Online retail in Australia 2007-2013

This study of online retail in Australia from 2007-13, part of the World Internet Project (WIP) reveals a consistent pattern of large increases in the number of online purchases made by Australian consumers, reaching an average expenditure of 2616 a year in 2013. Online shopping in Australia is enjoying a strong second wave of growth as more consumers build internet browsing, purchasing and financial transactions into their everyday lives.  After an apparent plateau between 2009 and 2011, this latest survey confirms that online shopping by Australian consumers grew strongly again between 2011 and 2013.  The mean value of monthly online purchases by Australians grew by 5.8% to 218 from 2011-13, while the actual number of internet purchases grew by 46.2%. Men are still the internet shopping kings, buying $229 in online goods a month, compared to women’s purchases of$204. The good news for Australian businesses is that local retailers are maintaining their share of this growth, as Australian consumers maintain their strong preference for shopping with domestically-based websites.  Three out of ten Australians now shop online every week, or more often, compared with two in ten New Zealanders and one in ten Swiss. There has also been a continued major upsurge in the number of Australians using the internet for financial transactions. For example people making travel bookings online grew from 49% in 2007 to 73% in 2013, those paying bills grew from 43% to 72% and those purchasing event tickets from 36% to 65%. The latest survey also reveals renewed growth in Australians buying digital content – movies, books, music, games etc – online rather than in-store. The WIP is conducted in 30 countries round the world to compare internet use and behaviour. In Australia it consists of an annual survey of 1000 people aged 18 or older and has been running since 2007. The WIP is part of the ARC Centre of Excellence for Creative Industries and Innovation. • Dr Scott Ewing is a Senior Research Fellow at the Swinburne Institute for Social Research and at the ARC Centre of Excellence in Creative Industries and Innovation. &nbsp

CCi digital futures 2014: the Internet in Australia

This report presents findings from the third survey of the Australian component of the World Internet Project. The survey was conducted in late 2013. This research is a project of the ARC Centre of Excellence for Creative Industries and Innovation at the Swinburne Institute for Social Research, Swinburne University of Technology. This report provides an overview of the study, presenting a broad picture of the Internet in Australia, with comparisons to our earlier 2007, 2009 and 2013 studies, and to the international findings of our partners in the World Internet Project. At the end of each section we have added some further analysis, examining aspects of the Australian data in more detail, and providing some international context using results from the findings of our international research partners. &nbsp

Success rates of re-excision after positive margins for invasive lobular carcinoma of the breast.

Rates of positive margins after surgical resection of invasive lobular carcinoma (ILC) are high (ranging from 18 to 60%), yet the efficacy of re-excision lumpReceptor subtypeectomy for clearing positive margins is unknown. Concerns about the diffuse nature of ILC may drive increased rates of completion mastectomy to treat positive margins, thus lowering breast conservation rates. We therefore determined the success rate of re-excision lumpectomy in women with ILC and positive margins after surgical resection. We identified 314 cases of stage I-III ILC treated with breast conserving surgery (BCS) at the University of California, San Francisco. Surgical procedures, pathology reports, and outcomes were analyzed using univariate and multivariate statistics and Cox-proportional hazards models. We evaluated outcomes before and after the year 2014, when new margin management consensus guidelines were published. Positive initial margins occurred in 118 (37.6%) cases. Of these, 62 (52.5%) underwent re-excision lumpectomy, which cleared the margin in 74.2%. On multivariate analysis, node negativity was significantly associated with successful re-excision (odds ratio [OR] 3.99, 95% CI 1.15-13.81, p = 0.029). After 2014, we saw fewer initial positive margins (42.7% versus 25.5%, p = 0.009), second surgeries (54.6% versus 20.2%, p < 0.001), and completion mastectomies (27.7% versus 4.5%, p < 0.001). In this large cohort of women with ILC, re-excision lumpectomy was highly successful at clearing positive margins. Additionally, positive margins and completion mastectomy rates significantly decreased over time. These findings highlight improvements in management of ILC, and suggest that completion mastectomy may not be required for those with positive margins after initial BCS

A Polypharmacological Approach to Relapse Prevention in an Animal Model of Heroin Addiction

Chemical compounds that target dopamine (DA) D1 or D3 receptors have shown promise as potential interventions in animal models of cue-induced relapse. However, undesirable side effects or pharmacodynamic profiles have limited the advancement of new compounds in preclinical studies when administered as independent treatments. In this series of experiments, we explored the effects of co-administration of a D1-recepter partial agonist (SKF 77434) and a D3-receptor antagonist (NGB 2904) in heroin-seeking rats within a ‘conflict’ model of abstinence and cue-induced relapse. Rats were first trained to press a lever to self-administer heroin and drug delivery was paired contingently with cues (e.g., light, pump noise). Self-initiated abstinence was facilitated by applying electrical current to the flooring in front of the levers. Lastly, a relapse response was provoked by noncontingent presentation of conditioned cues. Prior to provocation, rats received a systemic injection of SKF 77434, NGB 2904, or a combination of both compounds to assess treatment effects on lever pressing. Results indicated that the co-administration of low (i.e., independently ineffective) doses of both compounds was more effective in reducing cue-induced relapse to heroin seeking than either compound alone, with some evidence of drug synergism. Follow-up studies indicated that this reduction was not due to motoric impairment nor enhanced sensitivity to the electrified flooring and that this treatment did not significantly affect motivation for food. Implications for the treatment of opiate use disorder and recommendations for further research are discussed

Degradation of Perfluorinated Ether Lubricants on Pure Aluminum Surfaces: Semiempirical Quantum Chemical Modeling

The AM1 semiempirical quantum chemical method was used to model the interaction of perfluoroethers with aluminum surfaces. Perfluorodimethoxymethane and perfluorodimethyl ether were studied interacting with aluminum surfaces, which were modeled by a five-atom cluster and a nine-atom cluster. Interactions were studied for edge (high index) sites and top (low index) sites of the clusters. Both dissociative binding and nondissociative binding were found, with dissociative binding being stronger. The two different ethers bound and dissociated on the clusters in different ways: perfluorodimethoxymethane through its oxygen atoms, but perfluorodimethyl ether through its fluorine atoms. The acetal linkage of perfluorodimeth-oxymethane was the key structural feature of this molecule in its binding and dissociation on the aluminum surface models. The high-index sites of the clusters caused the dissociation of both ethers. These results are consistent with the experimental observation that perfluorinated ethers decompose in contact with sputtered aluminum surfaces

Predictive Models for Bariatric Surgery Risks with Imbalanced Medical Datasets

Bariatric surgery (BAR) has become a popular treatment for type 2 diabetes mellitus (T2DM) which is among the most critical obesity-related comorbidities. Patients who have bariatric surgery, are exposed to complications after surgery. Furthermore, the mid- to long-term complications after bariatric surgery can be deadly and increase the complexity of managing safety of these operations and healthcare costs. Current studies on BAR complications have mainly used risk scoring for identifying patients who are more likely to have complications after surgery. Though, these studies do not take into considera-tion the imbalanced nature of the data where the size of the class of interest (patients who have complications after surgery) is relatively small. We propose the use of imbalanced classification techniques to tackle the imbalanced bariatric surgery data: synthetic minority oversampling technique (SMOTE), random undersampling, and en-semble learning classification methods including Random Forest, Bagging, and AdaBoost. Moreover, we improve classification performance through using Chi-Squared, Information Gain, and Correlation-based feature selection (CFS) techniques. We study the Premier Healthcare Database with focus on the most-frequent complications includ-ing Diabetes, Angina, Heart Failure, and Stroke. Our results show that the ensemble learning-based classification techniques using any feature selection method mentioned above are the best approach for handling the imbalanced nature of the bariatric surgical outcome data. In our evaluation, we find a slight preference toward using SMOTE method compared to the random undersampling method. These results demonstrate the potential of machine-learning tools as clinical decision support in identifying risks/outcomes associated with bariatric surgery and their effectiveness in reducing the surgery complications as well as improving patient care

A direct urea fuel cell - power from fertiliser and waste

For the first time, a working direct urea and direct urine fuel cell has been developed to generate electricity directly from urea or urine

A new approach to numerical characterisation of wear particle surfaces in three-dimensions for wear study

In the wear and tear process of synovial joints, wear particles generated and released from articular cartilage within the joints have surface topography and mechanical property which can be used to reveal wear conditions. Three-dimensional (3D) particle images acquired using laser scanning confocal microscopy (LSCM) contain appropriate surface information for quantitatively characterizing the surface morphology and changes to seek a further understanding of the wear process and wear features. This paper presents a new attempt on the 3D numerical characterisation of wear particle surfaces using the field and feature parameter sets which are defined in ISO/FDIS 25178-2. Based on the innovative pattern recognition capability, the feature parameters are, for the first time, employed for quantitative analysis of wear debris surface textures. Through performing parameter classification, ANOVA analysis and correlation analysis, typical changing trends of the surface transformation of the wear particles along with the severity of wear conditions and osteoarthritis (OA) have been observed. Moreover, the feature parameters have shown a significant sensitivity with the wear particle surfaces texture evolution under OA development. A correlation analysis of the numerical analysis results of cartilage surface texture variations and that of their wear particles has been conducted in this study. Key surface descriptors have been determined. Further research is needed to verify the above outcomes using clinic samples