Accelerating the Mathematics Learning of Low Socio-Economic Status Junior Secondary Students : an early report

The Accelerating the Mathematics Learning of Low Socio-Economic Status Junior Secondary Students project aims to address the issues faced by very underperforming mathematics students as they enter high school. Its aim is to accelerate learning of mathematics through a vertical curriculum to enable students to access Year 10 mathematics subjects, thus improving life chances. This paper reports upon the theory underpinning this project and illustrates it with examples of the curriculum that has been designed to achieve acceleration.

Evaluating the use of online synchronous communication to enhance learning in statistics

According to social constructivists, learners are active participants in constructing new knowledge in a social process where they interact with others. In these social settings teachers or more knowledgeable peers provide support. This research study investigated the contribution that an online synchronous tutorial makes to support teaching and learning of undergraduate introductory statistics offered by an Australian regional university at a distance. The introductory statistics course which served as a research setting in this study was a requirement of a variety of programs at the University, including psychology, business and science. Often students in these programs perceive this course to be difficult and irrelevant to their programs of study. Negative attitudes and associated anxiety mean that students often struggle with the content. While asynchronous discussion forums have been shown to provide a level of interaction and support, it was anticipated that online synchronous tutorials would offer immediate feedback to move students forward through ―stuck places.‖ At the beginning of the semester the researcher offered distance students in this course the opportunity to participate in a weekly online synchronous tutorial which was an addition to the usual support offered by the teaching team. This tutorial was restricted to 12 volunteers to allow sufficient interaction to occur for each of the participants. The researcher, as participant-observer, conducted the weekly tutorials using the University's interactive online learning platform, Wimba Classroom, whereby participants interacted using audio, text chat and a virtual whiteboard. Prior to the start of semester, participants were surveyed about their previous mathematical experiences, their perceptions of the introductory statistics course and why they wanted to participate in the online tutorial. During the semester, they were regularly asked pertinent research questions related to their personal outcomes from the tutorial sessions. These sessions were recorded using screen capture software and the participants were interviewed about their experiences at the end of the semester. Analysis of these data indicated that the perceived value of online synchronous tutorial lies in the interaction with fellow students and a content expert and with the immediacy of feedback given. The collaborative learning environment offered the support required to maintain motivation, enhance confidence and develop problemsolving skills in these distance students of introductory statistics. Based on these findings a model of online synchronous learning is proposed.

Exenatide extended-release; clinical trials, patient preference, and economic considerations

Type 2 diabetes remains an escalating world-wide problem, despite a range of treatments. The revelation that insulin secretion is under the control of a gut hormone, glucagon-like peptide 1 (GLP-1) led to a new paradigm in the management of type 2 diabetes, medicines that directly stimulate, or that prolong the actions of the endogenous GLP-1, at its receptors. Exenatide is an agonist at the GLP-1 receptors, and was initially developed as a subcutaneous twice daily medication, ExBID. The clinical trials with ExBID established a role for exenatide in the treatment of type 2 diabetes. Subsequently, once weekly exenatide (ExQW) was shown to have advantages over ExBID, and there is now more emphasis on the development of ExQW. ExQW alone reduces glycosylated haemoglobin (HbA1c) and body weight, and is well tolerated. ExQW has been compared to sitagliptin, pioglitazone and metformin, and shown to have a greater ability to reduce HbA1c than these other medicines. The only preparation of insulin, which ExQW has been compared to, is insulin glargine, and the ExQW has some favourable properties in this comparison, notably causing weight loss, compared to the gain with insulin glargine. ExQW has been compared to another GLP-1 receptor agonist, liraglutide, and ExQW is non-inferior to liraglutide in reducing HbA1c. The small amount of evidence available, shows that subjects with type 2 diabetes, prefer ExQW to ExBID, and that adherence was high to these in the clinical trial setting. Healthcare and economic modelling suggests that ExQW will reduce diabetic complications and be cost-effective, compared to other medications, with long term use. Little is known about whether subjects with type 2 diabetes prefer ExQW to other medicines, and whether adherence is good to ExQW in practice, and these important topics require further study.

Measuring global economic interdependence : a hierarchical network approach

This paper investigates the business cycle co-movement across countries and regions since 1950 as a measure for quantifying the economic interdependence in the ongoing globalisation process. Our methodological approach is based on analysis of a correlation matrix and the networks it contains. Such an approach summarises the interaction and interdependence of all elements, and it represents a more accurate measure of the global interdependence involved in an economic system. Our results show (1) the dynamics of interdependence has been driven more by synchronisation in regional growth patterns than by the synchronisation of the world economy, and (2) world crisis periods dramatically increase the global co-movement in the world economy.

A Century of American Economic Review : Insights on Critical Factors in Journal Publishing

By using information collected from numerous American Economic Review publications from the last 100 years, Torgler and Piatti examine the top publishing institutions to determine their most renowned AER papers based on citation success. Areas of interest include how often an individual can publish in the AER, how equally successful citations are distributed and who the top AER publishing authors are. The book explores what the level of cooperation is among authors and what drives systems such as the alphabetical name ordering. Torgler and Piatti critically examine the individual characteristics of AER authors, editors, editorial board members and referees and even tackle more intricate details such as the frequency of female publications in the AER. The authors observe and analyse the relationship between academic age and publication performance to see if there is any pattern on these factors and citation success. The book then goes on to analyse data concerning awards, and whether awards can increase the probability of publishing in the AER at a later stage

The local library across the digital and physical city : opportunities for economic development

This paper considers the role of the public library as a community hub, engagement space, and entrepreneurial incubator in the context of the city, city governance, and local government planning. It considers this role from the perspective of library experts and their future visions for libraries in a networked knowledge economy. Public libraries (often operated by or on behalf of local governments) potentially play a pivotal role for local governments in positioning communities within the global digital network. Fourteen qualitative interviews with library experts informed the study which investigates how the relationship between digital technology and the physical library space can potentially support the community to develop innovative, collaborative environments for transitioning to a digital future. The study found that libraries can capitalise on their position as community hubs for two purposes: first, to build vibrant community networks and forge economic links across urban localities; and second, to cross the digital divide and act as places of innovation and lifelong learning. Libraries provide a specific combination of community and technology spaces and have significant tangible connection points in the digital age. The paper further discusses the potential benefits for libraries in using ICT networks and infrastructure, such as the National Broadband Network in Australia. These networks could facilitate greater use of library assets and community knowledge, which, in turn, could assist knowledge economies and regional prosperity.

Examining the impact of climate change on dengue transmission in the Asia-Pacific region

Dengue fever (DF) is a serious public health concern in many parts of the world. An increase in DF incidence has been observed globally over the past decades. Multiple factors including urbanisation, increased international travels and global climate change are thought to be responsible for increased DF. However, little research has been conducted in the Asia-Pacific region about the impact of these changes on dengue transmission. The overarching aim of this thesis is to explore the spatiotemporal pattern of DF transmission in the Asia-Pacific region and project the future risk of DF attributable to climate change. Annual data of DF outbreaks for sixteen countries in the Asia-Pacific region over the last fifty years were used in this study. The results show that the geographic range of DF in this region increased significantly over the study period. Thailand, Vietnam and Laos were identified as the highest risk areas and there was a southward expansion observed in the transmission pattern of DF which might have originated from Philippines or Thailand. Additionally, the detailed DF data were obtained and the space-time clustering of DF transmission was examined in Bangladesh. Monthly DF data were used for the entire country at the district level during 2000-2009. Dhaka district was identified as the most likely DF cluster in Bangladesh and several districts of the southern part of Bangladesh were identified as secondary clusters in the years 2000-2002. In order to examine the association between meteorological factors and DF transmission and to project the future risk of DF using different climate change scenarios, the climate-DF relationship was examined in Dhaka, Bangladesh. The results show that climate variability (particularly maximum temperature and relative humidity) was positively associated with DF transmission in Dhaka. The effects of climate variability were observed at a lag of four months which might help to potentially control and prevent DF outbreaks through effective vector management and community education. Based on the quantitative assessment of the climate-DF relationship, projected climate change will likely increase mosquito abundance and activity and DF in this area. Assuming a temperature increase of 3.3oC without any adaptation measures and significant changes in socio-economic conditions, the consequence will be devastating, with a projected annual increase of 16,030 cases in Dhaka, Bangladesh by the end of this century. Therefore, public health authorities need to be prepared for likely increase of DF transmission in this region. This study adds to the literature on the recent trends of DF and impacts of climate change on DF transmission. These findings may have significant public health implications for the control and prevention of DF, particularly in the Asia- Pacific region.

Bayesian networks in environmental and resource management

This overview article for the special series “Bayesian Networks in Environmental and Resource Management” reviews 7 case study articles with the aim to compare Bayesian network (BN) applications to different environmental and resource management problems from around the world. The article discusses advances in the last decade in the use of BNs as applied to environmental and resource management. We highlight progress in computational methods, best-practices for model design and model communication. We review several research challenges to the use of BNs in environmental and resource management that we think may find a solution in the near future with further research attention.

Vulnerability held not to be pre-requisite for establishing a duty of care in claims of pure economic Loss

Case note Apache Energy Ltd v Alcoa of Australia Ltd (No 2) [2013] In 2011, headlines were made when Alcoa sued Apache Energy and its partners for $158 million, a loss it claimed was a consequence of Apache Energy failing to adequately inspect and maintain the gas pipelines that supplied the gas used by Alcoa in its business. As the loss was not a consequence of any property damage or injury to Alcoa, the loss is characterised as pure economic loss...

Did socio-ecological factors drive the spatiotemporal patterns of pandemic influenza A (H1N1)?

BACKGROUND Pandemic influenza A (H1N1) has a significant public health impact. This study aimed to examine the effect of socio-ecological factors on the transmission of H1N1 in Brisbane, Australia. METHODOLOGY We obtained data from Queensland Health on numbers of laboratory-confirmed daily H1N1 in Brisbane by statistical local areas (SLA) in 2009. Data on weather and socio-economic index were obtained from the Australian Bureau of Meteorology and the Australian Bureau of Statistics, respectively. A Bayesian spatial conditional autoregressive (CAR) model was used to quantify the relationship between variation of H1N1 and independent factors and to determine its spatiotemporal patterns. RESULTS Our results show that average increase in weekly H1N1 cases were 45.04% (95% credible interval (CrI): 42.63-47.43%) and 23.20% (95% CrI: 16.10-32.67%), for a 1 °C decrease in average weekly maximum temperature at a lag of one week and a 10mm decrease in average weekly rainfall at a lag of one week, respectively. An interactive effect between temperature and rainfall on H1N1 incidence was found (changes: 0.71%; 95% CrI: 0.48-0.98%). The auto-regression term was significantly associated with H1N1 transmission (changes: 2.5%; 95% CrI: 1.39-3.72). No significant association between socio-economic indexes for areas (SEIFA) and H1N1 was observed at SLA level. CONCLUSIONS Our results demonstrate that average weekly temperature at lag of one week and rainfall at lag of one week were substantially associated with H1N1 incidence at a SLA level. The ecological factors seemed to have played an important role in H1N1 transmission cycles in Brisbane, Australia.

The importance of importance : its impact on decision-making in mall retail categories during an economic downturn

The study examines how, during an economic downturn, the perceived importance of the value offering of retail store categories, as identified by a major international mall operator based in Australia, influences the relationship between consumers’ shopping attitudes and likelihood of purchasing in those categories. The findings show variance in the importance pertaining to retail store categories between those that have and those that have not altered their shopping behaviour. Different mediating effects were found in the major, mini-major, leisure, apparel, and mobile phone categories, suggestive of each group having differing levels of self-interest in the value offerings of each category, thus, symptomatic of dissimilar decision-making strategies for each group. Contributions to theory and practice are discussed.

Cycling for transport and recreation : associations with socio-economic position, environmental perceptions, and psychological disposition

OBJECTIVE Interest is growing in promoting utility cycling (i.e., for transport) as a means of incorporating daily physical activity (PA) into people’s lives, but little is known about correlates of utility cycling. Our primary aim was to examine cross-sectional relationships between socio-economic characteristics, neighborhood environment perceptions and psychological disposition with utility cycling (with or without additional recreational cycling). A secondary aim was to compare these relationships with those for recreation-only cycling. METHOD Baseline survey data (2007) from 10,233 participants in HABITAT, a multilevel longitudinal study of PA, sedentary behavior, and health in Brisbane adults aged 40-65 years, were analysed using multinomial regression modelling. RESULTS Greater income, habitual PA, and positive beliefs about PA were associated with utility and recreation-only cycling (p<0.05). Always having vehicle access and not in the labor force were associated with recreation-only cycling (p<0.05). Some or no vehicle access, part-time employment, and perceived environmental factors (little crime, few cul-de-sacs, nearby transport and recreational destinations) were associated with utility cycling (p<0.05). CONCLUSION Our findings suggest differences in associations between socio-economic, neighborhood perceptions and psychological factors and utility and recreation-only cycling in Brisbane residents aged 40-65 years. Tailored approaches appear to be required to promote utility and recreational cycling.

Learning detectors quickly with stationary statistics

Computer vision is increasingly becoming interested in the rapid estimation of object detectors. The canonical strategy of using Hard Negative Mining to train a Support Vector Machine is slow, since the large negative set must be traversed at least once per detector. Recent work has demonstrated that, with an assumption of signal stationarity, Linear Discriminant Analysis is able to learn comparable detectors without ever revisiting the negative set. Even with this insight, the time to learn a detector can still be on the order of minutes. Correlation filters, on the other hand, can produce a detector in under a second. However, this involves the unnatural assumption that the statistics are periodic, and requires the negative set to be re-sampled per detector size. These two methods differ chie y in the structure which they impose on the co- variance matrix of all examples. This paper is a comparative study which develops techniques (i) to assume periodic statistics without needing to revisit the negative set and (ii) to accelerate the estimation of detectors with aperiodic statistics. It is experimentally verified that periodicity is detrimental.

Demand-side response model to avoid spike of electricity price

The aim of this work is to develop a demand-side-response model, which assists electricity consumers exposed to the market price to independently and proactively manage air-conditioning peak electricity demand. The main contribution of this research is to show how consumers can optimize the energy cost caused by the air conditioning load considering to several cases e.g. normal price, spike price, and the probability of a price spike case. This model also investigated how air-conditioning applies a pre-cooling method when there is a substantial risk of a price spike. The results indicate the potential of the scheme to achieve financial benefits for consumers and target the best economic performance for electrical generation distribution and transmission. The model was tested with Queensland electricity market data from the Australian Energy Market Operator and Brisbane temperature data from the Bureau of Statistics regarding hot days from 2011 to 2012.

Cell image classification using histograms, higher order statistics and adaboost

A cell classification algorithm that uses first, second and third order statistics of pixel intensity distributions over pre-defined regions is implemented and evaluated. A cell image is segmented into 6 regions extending from a boundary layer to an inner circle. First, second and third order statistical features are extracted from histograms of pixel intensities in these regions. Third order statistical features used are one-dimensional bispectral invariants. 108 features were considered as candidates for Adaboost based fusion. The best 10 stage fused classifier was selected for each class and a decision tree constructed for the 6-class problem. The classifier is robust, accurate and fast by design.