Plant-made therapeutics: An emerging platform in South Africa

The field of plant-made therapeutics in South Africa is well established in the form of exploitation of the country's considerable natural plant diversity, both in the use of native plants in traditional herbal medicines over many centuries, and in the more modern extraction of pharmacologically-active compounds from plants, including those known to traditional healers. In recent years, this has been added to by the use of plants for the stable or transient expression of pharmaceutically-important compounds, largely protein-based biologics and vaccines. South Africa has a well-developed plant biotechnology community, as well as a comprehensive legislative framework for the regulation of the exploitation of local botanic resources, and of genetically-modified organisms. The review explores the investigation of both conventional and recombinant plants for pharmaceutical use in South Africa, as well as describing the relevant legislative and regulatory frameworks. Potential opportunities for national projects, as well as factors limiting biopharming in South Africa are discussed. © 2011.

Forging the heteroglossic citizen : articulating local, national, regional and global horizons in the Australian Curriculum

This article offers a discourse analysis comparing selected articles in the national press over the consultative period for Phase 1 subjects in the new Australian Curriculum, with rationales prefacing official Australian Curriculum Assessment and Reporting Authority documents. It traces how various versions of Australia, its ‘nation-ness’ and its future citizens have been taken up in the final product. The analysis uses Lemke's analytic elaboration of Bakhtin's concept of heteroglossia and its derivative, intertextuality. It identifies a range of intertextual thematic formations around ‘nation’, ‘history’, ‘citizen’ and ‘curriculum’ circulating in the public debates, then traces their presence in official curriculum documents. Rather than concluding that these themes are contradictory and incoherent, the conclusion asks how these multiple dialogic facets of Australian nation-ness potentially offer a better response to complex times than any coherent monologic orthodoxy might.

Spatial and temporal analysis of Barmah Forest virus disease in Queensland, Australia

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.

An index of best practice performance reporting for Malaysian local authorities

Abstract Purpose – The purpose of this paper is to identify stakeholders’ expectations of information to be conveyed in local authorities’ annual reports and to develop an index of best practice performance reporting. Design/methodology/approach – The paper describes the development of a disclosure index emphasizing the public interest aspect of reporting and the need to provide relevant and meaningful information to stakeholders. The index was crafted from a public accountability perspective and based on the expectations of stakeholders as reconciled and validated by a Delphi panel of experts. Findings – The wide scope of information that was dentified as being important for disclosure by local authorities is consistent with the public accountability paradigm which requires the reporting of comprehensive information (both financial and non financial), about the condition, performance, activities and progress of the entity. Originality/value – The research posits a model of best practice performance reporting for Malaysian, and other, local authorities to meet the need for greater accountability by these entities.

Broadband today : the role of Australian local government authorities

The paper seeks to clarify the role of Local Government Authorities in facilitating the Australian digital economy. It does this by analysing responses to the 2012 BTA, NBN and Digital Economy Survey. This reveals the level of recognition by LGAs of relevant issues; their level of use of federal, state and other programs designed to enable end user engagement; and other actions LGAs are undertaking to enable their regional digital economies. The analysis reinforces the significant role of LGAs in the future of Australia’s digital economy and identifies areas where assistance may be required.

Diversification for sustainable development in rural and regional Australia : how local community leaders conceptualise the impacts and opportunities from agriculture, tourism and mining

Although the multiple economic, environmental and social challenges threatening the viability of rural and regional communities in Australia are well-known, little research has explored how community leaders conceptualise the impact and opportunities associated with economic diversification from agriculture into alternative industries, such as tourism and mining. This qualitative research, utilising the Darling Downs in Queensland as a case study, documents how 28 local community leaders have experienced this economic diversification process. The findings reveal that local community leaders have a deep understanding about the opportunities and challenges presented by diversification, articulating a clear vision about how to achieve the best possible future for their region. Despite excitement about growth, there were concerns about preserving heritage, the increased pressure on local infrastructure and an ageing population. By documenting local leader’s insights, these findings may help inform planning for rural and regional communities and facilitate management of the exciting yet challenging process of growth and diversification

The roles of procedural justice and social learning in improving self organizing capabilities of local communities for sustainable development in decentralized Indonesia

The development planning process under Law No. 25/2004 is said to be a new approach to increase public participation in decentralised Indonesia. This Law has introduced planning mechanisms, called Musyawarah Perencanaan Pembangunan (Musrenbang), to provide a forum for development planning. In spite of the expressed intention of these mechanisms to improve public participation, some empirical observations have cast doubt on the outcomes. As a result, some local governments have tried to provide alternative mechanisms to promote for participation in local development planning. Since planning is often said to be one of the most effective ways to improve community empowerment, it is of particular concern, to examine the extent to which the current local development planning processes in Indonesia provide sufficient opportunities to improve the self organising capabilities of communities to sustain development programs to meet local needs. With this objective in mind, this paper examines problems encountered by the new local planning mechanism (Musrenbang) in increasing local community empowerment particularly regarding their self organising capabilities. The concept of community empowerment as a pathway to social justice is explored to identify its key elements and approaches and to show how they can be incorporated within planning processes. Having discussed this, it is then argued that to change current unfavorable outcomes, procedural justice and social learning approaches need to be adopted as pathways to community empowerment. Lastly it is also suggested that an alternative local planning process, called Sistem Dukungan (SISDUK), introduced in South Suluwezi in collaboration with JAICA in 2006 (?) offers scope to incorporate such procedural justice and social learning approaches to improve the self organizing capabilities of local communities.

Delineating the practice profile of advanced practice nursing : a cross-sectional survey using the modified strong model of advanced practice

AIMS: To test a model that delineates advanced practice nursing from the practice profile of other nursing roles and titles. BACKGROUND: There is extensive literature on advanced practice reporting the importance of this level of nursing to contemporary health service and patient outcomes. Literature also reports confusion and ambiguity associated with advanced practice nursing. Several countries have regulation and delineation for the nurse practitioner, but there is less clarity in definition and service focus of other advanced practice nursing roles. DESIGN: A statewide survey. METHODS: Using the modified Strong Model of Advanced Practice Role Delineation tool, a survey was conducted in 2009 with a random sample of registered nurses/midwives from government facilities in Queensland, Australia. Analysis of variance compared total and subscale scores across groups according to grade. Linear, stepwise multiple regression analysis examined factors influencing advanced practice nursing activities across all domains. RESULTS: There were important differences according to grade in mean scores for total activities in all domains of advanced practice nursing. Nurses working in advanced practice roles (excluding nurse practitioners) performed more activities across most advanced practice domains. Regression analysis indicated that working in clinical advanced practice nursing roles with higher levels of education were strong predictors of advanced practice activities overall. CONCLUSION: Essential and appropriate use of advanced practice nurses requires clarity in defining roles and practice levels. This research delineated nursing work according to grade and level of practice, further validating the tool for the Queensland context and providing operational information for assigning innovative nursing service.

Mixed convection along a vertical flat plate in a non-absorbing medium

Here mixed convection boundary layer flow of a viscous fluid along a heated vertical semi-infinite plate is investigated in a non-absorbing medium. The relationship between convection and thermal radiation is established via boundary condition of second kind on the thermally radiating vertical surface. The governing boundary layer equations are transformed into dimensionless parabolic partial differential equations with the help of appropriate transformations and the resultant system is solved numerically by applying straightforward finite difference method along with Gaussian elimination technique. It is worthy to note that Prandlt number, Pr, is taken to be small (<< 1) which is appropriate for liquid metals. Moreover, the numerical results are demonstrated graphically by showing the effects of important physical parameters, namely, the modified Richardson number (or mixed convection parameter), Ri*, and surface radiation parameter, R, in terms of local skin friction and local Nusselt number coefficients.

Kernel analysis on Grassmann manifolds for action recognition

Modelling video sequences by subspaces has recently shown promise for recognising human actions. Subspaces are able to accommodate the effects of various image variations and can capture the dynamic properties of actions. Subspaces form a non-Euclidean and curved Riemannian manifold known as a Grassmann manifold. Inference on manifold spaces usually is achieved by embedding the manifolds in higher dimensional Euclidean spaces. In this paper, we instead propose to embed the Grassmann manifolds into reproducing kernel Hilbert spaces and then tackle the problem of discriminant analysis on such manifolds. To achieve efficient machinery, we propose graph-based local discriminant analysis that utilises within-class and between-class similarity graphs to characterise intra-class compactness and inter-class separability, respectively. Experiments on KTH, UCF Sports, and Ballet datasets show that the proposed approach obtains marked improvements in discrimination accuracy in comparison to several state-of-the-art methods, such as the kernel version of affine hull image-set distance, tensor canonical correlation analysis, spatial-temporal words and hierarchy of discriminative space-time neighbourhood features.

Retrieving information from microblog using pattern mining and relevance feedback

Retrieving information from Twitter is always challenging due to its large volume, inconsistent writing and noise. Most existing information retrieval (IR) and text mining methods focus on term-based approach, but suffers from the problems of terms variation such as polysemy and synonymy. This problem deteriorates when such methods are applied on Twitter due to the length limit. Over the years, people have held the hypothesis that pattern-based methods should perform better than term-based methods as it provides more context, but limited studies have been conducted to support such hypothesis especially in Twitter. This paper presents an innovative framework to address the issue of performing IR in microblog. The proposed framework discover patterns in tweets as higher level feature to assign weight for low-level features (i.e. terms) based on their distributions in higher level features. We present the experiment results based on TREC11 microblog dataset and shows that our proposed approach significantly outperforms term-based methods Okapi BM25, TF-IDF and pattern based methods, using precision, recall and F measures.

Investigation of ternary zirconia ceramics

Transformation toughening ceramics (TTCs) are engineering materials which combine ceramic properties such as hardness, corrosion resistance and low thermal conductivity with good toughness and mechanical strength. At elevated temperatures their use is limited due to destabilisation of the transformation toughening microstructure (partially stabilised zirconia or PSZ) or creep and hydrothermal degradation (tetragonal zirconia polycrystals or TZPs). Despite these limitations, the use of TTCs, particularly zirconia based, has become widespread. To date, most commercial TTCs are based on combinations of zirconia and one stabilising oxide. This work investigates a zirconia ceramic containing two stabilisers, namely yttria and titania in roughly equal proportions.

Advanced battery storage control for an autonomous microgrid

A new control method for battery storage to maintain acceptable voltage profile in autonomous microgrids is proposed in this article. The proposed battery control ensures that the bus voltages in the microgrid are maintained during disturbances such as load change, loss of micro-sources, or distributed generations hitting power limit. Unlike the conventional storage control based on local measurements, the proposed method is based on an advanced control technique, where the reference power is determined based on the voltage drop profile at the battery bus. An artificial neural network based controller is used to determine the reference power needed for the battery to hold the microgrid voltage within regulation limits. The pattern of drop in the local bus voltage during power imbalance is used to train the controller off-line. During normal operation, the battery floats with the local bus voltage without any power injection. The battery is charged or discharged during the transients with a high gain feedback loop. Depending on the rate of voltage fall, it is switched to power control mode to inject the reference power determined by the proposed controller. After a defined time period, the battery power injection is reduced to zero using slow reverse-droop characteristics, ensuring a slow rate of increase in power demand from the other distributed generations. The proposed control method is simulated for various operating conditions in a microgrid with both inertial and converter interfaced sources. The proposed battery control provides a quick load pick up and smooth load sharing with the other micro-sources in a disturbance. With various disturbances, maximum voltage drop over 8% with conventional energy storage is reduced within 2.5% with the proposed control method.

Optimal power system stabilizer tuning in multi-machine system via an improved differential evolution

Power system stabilizer (PSS) is one of the most important controllers in modern power systems for damping low frequency oscillations. Many efforts have been dedicated to design the tuning methodologies and allocation techniques to obtain optimal damping behaviors of the system. Traditionally, it is tuned mostly for local damping performance, however, in order to obtain a globally optimal performance, the tuning of PSS needs to be done considering more variables. Furthermore, with the enhancement of system interconnection and the increase of system complexity, new tools are required to achieve global tuning and coordination of PSS to achieve optimal solution in a global meaning. Differential evolution (DE) is a recognized as a simple and powerful global optimum technique, which can gain fast convergence speed as well as high computational efficiency. However, as many other evolutionary algorithms (EA), the premature of population restricts optimization capacity of DE. In this paper, a modified DE is proposed and applied for optimal PSS tuning of 39-Bus New-England system. New operators are introduced to reduce the probability of getting premature. To investigate the impact of system conditions on PSS tuning, multiple operating points will be studied. Simulation result is compared with standard DE and particle swarm optimization (PSO).

Value added products from modified kaolins : new chemical routes to new markets

Chemical treatments of kaolins to produce nanocrystalline or "X-ray amorphous", stable aluminosilicates with variable - but reproducible - types of micro- and meso-porosity have been developed. These materials show cation exchange capacities and surface area values significantly higher (ranging from 10x to 100x) than kaolin and show good acid resistance to pH~3.0. The combination of these properties offers strong potential for many new applications of kaolin-derived materials in large worldwide markets such as environmental remediation and catalysis. Kaolin amorphous derivative (KAD) is well-suited to removal of many toxic metals down to ppb range from acid mine drainage. Engineering development trials of the KAD manufacturing process and the utilisation of KAD in polluted waters such as acid mine drainage indicates that scale-up from bench-scale is not a barrier to market entry.