908 resultados para Proficiency Rating
Resumo:
Fire resistance of load bearing Light Gauge Steel Frame (LSF) wall systems is important to protect lives and properties in fire accidents. Recent fire tests of LSF walls made of the new cold-formed and welded hollow flange channel (HFC) section studs and the commonly used lipped channel section (LCS) studs have shown the influence of stud sections on the fire resistance rating (FRR) of LSF walls. To advance the use of HFC section studs and to verify the outcomes from the fire tests, finite element models were developed to predict the structural fire performance of LSF walls made of welded HFC section studs. The developed models incorporated the measured non-uniform temperature distributions in LSF wall studs due to the exposure of standard fire on one side, and accurate elevated temperature mechanical properties of steel used in the stud sections. These models simulated the various complexities involved such as thermal bowing and neutral axis shift caused by the non-uniform temperature distribution in the studs. The finite element analysis (FEA) results agreed well with the full scale fire test results including the FRR, outer hot and cold flange temperatures at failure and axial deformation and lateral displacement profiles. They also confirmed the superior fire performance of LSF walls made of HFC section studs. The applicability of both transient and steady state FEA of LSF walls under fire conditions was verified in this study, which also investigated the effects of using various temperature distribution patterns across the cross-section of HFC section studs on the FRR of LSF walls. This paper presents the details of this numerical study and the results.
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Background The Palliative Care Problem Severity Score is a clinician-rated tool to assess problem severity in four palliative care domains (pain, other symptoms, psychological/spiritual, family/carer problems) using a 4-point categorical scale (absent, mild, moderate, severe). Aim To test the reliability and acceptability of the Palliative Care Problem Severity Score. Design: Multi-centre, cross-sectional study involving pairs of clinicians independently rating problem severity using the tool. Setting/participants Clinicians from 10 Australian palliative care services: 9 inpatient units and 1 mixed inpatient/community-based service. Results A total of 102 clinicians participated, with almost 600 paired assessments completed for each domain, involving 420 patients. A total of 91% of paired assessments were undertaken within 2 h. Strength of agreement for three of the four domains was moderate: pain (Kappa = 0.42, 95% confidence interval = 0.36 to 0.49); psychological/spiritual (Kappa = 0.48, 95% confidence interval = 0.42 to 0.54); family/carer (Kappa = 0.45, 95% confidence interval = 0.40 to 0.52). Strength of agreement for the remaining domain (other symptoms) was fair (Kappa = 0.38, 95% confidence interval = 0.32 to 0.45). Conclusion The Palliative Care Problem Severity Score is an acceptable measure, with moderate reliability across three domains. Variability in inter-rater reliability across sites and participant feedback indicate that ongoing education is required to ensure that clinicians understand the purpose of the tool and each of its domains. Raters familiar with the patient they were assessing found it easier to assign problem severity, but this did not improve inter-rater reliability.
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The export of sediments from coastal catchments can have detrimental impacts on estuaries and near shore reef ecosystems such as the Great Barrier Reef. Catchment management approaches aimed at reducing sediment loads require monitoring to evaluate their effectiveness in reducing loads over time. However, load estimation is not a trivial task due to the complex behaviour of constituents in natural streams, the variability of water flows and often a limited amount of data. Regression is commonly used for load estimation and provides a fundamental tool for trend estimation by standardising the other time specific covariates such as flow. This study investigates whether load estimates and resultant power to detect trends can be enhanced by (i) modelling the error structure so that temporal correlation can be better quantified, (ii) making use of predictive variables, and (iii) by identifying an efficient and feasible sampling strategy that may be used to reduce sampling error. To achieve this, we propose a new regression model that includes an innovative compounding errors model structure and uses two additional predictive variables (average discounted flow and turbidity). By combining this modelling approach with a new, regularly optimised, sampling strategy, which adds uniformity to the event sampling strategy, the predictive power was increased to 90%. Using the enhanced regression model proposed here, it was possible to detect a trend of 20% over 20 years. This result is in stark contrast to previous conclusions presented in the literature. (C) 2014 Elsevier B.V. All rights reserved.
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We consider the development of statistical models for prediction of constituent concentration of riverine pollutants, which is a key step in load estimation from frequent flow rate data and less frequently collected concentration data. We consider how to capture the impacts of past flow patterns via the average discounted flow (ADF) which discounts the past flux based on the time lapsed - more recent fluxes are given more weight. However, the effectiveness of ADF depends critically on the choice of the discount factor which reflects the unknown environmental cumulating process of the concentration compounds. We propose to choose the discount factor by maximizing the adjusted R-2 values or the Nash-Sutcliffe model efficiency coefficient. The R2 values are also adjusted to take account of the number of parameters in the model fit. The resulting optimal discount factor can be interpreted as a measure of constituent exhaustion rate during flood events. To evaluate the performance of the proposed regression estimators, we examine two different sampling scenarios by resampling fortnightly and opportunistically from two real daily datasets, which come from two United States Geological Survey (USGS) gaging stations located in Des Plaines River and Illinois River basin. The generalized rating-curve approach produces biased estimates of the total sediment loads by -30% to 83%, whereas the new approaches produce relatively much lower biases, ranging from -24% to 35%. This substantial improvement in the estimates of the total load is due to the fact that predictability of concentration is greatly improved by the additional predictors.
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We consider estimating the total load from frequent flow data but less frequent concentration data. There are numerous load estimation methods available, some of which are captured in various online tools. However, most estimators are subject to large biases statistically, and their associated uncertainties are often not reported. This makes interpretation difficult and the estimation of trends or determination of optimal sampling regimes impossible to assess. In this paper, we first propose two indices for measuring the extent of sampling bias, and then provide steps for obtaining reliable load estimates that minimizes the biases and makes use of informative predictive variables. The key step to this approach is in the development of an appropriate predictive model for concentration. This is achieved using a generalized rating-curve approach with additional predictors that capture unique features in the flow data, such as the concept of the first flush, the location of the event on the hydrograph (e.g. rise or fall) and the discounted flow. The latter may be thought of as a measure of constituent exhaustion occurring during flood events. Forming this additional information can significantly improve the predictability of concentration, and ultimately the precision with which the pollutant load is estimated. We also provide a measure of the standard error of the load estimate which incorporates model, spatial and/or temporal errors. This method also has the capacity to incorporate measurement error incurred through the sampling of flow. We illustrate this approach for two rivers delivering to the Great Barrier Reef, Queensland, Australia. One is a data set from the Burdekin River, and consists of the total suspended sediment (TSS) and nitrogen oxide (NO(x)) and gauged flow for 1997. The other dataset is from the Tully River, for the period of July 2000 to June 2008. For NO(x) Burdekin, the new estimates are very similar to the ratio estimates even when there is no relationship between the concentration and the flow. However, for the Tully dataset, by incorporating the additional predictive variables namely the discounted flow and flow phases (rising or recessing), we substantially improved the model fit, and thus the certainty with which the load is estimated.
Resumo:
There are numerous load estimation methods available, some of which are captured in various online tools. However, most estimators are subject to large biases statistically, and their associated uncertainties are often not reported. This makes interpretation difficult and the estimation of trends or determination of optimal sampling regimes impossible to assess. In this paper, we first propose two indices for measuring the extent of sampling bias, and then provide steps for obtaining reliable load estimates by minimizing the biases and making use of possible predictive variables. The load estimation procedure can be summarized by the following four steps: - (i) output the flow rates at regular time intervals (e.g. 10 minutes) using a time series model that captures all the peak flows; - (ii) output the predicted flow rates as in (i) at the concentration sampling times, if the corresponding flow rates are not collected; - (iii) establish a predictive model for the concentration data, which incorporates all possible predictor variables and output the predicted concentrations at the regular time intervals as in (i), and; - (iv) obtain the sum of all the products of the predicted flow and the predicted concentration over the regular time intervals to represent an estimate of the load. The key step to this approach is in the development of an appropriate predictive model for concentration. This is achieved using a generalized regression (rating-curve) approach with additional predictors that capture unique features in the flow data, namely the concept of the first flush, the location of the event on the hydrograph (e.g. rise or fall) and cumulative discounted flow. The latter may be thought of as a measure of constituent exhaustion occurring during flood events. The model also has the capacity to accommodate autocorrelation in model errors which are the result of intensive sampling during floods. Incorporating this additional information can significantly improve the predictability of concentration, and ultimately the precision with which the pollutant load is estimated. We also provide a measure of the standard error of the load estimate which incorporates model, spatial and/or temporal errors. This method also has the capacity to incorporate measurement error incurred through the sampling of flow. We illustrate this approach using the concentrations of total suspended sediment (TSS) and nitrogen oxide (NOx) and gauged flow data from the Burdekin River, a catchment delivering to the Great Barrier Reef. The sampling biases for NOx concentrations range from 2 to 10 times indicating severe biases. As we expect, the traditional average and extrapolation methods produce much higher estimates than those when bias in sampling is taken into account.
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Mapping and evaluating a student's progress on placement is a core element of social work education but there has been scant attention to indicate how to effectively create and assess student learning and performance. This paper outlines a project undertaken by the Combined Schools of Social Work to develop a common learning and assessment tool that is being used by all social work schools in Victoria. The paper describes how the Common Assessment Tool (CAT) was developed, drawing on the Australian Association of Social Work Practice Standards, leading to seven key learning areas that form the basis of the assessment of a student's readiness for practice. An evaluation of the usefulness of the CAT was completed by field educators, liaison staff, and students, which confirmed that the CAT was a useful framework for evaluating students' learning goals. The feedback also identified a number of problematic features that were addressed in a revised CAT and rating scale.
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English is currently ascendant as the language of globalisation, evident in its mediation of interactions and transactions worldwide. For many international students, completion of a degree in English means significant credentialing and increased job prospects. Australian universities are the third largest English-speaking destination for overseas students behind the United States and the United Kingdom. International students comprise one-fifth of the total Australian university population, with 80% coming from Asian countries (ABS, 2010). In this competitive higher education market, English has been identified as a valued ‘good’. Indeed, universities have been critiqued for relentlessly reproducing the “hegemony and homogeneity of English” (Marginson, 2006, p. 37) in order to sustain their advantage in the education market. For international students, English is the gatekeeper to enrolment, the medium of instruction and the mediator of academic success. For these reasons, English is not benign, yet it remains largely taken-for-granted in the mainstream university context. This paper problematises the naturalness of English and reports on a study of an Australian Master of Education course in which English was a focus. The study investigated representations of English as they were articulated across a chain of texts including the university strategic plan, course assessment criteria, student assignments, lecturer feedback, and interviews. Critical Discourse Analysis (CDA) and Foucault’s work on discourse enabled understandings of how a particular English is formed through an apparatus of specifications, exclusionary thresholds, strategies for maintenance (and disruption), and privileged concepts and speaking positions. The findings indicate that English has hegemonic status within the Australian university, with material consequences for students whose proficiency falls outside the thresholds of accepted English practice. Central to the constitution of what counts as English is the relationship of equivalence between standard written English and successful academic writing. International students’ representations of English indicate a discourse that impacts on identities and practices and preoccupies them considerably as they negotiate language and task demands. For the lecturer, there is strategic manoeuvring within the institutional regulative regime to support students’ English language needs using adapted assessment practices, explicit teaching of academic genres and scaffolded classroom interaction. The paper concludes with the implications for university teaching and learning.
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A 26-hour English reading comprehension course was taught to two groups of second year Finnish Pharmacy students: a virtual group (33 students) and a teacher-taught group (25 students). The aims of the teaching experiment were to find out: 1.What has to be taken into account when teaching English reading comprehension to students of pharmacy via the Internet and using TopClass? 2. How will the learning outcomes of the virtual group and the control group differ? 3. How will the students and the Department of Pharmacy respond to the different and new method, i.e. the virtual teaching method? 4. Will it be possible to test English reading comprehension learning material using the groupware tool TopClass? The virtual exercises were written within the Internet authoring environment, TopClass. The virtual group was given the reading material and grammar booklet on paper, but they did the reading comprehension tasks (written by the teacher), autonomously via the Internet. The control group was taught by the same teacher in 12 2-hour sessions, while the virtual group could work independently within the given six weeks. Both groups studied the same material: ten pharmaceutical articles with reading comprehension tasks as well as grammar and vocabulary exercises. Both groups took the same final test. Students in both groups were asked to evaluate the course using a 1 to 5 rating scale and they were also asked to assess their respective courses verbally. A detailed analysis of the different aspects of the student evaluation is given. Conclusions: 1.The virtual students learned pharmaceutical English relatively well but not significantly better than the classroom students 2. The overall student satisfaction in the virtual pharmacy English reading comprehension group was found to be higher than that in the teacher-taught control group. 3. Virtual learning is easier for linguistically more able students; less able students need more time with the teacher. 4. The sample in this study is rather small, but it is a pioneering study. 5. The Department of Pharmacy in the University of Helsinki wishes to incorporate virtual English reading comprehension teaching in its curriculum. 6. The sophisticated and versatile TopClass system is relatively easy for a traditional teacher and quite easy for the students to learn. It can be used e.g. for automatic checking of routine answers and document transfer, which both lighten the workloads of both parties. It is especially convenient for teaching reading comprehension. Key words: English reading comprehension, teacher-taught class, virtual class, attitudes of students, learning outcomes
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An adaptive conjoint analysis was use to evaluate stakeholders' opinion of welfare indicators for ship-transported sheep and cattle, both onboard and in pre-export depots. In consultations with two nominees of each identified stakeholder group (government officials, animal welfare representatives, animal scientists, stockpersons, producers/pre-export depot operators, exporters/ship owners and veterinarians), 18 potential indicators were identified Three levels were assigned to each using industry statistics and expert opinion, representing those observed on the best and worst 5% of voyages and an intermediate value. A computer-based questionnaire was completed by 135 stakeholders (48% of those invited). All indicators were ranked by respondents in the assigned order, except fodder intake, in which case providing the amount necessary to maintain bodyweight was rated better than over or underfeeding, and time in the pre-export assembly depot, in which case 5 days was rated better than 0 or 10 days. The respective Importance Values (a relative rating given by the respondent) for each indicator were, in order of declining importance: mortality (8.6%), clinical disease incidence (8.2%), respiration rate (6.8%), space allowance (6.2%), ammonia levels (6.1%), weight change (6.0%), wet bulb temperature (6.0%), time in assembly depot (5.4%), percentage of animals in hospital pen (5.4%), fodder intake (5.2%), stress-related metabolites (5.0%), percentage of feeding trough utilised (5.0%), injuries (4.8%), percentage of animals able to access food troughs at any one time (4.8%), percentage of animals lying down (4.7%), cortisol concentration (4.5Y.), noise (3.9y.), and photoperiod (3.4%). The different stakeholder groups were relatively consistent in their ranking of the indicators, with all groups nominating the some top two and at least five of the top seven indicators. Some of the top indicators, in particular mortality, disease incidence and temperature, are already recorded in the Australian industry, but the study identified potential new welfare indicators for exported livestock, such as space allowance and ammonia concentration, which could be used to improve welfare standards if validated by scientific data. The top indicators would also be useful worldwide for countries engaging in long distance sea transport of livestock.
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This project was a step forward in improving the voltage profile of traditional low voltage distribution networks with high photovoltaic generation or high peak demand. As a practical and economical solution, the developed methods use a Dynamic Voltage Restorer or DVR, which is a series voltage compensator, for continuous and communication-less power quality enhancement. The placement of DVR in the network is optimised in order to minimise its power rating and cost. In addition, new approaches were developed for grid synchronisation and control of DVR which are integrated with the voltage quality improvement algorithm for stable operation.
Resumo:
A switched DC voltage three level NPC is proposed in this paper to eliminate capacitor balancing problems in conventional three-level Neutral Point Clamped (NPC) inverter. The proposed configuration requires only one DC link with a voltage V-dc/2, where V-dc is the DC link voltage in a onventional NPC inverter. To get rated DC link voltage (V-dc), the voltage source is alternately onnected in parallel to one of the two series capacitors using two switches and two diodes with device voltage rating of V-dc/2. The frequency at which the voltage source is switched is independent and will not affect the operation of NPC inverter. The switched voltage source in this configuration balances the capacitors automatically. The proposed configuration can also be used as a conventional two level inverter in lower modulation range, thereby increases the reliability of the drive system. A space vector based PWM scheme is used to verify this proposed topology.
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- Introduction Research identifies truck drivers as being at high risk of chronic disease. For most truck drivers their workplace is their vehicle. Truck drivers’ health is impacted by the limitations of this unique working environment, including reduced opportunities for physical activity and the intake of healthy foods. Workplaces are widely recognised as effective platforms for health promotion. However, the effectiveness of traditional and contemporary health promotion interventions in truck drivers’ novel workplace is unknown. - Methods This project worked with six transport industry workplaces in Queensland, Australia over a two-year period. Researchers used Participatory Action Research (PAR) processes to engage truck drivers and workplace managers in the implementation and evaluation of six workplace health promotion interventions. These interventions were designed to support truck drivers to increase their physical activity and access to healthy foods at work. They included traditional health promotion interventions such as a free fruit initiative, a ten thousand steps challenge, personal health messages and workplace posters, and a contemporary social media intervention. Participants were engaged via focus groups, interviews and mixed-methods surveys. - Results The project achieved positive changes in truck drivers’ health knowledge and health behaviours, particularly related to nutrition. There were positive changes in truck drivers’ self-reported health rating, body mass index (BMI) and readiness to make health-related lifestyle changes. There were also positive changes in truck drivers reporting their workplace as a key source of health information. These changes were underpinned by a positive shift in the culture of participating workplaces. Truck drivers’ perceptions of their workplace valuing, encouraging, modelling and facilitating healthy nutrition and physical activity behaviours improved. PAR processes enabled researchers to develop relationships with workplace managers, contextualise interventions and deliver rigorous outcomes. Despite the novelty of truck drivers’ mobile workplace, traditional health promotion interventions were more effective than contemporary ones. - Conclusion In this workplace health promotion project targeting a ‘hard-to-reach’ group of truck drivers, a combination of well-designed traditional workplace interventions and the PAR process resulted in positive health outcomes.
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Internal browning disorders, including brown fleck (BF), in potato (Solanum tuberosum) tubers greatly reduce tuber quality, but the causes are not well understood. This is due, in part, to the highly variable data provided by visual value-based rating systems. A digital imaging technique was developed to quantify accurately the incidence of internal browning in potato tubers. Images of tuber sections were scanned using a flatbed scanner and digitally enhanced to highlight tuber BF lesions, and the area of affected tissue calculated using pixel quantification software. Digital imaging allowed for the determination of previously unused indices of the incidence and severity of internal browning in potato tubers. Statistical analysis of the comparison between digitally derived and visual-rating BF data from a glasshouse experiment showed that digital data greatly improved the delineation of treatment effects. The F-test probability was further improved through square root or logarithmic data transformations of the digital data, but not of the visual-rating data. Data from a field experiment showed that the area of tuber affected by BF and the number of small BF lesions increased with time and with increase in tuber size. The results from this study indicate that digital imaging of internal browning disorders of potato tubers holds much promise in determining their causes that heretofore have proved elusive.
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Approximately one-third of stroke patients experience depression. Stroke also has a profound effect on the lives of caregivers of stroke survivors. However, depression in this latter population has received little attention. In this study the objectives were to determine which factors are associated with and can be used to predict depression at different points in time after stroke; to compare different depression assessment methods among stroke patients; and to determine the prevalence, course and associated factors of depression among the caregivers of stroke patients. A total of 100 consecutive hospital-admitted patients no older than 70 years of age were followed for 18 months after having their first ischaemic stroke. Depression was assessed according to the Diagnostic and Statistical Manual of Mental Disorders (DSM-III-R), Beck Depression Inventory (BDI), Hamilton Rating Scale (HRSD), Visual Analogue Mood Scale (VAMS), Clinical Global Impression (CGI) and caregiver ratings. Neurological assessments and a comprehensive neuropsychological test battery were performed. Depression in caregivers was assessed by BDI. Depressive symptoms had early onsets in most cases. Mild depressive symptoms were often persistent with little change during the 18-month follow-up, although there was an increase in major depression over the same time interval. Stroke severity was associated with depression especially from 6 to 12 months post-stroke. At the acute phase, older patients were at higher risk of depression, and a higher proportion of men were depressed at 18 months post-stroke. Of the various depression assessment methods, none stood clearly apart from the others. The feasibility of each did not differ greatly, but prevalence rates differed widely according to the different criteria. When compared against DSM-III-R criteria, sensitivity and specificity were acceptable for the CGI, BDI, and HRSD. The CGI and BDI had better sensitivity than the more specific HRSD. The VAMS seemed not to be a reliable method for assessing depression among stroke patients. The caregivers often rated patients depression as more severe than did the patients themselves. Moreover, their ratings seemed to be influenced by their own depression. Of the caregivers, 30-33% were depressed. At the acute phase, caregiver depression was associated with the severity of the stroke and the older age of the patient. The best predictor of caregiver depression at later follow-up was caregiver depression at the acute phase. The results suggest that depression should be assessed during the early post-stroke period and that the follow-up of those at risk of poor emotional outcome should be extended beyond the first year post-stroke. Further, the assessment of well-being of the caregivers of stroke patients should be included as a part of a rehabilitation plan for stroke patients.