Nature and extent of genetic diversity of dengue viruses determined by 454 pyrosequencing

Dengue virus (DENV) populations are characteristically highly diverse. Regular lineage extinction and replacement is an important dynamic DENV feature, and most DENV lineage turnover events are associated with increased incidence of disease. The role of genetic diversity in DENV lineage extinctions is not understood. We investigated the nature and extent of genetic diversity in the envelope (E) gene of DENV serotype 1 representing different lineages histories. A region of the DENV genome spanning the E gene was amplified and sequenced by Roche/454 pyrosequencing. The pyrosequencing results identified distinct sub-populations (haplotypes) for each DENV-1 E gene. A phylogenetic tree was constructed with the consensus DENV-1 E gene nucleotide sequences, and the sequences of each constructed haplotype showed that the haplotypes segregated with the Sanger consensus sequence of the population from which they were drawn. Haplotypes determined through pyrosequencing identified a recombinant DENV genome that could not be identified through Sanger sequencing. Nucleotide level sequence diversities of DENV-1 populations determined from SNP analysis were very low, estimated from 0.009-0.01. There were also no stop codon, frameshift or non-frameshift mutations observed in the E genes of any lineage. No significant correlations between the accumulation of deleterious mutations or increasing genetic diversity and lineage extinction were observed (p>0.5). Although our hypothesis that accumulation of deleterious mutations over time led to the extinction and replacement of DENV lineages was ultimately not supported by the data, our data does highlight the significant technical issues that must be resolved in the way in which population diversity is measured for DENV and other viruses. The results provide an insight into the within-population genetic structure and diversity of DENV-1 populations.

from "The Roving Party"

They walked down through a dry creek bed lined with swamp gums grown so close together they appeared as one living whole. The men passed around these trees in single file, among sun shafts which pierced the canopy but threw no light upon their faces nor warmed their bones. In the gloom the air was thick with flies and the mushrooms grew like the sightless larvae of some queer and unnamed vermin. Before long they found themselves among a stand of trees which had been stripped of their bark for windbreaks. The naked trunks were carved over with bisected circles, detailings of the moon and sun, images of snakes and roo. The Parramatta men gazed at the finely wrought icons but John Batman found more to hold his attention. Pressed onto the flesh of the tree was a bloody handprint. Batman removed his hat and crouched to examine the ground and Black Bill joined him. One injured man had passed this way...

Comparison of decision tree, support vector machines, and Bayesian network approaches for classification of falls in Parkinson’s disease

Being able to accurately predict the risk of falling is crucial in patients with Parkinson’s dis- ease (PD). This is due to the unfavorable effect of falls, which can lower the quality of life as well as directly impact on survival. Three methods considered for predicting falls are decision trees (DT), Bayesian networks (BN), and support vector machines (SVM). Data on a 1-year prospective study conducted at IHBI, Australia, for 51 people with PD are used. Data processing are conducted using rpart and e1071 packages in R for DT and SVM, con- secutively; and Bayes Server 5.5 for the BN. The results show that BN and SVM produce consistently higher accuracy over the 12 months evaluation time points (average sensitivity and specificity > 92%) than DT (average sensitivity 88%, average specificity 72%). DT is prone to imbalanced data so needs to adjust for the misclassification cost. However, DT provides a straightforward, interpretable result and thus is appealing for helping to identify important items related to falls and to generate fallers’ profiles.

Product-library-derived specification parameters in building information models augmentation

This paper conceptualizes a framework for bridging the BIM (building information modelling)-specifications divide through augmenting objects within BIM with specification parameters derived from a product library. We demonstrate how model information, enriched with data at various LODs (levels of development), can evolve simultaneously with design and construction using different representation of a window object embedded in a wall as lifecycle phase exemplars at different levels of granularity. The conceptual standpoint is informed by the need for exploring a methodological approach which extends beyond current limitations of current modelling platforms in enhancing the information content of BIM models. Therefore, this work demonstrates that BIM objects can be augmented with construction specification parameters leveraging product libraries.

Clinical tips: Mental health and Christmas explained

Christmas is usually a time for celebration, being with family and friends, opening presents, stuffing yourself silly with food at Christmas lunch – then doing it all over again at dinner. However, this may not be the case for some people. Relationships with family may be strained, or there may have been the loss of a loved one or significant other...

Clinical tips: The “12 days of Christmas” - surviving and preparing for Christmas as a retailer

“We wish you a Merry Christmas, and a Happy New Year” ... when the Christmas carols start playing in the pharmacy, it is a reminder the silly season has crept up on us. Christmas should be a time of celebration, fun and spending time with loved ones and families. However, if pharmacies are not prepared it can easily turn into the “nightmare before Christmas”. So to make sure everything runs smoothly like Santa’s schedule, we have compiled a few tips to help retailers survive and prepare for Christmas...

Knowledge discovery from tree databases using balanced optimal search

This research is a step forward in discovering knowledge from databases of complex structure like tree or graph. Several data mining algorithms are developed based on a novel representation called Balanced Optimal Search for extracting implicit, unknown and potentially useful information like patterns, similarities and various relationships from tree data, which are also proved to be advantageous in analysing big data. This thesis focuses on analysing unordered tree data, which is robust to data inconsistency, irregularity and swift information changes, hence, in the era of big data it becomes a popular and widely used data model.

“Come in and look around.” Professional development of student teachers through public pedagogy in a library exhibition

This paper describes a public pedagogy project embedded into "The Global Teacher", a subject within the Bachelor of Education program for student teachers at an Australian university. The subject provides a global perspective on socio-political issues that shape education. In 2013, The Global Teacher introduced an approach that asked student teachers to create a museum-style exhibition depicting six global education themes. This exhibition was displayed in the State Library and the public were invited to engage with the installations and the student teachers who created them. Our paper describes how the project was implemented by means of close collaboration between the QUT teacher educators, curators at the State Library of Queensland (SLQ), and student groups working on visually translating their understandings of global educational issues into a public exhibition. We discuss what was learned by our students and ourselves, as teacher educators, by engaging in this public pedagogy.

Aussie retailers should get their Christmas wish this year

Consumer Sentiment fell by 4.8% in December, but despite the drop other indicators still point toward a robust Christmas period for retailers. Retail trade recorded its strongest result for three consecutive months to October, with Queensland and Western Australia leading the way. A closer inspection of ABS Retail figures indicate six consecutive months of positive results and this suggests consumer confidence has finally returned to the market. But it may not be a rosy outlook for all retail sectors. Overall we are spending more, but not where we once traditionally did.

Sorry Joe, consumer spending will disappoint Santa this Christmas

Treasurer Joe Hockey called on shoppers this week to “not let Santa down” and asked them to spend up big at the stores this Christmas. Unfortunately, the latest retail and consumer confidence data indicate his calls are falling on deaf ears. Westpac’s Consumer Confidence Index shows pessimists outnumber optimists. This has been the case for the last nine months. The index was up 1.9% in November, but still well below its level a year ago.

Five tricks retailers will use to make you shop this Christmas

Australian shoppers are predicted to spend nearly A$47 billion this Christmas. But retailers have to work harder and harder to get shoppers to pull out their wallets. Here are five strategies retailers will be using to get us to part with our hard earned coin.

Activity recognition using binary tree SVM

This paper presents an effective classification method based on Support Vector Machines (SVM) in the context of activity recognition. Local features that capture both spatial and temporal information in activity videos have made significant progress recently. Efficient and effective features, feature representation and classification plays a crucial role in activity recognition. For classification, SVMs are popularly used because of their simplicity and efficiency; however the common multi-class SVM approaches applied suffer from limitations including having easily confused classes and been computationally inefficient. We propose using a binary tree SVM to address the shortcomings of multi-class SVMs in activity recognition. We proposed constructing a binary tree using Gaussian Mixture Models (GMM), where activities are repeatedly allocated to subnodes until every new created node contains only one activity. Then, for each internal node a separate SVM is learned to classify activities, which significantly reduces the training time and increases the speed of testing compared to popular the `one-against-the-rest' multi-class SVM classifier. Experiments carried out on the challenging and complex Hollywood dataset demonstrates comparable performance over the baseline bag-of-features method.

Knowledge unlatched : A global library consortium model for funding Open Access scholarly books

Specialist scholarly books, including monographs, allow researchers to present their work, pose questions and to test and extend areas of theory through long-form writing. In spite of the fact that research communities all over the world value monographs and depend heavily on them as a requirement of tenure and promotion in many disciplines, sales of this kind of book are in free fall, with some estimates suggesting declines of as much as 90% over twenty years (Willinsky 2006). Cashstrapped monograph publishers have found themselves caught in a negative cycle of increasing prices and falling sales, with few resources left to support experimentation, business model innovation or engagement with digital technology and Open Access (OA). This chapter considers an important attempt to tackle failing markets for scholarly monographs, and to enable the wider adoption of OA licenses for book-length works: the 2012 – 2014 Knowledge Unlatched pilot. Knowledge Unlatched is a bold attempt to reconfigure the market for specialist scholarly books: moving it beyond the sale of ‘content’ towards a model that supports the services valued by scholarly and wider communities in the context of digital possibility. Its success has powerful implications for the way we understand copyright’s role in the creative industries, and the potential for established institutions and infrastructure to support the open and networked dynamics of a digital age.

The impact of the public library as a creative place in the community: A contextual review

This review examines recent literature on the public library as a creative place and the ways in which socio-cultural impact is being measured in assessments of cultural value. Inputs such as funding and staffing are frequently measured against outputs such as visitor numbers and lending frequencies, but qualitative measures (outcomes and impacts) are minimal in the literature because of the lack of persuasive evaluative frameworks and the difficulty of designing and facilitating the evaluations at local and national levels. Nevertheless, when combined with data about outputs and outcomes, the impact on individuals and their communities can be measured effectively and reported persuasively (Poll 2012, p.124). This contextual review provides an overview of current thinking about public libraries and creative spaces with particular attention paid to the rise of so-called makerspaces and Fab Labs. This includes discussion on the types of creative activities that are occurring in the public library context, and an outline of the rhetoric and reality of the public library as a community space. These outlines are reconsidered in a discussion of the evaluative frameworks that have been employed by libraries in the past, followed by an account of some prominent creative spaces that have been formally evaluated. The existence of creative spaces in public libraries is in a state of constant flux, and the development and redevelopment of evaluative frameworks will ensure that published reports will continue to appear throughout 2015 and beyond. This review provides a brief snapshot of the state of the field as it is in the first quarter of 2015.