581 resultados para First-motion polarization
Resumo:
Communities of practice (CoPs) may be defined as groups of people who are mutually bound by what they do together (Wenger, 1998, p. 2), that is, they “form to share what they know, to learn from one another regarding some aspects of their work and to provide a social context for that work” (Nickols, 2000, para. 1). They are “emergent” in that the shape and membership emerges in the process of activity (Lees, 2005, p. 7). People in CoPs share their knowledge and experiences freely with the purpose of finding inventive ways to approach new problems (Wenger & Snyder, 2000, p. 2). They can be seen as “shared histories of learning” (Wenger, 1998, p. 86). For some time, QUT staff have been involved in a number of initiatives aimed at sharing ideas and resources for teaching first year students such as the Coordinators of Large First Year Units Working Party. To harness these initiatives and maximise their influence, the leaders of the Transitions In Project (TIP)1 decided to form a CoP around the design, assessment and management of large first year units.
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Institutions should enact holistic approaches that address students’ personal, social and academic engagement in the early weeks of first year to facilitate retention (Nelson, Kift & Clarke, 2008). This holistic approach is central to the FYE program at Queensland University of Technology (QUT), which was established to maximise learning engagement and hence positively influence the retention of commencing students. The program aims to • engage students in their learning through an intentionally designed and enacted curriculum (Kift, 2008) • facilitate timely access to life and learning support • promote a sense of belonging to the discipline, cohort and profession. The FYE program’s aims are achieved by strategic alliances between academic and professional staff across the institution.
Resumo:
Institutions should enact holistic approaches that address students’ personal, social and academic engagement in the early weeks of first year to facilitate retention (Nelson, Kift & Clarke, 2008). This holistic approach is central to the FYE program at Queensland University of Technology (QUT), which was established to maximise learning engagement and hence positively influence the retention of commencing students.
Resumo:
Background: The transition to school is a sensitive period for children in relation to school success. In the early school years, children need to develop positive attitudes to school and have experiences that promote academic, behavioural and social competence. When children begin school there are higher expectations of responsibility and independence and in the year one class, there are more explicit academic goals for literacy and numeracy and more formal instruction. Most importantly, children’s early attitudes to learning and learning styles have an impact on later educational outcomes. Method: Data were drawn from The Longitudinal Study of Australian Children (LSAC). LSAC is a cross-sequential cohort study funded by the Australian Government. In these analyses, Wave 2 (2006) data for 2499 children in the Kindergarten Cohort were used. Children, at Wave 2, were in the first year of formal school. They had a mean age of 6.9 years (SD= 0.26). Measures included a 6-item measure of Approaches to Learning (task persistence, independence) and the Academic Rating Scales for language and literacy and mathematical thinking. Teachers rated their relationships with children on the short form of the STRS. Results: Girls were rated by their teachers as doing better than boys on Language and literacy, Approaches to learning; and they had a better relationship with their teacher. Children from an Aboriginal or Torres Strait Island (ATSI) background were rated as doing less well on Language and Literacy and Mathematical thinking and on their Approaches to learning. Children from high Socio Economic Position families are doing better on teacher rated Language and Literacy, Mathematical thinking, Approaches to learning and they had a better relationship with their teacher. Conclusions: Findings highlight the importance of key demographic variables in understanding children’s early school success.
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A five-section questionnaire was mailed to all 234 authorised Australian nurse practitioners in late 2007. An 85% response rate was achieved (202 responses). Respondents had a mean age of 47.0 years and 84.2% were women. Only 145 nurse practitioners (72% of respondents) reported being employed in Australia at the time of the census. Emergency nurse practitioners were the most commonly employed nationally (26.9%). Nearly one third of employed nurse practitioners reported that they were still awaiting approval to prescribe medications despite this being a core legislated skill. Over 70% stated that lack of Medicare provider numbers and lack of authority to prescribe through the Pharmaceut ical Benef its Scheme was extremely limiting to their practice. These findings are consistent with the international literature describing establishment of reformative
Resumo:
Ethyl-eicosapentaenoic acid (E-EPA) is an omega-3 fatty acid that has been used in a range of neuropsychiatric conditions with some benefits. However, its mechanism of action is unknown. Here, we investigate its effects on in vivo brain metabolism in first-episode psychosis (FEP). Proton magnetic resonance spectroscopy at 3 T was performed in the temporal lobes of 24 FEP patients before and after 12 weeks of treatment in the context of a larger double-blind, placebo-controlled E-EPA augmentation study. Treatment group effects for glutathione (F1,12=6.1, p=0.03), and a hemisphere-by-group interaction for glutamine/glutamate (F1,20=4.4, p=0.049) were found. Glutathione increased bilaterally and glutamate/glutamine increased in the left hemisphere following E-EPA administration. Improvement in negative symptoms correlated with metabolic brain changes, particularly glutathione (r=-0.57). These results suggest that E-EPA augmentation alters glutathione availability and modulates the glutamine/glutamate cycle in early psychosis, with some of the metabolic brain changes being correlated with negative symptom improvement. Larger confirmatory studies of these postulated metabolic brain effects of E-EPA are warranted.
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Schizophrenia is associated with significant brain abnormalities, including changes in brain metabolites as measured by proton magnetic resonance spectroscopy (MRS). What remains unclear is the extent to which these changes are a consequence of the emergence of psychotic disorders or the result of treatment with antipsychotic medication. We assessed 34 patients with first episode psychosis (15 antipsychotic naïve) and 19 age- and gender-matched controls using short-echo MRS in the medial temporal lobe bilaterally. Overall, there were no differences in any metabolite, regardless of treatment status. However, when the analysis was limited to patients with a diagnosis of schizophrenia, schizophreniform or schizoaffective disorder, significant elevations of creatine/phosphocreatine (Cr/PCr) and myo-inositol (mI) were found in the treated group. These data indicate a relative absence of temporal lobe metabolic abnormalities in first episode psychosis, but suggest that some treatment-related changes in mI might be apparent in patients with schizophrenia-spectrum diagnoses. Seemingly illness-related Cr/PCr elevations were also specific to the diagnosis of schizophrenia-spectrum disorder and seem worthy of future study.
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It has been argued that intentional first year curriculum design has a critical role to play in enhancing first year student engagement, success and retention (Kift, 2008). A fundamental first year curriculum objective should be to assist students to make the successful transition to assessment in higher education. Scott (2006) has identified that ‘relevant, consistent and integrated assessment … [with] prompt and constructive feedback’ are particularly relevant to student retention generally; while Nicol (2007) suggests that ‘lack of clarity regarding expectations in the first year, low levels of teacher feedback and poor motivation’ are key issues in the first year. At the very minimum, if we expect first year students to become independent and self-managing learners, they need to be supported in their early development and acquisition of tertiary assessment literacies (Orrell, 2005). Critical to this attainment is the necessity to alleviate early anxieties around assessment information, instructions, guidance, and performance. This includes, for example: inducting students thoroughly into the academic languages and assessment genres they will encounter as the vehicles for evidencing learning success; and making expectations about the quality of this evidence clear. Most importantly, students should receive regular formative feedback of their work early in their program of study to aid their learning and to provide information to both students and teachers on progress and achievement. Leveraging research conducted under an ALTC Senior Fellowship that has sought to articulate a research-based 'transition pedagogy' (Kift & Nelson, 2005) – a guiding philosophy for intentional first year curriculum design and support that carefully scaffolds and mediates the first year learning experience for contemporary heterogeneous cohorts – this paper will discuss theoretical and practical strategies and examples that should be of assistance in implementing good assessment and feedback practices across a range of disciplines in the first year.
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This paper describes an initiative in the Faculty of Health at the Queensland University of Technology, Australia, where a short writing task was introduced to first year undergraduates in four courses including Public Health, Nursing, Social Work and Human Services, and Human Movement Studies. Over 1,000 students were involved in the trial. The task was assessed using an adaptation of the MASUS Procedure (Measuring the Academic Skills of University Students) (Webb & Bonanno, 1994). Feedback to the students including MASUS scores then enabled students to be directed to developmental workshops targeting their academic literacy needs. Students who achieved below the benchmark score were required to attend academic writing workshops in order to obtain the same summative 10% that was obtained by those who had achieved above the benchmark score. The trial was very informative, in terms of determining task appropriateness and timing, student feedback, student use of support, and student perceptions of the task and follow-up workshops. What we learned from the trial will be presented with a view to further refinement of this initiative.
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First-degree relatives of men with prostate cancer have a higher risk of being diagnosed with prostate cancer than men without a family history. The present review examines the prevalence and predictors of testing in first-degree relatives, perceptions of risk, prostate cancer knowledge and psychological consequences of screening. Medline, PsycInfo and Cinahl databases were searched for articles examining risk perceptions or screening practices of first-degree relatives of men with prostate cancer for the period of 1990 to August 2007. Eighteen studies were eligible for inclusion. First-degree relatives participated in prostate-specific antigen (PSA) testing more and perceived their risk of prostate cancer to be higher than men without a family history. Family history factors (e.g. being an unaffected son rather than an unaffected brother) were consistent predictors of PSA testing. Studies were characterized by sampling biases and a lack of longitudinal assessments. Prospective, longitudinal assessments with well-validated and comprehensive measures are needed to identify factors that cue the uptake of screening and from this develop an evidence base for decision support. Men with a family history may benefit from targeted communication about the risks and benefits of prostate cancer testing that responds to the implications of their heightened risk.
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This article explores two matrix methods to induce the ``shades of meaning" (SoM) of a word. A matrix representation of a word is computed from a corpus of traces based on the given word. Non-negative Matrix Factorisation (NMF) and Singular Value Decomposition (SVD) compute a set of vectors corresponding to a potential shade of meaning. The two methods were evaluated based on loss of conditional entropy with respect to two sets of manually tagged data. One set reflects concepts generally appearing in text, and the second set comprises words used for investigations into word sense disambiguation. Results show that for NMF consistently outperforms SVD for inducing both SoM of general concepts as well as word senses. The problem of inducing the shades of meaning of a word is more subtle than that of word sense induction and hence relevant to thematic analysis of opinion where nuances of opinion can arise.
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Although placing reflective markers on pedestrians’ major joints can make pedestrians more conspicuous to drivers at night, it has been suggested that this “biological motion” effect may be reduced when visual clutter is present. We tested whether extraneous points of light affected the ability of 12 younger and 12 older drivers to see pedestrians as they drove on a closed road at night. Pedestrians wore black clothing alone or with retroreflective markings in four different configurations. One pedestrian walked in place and was surrounded by clutter on half of the trials. Another was always surrounded by visual clutter but either walked in place or stood still. Clothing configuration, pedestrian motion, and driver age influenced conspicuity but clutter did not. The results confirm that even in the presence of visual clutter pedestrians wearing biological motion configurations are recognized more often and at greater distances than when they wear a reflective vest.
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The importance of student engagement to higher education quality, making deep learning outcomes possible for students, and achieving student retention, is increasingly being understood. The issue of student engagement in the first year of tertiary study is of particular significance. This paper takes the position that the first year curriculum, and the pedagogical principles that inform its design, are critical influencers of student engagement in the first year learning environment. We use an analysis of case studies prepared for Kift’s ALTC Senior Fellowship to demonstrate ways in which student engagement in the first year of tertiary study can be successfully supported through intentional curriculum design that motivates students to learn, provides a positive learning climate, and encourages students to be active in their learning.
Resumo:
3D Motion capture is a medium that plots motion, typically human motion, converting it into a form that can be represented digitally. It is a fast evolving field and recent inertial technology may provide new artistic possibilities for its use in live performance. Although not often used in this context, motion capture has a combination of attributes that can provide unique forms of collaboration with performance arts. The inertial motion capture suit used for this study has orientation sensors placed at strategic points on the body to map body motion. Its portability, real-time performance, ease of use, and its immunity from line-of-sight problems inherent in optical systems suggest it would work well as a live performance technology. Many animation techniques can be used in real-time. This research examines a broad cross-section of these techniques using four practice-led cases to assess the suitability of inertial motion capture to live performance. Although each case explores different visual possibilities, all make use of the performativity of the medium, using either an improvisational format or interactivity among stage, audience and screen that would be difficult to emulate any other way. A real-time environment is not capable of reproducing the depth and sophistication of animation people have come to expect through media. These environments take many hours to render. In time the combination of what can be produced in real-time and the tools available in a 3D environment will no doubt create their own tree of aesthetic directions in live performance. The case study looks at the potential of interactivity that this technology offers.
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Financial processes may possess long memory and their probability densities may display heavy tails. Many models have been developed to deal with this tail behaviour, which reflects the jumps in the sample paths. On the other hand, the presence of long memory, which contradicts the efficient market hypothesis, is still an issue for further debates. These difficulties present challenges with the problems of memory detection and modelling the co-presence of long memory and heavy tails. This PhD project aims to respond to these challenges. The first part aims to detect memory in a large number of financial time series on stock prices and exchange rates using their scaling properties. Since financial time series often exhibit stochastic trends, a common form of nonstationarity, strong trends in the data can lead to false detection of memory. We will take advantage of a technique known as multifractal detrended fluctuation analysis (MF-DFA) that can systematically eliminate trends of different orders. This method is based on the identification of scaling of the q-th-order moments and is a generalisation of the standard detrended fluctuation analysis (DFA) which uses only the second moment; that is, q = 2. We also consider the rescaled range R/S analysis and the periodogram method to detect memory in financial time series and compare their results with the MF-DFA. An interesting finding is that short memory is detected for stock prices of the American Stock Exchange (AMEX) and long memory is found present in the time series of two exchange rates, namely the French franc and the Deutsche mark. Electricity price series of the five states of Australia are also found to possess long memory. For these electricity price series, heavy tails are also pronounced in their probability densities. The second part of the thesis develops models to represent short-memory and longmemory financial processes as detected in Part I. These models take the form of continuous-time AR(∞) -type equations whose kernel is the Laplace transform of a finite Borel measure. By imposing appropriate conditions on this measure, short memory or long memory in the dynamics of the solution will result. A specific form of the models, which has a good MA(∞) -type representation, is presented for the short memory case. Parameter estimation of this type of models is performed via least squares, and the models are applied to the stock prices in the AMEX, which have been established in Part I to possess short memory. By selecting the kernel in the continuous-time AR(∞) -type equations to have the form of Riemann-Liouville fractional derivative, we obtain a fractional stochastic differential equation driven by Brownian motion. This type of equations is used to represent financial processes with long memory, whose dynamics is described by the fractional derivative in the equation. These models are estimated via quasi-likelihood, namely via a continuoustime version of the Gauss-Whittle method. The models are applied to the exchange rates and the electricity prices of Part I with the aim of confirming their possible long-range dependence established by MF-DFA. The third part of the thesis provides an application of the results established in Parts I and II to characterise and classify financial markets. We will pay attention to the New York Stock Exchange (NYSE), the American Stock Exchange (AMEX), the NASDAQ Stock Exchange (NASDAQ) and the Toronto Stock Exchange (TSX). The parameters from MF-DFA and those of the short-memory AR(∞) -type models will be employed in this classification. We propose the Fisher discriminant algorithm to find a classifier in the two and three-dimensional spaces of data sets and then provide cross-validation to verify discriminant accuracies. This classification is useful for understanding and predicting the behaviour of different processes within the same market. The fourth part of the thesis investigates the heavy-tailed behaviour of financial processes which may also possess long memory. We consider fractional stochastic differential equations driven by stable noise to model financial processes such as electricity prices. The long memory of electricity prices is represented by a fractional derivative, while the stable noise input models their non-Gaussianity via the tails of their probability density. A method using the empirical densities and MF-DFA will be provided to estimate all the parameters of the model and simulate sample paths of the equation. The method is then applied to analyse daily spot prices for five states of Australia. Comparison with the results obtained from the R/S analysis, periodogram method and MF-DFA are provided. The results from fractional SDEs agree with those from MF-DFA, which are based on multifractal scaling, while those from the periodograms, which are based on the second order, seem to underestimate the long memory dynamics of the process. This highlights the need and usefulness of fractal methods in modelling non-Gaussian financial processes with long memory.