A novel corepressor, BCoR-L1, represses transcription through an interaction with CtBP

Corepressors play a crucial role in negative gene regulation and are defective in several diseases. BCoR is a corepressor for the BCL6 repressor protein. Here we describe and functionally characterize BCoR-L1, a homolog of BCoR. When tethered to a heterologous promoter, BCoR-L1 is capable of strong repression. Like other corepressors, BCoR-L1 associates with histone deacetylase (HDAC) activity. Specifically, BCoR-L1 coprecipitates with the Class II HDACs, HDAC4, HDAC5, and HDAC7, suggesting that they are involved in its role as a transcriptional repressor. BCoR-L1 also interacts with the CtBP corepressor through a CtBP-interacting motif in its amino terminus. Abrogation of the CtBP binding site within BCoR-L1 partially relieves BCoR-L1-mediated transcriptional repression. Furthermore, BCoR-L1 is located on the E-cadherin promoter, a known CtBP-regulated promoter, and represses the E-cadherin promoter activity in a reporter assay. The inhibition of BCoR-L1 expression by RNA-mediated interference results in derepression of E-cadherin in cells that do not normally express E-cadherin, indicating that BCoR-L1 contributes to the repression of an authentic endogenous CtBP target.

Physical and functional interaction of the archaeal single-stranded DNA-binding protein SSB with RNA polymerase

Archaeal transcription utilizes a complex multisubunit RNA polymerase and the basal transcription factors TBP and TF(II)B, closely resembling its eukaryal counterpart. We have uncovered a tight physical and functional interaction between RNA polymerase and the single-stranded DNA-binding protein SSB in Sulfolobus solfataricus. SSB stimulates transcription from promoters in vitro under TBP-limiting conditions and supports transcription in the absence of TBP. SSB also rescues transcription from repression by reconstituted chromatin. We demonstrate the potential for promoter melting by SSB, suggesting a plausible basis for the stimulation of transcription. This stimulation requires both the single-stranded DNA-binding domain and the acidic C-terminal tail of the SSB. The tail forms a stable interaction with RNA polymerase. These data reveal an unexpected role for single-stranded DNA-binding proteins in transcription in archaea.

Cultivating Innovation through Social Relationships: A Qualitative Study of Outstanding Australian Innovators in Science, Technology and the Creative Industries

In this chapter, we describe and explore social relationship patterns associated with outstanding innovation. In doing so, we draw upon the findings of 16 in-depth interviews with award-winning Australian innovators from science & technology and the creative industries. The interviews covered topics relating to various influences on individual innovation capacity and career development. We found that for all of the participants, innovation was a highly social process. Although each had been recognised individually for their innovative success, none worked in isolation. The ability to generate innovative outcomes was grounded in certain types of interaction and collaboration. We outline the distinctive features of the social relationships which seem to be important to innovation, and ask which ‘social network capabilities’ might underlie the ability to create an optimal pattern of interpersonal relationships. We discuss the implications of these findings for universities, which we argue play a key role in the development of nascent innovators.

Digital image processing techniques for pavement macro-texture analysis

Road surface macro-texture is an indicator used to determine the skid resistance levels in pavements. Existing methods of quantifying macro-texture include the sand patch test and the laser profilometer. These methods utilise the 3D information of the pavement surface to extract the average texture depth. Recently, interest in image processing techniques as a quantifier of macro-texture has arisen, mainly using the Fast Fourier Transform (FFT). This paper reviews the FFT method, and then proposes two new methods, one using the autocorrelation function and the other using wavelets. The methods are tested on pictures obtained from a pavement surface extending more than 2km's. About 200 images were acquired from the surface at approx. 10m intervals from a height 80cm above ground. The results obtained from image analysis methods using the FFT, the autocorrelation function and wavelets are compared with sensor measured texture depth (SMTD) data obtained from the same paved surface. The results indicate that coefficients of determination (R2) exceeding 0.8 are obtained when up to 10% of outliers are removed.

High resolution tiled display walls

Scalable high-resolution tiled display walls are becoming increasingly important to decision makers and researchers because high pixel counts in combination with large screen areas facilitate content rich, simultaneous display of computer-generated visualization information and high-definition video data from multiple sources. This tutorial is designed to cater for new users as well as researchers who are currently operating tiled display walls or 'OptiPortals'. We will discuss the current and future applications of display wall technology and explore opportunities for participants to collaborate and contribute in a growing community. Multiple tutorial streams will cover both hands-on practical development, as well as policy and method design for embedding these technologies into the research process. Attendees will be able to gain an understanding of how to get started with developing similar systems themselves, in addition to becoming familiar with typical applications and large-scale visualisation techniques. Presentations in this tutorial will describe current implementations of tiled display walls that highlight the effective usage of screen real-estate with various visualization datasets, including collaborative applications such as visualcasting, classroom learning and video conferencing. A feature presentation for this tutorial will be given by Jurgen Schulze from Calit2 at the University of California, San Diego. Jurgen is an expert in scientific visualization in virtual environments, human-computer interaction, real-time volume rendering, and graphics algorithms on programmable graphics hardware.

Frequency decomposition techniques for increased discriminative 3D facial information capture

Eigen-based techniques and other monolithic approaches to face recognition have long been a cornerstone in the face recognition community due to the high dimensionality of face images. Eigen-face techniques provide minimal reconstruction error and limit high-frequency content while linear discriminant-based techniques (fisher-faces) allow the construction of subspaces which preserve discriminatory information. This paper presents a frequency decomposition approach for improved face recognition performance utilising three well-known techniques: Wavelets; Gabor / Log-Gabor; and the Discrete Cosine Transform. Experimentation illustrates that frequency domain partitioning prior to dimensionality reduction increases the information available for classification and greatly increases face recognition performance for both eigen-face and fisher-face approaches.

Design for inspiration : children, personal connections and educational technology

The project is working towards building an understanding of the personal interests and experiences of children with the aim of designing appropriate, usable and, most importantly, inspirational educational technology. kidprobe, an adaptation of the technology probe concept, has been used as a lightweight method of gaining contextual information about children's interactions with 'fun' technology. kidprobe has produced design inspiration which focuses primarily on the social and emotional connections children made. The use of kidprobe has generated some important ideas for improving the use of probes with children. It is an important first step in understanding how to effectively adapt probing techniques to inspire the design of technology for children.

Addressing sustainable living using a collaborative approach and multi-disciplinary techniques

In order to achieve meaningful reductions in individual ecological footprints, individuals must dramatically alter their day to day behaviours. Effective interventions will need to be evidence based and there is a necessity for the rapid transfer or communication of information from the point of research, into policy and practice. A number of health disciplines, including psychology and public health, share a common mission to promote health and well-being and it is becoming clear that the most practical pathway to achieving this mission is through interdisciplinary collaboration. This paper argues that an interdisciplinary collaborative approach will facilitate research that results in the rapid transfer of findings into policy and practice. The application of this approach is described in relation to the Green Living project which explored the psycho-social predictors of environmentally friendly behaviour. Following a qualitative pilot study, and in consultation with an expert panel comprising academics, industry professionals and government representatives, a self-administered mail survey was distributed to a random sample of 3000 residents of Brisbane and Moreton Bay (Queensland, Australia). The Green Living survey explored specific beliefs which included attitudes, norms, perceived control, intention and behaviour, as well as a number of other constructs such as environmental concern and altruism. This research has two beneficial outcomes. First, it will inform a practical model for predicting sustainable living behaviours and a number of local councils have already expressed an interest in making use of the results as part of their ongoing community engagement programs. Second, it provides an example of how a collaborative interdisciplinary project can provide a more comprehensive approach to research than can be accomplished by a single disciplinary project.

A methodology for object identification and tracking in construction based on spatial modeling and image matching techniques

Understanding the motion characteristics of on-site objects is desirable for the analysis of construction work zones, especially in problems related to safety and productivity studies. This article presents a methodology for rapid object identification and tracking. The proposed methodology contains algorithms for spatial modeling and image matching. A high-frame-rate range sensor was utilized for spatial data acquisition. The experimental results indicated that an occupancy grid spatial modeling algorithm could quickly build a suitable work zone model from the acquired data. The results also showed that an image matching algorithm is able to find the most similar object from a model database and from spatial models obtained from previous scans. It is then possible to use the matched information to successfully identify and track objects.

Machine learning techniques to improve software quality

A significant proportion of the cost of software development is due to software testing and maintenance. This is in part the result of the inevitable imperfections due to human error, lack of quality during the design and coding of software, and the increasing need to reduce faults to improve customer satisfaction in a competitive marketplace. Given the cost and importance of removing errors improvements in fault detection and removal can be of significant benefit. The earlier in the development process faults can be found, the less it costs to correct them and the less likely other faults are to develop. This research aims to make the testing process more efficient and effective by identifying those software modules most likely to contain faults, allowing testing efforts to be carefully targeted. This is done with the use of machine learning algorithms which use examples of fault prone and not fault prone modules to develop predictive models of quality. In order to learn the numerical mapping between module and classification, a module is represented in terms of software metrics. A difficulty in this sort of problem is sourcing software engineering data of adequate quality. In this work, data is obtained from two sources, the NASA Metrics Data Program, and the open source Eclipse project. Feature selection before learning is applied, and in this area a number of different feature selection methods are applied to find which work best. Two machine learning algorithms are applied to the data - Naive Bayes and the Support Vector Machine - and predictive results are compared to those of previous efforts and found to be superior on selected data sets and comparable on others. In addition, a new classification method is proposed, Rank Sum, in which a ranking abstraction is laid over bin densities for each class, and a classification is determined based on the sum of ranks over features. A novel extension of this method is also described based on an observed polarising of points by class when rank sum is applied to training data to convert it into 2D rank sum space. SVM is applied to this transformed data to produce models the parameters of which can be set according to trade-off curves to obtain a particular performance trade-off.

Innovation, interaction, and inclusion : heritage luxury brands in collusion with the consumer

Many luxury heritage brands operate on the misconception that heritage is interchangeable with history rather than representative of the emotional response they originally developed in their customer. This idea of heritage as static history inhibits innovation, prevents dynamic renewal and impedes their ability to redefine, strengthen and position their brand in current and emerging marketplaces. This paper examines a number of heritage luxury brands that have successfully identified the original emotional responses they developed in their customers and, through innovative approaches in design, marketing, branding and distribution evoke these responses in contemporary consumers. Using heritage and innovation hand-in-hand, these brands have continued to grow and develop a vision of heritage that incorporates both historical and contemporary ideas to meet emerging customer needs. While what constitutes a ‘luxury’ item is constantly challenged in this era of accessible luxury products, up-scaling and aspirational spending, this paper sees consumers’ emotional needs as the key element in defining the concept of luxury. These emotional qualities consistently remain relevant due to their ability to enhance a positive sense of identity for the brand user. Luxury is about the ‘experience’ not just the product providing the consumer with a sense of enhanced status or identity through invoked feelings of exclusivity, authenticity, quality, uniqueness and culture. This paper will analyse luxury heritage brands that have successfully combined these emotional values with those of their ‘heritage’ to create an aura of authenticity and nostalgia that appeals to contemporary consumers. Like luxury, the line where clothing becomes fashion is blurred in the contemporary fashion industry; however, consumer emotion again plays an important role. For example, clothing becomes ‘fashion’ for consumers when it affects their self perception rather than fulfilling basic functions of shelter and protection. Successful luxury heritage brands can enhance consumers’ sense of self by involving them in the ‘experience’ and ‘personality’ of the brand so they see it as a reflection of their own exclusiveness, authentic uniqueness, belonging and cultural value. Innovation is a valuable tool for heritage luxury brands to successfully generate these desired emotional responses and meet the evolving needs of contemporary consumers. While traditionally fashion has been a monologue from brand to consumer, new technology has given consumers a voice to engage brands in a conversation to express their evolving needs, ideas and feedback. As a result, in this consumer-empowered era of information sharing, this paper defines innovation as the ability of heritage luxury brands to develop new design and branding strategies in response to this consumer feedback while retaining the emotional core values of their heritage. This paper analyses how luxury heritage brands can effectively position themselves in the contemporary marketplace by separating heritage from history to incorporate innovative strategies that will appeal to consumer needs of today and tomorrow.

Improving team dynamics and innovation : the “Aspect Design” approach applied to interaction design

Interaction Design is a fast developing branch of Industrial Design. The availability of cheap microprocessors and sensor electronics allow interactions between people and products that were until recently impossible. This has added additional layers of complexity to the design process. Novice designers find it difficult to effectively juggle these complexities and typically tend to focus on one aspect at a time. They also tend to take a linear, step-by-step approach to the design process in contrast to expert designers who pursue “parallel lines of thought” whilst simultaneously co-evolving both problem and solution. (Lawson, 1993) This paper explores an approach that encourages designers (in this case novice designers) to take a parallel rather than linear approach to the design process. It also addresses the problem of social loafing that tends to occur in team activities.

Study of the interaction between 10-hydroxycamptothecine and DNA with the use of ethidium bromide dye as a fluorescence probe

The interaction of 10-hydroxycamptothecine (HCPT) with DNA under pseudo-physiological conditions (Tris-HCl buffer of pH 7.4), using ethidium bromide (EB) dye as a probe, was investigated with the use of spectrofluorimetry, UV-vis spectrometry and viscosity measurement. The binding constant and binding number for HCPT with DNA were evaluated as (7.1 ± 0.5) × 104 M-1 and 1.1, respectively, by multivariate curve resolution-alternating least squares (MCR-ALS). Moreover, parallel factor analysis (PARAFAC) was applied to resolve the three-way fluorescence data obtained from the interaction system, and the concentration information for the three components of the system at equilibrium was simultaneously obtained. It was found that there was a cooperative interaction between the HCPT-DNA complex and EB, which produced a ternary complex of HCPT-DNA-EB. © 2011 Elsevier B.V.

Intimate transactions : art, exhibition and interaction within distributed network environments

The broad research questions of the book are: How can successful, interdisciplinary collaboration contribute to research innovation through Practice-led research? What contributes to the design, production and curation of successful new media art? What are the implications of exhibiting it across dual sites for artists, curators and participant audiences? Is it possible to create an 'intimate transaction' between people who are separated by vast distances but joined by interfaces and distributed networks? Centred on a new media work of the same name by the Transmute Collective (led by Keith Armstrong), this book provides insights from multidisciplinary perspectives. Visual, sound and performance artists, furniture designers, spatial architects, technology systems designers, and curators who collaborated in the production of Intimate Transactions discuss their design philosophies, working processes and resolution of this major new media work. Analytical and philosophical essays by international writers complement these writings on production. They consider how new media art, like Intimate Transactions, challenges traditional understandings of art, curatorial installation and exhibition experience because of the need to take into account interaction, the reconfiguration of space, co-presence, performativity and inter-site collaboration.