Molecular genetic analyses of RFLPs for PCR-amplified growth hormone gene, renal kallikrein gene and atrial natriuretic factor gene in essential hypertension

The present study examined polymorphisms of genes that might be involved in the onset of essential hypertension (HT). These included the (i) growth hormone gene (GH1), whose locus has recently been linked to elevated blood pressure (BP) in the stroke-prone SHR, although recent sib-pair analysis of a polymorphism near the human chorionic somatomammotropin gene (a member of the GH cluster) was unable to show linkage with HT; (ii) renal kallikrein gene (KLK1); and (iii) atrial natriuretic factor gene (ANF), where a primary defect in production or activity of kallikrein or ANF could cause NaCl retention and vasoconstriction. Association analyses were conducted to compare restriction fragment length polymorphisms (RFLPs) of each gene in 85 HT and 95 normotensive (NT) Caucasian subjects whose parents had a similar BP status at age ≥50 years. The frequency of the minor allele of (i) a RsaI RFLP in the promoter of GH1, amplified from leukocyte DNA by the polymerase chain reaction, was 0.15 in the HT group and 0.14 in the NT group (χ1=0.34, P=0.55); (ii) a TaqI RFLP for KLK1 was 0.035 in the HT group and 0.015 in the NT group (χ2=1.5, P=0.21); and (iii) a XhoI RFLP for ANF was 0.50 in HTs and 0.46 in NTs (χ2=0.20, P=0.65). Studies of HT pedigrees found one family in which the ANF locus and HT were not linked, owing to an obligate recombinant. The present data thus provide no evidence for involvement of the growth hormone, renal kallikrein, nor ANF gene in the causation of essential hypertension.

Scene invariant multi camera crowd counting

Automated crowd counting has become an active field of computer vision research in recent years. Existing approaches are scene-specific, as they are designed to operate in the single camera viewpoint that was used to train the system. Real world camera networks often span multiple viewpoints within a facility, including many regions of overlap. This paper proposes a novel scene invariant crowd counting algorithm that is designed to operate across multiple cameras. The approach uses camera calibration to normalise features between viewpoints and to compensate for regions of overlap. This compensation is performed by constructing an 'overlap map' which provides a measure of how much an object at one location is visible within other viewpoints. An investigation into the suitability of various feature types and regression models for scene invariant crowd counting is also conducted. The features investigated include object size, shape, edges and keypoints. The regression models evaluated include neural networks, K-nearest neighbours, linear and Gaussian process regresion. Our experiments demonstrate that accurate crowd counting was achieved across seven benchmark datasets, with optimal performance observed when all features were used and when Gaussian process regression was used. The combination of scene invariance and multi camera crowd counting is evaluated by training the system on footage obtained from the QUT camera network and testing it on three cameras from the PETS 2009 database. Highly accurate crowd counting was observed with a mean relative error of less than 10%. Our approach enables a pre-trained system to be deployed on a new environment without any additional training, bringing the field one step closer toward a 'plug and play' system.

Measurement, modelling and capacity analysis for novel, fixed multi-user single-antenna MIMO-OFDM system, in rural environments

High-speed broadband internet access is widely recognised as a catalyst to social and economic development. However, the provision of broadband Internet services with the existing solutions to rural population, scattered over an extensive geographical area, remains both an economic and technical challenge. As a feasible solution, the Commonwealth Scientific and Industrial Research Organization (CSIRO) proposed a highly spectrally efficient, innovative and cost-effective fixed wireless broadband access technology, which uses analogue TV frequency spectrum and Multi-User MIMO (MUMIMO) technology with Orthogonal-Frequency-Division-Multiplexing (OFDM). MIMO systems have emerged as a promising solution for the increasing demand of higher data rates, better quality of service, and higher network capacity. However, the performance of MIMO systems can be significantly affected by different types of propagation environments e.g., indoor, outdoor urban, or outdoor rural and operating frequencies. For instance, large spectral efficiencies associated with MIMO systems, which assume a rich scattering environment in urban environments, may not be valid for all propagation environments, such as outdoor rural environments, due to the presence of less scatterer densities. Since this is the first time a MU-MIMO-OFDM fixed broadband wireless access solution is deployed in a rural environment, questions from both theoretical and practical standpoints arise; For example, what capacity gains are available for the proposed solution under realistic rural propagation conditions?. Currently, no comprehensive channel measurement and capacity analysis results are available for MU-MIMO-OFDM fixed broadband wireless access systems which employ large scale multiple antennas at the Access Point (AP) and analogue TV frequency spectrum in rural environments. Moreover, according to the literature, no deterministic MU-MIMO channel models exist that define rural wireless channels by accounting for terrain effects. This thesis fills the aforementioned knowledge gaps with channel measurements, channel modeling and comprehensive capacity analysis for MU-MIMO-OFDM fixed wireless broadband access systems in rural environments. For the first time, channel measurements were conducted in a rural farmland near Smithton, Tasmania using CSIRO's broadband wireless access solution. A novel deterministic MU-MIMO-OFDM channel model, which can be used for accurate performance prediction of rural MUMIMO channels with dominant Line-of-Sight (LoS) paths, was developed under this research. Results show that the proposed solution can achieve 43.7 bits/s/Hz at a Signal-to- Noise Ratio (SNR) of 20 dB in rural environments. Based on channel measurement results, this thesis verifies that the deterministic channel model accurately predicts channel capacity in rural environments with a Root Mean Square (RMS) error of 0.18 bits/s/Hz. Moreover, this study presents a comprehensive capacity analysis of rural MU-MIMOOFDM channels using experimental, simulated and theoretical models. Based on the validated deterministic model, further investigations on channel capacity and the eects of capacity variation, with different user distribution angles (θ) around the AP, were analysed. For instance, when SNR = 20dB, the capacity increases from 15.5 bits/s/Hz to 43.7 bits/s/Hz as θ increases from 10° to 360°. Strategies to mitigate these capacity degradation effects are also presented by employing a suitable user grouping method. Outcomes of this thesis have already been used by CSIRO scientists to determine optimum user distribution angles around the AP, and are of great significance for researchers and MU-MUMO-OFDM system developers to understand the advantages and potential capacity gains of MU-MIMO systems in rural environments. Also, results of this study are useful to further improve the performance of MU-MIMO-OFDM systems in rural environments. Ultimately, this knowledge contribution will be useful in delivering efficient, cost-effective high-speed wireless broadband systems that are tailor-made for rural environments, thus, improving the quality of life and economic prosperity of rural populations.

Sequential decision fusion of multibiometrics applied to text-dependent speaker verification for controlled errors

Reliability of the performance of biometric identity verification systems remains a significant challenge. Individual biometric samples of the same person (identity class) are not identical at each presentation and performance degradation arises from intra-class variability and inter-class similarity. These limitations lead to false accepts and false rejects that are dependent. It is therefore difficult to reduce the rate of one type of error without increasing the other. The focus of this dissertation is to investigate a method based on classifier fusion techniques to better control the trade-off between the verification errors using text-dependent speaker verification as the test platform. A sequential classifier fusion architecture that integrates multi-instance and multisample fusion schemes is proposed. This fusion method enables a controlled trade-off between false alarms and false rejects. For statistically independent classifier decisions, analytical expressions for each type of verification error are derived using base classifier performances. As this assumption may not be always valid, these expressions are modified to incorporate the correlation between statistically dependent decisions from clients and impostors. The architecture is empirically evaluated by applying the proposed architecture for text dependent speaker verification using the Hidden Markov Model based digit dependent speaker models in each stage with multiple attempts for each digit utterance. The trade-off between the verification errors is controlled using the parameters, number of decision stages (instances) and the number of attempts at each decision stage (samples), fine-tuned on evaluation/tune set. The statistical validation of the derived expressions for error estimates is evaluated on test data. The performance of the sequential method is further demonstrated to depend on the order of the combination of digits (instances) and the nature of repetitive attempts (samples). The false rejection and false acceptance rates for proposed fusion are estimated using the base classifier performances, the variance in correlation between classifier decisions and the sequence of classifiers with favourable dependence selected using the 'Sequential Error Ratio' criteria. The error rates are better estimated by incorporating user-dependent (such as speaker-dependent thresholds and speaker-specific digit combinations) and class-dependent (such as clientimpostor dependent favourable combinations and class-error based threshold estimation) information. The proposed architecture is desirable in most of the speaker verification applications such as remote authentication, telephone and internet shopping applications. The tuning of parameters - the number of instances and samples - serve both the security and user convenience requirements of speaker-specific verification. The architecture investigated here is applicable to verification using other biometric modalities such as handwriting, fingerprints and key strokes.

Development of school connectedness as a component of an injury prevention program for early adolescents

The current program of research addresses the need for multi-level programs to target the major increase in injury rates that occurs throughout adolescence. Specifically, it involves the investigation of school connectedness as a protective factor for adolescent injury, and the development of school connectedness as a component of an injury prevention program. To date, school-based risk taking and injury prevention has frequently been limited to addressing adolescents' knowledge and attitudes to risk behaviours, and has largely overlooked the importance of the wider school social context as a protective factor in adolescent development. Additionally, school connectedness has been primarily studied in terms of its impact on student achievement, wellbeing and risk taking behaviour, and research has not yet addressed possible links with injury. Further, school connectedness intervention programs have targeted risk taking behaviours without evaluating their potential impact on injury outcomes. This is the first reported research to develop strategies to increase school connectedness as part of a school-based injury prevention program. The research program was conceptualised as three distinct stages. The development of these research stages was informed by a comprehensive review of the literature on adolescent risk taking, injury and school-based prevention, as well as on school connectedness and its importance in adolescence. A review of the school connectedness literature indicated that students' connectedness is largely influenced by relationships within the school context including with teachers and other school staff, and is therefore a potentially modifiable factor that may be targeted in school-based programs. Overall, the literature shows school connectedness to be a key protective factor in adolescent development. This review established a foundation from which the current program of research was designed. The first stage of the research involved an empirical investigation of the relationship between adolescent risk taking-related injuries and school connectedness. Stage one incorporated two studies. The first involved the development of a measure of adolescent injury, the Extended Adolescent Injury Checklist (E-AIC), for use in the current research as well as in future school-based studies and program evaluation. The results of this study also highlighted the extent of the problem of risk-related injury in adolescence. The second study in Stage one examined the relationship between students' reports of school connectedness, risk taking behaviour and risk taking-related injuries on the E-AIC. The results of this study showed significant relationships between increased school connectedness and reduced reported engagement in transport and violence risk taking, and fewer associated injuries. This study therefore suggested the potential for school-based injury prevention programs to incorporate strategies targeting increased adolescent connectedness to school. The second stage of this research involved the compilation of an evidence base to inform the design of a school connectedness intervention. Stage two also incorporated two studies. The first study in Stage two involved a systematic review of programs that have targeted school connectedness for reduced risk taking and injury. The results of this study revealed that interventions targeting school connectedness can be effective in reducing adolescent risk taking behaviour, and also provided an evidence base for the design of the current school connectedness intervention. The second study in Stage two examined teachers' understanding and perceptions of school connectedness. This qualitative study indicated that teachers consider students' connectedness to be an important factor that relates to their risk taking behaviour; and also provided directions and content for the intervention design stage. The third stage of this research built upon the findings of each of the previous studies, and involved the design, implementation and evaluation of a school connectedness intervention as a component of an adolescent injury prevention program, Skills for Preventing Injury in Youth (SPIY). This connectedness intervention was designed as a professional development workshop for teachers of 13 to 14 year old adolescents, and was developed as a complementary component to the curriculum-based SPIY program. The SPIY connectedness component was implemented and evaluated using process and six-month impact evaluation methodologies. The results of this study revealed that teachers saw value in the program and made use of the strategies presented, and that program school students' self-reported violence risk behaviour was reduced at six-month follow-up. Despite these promising findings, the results of this study did not demonstrate a significant impact of the program on change in students' connectedness to school, relative to comparison schools. The positive impact on self-reported violence risk behaviour was however replicated in additional analyses comparing students participating in the connectedness version of SPIY with students participating in an earlier curriculumonly version of the program. This finding indicated that the connectedness component has additional benefits relating to reduction in violence risks, over and above a curriculum-only version of the program. This research was the first reported to address the relationship between school connectedness and adolescent injury outcomes, and to develop school connectedness as a component of an adolescent injury prevention program. Overall, the results of this program of research have demonstrated the importance of incorporating strategies targeting the wider school social context, including school connectedness, in adolescent injury prevention programs. This research has important implications for future research and practice in adolescent injury prevention.

Testing the psychometric properties of the Brisbane Practice Environment Measure using Exploratory Factor Analysis and Confirmatory Factor Analysis in an Australian registered nurse population

A cross-sectional survey was conducted, and the construct validity and reliability of the Brisbane Practice Environment Measure in an Australian sample of registered nurses were examined. Nurses were randomly selected from the database of an Australian nursing organization. The original 33 items of the Brisbane Practice Environment Measure were utilized to inform the psychometric properties using confirmatory factor analysis. The Cronbach's alpha was 0.938 for the total scale and ranged 0.657–0.887 for the subscales. A five-factor structure of the measure was confirmed, χ2 = 944.622, (P < 0.01), χ2/d.f. ratio = 2.845, Tucker Lewis Index 0.929, Root Mean Square Error = 0.061 and Comparative Fit Index = 0.906. The selected 28 items of the measure proved reliable and valid in measuring effects of the practice environment upon Australian nurses. The implications are that regular measurement of the practice environment using these 28 items might assist in the development of strategies which might improve job satisfaction and retention of registered nurses in Australia.

Two stage unity power factor rectifier design

This paper presents the design process utilised for producing a two stage isolated Unity Power Factor (UPF) rectifier. The important yet less intuitive aspects of the design process are highlighted to aid in the simplification of designing a power converter which meets future UPF standards. Two converter designs are presented, a 200W converter utilising a critical conduction controller and a 750W converter based around a continuous conduction controller. Both designs presented were based on the requirements of an audio power amplifier, but the processes apply equally to a range of applications.

Multi-converter topology evaluation for connection of low voltage DC sources

A design for a cascaded multilevel DC-DC converter is proposed. The applications of a multilevel converter and the design issues involved in changing from a single converter to multiple converters are discussed. Implementation of the multilevel system using multiple Cuk converters is suggested and explanations of design decisions are given. The merits of the proposed design are discussed.

A transcription factor map as revealed by a genome-wide gene expression analysis of whole-blood mRNA transcriptome in multiple sclerosis

Background Several lines of evidence suggests that transcription factors are involved in the pathogenesis of Multiple Sclerosis (MS) but a complete mapping the whole network has been elusive. One of the reasons is that there are several clinical subtypes of MS and transcription factors which may be involved in one subtype may not be in others. We investigated the possibility that this network could be mapped using microarray technologies and modern bioinformatics methods on a dataset from whole blood in 99 untreated MS patients (36 Relapse Remitting MS, 43 Primary Progressive MS, and 20 Secondary Progressive MS) and 45 age-matched healthy controls, Methodology/Principal Findings We have used two different analytical methodologies: a differential expression analysis and a differential co-expression analysis, which have converged on a significant number of regulatory motifs that seem to be statistically overrepresented in genes which are either differentially expressed (or differentially co-expressed) in cases and controls (e.g. V$KROX_Q6, p-value < 3.31E-6; V$CREBP1_Q2, p-value < 9.93E-6, V$YY1_02, p-value < 1.65E-5). Conclusions/significance: Our analysis uncovered a network of transcription factors that potentially dysregulate several genes in MS or one or more of its disease subtypes. Analysing the published literature we have found that these transcription factors are involved in the early T-lymphocyte specification and commitment as well as in oligodendrocytes dedifferentiation and development. The most significant transcription factors motifs were for the Early Growth response EGR/KROX family, ATF2, YY1 (Yin and Yang 1), E2F-1/DP-1 and E2F-4/DP-2 heterodimers, SOX5, and CREB and ATF families.

A fuzzy TOPSIS based multi criteria performance measurement model for lean supply chain

Increasing global competition, rapid technological changes, advances in manufacturing and information technology and discerning customers are forcing supply chains to adopt improvement practices that enable them to deliver high quality products at a lower cost and in a shorter period of time. A lean initiative is one of the most effective approaches toward achieving this goal. In the lean improvement process, it is critical to measure current and desired performance level in order to clearly evaluate the lean implementation efforts. Many attempts have tried to measure supply chain performance incorporating both quantitative and qualitative measures but failed to provide an effective method of measuring improvements in performances for dynamic lean supply chain situations. Therefore, the necessity of appropriate measurement of lean supply chain performance has become imperative. There are many lean tools available for supply chains; however, effectiveness of a lean tool depends on the type of the product and supply chain. One tool may be highly effective for a supply chain involved in high volume products but may not be effective for low volume products. There is currently no systematic methodology available for selecting appropriate lean strategies based on the type of supply chain and market strategy This thesis develops an effective method to measure the performance of supply chain consisting of both quantitative and qualitative metrics and investigates the effects of product types and lean tool selection on the supply chain performance Supply chain performance matrices and the effects of various lean tools over performance metrics mentioned in the SCOR framework have been investigated. A lean supply chain model based on the SCOR metric framework is then developed where non- lean and lean as well as quantitative and qualitative metrics are incorporated in appropriate metrics. The values of appropriate metrics are converted into triangular fuzzy numbers using similarity rules and heuristic methods. Data have been collected from an apparel manufacturing company for multiple supply chain products and then a fuzzy based method is applied to measure the performance improvements in supply chains. Using the fuzzy TOPSIS method, which chooses an optimum alternative to maximise similarities with positive ideal solutions and to minimise similarities with negative ideal solutions, the performances of lean and non- lean supply chain situations for three different apparel products have been evaluated. To address the research questions related to effective performance evaluation method and the effects of lean tools over different types of supply chains; a conceptual framework and two hypotheses are investigated. Empirical results show that implementation of lean tools have significant effects over performance improvements in terms of time, quality and flexibility. Fuzzy TOPSIS based method developed is able to integrate multiple supply chain matrices onto a single performance measure while lean supply chain model incorporates qualitative and quantitative metrics. It can therefore effectively measure the improvements for supply chain after implementing lean tools. It is demonstrated that product types involved in the supply chain and ability to select right lean tools have significant effect on lean supply chain performance. Future study can conduct multiple case studies in different contexts.

Algorithm clustering for multi-algorithm processor design

An Application Specific Instruction-set Processor (ASIP) is a specialized processor tailored to run a particular application/s efficiently. However, when there are multiple candidate applications in the application’s domain it is difficult and time consuming to find optimum set of applications to be implemented. Existing ASIP design approaches perform this selection manually based on a designer’s knowledge. We help in cutting down the number of candidate applications by devising a classification method to cluster similar applications based on the special-purpose operations they share. This provides a significant reduction in the comparison overhead while resulting in customized ASIP instruction sets which can benefit a whole family of related applications. Our method gives users the ability to quantify the degree of similarity between the sets of shared operations to control the size of clusters. A case study involving twelve algorithms confirms that our approach can successfully cluster similar algorithms together based on the similarity of their component operations.

Multi-wall carbon nanotube coating of fluorine-doped tin oxide as an electrode surface modifier for polymer solar cells

A controlled layer of multi-wall carbon nanotubes (MWCNT) was grown directly on top of fluorine-doped tin oxide (FTO) glass electrodes as a surface modifier for improving the performance of polymer solar cells. By using low-temperature chemical vapor deposition with short synthesis times, very short MWCNTs were grown, these uniformly decorating the FTO surface. The chemical vapor deposition parameters were carefully refined to balance the tube size and density, while minimizing the decrease in conductivity and light harvesting of the electrode. As created FTO/CNT electrodes were applied to bulk-heterojunction polymer solar cells, both in direct and inverted architecture. Thanks to the inclusion of MWCNT and the consequent nano-structuring of the electrode surface, we observe an increase in external quantum efficiency in the wavelength range from 550 to 650 nm. Overall, polymer solar cells realized with these FTO/CNT electrodes attain power conversion efficiency higher than 2%, outclassing reference cells based on standard FTO electrodes.

Premonolayer oxidation of nanostructured gold : an important factor influencing electrocatalytic activity

The study of the electrodeposition of polycrystalline gold in aqueous solution is important from the viewpoint that in electrocatalysis applications ill-defined micro- and nanostructured surfaces are often employed. In this work, the morphology of gold was controlled by the electrodeposition potential and the introduction of Pb(CH3COO)2•3H2O into the plating solution to give either smooth or nanostructured gold crystallites or large dendritic structures which have been characterized by scanning electron microscopy (SEM). The latter structures were achieved through a novel in situ galvanic replacement of lead with AuCl4−(aq) during the course of gold electrodeposition. The electrochemical behavior of electrodeposited gold in the double layer region was studied in acidic and alkaline media and related to electrocatalytic performance for the oxidation of hydrogen peroxide and methanol. It was found that electrodeposited gold is a significantly better electrocatalyst than a polished gold electrode; however, performance is highly dependent on the chosen deposition parameters. The fabrication of a deposit with highly active surface states, comparable to those achieved at severely disrupted metal surfaces through thermal and electrochemical methods, does not result in the most effective electrocatalyst. This is due to significant premonolayer oxidation that occurs in the double layer region of the electrodeposited gold. In particular, in alkaline solution, where gold usually shows the most electrocatalytic activity, these active surface states may be overoxidized and inhibit the electrocatalytic reaction. However, the activity and morphology of an electrodeposited film can be tailored whereby electrodeposited gold that exhibits nanostructure within the crystallites on the surface demonstrated enhanced electrocatalytic activity compared to smaller smooth gold crystallites and larger dendritic structures in potential regions well within the double layer region.

Food and Brisbane households : dietary, social and health consequences of food insecurity

Background & Aims: Access to sufficient amounts of safe and culturally-acceptable foods is a fundamental human right. Food security exists when all people, at all times, have physical, social, and economic access to sufficient, safe and nutritious food to meet their dietary needs and food preferences for an active and healthy life. Food insecurity therefore occurs when the availability or access to sufficient amounts of nutritionally-adequate, culturally-appropriate and safe foods, or, the ability to acquire such foods in socially-acceptable ways, is limited. Food insecurity may result in significant adverse effects for the individual and these outcomes may vary between adults and children. Among adults, food insecurity may be associated with overweight or obesity, poorer self-rated general health, depression, increased health-care utilisation and dietary intakes less consistent with national recommendations. Among children, food insecurity may result in poorer self or parent-reported general health, behavioural problems, lower levels of academic achievement and poor social outcomes. The majority of research investigating the potential correlates of food insecurity has been undertaken in the United States (US), where regular national screening for food insecurity is undertaken using a comprehensive multi-item measurement. In Australia, screening for food insecurity takes place on a three yearly basis via the use of a crude, single-item included in the National Health Survey (NHS). This measure has been shown to underestimate the prevalence of food insecurity by 5%. From 1995 – 2004, the prevalence of food insecurity among the Australian population remained stable at 5%. Due to the perceived low prevalence of this issue, screening for food insecurity was not undertaken in the most recent NHS. Furthermore, there are few Australian studies investigating the potential determinants of food insecurity and none investigating potential outcomes among adults and children. This study aimed to examine these issues by a) investigating the prevalence of food insecurity among households residing in disadvantaged urban areas and comparing prevalence rates estimated by the more comprehensive 18-item and 6-item United States Department of Agriculture (USDA) Food Security Survey Module (FSSM) to those estimated by the current single-item measure used for surveillance in Australia and b) investigating the potential determinants and outcomes of food insecurity, Methods: A comprehensive literature review was undertaken to investigate the potential determinants and consequences of food insecurity among developed countries. This was followed by a cross-sectional study in which 1000 households from the most disadvantaged 5% of Brisbane areas were sampled and data collected via mail-based survey (final response rate = 53%, n = 505). Data were collected for food security status, sociodemographic characteristics (household income, education, age, gender, employment status, housing tenure and living arrangements), fruit and vegetable intakes, meat and take-away consumption, presence of depressive symptoms, presence of chronic disease and body mass index (BMI) among adults. Among children, data pertaining to BMI, parent-reported general health, days away from school and activities and behavioural problems were collected. Rasch analysis was used to investigate the psychometric properties of the 18-, 10- and 6-item adaptations of the USDA-FSSM, and McNemar's test was used to investigate the difference in the prevalence of food insecurity as measured by these three adaptations compared to the current single-item measure used in Australia. Chi square and logistic regression were used to investigate the differences in dietary and health outcomes among adults and health and behavioural outcomes among children. Results were adjusted for equivalised household income and, where necessary, for indigenous status, education and family type. Results: Overall, 25% of households in these urbanised-disadvantaged areas reported experiencing food insecurity; this increased to 34% when only households with children were analysed. The current reliance on a single-item measure to screen for food insecurity may underestimate the true burden among the Australian population, as this measure was shown to significantly underestimate the prevalence of food insecurity by five percentage points. Internationally, major potential determinants of food insecurity included poverty and indicators of poverty, such as low-income, unemployment and lower levels of education. Ethnicity, age, transportation and cooking and financial skills were also found to be potential determinants of food insecurity. Among Australian adults in disadvantaged urban areas, food insecurity was associated with a three-fold increase in experiencing poorer self-rated general health and a two-to-five-fold increase in the risk of depression. Furthermore, adults from food insecure households were twoto- three times more likely to have seen a general practitioner and/or been admitted to hospital within the previous six months, compared to their food secure counterparts. Weight status and intakes of fruits, vegetables and meat were not associated with food insecurity. Among Australian households with children, those in the lowest tertile were over 16 times more likely to experience food insecurity compared to those in the highest tertile for income. After adjustment for equivalised household income, children from food insecure households were three times more likely to have missed days away from school or other activities. Furthermore, children from food insecure households displayed a two-fold increase in atypical emotions and behavioural difficulties. Conclusions: Food insecurity is an important public health issue and may contribute to the burden on the health care system through its associations with depression and increased health care utilisation among adults and behavioural and emotional problems among children. Current efforts to monitor food insecurity in Australia do not occur frequently and use a tool that may underestimate the prevalence of food insecurity. Efforts should be made to improve the regularity of screening for food insecurity via the use of a more accurate screening measure. Most of the current strategies that aim to alleviate food insecurity do not sufficiently address the issue of insufficient financial resources for acquiring food; a factor which is an important determinant of food insecurity. Programs to address this issue should be developed in collaboration with groups at higher risk of developing food insecurity and should incorporate strategies to address the issue of low income as a barrier to food acquisition.

Particle Swarm algorithm with Fuzzy decision making for a multi-objective economic and environmental optimization of design of a thermal system

Multi-Objective optimization for designing of a benchmark cogeneration system known as CGAM cogeneration system has been performed. In optimization approach, the thermoeconomic and Environmental aspects have been considered, simultaneously. The environmental objective function has been defined and expressed in cost terms. One of the most suitable optimization techniques developed using a particular class of search algorithms known as; Multi-Objective Particle Swarm Optimization (MOPSO) algorithm has been used here. This approach has been applied to find the set of Pareto optimal solutions with respect to the aforementioned objective functions. An example of fuzzy decision-making with the aid of Bellman-Zadeh approach has been presented and a final optimal solution has been introduced.