995 resultados para Wide-range


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In sport and exercise biomechanics, forward dynamics analyses or simulations have frequently been used in attempts to establish optimal techniques for performance of a wide range of motor activities. However, the accuracy and validity of these simulations is largely dependent on the complexity of the mathematical model used to represent the neuromusculoskeletal system. It could be argued that complex mathematical models are superior to simple mathematical models as they enable basic mechanical insights to be made and individual-specific optimal movement solutions to be identified. Contrary to some claims in the literature, however, we suggest that it is currently not possible to identify the complete optimal solution for a given motor activity. For a complete optimization of human motion, dynamical systems theory implies that mathematical models must incorporate a much wider range of organismic, environmental and task constraints. These ideas encapsulate why sports medicine specialists need to adopt more individualized clinical assessment procedures in interpreting why performers' movement patterns may differ.

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This special issue aims to provide up-to-date knowledge and the latest scientific concepts and technological developments in the processing, characterization, testing, mechanics, modeling and applications of a broad range of advanced materials. The many contributors, from Denmark, Germany, UK, Iran, Saudi Arabia, Malaysia, Japan, the People’s Republic of China, Singapore, Taiwan, USA, New Zealand and Australia, present a wide range of topics including: nanomaterials, thin films and coatings, metals and alloys, composite materials, materials processing and characterization, biomaterials and biomechanics, and computational materials science and simulation. The work will therefore be of great interest to a broad spectrum of researchers and technologists.

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This document is a collection of ‘cases’ adapted from interviews with supervisors of higher degree research students from the technology disciplines. The supervisors come from a wide range of sub disciplines and represent many levels of experience. We follow in this document Hammond and Ryland’s (2009)2 suggested ranking of supervision experience:  No completions – No experience or new supervisors, with no doctoral completions as principal supervisor  Experienced – 1 to 5 doctoral completions as principal supervisor  Very experienced – over 6 doctoral completions as principal supervisor The cases focus attention on thinking about supervision as a teaching and learning practice; a dimension of higher degree research supervision that is increasingly being recognized as important. They are offered as prompts for individuals and groups of supervisors in thinking about their supervision as a teaching and learning practice.

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Purpose of review: To critique the recent literature on telephone, correspondence-based, and computerized interventions for alcohol problems, which enhance or substitute for practitioner-delivered treatments. Recent findings: There is an unmet need for screening, assessment and intervention for alcohol problems, in part because of the difficulty in accessing such treatment within the current health care system. Research on the efficacy of correspondence or electronic (for example Internet-based) interventions is beginning to emerge. In the period 2003–2004 we identified nine acceptability or feasibility studies of these approaches and seven efficacy trials covering a wide range of settings. These modes of intervention are acceptable to patients and the public, and with careful planning, can be implemented in a variety of settings. Treatment trials demonstrate the efficacy of these interventions in reducing hazardous drinking by university students, in delaying initiation of heavy drinking in children and adolescents, and, intriguingly, in addressing insomnia among recovering alcoholics. Summary: There is strong support among potential users for alcohol interventions that employ telephone assistance, written correspondence, and the Internet. These new technologies offer the prospect of increasing the reach of interventions for problem drinking and being cost- effective alternatives or supplements to face-to-face health service delivery.

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Objectives: To determine opinions and experiences of health professionals concerning the management of people with comorbid substance misuse and mental health disorders. Method: We conducted a survey of staff from mental health services and alcohol and drug services across Queensland. Survey items on problems and potential solutions had been generated by focus groups. Results: We analysed responses from 112 staff of alcohol and drug services and 380 mental health staff, representing a return of 79% and 42% respectively of the distributed surveys. One or more issues presented a substantial clinical management problem for 98% of respondents. Needs for increased facilities or services for dual disorder clients figured prominently. These included accommodation or respite care, work and rehabilitation programs, and support groups and resource materials for families. Needs for adolescent dual diagnosis services and after-hours alcohol and drug consultations were also reported. Each of these issues raised substantial problems for over 70% of staff. Another set of problems involved coordination of client care across mental health and alcohol and drug services, including disputes over duty of care. Difficulties with intersectoral liaison were more pronounced for alcohol and drug staff than for mental health. A majority of survey respondents identified 13 solutions as practical. These included routine screening for dual diagnosis at intake, and a range of proposals for closer intersectoral communication such as exchanging client information, developing shared treatment plans, conducting joint case conferences and offering consultation facilities. Conclusions: A wide range of problems for the management of comorbid disorders were identified. While solution of some problems will require resource allocation, many may be addressed by closer liaison between existing services.

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There is increasing agreement that understanding complexity is important for project management because of difficulties associated with decision-making and goal attainment which appear to stem from complexity. However the current operational definitions of complex projects, based upon size and budget, have been challenged and questions have been raised about how complexity can be measured in a robust manner that takes account of structural, dynamic and interaction elements. Thematic analysis of data from 25 in-depth interviews of project managers involved with complex projects, together with an exploration of the literature reveals a wide range of factors that may contribute to project complexity. We argue that these factors contributing to project complexity may define in terms of dimensions, or source characteristics, which are in turn subject to a range of severity factors. In addition to investigating definitions and models of complexity from the literature and in the field, this study also explores the problematic issues of ‘measuring’ or assessing complexity. A research agenda is proposed to further the investigation of phenomena reported in this initial study.

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There is a growing interest in and support for education for sustainability in Australian schools. Australian Government schemes such as the Australian Sustainable Schools Initiative (AuSSI), along with strategies such as Educating for a Sustainable Future: A National Environmental Education Statement for Australian Schools(NEES(Australian Government and Curriculum Corporation (2005) and Living Sustainably: The Australian Government’s National Action Plan for Education for Sustainability (Australian Government 2009), recognise the need and offer support for education for sustainability in Australian schools. The number of schools that have engaged with AuSSI indicates that this interest also exists within Australian schools. Despite this, recent research indicates that pre-service teacher education institutions and programs are not doing all they can to prepare teachers for teaching education for sustainability or for working within sustainable schools. The education of school teachers plays a vital role in achieving changes in teaching and learning in schools. Indeed, the professional development of teachers in education for sustainability has been identified as ‘the priority of priorities’. Much has been written about the need to ‘reorient teacher education towards sustainability’. Teacher education is seen as a key strategy that is yet to be effectively utilised to embed education for sustainability in schools. Mainstreaming sustainability in Australian schools will not be achieved without the preparation of teachers for this task. The Mainstreaming Sustainability model piloted in this study seeks to engage a range of stakeholder organisations and key agents of change within a system to all work simultaneously to bring about a change, such as the mainstreaming of sustainability. The model is premised on the understanding that sustainability will be mainstreamed within teacher education if there is engagement with key agents of change across the wider teacher education system and if the key agents of change are ‘deeply’ involved in making the change. The model thus seeks to marry broad engagement across a system with the active participation of stakeholders within that system. Such a systemic approach is a way of bringing together diverse viewpoints to make sense of an issue and harness that shared interpretation to define boundaries, roles and relationships leading to a better defined problem that can be acted upon more effectively. Like action research, the systemic approach is also concerned with modelling change and seeking plausible solutions through collaboration between stakeholders. This is important in ensuring that outcomes are useful to the researchers/stakeholders and the system being researched as it creates partnerships and commitments to the outcomes by stakeholder participants. The study reported on here examines whether the ‘Mainstreaming Sustainability’ model might be effective as a means to mainstream sustainability in pre-service teacher education. This model, developed in an earlier study, was piloted in the Queensland teacher education system in order to examine its effectiveness in creating organisational and systemic change. The pilot project in Queensland achieved a number of outcomes. The project: • provided useful insights into the effectiveness of the Mainstreaming Sustainability model in bringing about change while also building research capacity within the system • developed capacities within the teacher education community: o developing competencies in education for sustainability o establishing more effective interactions between decision-makers and other stakeholders o establishing a community of inquiry • changed teaching and learning approaches used in participating teacher education institutions through: o curriculum and resource development o the adoption of education for sustainability teaching and learning processes o the development of institutional policies • improved networks within the teacher education system through: o identifying key agents of change within the system o developing new, and building on existing, partnerships between schools, teacher education institutions and government agencies • engaged relevant stakeholders such as government agencies and non-government organisations to understand and support the change Our findings indicate that the Mainstreaming Sustainability model is able to facilitate organisational and systemic change – over time – if: • the individuals involved have the conceptual and personal capacities needed to facilitate change, that is, to be a key agent of change • stakeholders are engaged as participants in the process of change, not simply as ‘interested parties’ • there is a good understanding of systemic change and the opportunities for leveraging change within systems. In particular, in seeking to mainstream sustainability in pre-service teacher education in Queensland it has become clear that one needs to build capacity for change within participants such as knowledge of education for sustainability, conceptual skills in systemic thinking, action research and organisational change, and leadership skills. It is also of vital importance that key agents of change – those individuals who are ‘hubs’ within a system and can leverage for change across a wide range of the system – are identified and engaged with as early as possible. Key agents of change can only be correctly identified, however, if the project leaders and known participants have clearly identified the boundary to their system as this enables the system, sub-system and environment of the system to be understood. Through mapping the system a range of key organisations and stakeholders will be identified, including government and nongovernment organisations, teacher education students, teacher education academics, and so on. On this basis, key agents of change within the system and sub-system can be identified and invited to assist in working for change. A final insight is that it is important to have time – and if necessary the funding to ‘buy time’ – in seeking to bring about system-wide change. Seeking to bring about system-wide change is an ambitious project, one that requires a great deal of effort and time. These insights provide some considerations for those seeking to utilise the Mainstreaming Sustainability model to bring about change within and across a pre-service teacher education system.

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This set of papers in this issue of "Addictive Behaviors" was presented at the 2004 'Addictions' conference, which, for the first time, was held in the Southern Hemisphere, on the Sunshine Coast of Queensland, Australia. The theme of the conference, Crossing Boundaries: Implications of Advances in Basic Sciences for the Management of Addiction, speaks for itself. The papers derive from a wide range of empirical paradigms and cover issues with relevance to the development of addiction, to the maintenance of problematic use, and to assessment, treatment, and relapse. Research from Europe and the United States is represented, as well as work from Australia. An international perspective is strongly emphasized from the initial paper by Obot, Poznyak, and Moneiro, (see record 2004-19599-015) which describes the WHO Report on the Neuroscience of Psychoactive Substance Use and Dependence, and summarises some of the report's implications for policy and practice. Hall, Carter, and Morley (see record 2004-19599-014) close the issue with a paper on the wide-ranging ethical implications of advances in neuroscience research, including issues arising from the identification of high risk for addiction, the potential for coercive pharmacotherapy, use of medications to enhance function, and risks to privacy.

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The wide range of contributing factors and circumstances surrounding crashes on road curves suggest that no single intervention can prevent these crashes. This paper presents a novel methodology, based on data mining techniques, to identify contributing factors and the relationship between them. It identifies contributing factors that influence the risk of a crash. Incident records, described using free text, from a large insurance company were analysed with rough set theory. Rough set theory was used to discover dependencies among data, and reasons using the vague, uncertain and imprecise information that characterised the insurance dataset. The results show that male drivers, who are between 50 and 59 years old, driving during evening peak hours are involved with a collision, had a lowest crash risk. Drivers between 25 and 29 years old, driving from around midnight to 6 am and in a new car has the highest risk. The analysis of the most significant contributing factors on curves suggests that drivers with driving experience of 25 to 42 years, who are driving a new vehicle have the highest crash cost risk, characterised by the vehicle running off the road and hitting a tree. This research complements existing statistically based tools approach to analyse road crashes. Our data mining approach is supported with proven theory and will allow road safety practitioners to effectively understand the dependencies between contributing factors and the crash type with the view to designing tailored countermeasures.

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This work presents an extended Joint Factor Analysis model including explicit modelling of unwanted within-session variability. The goals of the proposed extended JFA model are to improve verification performance with short utterances by compensating for the effects of limited or imbalanced phonetic coverage, and to produce a flexible JFA model that is effective over a wide range of utterance lengths without adjusting model parameters such as retraining session subspaces. Experimental results on the 2006 NIST SRE corpus demonstrate the flexibility of the proposed model by providing competitive results over a wide range of utterance lengths without retraining and also yielding modest improvements in a number of conditions over current state-of-the-art.

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Recent studies have shown that delusion-like experiences (DLEs) are common among general populations. This study investigates whether the prevalence of these experiences are linked to the embracing of New Age thought. Logistic regression analyses were performed using data derived from a large community sample of young adults (N = 3777). Belief in a spiritual or higher power other than God was found to be significantly associated with endorsement of 16 of 19 items from Peters et al. (1999b) Delusional Inventory following adjustment for a range of potential confounders, while belief in God was associated with endorsement of four items. A New Age conception of the divine appears to be strongly associated with a wide range of DLEs. Further research is needed to determine a causal link between New Age philosophy and DLEs (e.g. thought disturbance, suspiciousness, and delusions of grandeur).

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Artificial neural networks (ANN) have demonstrated good predictive performance in a wide range of applications. They are, however, not considered sufficient for knowledge representation because of their inability to represent the reasoning process succinctly. This paper proposes a novel methodology Gyan that represents the knowledge of a trained network in the form of restricted first-order predicate rules. The empirical results demonstrate that an equivalent symbolic interpretation in the form of rules with predicates, terms and variables can be derived describing the overall behaviour of the trained ANN with improved comprehensibility while maintaining the accuracy and fidelity of the propositional rules.

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Suicide has drawn much attention from both the scientific community and the public. Examining the impact of socio-environmental factors on suicide is essential in developing suicide prevention strategies and interventions, because it will provide health authorities with important information for their decision-making. However, previous studies did not examine the impact of socio-environmental factors on suicide using a spatial analysis approach. The purpose of this study was to identify the patterns of suicide and to examine how socio-environmental factors impact on suicide over time and space at the Local Governmental Area (LGA) level in Queensland. The suicide data between 1999 and 2003 were collected from the Australian Bureau of Statistics (ABS). Socio-environmental variables at the LGA level included climate (rainfall, maximum and minimum temperature), Socioeconomic Indexes for Areas (SEIFA) and demographic variables (proportion of Indigenous population, unemployment rate, proportion of population with low income and low education level). Climate data were obtained from Australian Bureau of Meteorology. SEIFA and demographic variables were acquired from ABS. A series of statistical and geographical information system (GIS) approaches were applied in the analysis. This study included two stages. The first stage used average annual data to view the spatial pattern of suicide and to examine the association between socio-environmental factors and suicide over space. The second stage examined the spatiotemporal pattern of suicide and assessed the socio-environmental determinants of suicide, using more detailed seasonal data. In this research, 2,445 suicide cases were included, with 1,957 males (80.0%) and 488 females (20.0%). In the first stage, we examined the spatial pattern and the determinants of suicide using 5-year aggregated data. Spearman correlations were used to assess associations between variables. Then a Poisson regression model was applied in the multivariable analysis, as the occurrence of suicide is a small probability event and this model fitted the data quite well. Suicide mortality varied across LGAs and was associated with a range of socio-environmental factors. The multivariable analysis showed that maximum temperature was significantly and positively associated with male suicide (relative risk [RR] = 1.03, 95% CI: 1.00 to 1.07). Higher proportion of Indigenous population was accompanied with more suicide in male population (male: RR = 1.02, 95% CI: 1.01 to 1.03). There was a positive association between unemployment rate and suicide in both genders (male: RR = 1.04, 95% CI: 1.02 to 1.06; female: RR = 1.07, 95% CI: 1.00 to 1.16). No significant association was observed for rainfall, minimum temperature, SEIFA, proportion of population with low individual income and low educational attainment. In the second stage of this study, we undertook a preliminary spatiotemporal analysis of suicide using seasonal data. Firstly, we assessed the interrelations between variables. Secondly, a generalised estimating equations (GEE) model was used to examine the socio-environmental impact on suicide over time and space, as this model is well suited to analyze repeated longitudinal data (e.g., seasonal suicide mortality in a certain LGA) and it fitted the data better than other models (e.g., Poisson model). The suicide pattern varied with season and LGA. The north of Queensland had the highest suicide mortality rate in all the seasons, while there was no suicide case occurred in the southwest. Northwest had consistently higher suicide mortality in spring, autumn and winter. In other areas, suicide mortality varied between seasons. This analysis showed that maximum temperature was positively associated with suicide among male population (RR = 1.24, 95% CI: 1.04 to 1.47) and total population (RR = 1.15, 95% CI: 1.00 to 1.32). Higher proportion of Indigenous population was accompanied with more suicide among total population (RR = 1.16, 95% CI: 1.13 to 1.19) and by gender (male: RR = 1.07, 95% CI: 1.01 to 1.13; female: RR = 1.23, 95% CI: 1.03 to 1.48). Unemployment rate was positively associated with total (RR = 1.40, 95% CI: 1.24 to 1.59) and female (RR=1.09, 95% CI: 1.01 to 1.18) suicide. There was also a positive association between proportion of population with low individual income and suicide in total (RR = 1.28, 95% CI: 1.10 to 1.48) and male (RR = 1.45, 95% CI: 1.23 to 1.72) population. Rainfall was only positively associated with suicide in total population (RR = 1.11, 95% CI: 1.04 to 1.19). There was no significant association for rainfall, minimum temperature, SEIFA, proportion of population with low educational attainment. The second stage is the extension of the first stage. Different spatial scales of dataset were used between the two stages (i.e., mean yearly data in the first stage, and seasonal data in the second stage), but the results are generally consistent with each other. Compared with other studies, this research explored the variety of the impact of a wide range of socio-environmental factors on suicide in different geographical units. Maximum temperature, proportion of Indigenous population, unemployment rate and proportion of population with low individual income were among the major determinants of suicide in Queensland. However, the influence from other factors (e.g. socio-culture background, alcohol and drug use) influencing suicide cannot be ignored. An in-depth understanding of these factors is vital in planning and implementing suicide prevention strategies. Five recommendations for future research are derived from this study: (1) It is vital to acquire detailed personal information on each suicide case and relevant information among the population in assessing the key socio-environmental determinants of suicide; (2) Bayesian model could be applied to compare mortality rates and their socio-environmental determinants across LGAs in future research; (3) In the LGAs with warm weather, high proportion of Indigenous population and/or unemployment rate, concerted efforts need to be made to control and prevent suicide and other mental health problems; (4) The current surveillance, forecasting and early warning system needs to be strengthened, to trace the climate and socioeconomic change over time and space and its impact on population health; (5) It is necessary to evaluate and improve the facilities of mental health care, psychological consultation, suicide prevention and control programs; especially in the areas with low socio-economic status, high unemployment rate, extreme weather events and natural disasters.

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A wide range of screening strategies have been employed to isolate antibodies and other proteins with specific attributes, including binding affinity, specificity, stability and improved expression. However, there remains no high-throughput system to screen for target-binding proteins in a mammalian, intracellular environment. Such a system would allow binding reagents to be isolated against intracellular clinical targets such as cell signalling proteins associated with tumour formation (p53, ras, cyclin E), proteins associated with neurodegenerative disorders (huntingtin, betaamyloid precursor protein), and various proteins crucial to viral replication (e.g. HIV-1 proteins such as Tat, Rev and Vif-1), which are difficult to screen by phage, ribosome or cell-surface display. This study used the β-lactamase protein complementation assay (PCA) as the display and selection component of a system for screening a protein library in the cytoplasm of HEK 293T cells. The colicin E7 (ColE7) and Immunity protein 7 (Imm7) *Escherichia coli* proteins were used as model interaction partners for developing the system. These proteins drove effective β-lactamase complementation, resulting in a signal-to-noise ratio (9:1 – 13:1) comparable to that of other β-lactamase PCAs described in the literature. The model Imm7-ColE7 interaction was then used to validate protocols for library screening. Single positive cells that harboured the Imm7 and ColE7 binding partners were identified and isolated using flow cytometric cell sorting in combination with the fluorescent β-lactamase substrate, CCF2/AM. A single-cell PCR was then used to amplify the Imm7 coding sequence directly from each sorted cell. With the screening system validated, it was then used to screen a protein library based the Imm7 scaffold against a proof-of-principle target. The wild-type Imm7 sequence, as well as mutants with wild-type residues in the ColE7- binding loop were enriched from the library after a single round of selection, which is consistent with other eukaryotic screening systems such as yeast and mammalian cell-surface display. In summary, this thesis describes a new technology for screening protein libraries in a mammalian, intracellular environment. This system has the potential to complement existing screening technologies by allowing access to intracellular proteins and expanding the range of targets available to the pharmaceutical industry.

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Forecasting volatility has received a great deal of research attention, with the relative performances of econometric model based and option implied volatility forecasts often being considered. While many studies find that implied volatility is the pre-ferred approach, a number of issues remain unresolved, including the relative merit of combining forecasts and whether the relative performances of various forecasts are statistically different. By utilising recent econometric advances, this paper considers whether combination forecasts of S&P 500 volatility are statistically superior to a wide range of model based forecasts and implied volatility. It is found that a combination of model based forecasts is the dominant approach, indicating that the implied volatility cannot simply be viewed as a combination of various model based forecasts. Therefore, while often viewed as a superior volatility forecast, the implied volatility is in fact an inferior forecast of S&P 500 volatility relative to model-based forecasts.