Innovations in dietary interventions : Use of a photographic food diary method and telephone linked computerized care in chronic disease

Access to dietetic care is important in chronic disease management and innovative technologies assists in this purpose. Photographic dietary records (PhDR) using mobile phones or cameras are valid and convenient for patients. Innovations in providing dietary interventions via telephone and computer can also inform dietetic practice. Three studies are presented. A mobile phone method was validated by comparing energy intake (EI) to a weighed food record and a measure of energy expenditure (EE) obtained using the doubly labelled water technique in 10 adults with T2 diabetes. The level of agreement between mean (±sd) energy intake mobile phone (8.2±1.7 MJ) and weighed record (8.5±1.6 MJ) was high (p=0.392), however EI/EE for both methods gave similar levels of under-reporting (0.69 and 0.72). All subjects preferred using the mobile phone vs. weighed record. Nineteen individuals with Parkinsons disease kept 3-day PhDRs on three occasions using point-and-shoot digital cameras over a 12 week period. The camera was rated as easy to use by 89%, keeping a PhDR was considered acceptable by 94% and none would rather use a “pen and paper” method. Eighty-three percent felt confident to use the camera again to record intake. An interactive, automated telephone system designed to coach people with T2 diabetes to adopt and maintain diabetes self-care behaviours, including nutrition, showed trends for improvements in total fat, saturated fat and vegetable intake of the intervention group compared to control participants over 6 months. Innovative technologies are acceptable to patients with chronic conditions and can be incorporated into dietetic care.

Modal flexibility method for structural damage detection in suspension bridges

Suspension bridges meet the steadily growing demand for lighter and longer bridges in today’s infrastructure systems. These bridges are designed to have long life spans, but with age, their main cables and hangers could suffer from corrosion and fatigue. There is a need for a simple and reliable procedure to detect and locate such damage, so that appropriate retrofitting can be carried out to prevent bridge failure. Damage in a structure causes changes in its properties (mass, damping and stiffness) which in turn will cause changes in its vibration characteristics (natural frequencies, modal damping and mode shapes). Methods based on modal flexibility, which depends on both the natural frequencies and mode shapes, have the potential for damage detection. They have been applied successfully to beam and plate elements, trusses and simple structures in reinforced concrete and steel. However very limited applications for damage detection in suspension bridges have been identified to date. This paper examines the potential of modal flexibility methods for damage detection and localization of a suspension bridge under different damage scenarios in the main cables and hangers using numerical simulation techniques. Validated finite element model (FEM) of a suspension bridge is used to acquire mass normalized mode shape vectors and natural frequencies at intact and damaged states. Damage scenarios will be simulated in the validated FE models by varying stiffness of the damaged structural members. The capability of damage index based on modal flexibility to detect and locate damage is evaluated. Results confirm that modal flexibility based methods have the ability to successfully identify damage in suspension bridge main cables and hangers.

Bayesian inference of traffic volumes based on Bluetooth data

The study of the relationship between macroscopic traffic parameters, such as flow, speed and travel time, is essential to the understanding of the behaviour of freeway and arterial roads. However, the temporal dynamics of these parameters are difficult to model, especially for arterial roads, where the process of traffic change is driven by a variety of variables. The introduction of the Bluetooth technology into the transportation area has proven exceptionally useful for monitoring vehicular traffic, as it allows reliable estimation of travel times and traffic demands. In this work, we propose an approach based on Bayesian networks for analyzing and predicting the complex dynamics of flow or volume, based on travel time observations from Bluetooth sensors. The spatio-temporal relationship between volume and travel time is captured through a first-order transition model, and a univariate Gaussian sensor model. The two models are trained and tested on travel time and volume data, from an arterial link, collected over a period of six days. To reduce the computational costs of the inference tasks, volume is converted into a discrete variable. The discretization process is carried out through a Self-Organizing Map. Preliminary results show that a simple Bayesian network can effectively estimate and predict the complex temporal dynamics of arterial volumes from the travel time data. Not only is the model well suited to produce posterior distributions over single past, current and future states; but it also allows computing the estimations of joint distributions, over sequences of states. Furthermore, the Bayesian network can achieve excellent prediction, even when the stream of travel time observation is partially incomplete.

Second-order inelastic analysis of composite framed structures based on the refined plastic hinge method

Composite steel-concrete structures experience non-linear effects which arise from both instability-related geometric non-linearity and from material non-linearity in all of their component members. Because of this, conventional design procedures cannot capture the true behaviour of a composite frame throughout its full loading range, and so a procedure to account for those non-linearities is much needed. This paper therefore presents a numerical procedure capable of addressing geometric and material non-linearities at the strength limit state based on the refined plastic hinge method. Different material non-linearity for different composite structural components such as T-beams, concrete-filled tubular (CFT) and steel-encased reinforced concrete (SRC) sections can be treated using a routine numerical procedure for their section properties in this plastic hinge approach. Simple and conservative initial and full yield surfaces for general composite sections are proposed in this paper. The refined plastic hinge approach models springs at the ends of the element which are activated when the surface defining the interaction of bending and axial force at first yield is reached; a transition from the first yield interaction surface to the fully plastic interaction surface is postulated based on a proposed refined spring stiffness, which formulates the load-displacement relation for material non-linearity under the interaction of bending and axial actions. This produces a benign method for a beam-column composite element under general loading cases. Another main feature of this paper is that, for members containing a point of contraflexure, its location is determined with a simple application of the method herein and a node is then located at this position to reproduce the real flexural behaviour and associated material non-linearity of the member. Recourse is made to an updated Lagrangian formulation to consider geometric non-linear behaviour and to develop a non-linear solution strategy. The formulation with the refined plastic hinge approach is efficacious and robust, and so a full frame analysis incorporating geometric and material non-linearity is tractable. By way of contrast, the plastic zone approach possesses the drawback of strain-based procedures which rely on determining plastic zones within a cross-section and which require lengthwise integration. Following development of the theory, its application is illustrated with a number of varied examples.

Learning routines used by firms during construction of infrastructure projects using the alliance procurement method

Collaborative contracting has emerged over the past 15 years as an innovative project delivery framework that is particularly suited to infrastructure projects. Australia leads the world in the development of project and program alliance approaches to collaborative delivery. These approaches are considered to promise superior project results. However, very little is known about the learning routines that are most widely used in support of collaborative projects in general and alliance projects in particular. The literature on absorptive capacity and dynamic capabilities indicates that such learning enhances project performance. The learning routines employed at corporate level during the operation of collaborative infrastructure projects in Australia were examined through a large survey conducted in 2013. This paper presents a descriptive summary of the preliminary findings. The survey captured the experiences of 320 practitioners of collaborative construction projects, including public and private sector clients, contractors, consultants and suppliers (three per cent of projects were located in New Zealand, but for brevity’s sake the sample is referred to as Australian). The majority of projects identified used alliances (78.6%); whilst 9% used Early Contractor Involvement (ECI) contracts and 2.7% used Early Tender Involvement contracts, which are ‘slimmer’ types of collaborative contract. The remaining 9.7% of respondents used traditional contracts that employed some collaborative elements. The majority of projects were delivered for public sector clients (86.3%), and/or clients experienced with asset procurement (89.6%). All of the projects delivered infrastructure assets; one third in the road sector, one third in the water sector, one fifth in the rail sector, and the rest spread across energy, building and mining. Learning routines were explored within three interconnected phases: knowledge exploration, transformation and exploitation. The results show that explorative and exploitative learning routines were applied to a similar extent. Transformative routines were applied to a relatively low extent. It was also found that the most highly applied routine is ‘regularly applying new knowledge to collaborative projects’; and the least popular routine was ‘staff incentives to encourage information sharing about collaborative projects’. Future research planned by the authors will examine the impact of these routines on project performance.

Enhanced n-gram extraction using relevance feature discovery

Guaranteeing the quality of extracted features that describe relevant knowledge to users or topics is a challenge because of the large number of extracted features. Most popular existing term-based feature selection methods suffer from noisy feature extraction, which is irrelevant to the user needs (noisy). One popular method is to extract phrases or n-grams to describe the relevant knowledge. However, extracted n-grams and phrases usually contain a lot of noise. This paper proposes a method for reducing the noise in n-grams. The method first extracts more specific features (terms) to remove noisy features. The method then uses an extended random set to accurately weight n-grams based on their distribution in the documents and their terms distribution in n-grams. The proposed approach not only reduces the number of extracted n-grams but also improves the performance. The experimental results on Reuters Corpus Volume 1 (RCV1) data collection and TREC topics show that the proposed method significantly outperforms the state-of-art methods underpinned by Okapi BM25, tf*idf and Rocchio.

The link between infrastructure charges and housing affordability in Australia: Where is the empirical evidence?

Developer paid charges or contributions are a commonly used infrastructure funding mechanism for local governments. However, developers claim that these costs are merely passed on to home buyers, with adverse effects to housing affordability. Despite a plethora of government reports and industry advocacy, there remains no empirical evidence in Australia to confirm or quantify this passing on effect to home buyers and hence no data for which governments to base policy decision upon. This paper examines the question of who really pays for urban infrastructure and the impact of infrastructure charges on housing affordability. It presents the findings of a number of international empirical studies that provide evidence that infrastructure charges do increase house prices. Based on international findings, and in the absence of any Australian research, then these findings suggest that if the international findings are transferable, then there is empirical evidence to support the proposition that developer paid infrastructure charges are a significant contributor to increasing house prices.

A threshold analysis of dengue transmission in terms of weather variables and imported dengue cases in Australia

Dengue virus (DENV) transmission in Australia is driven by weather factors and imported dengue fever (DF) cases. However, uncertainty remains regarding the threshold effects of high-order interactions among weather factors and imported DF cases and the impact of these factors on autochthonous DF. A time-series regression tree model was used to assess the threshold effects of natural temporal variations of weekly weather factors and weekly imported DF cases in relation to incidence of weekly autochthonous DF from 1 January 2000 to 31 December 2009 in Townsville and Cairns, Australia. In Cairns, mean weekly autochthonous DF incidence increased 16.3-fold when the 3-week lagged moving average maximum temperature was <32 °C, the 4-week lagged moving average minimum temperature was ≥24 °C and the sum of imported DF cases in the previous 2 weeks was >0. When the 3-week lagged moving average maximum temperature was ≥32 °C and the other two conditions mentioned above remained the same, mean weekly autochthonous DF incidence only increased 4.6-fold. In Townsville, the mean weekly incidence of autochthonous DF increased 10-fold when 3-week lagged moving average rainfall was ≥27 mm, but it only increased 1.8-fold when rainfall was <27 mm during January to June. Thus, we found different responses of autochthonous DF incidence to weather factors and imported DF cases in Townsville and Cairns. Imported DF cases may also trigger and enhance local outbreaks under favorable climate conditions.

Cytotoxicity testing of burn wound dressings, ointments and creams : a method using polycarbonate cell culture inserts on a cell culture system

We have developed a method to test the cytotoxicity of wound dressings, ointments, creams and gels used in our Burn Centre, by placing them on a permeable Nunc Polycarbonate cell culture insert, incubated with a monolayer of cells (HaCaTs and primary human keratinocytes). METHODS: We performed two different methods to determine the relative toxicity to cells. (1) Photo visualisation: The dressings or compounds were positioned on the insert's membrane which was placed onto the monolayer tissue culture plate. After 24 h the surviving adherent cells were stained with Toluidine Blue and photos of the plates were taken. The acellular area of non-adherent dead cells which had been washed off with buffer was measured as a percentage of the total area of the plate. (2) Cell count of surviving cells: After 24 h incubation with the test material, the remaining cells were detached with trypsin, spun down and counted in a Haemocytometer with Trypan Blue, which differentiates between live and dead cells. RESULTS: Seventeen products were tested. The least cytotoxic products were Melolite, White soft Paraffin and Chlorsig1% Ointment. Some cytotoxicity was shown with Jelonet, Mepitel((R)), PolyMem((R)), DuoDerm((R)) and Xeroform. The most cytotoxic products included those which contained silver or Chlorhexidine and Paraffin Cream a moisturizer which contains the preservative Chlorocresol. CONCLUSION: This in vitro cell culture insert method allows testing of agents without direct cell contact. It is easy and quick to perform, and should help the clinician to determine the relative cytotoxicity of various dressings and the optimal dressing for each individual wound.

The impact of tobacco smoking on treatment for comorbid depression and alcohol misuse

Tobacco use is a major public health concern, and is associated with a number of mental illnesses as well as increased alcohol/other drug (AOD). Research into treatment for individuals experiencing such comorbidities is limited. Participants (n = 447) were those enrolled in the Depression and Alcohol Integrated and Single-focused Interventions project (Baker et al. 2010), and the Self Help for Alcohol/other drugs and DEpression project (Kay-Lambkin et al. Medical Journal of Australia 195:S44-S50, 2011a, Journal of Medical Internet Research 13(1):e11p11, b), who reported current depression and hazardous alcohol use at entry to the study. Smoking cessation was not targeted in, nor a goal of, treatment. After controlling for socioeconomic variables, tobacco use was not associated with higher levels of depressive symptoms at baseline; however heavy smokers (30+ cigarettes per day) consumed significantly more alcohol at baseline than did non-smokers (13 vs. 9 standard drinks per day). Baseline smoking severity did not impact on depression or alcohol use outcomes over a 12-month period. Reductions in tobacco use between baseline and 3-month follow-up were significantly associated with reductions in depression and alcohol consumption over the same time period. The study results suggest that tobacco use does not interfere with treatment for depression and alcohol use problems, and adds weight to the idea of considering specific treatment for tobacco use in the context of treatment for alcohol/other drug use.

Identifying Core Functions of Asset Management

It is widely acknowledged that effective asset management requires an interdisciplinary approach, in which synergies should exist between traditional disciplines such as: accounting, engineering, finance, humanities, logistics, and information systems technologies. Asset management is also an important, yet complex business practice. Business process modelling is proposed as an approach to manage the complexity of asset management through the modelling of asset management processes. A sound foundation for the systematic application and analysis of business process modelling in asset management is, however, yet to be developed. Fundamentally, a business process consists of activities (termed functions), events/states, and control flow logic. As both events/states and control flow logic are somewhat dependent on the functions themselves, it is a logical step to first identify the functions within a process. This research addresses the current gap in knowledge by developing a method to identify functions common to various industry types (termed core functions). This lays the foundation to extract such functions, so as to identify both commonalities and variation points in asset management processes. This method describes the use of a manual text mining and a taxonomy approach. An example is presented.