Self assembly of plasmonic core-satellite nano-assemblies mediated by hyperbranched polymer linkers

The morphology of plasmonic nano-assemblies has a direct influence on optical properties, such as localised surface plasmon resonance (LSPR) and surface enhanced Raman scattering (SERS) intensity. Assemblies with core-satellite morphologies are of particular interest, because this morphology has a high density of hot-spots, while constraining the overall size. Herein, a simple method is reported for the self-assembly of gold NPs nano-assemblies with a core-satellite morphology, which was mediated by hyperbranched polymer (HBP) linkers. The HBP linkers have repeat units that do not interact strongly with gold NPs, but have multiple end-groups that specifically interact with the gold NPs and act as anchoring points resulting in nano-assemblies with a large (~48 nm) core surrounded by smaller (~15 nm) satellites. It was possible to control the number of satellites in an assembly which allowed optical parameters such as SPR maxima and the SERS intensity to be tuned. These results were found to be consistent with finite-difference time domain (FDTD) simulations. Furthermore, the multiplexing of the nano-assemblies with a series of Raman tag molecules was demonstrated, without an observable signal arising from the HBP linker after tagging. Such plasmonic nano-assemblies could potentially serve as efficient SERS based diagnostics or biomedical imaging agents in nanomedicine.

A taxonomy of computation offloading in mobile cloud computing

The ability of cloud computing to provide almost unlimited storage, backup and recovery, and quick deployment contributes to its widespread attention and implementation. Cloud computing has also become an attractive choice for mobile users as well. Due to limited features of mobile devices such as power scarcity and inability to cater computationintensive tasks, selected computation needs to be outsourced to the resourceful cloud servers. However, there are many challenges which need to be addressed in computation offloading for mobile cloud computing such as communication cost, connectivity maintenance and incurred latency. This paper presents taxonomy of the computation offloading approaches which aim to address the challenges. The taxonomy provides guidelines to identify research scopes in computation offloading for mobile cloud computing. We also outline directions and anticipated trends for future research.

Everyone’s watching it : the role of hype in television engagement through social media

Social media is playing an ever-increasing role in both viewers engagement with television and in the television industries evaluation of programming, in Australia – which is the focus of our study - and beyond. Twitter hashtags and viewer comments are increasingly incorporated into broadcasts, while Facebook fan pages provide a means of marketing upcoming shows and television personalities directly into the social media feed of millions of users. Additionally, bespoke applications such as FanGo and ZeeBox, which interact with the mainstream social networks, are increasingly being utilized by broadcasters for interactive elements of programming (c.f. Harrington, Highfield and Bruns, 2012). However, both the academic and industry study of these platforms has focused on the measure of content during the specific broadcast of the show, or a period surrounding it (e.g. 3 hours before until 3 am the next day, in the case of 2013 Nielsen SocialGuide reports). In this paper, we argue that this focus ignores a significant period for both television producers and advertisers; the lead-up to the program. If, as we argue elsewhere (Bruns, Woodford, Highfield & Prowd, forthcoming), users are persuaded to engage with content both by advertising of the Twitter hash-tag or Facebook page and by observing their network connections engaging with such content, the period before and between shows may have a significant impact on a viewers likelihood to watch a show. The significance of this period for broadcasters is clearly highlighted by the efforts they afford to advertising forthcoming shows through several channels, including television and social media, but also more widely. Biltereyst (2004, p.123) has argued that reality television generates controversy to receive media attention, and our previous small-scale work on reality shows during 2013 and 2014 supports the theory that promoting controversial behavior is likely to lead to increased viewing (Woodford & Prowd, 2014a). It remains unclear, however, to what extent this applies to other television genres. Similarly, while networks use of social media has been increasing, best practices remain unclear. Thus, by applying our telemetrics, that is social media metrics for television based on sabermetric approaches (Woodford, Prowd & Bruns, forthcoming; c.f. Woodford & Prowd, 2014b), to the period between shows, we are able to better understand the period when key viewing decisions may be made, to establish the significance of observing discussions within your network during the period between shows, and identify best practice examples of promoting a show using social media.

Decision strategies for automated visual collision avoidance

This paper provides a preliminary analysis of an autonomous uncooperative collision avoidance strategy for unmanned aircraft using image-based visual control. Assuming target detection, the approach consists of three parts. First, a novel decision strategy is used to determine appropriate reference image features to track for safe avoidance. This is achieved by considering the current rules of the air (regulations), the properties of spiral motion and the expected visual tracking errors. Second, a spherical visual predictive control (VPC) scheme is used to guide the aircraft along a safe spiral-like trajectory about the object. Lastly, a stopping decision based on thresholding a cost function is used to determine when to stop the avoidance behaviour. The approach does not require estimation of range or time to collision, and instead relies on tuning two mutually exclusive decision thresholds to ensure satisfactory performance.

Asymmetric price range effects on vertical extensions

Vertical line extensions, both step-up and step-down, are common occurrence in consumer products. For example, Timex recently launched its luxury high-end Valentino line. On the other hand, many companies use downscale extensions to increase the overall sales volume. For instance, a number of luxury watch brands recently introduced watch collections with lower price points, like TAG Heur’s affordable watch the Aquaracer Calibre 5. Previous literature on vertical extensions has investigated how number of products in the line (Dacin and Smith 1994), the direction of the extension, brand concept (Kim, Lavack, and Smith 2001), and perceived risk (Lei, de Ruyter, and Wetzels 2008) affect extensions’ evaluation. Common to this literature is the use of models based on adaptation-level theory, which states that all relevant price information is integrated into a single prototype value and used in consumer judgments of price (Helson 1947; Mazumdar, Raj, and Sinha 2005). In the current research we argue that, while adaptation-level theory can be viewed as a useful simplification to understanding consumers’ evaluations, it misses out important contextual influences caused by a brand’s price range. Drawing on research on range-frequency theory (Mellers and Cooke 1994; Parducci 1965) we investigate the effects of price point distance and parent brand’s price range on evaluations of vertical extensions. Our reasoning leads to two important predictions that we test in a series of three experiments...

Practical visual odometry for car-like vehicles

A method for calculating visual odometry for ground vehicles with car-like kinematic motion constraints similar to Ackerman's steering model is presented. By taking advantage of this non-holonomic driving constraint we show a simple and practical solution to the odometry calculation by clever placement of a single camera. The method has been implemented successfully on a large industrial forklift and a Toyota Prado SUV. Results from our industrial test site is presented demonstrating the applicability of this method as a replacement for wheel encoder-based odometry for these vehicles.

Gelatine

A Social Public Display to Facilitate Shared Encounters in Coworking Spaces The idea behind ‘Gelatine’ is a system that facilitates shared encounters between coworkers and library users by allowing them to digitally ‘check in’ at a work space. Gelatine displays skills, areas of interest, and needs of currently present coworkers on a public screen. The system provides an online / mobile website for users to create a personal profile with keywords (‘tags’) that describe their skills, areas of interests, as well as areas that they have a problem in or want to learn more about. This profile information is linked to their RFID membership card, which they can swipe at one of the ‘checkin-points’ at the entrance or specific sub locations such as individual desks or coffee kiosk to confirm their presence in the space.

Supporting collaboration on very large-scale interactive wall surfaces

In this paper we describe CubIT, a multi-user presentation and collaboration system installed at the Queensland University of Technology’s (QUT) Cube facility. The ‘Cube’ is an interactive visualisation facility made up of five very large-scale interactive multi-panel wall displays, each consisting of up to twelve 55-inch multi-touch screens (48 screens in total) and massive projected display screens situated above the display panels. The paper outlines the unique design challenges, features, implementation and evaluation of CubIT. The system was built to make the Cube facility accessible to QUT’s academic and student population. CubIT enables users to easily upload and share their own media content, and allows multiple users to simultaneously interact with the Cube’s wall displays. The features of CubIT were implemented via three user interfaces, a multi-touch interface working on the wall displays, a mobile phone and tablet application and a web-based content management system. Each of these interfaces plays a different role and offers different interaction mechanisms. Together they support a wide range of collaborative features including multi-user shared workspaces, drag and drop upload and sharing between users, session management and dynamic state control between different parts of the system. The results of our evaluation study showed that CubIT was successfully used for a variety of tasks, and highlighted challenges with regards to user expectations regarding functionality as well as issues arising from public use.

Fine-mapping the HOXB region detects common variants tagging a rare coding allele : evidence for synthetic association in prostate cancer

The HOXB13 gene has been implicated in prostate cancer (PrCa) susceptibility. We performed a high resolution fine-mapping analysis to comprehensively evaluate the association between common genetic variation across the HOXB genetic locus at 17q21 and PrCa risk. This involved genotyping 700 SNPs using a custom Illumina iSelect array (iCOGS) followed by imputation of 3195 SNPs in 20,440 PrCa cases and 21,469 controls in The PRACTICAL consortium. We identified a cluster of highly correlated common variants situated within or closely upstream of HOXB13 that were significantly associated with PrCa risk, described by rs117576373 (OR 1.30, P = 2.62×10(-14)). Additional genotyping, conditional regression and haplotype analyses indicated that the newly identified common variants tag a rare, partially correlated coding variant in the HOXB13 gene (G84E, rs138213197), which has been identified recently as a moderate penetrance PrCa susceptibility allele. The potential for GWAS associations detected through common SNPs to be driven by rare causal variants with higher relative risks has long been proposed; however, to our knowledge this is the first experimental evidence for this phenomenon of synthetic association contributing to cancer susceptibility.

Aspect-based opinion extraction from customer reviews

Text is the main method of communicating information in the digital age. Messages, blogs, news articles, reviews, and opinionated information abounds on the Internet. People commonly purchase products online and post their opinions about purchased items. This feedback is displayed publicly to assist others with their purchasing decisions, creating the need for a mechanism with which to extract and summarize useful information for enhancing the decision-making process. Our contribution is to improve the accuracy of extraction by combining different techniques from three major areas, named Data Mining, Natural Language Processing techniques and Ontologies. The proposed framework sequentially mines product’s aspects and users’ opinions, groups representative aspects by similarity, and generates an output summary. This paper focuses on the task of extracting product aspects and users’ opinions by extracting all possible aspects and opinions from reviews using natural language, ontology, and frequent “tag” sets. The proposed framework, when compared with an existing baseline model, yielded promising results.

A two-stage item recommendation method using probabilistic ranking with reconstructed tensor model

In a tag-based recommender system, the multi-dimensional tag> correlation should be modeled effectively for finding quality recommendations. Recently, few researchers have used tensor models in recommendation to represent and analyze latent relationships inherent in multi-dimensions data. A common approach is to build the tensor model, decompose it and, then, directly use the reconstructed tensor to generate the recommendation based on the maximum values of tensor elements. In order to improve the accuracy and scalability, we propose an implementation of the -mode block-striped (matrix) product for scalable tensor reconstruction and probabilistically ranking the candidate items generated from the reconstructed tensor. With testing on real-world datasets, we demonstrate that the proposed method outperforms the benchmarking methods in terms of recommendation accuracy and scalability.

Electrochemical current rectification – a novel signal amplification strategy for highly sensitive and selective aptamer-based biosensor

Electrochemical aptamer-based (E-AB) sensors represent an emerging class of recently developed sensors. However, numerous of these sensors are limited by a low surface density of electrode-bound redox-oligonucleotides which are used as probe. Here we propose to use the concept of electrochemical current rectification (ECR) for the enhancement of the redox signal of E-AB sensors. Commonly, the probe-DNA performs a change in conformation during target binding and enables a nonrecurring charge transfer between redox-tag and electrode. In our system, the redox-tag of the probe-DNA is continuously replenished by solution-phase redox molecules. A unidirectional electron transfer from electrode via surface-linked redox-tag to the solution-phase redox molecules arises that efficiently amplifies the current response. Using this robust and straight-forward strategy, the developed sensor showed a substantial signal amplification and consequently improved sensitivity with a calculated detection limit of 114 nM for ATP, which was improved by one order of magnitude compared with the amplification-free detection and superior to other previous detection results using enzymes or nanomaterials-based signal amplification. To the best of our knowledge, this is the first demonstration of an aptamer-based electrochemical biosensor involving electrochemical rectification, which can be presumably transferred to other biomedical sensor systems.

Inspection of pole-like structures using a vision-controlled VTOL UAV and shared autonomy

We present an approach for the inspection of vertical pole-like infrastructure using a vertical take-off and landing (VTOL) unmanned aerial vehicle and shared autonomy. Inspecting vertical structures, such as light and power distribution poles, is a time consuming, dangerous and expensive task with high operator workload. To address these issues, we propose a VTOL platform that can operate at close-quarters, whilst maintaining a safe stand-off distance and rejecting environmental disturbances. We adopt an Image based Visual Servoing (IBVS) technique using only two line features to stabilise the vehicle with respect to a pole. Visual, inertial and sonar data are used, making the approach suitable for indoor or GPS-denied environments. Results from simulation and outdoor flight experiments demonstrate the system is able to successfully inspect and circumnavigate a pole.

An efficient tagging data interpretation and representation scheme for item recommendation

A tag-based item recommendation method generates an ordered list of items, likely interesting to a particular user, using the users past tagging behaviour. However, the users tagging behaviour varies in different tagging systems. A potential problem in generating quality recommendation is how to build user profiles, that interprets user behaviour to be effectively used, in recommendation models. Generally, the recommendation methods are made to work with specific types of user profiles, and may not work well with different datasets. In this paper, we investigate several tagging data interpretation and representation schemes that can lead to building an effective user profile. We discuss the various benefits a scheme brings to a recommendation method by highlighting the representative features of user tagging behaviours on a specific dataset. Empirical analysis shows that each interpretation scheme forms a distinct data representation which eventually affects the recommendation result. Results on various datasets show that an interpretation scheme should be selected based on the dominant usage in the tagging data (i.e. either higher amount of tags or higher amount of items present). The usage represents the characteristic of user tagging behaviour in the system. The results also demonstrate how the scheme is able to address the cold-start user problem.

Design of high mobility DPP-based polymer semiconductors for organic thin film transistors

π-Conjugated polymers are the most promising semiconductor materials to enable printed organic thin film transistors (OTFTs) due to their excellent solution processability and mechanical robustness. However, solution-processed polymer semiconductors have shown poor charge transport properties mainly originated from the disordered polymer chain packing in the solid state as compared to the thermally evaporated small molecular organic semiconductors. The low charge carrier mobility, typically < 0.1 cm2 /V.s, of polymer semiconductors poses a challenge for most intended applications such as displays and radio-frequency identification (RFID) tags. Here we present our recent results on the dike topyrrolopyrrole (DPP)-based polymers and demonstrate that when DPP is combined with appropriate electron donating moieties such as thiophene and thienothiophene, very high charge carrier mobility values of ~1 cm2/V.s could be achieved.