ALBERT

Description: Children’s favourite food and beverage brands use various tactics to foster positive associations and loyalty. This brand-consumer dynamic is frequently influenced by the use of implicit techniques and emotional appeals. Few studies have used physiological methods to examine the connections that brands build with children and the influence this has on their automatic responses. These techniques are potentially less prone to bias than behavioural or cognitive methods. This is the first study to explore the implicit response that children have to images of their favourite food and beverage brands using skin conductance responses as a marker of arousal. Australian children aged 8–11 years (n = 48) were recruited. Images of the participants’ favourite branded food and beverage products, alongside images of the same products unpackaged, their family and friends, and neutral objects were presented in a randomised order with a standard timed interval between images. Children were significantly more aroused by branded images of their favourite food and beverage products than by their unpackaged counterparts (p 〈 0.042, d = 0.4). The physiological response to the branded products was similar to the response to the children’s family and friends (p = 0.900, d = −0.02). These findings suggest that children may have an implicit connection to their favourite branded products.

Description: Children’s exposure to unhealthy food marketing is one factor contributing to childhood obesity. The impact of marketing on children’s weight likely occurs via a cascade pathway, through influences on children’s food brand awareness, emotional responses, purchasing and consumption. Thus, building emotional attachments to brands is a major marketing imperative. This study explored Australian children’s emotional attachments to food and drink brands and compared the strength of these attachments to their food marketing exposure, using television viewing as a proxy indicator. A cross-sectional face-to-face survey was conducted with 282 Australian children (8–12 years). Children were asked to indicate their agreement/disagreement with statements about their favourite food and drink brands, as an indicator of the strength and prominence of their brand attachments. Questions captured information about minutes/day of television viewing and the extent that they were exposed to advertising (watched live or did not skip through ads on recorded television). For those children who were exposed to advertisements, their age and commercial television viewing time had significant effects on food and drink brand attachments (p = 0.001). The development of brand attachments is an intermediary pathway through which marketing operates on behavioural and health outcomes. Reducing children’s exposure to unhealthy food marketing should be a policy priority for governments towards obesity and non-communicable disease prevention.

Description: Prior research explored reasons for tobacco use among pregnant Alaska Native (AN) women but did not address the postpartum period. This study followed up with AN women one to three years postpartum who had participated in a prenatal smoking cessation intervention study (Motivate Alaska Women (MAW) Phase 3) and had consented to be re-contacted for future studies. Of 47 eligible women, 32 (68%) participated. A semi-structured phone interview was conducted a mean of 2.0 years after delivery (range 1.6–2.8). Measures assessed self-reported tobacco use status in the 12 months after delivery, at 12 months postpartum, and at the time of the interview; reasons for maintaining abstinence, continued use, or relapse; and included the Perceived Stress Scale (PSS) and Negative Affect (NA) scale. Content analysis was used to generate themes from open-ended response items. Tobacco use was reported by 23 women (72%) at delivery, 30 (94%) within the 12 months after delivery, 27 (84%) at 12 months postpartum, and 29 (91%) at the time of the interview. Among nine women not using tobacco at delivery, seven (78%) relapsed during the 12 months after delivery. Of the 29 current tobacco users, 28 (97%) smoked cigarettes. Twenty-seven participants (84%) reported stress and 15 (52%) indicated addiction as reasons for continuing, starting, or resuming tobacco use. Types of stressors were related to parenting and traumatic experiences. Among current tobacco users, mean NA score (18.7) was significantly higher (p = 0.01) than the normative mean (14.8), but no differences were detected for PSS score. In this sample of AN women, postpartum tobacco use was highly prevalent, and stress was a primary reason that women endorsed for using tobacco. These preliminary results have several practice and research implications for exploring ways to support non-tobacco use among postpartum AN women.

Description: Tertiary recovery is directly dependent on the alteration in wettability and interfacial tension (IFT), hence releasing the trapped oil from rock pore spaces. Bio-surfactant water flooding to mobilise residual oil in reservoirs is a new and developing prospect that can be used more often in future due to its environmentally friendly nature and economic advantages. In this work, the impact of rhamnolipids as water soluble bio-surfactant solutions on the interfacial activities of saline water and the wettability of carbonate rock are studied at elevated temperature. The effectiveness of the bio-surfactant as a rock wettability modifier is analysed in the presence of different salinities, in particular SO42− ions. The reason for the focus on SO42− is its high affinity towards calcite surfaces, and hence its ability to intervene strongly on bio-surfactant performance. To achieve the objectives of this study, the oil-wet calcite samples at elevated temperature were put through a washing process that included bio-surfactant solutions in seawater at various concentrations of sodium sulphate ions, where the measurement of the contact angles of each sample after treatment and the IFT between the oil model and the washing solutions were taken. The obtained results illustrated that bio-surfactants (rhamnolipids) with incremental concentrations of SO42− ions in sea water (up to three times higher than the original ion concentration) can lower the IFT, and assessed changing the rocks towards greater water-wettability. This study reveals that the alteration of SO42− ions had a greater impact on the wettability alteration, whereas rhamnolipids were better at reducing the IFT between the oil phase and the aqueous phase. This study also looked at temperatures of 50 °C and 70 °C, which demonstrated undesired influences on the wettability and IFT. Bio-surfactants at high temperature showed less interfacial activity, thus indicating that rhamnolipids are not active at high temperatures, while the addition of SO42− shows a continuous decrease in the contact angle and IFT measurements at high temperature.

Description: The Landsat record represents an amazing resource for discovering land-cover changes and monitoring the Earth’s surface. However, making the most use of the available data, especially for automated applications ingesting thousands of images without human intervention, requires a robust screening of cloud and cloud-shadow, which contaminate clear views of the land surface. We constructed a deep convolutional neural network (CNN) model to semantically segment Landsat 8 images into regions labeled clear-sky, clouds, cloud-shadow, water, and snow/ice. For training, we constructed a global, hand-labeled dataset of Landsat 8 imagery; this labor-intensive process resulted in the uniquely high-quality dataset needed for the creation of a high-quality model. The CNN model achieves results on par with the ability of human interpreters, with a total accuracy of 97.1%, omitting only 3.5% of cloud pixels and 4.8% of cloud shadow pixels, which is seven to eight times fewer missed pixels than the masks distributed with the imagery. By harnessing the power of advanced tensor processing units, the classification of full images is I/O bound, making this approach a feasible method to generate masks for the entire Landsat 8 archive.

Description: Detailed vegetation maps are needed for wetland conservation and restoration as different vegetation communities have distinct water requirements. It is a continuous challenge to map the distribution of different wetland types on a regional scale, and a trade-off between the categorical details and availability of resources to ensure broad applications is often necessary for operational mapping. Here, we evaluated the capacity and performance of statistical learning in discriminating wetland types using Landsat time series and geomorphological variables computed from Light Detection and Ranging (LiDAR) and Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM). Our study showed that there was a discrimination limit of statistical learning in wetland mapping. The approach was clearly inadequate in distinguishing certain wetland types. In semiarid Australia, our results suggested that the appropriate level for floodplain wetland mapping included four classes: tree-dominated woodlands, shrublands, vegetated swamps, and non-flood-dependent terrestrial communities. Our results also demonstrated that the geomorphological metrics significantly improved the accuracy of wetland classification. Furthermore, geomorphological metrics derived from the freely available coarser resolution SRTM DEM were as beneficial for wetland mapping as those extracted from finer scale commercially-based LiDAR DEM. The finding enables the widespread applications of our approach, as both data sources are freely available globally.

Description: Epidemic thunderstorm asthma (ETA) is an emerging public health threat in Australia, highlighted by the 2016 event in Melbourne, Victoria, that overwhelmed health services and caused loss of life. However, there is limited understanding of the regional variations in risk. We evaluated the public health risk of ETA in the nearby state of Tasmania by quantifying the frequency of potential ETA episodes and applying a standardized natural disaster risk assessment framework. Using a case–control approach, we analyzed emergency presentations in Tasmania’s public hospitals from 2002 to 2017. Cases were defined as days when asthma presentations exceeded four standard deviations from the mean, and controls as days when asthma presentations were less than one standard deviation from the mean. Four controls were randomly selected for each case. Independently, a meteorologist identified the dates of potential high-risk thunderstorm events. No case days coincided with thunderstorms during the study period. ETA was assessed as a very low risk to the Tasmanian population, with these findings informing risk prioritization and resource allocation. This approach may be scaled and applied in other settings to determine local ETA risk. Furthermore, the identification of hazards using this method allows for critical analysis of existing public health systems.

Description: Transition matrices, containing credit risk information in the form of ratings based on discrete observations, are published annually by rating agencies. A substantial issue arises, as for higher rating classes practically no defaults are observed yielding default probabilities of zero. This does not always reflect reality. To circumvent this shortcoming, estimation techniques in continuous-time can be applied. However, raw default data may not be available at all or not in the desired granularity, leaving the practitioner to rely on given one-year transition matrices. Then, it becomes necessary to transform the one-year transition matrix to a generator matrix. This is known as the embedding problem and can be formulated as a nonlinear optimization problem, minimizing the distance between the exponential of a potential generator matrix and the annual transition matrix. So far, in credit risk-related literature, solving this problem directly has been avoided, but approximations have been preferred instead. In this paper, we show that this problem can be solved numerically with sufficient accuracy, thus rendering approximations unnecessary. Our direct approach via nonlinear optimization allows one to consider further credit risk-relevant constraints. We demonstrate that it is thus possible to choose a proper generator matrix with additional structural properties.

Description: Wildfire, a natural part of many ecosystems, has also resulted in significant disasters impacting ecology and human life in Australia. This study proposes a prototype of fire propagation prediction as an extension of preceding research; this system is called “Cloud computing based bushfire prediction”, the computational performance of which is expected to be about twice that of the traditional client-server (CS) model. As the first step in the modelling approach, this prototype focuses on the prediction of fire propagation. The direction of fire is limited in regular grid approaches, such as cellular automata, due to the shape of the uniformed grid, while irregular grids are freed from this constraint. In this prototype, fire propagation is computed from a centroid regardless of grid shape to remove the above constraint. Additionally, the prototype employs existing fire indices, including the Grassland Fire Danger Index (GFDI), Forest Fire Danger Index (FFDI) and Button Grass Moorland Fire Index (BGML). A number of parameters, such as Digital Elevation Model (DEM) and forecast weather data, are prepared for use in the calculation of the indices above. The fire study area is located around Lake Mackenzie in the central north of Tasmania where a fire burnt approximately 247.11 km 2 in January 2016. The prototype produces nine different prediction results with three polygon configurations, including Delaunay Triangulation, Square and Voronoi, using three different resolutions: fine, medium and coarse. The Delaunay Triangulation, which has the greatest number of adjacent grids among three shapes of polygon, shows the shortest elapsed time for spread of fire compared to other shapes. The medium grid performs the best trade-off between cost and time among the three grain sizes of prediction polygons, and the coarse size shows the best cost-effectiveness. A staging approach where coarse size prediction is released initially, followed by a medium size one, can be a pragmatic solution for the purpose of providing timely evacuation guidance.

Description: In Vietnam, approximately 39 million tons of rice (Oryza sativa) residues accrue every year. In this study, we quantified soil nutrient balances of paddy rice fields under different crop-residue management practices in northern Vietnam. On twelve farms, we calculated nutrient balances for the four prevalent rice-residue management practices, i.e., (1) direct incorporation of rice residues into the soil, (2) application of rice-residue compost, (3) burning of rice residues on the field, and (4) the use of rice residues as fodder for livestock. Soils under practices (1) to (3) showed a positive nutrient balance, which indicates that soil fertility can be maintained under these practices and that the amounts of chemical fertilizers can be considerably reduced. If not, there is a risk of eutrophication in the surrounding surface waterbodies. Practice (4), in contrast, resulted in a negative nutrient balance, which indicates the need for returning nutrients to the soils. From our findings we conclude that knowledge about the effects of rice-residue management practices on nutrient cycles may help to optimize the use of fertilizers, resulting in a more sustainable form of agriculture.