540 resultados para work function
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Material for this paper comes partly from a report commissioned by the Department of Family Services, Aboriginal and Islander Affairs. The report is the result of a multi-strategy research project designed to assess the impact of gaming machines on the fundraising capacity of charitable and community organisations in Queensland. The first Queensland gaming machine was commissioned on 11 February 1992. By 30 November 1994 there were: · 636 clubs operating 13,162 gaming machines · 436 hotels/taverns operating 3,468 gaming machines.1 It was anticipated that the introduction of gaming machines would impact on charities and community organisations. The adverse impacts would be through competition with charity gaming and disposable income that might otherwise be directed towards donations. Some also expressed concern that charities would be relied on to finance social services for problem gamblers. This paper seeks to describe the donations and grants derived by charities from Gaming Machine revenues. Such revenues primarily come from either government distributions from its gaming machine taxes and levies or gaming machine club donations. A final comment is made on the opinions of charitable fundraising professionals about the impact of gaming machine levies on club donations.
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This paper examines the way psychologists and others in teh helping professions can deal with stressors in their lives and still work effectively. Three questions will be asked. First "What are the essential ingredients of an environment that supports psychologists going through personal stressors? Second, "What are the personal characteristics and strategies that give resilience to a professional during this period?" and third,"How does the stressor or grieving process influence a psychologist's therapy?" The whole will be fitted into a visual framework and the interaction of the three main variables (client, therapist and stressor) will be explored.
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Current unbalance is a significant power quality problem in distribution networks. This problem increases further with the increased penetration of single-phase photovoltaic cells. In this paper, a new approach is developed for current unbalance reduction in medium voltage distribution networks. The method is based on utilization of three single-phase voltage source converters connected in delta configuration between the phases. Each converter is controlled to function as a varying capacitor. The combination of the load and the compensator will result in a balanced load with unity power factor. The efficacy of the proposed current unbalance reduction concept is verified through dynamic simulations in PSCAD/EMTDC.
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Total hip arthroplasty (THA) has a proven clinical record for providing pain relief and return of function to patients with disabling arthritis. There are many successful options for femoral implant design and fixation. Cemented, polished, tapered femoral implants have been shown to have excellent results in national joint registries and long-term clinical series. These implants are usually 150mm long at their lateral aspect. Due to their length, these implants cannot always be offered to patients due to variations in femoral anatomy. Polished, tapered implants as short as 95mm exist, however their small proximal geometry (neck offset and body size) limit their use to smaller stature patients. There is a group of patients in which a shorter implant with a maintained proximal body size would be advantageous. There are also potential benefits to a shorter implant in standard patient populations such as reduced bone removal due to reduced reaming, favourable loading of the proximal femur, and the ability to revise into good proximal bone stock if required. These factors potentially make a shorter implant an option for all patient populations. The role of implant length in determining the stability of a cemented, polished, tapered femoral implant is not well defined by the literature. Before changes in implant design can be made, a better understanding of the role of each region in determining performance is required. The aim of the thesis was to describe how implant length affects the stability of a cemented, polished, tapered femoral implant. This has been determined through an extensive body of laboratory testing. The major findings are that for a given proximal body size, a reduction in implant length has no effect on the torsional stability of a polished, tapered design, while a small reduction in axial stability should be expected. These findings are important because the literature suggests that torsional stability is the major determinant of long-term clinical performance of a THA system. Furthermore, a polished, tapered design is known to be forgiving of cement-implant interface micromotion due to the favourable wear characteristics. Together these findings suggest that a shorter polished, tapered implant may be well tolerated. The effect of a change in implant length on the geometric characteristics of polished, tapered design were also determined and applied to the mechanical testing. Importantly, interface area does play a role in stability of the system; however it is the distribution of the interface and not the magnitude of the area that defines stability. Taper angle (at least in the range of angles seen in this work) was shown not to be a determinant of axial or torsional stability. A range of implants were tested, comparing variations in length, neck offset and indication (primary versus cement-in-cement revision). At their manufactured length, the 125mm implants were similar to their longer 150mm counterparts suggesting that they may be similarly well tolerated in the clinical environment. However, the slimmer cement-in-cement revision implant was shown to have a poorer mechanical performance, suggesting their use in higher demand patients may be hazardous. An implant length of 125mm has been shown to be quite stable and the results suggest that a further reduction to 100mm may be tolerated. However, further work is required. A shorter implant with maintained proximal body size would be useful for the group of patients who are unable to access the current standard length implants due to variations in femoral anatomy. Extending the findings further, the similar function with potential benefits of a shorter implant make their application to all patients appealing.
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The serviceability and safety of bridges are crucial to people’s daily lives and to the national economy. Every effort should be taken to make sure that bridges function safely and properly as any damage or fault during the service life can lead to transport paralysis, catastrophic loss of property or even casualties. Nonetheless, aggressive environmental conditions, ever-increasing and changing traffic loads and aging can all contribute to bridge deterioration. With often constrained budget, it is of significance to identify bridges and bridge elements that should be given higher priority for maintenance, rehabilitation or replacement, and to select optimal strategy. Bridge health prediction is an essential underpinning science to bridge maintenance optimization, since the effectiveness of optimal maintenance decision is largely dependent on the forecasting accuracy of bridge health performance. The current approaches for bridge health prediction can be categorised into two groups: condition ratings based and structural reliability based. A comprehensive literature review has revealed the following limitations of the current modelling approaches: (1) it is not evident in literature to date that any integrated approaches exist for modelling both serviceability and safety aspects so that both performance criteria can be evaluated coherently; (2) complex system modelling approaches have not been successfully applied to bridge deterioration modelling though a bridge is a complex system composed of many inter-related bridge elements; (3) multiple bridge deterioration factors, such as deterioration dependencies among different bridge elements, observed information, maintenance actions and environmental effects have not been considered jointly; (4) the existing approaches are lacking in Bayesian updating ability to incorporate a variety of event information; (5) the assumption of series and/or parallel relationship for bridge level reliability is always held in all structural reliability estimation of bridge systems. To address the deficiencies listed above, this research proposes three novel models based on the Dynamic Object Oriented Bayesian Networks (DOOBNs) approach. Model I aims to address bridge deterioration in serviceability using condition ratings as the health index. The bridge deterioration is represented in a hierarchical relationship, in accordance with the physical structure, so that the contribution of each bridge element to bridge deterioration can be tracked. A discrete-time Markov process is employed to model deterioration of bridge elements over time. In Model II, bridge deterioration in terms of safety is addressed. The structural reliability of bridge systems is estimated from bridge elements to the entire bridge. By means of conditional probability tables (CPTs), not only series-parallel relationship but also complex probabilistic relationship in bridge systems can be effectively modelled. The structural reliability of each bridge element is evaluated from its limit state functions, considering the probability distributions of resistance and applied load. Both Models I and II are designed in three steps: modelling consideration, DOOBN development and parameters estimation. Model III integrates Models I and II to address bridge health performance in both serviceability and safety aspects jointly. The modelling of bridge ratings is modified so that every basic modelling unit denotes one physical bridge element. According to the specific materials used, the integration of condition ratings and structural reliability is implemented through critical failure modes. Three case studies have been conducted to validate the proposed models, respectively. Carefully selected data and knowledge from bridge experts, the National Bridge Inventory (NBI) and existing literature were utilised for model validation. In addition, event information was generated using simulation to demonstrate the Bayesian updating ability of the proposed models. The prediction results of condition ratings and structural reliability were presented and interpreted for basic bridge elements and the whole bridge system. The results obtained from Model II were compared with the ones obtained from traditional structural reliability methods. Overall, the prediction results demonstrate the feasibility of the proposed modelling approach for bridge health prediction and underpin the assertion that the three models can be used separately or integrated and are more effective than the current bridge deterioration modelling approaches. The primary contribution of this work is to enhance the knowledge in the field of bridge health prediction, where more comprehensive health performance in both serviceability and safety aspects are addressed jointly. The proposed models, characterised by probabilistic representation of bridge deterioration in hierarchical ways, demonstrated the effectiveness and pledge of DOOBNs approach to bridge health management. Additionally, the proposed models have significant potential for bridge maintenance optimization. Working together with advanced monitoring and inspection techniques, and a comprehensive bridge inventory, the proposed models can be used by bridge practitioners to achieve increased serviceability and safety as well as maintenance cost effectiveness.
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Quality oriented management systems and methods have become the dominant business and governance paradigm. From this perspective, satisfying customers’ expectations by supplying reliable, good quality products and services is the key factor for an organization and even government. During recent decades, Statistical Quality Control (SQC) methods have been developed as the technical core of quality management and continuous improvement philosophy and now are being applied widely to improve the quality of products and services in industrial and business sectors. Recently SQC tools, in particular quality control charts, have been used in healthcare surveillance. In some cases, these tools have been modified and developed to better suit the health sector characteristics and needs. It seems that some of the work in the healthcare area has evolved independently of the development of industrial statistical process control methods. Therefore analysing and comparing paradigms and the characteristics of quality control charts and techniques across the different sectors presents some opportunities for transferring knowledge and future development in each sectors. Meanwhile considering capabilities of Bayesian approach particularly Bayesian hierarchical models and computational techniques in which all uncertainty are expressed as a structure of probability, facilitates decision making and cost-effectiveness analyses. Therefore, this research investigates the use of quality improvement cycle in a health vii setting using clinical data from a hospital. The need of clinical data for monitoring purposes is investigated in two aspects. A framework and appropriate tools from the industrial context are proposed and applied to evaluate and improve data quality in available datasets and data flow; then a data capturing algorithm using Bayesian decision making methods is developed to determine economical sample size for statistical analyses within the quality improvement cycle. Following ensuring clinical data quality, some characteristics of control charts in the health context including the necessity of monitoring attribute data and correlated quality characteristics are considered. To this end, multivariate control charts from an industrial context are adapted to monitor radiation delivered to patients undergoing diagnostic coronary angiogram and various risk-adjusted control charts are constructed and investigated in monitoring binary outcomes of clinical interventions as well as postintervention survival time. Meanwhile, adoption of a Bayesian approach is proposed as a new framework in estimation of change point following control chart’s signal. This estimate aims to facilitate root causes efforts in quality improvement cycle since it cuts the search for the potential causes of detected changes to a tighter time-frame prior to the signal. This approach enables us to obtain highly informative estimates for change point parameters since probability distribution based results are obtained. Using Bayesian hierarchical models and Markov chain Monte Carlo computational methods, Bayesian estimators of the time and the magnitude of various change scenarios including step change, linear trend and multiple change in a Poisson process are developed and investigated. The benefits of change point investigation is revisited and promoted in monitoring hospital outcomes where the developed Bayesian estimator reports the true time of the shifts, compared to priori known causes, detected by control charts in monitoring rate of excess usage of blood products and major adverse events during and after cardiac surgery in a local hospital. The development of the Bayesian change point estimators are then followed in a healthcare surveillances for processes in which pre-intervention characteristics of patients are viii affecting the outcomes. In this setting, at first, the Bayesian estimator is extended to capture the patient mix, covariates, through risk models underlying risk-adjusted control charts. Variations of the estimator are developed to estimate the true time of step changes and linear trends in odds ratio of intensive care unit outcomes in a local hospital. Secondly, the Bayesian estimator is extended to identify the time of a shift in mean survival time after a clinical intervention which is being monitored by riskadjusted survival time control charts. In this context, the survival time after a clinical intervention is also affected by patient mix and the survival function is constructed using survival prediction model. The simulation study undertaken in each research component and obtained results highly recommend the developed Bayesian estimators as a strong alternative in change point estimation within quality improvement cycle in healthcare surveillances as well as industrial and business contexts. The superiority of the proposed Bayesian framework and estimators are enhanced when probability quantification, flexibility and generalizability of the developed model are also considered. The empirical results and simulations indicate that the Bayesian estimators are a strong alternative in change point estimation within quality improvement cycle in healthcare surveillances. The superiority of the proposed Bayesian framework and estimators are enhanced when probability quantification, flexibility and generalizability of the developed model are also considered. The advantages of the Bayesian approach seen in general context of quality control may also be extended in the industrial and business domains where quality monitoring was initially developed.
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Background We have previously demonstrated that human kidney proximal tubule epithelial cells (PTEC) are able to modulate autologous T and B lymphocyte responses. It is well established that dendritic cells (DC) are responsible for the initiation and direction of adaptive immune responses and that these cells occur in the renal interstitium in close apposition to PTEC under inflammatory disease settings. However, there is no information regarding the interaction of PTEC with DC in an autologous human context. Methods Human monocytes were differentiated into monocyte-derived DC (MoDC) in the absence or presence of primary autologous activated PTEC and matured with polyinosinic:polycytidylic acid [poly(I:C)], while purified, pre-formed myeloid blood DC (CD1c+ BDC) were cultured with autologous activated PTEC in the absence or presence of poly(I:C) stimulation. DC responses were monitored by surface antigen expression, cytokine secretion, antigen uptake capacity and allogeneic T-cell-stimulatory ability. Results The presence of autologous activated PTEC inhibited the differentiation of monocytes to MoDC. Furthermore, MoDC differentiated in the presence of PTEC displayed an immature surface phenotype, efficient phagocytic capacity and, upon poly(I:C) stimulation, secreted low levels of pro-inflammatory cytokine interleukin (IL)-12p70, high levels of anti-inflammatory cytokine IL-10 and induced weak Th1 responses. Similarly, pre-formed CD1c+ BDC matured in the presence of PTEC exhibited an immature tolerogenic surface phenotype, strong endocytic and phagocytic ability and stimulated significantly attenuated T-cell proliferative responses. Conclusions Our data suggest that activated PTEC regulate human autologous immunity via complex interactions with DC. The ability of PTEC to modulate autologous DC function has important implications for the dampening of pro-inflammatory immune responses within the tubulointerstitium in renal injuries. Further dissection of the mechanisms of PTEC modulation of autologous immune responses may offer targets for therapeutic intervention in renal medicine.
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Introduction This study is a snapshot of Australian donor motivations and donor barriers to crowdfunding, and provides some indicative recommendations on ways the uptake of crowdfunding in the creative industries might increase. It is based upon a literature review and semi-structured interviews with 17 stakeholders who have used crowdfunding in Australia, including: creative producers seeking funds; financial crowdfunding donors; Artsupport Australia mentors of artists who are using crowdfunding; and crowdfunding site stakeholders. About the report Artsupport Australia commissioned the Queensland University of Technology Creative Industries team to produce a report on trends related to crowdfunding, particularly identifying barriers and motivations that might be associated with it. Artsupport Australia suggested a list of interview candidates, based on those individuals’ knowledge or experience with crowdfunding, to provide a better understanding of perceptions of this emerging practice, and to inform discussions on whether it is a useful revenue generating mechanism for the cultural sector.
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The paper discusses an aspect of reading research methodology as represented by papers published by the Reading Research Quarterly from the beginning of 1989(volume 24, Number 1) to the end of 1993 (volume 28, Number 4). The discussion suggests some points of departure between this research community and an Australian community broadly defined as poststructural. A focus for this investigation is the function of “gender” within the methodological approaches of the two communities. Suggestions are made regarding some potentially productive points of intersection between the work of American and Australian reading researchers.
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Since the 1980s, higher education in Australia has undergone significant change which has led to the belief that universities should cultivate students’ generic skills and attributes. For example, Achieving Quality states that generic skills ‘should represent the central achievements of higher education as a process’ (Higher Education Council, 1992, p 20). The CALD Standards for Australian Law Schools also recognise that tertiary curricula should ‘seek to develop knowledge, understanding, skills, and values’ (Council of Australian Law Deans, 2009, [2.3]. See also AQF Council, 2010, pp 32-5, 40-2; AQF Council, 2011, p 45-50). This more instrumentalist view of education is similarly exhibited by students (Saulwick and Muller, 2006, pp 7, 34). No longer does the modern graduate expect their university degree to equip them solely with the content knowledge of their discipline, but also with the skills and attributes relevant to their career and prospective employment.
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Background: There is a need to better describe and understand the prevalence of breast cancer treatment-related adverse effects amenable to physical therapy and rehabilitative exercise. Prior studies have been limited to single issues and lacked long term follow-up. The Pulling Through Study provides data on prevalence of adverse effects in breast cancer survivors followed over six years. Methods: A population-based sample of Australian women (n=287) diagnosed with invasive, unilateral breast cancer was followed for a median of 6.6 years and prospectively assessed for treatment-related complications at 6, 12, 18 months, and 6 years post-diagnosis. Assessments included post-surgical complications, skin or tissue reaction to radiation therapy, upper-body symptoms, lymphedema, 10% weight gain, fatigue, and upper-quadrant function. The proportion of women with positive indication for each complication and one or more complication was estimated using all available data at each time point. Women were only considered to have a specific complication if they reported the highest two levels of the Likert scale for self-reported issues. Results: At six years post-diagnosis over 60% of women experienced one or more side effects amenable to rehabilitative intervention. The proportion of women experiencing 3 or more side effects decreased throughout follow-up, while the proportion experiencing no side effects remained stable around 40% from 12 months to six years. Weight gain was the only complication to increase in prevalence over time. Conclusion: These data support the development of a multi-disciplinary prospective surveillance approach for the purposes of managing and treating adverse effects in breast cancer survivors.
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Binge-like patterns of excessive drinking during young adulthood increase the propensity for alcohol use disorders (AUDs) later in adult life; however, the mechanisms that drive this are not completely understood. Previous studies showed that the δ-opioid peptide receptor (DOP-R) is dynamically regulated by exposure to ethanol and that the DOP-R plays a role in ethanol-mediated behaviors. The aim of this study was to determine the role of the DOP-R in high ethanol consumption from young adulthood through to late adulthood by measuring DOP-R-mediated [(35)S]GTPγS binding in brain membranes and DOP-R-mediated analgesia using a rat model of high ethanol consumption in Long Evans rats. We show that DOP-R activity in the dorsal striatum and DOP-R-mediated analgesia changes during development, being highest during early adulthood and reduced in late adulthood. Intermittent access to ethanol but not continuous ethanol or water from young adulthood leads to an increase in DOP-R activity in the dorsal striatum and DOP-R-mediated analgesia into late adulthood. Multiple microinfusions of naltrindole into the dorsal striatum or multiple systemic administration of naltrindole reduces ethanol consumption, and following termination of treatment, DOP-R activity in the dorsal striatum is attenuated. These findings suggest that DOP-R activity in the dorsal striatum plays a role in high levels of ethanol consumption and suggest that targeting the DOP-R is an alternative strategy for the treatment of AUDs.
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Models of cell invasion incorporating directed cell movement up a gradient of an external substance and carrying capacity-limited proliferation give rise to travelling wave solutions. Travelling wave profiles with various shapes, including smooth monotonically decreasing, shock-fronted monotonically decreasing and shock-fronted nonmonotone shapes, have been reported previously in the literature. The existence of tacticallydriven shock-fronted nonmonotone travelling wave solutions is analysed for the first time. We develop a necessary condition for nonmonotone shock-fronted solutions. This condition shows that some of the previously reported shock-fronted nonmonotone solutions are genuine while others are a consequence of numerical error. Our results demonstrate that, for certain conditions, travelling wave solutions can be either smooth and monotone, smooth and nonmonotone or discontinuous and nonmonotone. These different shapes correspond to different invasion speeds. A necessary and sufficient condition for the travelling wave with minimum wave speed to be nonmonotone is presented. Several common forms of the tactic sensitivity function have the potential to satisfy the newly developed condition for nonmonotone shock-fronted solutions developed in this work.
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There is a notable shortage of empirical research directed at measuring the magnitude and direction of stress effects on performance in a controlled environment. One reason for this is the inherent difficulties in identifying and isolating direct performance measures for individuals. Additionally, most traditional work environments contain a multitude of exogenous factors impacting individual performance, but controlling for all such factors is generally unfeasible (omitted variable bias). Moreover, instead of asking individuals about their self-reported stress levels, we observe workers’ behaviour in situations that can be classified as stressful. For this reason, we have stepped outside the traditional workplace in an attempt to gain greater controllability of these factors using the sports environment as our experimental space. We empirically investigate the relationship between stress and performance, in an extreme pressure situation (football penalty kicks) in a winner take all sporting environment (FIFA World Cup and UEFA European Cup competitions). Specifically, we examine all the penalty shootouts between 1976 and 2008 covering in total 16 events. The results indicate that extreme stressors can have a positive or negative impact on individuals’ performance. On the other hand, more commonly experienced stressors do not affect professionals’ performances.
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The inquiries to return predictability are traditionally limited to conditional mean, while literature on portfolio selection is replete with moment-based analysis with up to the fourth moment being considered. This paper develops a distribution-based framework for both return prediction and portfolio selection. More specifically, a time-varying return distribution is modeled through quantile regressions and copulas, using quantile regressions to extract information in marginal distributions and copulas to capture dependence structure. A preference function which captures higher moments is proposed for portfolio selection. An empirical application highlights the additional information provided by the distributional approach which cannot be captured by the traditional moment-based methods.