Paradigm shift to enhanced water supply planning through augmented grids, scarcity pricing and adaptive factory water : a system dynamics approach

This paper details a system dynamics model developed to simulate proposed changes to water governance through the integration of supply, demand and asset management processes. To effectively accomplish this, interconnected feedback loops in tariff structures, demand levels and financing capacity are included in the model design, representing the first comprehensive life-cycle modelling of potable water systems. A number of scenarios were applied to Australia's populated South-east Queensland region, demonstrating that introducing temporary drought pricing (i.e. progressive water prices set inverse with availability), in conjunction with supply augmentation through rain-independent sources, is capable of efficiently providing water security in the future. Modelling demonstrated that this alternative tariff structure reduced demand in scarcity periods thereby preserving supply, whilst revenues are maintained to build new water supply infrastructure. In addition to exploring alternative tariffs, the potential benefits of using adaptive pressure-retarded osmosis desalination plants for both potable water and power generation was explored. This operation of these plants for power production, when they would otherwise be idle, shows promise in reducing their net energy and carbon footprints. Stakeholders in industry, government and academia were engaged in model development and validation. The constructed model displays how water resource systems can be reorganised to cope with systemic change and uncertainty.

Predicting avian distributions to evaluate spatiotemporal overlap with locust control operations in eastern Australia.

Locusts and grasshoppers cause considerable economic damage to agriculture worldwide. The Australian Plague Locust Commission uses multiple pesticides to control locusts in eastern Australia. Avian exposure to agricultural pesticides is of conservation concern, especially in the case of rare and threatened species. The aim of this study was to evaluate the probability of pesticide exposure of native avian species during operational locust control based on knowledge of species occurrence in areas and times of application. Using presence-absence data provided by the Birds Australia Atlas for 1998 to 2002, we developed a series of generalized linear models to predict avian occurrences on a monthly basis in 0.5 degrees grid cells for 280 species over 2 million km2 in eastern Australia. We constructed species-specific models relating occupancy patterns to survey date and location, rainfall, and derived habitat preference. Model complexity depended on the number of observations available. Model output was the probability of occurrence for each species at times and locations of past locust control operations within the 5-year study period. Given the high spatiotemporal variability of locust control events, the variability in predicted bird species presence was high, with 108 of the total 280 species being included at least once in the top 20 predicted species for individual space-time events. The models were evaluated using field surveys collected between 2000 and 2005, at sites with and without locust outbreaks. Model strength varied among species. Some species were under- or over-predicted as times and locations of interest typically did not correspond to those in the prediction data set and certain species were likely attracted to locusts as a food source. Field surveys demonstrated the utility of the spatially explicit species lists derived from the models but also identified the presence of a number of previously unanticipated species. These results also emphasize the need for special consideration of rare and threatened species that are poorly predicted by presence-absence models. This modeling exercise was a useful a priori approach in species risk assessments to identify species present at times and locations of locust control applications, and to discover gaps in our knowledge and need for further focused data collection.

Classification of neural action potentials using mean shift clustering

 Understanding neural functions requires the observation of the activities of single neurons that are represented via electrophysiological data. Processing and understanding these data are challenging problems in biomedical engineering. A microelectrode commonly records the activity of multiple neurons. Spike sorting is a process of classifying every single action potential (spike) to a particular neuron. This paper proposes a combination between diffusion maps (DM) and mean shift clustering method for spike sorting. DM is utilized to extract spike features, which are highly capable of discriminating different spike shapes. Mean shift clustering provides an automatic unsupervised clustering, which takes extracted features from DM as inputs. Experimental results show a noticeable dominance of the features extracted by DM compared to those selected by wavelet transformation (WT). Accordingly, the proposed integrated method is significantly superior to the popular existing combination of WT and superparamagnetic clustering regarding spike sorting accuracy.

How do SMEs with single and multiple owners finance their operations differently? Empirical evidence from China

We study the impact of firm-level characteristics on the capital structures of private small and medium-sized enterprises (SMEs) as well as the differences between the capital structures adopted by SMEs with single and multiple owners in China. Our findings highlight the limited use of asset-based financing by Chinese SMEs. We also find that the propensity of SMEs with single-owners to use external debt was significantly less than those with multiple owners. Furthermore, our findings suggest that single-owned firms are subject to a more constrained pecking order than those with multiple owners.

How social work can contribute in the shift to personalised, recovery-oriented psycho-social disability support services

This paper presents the findings from an Australian study in which forty-one people, who self-identified as having a psycho-social disability as a result of mental health problems, spoke about their priorities for treatment, care and support within a personalised funding context. The research enabled an improved understanding of the choices about support that people with psycho-social disabilities would make if offered individualised funding packages. Participants prioritised specific supports to improve their health, financial situation, social connection, housing and personal relationships. A relationship with a support worker with a range of skills was identified as a key facilitator of these life goals, but people with psycho-social disabilities also valued opportunities to have discretionary funds to directly address the major problems they face, including stigma, discrimination and poverty. The paper argues that social workers can potentially fill a range of roles and are well placed to work in partnership with people with psycho-social disabilities. Particularly, they have skills in co-production of services, negotiation and advocacy that are required if individual funding is to be maximised for user control, social justice and personal recovery outcomes.

Complex simulation of stockyard mining operations

Conflicts between resources in stockyards cause mining companies millions of dollars a year. An effective planning strategy needs to be established in order to reduce these operational conflicts. In this research a stockyard simulation model of a mining operation is proposed. The simulation uses discrete event and continuous strategies to create a high detail level of visualization and animation that closely resemble actual stockyard operation. The proposed simulation model is tightly integrated with a stockpile planner and it is used to evaluate the feasibility of a given production plan. The high detail visualization of the simulation model allows planner to determine the source of conflict, which can be used to guide the elimination of these conflicts.

Sleep quantity and quality is not compromised during planned burn shifts of less than 12 h

Planned burning is a preventative strategy aimed at decreasing fuel loads to reduce the severity of future wildfire events. During planned burn operations, firefighters can work long shifts. Furthermore, remote burning locations may require firefighters to sleep away from home between shifts. The existing evidence surrounding firefighters' sleep during such operations is exclusively anecdotal. The aims of the study were to describe firefighters' sleep during planned burn operations and evaluate the impact of the key operational factors (shift start time, shift length and sleeping location) that may contribute to inadequate sleep. Thirty-three salaried firefighters were recruited from Australia's fire agencies and sleep was measured objectively using wrist actigraphy for four weeks. All variables were examined in two conditions: (1) burn days, and (2) non-burn days. Time in bed, total sleep time, sleep latency and sleep efficiency were evaluated objectively. Subjective reports of pre- and post-sleep fatigue, sleep location, sleep quality, sleep quantity, number of times woken and sleep timing were also recorded. Analyses revealed no differences in measures of sleep quantity and quality when comparing non-burn and burn days. Total sleep time was less when planned burn shifts were >12 h. However, on burn days, work shift start time as well as sleeping location did not impact firefighters' sleep quantity. Self-reported levels of pre- and post-sleep fatigue were greater on burn days compared to non-burn days. These findings indicate that sleep quantity and quality are not compromised during planned burn operations <12 h in duration.