Online alcohol interventions : a systematic review

Background: There has been a significant increase in the availability of online programs for alcohol problems. A systematic review of the research evidence underpinning these programs is timely. Objectives: Our objective was to review the efficacy of online interventions for alcohol misuse. Systematic searches of Medline, PsycINFO, Web of Science, and Scopus were conducted for English abstracts (excluding dissertations) published from 1998 onward. Search terms were: (1) Internet, Web*; (2) online, computer*; (3) alcohol*; and (4) E\effect*, trial*, random* (where * denotes a wildcard). Forward and backward searches from identified papers were also conducted. Articles were included if (1) the primary intervention was delivered and accessed via the Internet, (2) the intervention focused on moderating or stopping alcohol consumption, and (3) the study was a randomized controlled trial of an alcohol-related screen, assessment, or intervention. Results: The literature search initially yielded 31 randomized controlled trials (RCTs), 17 of which met inclusion criteria. Of these 17 studies, 12 (70.6%) were conducted with university students, and 11 (64.7%) specifically focused on at-risk, heavy, or binge drinkers. Sample sizes ranged from 40 to 3216 (median 261), with 12 (70.6%) studies predominantly involving brief personalized feedback interventions. Using published data, effect sizes could be extracted from 8 of the 17 studies. In relation to alcohol units per week or month and based on 5 RCTs where a measure of alcohol units per week or month could be extracted, differential effect sizes to post treatment ranged from 0.02 to 0.81 (mean 0.42, median 0.54). Pre-post effect sizes for brief personalized feedback interventions ranged from 0.02 to 0.81, and in 2 multi-session modularized interventions, a pre-post effect size of 0.56 was obtained in both. Pre-post differential effect sizes for peak blood alcohol concentrations (BAC) ranged from 0.22 to 0.88, with a mean effect size of 0.66. Conclusions: The available evidence suggests that users can benefit from online alcohol interventions and that this approach could be particularly useful for groups less likely to access traditional alcohol-related services, such as women, young people, and at-risk users. However, caution should be exercised given the limited number of studies allowing extraction of effect sizes, the heterogeneity of outcome measures and follow-up periods, and the large proportion of student-based studies. More extensive RCTs in community samples are required to better understand the efficacy of specific online alcohol approaches, program dosage, the additive effect of telephone or face-to-face interventions, and effective strategies for their dissemination and marketing.

Model and prototype for querying multiple linked scientific datasets

Scientists need to transfer semantically similar queries across multiple heterogeneous linked datasets. These queries may require data from different locations and the results are not simple to combine due to differences between datasets. A query model was developed to make it simple to distribute queries across different datasets using RDF as the result format. The query model, based on the concept of publicly recognised namespaces for parts of each scientific dataset, was implemented with a configuration that includes a large number of current biological and chemical datasets. The configuration is flexible, providing the ability to transparently use both private and public datasets in any query. A prototype implementation of the model was used to resolve queries for the Bio2RDF website, including both Bio2RDF datasets and other datasets that do not follow the Bio2RDF URI conventions.

Improving matching process in social network using implicit and explicit user information

Personalised social matching systems can be seen as recommender systems that recommend people to others in the social networks. However, with the rapid growth of users in social networks and the information that a social matching system requires about the users, recommender system techniques have become insufficiently adept at matching users in social networks. This paper presents a hybrid social matching system that takes advantage of both collaborative and content-based concepts of recommendation. The clustering technique is used to reduce the number of users that the matching system needs to consider and to overcome other problems from which social matching systems suffer, such as cold start problem due to the absence of implicit information about a new user. The proposed system has been evaluated on a dataset obtained from an online dating website. Empirical analysis shows that accuracy of the matching process is increased, using both user information (explicit data) and user behavior (implicit data).

Theoretical model of user acceptance : in the view of measuring success in web personalization

This paper attempts to develop a theoretical acceptance model for measuring Web personalization success. Key factors impacting Web personalization acceptance are identified from a detailed literature review. The final model is then cast in a structural equation modeling (SEM) framework comprising nineteen manifest variables, which are grouped into three focal behaviors of Web users. These variables could provide a framework for better understanding of numerous factors that contribute to the success measures of Web personalization technology. Especially, those concerning the quality of personalized features and how personalized information through personalized Website can be delivered to the user. The interrelationship between success constructs is also explained. Empirical validations of this theoretical model are expected on future research.

Evidence of multiwall carbon nanotube deformation caused by poly(3-hexylthiophene) adhesion

We show that when a soft polymer like Poly(3-hexyl-thiophene) wraps multiwall nanotubes by coiling around the main axis, a localized deformation of the nanotube structure is observed. High resolution transmission electron microscopy shows that radial compressions of about 4% can take place, and could possibly lead to larger interlayer distance between the nanotube inner walls and reduce the innermost nanotube radius. The mechanical stress due to the polymer presence was confirmed by Raman spectroscopic observation of a gradual upshift of the carbon nanotube G-band when the polymer content in the composites was progressively increased. Vibrational spectroscopy also indicates that charge transfer from the polymer to the nanotubes is responsible for a peak frequency relative downshift for high P3HT-content samples. Continuously acquired transmission electron microscopy images at rising temperature show the MWCNT elastic compression and relaxation due to polymer rearrangement on the nanotube surface.

Electron diffusion and back reaction in dye-sensitized solar cells : the effect of nonlinear recombination kinetics

The electron collection efficiency in dye-sensitized solar cells (DSCs) is usually related to the electron diffusion length, L = (Dτ)^1/2, where D is the diffusion coefficient of mobile electrons and τ is their lifetime, which is determined by electron transfer to the redox electrolyte. Analysis of incident photon-to-current efficiency (IPCE) spectra for front and rear illumination consistently gives smaller values of L than those derived from small amplitude methods. We show that the IPCE analysis is incorrect if recombination is not first-order in free electron concentration, and we demonstrate that the intensity dependence of the apparent L derived by first-order analysis of IPCE measurements and the voltage dependence of L derived from perturbation experiments can be fitted using the same reaction order, γ ≈ 0.8. The new analysis presented in this letter resolves the controversy over why L values derived from small amplitude methods are larger than those obtained from IPCE data.

Leveraging R&D investment for the Australian built environment

This paper discusses a current research project building new understandings and knowledge relevant to R&D funding strategies in Australia. Building on a retrospective analysis of R&D trends and industry outcomes, an industry roadmap will be developed to inform R&D policies more attuned to future industry needs to improve research investment effectiveness. The project will also include analysis of research team formation and management (involving end users from public and private sectors together with research and knowledge institutions), and dissemination of outcomes and uptake in the Australian building and construction industry. The project will build on previous research extending open innovation system theory and network analysis and procurement, focused on R&D. Through the application of dynamic capabilities and strategic foresighting theory, an industry roadmap for future research investment will be developed, providing a stronger foundation for more targeted policy recommendations. This research will contribute to more effective construction processes in the future through more targeted research funding and more effective research partnerships between industry and researchers.

Assurance of learning : the role of work integrated learning and industry partners

In the partnering with students and industry it is important for universities to recognize and value the nature of knowledge and learning that emanates from work integrated learning experiences is different to formal university based learning. Learning is not a by-product of work rather learning is fundamental to engaging in work practice. Work integrated learning experiences provide unique opportunities for students to integrate theory and practice through the solving of real world problems. This paper reports findings to date of a project that sought to identify key issues and practices faced by academics, industry partners and students engaged in the provision and experience of work integrated learning within an undergraduate creative industries program at a major metropolitan university. In this paper, those findings are focused on some of the particular qualities and issues related to the assessment of learning at and through the work integrated experience. The findings suggest that the assessment strategies needed to better value the knowledges and practices of the Creative Industries. The paper also makes recommendations about how industry partners might best contribute to the assessment of students’ developing capabilities and to continuous reflection on courses and the assurance of learning agenda.

The Australian Nonprofit Sector Legal Almanac 2010, ACPNS Working Paper 53

This is the third year that we have summarised annual developments in the law for nonprofit staff, boards and volunteers. We were encouraged by the interest shown in last year’s publication and the use made of the digital copy on our web site, so here is the almanac for the Jan 2010–Dec 2010 period. We are delighted that the Australian Charity Law Association and PilchConnect (Victoria) have again agreed to contribute and promote the publication as well. These two organisations are beginning to fill the void of professional legal development and assistance to small nonprofit organisations that has characterised Australia for too many years. The first conference of the Australian Charity Law Association in Sydney was a significant event and one of the addresses is included in the Almanac. Other materials from the conference can be accessed at the Centre’s website.

Crown copyright

Copyright protects much of the creative, cultural, educational, scientific and informational material generated by federal, State/Territory and local governments and their constituent departments and agencies. Governments at all levels develop, manage and distribute a vast array of materials in the form of documents, reports, websites, datasets and databases on CD or DVD and files that can be downloaded from a website. Under the Copyright Act 1968 (Cth), with few exceptions government copyright is treated the same as copyright owned by non-government parties insofar as the range of protected materials and the exclusive proprietary rights attaching to them are concerned. However, the rationale for recognizing copyright in public sector materials and vesting ownership of copyright in governments is fundamentally different to the main rationales underpinning copyright generally. The central justification for recognizing Crown copyright is to ensure that government documents and materials created for public administrative purposes are disseminated in an accurate and reliable form. Consequently, the exclusive rights held by governments as copyright owners must be exercised in a manner consistent with the rationale for conferring copyright ownership on them. Since Crown copyright exists primarily to ensure that documents and materials produced for use in the conduct of government are circulated in an accurate and reliable form, governments should exercise their exclusive rights to ensure that their copyright materials are made available for access and reuse, in accordance with any laws and policies relating to access to public sector materials. While copyright law vests copyright owners with extensive bundles of exclusive rights which can be exercised to prevent others making use of the copyright material, in the case of Crown copyright materials these rights should rarely be asserted by government to deviate from the general rule that Crown copyright materials will be available for “full and free reproduction” by the community at large.

User profiling based on folksonomy information in Web 2.0 for personalized recommender systems

Information overload has become a serious issue for web users. Personalisation can provide effective solutions to overcome this problem. Recommender systems are one popular personalisation tool to help users deal with this issue. As the base of personalisation, the accuracy and efficiency of web user profiling affects the performances of recommender systems and other personalisation systems greatly. In Web 2.0, the emerging user information provides new possible solutions to profile users. Folksonomy or tag information is a kind of typical Web 2.0 information. Folksonomy implies the users‘ topic interests and opinion information. It becomes another source of important user information to profile users and to make recommendations. However, since tags are arbitrary words given by users, folksonomy contains a lot of noise such as tag synonyms, semantic ambiguities and personal tags. Such noise makes it difficult to profile users accurately or to make quality recommendations. This thesis investigates the distinctive features and multiple relationships of folksonomy and explores novel approaches to solve the tag quality problem and profile users accurately. Harvesting the wisdom of crowds and experts, three new user profiling approaches are proposed: folksonomy based user profiling approach, taxonomy based user profiling approach, hybrid user profiling approach based on folksonomy and taxonomy. The proposed user profiling approaches are applied to recommender systems to improve their performances. Based on the generated user profiles, the user and item based collaborative filtering approaches, combined with the content filtering methods, are proposed to make recommendations. The proposed new user profiling and recommendation approaches have been evaluated through extensive experiments. The effectiveness evaluation experiments were conducted on two real world datasets collected from Amazon.com and CiteULike websites. The experimental results demonstrate that the proposed user profiling and recommendation approaches outperform those related state-of-the-art approaches. In addition, this thesis proposes a parallel, scalable user profiling implementation approach based on advanced cloud computing techniques such as Hadoop, MapReduce and Cascading. The scalability evaluation experiments were conducted on a large scaled dataset collected from Del.icio.us website. This thesis contributes to effectively use the wisdom of crowds and expert to help users solve information overload issues through providing more accurate, effective and efficient user profiling and recommendation approaches. It also contributes to better usages of taxonomy information given by experts and folksonomy information contributed by users in Web 2.0.

Connecting users and items with weighted tags for personalized item recommendations

Social tags are an important information source in Web 2.0. They can be used to describe users’ topic preferences as well as the content of items to make personalized recommendations. However, since tags are arbitrary words given by users, they contain a lot of noise such as tag synonyms, semantic ambiguities and personal tags. Such noise brings difficulties to improve the accuracy of item recommendations. To eliminate the noise of tags, in this paper we propose to use the multiple relationships among users, items and tags to find the semantic meaning of each tag for each user individually. With the proposed approach, the relevant tags of each item and the tag preferences of each user are determined. In addition, the user and item-based collaborative filtering combined with the content filtering approach are explored. The effectiveness of the proposed approaches is demonstrated in the experiments conducted on real world datasets collected from Amazon.com and citeULike website.

Parallel user profiling based on folksonomy for Large Scaled Recommender Systems : an implimentation of Cascading MapReduce

The Large scaled emerging user created information in web 2.0 such as tags, reviews, comments and blogs can be used to profile users’ interests and preferences to make personalized recommendations. To solve the scalability problem of the current user profiling and recommender systems, this paper proposes a parallel user profiling approach and a scalable recommender system. The current advanced cloud computing techniques including Hadoop, MapReduce and Cascading are employed to implement the proposed approaches. The experiments were conducted on Amazon EC2 Elastic MapReduce and S3 with a real world large scaled dataset from Del.icio.us website.

The Figures

This short film, created by David Megarrity and Luke Monsour, experimented within a short timeframe with the challenge of superimposition of hand-drawn backgrounds, non-verbal action, and a short, sharp shoot. The aim was also to find a single piece of standalone music that would act as an unedited soundtrack It won Best Queensland Film at the Woodford Film Festival in 2005, and was screened at Base-Court, Lausanne Switzerland in 2006, and the Westgarth Film Festival 2005. It was acquired by comedy website minimovie in 2007.

Forced landing technologies for unmanned aerial vehicles : towards safer operations

While using unmanned systems in combat is not new, what will be new in the foreseeable future is how such systems are used and integrated in the civilian space. The potential use of Unmanned Aerial Vehicles in civil and commercial applications is becoming a fact, and is receiving considerable attention by industry and the research community. The majority of Unmanned Aerial Vehicles performing civilian tasks are restricted to flying only in segregated space, and not within the National Airspace. The areas that UAVs are restricted to flying in are typically not above populated areas, which in turn are the areas most useful for civilian applications. The reasoning behind the current restrictions is mainly due to the fact that current UAV technologies are not able to demonstrate an Equivalent Level of Safety to manned aircraft, particularly in the case of an engine failure which would require an emergency or forced landing. This chapter will preset and guide the reader through a number of developments that would facilitate the integration of UAVs into the National Airspace. Algorithms for UAV Sense-and-Avoid and Force Landings are recognized as two major enabling technologies that will allow the integration of UAVs in the civilian airspace. The following sections will describe some of the techniques that are currently being tested at the Australian Research Centre for Aerospace Automation (ARCAA), which places emphasis on the detection of candidate landing sites using computer vision, the planning of the descent path trajectory for the UAV, and the decision making process behind the selection of the final landing site.