of pollutants affinity, TSS was found to be the predominant parameter for particulate heavy metals build-up and total dissolved solids was found to be the predominant parameter for he potential dissolved particulate fraction in heavy metals build-up. It was also found that land use did not play a significant role in the build-up of traffic generated heavy metals and volatile organics.

Secure data aggregation in wireless sensor networks

A Wireless Sensor Network (WSN) is a set of sensors that are integrated with a physical environment. These sensors are small in size, and capable of sensing physical phenomena and processing them. They communicate in a multihop manner, due to a short radio range, to form an Ad Hoc network capable of reporting network activities to a data collection sink. Recent advances in WSNs have led to several new promising applications, including habitat monitoring, military target tracking, natural disaster relief, and health monitoring. The current version of sensor node, such as MICA2, uses a 16 bit, 8 MHz Texas Instruments MSP430 micro-controller with only 10 KB RAM, 128 KB program space, 512 KB external ash memory to store measurement data, and is powered by two AA batteries. Due to these unique specifications and a lack of tamper-resistant hardware, devising security protocols for WSNs is complex. Previous studies show that data transmission consumes much more energy than computation. Data aggregation can greatly help to reduce this consumption by eliminating redundant data. However, aggregators are under the threat of various types of attacks. Among them, node compromise is usually considered as one of the most challenging for the security of WSNs. In a node compromise attack, an adversary physically tampers with a node in order to extract the cryptographic secrets. This attack can be very harmful depending on the security architecture of the network. For example, when an aggregator node is compromised, it is easy for the adversary to change the aggregation result and inject false data into the WSN. The contributions of this thesis to the area of secure data aggregation are manifold. We firstly define the security for data aggregation in WSNs. In contrast with existing secure data aggregation definitions, the proposed definition covers the unique characteristics that WSNs have. Secondly, we analyze the relationship between security services and adversarial models considered in existing secure data aggregation in order to provide a general framework of required security services. Thirdly, we analyze existing cryptographic-based and reputationbased secure data aggregation schemes. This analysis covers security services provided by these schemes and their robustness against attacks. Fourthly, we propose a robust reputationbased secure data aggregation scheme for WSNs. This scheme minimizes the use of heavy cryptographic mechanisms. The security advantages provided by this scheme are realized by integrating aggregation functionalities with: (i) a reputation system, (ii) an estimation theory, and (iii) a change detection mechanism. We have shown that this addition helps defend against most of the security attacks discussed in this thesis, including the On-Off attack. Finally, we propose a secure key management scheme in order to distribute essential pairwise and group keys among the sensor nodes. The design idea of the proposed scheme is the combination between Lamport's reverse hash chain as well as the usual hash chain to provide both past and future key secrecy. The proposal avoids the delivery of the whole value of a new group key for group key update; instead only the half of the value is transmitted from the network manager to the sensor nodes. This way, the compromise of a pairwise key alone does not lead to the compromise of the group key. The new pairwise key in our scheme is determined by Diffie-Hellman based key agreement.

Integrated Acquisition Engineering Model for acquiring heavy engineering assets

In asset intensive industries such as mining, oil & gas, utilities etc. most of the capital expenditure happens on acquiring engineering assets. Process of acquiring assets is called as “Procurement” or “Acquisition”. An asset procurement decision should be taken in consideration with the installation, commissioning, operational, maintenance and disposal needs of an asset or spare. However, such cross-functional collaboration and communication does not appear to happen between engineering, maintenance, warehousing and procurement functions in many asset intensive industries. Acquisition planning and execution are two distinct parts of asset acquisition process. Acquisition planning or procurement planning is responsible for determining exactly what is required to be purchased. It is important that an asset acquisition decision is the result of cross-functional decision making process. An acquisition decision leads to a formal purchase order. Most costly asset decisions occur even before they are acquired. Therefore, acquisition decision should be an outcome of an integrated planning & decision making process. Asset intensive organizations both, Government and non Government in Australia spent AUD 102.5 Billion on asset acquisition in year 2008-09. There is widespread evidence of many assets and spare not being used or utilized and in the end are written off. This clearly shows that many organizations end up buying assets or spares which were not required or non-conforming to the needs of user functions. It is due the fact that strategic and software driven procurement process do not consider all the requirements from various functions within the organization which contribute to the operation and maintenance of the asset over its life cycle. There is a lot of research done on how to implement an effective procurement process. There are numerous software solutions available for executing a procurement process. However, not much research is done on how to arrive at a cross functional procurement planning process. It is also important to link procurement planning process to procurement execution process. This research will discuss ““Acquisition Engineering Model” (AEM) framework, which aims at assisting acquisition decision making based on various criteria to satisfy cross-functional organizational requirements. Acquisition Engineering Model (AEM) will consider inputs from corporate asset management strategy, production management, maintenance management, warehousing, finance and HSE. Therefore, it is essential that the multi-criteria driven acquisition planning process is carried out and its output is fed to the asset acquisition (procurement execution) process. An effective procurement decision making framework to perform acquisition planning which considers various functional criteria will be discussed in this paper.

Drivers of supply chain collaboration among Finnish manufacturers

This paper focuses on data exchange relationships and ways to improve collaboration in the supply chain. Initially, the paper examines the information needs and alternatives in supply chain management. In the second part, the paper identifies different sets of factors that are likely to influence information sharing with suppliers, from the manufacturers’ point of view. Results from a Finnish Manufacturing industry survey show that manufacturers provided substantial information on demand data, production schedules, and inventories to their suppliers. Respondents perceived delivery performance measured by the timeliness, accuracy, and defect rate of deliveries as the primary incentives for supplier collaboration. On the other hand, supplier image and the market in which the supplier operates were found to be less relevant in determining the intensity of collaboration.

Supply chain sustainability : a relationship management approach moderated by culture and commitment

This research explores the nature of relationship management on construction projects in Australia and examines the effects of culture, by means of Schwarz’s value survey, on relationships under different contract strategies. The research was based on the view that the development of a sustainable supply chain depends on the transfer of knowledge and capabilities from the larger players in the supply chain through collaboration brought about by relationship management. The research adopted a triangulated approach in which quantitative data were collected by questionnaire, interviews were conducted to explore and enrich the quantitative data and case studies were undertaken in order to illustrate and validate the findings. The aim was to investigate how values and attitudes enhance or reduce the incorporation of the supply chain into the project. From the research it was found that the degree of match and mismatch between values and contract strategy impacts commitment and the engagement and empowerment of the supply chain.

Maintenance chain integration using Petri-net enabled multiagent system modeling and implementation approach

Engineering asset management (EAM) is a broad discipline and the EAM functions and processes are characterized by its distributed nature. However, engineering asset nowadays mostly relies on self-maintained experiential rule bases and periodic maintenance, which is lacking a collaborative engineering approach. This research proposes a collaborative environment integrated by a service center with domain expertise such as diagnosis, prognosis, and asset operations. The collaborative maintenance chain combines asset operation sites, service center (i.e., maintenance operation coordinator), system provider, first tier collaborators, and maintenance part suppliers. Meanwhile, to realize the automation of communication and negotiation among organizations, multiagent system (MAS) technique is applied to enhance the entire service level. During the MAS design processes, this research combines Prometheus MAS modeling approach with Petri-net modeling methodology and unified modeling language to visualize and rationalize the design processes of MAS. The major contributions of this research include developing a Petri-net enabled Prometheus MAS modeling methodology and constructing a collaborative agent-based maintenance chain framework for integrated EAM.

Mood and interpersonal functioning in heavy smokers

Male and female adult heavy smokers (n = 96) and non-smokers (n = 123) were compared on the Depression Anxiety Stress Scales (DASS), Adult Attachment Scale (AAS), Fear of Intimacy Scale (FIS), Negative Mood Regulation (NMR) Scale and Affect Intensity Measure (AIM). Compared with non-smokers, smokers scored significantly higher on DASS-Stress, DASS-Anxiety, and DASS-Depression, and significantly lower on NMR, AAS-Depend and AAS-Close. Smokers also scored marginally higher on FIS. Results suggest mood and relationship dysfunction in smokers, similar to the findings of a previous investigation of detoxified inpatients undergoing treatment for substance (alcohol, heroin, or methamphetamine) dependence.

A Python package for Bayesian estimation using Markov Chain Monte Carlo

Markov chain Monte Carlo (MCMC) estimation provides a solution to the complex integration problems that are faced in the Bayesian analysis of statistical problems. The implementation of MCMC algorithms is, however, code intensive and time consuming. We have developed a Python package, which is called PyMCMC, that aids in the construction of MCMC samplers and helps to substantially reduce the likelihood of coding error, as well as aid in the minimisation of repetitive code. PyMCMC contains classes for Gibbs, Metropolis Hastings, independent Metropolis Hastings, random walk Metropolis Hastings, orientational bias Monte Carlo and slice samplers as well as specific modules for common models such as a module for Bayesian regression analysis. PyMCMC is straightforward to optimise, taking advantage of the Python libraries Numpy and Scipy, as well as being readily extensible with C or Fortran.

Studies of granulosa cell maturation in dominant and subordinate bovine follicles : novel extracellular matrix focimatrix is co-ordinately regulated with cholesterol side-chain cleavage CYP11A1

During growth of antral ovarian follicles granulosa cells first become associated with a novel type of extracellular matrix, focimatrix, and at larger sizes follicles become either subordinate or dominant. To examine this, bovine subordinate (9.0±s.e.m. 0.4 mm; n=16), partially dominant (12.0±0.6 mm; n=18) and fully dominant (15.0±0.4 mm; n=14) follicles were examined by real time RT-PCR analyses of granulosa cells and by immunohistochemistry of focimatrix. Changes in the expression of FSH receptor, LH receptor, cholesterol side-chain cleavage (CYP11A1), 3β-hydroxysteroid dehydrogenase, aromatase (CYP19A1) and inhibin-α and β-B were observed as expected for follicle sizes examined. After adjusting for size differences, only CYP11A1 was significantly different between the groups, and elevated in dominant follicles. Also after adjusting for differences in size there were no significant differences in expression of focimatrix components collagen type IV α-1 (COL4A1), laminin β-2, nidogen 1 (NID1), and perlecan (HSPG2) or the volume density of NID1 and -2 and HSPG2. The volume density of focimatrix components in laminin 111 was significantly elevated in dominant follicles. Adjusting for analysis of more than one follicle per animal and for multiple correlations, CYP11A1 mRNA levels were highly correlated with the focimatrix genes COL4A1, NID1 and -2 and HSPG2. Thus, focimatrix may potentially regulate CYP11A1 expression, and the regulation of both could be important in follicular dominance.

Volcanology and petrology of submarine volcanoes of the New Hebrides island arc

The New Hebrides Island Arc, an intra-oceanic island chain in the southwest Pacific, is formed by subduction of the Indo-Australian Plate beneath the Pacific Plate. The southern end of the New Hebrides Island Arc is an ideal location to study the magmatic and tectonic interaction of an emerging island arc as this part of the island chain is less than 3 million years old. A tectonically complex island arc, it exhibits a change in relative subduction rate from ~12cm/yr to 6 cm/yr before transitioning to a left-lateral strike slip zone at its southern end. Two submarine volcanic fields, Gemini-Oscostar and Volsmar, occur at this transition from normal arc subduction to sinistral strike slip movement. Multi-beam bathymetry and dredge samples collected during the 2004 CoTroVE cruise onboard the RV Southern Surveyor help define the relationship between magmatism and tectonics, and the source for these two submarine volcanic fields. Gemini-Oscostar volcanic field (GOVF), dominated by northwest-oriented normal faults, has mature polygenetic stratovolcanoes with evidence for explosive subaqueous eruptions and homogeneous monogenetic scoria cones. Volsmar volcanic field (VVF), located 30 km south of GOVF, exhibits a conjugate set of northwest and eastwest-oriented normal faults, with two polygenetic stratovolcanoes and numerous monogenetic scoria cones. A deep water caldera provides evidence for explosive eruptions at 1500m below sea level in the VVF. Both volcanic fields are dominated by low-K island arc tholeiites and basaltic andesites with calcalkalic andesite and dacite being found only in the GOVF. Geochemical signatures of both volcanic fields continue the along-arc trend of decreasing K2O with both volcanic fields being similar to the New Hebrides central chain lavas. Lavas from both fields display a slight depletion in high field strength elements and heavy rare earth elements, and slight enrichments in large-ion lithophile elements and light rare earth elements with respect to N-MORB mantle. Sr and Nd isotope data correlate with heavy rare earth and high field strength element data to show that both fields are derived from depleted mantle. Pb isotopes define Pacific MORB mantle sources and are consistent with isotopic variation along the New Hebrides Island Arc. Pb isotopes show no evidence for sediment contamination; the subduction component enrichment is therefore a slab-derived enrichment. There is a subtle spatial variation in source chemistry which sees a northerly trend of decreasing enrichment of slab-derived fluids.

Chain scission resists for extreme ultraviolet lithography based on high performance polysulfone-containing polymers

A series of polymers with a comb architecture were prepared where the poly(olefin sulfone) backbone was designed to be highly sensitive to extreme ultraviolet (EUV) radiation, while the well-defined poly(methyl methacrylate) (PMMA) arms were incorporated with the aim of increasing structural stability. It is hypothesized that upon EUV radiation rapid degradation of the polysulfone backbone will occur leaving behind the well-defined PMMA arms. The synthesized polymers were characterised and have had their performance as chain-scission EUV photoresists evaluated. It was found that all materials possess high sensitivity towards degradation by EUV radiation (E0 in the range 4–6 mJ cm−2). Selective degradation of the poly(1-pentene sulfone) backbone relative to the PMMA arms was demonstrated by mass spectrometry headspace analysis during EUV irradiation and by grazing-angle ATR-FTIR. EUV interference patterning has shown that materials are capable of resolving 30 nm 1:1 line:space features. The incorporation of PMMA was found to increase the structural integrity of the patterned features. Thus, it has been shown that terpolymer materials possessing a highly sensitive poly(olefin sulfone) backbone and PMMA arms are able to provide a tuneable materials platform for chain scission EUV resists. These materials have the potential to benefit applications that require nanopattering, such as computer chip manufacture and nano-MEMS.