Optimisation of open pit mine block sequencing

This study presents a comprehensive mathematical model for open pit mine block sequencing problem which considers technical aspects of real-life mine operations. As the open pit block sequencing problem is an NP-hard, state-of-the-art heuristics algorithms, including constructive heuristic, local search, simulated annealing, and tabu search are developed and coded using MATLAB programming language. Computational experiments show that the proposed algorithms are satisfactory to solve industrial-scale instances. Numerical investigation and sensitivity analysis based on real-world data are also conducted to provide insightful and quantitative recommendations for mine schedulers and planners.

Mathematical models for collective cell spreading

Collective cell spreading is frequently observed in development, tissue repair and disease progression. Mathematical modelling used in conjunction with experimental investigation can provide key insights into the mechanisms driving the spread of cell populations. In this study, we investigated how experimental and modelling frameworks can be used to identify several key features underlying collective cell spreading. In particular, we were able to independently quantify the roles of cell motility and cell proliferation in a spreading cell population, and investigate how these roles are influenced by factors such as the initial cell density, type of cell population and the assay geometry.

Interaction design for tablet based edutainment systems for mathematical education of primary student

Mathematics has been perceived as the core area of learning in most educational systems around the world including Sri Lanka. Unfortunately, it is clearly visible that a majority of Sri Lankan students are failing in their basic mathematics when the recent grade five scholarship examination and ordinary level exam marks are analysed. According to Department of Examinations Sri Lanka , on average, over 88 percent of the students are failing in the grade 5 scholarship examinations where mathematics plays a huge role while about 50 percent of the students fail in there ordinary level mathematics examination. Poor or lack of basic mathematics skills has been identified as the root cause.

Early mathematical learning: Number processing skills and executive function at 5 and 8 years of age

This research investigated differences and associations in performance in number processing and executive function for children attending primary school in a large Australian metropolitan city. In a cross-sectional study, performance of 25 children in the first full-time year of school, (Prep; mean age = 5.5 years) and 21 children in Year 3 (mean age = 8.5 years) completed three number processing tasks and three executive function tasks. Year 3 children consistently outperformed the Prep year children on measures of accuracy and reaction time, on the tasks of number comparison, calculation, shifting, and inhibition but not on number line estimation. The components of executive function (shifting, inhibition, and working memory) showed different patterns of correlation to performance on number processing tasks across the early years of school. Findings could be used to enhance teachers’ understanding about the role of the cognitive processes employed by children in numeracy learning, and so inform teachers’ classroom practices.

Overcoming language barriers in healthcare: A protocol for investigating safe and effective communication when patients or clinicians use a second language

Background Miscommunication in the healthcare sector can be life-threatening. The rising number of migrant patients and foreign-trained staff means that communication errors between a healthcare practitioner and patient when one or both are speaking a second language are increasingly likely. However, there is limited research that addresses this issue systematically. This protocol outlines a hospital-based study examining interactions between healthcare practitioners and their patients who either share or do not share a first language. Of particular interest are the nature and efficacy of communication in language-discordant conversations, and the degree to which risk is communicated. Our aim is to understand language barriers and miscommunication that may occur in healthcare settings between patients and healthcare practitioners, especially where at least one of the speakers is using a second (weaker) language. Methods/Design Eighty individual interactions between patients and practitioners who speak either English or Chinese (Mandarin or Cantonese) as their first language will be video recorded in a range of in- and out-patient departments at three hospitals in the Metro South area of Brisbane, Australia. All participants will complete a language background questionnaire. Patients will also complete a short survey rating the effectiveness of the interaction. Recordings will be transcribed and submitted to both quantitative and qualitative analyses to determine elements of the language used that might be particularly problematic and the extent to which language concordance and discordance impacts on the quality of the patient-practitioner consultation. Discussion Understanding the role that language plays in creating barriers to healthcare is critical for healthcare systems that are experiencing an increasing range of culturally and linguistically diverse populations both amongst patients and practitioners. The data resulting from this study will inform policy and practical solutions for communication training, provide an agenda for future research, and extend theory in health communication.

Orientations to Critical Literacy for English as an Additional Language or Dialect (EAL/D) learners: A case study of four teachers of senior English

Recently, the debate around critical literacy has dissipated as literacy education agendas and attendant policies shift to embrace more hybrid approaches to the teaching of senior English. This paper reports on orientations towards critical literacy as expressed by four teachers of senior English who teach culturally and linguistically diverse learners. Teachers’ understandings of critical literacy are important given the emphasis on Critical and Creative Thinking as well as Literacy as General Capabilities underpinning the Australian Curriculum. Using critical discourse analysis and Janks' (2010) Synthesis Model of Critical Literacy, interview and classroom data from four teachers of English as an Additional Language or Dialect (EAL/D) learners in two high schools were analysed for the ways these teachers constructed critical literacy in their talk and practice. While all four teachers indicated significant commitment to critical literacy as an approach to English language teaching, their understandings varied. These ranged from providing access to powerful genres, to rationalist approaches to interrogating text, with less emphasis on multimodal design and drawing on learner diversity. This has significant implications for what kind of learning is being offered to EAL/D learners in the name of English teaching, for syllabus design, and for teacher professional development.

Negotiating Chineseness through learning Chinese as a Heritage Language in Australia: The role of habitus

While education researchers have drawn on the work of a wide diversity of theorists over the years, much contemporary theory building in these areas has revolved around the work of Pierre Bourdieu. Theory as Method in Research develops the capacity of students, researchers and teachers to successfully put Bourdieu’s ideas to work in their own research and prepare them effectively for conducting Masters and Doctoral scholarships. Structured around four core themes, this book provides a range of research case studies exploring educational identities, educational inequalities, school leadership and management, and research in teacher education. Issues as diverse as Chinese language learning and identity, school leadership in Australia and the school experience of Afro-Trinidadian boys, are covered, intertwined with a set of innovative approaches to theory application in education research. This collection brings together, in one comprehensive volume, a set of education researchers who place Pierre Bourdieu’s key concepts such as habitus, capital and field at the centre of their research methodologies. Full of insight and innovation, the book is an essential read for practitioners, student teachers, researchers and academics who want to harness the potential of Bourdieu’s core concepts in their own work, thereby helping to bridge the gap between theory and method in education research.

Learning Chinese as a Heritage Language: An Australian Perspective

Summary: This book explores the fascinating topic of heritage language learning, looking in particular at Chinese Australians' learning of Chinese. The author studies the investment, challenges and benefits of heritage language learning across varied contexts including school, work, home and in the community. The book investigates how Chinese Australians navigate and negotiate their Chineseness and how resources are used to support their learning. The book is based on a mixed methods study which uses Bourdieu's sociological theory, and offers implications for sociologists of language and education, Chinese heritage language learners and teachers, as well as language and cultural policy makers. Review: This book is a compelling account of the habitus of Chineseness in a world of mobility. It offers up a plethora of insights into the implication of heritage language learning in the constitution of Chinese identity; it makes available a sophisticated mixed methods approach for using the thinking tools of Pierre Bourdieu; it adds to these tools a nuanced cultural dimension. Karen Dooley, Queensland University of Technology, Australia In our increasingly trans-migratory world, language can be central to cultural identity. Dr Mu’s research breaks new ground by adapting Bourdieu’s insights to examine how cultural identity (‘Chinese-ness’) is linguistically learned and practiced in Australia. His remarkable book will interest educators and researchers grappling with how language pertains to identity. Tom Strong, University of Calgary, Canada A thought-provoking, highly engaging work that has deftly shown how Bourdieusian framework can be applied in the research field of literacy education and Heritage Language learning. A must-read for those interested in overseas Chinese communities and Heritage Language learning across various immigrant communities in general! Liang Du, Beijing Normal University, China

Introduction to "Learning Chinese as a Heritage Language : An Australia Perspective"

The book grapples with the complex entanglement of identity construction, language choice, cultural heritage, and social orders. Specifically, the book investigates how Chinese Australians negotiate their Chineseness and capitalise on resources through learning Chinese as a heritage language in Australia and beyond. Though the book is concerned with Chinese Australians, knowledge built and lessons learned can provide insight into other multicultural settings where people of Chinese descent are becoming increasingly prominent in representing the cultural and linguistic diversity of the society, and more recently, in contributing to the economic dynamics of the society. In addition, the focus on the potholes and distractions as well as the benefits and gains of heritage language learning is not restricted to Chinese diaspora, but relevant to ethnic minority individuals and communities elsewhere.

On the mathematical modeling of wound healing angiogenesis in skin as a reaction-transport process

Over the last 30 years, numerous research groups have attempted to provide mathematical descriptions of the skin wound healing process. The development of theoretical models of the interlinked processes that underlie the healing mechanism has yielded considerable insight into aspects of this critical phenomenon that remain difficult to investigate empirically. In particular, the mathematical modeling of angiogenesis, i.e., capillary sprout growth, has offered new paradigms for the understanding of this highly complex and crucial step in the healing pathway. With the recent advances in imaging and cell tracking, the time is now ripe for an appraisal of the utility and importance of mathematical modeling in wound healing angiogenesis research. The purpose of this review is to pedagogically elucidate the conceptual principles that have underpinned the development of mathematical descriptions of wound healing angiogenesis, specifically those that have utilized a continuum reaction-transport framework, and highlight the contribution that such models have made toward the advancement of research in this field. We aim to draw attention to the common assumptions made when developing models of this nature, thereby bringing into focus the advantages and limitations of this approach. A deeper integration of mathematical modeling techniques into the practice of wound healing angiogenesis research promises new perspectives for advancing our knowledge in this area. To this end we detail several open problems related to the understanding of wound healing angiogenesis, and outline how these issues could be addressed through closer cross-disciplinary collaboration.

Using collaboration and technology to enhance Vietnamese students' English language writing skills

This action research study investigated face-to-face and wiki technology collaboration to enhance students' English writing skills in a second language (L2) class in Vietnam. The thesis is underpinned by socio-cultural theory and argues that collaborative learning using wikis led to an enhancement in L2 writing skills. The findings show that collaborating via wikis challenged traditional L2 writing pedagogy in the following ways: increased student autonomy; understanding formative feedback; and awareness of process writing, genre and audiences. This study contributes practical knowledge about affordances and constraints of collaborative writing using wikis in Vietnam and other countries where traditional pedagogies are prevalent.

Mathematical modeling for improved greenhouse gas balances, agro-ecosystems, and policy development: Lessons from the Australian experience

If the land sector is to make significant contributions to mitigating anthropogenic greenhouse gas (GHG) emissions in coming decades, it must do so while concurrently expanding production of food and fiber. In our view, mathematical modeling will be required to provide scientific guidance to meet this challenge. In order to be useful in GHG mitigation policy measures, models must simultaneously meet scientific, software engineering, and human capacity requirements. They can be used to understand GHG fluxes, to evaluate proposed GHG mitigation actions, and to predict and monitor the effects of specific actions; the latter applications require a change in mindset that has parallels with the shift from research modeling to decision support. We compare and contrast 6 agro-ecosystem models (FullCAM, DayCent, DNDC, APSIM, WNMM, and AgMod), chosen because they are used in Australian agriculture and forestry. Underlying structural similarities in the representations of carbon flows though plants and soils in these models are complemented by a diverse range of emphases and approaches to the subprocesses within the agro-ecosystem. None of these agro-ecosystem models handles all land sector GHG fluxes, and considerable model-based uncertainty exists for soil C fluxes and enteric methane emissions. The models also show diverse approaches to the initialisation of model simulations, software implementation, distribution, licensing, and software quality assurance; each of these will differentially affect their usefulness for policy-driven GHG mitigation prediction and monitoring. Specific requirements imposed on the use of models by Australian mitigation policy settings are discussed, and areas for further scientific development of agro-ecosystem models for use in GHG mitigation policy are proposed.

FlexAnalytics: A flexible data analytics framework for big data applications with I/O performance improvement

Increasingly larger scale applications are generating an unprecedented amount of data. However, the increasing gap between computation and I/O capacity on High End Computing machines makes a severe bottleneck for data analysis. Instead of moving data from its source to the output storage, in-situ analytics processes output data while simulations are running. However, in-situ data analysis incurs much more computing resource contentions with simulations. Such contentions severely damage the performance of simulation on HPE. Since different data processing strategies have different impact on performance and cost, there is a consequent need for flexibility in the location of data analytics. In this paper, we explore and analyze several potential data-analytics placement strategies along the I/O path. To find out the best strategy to reduce data movement in given situation, we propose a flexible data analytics (FlexAnalytics) framework in this paper. Based on this framework, a FlexAnalytics prototype system is developed for analytics placement. FlexAnalytics system enhances the scalability and flexibility of current I/O stack on HEC platforms and is useful for data pre-processing, runtime data analysis and visualization, as well as for large-scale data transfer. Two use cases – scientific data compression and remote visualization – have been applied in the study to verify the performance of FlexAnalytics. Experimental results demonstrate that FlexAnalytics framework increases data transition bandwidth and improves the application end-to-end transfer performance.

5-year Chlamydia vaccination programme could reverse disease-related koala population decline: Predictions from a mathematical model using field data

BACKGROUND Many koala populations around Australia are in serious decline, with a substantial component of this decline in some Southeast Queensland populations attributed to the impact of Chlamydia. A Chlamydia vaccine for koalas is in development and has shown promise in early trials. This study contributes to implementation preparedness by simulating vaccination strategies designed to reverse population decline and by identifying which age and sex category it would be most effective to target. METHODS We used field data to inform the development and parameterisation of an individual-based stochastic simulation model of a koala population endemic with Chlamydia. The model took into account transmission, morbidity and mortality caused by Chlamydia infections. We calibrated the model to characteristics of typical Southeast Queensland koala populations. As there is uncertainty about the effectiveness of the vaccine in real-world settings, a variety of potential vaccine efficacies, half-lives and dosing schedules were simulated. RESULTS Assuming other threats remain constant, it is expected that current population declines could be reversed in around 5-6 years if female koalas aged 1-2 years are targeted, average vaccine protective efficacy is 75%, and vaccine coverage is around 10% per year. At lower vaccine efficacies the immunological effects of boosting become important: at 45% vaccine efficacy population decline is predicted to reverse in 6 years under optimistic boosting assumptions but in 9 years under pessimistic boosting assumptions. Terminating a successful vaccination programme at 5 years would lead to a rise in Chlamydia prevalence towards pre-vaccination levels. CONCLUSION For a range of vaccine efficacy levels it is projected that population decline due to endemic Chlamydia can be reversed under realistic dosing schedules, potentially in just 5 years. However, a vaccination programme might need to continue indefinitely in order to maintain Chlamydia prevalence at a sufficiently low level for population growth to continue.

Structure matters: Adoption of structured classification Approach in the context of cognitive presence classification

Within online learning communities, receiving timely and meaningful insights into the quality of learning activities is an important part of an effective educational experience. Commonly adopted methods – such as the Community of Inquiry framework – rely on manual coding of online discussion transcripts, which is a costly and time consuming process. There are several efforts underway to enable the automated classification of online discussion messages using supervised machine learning, which would enable the real-time analysis of interactions occurring within online learning communities. This paper investigates the importance of incorporating features that utilise the structure of on-line discussions for the classification of "cognitive presence" – the central dimension of the Community of Inquiry framework focusing on the quality of students' critical thinking within online learning communities. We implemented a Conditional Random Field classification solution, which incorporates structural features that may be useful in increasing classification performance over other implementations. Our approach leads to an improvement in classification accuracy of 5.8% over current existing techniques when tested on the same dataset, with a precision and recall of 0.630 and 0.504 respectively.