A method for risk analysis across governance systems : a great barrier reef case study

Healthy governance systems are key to delivering sound environmental management outcomes from global to local scales. There are, however, surprisingly few risk assessment methods that can pinpoint those domains and sub-domains within governance systems that are most likely to influence good environmental outcomes at any particular scale, or those if absent or dysfunctional, most likely to prevent effective environmental management. This paper proposes a new risk assessment method for analysing governance systems. This method is then tested through its preliminary application to a significant real-world context: governance as it relates to the health of Australia's Great Barrier Reef (GBR). The GBR exists at a supra-regional scale along most of the north eastern coast of Australia. Brodie et al (2012 Mar. Pollut. Bull. 65 81-100) have recently reviewed the state and trend of the health of the GBR, finding that overall trends remain of significant concern. At the same time, official international concern over the governance of the reef has recently been signalled globally by the International Union for the Conservation of Nature (IUCN). These environmental and political contexts make the GBR an ideal candidate for use in testing and reviewing the application of improved tools for governance risk assessment. © 2013 IOP Publishing Ltd.

Hybrid genetic algorithm for elimination of severe stress concentration in railhead ends

This paper presents a computational method for eliminating severe stress concentration at the unsupported railhead ends in rail joints through innovative shape optimization of the contact zone, which is complex due to near field nonlinear contact. With a view to minimizing the computational efforts, hybrid genetic algorithm method coupled with parametric finite element has been developed and compared with the traditional genetic algorithm (GA). The shape of railhead top surface where the wheel contacts nonlinearly was optimized using the hybridized GA method. Comparative study of the optimal result and the search efficiency between the traditional and hybrid GA methods has shown that the hybridized GA provides the optimal shape in fewer computational cycles without losing accuracy. The method will be beneficial to solving complex engineering problems involving contact nonlinearity.

Physiological basis of salt stress tolerance in rice expressing the antiapoptotic gene SfIAP

Programmed cell death-associated genes, especially antiapoptosis-related genes have been reported to confer tolerance to a wide range of biotic and abiotic stresses in dicotyledonous plants such as tobacco (Nicotiana tabacum L.) and tomato (Solanum lycopersicum L.). This is the first time the antiapoptotic gene SfIAP was transformed into a monocotyledonous representative: rice (Oryza sativa L.). Transgenic rice strains expressing SfIAP were generated by the Agrobacterium-mediated transformation method and rice embryogenic calli, and assessed for their ability to confer tolerance to salt stress at both the seedling and reproductive stages using a combination of molecular, agronomical, physiological and biochemical techniques. The results show that plants expressing SfIAP have higher salt tolerance levels in comparison to the wild-type and vector controls. By preventing cell death at the onset of salt stress and maintaining the cell membrane’s integrity, SfIAP transgenic rice plants can retain plant water status, ion homeostasis, photosynthetic efficiency and growth to combat salinity successfully.

Physical activity recognition from accelerometer data using a multi-scale ensemble method

Accurate and detailed measurement of an individual's physical activity is a key requirement for helping researchers understand the relationship between physical activity and health. Accelerometers have become the method of choice for measuring physical activity due to their small size, low cost, convenience and their ability to provide objective information about physical activity. However, interpreting accelerometer data once it has been collected can be challenging. In this work, we applied machine learning algorithms to the task of physical activity recognition from triaxial accelerometer data. We employed a simple but effective approach of dividing the accelerometer data into short non-overlapping windows, converting each window into a feature vector, and treating each feature vector as an i.i.d training instance for a supervised learning algorithm. In addition, we improved on this simple approach with a multi-scale ensemble method that did not need to commit to a single window size and was able to leverage the fact that physical activities produced time series with repetitive patterns and discriminative features for physical activity occurred at different temporal scales.

A novel identification method for ultra trace detection of biomolecules using functionalised Surface Enhanced Raman Spectroscopy (SERS)

This thesis developed a new method for measuring extremely low amounts of organic and biological molecules, using Surface enhanced Raman Spectroscopy. This method has many potential applications, e.g. medical diagnosis, public health, food provenance, antidoping, forensics and homeland security. The method development used caffeine as the small molecule example, and erythropoietin (EPO) as the large molecule. This method is much more sensitive and specific than currently used methods; rapid, simple and cost effective. The method can be used to detect target molecules in beverages and biological fluids without the usual preparation steps.

Application of a hybrid Entropy–McKinsey Matrix method in evaluating sustainable urbanization : a China case study

Although urbanization can promote social and economic development, it can also cause various problems. As the key decision makers of urbanization, local governments should be able to evaluate urbanization performance, summarize experiences, and find problems caused by urbanization. This paper introduces a hybrid Entropy–McKinsey Matrix method for evaluating sustainable urbanization. The McKinsey Matrix is commonly referred to as the GE Matrix. The values of a development index (DI) and coordination index (CI) are calculated by employing the Entropy method and are used as a basis for constructing a GE Matrix. The matrix can assist in assessing sustainable urbanization performance by locating the urbanization state point. A case study of the city of Jinan in China demonstrates the process of using the evaluation method. The case study reveals that the method is an effective tool in helping policy makers understand the performance of urban sustainability and therefore formulate suitable strategies for guiding urbanization toward better sustainability.

Self-organized ZnO nanodot arrays : effective control using SiNx interlayers and low-temperature plasmas

An advanced inductively coupled plasma (ICP)-assisted rf magnetron sputtering deposition method is developed to synthesize regular arrays of pear-shaped ZnO nanodots on a thin SiNx buffer layer pre-deposited onto a silicon substrate. It is shown that the growth of ZnO nanodots obey the cubic root-law behavior. It is also shown that the synthesized ZnO nanodots are highly-uniform, controllable by the experimental parameters, and also feature good structural and photoluminescent properties. These results suggest that this custom-designed ICP-based technique is very effective and highly-promising for the synthesis of property- and size-controllable highly-uniform ZnO nanodots suitable for next-generation light emitting diodes, energy storage, UV nanolasers, and other applications.

E-mail in the workplace : the role of stress appraisals and normative response pressure in the relationship between email stressors and employee strain

In many organizations, e-mail is an effective and dominant workplace application tool; however, research identifying its role as a potential workplace stressor remains limited. Utilizing the Transactional Model of Stress (Lazarus & Folkman, 1984), 215 full-time administrative and academic staff at a university were surveyed about workplace e-mail. The aim was to study the effects of potential e-mail stressors on emotional exhaustion as mediated and moderated by person and situation variables. Results indicated that 2 distinct e-mail stressors—high quantity and poor quality (in terms of high emotionality and ambiguity) of workplace e-mail—were associated both with stress appraisals (e-mail overload and e-mail uncertainty) and with emotional exhaustion. Furthermore, the effects of the 2 e-mail stressors on emotional exhaustion were mediated by appraised e-mail overload. Perceived normative response pressure—a relevant aspect of the specific work environment—added to the explanation of emotional exhaustion and accentuated the positive effect of e-mail ambiguity on emotional exhaustion, although effects involving normative response pressure were not explained by the stress appraisals.

Ectopic overexpression of a mungbean vacuolar Na+/H+ antiporter gene (VrNHX1) leads to increased salinity stress tolerance in transgenic Vigna unguiculata L. Walp

Salinity is a major threat to sustainable agriculture worldwide. Plant NHX exchangers play an important role in conferring salt tolerance under salinity stress. In this study, a vacuolar Na+/H+ antiporter gene VrNHX1 (Genbank Accession No. JN656211.1) from mungbean (Vigna radiata) was introduced into cowpea (Vigna unguiculata) by the Agrobacterium tumefaciens-mediated transformation method. Polymerase chain reaction and Southern blot hybridization confirmed the stable integration of VrNHX1 into the cowpea genome. Comparative expression analysis by semi-quantitative RT-PCR revealed higher expression of VrNHX1 in transgenic cowpea plants than wild-type. Under salt stress conditions, T2 transgenic 35S:VrNHX1 cowpea lines exhibited higher tolerance to 200 mM NaCl treatment than wild-type. Furthermore, T2 transgenic 35S:VrNHX1 lines maintained a higher K+/Na+ ratio in the aerial parts under salt stress and accumulated higher [Na+] in roots than wild-type. Physiological analysis revealed lower levels of lipid peroxidation, hydrogen peroxide and oxygen radical production but higher levels of relative water content and proline, ascorbate and chlorophyll contents in T2 transgenic 35S:VrNHX1 lines.

Straminipilan protists : a study of their taxonomic position, morphology and abiotic stress-mediated gene expression

Thraustochytrids have become of considerable industrial and scientific interest in the past decade due to their health benefits. They have been proven to be the principle source in marine and estuarine fish diets with high percentage of long chain (LC) or polyunsaturated fatty acids (PUFA). Therefore, the oil extracted from fish for human document.forms[0].elements[13].select();consumption is rich in PUFA with high omega-3 fatty acid content. Docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA) of all of the omega-3 fatty acids, are considered beneficial essential oils for humans with a wide range of health benefits. These include brain and neural development in infants, general wellbeing of adults and drug delivery through precursor molecules. They have become one of the most extensively studied organisms for industrial oil preparations as PUFA extraction from fish becomes less profitable. Many forms of these Thraustochytrid oils are being trialled for human consumption all over the world. In Australia, there has been little research performed on these organisms in the past ten years. A few Australian studies have been conducted in the form of comparative studies related to PUFA production within the related genera, but not focussed on their identification or cellular and genomic characterisation. Therefore, the main aim of this study was to investigate the morphological and genetic characteristics of Australian Thraustochytrids in order to aid in their identification and characterisation, as well as to better understand the effect of environmental conditions in the regulation of PUFA production. It was also noted that there was a knowledge gap in the preservation and total genomic DNA extraction of these organisms for the purposes of scientific research. The cryopreservation of these organisms for studies around the world follows existing generic methods. However, it is well understood that many of these generic methods attract not only high costs for chemicals, but also uses considerable storage space and other resources, all of which can be improved with new or modified approaches. In this context, a simple and inexpensive bead preservation method is described, without compromising the storage shelf life. We also describe, for the first time, the effects of culture age on the successful cryopreservation of Thraustochytrids. It was evident in the literature that DNA and RNA extractions for molecular and genetic studies of Thraustochytrids follow the classical phenol-chloroform extraction methods. It was also observed that modern protocols failed to avoid the use of phenol-chloroform rather than improving preparation and cell disruption. In order to provide a high quantity and quality DNA extraction, a modified protocol has been introduced that employs the use of modern commercial extraction kits and standard laboratory equipment. Thraustochytrids have been shown to be highly conserved in their 18S rDNA gene sequences, which is used as the current standard for identification. It was demonstrated that the 18S rDNA gene sequence limits the recognition of closely related genera or within the genera from each member. Therefore, it was proposed that another profile, such as a randomly amplified polymorphic DNA (RAPD) based profiling system, be tested for use in the characterisation of Thraustochytrids. The RAPD profiles were shown to provide a unique DNA fingerprint for each isolate and small variations in their genome were able to be detected. This method involved the use of a minimum number of standard arbitrary primers and with an increase in the number of different primers used, a very high discrimination between organisms could be achieved. However, the method was not suitable for taxonomic purposes because the results did not correlate with other taxonomic features such as morphology. Another knowledge gap was found with respect to Australian Thraustochytrid growth characteristics, in that these had not been recorded and published. In order to rectify this, a record of colony and microscopic features of 12 selected isolates was performed. The results of preliminary studies indicated that further microbiological and biochemical studies are needed for full characterisation of these organisms. This information is of great importance to bio-prospecting of new Thraustochytrids from Australian ecosystems and would allow for their accurate identification, and so permit the prediction of their PUFA capability by comparison with related genera/species. It was well recognized that environmental stress plays a role in the PUFA production and is mainly due to the reactive oxygen species as abiotic stress (Chiou et al., 2001; Okuyama et al., 2008; Shabala et al., 2009; Shabala et al., 2001). In this aspect, this study makes the first attempt towards better understanding of this phenomenon by way of the use of real-time PCR for the detection of environmental effects on the regulation of PUFA production. Three main environmental conditions including temperature, pH and oxygen availability were monitored as stress inducers. In summary, this study provides novel approaches for the preservation and handling of Thraustochytrids, their molecular biological features, taxonomy, characterisation and responses to environmental factors with respect to their oil production enzymes. The information produced from this study will prove to be vital for both industrial and scientific investigations in the future.

High-yeld RNA-extraction method for saliva

BACKGROUND: The use of salivary diagnostics is increasing because of its noninvasiveness, ease of sampling, and the relatively low risk of contracting infectious organisms. Saliva has been used as a biological fluid to identify and validate RNA targets in head and neck cancer patients. The goal of this study was to develop a robust, easy, and cost-effective method for isolating high yields of total RNA from saliva for downstream expression studies. METHODS: Oral whole saliva (200 mu L) was collected from healthy controls (n = 6) and from patients with head and neck cancer (n = 8). The method developed in-house used QIAzol lysis reagent (Qiagen) to extract RNA from saliva (both cell-free supernatants and cell pellets), followed by isopropyl alcohol precipitation, cDNA synthesis, and real-time PCR analyses for the genes encoding beta-actin ("housekeeping" gene) and histatin (a salivary gland-specific gene). RESULTS: The in-house QIAzol lysis reagent produced a high yield of total RNA (0.89 -7.1 mu g) from saliva (cell-free saliva and cell pellet) after DNase treatment. The ratio of the absorbance measured at 260 nm to that at 280 nm ranged from 1.6 to 1.9. The commercial kit produced a 10-fold lower RNA yield. Using our method with the QIAzol lysis reagent, we were also able to isolate RNA from archived saliva samples that had been stored without RNase inhibitors at -80 degrees C for >2 years. CONCLUSIONS: Our in-house QIAzol method is robust, is simple, provides RNA at high yields, and can be implemented to allow saliva transcriptomic studies to be translated into a clinical setting.

Heartbeat and economic decisions : observing mental stress among proposers and responders in the ultimatum bargaining game

The ultimatum bargaining game (UBG), a widely used method in experimental economics, clearly demonstrates that motives other than pure monetary reward play a role in human economic decision making. In this study, we explore the behaviour and physiological reactions of both responders and proposers in an ultimatum bargaining game using heart rate variability (HRV), a small and nonintrusive technology that allows observation of both sides of an interaction in a normal experimental economics laboratory environment. We find that low offers by a proposer cause signs of mental stress in both the proposer and the responder; that is, both exhibit high ratios of low to high frequency activity in the HRV spectrum.

A novel tuning method for advanced line drop compensator and its application to response coordination of distributed generation with voltage regulating devices

Nowadays, integration of small-scale electricity generators, known as Distributed Generation (DG), into distribution networks has become increasingly popular. This tendency together with the falling price of DG units has a great potential in giving the DG a better chance to participate in voltage regulation process, in parallel with other regulating devices already available in the distribution systems. The voltage control issue turns out to be a very challenging problem for distribution engineers, since existing control coordination schemes need to be reconsidered to take into account the DG operation. In this paper, a control coordination approach is proposed, which is able to utilize the ability of the DG as a voltage regulator, and at the same time minimize the interaction of DG with another DG or other active devices, such as On-load Tap Changing Transformer (OLTC). The proposed technique has been developed based on the concepts of protection principles (magnitude grading and time grading) for response coordination of DG and other regulating devices and uses Advanced Line Drop Compensators (ALDCs) for implementation. A distribution feeder with tap changing transformer and DG units has been extracted from a practical system to test the proposed control technique. The results show that the proposed method provides an effective solution for coordination of DG with another DG or voltage regulating devices and the integration of protection principles has considerably reduced the control interaction to achieve the desired voltage correction.

Emotional effort and perceived support in renal nursing: A comparative interview study

Background: Social support is an important moderator of poor well-being outcomes for nurses engaged in emotional labour with patients; however, the most effective support for renal nurses is not well understood compared with other specialties. Objectives: To identify patterns and themes in how renal nurses and two other specialties engage with patients’ emotional expressions, express their own emotion and access and provide support for emotional expenditure. Method: Renal, emergency and palliative care nurses from Perth, Western Australia, were interviewed. Results: Renal nurses engage in significant amounts of emotional labour with patients, and identify co-workers as the most important source of support due to their availability and a sense of shared experience. However, comparative analysis showed that renal nurses do not recognise their emotional expenditure as readily and have less certainty of co-worker support. Conclusions: Because their high levels of emotional engagement with patients are mostly positive, renal nurses are less prepared than other nurses to manage difficult emotional situations. As co-worker support is highly valued, organisations should train renal nurses specifically to support one another.

Centroid training to achieve effective text classification

Traditional text classification technology based on machine learning and data mining techniques has made a big progress. However, it is still a big problem on how to draw an exact decision boundary between relevant and irrelevant objects in binary classification due to much uncertainty produced in the process of the traditional algorithms. The proposed model CTTC (Centroid Training for Text Classification) aims to build an uncertainty boundary to absorb as many indeterminate objects as possible so as to elevate the certainty of the relevant and irrelevant groups through the centroid clustering and training process. The clustering starts from the two training subsets labelled as relevant or irrelevant respectively to create two principal centroid vectors by which all the training samples are further separated into three groups: POS, NEG and BND, with all the indeterminate objects absorbed into the uncertain decision boundary BND. Two pairs of centroid vectors are proposed to be trained and optimized through the subsequent iterative multi-learning process, all of which are proposed to collaboratively help predict the polarities of the incoming objects thereafter. For the assessment of the proposed model, F1 and Accuracy have been chosen as the key evaluation measures. We stress the F1 measure because it can display the overall performance improvement of the final classifier better than Accuracy. A large number of experiments have been completed using the proposed model on the Reuters Corpus Volume 1 (RCV1) which is important standard dataset in the field. The experiment results show that the proposed model has significantly improved the binary text classification performance in both F1 and Accuracy compared with three other influential baseline models.