Maternal employment, work experiences, and financial well-being of Australian mothers who care for young children with special health care needs

The employment and work experiences of mothers who care for young children with special health care needs is the focus of this study. It addresses a gap in the research literature, by providing an understanding of how mothers’ caring role may affect employment conditions, family life, and financial well-being. Quantitative data are drawn from Growing Up in Australia: The Longitudinal Study of Australian Children. The current study employs a matched case–control methodology to compare the experiences of a group of 292 mothers whose children (aged 4-5 years) with long-term special health care needs with those mothers whose children were typically developing. There were few differences between the two groups with regard to job characteristics and job quality. There were significant differences between the two groups with regard to work–family balance. Fewer mothers with children with special health care needs reported work having a positive effect on family functioning.

The educational context and services of children with additional needs in their first years of school in Australia

In Australia, children with additional needs are now primarily educated in mainstream regular classes and schools. While discussion has focused on teacher attitudes, teacher preparation and professional development to support the academic progress of children with additional needs, there is limited research examining the educational contexts and services provided to such children in Australian schools. This descriptive paper examines the educational contexts of 563 Australian children with additional needs, in reference to 3600 of their typically developing peers. Data in relation to educational setting, retention, prevalence of additional needs, access to specialist services, learning support, and individual programming are reported.

A model for reflection in the pedagogic field of higher education

This chapter provides an introduction to the use of pedagogical patterns in capturing and sharing educational design experience. In higher education, helping students to learn to engage in productive reflection presents a complex set of challenges. Delicate balances must be found: too little structure and support for students’ reflective work can leave them floundering; too much, and some will remain dependent. Moreover, this is a dynamic teaching problem – scaffolding needs to be adjusted as students develop confidence and capability, which they will do at different rates. The model presented in this chapter embraces the three main elements that teachers can legitimately design, or help set in place, to support their students’ reflective activity: good tasks, the right tools, and appropriate divisions of labour. It delineates a complex, shifting architecture of tasks, tools and people, activities and outcomes associated with reflective learning. It shows how the designable elements of this complex mix can be described in patterns and pattern languages, which then become design resources for teachers’ own action, reflection and professional development.

Memory and Epileptogenesis in Complex Biological and Simulated Systems

Oscillations of neural activity may bind widespread cortical areas into a neural representation that encodes disparate aspects of an event. In order to test this theory we have turned to data collected from complex partial epilepsy (CPE) patients with chronically implanted depth electrodes. Data from regions critical to word and face information processing was analyzed using spectral coherence measurements. Similar analyses of intracranial EEG (iEEG) during seizure episodes display HippoCampal Formation (HCF)—NeoCortical (NC) spectral coherence patterns that are characteristic of specific seizure stages (Klopp et al. 1996). We are now building a computational memory model to examine whether spatio-temporal patterns of human iEEG spectral coherence emerge in a computer simulation of HCF cellular distribution, membrane physiology and synaptic connectivity. Once the model is reasonably scaled it will be used as a tool to explore neural parameters that are critical to memory formation and epileptogenesis.

Variation in parental magmas of Mt Rouse, a complex polymagmatic monogenetic volcano in the basaltic intraplate Newer Volcanics Province, southeast Australia

Monogenetic volcanoes have long been regarded as simple in nature, involving single magma batches and uncomplicated evolutions; however, recent detailed research into individual centres is challenging that assumption. Mt Rouse (Kolor) is the volumetrically largest volcano in the monogenetic Newer Volcanics Province of southeast Australia. This study presents new major, trace and Sr–Nd–Pb isotope data for samples selected on the basis of a detailed stratigraphic framework analysis of the volcanic products from Mt Rouse. The volcano is the product of three magma batches geochemically similar to Ocean–Island basalts, featuring increasing LREE enrichment with each magma batch (batches A, B and C) but no evidence of crustal contamination; the Sr–Nd–Pb isotopes define two groupings. Modelling suggests that the magmas were sourced from a zone of partial melting crossing the lithosphere–asthenosphere boundary, with batch A forming a large volume partial melt in the deep lithosphere (1.7 GPa/55.5 km); and batches B and C from similar areas within the shallow asthenosphere (1.88 GPa/61 km and 1.94 GPa/63 km, respectively). The formation and extraction of these magmas may have been due to high deformation rates in the mantle caused by edge-driven convection and asthenospheric upwelling. The lithosphere– asthenosphere boundary is important with respect to NVP volcanism. An eruption chronology involves sequential eruption of magma batches A, C and B, followed by simultaneous eruption of batches A and B. Mt Rouse is a complex polymagmatic monogenetic volcano that illustrates the complexity of monogenetic volcanism and demonstrates the importance of combining detailed stratigraphic analysis alongside systematic geochemical sampling.

Further development of discrete computational techniques for calculation of restricted diffusion propagators in porous media

Magnetic resonance is a well-established tool for structural characterisation of porous media. Features of pore-space morphology can be inferred from NMR diffusion-diffraction plots or the time-dependence of the apparent diffusion coefficient. Diffusion NMR signal attenuation can be computed from the restricted diffusion propagator, which describes the distribution of diffusing particles for a given starting position and diffusion time. We present two techniques for efficient evaluation of restricted diffusion propagators for use in NMR porous-media characterisation. The first is the Lattice Path Count (LPC). Its physical essence is that the restricted diffusion propagator connecting points A and B in time t is proportional to the number of distinct length-t paths from A to B. By using a discrete lattice, the number of such paths can be counted exactly. The second technique is the Markov transition matrix (MTM). The matrix represents the probabilities of jumps between every pair of lattice nodes within a single timestep. The propagator for an arbitrary diffusion time can be calculated as the appropriate matrix power. For periodic geometries, the transition matrix needs to be defined only for a single unit cell. This makes MTM ideally suited for periodic systems. Both LPC and MTM are closely related to existing computational techniques: LPC, to combinatorial techniques; and MTM, to the Fokker-Planck master equation. The relationship between LPC, MTM and other computational techniques is briefly discussed in the paper. Both LPC and MTM perform favourably compared to Monte Carlo sampling, yielding highly accurate and almost noiseless restricted diffusion propagators. Initial tests indicate that their computational performance is comparable to that of finite element methods. Both LPC and MTM can be applied to complicated pore-space geometries with no analytic solution. We discuss the new methods in the context of diffusion propagator calculation in porous materials and model biological tissues.

Recreational needs and service performance expectations

The theoretical contribution of this study lies with its focus on subjective experiencing, that is, the emotional convergence between feeling states, and perceptions of servicescapes and holiday activities. An empirical study models the impact of recreational needs on the perceived importance of destination attributes and intentions to participate in activities. A sample of prospective tourists was asked to indicate how important they considered servicescape elements to be in their general holiday planning. They were also asked to report on their emotional state (orientation) as a proxy for their needs for recreation, and to state their intention and likely involvement with holiday activities. Results suggest that those with high recreational needs (self-reflexive and inward-looking) regard elements of tourism servicescapes as significantly more important than those without (who are outward-looking and energetic), as well as show significant variations in their inclinations to be active and explorative at destinations. Rather, those with higher recreational needs as measured by combinations of lack of energy, self-confidence, and physiological well-being look for creature comfort, coziness, and familiarity, in other words, for things they already know and have experienced before. Subjective experiencing and service performance evaluations are thereby suggested to be influenced by emotional states. These states may also impact tourists' recognition of destination uniqueness as a major component of a destination's competitive advantage that cannot easily be copied. As a consequence, it may be worth reconsidering the role of recreation in tourism service design. Turning an inwardlooking focus bent on recreation to an outward-looking one interested in discovery would enable more tourists to more fully experience the destination before they leave.

The challenges of meeting the needs of children with Autism Spectrum Disorders (ASD) during out of hospital interactoins with Paramedics

This poster presents the results of a critical review of the literature on the intersection between paramedic practice with Autism Spectrum Disorder (ASD) and previews the clinical and communication challenges likely to be experienced with these patients. Paramedics in Australia provide 24/7 out-of-hospital care to the community. Although their core business is to provide emergency care, paramedics also provide care for vulnerable people as a consequence of the social, economic or domestic milieu. Little is known about the frequency of use of emergency out-of-hospital services by children with ASD and their families. Similarly, little is known about the attitudes and perceptions of paramedics to children with ASD and their emergency health care. However, individuals with ASD are likely to require paramedic services at some point across the life span and may be more frequent users of health services as a consequence of the challenges they face. The high rate of co-morbidities of people diagnosed with ASD is reported and includes seizure disorders, gastro-intestinal disorders, metabolic disorders, hormonal dysfunction, ear, nose and throat infections, hearing impairment, hypertension, allergies/anaphylaxis, immune disorders, migraine and diabetes, gross/fine motor skill dysfunction, premature birth, birth defects, obesity and mental illness. Individuals with ASD may frequently experience concurrent communication, behaviour and sensory challenges. Consequently, Paramedics can encounter difficulties gathering important patient information which may compromise sensitive care. These interactions occur often in high pressure and emotionally challenging environments, which add to the difficulties in communicating the treatment and transport needs of this population.

Bayesian networks for information synthesis in complex systems

This thesis introduces a method of applying Bayesian Networks to combine information from a range of data sources for effective decision support systems. It develops a set of techniques in development, validation, visualisation, and application of Complex Systems models, with a working demonstration in an Australian airport environment. The methods presented here have provided a modelling approach that produces highly flexible, informative and applicable interpretations of a system's behaviour under uncertain conditions. These end-to-end techniques are applied to the development of model based dashboards to support operators and decision makers in the multi-stakeholder airport environment. They provide highly flexible and informative interpretations and confidence in these interpretations of a system's behaviour under uncertain conditions.

Diagnose this if you can: On the effectiveness of search engines in finding medical self-diagnosis information

An increasing amount of people seek health advice on the web using search engines; this poses challenging problems for current search technologies. In this paper we report an initial study of the effectiveness of current search engines in retrieving relevant information for diagnostic medical circumlocutory queries, i.e., queries that are issued by people seeking information about their health condition using a description of the symptoms they observes (e.g. hives all over body) rather than the medical term (e.g. urticaria). This type of queries frequently happens when people are unfamiliar with a domain or language and they are common among health information seekers attempting to self-diagnose or self-treat themselves. Our analysis reveals that current search engines are not equipped to effectively satisfy such information needs; this can have potential harmful outcomes on people’s health. Our results advocate for more research in developing information retrieval methods to support such complex information needs.

Visualization of complex biological systems: An immune response model using OpenGL

In this paper we present an update on our novel visualization technologies based on cellular immune interaction from both large-scale spatial and temporal perspectives. We do so with a primary motive: to present a visually and behaviourally realistic environment to the community of experimental biologists and physicians such that their knowledge and expertise may be more readily integrated into the model creation and calibration process. Visualization aids understanding as we rely on visual perception to make crucial decisions. For example, with our initial model, we can visualize the dynamics of an idealized lymphatic compartment, with antigen presenting cells (APC) and cytotoxic T lymphocyte (CTL) cells. The visualization technology presented here offers the researcher the ability to start, pause, zoom-in, zoom-out and navigate in 3-dimensions through an idealised lymphatic compartment.

Incorporating complex train paths to an analysis of absolute capacity

Railways are an important mode of transportation. They are however large and complex and their construction, management and operation is time consuming and costly. Evidently planning the current and future activities is vital. Part of that planning process is an analysis of capacity. To determine what volume of traffic can be achieved over time, a variety of railway capacity analysis techniques have been created. A generic analytical approach that incorporates more complex train paths however has yet to be provided. This article provides such an approach. This article extends a mathematical model for determining the theoretical capacity of a railway network. The main contribution of this paper is the modelling of more complex train paths whereby each section can be visited many times in the course of a train’s journey. Three variant models are formulated and then demonstrated in a case study. This article’s numerical investigations have successively shown the applicability of the proposed models and how they may be used to gain insights into system performance.

Projecting future air pollution-related mortality under a changing climate: Progress, uncertainties and research needs

Background Climate change may affect mortality associated with air pollutants, especially for fine particulate matter (PM2.5) and ozone (O3). Projection studies of such kind involve complicated modelling approaches with uncertainties. Objectives We conducted a systematic review of researches and methods for projecting future PM2.5-/O3-related mortality to identify the uncertainties and optimal approaches for handling uncertainty. Methods A literature search was conducted in October 2013, using the electronic databases: PubMed, Scopus, ScienceDirect, ProQuest, and Web of Science. The search was limited to peer-reviewed journal articles published in English from January 1980 to September 2013. Discussion Fifteen studies fulfilled the inclusion criteria. Most studies reported that an increase of climate change-induced PM2.5 and O3 may result in an increase in mortality. However, little research has been conducted in developing countries with high emissions and dense populations. Additionally, health effects induced by PM2.5 may dominate compared to those caused by O3, but projection studies of PM2.5-related mortality are fewer than those of O3-related mortality. There is a considerable variation in approaches of scenario-based projection researches, which makes it difficult to compare results. Multiple scenarios, models and downscaling methods have been used to reduce uncertainties. However, few studies have discussed what the main source of uncertainties is and which uncertainty could be most effectively reduced. Conclusions Projecting air pollution-related mortality requires a systematic consideration of assumptions and uncertainties, which will significantly aid policymakers in efforts to manage potential impacts of PM2.5 and O3 on mortality in the context of climate change.