Evaluating MPPT converter topologies using a MATLAB PV model

An accurate PV module electrical model is presented based on the Shockley diode equation. The simple model has a photo-current current source, a single diode junction and a series resistance, and includes temperature dependences. The method of parameter extraction and model evaluation in Matlab is demonstrated for a typical 60W solar panel. This model is used to investigate the variation of maximumpower point with temperature and insolation levels. A comparison of buck versus boostmaximum power point tracker (MPPT) topologies is made, and compared with a direct connection to a constant voltage (battery) load. The boost converter is shown to have a slight advantage over the buck, since it can always track the maximum power point.

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.

Fluid-structure interaction analysis of full scale vehicle-barrier impact using coupled SPH-FEA

Portable water-filled barriers (PWFB) are roadside structures used to separate moving traffic from work-zones. Numerical PWFB modelling is preferred in the design stages prior to actual testing. This paper aims to study the fluid-structure interaction of PWFB under vehicular impact using several methods. The strategy to treat water as non-structural mass was proposed and the errors were investigated. It was found that water can be treated with the FEA-NSM model for velocities higher than 80kmh-1. However, full SPH/FEA model is still the best treatment for water and necessary for lower impact velocities. The findings in this paper can be used as guidelines for modelling and designing PWFB.

"You’ve modelled and now what?" : Exploring determinants of process model re-use

Business process modelling as a practice and research field has received great attention over recent years. Organizations invest significantly into process modelling in terms of training, tools, capabilities and resources. The return on this investment is a function of process model re-use, which we define as the recurring use of process models to support organizational work tasks. While prior research has examined re-use as a design principle, we explore re-use as a behaviour, because evidence suggest that analysts’ re-use of process models is indeed limited. In this paper we develop a two-stage conceptualization of the key object-, behaviour- and socioorganization-centric factors explaining process model re-use behaviour. We propose a theoretical model and detail implications for its operationalization and measurement. Our study can provide significant benefits to our understanding of process modelling and process model use as key practices in analysis and design.

A model for research supervision of international students in engineering and information technology disciplines

A large proportion (over 12 per cent) of international and non-English speaking background (NESB) postgraduate research students enrol in engineering and information technology (IT) programs in Australian universities. They find themselves in an advanced research culture, and are technically and scientifically challenged early in their programs. This is in addition to cultural, social and religious isolation and linguistic barriers they have to contend with. The project team surveyed this cohort at QUT and UWA, on the hypothesis that they face challenges that are more discipline-specific. The results of the survey indicate that existing supervisory frameworks which are limited to linguistic contexts are not fully assisting these students and supervisors to achieve high quality research. The goal of this project is to extend these supervisory frameworks to a holistic model that will address the unique needs and supervisory issues these students face in engineering and IT disciplines. The model will be useable by all other Australian universities.

A biological staging model for operable non-small cell lung cancer

Background Currently the best prognostic index for operable non-small cell lung cancer (NSCLC) is the TNM staging system. Molecular biology holds the promise of predicting outcome for the individual patient and identifying novel therapeutic targets. Angiogenesis, matrix metalloproteinases (MMP)-2 and -9, and the erb/HER type I tyrosine kinase receptors are all implicated in the pathogenesis of NSCLC. Methods A retrospective analysis of 167 patients with resected stage I-IIIa NSCLC and >60 days postoperative survival with a minimum follow up of 2 years was undertaken. Immunohistochemical analysis was performed on paraffin embedded sections for the microvessel marker CD34, MMP-2 and MMP-9, EGFR, and c-erbB-2 to evaluate the relationships between and impact on survival of these molecular markers. Results Tumour cell MMP-9 (HR 1.91 (1.23-2.97)), a high microvessel count (HR 1.97 (1.28-3.03)), and stage (stage II HR 1.44 (0.87-2.40), stage IIIa HR 2.21 (1.31-3.74)) were independent prognostic factors. Patients with a high microvessel count and tumour cell MMP-9 expression had a worse outcome than cases with only one (HR 1.68 (1.04-2.73)) or neither (HR 4.43 (2.29-8.57)) of these markers. EGFR expression correlated with tumour cell MMP-9 expression (p<0.001). Immunoreactivity for both of these factors within the same tumour was associated with a poor prognosis (HR 2.22 (1.45-3.41)). Conclusion Angiogenesis, EGFR, and MMP-9 expression provide prognostic information independent of TNM stage, allowing a more accurate outcome prediction for the individual patient. The development of novel anti-angiogenic agents, EGFR targeted therapies, and MMP inhibitors suggests that target specific adjuvant treatments may become a therapeutic option in patients with resected NSCLC.

Characterisation of a human skin equivalent model to study the effects of ultraviolet B radiation on keratinocytes

The incidences of skin cancers resulting from chronic ultraviolet radiation (UVR) exposure are on the incline both in Australia and globally. Hence, the cellular and molecular pathways associated with UVR-induced photocarcinogenesis urgently need to be elucidated, in order to develop more robust preventative and treatment strategies against skin cancers. In vitro investigations into the effects of UVR (in particular the highly-mutagenic UVB wavelength) have, to date, mainly involved the use of cell culture and animal models. However, these models possess biological disparities to native skin, which to some extent have limited their relevance to the in vivo situation. To address this, we characterised a 3-dimensional, tissue-engineered human skin equivalent (HSE) model (consisting of primary human keratinocytes cultured on a dermal-derived scaffold) as a representation of a more physiologically-relevant platform to study keratinocyte responses to UVB. Significantly, we demonstrate that this model retains several important epidermal properties of native skin. Moreover, UVB-irradiation of the HSE constructs was shown to induce key markers of photodamage in the HSE keratinocytes, including the formation of cyclobutane pyrimidine dimers, the activation of apoptotic pathways, the accumulation of p53 and the secretion of inflammatory cytokines. Importantly, we also demonstrate that the UVB-exposed HSE constructs retain the capacity for epidermal repair and regeneration following photodamage. Together, our results demonstrate the potential of this skin equivalent model as a tool to study various aspects of the acute responses of human keratinocytes to UVB radiation damage.

Developing a model of links between general and workplace belongingness and depressive symptoms

Given the high prevalence of depression in the community there is urgent need to understand the interpersonal predictors of this disorder. Data from large community samples indicates that a diminished sense of belonging appears to be the most salient and immediate antecedent of a rapid depressive response. Belongingness in the workplace is also very important and associated with depressive symptoms over and above associations attributable to general or community belongingness. Finally it appears that the personality factor of interpersonal sensitivity moderates the relationship between belongingness and depressive symptoms. Results have extensive future implications for the prevention and treatment of depression.

Plasmodium vivax malaria incidence over time and its association with temperature and rainfall in four counties of Yunnan Province, China

Background Transmission of Plasmodium vivax malaria is dependent on vector availability, biting rates and parasite development. In turn, each of these is influenced by climatic conditions. Correlations have previously been detected between seasonal rainfall, temperature and malaria incidence patterns in various settings. An understanding of seasonal patterns of malaria, and their weather drivers, can provide vital information for control and elimination activities. This research aimed to describe temporal patterns in malaria, rainfall and temperature, and to examine the relationships between these variables within four counties of Yunnan Province, China. Methods Plasmodium vivax malaria surveillance data (1991–2006), and average monthly temperature and rainfall were acquired. Seasonal trend decomposition was used to examine secular trends and seasonal patterns in malaria. Distributed lag non-linear models were used to estimate the weather drivers of malaria seasonality, including the lag periods between weather conditions and malaria incidence. Results There was a declining trend in malaria incidence in all four counties. Increasing temperature resulted in increased malaria risk in all four areas and increasing rainfall resulted in increased malaria risk in one area and decreased malaria risk in one area. The lag times for these associations varied between areas. Conclusions The differences detected between the four counties highlight the need for local understanding of seasonal patterns of malaria and its climatic drivers.

Forging the synergy between anticipation and innovation : the futures action model

This paper presents the theory and practice of the Futures Action Model (FAM). FAM has been in development for over a decade, in a number of contexts and iterations. It is a creative methodology that uses a variety of concepts and tools to guide participants through the conception and modeling of enterprises, services, social innovations and projects in the context of emerging futures. It is used to generate strategic options that people can utilise to build opportunities for value creation as they move into the future. This paper details examples in its development, and provides theoretical and practical guidelines for educators and business facilitators to use the FAM system in their own workplaces.

Conservative surgical debridement as a burn treatment : supporting evidence from a porcine burn model

In thermal deep-dermal burns, surgical debridement is normally used in conjunction with skin grafting or skin substitutes and debridement alone as a burn treatment is not usually practiced. The current study addresses whether or not debridement alone would enhance burn wound healing on small deep-dermal-partial thickness burns. This was a prospective and blinded experimental trial using a porcine deep-dermal-partial thickness burn model. Four burns, approximately 50 cm(2) in size, were created on each of eight pigs. Two burns from each pig were immediately surgically debrided and the other two were not debrided as the internal control. Hydrate gel together with paraffin gauze were used to cover the burns for four pigs and silver dressings for the other four. Clinical assessment of wound healing was conducted over a 6-week period. Skin samples were collected at the end of the experiment and histopathological evaluation was performed. The results show thinner scar formation and lower scar height in the debrided compared with nondebrided wounds in the hydrate gel/paraffin gauze groups. There were no statistically significant differences in wound healing assessment between the debrided and nondebrided wounds dressed with silver dressings. This study provides supporting evidence that immediate debridement with an appropriate dressing and without skin grafting may promote wound healing, suggesting its potential benefit for clinical patients.

The development of a carrying capacity assessment model for the Australian socio-environmental context

A key aim of this research was to highlight how society's understanding of constraints to the productive capacity of its resource base is vital to its long-term survival. This was achieved through the development of an online model, the Carrying Capacity Dashboard. The Dashboard was developed to estimate how much land Australian populations require for the production of their food, textiles, timber and liquid fuel. Findings reveal that Australia's estimated carrying capacity is currently over 40 million people but longer-term and more regional analyses suggest a much smaller number. Carrying capacity assessment also indicates that optimal resource security is to be found in balancing both small and large-scale self-sufficiency.

Thromboxane synthase expression and correlation with VEGF and angiogenesis in non-small cell lung cancer

Background Thromboxane synthase (TXS) metabolizes prostaglandin H2 into thromboxanes, which are biologically active on cancer cells. TXS over-expression has been reported in a range of cancers, and associated with angiogenesis and poor outcome. TXS has been identified as a potential therapeutic target in NSCLC. This study examines a link between TXS expression, angiogenesis, and survival in NSCLC. Methods TXS and VEGF metabolite levels were measured in NSCLC serum samples (n=46) by EIA. TXB2 levels were correlated with VEGF. A 204-patient TMA was stained for TXS, VEGF, and CD-31 expression. Expression was correlated with a range of clinical parameters, including overall survival. TXS expression was correlated with VEGF and CD-31. Stable TXS clones were generated and the effect of overexpression on tumor growth and angiogenesis markers was examined in-vitro and in-vivo (xenograft mouse model). Results Serum TXB2 levels were correlated with VEGF (p<0.05). TXS and VEGF were expressed to a varying degree in NSCLC tissue. TXS was associated with VEGF (p<0.0001) and microvessel density (CD-31; p<0.05). TXS and VEGF expression levels were higher in adenocarcinoma (p<0.0001) and female patients (p<0.05). Stable overexpression of TXS increased VEGF secretion in-vitro. While no significant association with patient survival was observed for either TXS or VEGF in our patient cohort, TXS overexpression significantly (p<0.05) increased tumor growth in-vivo. TXS overexpression was also associated with higher levels of VEGF, microvessel density, and reduced apoptosis in xenograft tumors. Conclusion TXS promotes tumor growth in-vivo in NSCLC, an effect which is at least partly mediated through increased tumor angiogenesis.

The mouse model of Chlamydia genital tract infection: a review of infection, disease, immunity and vaccine development

Chlamydia trachomatis is the most common sexually transmitted bacterial infection worldwide. The impact of this pathogen on human reproduction has intensified research efforts to better understand chlamydial infection and pathogenesis. Whilst there are animal models available that mimic the many aspects of human chlamydial infection, the mouse is regarded as the most practical and widely used of the models. Studies in mice have greatly contributed to our understanding of the host-pathogen interaction and provided an excellent medium for evaluating vaccines. Here we explore the advantages and disadvantages of all animal models of chlamydial genital tract infection, with a focus on the murine model and what we have learnt from it so far.

An Artificial Neutral Network (ANN) model for predicting biodiesel kinetic viscosity as a function of temperature and chemical compositions

An Artificial Neural Network (ANN) is a computational modeling tool which has found extensive acceptance in many disciplines for modeling complex real world problems. An ANN can model problems through learning by example, rather than by fully understanding the detailed characteristics and physics of the system. In the present study, the accuracy and predictive power of an ANN was evaluated in predicting kinetic viscosity of biodiesels over a wide range of temperatures typically encountered in diesel engine operation. In this model, temperature and chemical composition of biodiesel were used as input variables. In order to obtain the necessary data for model development, the chemical composition and temperature dependent fuel properties of ten different types of biodiesels were measured experimentally using laboratory standard testing equipments following internationally recognized testing procedures. The Neural Networks Toolbox of MatLab R2012a software was used to train, validate and simulate the ANN model on a personal computer. The network architecture was optimised following a trial and error method to obtain the best prediction of the kinematic viscosity. The predictive performance of the model was determined by calculating the absolute fraction of variance (R2), root mean squared (RMS) and maximum average error percentage (MAEP) between predicted and experimental results. This study found that ANN is highly accurate in predicting the viscosity of biodiesel and demonstrates the ability of the ANN model to find a meaningful relationship between biodiesel chemical composition and fuel properties at different temperature levels. Therefore the model developed in this study can be a useful tool in accurately predict biodiesel fuel properties instead of undertaking costly and time consuming experimental tests.