Food and move project, promoting healthy eating & physical activity in a secondary school setting, pat 1: baseline data, interventions and future recommendations

The Food and Move project was a collaborative project with the students, staff and parents from four Warrnambool secondary colleges which focussed on promoting healthy eating and physical activity in secondary schools and built capacity for ongoing health promotion to address overweight/obesity.

The project aimed to:

1. Increase awareness amongst students, parents and staff of the links between regular physical activity and good nutrition to achieve optimal health.
2. Increase awareness amongst students, parents and staff of childhood/adolescent obesity and its implications for future health.
3. Improve the opportunities for students to access healthy food at their school canteen.
4. Improve the opportunities for students to access physical activity at recess and lunchtime.
5. Prepare a resource package of initiatives for use in secondary colleges to support the provision of opportunities for healthy eating and physical activity at Warrnambool secondary colleges.
6. Support the development of appropriate physical activity and nutrition curricula.

Manual on application of molecular tools in aquaculture and inland fisheries management. Part I : laboratory protocols, data management and analysis

The aim of this manual is to provide a comprehensive practical tool for the generation and analysis of genetic data for subsequent application in aquatic resources management in relation to genetic stock identification in inland fisheries and aquaculture. The material only covers general background on genetics in relation to aquaculture and fisheries resource management, the techniques and relevant methods of data analysis that are commonly used to address questions relating to genetic resource characterisation and population genetic analyses. No attempt is made to include applications of genetic improvement techniques e.g. selective breeding or producing genetically modified organisms (GMOs). The manual includes two ‘stand-alone’ parts, of which this is the second volume: Part 1 – Conceptual basis of population genetic approaches: will provide a basic foundation on genetics in general, and concepts of population genetics. Issues on the choices of molecular markers and project design are also discussed. Part 2 – Laboratory protocols, data management and analysis: will provide step-by-step protocols of the most commonly used molecular genetic techniques utilised in population genetics and systematic studies. In addition, a brief discussion and explanation of how these data are managed and analysed is also included. This manual is expected to enable NACA member country personnel to be trained to undertake molecular genetic studies in their own institutions, and as such is aimed at middle and higher level technical grades. The manual can also provide useful teaching material for specialised advanced level university courses in the region and postgraduate students. The manual has gone through two development/improvement stages. The initial material was tested at a regional workshop and at the second stage feedback from participants was used to improve the contents.

Review of prevalence data in, and evaluation of methods for cross cultural adaptation of, UK surveys on tobacco and alcohol in ethnic minority groups

Objective To assess the adequacy of cross cultural adaptations of survey questions on self reported tobacco and alcohol consumption in the United Kingdom.

Design Assessment of consistency of data between studies identified through literature review. Studies evaluated with 12 guidelines developed from the research literature on achieving cross cultural comparability.

Results The literature review identified 18 key studies, five of them on national samples. Survey instruments were obtained for 15 of these. The comparison of prevalence data in national surveys showed some important discrepancies, greater for tobacco than for alcohol. For example, prevalence of cigarette smoking in Bangladeshi women was 6% in a national survey in 1994 and 1% in a national survey in 1999; in Chinese men it was 31% in a survey in 1993-4 and 17% in one in 1999; in African-Caribbean men it was 29% in a 1992 survey and 42% in one in 1993-4. The most guidelines met by any study was three, although one study partly met a fourth. Two studies met no guidelines. Only four studies consulted with ethnic minority communities in developing the questionnaire, none checked each language version with all others, and two stated the questionnaire had not been validated.

Conclusions Surveys have not followed best practice in relation to measurement of risk factors in cross cultural settings. There is inconsistency in the prevalence data on smoking provided by different major national UK studies. Users of such data should be aware of their limitations. Research is needed to help achieve linguistic equivalence of survey questions in cross cultural research.

Using MediaWiki as an efficient data repository and ubiquitous learning tool : an Australian example

The functionality of MediaWiki ensures it is a valuable learning repository for sharing and storing information. Constructivist learning can be promoted alongside a wiki repository and various wireless u-learning tools such as mobile phones and digital cameras, to encourage students to gather and share a range of primary and secondary information in a variety of subject areas. This paper outlines one initiative adopted at an Australian University specialising in distance education, which uses a MediaWiki as the primary method for content delivery. Over a period of three-years, the Drugs, Crime and Society wiki has evolved into an organic information repository for storing and accessing current research, press and drug agency material that supplements core themes examined in each topic of the curriculum. A constructivist approach has been employed to encourage students to engage in a range of assessable and non-assessable information sharing activities. The paper also demonstrates how the Drugs, Crime and Society wiki can be accessed through various wireless u-learning technologies, which enables students undertaking field placements to add and share primary information with other students and practitioners working in the drugs field.

Semantic data modelling and visualization using Noetica

Noetica is a tool for structuring knowledge about concepts and the reIationships between them. It differs from typical information systems in that the knowledge it represents is abstract, highly connected, and includes meta-knowledge (knowledge about knowledge). Noetica represents knowledge using a strongly typed graph data model. By providing a rich type system it is possible to represent conceptual information using formalized structures. A class hierarchy provides a basic classification for all objects. This allows for a consistency of representation that is not often found in `free' semantic networks, and gives the ability to easily extend a knowledge model while retaining its semantics. Visualization and query tools are provided for this data model. Visualization can be used to explore complete sets of link-classes, show paths while navigating through the database, or visualize the results of queries. Noetica supports goal-directed queries (a series of user-supplied goals that the system attempts to satisfy in sequence) and pathfinding queries (where the system finds relationships between objects in the database by following links).

A hybrid neural classifier for dimensionality reduction and data visualization and its application to fault detection and classification of induction motors

In this paper, a hybrid neural classifier combining the auto-encoder neural network and the Lattice Vector Quantization (LVQ) model is described. The auto-encoder network is used for dimensionality reduction by projecting high dimensional data into the 2D space. The LVQ model is used for data visualization by forming and adapting the granularity of a data map. The mapped data are employed to predict the target classes of new data samples. To improve classification accuracy, a majority voting scheme is adopted by the hybrid classifier. To demonstrate the applicability of the hybrid classifier, a series of experiments using simulated and real fault data from induction motors is conducted. The results show that the hybrid classifier is able to outperform the Multi-Layer Perceptron neural network, and to produce very good classification accuracy rates for various fault conditions of induction motors.