Characterisation of multi wall carbon nanotube–polymer composites for strain sensing applications

Carbon nanotubes (CNTs) have excellent electrical, mechanical and electromechanical properties. When CNTs are incorporated into polymers, electrically conductive composites with high electrical conductivity at very low CNT content (often below 1% wt CNT) result. Due to the change in electrical properties under mechanical load, carbon nanotube/polymer composites have attracted significant research interest especially due to their potential for application in in-situ monitoring of stress distribution and active control of strain sensing in composite structures or as strain sensors. To sucessfully develop novel devices for such applications, some of the major challenges that need to be overcome include; in-depth understanding of structure-electrical conductivity relationships, response of the composites under changing environmental conditions and piezoresistivity of different types of carbon nanotube/polymer sensing devices. In this thesis, direct current (DC) and alternating current (AC) conductivity of CNT-epoxy composites was investigated. Details of microstructure obtained by scanning electron microscopy were used to link observed electrical properties with structure using equivalent circuit modeling. The role of polymer coatings on macro and micro level electrical conductivity was investigated using atomic force microscopy. Thermal analysis and Raman spectroscopy were used to evaluate the heat flow and deformation of carbon nanotubes embedded in the epoxy, respectively, and related to temperature induced resistivity changes. A comparative assessment of piezoresistivity was conducted using randomly mixed carbon nanotube/epoxy composites, and new concept epoxy- and polyurethane-coated carbon nanotube films. The results indicate that equivalent circuit modelling is a reliable technique for estimating values of the resistance and capacitive components in linear, low aspect ratio-epoxy composites. Using this approach, the dominant role of tunneling resistance in determining the electrical conductivity was confirmed, a result further verified using conductive-atomic force microscopy analysis. Randomly mixed CNT-epoxy composites were found to be highly sensitive to mechanical strain and temperature variation compared to polymer-coated CNT films. In the vicinity of the glass transition temperature, the CNT-epoxy composites exhibited pronounced resistivity peaks. Thermal and Raman spectroscopy analyses indicated that this phenomenon can be attributed to physical aging of the epoxy matrix phase and structural rearrangement of the conductive network induced by matrix expansion. The resistivity of polymercoated CNT composites was mainly dominated by the intrinsic resistivity of CNTs and the CNT junctions, and their linear, weakly temperature sensitive response can be described by a modified Luttinger liquid model. Piezoresistivity of the polymer coated sensors was dominated by break up of the conducting carbon nanotube network and the consequent degradation of nanotube-nanotube contacts while that of the randomly mixed CNT-epoxy composites was determined by tunnelling resistance between neighbouring CNTs. This thesis has demonstrated that it is possible to use microstructure information to develop equivalent circuit models that are capable of representing the electrical conductivity of CNT/epoxy composites accurately. New designs of carbon nanotube based sensing devices, utilising carbon nanotube films as the key functional element, can be used to overcome the high temperature sensitivity of randomly mixed CNT/polymer composites without compromising on desired high strain sensitivity. This concept can be extended to develop large area intelligent CNT based coatings and targeted weak-point specific strain sensors for use in structural health monitoring.

Book review of Wang, Y., & Pizam, A. (Eds). 2011. Destination Marketing and Management – Theories and Applications.

A contentious issue in the field of destination marketing has been the recent tendency by some authors to refer to destination marketing organisations (DMOs) as destination management organisations. This nomenclature infers control over destination resources, a level of influence that is in reality held by few DMOs. This issue of a lack of control over the destination ‘amalgam’ is acknowledged by a number of the contributors, including the editors and the discussion on destination competitiveness by J.R. Brent Ritchie and Geoffrey Crouch, and is perhaps best summed up by Alan Fyall in the concluding chapter: “...unless all elements are owned by the same body, then the ability to control and influence the direction, quality and development of the destination pose very real challenges’ (p. 343). The title of the text acknowledges both marketing and management, in relation to theories and applications. While there are insightful propositions about ideals of destination management, readers will find there is a lack of coverage of destination management in practise by DMOs. This represents fertile ground for future research.

Prostate cancer biomarkers and the emerging proteomic techniques used in biomarker research

Prostate cancer (CaP) is the second leading cause of cancer-related deaths in North American males and the most common newly diagnosed cancer in men world wide. Biomarkers are widely used for both early detection and prognostic tests for cancer. The current, commonly used biomarker for CaP is serum prostate specific antigen (PSA). However, the specificity of this biomarker is low as its serum level is not only increased in CaP but also in various other diseases, with age and even body mass index. Human body fluids provide an excellent resource for the discovery of biomarkers, with the advantage over tissue/biopsy samples of their ease of access, due to the less invasive nature of collection. However, their analysis presents challenges in terms of variability and validation. Blood and urine are two human body fluids commonly used for CaP research, but their proteomic analyses are limited both by the large dynamic range of protein abundance making detection of low abundance proteins difficult and in the case of urine, by the high salt concentration. To overcome these challenges, different techniques for removal of high abundance proteins and enrichment of low abundance proteins are used. Their applications and limitations are discussed in this review. A number of innovative proteomic techniques have improved detection of biomarkers. They include two dimensional differential gel electrophoresis (2D-DIGE), quantitative mass spectrometry (MS) and functional proteomic studies, i.e., investigating the association of post translational modifications (PTMs) such as phosphorylation, glycosylation and protein degradation. The recent development of quantitative MS techniques such as stable isotope labeling with amino acids in cell culture (SILAC), isobaric tags for relative and absolute quantitation (iTRAQ) and multiple reaction monitoring (MRM) have allowed proteomic researchers to quantitatively compare data from different samples. 2D-DIGE has greatly improved the statistical power of classical 2D gel analysis by introducing an internal control. This chapter aims to review novel CaP biomarkers as well as to discuss current trends in biomarker research from two angles: the source of biomarkers (particularly human body fluids such as blood and urine), and emerging proteomic approaches for biomarker research.

Accuracy of FEM and BEM for electromagnetic flux calculations in high power applications

The development and design of electric high power devices with electromagnetic computer-aided engineering (EM-CAE) software such as the Finite Element Method (FEM) and Boundary Element Method (BEM) has been widely adopted. This paper presents the analysis of a Fault Current Limiter (FCL), which acts as a high-voltage surge protector for power grids. A prototype FCL was built. The magnetic flux in the core and the resulting electromagnetic forces in the winding of the FCL were analyzed using both FEM and BEM. An experiment on the prototype was conducted in a laboratory. The data obtained from the experiment is compared to the numerical solutions to determine the suitability and accuracy of the two methods.

WSUD application audit at Gold Coast City

In recent years, Water Sensitive Urban Design (WSUD) has been strongly promoted in South East Queensland to mitigate quantity and quality issues in relation to stormwater. Gold Coast City Council has implemented WSUD devices widely for stormwater management for a number of years and is planning to continue this practice into the future. According to the planning policy of Gold Coast City Council, the adoption of WSUD practices is now mandatory for any new development within the city. As a result, Council is expected to be in possession of tens of millions of dollars of these assets in the future and will be responsible for their maintenance and long-term management. Any shortcoming in the implementation of best practice can potentially result in substantial liability for the Council in the future. However, there has been limited evaluation of WSUD systems in relation to their performance, long-term maintenance, and current knowledge gaps. It was considered that periodical audits of WSUD applications on the Gold Coast is vital to ensure that Council’s WSUD policies are continually improved to new learning and best practice is implemented and risk to Council is mitigated. After a series of stakeholder interviews within Council to understand current practical issues (weaknesses and strengths) in relation to the implementation of WSUD on the Gold Coast, a field audit comprising of condition assessment of eleven WSUD systems within four suburbs was undertaken to identify weaknesses and strengths in WSUD implementation on the Gold Coast. The outcomes of this study are presented in this paper.

Reliability of partial ambiguity fixing with multiple GNSS constellations

Reliable ambiguity resolution (AR) is essential to Real-Time Kinematic (RTK) positioning and its applications, since incorrect ambiguity fixing can lead to largely biased positioning solutions. A partial ambiguity fixing technique is developed to improve the reliability of AR, involving partial ambiguity decorrelation (PAD) and partial ambiguity resolution (PAR). Decorrelation transformation could substantially amplify the biases in the phase measurements. The purpose of PAD is to find the optimum trade-off between decorrelation and worst-case bias amplification. The concept of PAR refers to the case where only a subset of the ambiguities can be fixed correctly to their integers in the integer least-squares (ILS) estimation system at high success rates. As a result, RTK solutions can be derived from these integer-fixed phase measurements. This is meaningful provided that the number of reliably resolved phase measurements is sufficiently large for least-square estimation of RTK solutions as well. Considering the GPS constellation alone, partially fixed measurements are often insufficient for positioning. The AR reliability is usually characterised by the AR success rate. In this contribution an AR validation decision matrix is firstly introduced to understand the impact of success rate. Moreover the AR risk probability is included into a more complete evaluation of the AR reliability. We use 16 ambiguity variance-covariance matrices with different levels of success rate to analyse the relation between success rate and AR risk probability. Next, the paper examines during the PAD process, how a bias in one measurement is propagated and amplified onto many others, leading to more than one wrong integer and to affect the success probability. Furthermore, the paper proposes a partial ambiguity fixing procedure with a predefined success rate criterion and ratio-test in the ambiguity validation process. In this paper, the Galileo constellation data is tested with simulated observations. Numerical results from our experiment clearly demonstrate that only when the computed success rate is very high, the AR validation can provide decisions about the correctness of AR which are close to real world, with both low AR risk and false alarm probabilities. The results also indicate that the PAR procedure can automatically chose adequate number of ambiguities to fix at given high-success rate from the multiple constellations instead of fixing all the ambiguities. This is a benefit that multiple GNSS constellations can offer.

Digital dietetics : practices and attitudes to technology use among Australian dietitians

Recent advancements in the capabilities of information and communication technologies (ICT) offer unique avenues to support the delivery of nutrition care. Despite ICTs being widely available, evidence on the practices and attitudes with regard to ICT use among dietitians is limited. A cross-sectional survey of Dietitians Association of Australia members was administered online in August 2011. All dietitians who responded (n=87) had access to a computer at work. Half reported providing non face-to-face consultations, with the telephone and email the most common modes of delivery. The use of smart phones was prevalent for 49% of practitioners, with 30% recommending nutrition-related applications and/or programs to clients. Benefits to technology use in practice most commonly reported included improvements in access to information/resources, time management, and workflow efficiency. Barriers identified related to cost and access to technology, and lack of suitable programs/applications. Technology was viewed as an important tool in practice among 93% of dietitians surveyed, however only 38% were satisfied with their current level of use. The majority (81%) believed more technology should be integrated within dietetics, while 85% indicated that the development of suitable and practical applications andprograms is necessary for future practice. Technology is regarded as an important tool by Australian dietitians, with an expressed need for theirinclusion to further facilitate nutrition care. Regular and ongoing evaluation of technology use among dietitians is vital to ensure thatapplications and use are evidence based and relevant to consumers in the digital world.

Do thermal agents affect range of movement and mechanical properties in soft tissues? A systematic review

OBJECTIVES: To examine the effect of thermal agents on the range of movement (ROM) and mechanical properties in soft tissue and to discuss their clinical relevance. DATA SOURCES: Electronic databases (Cochrane Central Register of Controlled Trials, MEDLINE, and EMBASE) were searched from their earliest available record up to May 2011 using Medical Subjects Headings and key words. We also undertook related articles searches and read reference lists of all incoming articles. STUDY SELECTION: Studies involving human participants describing the effects of thermal interventions on ROM and/or mechanical properties in soft tissue. Two reviewers independently screened studies against eligibility criteria. DATA EXTRACTION: Data were extracted independently by 2 review authors using a customized form. Methodologic quality was also assessed by 2 authors independently, using the Cochrane risk of bias tool. DATA SYNTHESIS: Thirty-six studies, comprising a total of 1301 healthy participants, satisfied the inclusion criteria. There was a high risk of bias across all studies. Meta-analyses were not undertaken because of clinical heterogeneity; however, effect sizes were calculated. There were conflicting data on the effect of cold on joint ROM, accessory joint movement, and passive stiffness. There was limited evidence to determine whether acute cold applications enhance the effects of stretching, and further evidence is required. There was evidence that heat increases ROM, and a combination of heat and stretching is more effective than stretching alone. CONCLUSIONS: Heat is an effective adjunct to developmental and therapeutic stretching techniques and should be the treatment of choice for enhancing ROM in a clinical or sporting setting. The effects of heat or ice on other important mechanical properties (eg, passive stiffness) remain equivocal and should be the focus of future study.

Making a case for social impact assessment in urban development : social impacts and legal disputes in Queensland, Australia

Urban land use planning and policy decisions are often contested, with the multiple stakeholders (business, developers, residents, policymakers and the wider community) frequently holding opposing viewpoints about the issues and best solution. In recent years, however, the participatory process of social impact assessment (SIA) has received significant attention as a way to mitigate conflict, facilitating negotiation and conflict resolution. This paper examines how social impacts have informed development appeals in Australia, focussing on ten cases from the Queensland Planning and Environment Court (QPEC). Half are appeals from community members (typically neighbours) wanting to oppose approvals and half from organisations appealing against City Councils’ decisions to deny their development applications. While legal challenges do not necessarily reflect attitudes and practices, they provide a means to begin to assess how social impacts (although not often explicitly defined as such) inform development related disputes. Based on the nature and outcomes of 10 QPEC cases, we argue that many legal cases could have been avoided if SIA had been undertaken appropriately. First, the issues in each case are clearly social, incorporating impacts on amenity, the character of an area, the needs of different social groups, perceptions of risk and a range of other social issues. Second, the outcomes and recommendations from each case, such as negotiating agreements, modifying plans and accommodating community concerns would have been equally served thorough SIA. Our argument is that engagement at an early stage, utilising SIA, could have likely achieved the same result in a less adversarial and much less expensive and time-consuming environment than a legal case.

Personalization in tag ontology learning for recommendation making

Due to the explosive growth of the Web, the domain of Web personalization has gained great momentum both in the research and commercial areas. One of the most popular web personalization systems is recommender systems. In recommender systems choosing user information that can be used to profile users is very crucial for user profiling. In Web 2.0, one facility that can help users organize Web resources of their interest is user tagging systems. Exploring user tagging behavior provides a promising way for understanding users’ information needs since tags are given directly by users. However, free and relatively uncontrolled vocabulary makes the user self-defined tags lack of standardization and semantic ambiguity. Also, the relationships among tags need to be explored since there are rich relationships among tags which could provide valuable information for us to better understand users. In this paper, we propose a novel approach for learning tag ontology based on the widely used lexical database WordNet for capturing the semantics and the structural relationships of tags. We present personalization strategies to disambiguate the semantics of tags by combining the opinion of WordNet lexicographers and users’ tagging behavior together. To personalize further, clustering of users is performed to generate a more accurate ontology for a particular group of users. In order to evaluate the usefulness of the tag ontology, we use the tag ontology in a pilot tag recommendation experiment for improving the recommendation performance by exploiting the semantic information in the tag ontology. The initial result shows that the personalized information has improved the accuracy of the tag recommendation.

From tiers to tables – enhancing student experience through collaborative learning spaces

BACKGROUND Collaborative and active learning have been clearly identified as ways students can engage in learning with each other and the academic staff. Traditional tier based lecture theatres and the didactic style they engender are not popular with students today as evidenced by the low attendance rates for lectures. Many universities are installing spaces designed with tables for group interaction with evolutions on spaces such as the TEAL (Technology Enabled Active Learning) (Massachusetts Institute of Technology, n.d.) and SCALE-UP (Student-Centred Activities for Large-Enrolment Undergraduate Programs) (North Carolina State University, n.d.) models. Technology advances in large screen computers and applications have also aided the move to these collaborative spaces. How well have universities structured learning using these spaces and how have students engaged with the content, technology, space and each other? This paper investigates the application of collaborative learning in such spaces for a cohort of 800+ first year engineers in the context of learning about and developing professional skills representative of engineering practice. PURPOSE To determine whether moving from tiers to tables enhances the student experience. Does utilising technology rich, activity based, collaborative learning spaces lead to positive experiences and active engagement of first year undergraduate engineering students? In developing learning methodology and approach in new learning spaces, what needs to change from a more traditional lecture and tutorial configuration? DESIGN/METHOD A post delivery review and analysis of outcomes was undertaken to determine how well students and tutors engaged with learning in new collaborative learning spaces. Data was gathered via focus group and survey of tutors, students survey and attendance observations. The authors considered the unit delivery approach along with observed and surveyed outcomes then conducted further review to produce the reported results. RESULTS Results indicate high participation in the collaborative sessions while the accompanying lectures were poorly attended. Students reported a high degree of satisfaction with the learning experience; however more investigation is required to determine the degree of improvement in retained learning outcomes. Survey feedback from tutors found that students engaged well in the activities during tutorials and there was an observed improvement in the quality of professional practice modelled by students during sessions. Student feedback confirmed the positive experiences in these collaborative learning spaces with 30% improvement in satisfaction ratings from previous years. CONCLUSIONS It is concluded that the right mix of space, technology and appropriate activities does engage students, improve participation and create a rich experience to facilitate potential for improved learning outcomes. The new Collaborative Teaching Spaces, together with integrated technology and tailored activities, has transformed the delivery of this unit and improved student satisfaction in tutorials significantly.

A multivariate approach to the identification of surrogate parameters for heavy metals in stormwater

Stormwater is a potential and readily available alternative source for potable water in urban areas. However, its direct use is severely constrained by the presence of toxic pollutants, such as heavy metals (HMs). The presence of HMs in stormwater is of concern because of their chronic toxicity and persistent nature. In addition to human health impacts, metals can contribute to adverse ecosystem health impact on receiving waters. Therefore, the ability to predict the levels of HMs in stormwater is crucial for monitoring stormwater quality and for the design of effective treatment systems. Unfortunately, the current laboratory methods for determining HM concentrations are resource intensive and time consuming. In this paper, applications of multivariate data analysis techniques are presented to identify potential surrogate parameters which can be used to determine HM concentrations in stormwater. Accordingly, partial least squares was applied to identify a suite of physicochemical parameters which can serve as indicators of HMs. Datasets having varied characteristics, such as land use and particle size distribution of solids, were analyzed to validate the efficacy of the influencing parameters. Iron, manganese, total organic carbon, and inorganic carbon were identified as the predominant parameters that correlate with the HM concentrations. The practical extension of the study outcomes to urban stormwater management is also discussed.

Critical timescales and time intervals for coupled linear processes

In 1991, McNabb introduced the concept of mean action time (MAT) as a finite measure of the time required for a diffusive process to effectively reach steady state. Although this concept was initially adopted by others within the Australian and New Zealand applied mathematics community, it appears to have had little use outside this region until very recently, when in 2010 Berezhkovskii and coworkers rediscovered the concept of MAT in their study of morphogen gradient formation. All previous work in this area has been limited to studying single–species differential equations, such as the linear advection–diffusion–reaction equation. Here we generalise the concept of MAT by showing how the theory can be applied to coupled linear processes. We begin by studying coupled ordinary differential equations and extend our approach to coupled partial differential equations. Our new results have broad applications including the analysis of models describing coupled chemical decay and cell differentiation processes, amongst others.

Students’ approaches to learning a new mathematical model

In this article, we report on the findings of an exploratory study into the experience of undergraduate students as they learn new mathematical models. Qualitative and quanti- tative data based around the students’ approaches to learning new mathematical models were collected. The data revealed that students actively adopt three approaches to under- standing a new mathematical model: gathering information for the task of understanding the model, practising with and using the model, and finding interrelationships between elements of the model. We found that the students appreciate mathematical models that have a real world application and that this can be used to engage students in higher level learning approaches.

Towards Bayesian experimental design for nonlinear models that require a large number of sampling times

The use of Bayesian methodologies for solving optimal experimental design problems has increased. Many of these methods have been found to be computationally intensive for design problems that require a large number of design points. A simulation-based approach that can be used to solve optimal design problems in which one is interested in finding a large number of (near) optimal design points for a small number of design variables is presented. The approach involves the use of lower dimensional parameterisations that consist of a few design variables, which generate multiple design points. Using this approach, one simply has to search over a few design variables, rather than searching over a large number of optimal design points, thus providing substantial computational savings. The methodologies are demonstrated on four applications, including the selection of sampling times for pharmacokinetic and heat transfer studies, and involve nonlinear models. Several Bayesian design criteria are also compared and contrasted, as well as several different lower dimensional parameterisation schemes for generating the many design points.