981 resultados para BREEDING SYSTEMS


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Diabetic foot ulcers are one of the most hospitalised diabetes complications and contribute to many leg amputations. Trained diabetic foot teams and specialists managing diabetic foot ulcers have demonstrated reductions in amputations and hospitalisation by up to 90%. Few such teams exist in Australia. Thus, access is limited for all geographical populations and may somewhat explain the high rates of hospitalisation. Aim: This pilot study aims to analyse if local clinicians managing diabetic foot complications report improved access to diabetic foot specialists and outcomes with the introduction of a telehealth store-and-forward system. Method: A store-and-forward telehealth system was implemented in six different Queensland locations between August 2009 and February 2010. Sites were offered ad hoc and/or fortnightly telehealth access to a diabetic foot speciality service. A survey was sent six months following commencement of the trial to the 14 eligible clinicians involved in the trial to gauge clinical perception of the telehealth system. Results: Eight participants returned the surveys. The majority of responding clinicians reported that the telehealth system was easy to use (100%), improved their access to diabetic foot speciality services (75%), improved upskilling of local diabetes service staff (100%), and improved patient outcomes (100%). Conclusion: This pilot study suggests that clinicians found the use of a telehealth store-and-forward system very useful in improving access to speciality services, clinical skills and patient outcomes. This study supports the recommendation that telehealth systems should be made available for diabetic foot ulcer management.

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This paper studies time integration methods for large stiff systems of ordinary differential equations (ODEs) of the form u'(t) = g(u(t)). For such problems, implicit methods generally outperform explicit methods, since the time step is usually less restricted by stability constraints. Recently, however, explicit so-called exponential integrators have become popular for stiff problems due to their favourable stability properties. These methods use matrix-vector products involving exponential-like functions of the Jacobian matrix, which can be approximated using Krylov subspace methods that require only matrix-vector products with the Jacobian. In this paper, we implement exponential integrators of second, third and fourth order and demonstrate that they are competitive with well-established approaches based on the backward differentiation formulas and a preconditioned Newton-Krylov solution strategy.

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Building prefabrication is known as Industrialised Building Systems (IBS) in Malaysia. This construction method possesses unique characteristics that are central to sustainable construction. For example, offsite construction enables efficient management of construction wastage by identifying major causes of waste arising during both the design and construction stages. These causes may then be eliminated by the improvement process in IBS component's manufacturing. However, current decisions on using IBS are typically financial driven and hinder the wider ranged adoption. In addition, current IBS misconceptions and the failure of rating schemes in evaluating the sustainability of IBS affect its implementation. A new approach is required to provide better understanding on the sustainability potential of IBS among stakeholders. Such approach should also help project the outcomes of each levels of decision-making to respond to social, economy and environmental challenges. This paper presents interim findings of research aimed at developing a framework for sustainable IBS development and suggests a more holistic approach to achieve sustainability. A framework of embedding sustainability factors is considered in three main phases of IBS construction; 1) Pre-construction, 2) Construction and 3) Post-construction phase. SWOT analysis was used to evaluate the strengths, weaknesses, opportunities and threats involved in the IBS implementations. The action plans are formulated from the analysis of sustainable objectives. This approach will show where and how sustainability should be integrated to improve IBS construction. A mix of quantitative and qualitative methodology was used in this research to explore the potential of IBS in integrating sustainability. The tools used in the study are questionnaires and semi-structured interviews. Outcomes from these tools lead to the identification of viable approaches involving 18 critical factors to improve sustainability in IBS constructions. Finally, guidelines for decision-making are being developed to provide a useful source of information and support to mutual benefit of the stakeholders in integrating sustainability issues and concepts into IBS applications.

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In this paper, we present the outcomes of a project on the exploration of the use of Field Programmable Gate Arrays(FPGAs) as co-processors for scientific computation. We designed a custom circuit for the pipelined solving of multiple tri-diagonal linear systems. The design is well suited for applications that require many independent tri diagonal system solves, such as finite difference methods for solving PDEs or applications utilising cubic spline interpolation. The selected solver algorithm was the Tri Diagonal Matrix Algorithm (TDMA or Thomas Algorithm). Our solver supports user specified precision thought the use of a custom floating point VHDL library supporting addition, subtraction, multiplication and division. The variable precision TDMA solver was tested for correctness in simulation mode. The TDMA pipeline was tested successfully in hardware using a simplified solver model. The details of implementation, the limitations, and future work are also discussed.

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Barmah Forest virus (BFV) disease is one of the most widespread mosquito-borne diseases in Australia. The number of outbreaks and the incidence rate of BFV in Australia have attracted growing concerns about the spatio-temporal complexity and underlying risk factors of BFV disease. A large number of notifications has been recorded continuously in Queensland since 1992. Yet, little is known about the spatial and temporal characteristics of the disease. I aim to use notification data to better understand the effects of climatic, demographic, socio-economic and ecological risk factors on the spatial epidemiology of BFV disease transmission, develop predictive risk models and forecast future disease risks under climate change scenarios. Computerised data files of daily notifications of BFV disease and climatic variables in Queensland during 1992-2008 were obtained from Queensland Health and Australian Bureau of Meteorology, respectively. Projections on climate data for years 2025, 2050 and 2100 were obtained from Council of Scientific Industrial Research Organisation. Data on socio-economic, demographic and ecological factors were also obtained from relevant government departments as follows: 1) socio-economic and demographic data from Australian Bureau of Statistics; 2) wetlands data from Department of Environment and Resource Management and 3) tidal readings from Queensland Department of Transport and Main roads. Disease notifications were geocoded and spatial and temporal patterns of disease were investigated using geostatistics. Visualisation of BFV disease incidence rates through mapping reveals the presence of substantial spatio-temporal variation at statistical local areas (SLA) over time. Results reveal high incidence rates of BFV disease along coastal areas compared to the whole area of Queensland. A Mantel-Haenszel Chi-square analysis for trend reveals a statistically significant relationship between BFV disease incidence rates and age groups (ƒÓ2 = 7587, p<0.01). Semi-variogram analysis and smoothed maps created from interpolation techniques indicate that the pattern of spatial autocorrelation was not homogeneous across the state. A cluster analysis was used to detect the hot spots/clusters of BFV disease at a SLA level. Most likely spatial and space-time clusters are detected at the same locations across coastal Queensland (p<0.05). The study demonstrates heterogeneity of disease risk at a SLA level and reveals the spatial and temporal clustering of BFV disease in Queensland. Discriminant analysis was employed to establish a link between wetland classes, climate zones and BFV disease. This is because the importance of wetlands in the transmission of BFV disease remains unclear. The multivariable discriminant modelling analyses demonstrate that wetland types of saline 1, riverine and saline tidal influence were the most significant risk factors for BFV disease in all climate and buffer zones, while lacustrine, palustrine, estuarine and saline 2 and saline 3 wetlands were less important. The model accuracies were 76%, 98% and 100% for BFV risk in subtropical, tropical and temperate climate zones, respectively. This study demonstrates that BFV disease risk varied with wetland class and climate zone. The study suggests that wetlands may act as potential breeding habitats for BFV vectors. Multivariable spatial regression models were applied to assess the impact of spatial climatic, socio-economic and tidal factors on the BFV disease in Queensland. Spatial regression models were developed to account for spatial effects. Spatial regression models generated superior estimates over a traditional regression model. In the spatial regression models, BFV disease incidence shows an inverse relationship with minimum temperature, low tide and distance to coast, and positive relationship with rainfall in coastal areas whereas in whole Queensland the disease shows an inverse relationship with minimum temperature and high tide and positive relationship with rainfall. This study determines the most significant spatial risk factors for BFV disease across Queensland. Empirical models were developed to forecast the future risk of BFV disease outbreaks in coastal Queensland using existing climatic, socio-economic and tidal conditions under climate change scenarios. Logistic regression models were developed using BFV disease outbreak data for the existing period (2000-2008). The most parsimonious model had high sensitivity, specificity and accuracy and this model was used to estimate and forecast BFV disease outbreaks for years 2025, 2050 and 2100 under climate change scenarios for Australia. Important contributions arising from this research are that: (i) it is innovative to identify high-risk coastal areas by creating buffers based on grid-centroid and the use of fine-grained spatial units, i.e., mesh blocks; (ii) a spatial regression method was used to account for spatial dependence and heterogeneity of data in the study area; (iii) it determined a range of potential spatial risk factors for BFV disease; and (iv) it predicted the future risk of BFV disease outbreaks under climate change scenarios in Queensland, Australia. In conclusion, the thesis demonstrates that the distribution of BFV disease exhibits a distinct spatial and temporal variation. Such variation is influenced by a range of spatial risk factors including climatic, demographic, socio-economic, ecological and tidal variables. The thesis demonstrates that spatial regression method can be applied to better understand the transmission dynamics of BFV disease and its risk factors. The research findings show that disease notification data can be integrated with multi-factorial risk factor data to develop build-up models and forecast future potential disease risks under climate change scenarios. This thesis may have implications in BFV disease control and prevention programs in Queensland.

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Dengue fever is one of the world’s most important vector-borne diseases. The transmission area of this disease continues to expand due to many factors including urban sprawl, increased travel and global warming. Current preventative techniques are primarily based on controlling mosquito vectors as other prophylactic measures, such as a tetravalent vaccine are unlikely to be available in the foreseeable future. However, the continually increasing dengue incidence suggests that this strategy alone is not sufficient. Epidemiological models attempt to predict future outbreaks using information on the risk factors of the disease. Through a systematic literature review, this paper aims at analyzing the different modeling methods and their outputs in terms of accurately predicting disease outbreaks. We found that many previous studies have not sufficiently accounted for the spatio-temporal features of the disease in the modeling process. Yet with advances in technology, the ability to incorporate such information as well as the socio-environmental aspect allowed for its use as an early warning system, albeit limited geographically to a local scale.

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EHealth systems promise enviable benefits and capabilities for healthcare. But, the technologies that make these capabilities possible brings with them undesirable drawback such as information security related threats which need to be appropriately addressed. Lurking in these threats are patient privacy concerns. Fulfilling these privacy concerns have proven to be difficult since they often conflict with information requirements of care providers. It is important to achieve a proper balance between these requirements. We believe that information accountability can achieve this balance. In this paper we introduce accountable-eHealth systems. We will discuss how our designed protocols can successfully address the aforementioned requirement. We will also compare characteristics of AeH systems with Australia’s PCEHR system and identify similarities and highlight the differences and the impact those differences would have to the eHealth domain.

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Information privacy requirements of patients and information requirements of healthcare providers (HCP) are competing concerns. Reaching a balance between these requirements have proven difficult but is crucial for the success of eHealth systems. The traditional approaches to information management have been preventive measures which either allow or deny access to information. We believe that this approach is inappropriate for a domain such as healthcare. We contend that introducing information accountability (IA) to eHealth systems can reach the aforementioned balance without the need for rigid information control. IA is a fairly new concept to computer science, hence; there are no unambiguously accepted principles as yet. But the concept delivers promising advantages to information management in a robust manner. Accountable-eHealth (AeH) systems are eHealth systems which use IA principles as the measure for privacy and information management. AeH systems face three main impediments; technological, social and ethical and legal. In this paper, we present the AeH model and focus on the legal aspects of AeH systems in Australia. We investigate current legislation available in Australia regarding health information management and identify future legal requirements if AeH systems are to be implemented in Australia.

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Given the importance of water for rice production, this study examines the factors affecting the technical efficiency (TE) of irrigated rice farmers in village irrigation systems (VIS) in Sri Lanka. Primary data were collected from 460 rice farmers in the Kurunagala District, Sri Lanka, to estimate a stochastic translog production frontier for rice production. The mean TE of rice farming in village irrigation was found to be 0.72, although 63% of rice farmers exceeded this average. The most influential factors of TE are membership of Farmer Organisations (FOs) and the participatory rate in collective actions organised by FOs. The results suggest that enhancement of co-operative arrangements of farmers by strengthening the membership of FOs is considered important for increasing TE in rice farming in VIS.

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With the progressive exhaustion of fossil energy and the enhanced awareness of environmental protection, more attention is being paid to electric vehicles (EVs). Inappropriate siting and sizing of EV charging stations could have negative effects on the development of EVs, the layout of the city traffic network, and the convenience of EVs' drivers, and lead to an increase in network losses and a degradation in voltage profiles at some nodes. Given this background, the optimal sites of EV charging stations are first identified by a two-step screening method with environmental factors and service radius of EV charging stations considered. Then, a mathematical model for the optimal sizing of EV charging stations is developed with the minimization of total cost associated with EV charging stations to be planned as the objective function and solved by a modified primal-dual interior point algorithm (MPDIPA). Finally, simulation results of the IEEE 123-node test feeder have demonstrated that the developed model and method cannot only attain the reasonable planning scheme of EV charging stations, but also reduce the network loss and improve the voltage profile.

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This paper proposes a new approach for state estimation of angles and frequencies of equivalent areas in large power systems with synchronized phasor measurement units. Defining coherent generators and their correspondent areas, generators are aggregated and system reduction is performed in each area of inter-connected power systems. The structure of the reduced system is obtained based on the characteristics of the reduced linear model and measurement data to form the non-linear model of the reduced system. Then a Kalman estimator is designed for the reduced system to provide an equivalent dynamic system state estimation using the synchronized phasor measurement data. The method is simulated on two test systems to evaluate the feasibility of the proposed method.

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In recent years there has been a large emphasis placed on the need to use Learning Management Systems (LMS) in the field of higher education, with many universities mandating their use. An important aspect of these systems is their ability to offer collaboration tools to build a community of learners. This paper reports on a study of the effectiveness of an LMS (Blackboard©) in a higher education setting and whether both lecturers and students voluntarily use collaborative tools for teaching and learning. Interviews were conducted with participants (N=67) from the faculties of Science and Technology, Business, Health and Law. Results from this study indicated that participants often use Blackboard© as an online repository of learning materials and that the collaboration tools of Blackboard© are often not utilised. The study also found that several factors have inhibited the use and uptake of the collaboration tools within Blackboard©. These have included structure and user experience, pedagogical practice, response time and a preference for other tools.

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To enhance workplace safety in the construction industry it is important to understand interrelationships among safety risk factors associated with construction accidents. This study incorporates the systems theory into Heinrich’s domino theory to explore the interrelationships of risks and break the chain of accident causation. Through both empirical and statistical analyses of 9,358 accidents which occurred in the U.S. construction industry between 2002 and 2011, the study investigates relationships between accidents and injury elements (e.g., injury type, part of body, injury severity) and the nature of construction injuries by accident type. The study then discusses relationships between accidents and risks, including worker behavior, injury source, and environmental condition, and identifies key risk factors and risk combinations causing accidents. The research outcomes will assist safety managers to prioritize risks according to the likelihood of accident occurrence and injury characteristics, and pay more attention to balancing significant risk relationships to prevent accidents and achieve safer working environments.

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Destruction of cancer cells by genetically modified viral and nonviral vectors has been the aim of many research programs. The ability to target cytotoxic gene therapies to the cells of interest is an essential prerequisite, and the treatment has always had the potential to provide better and more long-lasting therapy than existing chemotherapies. However, the potency of these infectious agents requires effective testing systems, in which hypotheses can be explored both in vitro and in vivo before the establishment of clinical trials in humans. The real prospect of off-target effects should be eliminated in the preclinical stage, if current prejudices against such therapies are to be overcome. In this review we have set out, using adenoviral vectors as a commonly used example, to discuss some of the key parameters required to develop more effective testing, and to critically assess the current cellular models for the development and testing of prostate cancer biotherapy. Only by developing models that more closely mirror human tissues will we be able to translate literature publications into clinical trials and hence into acceptable alternative treatments for the most commonly diagnosed cancer in humans.

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In this paper, we present the outcomes of a project on the exploration of the use of Field Programmable Gate Arrays (FPGAs) as co-processors for scientific computation. We designed a custom circuit for the pipelined solving of multiple tri-diagonal linear systems. The design is well suited for applications that require many independent tri-diagonal system solves, such as finite difference methods for solving PDEs or applications utilising cubic spline interpolation. The selected solver algorithm was the Tri-Diagonal Matrix Algorithm (TDMA or Thomas Algorithm). Our solver supports user specified precision thought the use of a custom floating point VHDL library supporting addition, subtraction, multiplication and division. The variable precision TDMA solver was tested for correctness in simulation mode. The TDMA pipeline was tested successfully in hardware using a simplified solver model. The details of implementation, the limitations, and future work are also discussed.