STAR : Predicting recombination sites from amino acid sequence

Background Designing novel proteins with site-directed recombination has enormous prospects. By locating effective recombination sites for swapping sequence parts, the probability that hybrid sequences have the desired properties is increased dramatically. The prohibitive requirements for applying current tools led us to investigate machine learning to assist in finding useful recombination sites from amino acid sequence alone. Results We present STAR, Site Targeted Amino acid Recombination predictor, which produces a score indicating the structural disruption caused by recombination, for each position in an amino acid sequence. Example predictions contrasted with those of alternative tools, illustrate STAR'S utility to assist in determining useful recombination sites. Overall, the correlation coefficient between the output of the experimentally validated protein design algorithm SCHEMA and the prediction of STAR is very high (0.89). Conclusion STAR allows the user to explore useful recombination sites in amino acid sequences with unknown structure and unknown evolutionary origin. The predictor service is available from http://pprowler.itee.uq.edu.au/star.

Predicting structural disruption of proteins caused by crossover

We present a machine learning model that predicts a structural disruption score from a protein s primary structure. SCHEMA was introduced by Frances Arnold and colleagues as a method for determining putative recombination sites of a protein on the basis of the full (PDB) description of its structure. The present method provides an alternative to SCHEMA that is able to determine the same score from sequence data only. Circumventing the need for resolving the full structure enables the exploration of yet unresolved and even hypothetical sequences for protein design efforts. Deriving the SCHEMA score from a primary structure is achieved using a two step approach: first predicting a secondary structure from the sequence and then predicting the SCHEMA score from the predicted secondary structure. The correlation coefficient for the prediction is 0.88 and indicates the feasibility of replacing SCHEMA with little loss of precision.

Overview of INEX 2014

INEX investigates focused retrieval from structured documents by providing large test collections of structured documents, uniform evaluation measures, and a forum for organizations to compare their results. This paper reports on the INEX 2014 evaluation campaign, which consisted of three tracks: The Interactive Social Book Search Track investigated user information seeking behavior when interacting with various sources of information, for realistic task scenarios, and how the user interface impacts search and the search experience. The Social Book Search Track investigated the relative value of authoritative metadata and user-generated content for search and recommendation using a test collection with data from Amazon and LibraryThing, including user profiles and personal catalogues. The Tweet Contextualization Track investigated tweet contextualization, helping a user to understand a tweet by providing him with a short background summary generated from relevant Wikipedia passages aggregated into a coherent summary. INEX 2014 was an exciting year for INEX in which we for the third time ran our workshop as part of the CLEF labs. This paper gives an overview of all the INEX 2014 tracks, their aims and task, the built test-collections, the participants, and gives an initial analysis of the results.

Clinical data warehousing : a business analytics approach for managing health data

Heterogeneous health data is a critical issue when managing health information for quality decision making processes. In this paper we examine the efficient aggregation of lifestyle information through a data warehousing architecture lens. We present a proof of concept for a clinical data warehouse architecture that enables evidence based decision making processes by integrating and organising disparate data silos in support of healthcare services improvement paradigms.

A multidimensional collaborative filtering fusion approach with dimensionality reduction

Multidimensional data are getting increasing attention from researchers for creating better recommender systems in recent years. Additional metadata provides algorithms with more details for better understanding the interaction between users and items. While neighbourhood-based Collaborative Filtering (CF) approaches and latent factor models tackle this task in various ways effectively, they only utilize different partial structures of data. In this paper, we seek to delve into different types of relations in data and to understand the interaction between users and items more holistically. We propose a generic multidimensional CF fusion approach for top-N item recommendations. The proposed approach is capable of incorporating not only localized relations of user-user and item-item but also latent interaction between all dimensions of the data. Experimental results show significant improvements by the proposed approach in terms of recommendation accuracy.

Tensor reduction for user profiling in personalized recommender systems

User profiling is the process of constructing user models which represent personal characteristics and preferences of customers. User profiles play a central role in many recommender systems. Recommender systems recommend items to users based on user profiles, in which the items can be any objects which the users are interested in, such as documents, web pages, books, movies, etc. In recent years, multidimensional data are getting more and more attention for creating better recommender systems from both academia and industry. Additional metadata provides algorithms with more details for better understanding the interactions between users and items. However, most of the existing user/item profiling techniques for multidimensional data analyze data through splitting the multidimensional relations, which causes information loss of the multidimensionality. In this paper, we propose a user profiling approach using a tensor reduction algorithm, which we will show is based on a Tucker2 model. The proposed profiling approach incorporates latent interactions between all dimensions into user profiles, which significantly benefits the quality of neighborhood formation. We further propose to integrate the profiling approach into neighborhoodbased collaborative filtering recommender algorithms. Experimental results show significant improvements in terms of recommendation accuracy.

Refining user and item profiles based on multidimensional data for top-n item recommendation

In recommender systems based on multidimensional data, additional metadata provides algorithms with more information for better understanding the interaction between users and items. However, most of the profiling approaches in neighbourhood-based recommendation approaches for multidimensional data merely split or project the dimensional data and lack the consideration of latent interaction between the dimensions of the data. In this paper, we propose a novel user/item profiling approach for Collaborative Filtering (CF) item recommendation on multidimensional data. We further present incremental profiling method for updating the profiles. For item recommendation, we seek to delve into different types of relations in data to understand the interaction between users and items more fully, and propose three multidimensional CF recommendation approaches for top-N item recommendations based on the proposed user/item profiles. The proposed multidimensional CF approaches are capable of incorporating not only localized relations of user-user and/or item-item neighbourhoods but also latent interaction between all dimensions of the data. Experimental results show significant improvements in terms of recommendation accuracy.

Automation of underground truck haulage

This paper reviews the state-of-the art in the automation of underground truck haulage. Past attemps at automating LHDs and haul trucks are described and their particular strengths and weaknesses are listed. We argue that the simple auto-tram...

Leveraging the repository infrastructure to curate institutional heritage materials, learning objects and data assets

Developing and maintaining a successful institutional repository for research publications requires a considerable investment by the institution. Most of the money is spent on developing the skill-sets of existing staff or hiring new staff with the necessary skills. The return on this investment can be magnified by using this valuable infrastructure to curate collections of other materials such as learning objects, student work, conference proceedings and institutional or local community heritage materials. When Queensland University of Technology (QUT) implemented its repository for research publications (QUT ePrints) over 11 years ago, it was one of the first institutional repositories to be established in Australia. Currently, the repository holds over 29,000 open access research publications and the cumulative total number of full-text downloads for these document now exceeds 16 million. The full-text deposit rate for recently-published peer reviewed papers (currently over 74%) shows how well the repository has been embraced by QUT researchers. The success of QUT ePrints has resulted in requests to accommodate a plethora of materials which are ‘out of scope’ for this repository. QUT Library saw this as an opportunity to use its repository infrastructure (software, technical know-how and policies) to develop and implement a metadata repository for its research datasets (QUT Research Data Finder), a repository for research-related software (QUT Software Finder) and to curate a number of digital collections of institutional and local community heritage materials (QUT Digital Collections). This poster describes the repositories and digital collections curated by QUT Library and outlines the value delivered to the institution, and the wider community, by these initiatives.

Transnationalism and the Karen wrist-tying ceremony: An ethnographic account of Karen settlement practice in Brisbane

When settling, people often use cultural schema from their original homeland to build familiarity in unfamiliar surrounds. This paper draws on ethnographic fieldwork conducted by the first author in Brisbane, with the Karen community from Burma, during which participant observation and interview methods were used. We present an ethnographic account of the Brisbane Karen wrist-tying ceremony. The ceremony acts as an insight into the challenges for Karen whilst settling into Australia. It reflects multiple accounts of history and tradition, but simultaneously speaks to emerging, contemporary Karen contexts. This research contributes to richer understandings of settlement: it frames transnational cultural practice as a flexible mode of integration, rather than an exclusionary mode of othering. We propose that the integrative discourse of the ceremony creates familiarity and social connection in local and diasporic spaces. This acts as a counter to the challenges of Karen settlement including the negotiations of local/global identity politics.

Gender identity and brand incongruence: When in doubt, pursue masculinity

Gender identity is the extent to which an individual identifies with masculine or feminine personality traits. Sex roles in Western societies continue to evolve, so this research examines the developing relationship between gender identity and consumer responses to gendered branding. Grounded in self-congruency theory [Sirgy, M. J. (1982). Self-concept in consumer behavior: A critical review. Journal of Consumer Research, 9, 287–300], the present research reports an experiment that supports a congruence relationship between gender identity and brand response. Masculine consumers prefer masculine brands. The results also show incongruent brand rejection where masculine consumers react negatively to feminine brands although feminine consumers are more accepting of masculine brands. Further, the results suggest that gender identity is a more effective dimension for customer segmentation than biological sex. Overall, the results suggest that masculine brands are more effective than other gendered brand profiles for masculine, feminine, and androgynous consumers.

Reflections on damaged modernity: Lessons from the iconic architecture industry

For Adorno writing in 1953, Hollywood cinema was a medium of “regression” based on infantile wish fulfillment manufactured by the industrial repetition of the filmic image that he called a modern “hieroglyphics”—like the archaic language of pictures in Ancient Egypt, which guaranteed immortality after death in Egyptian burial rites. From that 1953 essay Prolog zum Fernsehen to Das Schema der Massenkultur in 1981, Adorno likened film frames to cultural ideograms: What he called the filmic “language of images” (Bildersprache) constituted a Hieroglyphenschrift that visualised forbidden sexual impulses and ideations of death and domination in the unconscious of the mass spectator. In his famous passage he writes, “As image, the image-writing (Bilderschrift) is a medium of regression, where the producer and consumer coincide; as writing, film resurrects the archaic images of modernity.” In other words, cinema takes the spectator on a journey into his unconscious in order to control him from within. It works, because the spectator begins to believe the film is speaking to him in his very own image-language (the unconscious), making him do and buy whatever capitalism demands. Modernity for Adorno is precisely the instrumentalisation of the collective unconscious through the mediatic images of the culture industry.

Writing fashion’s future: the gods and monsters of the Anthropocene

This paper identifies two narratives of the Anthropocene and explores how they play out in the realm of future-looking fashion production. Each narrative draws on mythic comparisons to gods and monsters to express humanity’s dilemmas, albeit from different perspectives. The first is a Malthusian narrative of collapse and scarcity, brought about by the monstrous, unstoppable nature of human technology set loose on the natural world. In this vein, philosopher Slavoj Zizek (2010) draws on Biblical analogies, likening ecological crisis to one of the four horsemen of the apocalypse. To find a myth to suit the present times, novelist A.S Byatt (2011) proposes Ragnarök, a Norse myth in which the gods destroy themselves. In contrast, the second narrative is one of technological cornucopia. Stewart Brand (2009, 27), self-described ‘eco-pragmatist’ writes, ‘we are as gods and we have to get good at it’. In his view, human technologies offer the only hope to mitigating the problems caused by human technology – Brand suggests harnessing nuclear power, bioengineering of crops and the geoengineering of the planet as the way forward. Similarly, the French philosopher Bruno Latour (2012, 274), exhorts us to “love our monsters”, likening our technologies to Doctor Frankenstein’s monster – set loose upon the world, and then reviled by his creator. For both Brand and Latour, human technology may be monstrous, but it must also be turned toward solutions. Within this schema, hopeful visions of the future of fashion are similarly divided. In the techno-enabled cornucopian future, the fashion industry embraces wearable technology, speed and efficiency. Technologies such as waterless dyeing, 3D printing and self-cleaning garments shift fashion into a new era of cleaner production. Meanwhile, in the narrative of scarcity, a more cautious approach sees fashion return to a new localism and valuing of the hand-made in a time of shrinking resources. Through discussion of future-looking fashion designers, brands, and activists, this paper explores how they may align along a spectrum to one of these two grand narratives of the future. The paper will discuss how these narratives may unconsciously shape the perspective of both producers and users around the fashion of today and the fashion of tomorrow. This paper poses the question: what stories can be written for fashion’s future in the Anthropocene, and are they fated, or can they be re-written?

The authentication of electronic evidence

This thesis examines whether the rules for of evidence, which were developed around paper over centuries, are adequate for the authentication of electronic evidence. The history of documentary evidence is examined, and the nature of electronic evidence is explored, particularly recent types of electronic evidence such as social media and 'the Cloud'. The old rules are then critically applied to the varied types of electronic evidence to determine whether or not these old rules are indeed adequate.

Cultures of sharing in 3D printing: What can we learn from the licence choices of Thingiverse users?

This article contributes to the discussion by analysing how users of the leading online 3D printing design repository Thingiverse manage their intellectual property (IP). 3D printing represents a fruitful case study for exploring the relationship between IP norms and practitioner culture. Although additive manufacturing technology has existed for decades, 3D printing is on the cusp of a breakout into the technological mainstream – hardware prices are falling; designs are circulating widely; consumer-friendly platforms are multiplying; and technological literacy is rising. Analysing metadata from more than 68,000 Thingiverse design files collected from the site, we examine the licensing choices made by users and explore the way this shapes the sharing practices of the site’s users. We also consider how these choices and practices connect with wider attitudes towards sharing and intellectual property in 3D printing communities. A particular focus of the article is how Thingiverse structures its regulatory framework to avoid IP liability, and the extent to which this may have a bearing on users’ conduct. The paper has three sections. First, we will offer a description of Thingiverse and how it operates in the 3D printing ecosystem, noting the legal issues that have arisen regarding Thingiverse’s Terms of Use and its allocation of intellectual property rights. Different types of Thingiverse licences will be detailed and explained. Second, the empirical metadata we have collected from Thingiverse will be presented, including the methods used to obtain this information. Third, we will present findings from this data on licence choice and the public availability of user designs. Fourth, we will look at the implications of these findings and our conclusions regarding the particular kind of sharing ethic that is present in Thingiverse; we also consider the “closed” aspects of this community and what this means for current debates about “open” innovation.