983 resultados para DBHF approach


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Structural fire safety has become one of the key considerations in the design and maintenance of the built infrastructure. Conventionally the fire resistance rating of load bearing Light gauge Steel Frame (LSF) walls is determined based on the standard time-temperature curve given in ISO 834. Recent research has shown that the true fire resistance of building elements exposed to building fires can be less than their fire resistance ratings determined based on standard fire tests. It is questionable whether the standard time-temperature curve truly represents the fuel loads in modern buildings. Therefore an equivalent fire severity approach has been used in the past to obtain fire resistance rating. This is based on the performance of a structural member exposed to a realistic design fire curve in comparison to that of standard fire time-temperature curve. This paper presents the details of research undertaken to develop an energy based time equivalent approach to obtain the fire resistance ratings of LSF walls exposed to realistic design fire curves with respect to standard fire exposure. This approach relates to the amount of energy transferred to the member. The proposed method was used to predict the fire resistance ratings of single and double layer plasterboard lined and externally insulated LSF walls. The predicted fire ratings were compared with the results from finite element analyses and fire design rules for three different wall configurations exposed to both rapid and prolonged fires. The comparison shows that the proposed energy method can be used to obtain the fire resistance ratings of LSF walls in the case of prolonged fires.

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This paper analyzes the application of rights-based approaches to disaster displacement in the Asia-Pacific region in order to assess whether the current framework is sufficient to protect the rights of internally displaced persons. It identifies that disaster-induced displacement is increasingly prevalent in the region and that economic and social conditions in many countries mean that the impact of displacement is often prolonged and more severe. The paper identifies the relevant human rights principles which apply in the context of disaster-induced displacement and examines their implementation in a number of soft-law instruments. While it identifies shortcomings in impementation and enforcement, the paper concludes that a rights-based approach could be enhanced by greater engagement with existing human rights treaties and greater implementation of soft-law principles, and that no new instrument is required.

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High-stakes testing has become an important element of the Australian educational landscape. As one part of the neo-liberal paradigm where beliefs in the individual and the free market are paramount, it is of concern how school leaders can respond to this phenomenon in an ethical manner. Ethics and ethical leadership have increased in prominence both in the educational administration literature and in the media (Cranston, Ehrich, & Kimber, 2006). In this paper we consider ethical theories on which school principals can draw, not only in the leadership of their own schools but in their relationships with other schools. We provide an example of a school leader sharing a successful intervention with other schools, illustrating that school leaders can create spaces for promoting the public good within the context of high-stakes testing.

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Access to transport systems and the connection to such systems provided to essential economic and social activities are critical to determine households' transportation disadvantage levels. In spite of the developments in better identifying transportation disadvantaged groups, the lack of effective policies resulted in the continuum of the issue as a significant problem. This paper undertakes a pilot case investigation as test bed for a new approach developed to reduce transportation policy shortcomings. The approach, ‘disadvantage-impedance index’, aims to ease transportation disadvantages by employing representative parameters to measure the differences between policy alternatives run in a simulation environment. Implemented in the Japanese town of Arao, the index uses trip-making behaviour and resident stated preference data. The results of the index reveal that even a slight improvement in accessibility and travel quality indicators makes a significant difference in easing disadvantages. The index, integrated into a four-step model, proves to be highly robust and useful in terms of quick diagnosis in capturing effective actions, and developing potentially efficient policies.

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This study examined the effect of an educational intervention utilizing principles of cognitive apprenticeship on students’ ability to apply clinical reasoning skills within the context of a purpose-built clinical vignette. A quasi-experimental, non-equivalent control-group design was used to evaluate the effect of the educational intervention on students’ accuracy, inaccuracy and self-confidence in clinical reasoning. This study makes an important contribution to nursing education by providing evidence to understand how best to facilitate nursing students’ development of clinical reasoning.

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Throughout history, communities and civilizations have sought to enhance the quality of community life and the well-being of its people. However, more recently there has been greater interest in attending to the details of community development by capitalizing on the improved ability to capture community well-being and successes scientifically. That interest invites greater attention to the development of indicators that can quantify those qualities of life that lead to strong and healthy communities. The selection of meaningful indicators is dependent upon several factors including a process that stimulates meaningful involvement of community stakeholders, but the single most important is the identification of an underlying model to guide the work. Indicators do not have meaning in themselves. For these measures to provide a coherent assessment of the community, an integrative approach to understanding what constitutes a healthy and strong community in a dynamic environment is required. A resilience perspective serves that purpose and provides a framework that is broad, neutral, and conceptually strong enough to structure development of significant sets of indicators. Exemplary community indicator processes across the nation, particularly recent efforts in the Phoenix, Arizona region, provide evidence supporting the value of indicator development for community building.

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We know from anecdote and research, science and art, that human resilience is a powerful, seemingly ubiquitous force. What is needed is a better understanding of the properties, variations, and applications of that concept to health and well-being. In this paper we put forth two definitions of resilience: Sustainability of purpose in the face of stress, and recovery from adversity. We review current thinking in the social sciences on the nature of biological, psychological and socio-community processes that may confer resilience. In doing so, we encourage greater attention to aspects of biopsychosocial resourcefulness as a dimension of influence on health and mental health distinct from measures of risk found in standard models of public health inquiry. Multi-level, longitudinal, and intervention methods are advocated for research and applications of the concept with conceptual guidelines for the examination of laboratory, diary, and community indicator data on manifestations of resilience across the life span.

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This paper reports on the results of a project aimed at creating a research-informed, pedagogically reliable, technology-enhanced learning and teaching environment that would foster engagement with learning. A first-year mathematics for engineering unit offered at a large, metropolitan Australian university provides the context for this research. As part of the project, the unit was redesigned using a framework that employed flexible, modular, connected e-learning and teaching experiences. The researchers, interested in an ecological perspective on educational processes, grounded the redesign principles in probabilistic learning design (Kirschner et al., 2004). The effectiveness of the redesigned environment was assessed through the lens of the notion of affordance (Gibson, 1977,1979, Greeno, 1994, Good, 2007). A qualitative analysis of the questionnaire distributed to students at the end of the teaching period provided insight into factors impacting on the successful creation of an environment that encourages complex, multidimensional and multilayered interactions conducive to learning.

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Background: Changing perspectives on the natural history of celiac disease (CD), new serology and genetic tests, and amended histological criteria for diagnosis cast doubt on past prevalence estimates for CD. We set out to establish a more accurate prevalence estimate for CD using a novel serogenetic approach.Methods: The human leukocyte antigen (HLA)-DQ genotype was determined in 356 patients with 'biopsy-confirmed' CD, and in two age-stratified, randomly selected community cohorts of 1,390 women and 1,158 men. Sera were screened for CD-specific serology.Results: Only five 'biopsy-confirmed' patients with CD did not possess the susceptibility alleles HLA-DQ2.5, DQ8, or DQ2.2, and four of these were misdiagnoses. HLA-DQ2.5, DQ8, or DQ2.2 was present in 56% of all women and men in the community cohorts. Transglutaminase (TG)-2 IgA and composite TG2/deamidated gliadin peptide (DGP) IgA/IgG were abnormal in 4.6% and 5.6%, respectively, of the community women and 6.9% and 6.9%, respectively, of the community men, but in the screen-positive group, only 71% and 75%, respectively, of women and 65% and 63%, respectively, of men possessed HLA-DQ2.5, DQ8, or DQ2.2. Medical review was possible for 41% of seropositive women and 50% of seropositive men, and led to biopsy-confirmed CD in 10 women (0.7%) and 6 men (0.5%), but based on relative risk for HLA-DQ2.5, DQ8, or DQ2.2 in all TG2 IgA or TG2/DGP IgA/IgG screen-positive subjects, CD affected 1.3% or 1.9%, respectively, of females and 1.3% or 1.2%, respectively, of men. Serogenetic data from these community cohorts indicated that testing screen positives for HLA-DQ, or carrying out HLA-DQ and further serology, could have reduced unnecessary gastroscopies due to false-positive serology by at least 40% and by over 70%, respectively.Conclusions: Screening with TG2 IgA serology and requiring biopsy confirmation caused the community prevalence of CD to be substantially underestimated. Testing for HLA-DQ genes and confirmatory serology could reduce the numbers of unnecessary gastroscopies. © 2013 Anderson et al.; licensee BioMed Central Ltd.

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Large Display Arrays (LDAs) use Light Emitting Diodes (LEDs) in order to inform a viewing audience. A matrix of individually driven LEDs allows the area represented to display text, images and video. LDAs have undergone rapid development over the past 10 years in both the modular and semi-flexible formats. This thesis critically analyses the communication architecture and processor functionality of current LDAs and presents an alternative method, that is, Scalable Flexible Large Display Arrays (SFLDAs). SFLDAs are more adaptable to a variety of applications because of enhancements in scalability and flexibility. Scalability is the ability to configure SFLDAs from 0.8m2 to 200m2. Flexibility is increased functionality within the processors to handle changes in configuration and the use of a communication architecture that standardises two-way communication throughout the SFLDA. While common video platforms such as Digital Video Interface (DVI), Serial Digital Interface (SDI), and High Definition Multimedia Interface (HDMI) are considered as solutions for the communication architecture of SFLDAs, so too is modulation, fibre optic, capacitive coupling and Ethernet. From an analysis of these architectures, Ethernet was identified as the best solution. The use of Ethernet as the communication architecture in SFLDAs means that both hardware and software modules are capable of interfacing to the SFLDAs. The Video to Ethernet Processor Unit (VEPU), Scoreboard, Image and Control Software (SICS) and Ethernet to LED Processor Unit (ELPU) have been developed to form the key components in designing and implementing the first SFLDA. Data throughput rate and spectrophotometer tests were used to measure the effectiveness of Ethernet within the SFLDA constructs. The result of testing and analysis of these architectures showed that Ethernet satisfactorily met the requirements of SFLDAs.

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Big Datasets are endemic, but they are often notoriously difficult to analyse because of their size, heterogeneity, history and quality. The purpose of this paper is to open a discourse on the use of modern experimental design methods to analyse Big Data in order to answer particular questions of interest. By appealing to a range of examples, it is suggested that this perspective on Big Data modelling and analysis has wide generality and advantageous inferential and computational properties. In particular, the principled experimental design approach is shown to provide a flexible framework for analysis that, for certain classes of objectives and utility functions, delivers near equivalent answers compared with analyses of the full dataset under a controlled error rate. It can also provide a formalised method for iterative parameter estimation, model checking, identification of data gaps and evaluation of data quality. Finally, it has the potential to add value to other Big Data sampling algorithms, in particular divide-and-conquer strategies, by determining efficient sub-samples.

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Background We have previously demonstrated that circulating NT-proBNP is truncated at the N and C termini. Aims of this study are three-fold: firstly to determine whether the NT-proBNP levels correlate with NYHA functional classes when measuring with different antibody pairs; secondly to evaluate the diagnostic potential of ProBNP and; thirdly to investigate whether combining NT-proBNP assays with or without ProBNP would lead to better diagnostic accuracies. Methods Plasma samples were collected from healthy controls (n = 52) and HF patients (n = 46). Customized AlphaLISA® immunoassays were developed and validated to measure the concentrations of proBNP and NT-proBNP (with antibodies targeting 13–45, 13–76, 28–76). The diagnostic performance and predictive value of proBNP and NT-proBNP assays and their combinations were evaluated. Results Plasma proBNP assay showed acceptable diagnostic performance. NT-proBNP13–76 assay is useful in diagnosing and stratifying HF patients. The diagnostic performance of NT-proBNP13–76 demonstrated improvement over commercial NT-proBNP tests. The combination of NT-proBNP13–76 with NT-proBNP28–76 assays gave the best diagnostic assay performance. Conclusion Our results demonstrate that while there is major heterogeneity in circulating NT-proBNP, specific epitopes of the peptides are extraordinarily stable, providing ideal targets for clinically useful diagnostic assays. Future new clinical diagnostic clinical trials should include a multimarker approach rather than using a single marker to diagnose HF.

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Agility is an essential part of many athletic activities. Currently, agility drill duration is the sole criterion used for evaluation of agility performance. The relationship between drill duration and factors such as acceleration, deceleration and change of direction, however, has not been fully explored. This paper provides a mathematical description of the relationship between velocity and radius of curvatures in an agility drill through implementation of a power law (PL). Two groups of skilled and unskilled participants performed a cyclic forward/backward shuttle agility test. Kinematic data was recorded using motion capture system at a sampling rate of 200 Hz. The logarithmic relationship between tangential velocity and radius of curvature of participant trajectories in both groups was established using the PL. The slope of the regression line was found to be 0.26 and 0.36, for the skilled and unskilled groups, respectively. The magnitudes of regression line slope for both groups were approximately 0.3 which is close to the expected 1/3 value. Results are an indication of how the PL could be implemented in an agility drill thus opening the way for establishment of a more representative measure of agility performance instead of drill duration.

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Introduction The Skin Self-Examination Attitude Scale (SSEAS) is a brief measure that allows for the assessment of attitudes in relation to skin self-examination. This study evaluated the psychometric properties of the SSEAS using Item Response Theory (IRT) methods in a large sample of men ≥ 50 years in Queensland, Australia. Methods A sample of 831 men (420 intervention and 411 control) completed a telephone assessment at the 13-month follow-up of a randomized-controlled trial of a video-based intervention to improve skin self-examination (SSE) behaviour. Descriptive statistics (mean, standard deviation, item–total correlations, and Cronbach’s alpha) were compiled and difficulty parameters were computed with Winsteps using the polytomous Rasch Rating Scale Model (RRSM). An item person (Wright) map of the SSEAS was examined for content coverage and item targeting. Results The SSEAS have good psychometric properties including good internal consistency (Cronbach’s alpha = 0.80), fit with the model and no evidence for differential item functioning (DIF) due to experimental trial grouping was detected. Conclusions The present study confirms the SSEA scale as a brief, useful and reliable tool for assessing attitudes towards skin self-examination in a population of men 50 years or older in Queensland, Australia. The 8-item scale shows unidimensionality, allowing levels of SSE attitude, and the item difficulties, to be ranked on a single continuous scale. In terms of clinical practice, it is very important to assess skin cancer self-examination attitude to identify people who may need a more extensive intervention to allow early detection of skin cancer.

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Rolling-element bearing failures are the most frequent problems in rotating machinery, which can be catastrophic and cause major downtime. Hence, providing advance failure warning and precise fault detection in such components are pivotal and cost-effective. The vast majority of past research has focused on signal processing and spectral analysis for fault diagnostics in rotating components. In this study, a data mining approach using a machine learning technique called anomaly detection (AD) is presented. This method employs classification techniques to discriminate between defect examples. Two features, kurtosis and Non-Gaussianity Score (NGS), are extracted to develop anomaly detection algorithms. The performance of the developed algorithms was examined through real data from a test to failure bearing. Finally, the application of anomaly detection is compared with one of the popular methods called Support Vector Machine (SVM) to investigate the sensitivity and accuracy of this approach and its ability to detect the anomalies in early stages.