The Alcohol Intervention Training Program (AITP): a response to alcohol misuse in the farming community

Background Farm men and women in Australia have higher levels of problematic alcohol use than their urban counterparts and experience elevated health risks associated with excessive alcohol consumption. The Sustainable Farm Families (SFF) program has worked successfully with farm men and women to address health, well- being and safety and has identified that further research and training is required to understand and address alcohol misuse behaviours. This project will add an innovative component to the program by training health professionals working with farm men and women to discuss and respond to alcohol-related physical and mental health problems. Methods/Design A mixed method design with multi-level evaluation will be implemented following the development and delivery of a training program (The Alcohol Intervention Training Program {AITP}) for Sustainable Farm Families health professionals. Pre-, post- and follow-up surveys will be used to assess both the impact of the training on the knowledge, confidence and skills of the health professionals to work with alcohol misuse and associated problems, and the impact of the training on the attitudes, behaviour and mental health of farm men and women who participate in the SFF project. Evaluations will take a range of forms including self-rated outcome measures and interviews. Discussion The success of this project will enhance the health and well-being of a critical population, the farm men and women of Australia, by producing an evidence-based strategy to assist them to adopt more positive alcohol-related behaviours that will lead to better physical and mental health.

An analysis of regression models for predicting the speed of a wave glider autonomous surface vehicle

An important aspect of robotic path planning for is ensuring that the vehicle is in the best location to collect the data necessary for the problem at hand. Given that features of interest are dynamic and move with oceanic currents, vehicle speed is an important factor in any planning exercises to ensure vehicles are at the right place at the right time. Here, we examine different Gaussian process models to find a suitable predictive kinematic model that enable the speed of an underactuated, autonomous surface vehicle to be accurately predicted given a set of input environmental parameters.

Direct iodination of isoindolines and isoindoline nitroxides as precursors to functionalized nitroxides

A new method for the direct aryl iodination of isoindolines and isoindoline nitroxides which utilizes periodic acid and potassium iodide in sulfuric acid is presented. Di-iodo functionalized tetramethyl and tetraethyl isoindolines and a di-iodo tetramethyl isoindoline nitroxide were prepared in high yield (70-82%). The analogous mono-iodo species were afforded in modest yield (34-48%). Iodinated nitrones were also obtained from a tetraethyl isoindoline nitroxide.

Rural people and the land

There is a long and fundamental connection between rural place and the land. Whereas land is simply the foundation for the construction of towns and cities, whose urban culture and economy thrives on human ingenuity and industry that may have little direct attachment to the physical ground over which it occurs, historical discourses of rurality place the land at the heart of the rural economy and society. Rural people, such discourses hold, live on the land, work the land, tend the land and know the land. The land formed not only the base of the rural economy (as ‘a physical, tangible resource which can be ploughed, sown, grazed, built upon’ (Macnaghten and Urry 1998, 200)), but also shaped rural culture and the rural calendar, and contributed to the constitution of the rural character (see Bell 1994). As such, the land is central to rural sense of place.

Mid-Holocene sea-level and coral reef demise : U-Th dating of subfossil corals in Moreton Bay, Australia

It is increasingly apparent that sea-level data (e.g. microfossil transfer functions, dated coral microatolls and direct observations from satellite and tidal gauges) vary temporally and spatially at regional to local scales, thus limiting our ability to model future sea-level rise for many regions. Understanding sealevel response at ‘far-field’ locations at regional scales is fundamental for formulating more relevant sea-level rise susceptibility models within these regions under future global change projections. Fossil corals and reefs in particular are valuable tools for reconstructing past sea levels and possible environmental phase shifts beyond the temporal constraints of instrumental records. This study used abundant surface geochronological data based on in situ subfossil corals and precise elevation surveys to determine previous sea level in Moreton Bay, eastern Australia, a far-field site. A total of 64 U-Th dates show that relative sea level was at least 1.1 m above modern lowest astronomical tide (LAT) from at least ˜6600 cal. yr BP. Furthermore, a rapid synchronous demise in coral reef growth occurred in Moreton Bay ˜5800 cal. yr BP, coinciding with reported reef hiatus periods in other areas around the Indo-Pacific region. Evaluating past reef growth patterns and phases allows for a better interpretation of anthropogenic forcing versus natural environmental/climatic cycles that effect reef formation and demise at all scales and may allow better prediction of reef response to future global change.

Baidu’s perfect paradox : free speech and the right to censor

China’s biggest search engine has a constitutional right to filter its search results, a US court found last month. But that’s just the start of the story. Eight New York-based pro-democracy activists sued Baidu Inc in 2011, seeking damages because Baidu prevents their work from showing up in search results. Baidu follows Chinese law that requires it to censor politically sensitive results. But in what the plaintiffs’ lawyer has dubbed a “perfect paradox”, US District Judge Jesse Furman has dismissed the challenge, explaining that to hold Baidu liable for its decisions to censor pro-democracy content would itself infringe the right to free speech.

The unfinished revolution : what is missing from the E&P industry’s move to “big data”

One cannot help but be impressed by the inroads that digital oilfield technologies have made into the exploration and production (E&P) industry in the past decade. Today’s production systems can be monitored by “smart” sensors that allow engineers to observe almost any aspect of performance in real time. Our understanding of how reservoirs are behaving has improved considerably since the dawn of this revolution, and the industry has been able to move away from point answers to more holistic “big picture” integrated solutions. Indeed, the industry has already reaped the rewards of many of these kinds of investments. Many billions of dollars of value have been delivered by this heightened awareness of what is going on within our assets and the world around them (Van Den Berg et al. 2010).

Spatial prediction on a river network

This article develops methods for spatially predicting daily change of dissolved oxygen (Dochange) at both sampled locations (134 freshwater sites in 2002 and 2003) and other locations of interest throughout a river network in South East Queensland, Australia. In order to deal with the relative sparseness of the monitoring locations in comparison to the number of locations where one might want to make predictions, we make a classification of the river and stream locations. We then implement optimal spatial prediction (ordinary and constrained kriging) from geostatistics. Because of their directed-tree structure, rivers and streams offer special challenges. A complete approach to spatial prediction on a river network is given, with special attention paid to environmental exceedances. The methodology is used to produce a map of Dochange predictions for 2003. Dochange is one of the variables measured as part of the Ecosystem Health Monitoring Program conducted within the Moreton Bay Waterways and Catchments Partnership.

The impact of transformative learning in a critical service-learning program on teacher development: Building a foundation for inclusive teaching

With international and national policies requiring teachers to adopt inclusive practices worldwide, this paper examines the impact of transformational learning in a critical service-learning program on final-year pre-service teachers’ approaches to inclusive teaching. Data from emailed questionnaires and focus group interviews are analysed through a social, critical framework. The results indicate that the critical service-learning program provided the students with an opportunity to consider diversity and inclusion in selecting teaching strategies, and to enact values suitable to inclusive practices and appreciation of diversity in schools. In this paper we argue that transformative learning experiences about inclusivity and diversity are needed if pre-service teachers are to be challenged to adopt inclusive values and practice in schools. A critical service-learning program for pre-service teachers provides a solid foundation on which to develop or build on the ability to think and teach inclusively.

Data as an asset : what the upstream oil & gas industry can learn about ‘big data’ from companies like Facebook

The upstream oil & gas industry has been contending with massive data sets and monolithic files for many years, but “Big Data”—that is, the ability to apply more sophisticated types of analytical tools to information in a way that extracts new insights or creates new forms of value—is a relatively new concept that has the potential to significantly re-shape the industry. Despite the impressive amount of value that is being realized by Big Data technologies in other parts of the marketplace, however, much of the data collected within the oil & gas sector tends to be discarded, ignored, or analyzed in a very cursory way. This paper examines existing data management practices in the upstream oil & gas industry, and compares them to practices and philosophies that have emerged in organizations that are leading the Big Data revolution. The comparison shows that, in companies that are leading the Big Data revolution, data is regarded as a valuable asset. The presented evidence also shows, however, that this is usually not true within the oil & gas industry insofar as data is frequently regarded there as descriptive information about a physical asset rather than something that is valuable in and of itself. The paper then discusses how upstream oil & gas companies could potentially extract more value from data, and concludes with a series of specific technical and management-related recommendations to this end.

The use of new generation geosynthetics in water treatment

The importance of clean drinking water in any community is absolutely vital if we as the consumers are to sustain a life of health and wellbeing. Suspended particles in surface waters not only provide the means to transport micro-organisms which can cause serious infections and diseases, they can also affect the performance capacity of a water treatment plant. In such situations pre-treatment ahead of the main plant is recommended. Previous research carried out using non-woven synthetic as a pre-filter materials for protecting slow sand filters from high turbidity showed that filter run times can be extended by several times and filters can be regenerated by simply removing and washing of the fabric ( Mbwette and Graham, 1987 and Mbwette, 1991). Geosynthetic materials have been extensively used for soil retention and dewatering in geotechnical applications and little research exists for the application of turbidity reduction in water treatment. With the development of new materials in geosynthetics today, it was hypothesized that the turbidity removal efficiency can be improved further by selecting appropriate materials. Two different geosynthetic materials (75 micron) tested at a filtration rate of 0.7 m/h yielded 30-45% reduction in turbidity with relatively minor head loss. It was found that the non-woven geotextile Propex 1701 retained the highest performance in both filtration efficiency and head loss across the varying turbidity ranges in comparison to other geotextiles tested. With 5 layers of the Propex 1701 an average percent reduction of approximately 67% was achieved with a head loss average of 4mm over the two and half hour testing period. Using the data collected for the Propex 1701 a mathematical model was developed for predicting the expected percent reduction given the ability to control the cost and as a result the number of layers to be used in a given filtration scenario.

Teaching reflection for service-learning

In this chapter, we discuss an approach for teaching pre-service teachers how to critically reflect on their experiences in a Service-learning program in an advanced subject about inclusive education. The approach was informed by critical social theory, with the expectation that students would engage in transformational learning. By explicitly teaching the students to engage in critical reflective thinking (Fishbowl discussions) and examine the depth of their critical reflection against a heuristic (the 4Rs reflection framework), the final-year Bachelor of Education students were able to gain a deeper understanding of the subject and experience transformational learning. We provide contextual information about the Service-learning program and discuss critical social theory for transformational learning, as well as how the teaching team taught critical reflection. Based on the evidence gathered from the students, we consider lessons learned by the teaching team and provide recommendations for teaching reflection in Service-learning programs.

Data as an asset: what the oil and gas sector can learn from other industries about “Big Data”

The upstream oil and gas industry has been contending with massive data sets and monolithic files for many years, but “Big Data” is a relatively new concept that has the potential to significantly re-shape the industry. Despite the impressive amount of value that is being realized by Big Data technologies in other parts of the marketplace, however, much of the data collected within the oil and gas sector tends to be discarded, ignored, or analyzed in a very cursory way. This viewpoint examines existing data management practices in the upstream oil and gas industry, and compares them to practices and philosophies that have emerged in organizations that are leading the way in Big Data. The comparison shows that, in companies that are widely considered to be leaders in Big Data analytics, data is regarded as a valuable asset—but this is usually not true within the oil and gas industry insofar as data is frequently regarded there as descriptive information about a physical asset rather than something that is valuable in and of itself. The paper then discusses how the industry could potentially extract more value from data, and concludes with a series of policy-related questions to this end.

The mathematical modelling of cheese ripening

A mathematical model is developed for the ripening of cheese. Such models may assist predicting final cheese quality using measured initial composition. The main constituent chemical reactions are described with ordinary differential equations. Numerical solutions to the model equations are found using Matlab. Unknown parameter values have been fitted using experimental data available in the literature. The results from the numerical fitting are in good agreement with the data. Statistical analysis is performed on near infrared data provided to the MISG. However, due to the inhomogeneity and limited nature of the data, not many conclusions can be drawn from the analysis. A simple model of the potential changes in acidity of cheese is also considered. The results from this model are consistent with cheese manufacturing knowledge, in that the pH of cheddar cheese does not significantly change during ripening.