953 resultados para Ranking paradigms


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A cohort of 161 underground miners who had been highly exposed to dinitrotoluene (DNT) in the copper-mining industry of the former German Democratic Republic was reinvestigated for signs of subclinical renal damage. The study included a screening of urinary proteins excreted by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE), and quantitations of the specific urinary proteins α 1-microglobulin and glutathione-S-transferase α (GST α) as biomarkers for damage of the proximal tubule and glutathione-S-transferase π (GST π) for damage of the distal tubule. The exposures were categorized semiquantitatively (low, medium, high, and very high), according to the type and duration of professional contact with DNT. A straight dose-dependence of pathological protein excretion patterns with the semiquantitative ranking of DNT exposure was seen. Most of the previously reported cancer cases of the urinary tract, especially those in the higher exposed groups, were confined to pathological urinary protein excretion patterns. The damage from DNT was directed toward the tubular system. In many cases, the appearance of Tamm-Horsfall protein, a 105-kD protein marker, was noted. Data on the biomarkers α 1-microglobulin, GST α, and GST π consistently demonstrated a dose-dependent increase in tubular damage, which confirmed the results of screening by SDS-PAGE and clearly indicated a nephrotoxic effect of DNT under the given conditions of exposure. Within the cluster of cancer patients observed among the DNT-exposed workers, only in exceptional cases were normal biomarker excretions found.

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The kinetics of acid-catalyzed hydrolysis of seven methylated aliphatic epoxides - R1R2C(O)CR3R4 (A: R1=R2=R3=R4=H; B: R1=R2=R3=H, R4=Me; C: R1=R2=H, R3=R4=Me; D: R1=R3=H, R2=R4=Me(trans); E: R1=R3=H, R2=R4=Me(cis); F: R1=R3=R4=Me, R2=H; G: R1=R2=R3=R4=Me) - has been studied at 36 ± 1.5°C. Compounds with two methyl groups at the same carbon atom of the oxirane ring exhibit highest rate constants (k(eff) in reciprocal molar concentration per second: 11.0 ± 1.3 for C, 10.7 ± 2.1 for F, and 8.7 ± 0.7 for G as opposed to 0.124 ± 0.003 for B, 0.305 ± 0.003 for D, and 0.635 ± 0.036 for E). Ethylene oxide (A) displays the lowest rate of hydrolysis (0.027 M-1 s-1). The results are consistent with literature data available for compounds A, B, and C. To model the reactivities we have employed quantum chemical calculations (MNDO, AM1, PM3, and MINDO/3) of the main reaction species. There is a correlation of the logarithm k(eff) with the total energy of epoxide ring opening. The best correlation coefficients (r) were obtained using the AM1 and MNDO methods (0.966 and 0.957, respectively). However, unlike MNDO, AM1 predicts approximately zero energy barriers for the oxirane ring opening of compounds B, C, E and G, which is not consistent with published kinetic data. Thus, the MNDO method provides a preferential means of modeling the acidic hydrolysis of the series of methylated oxiranes. The general ranking of mutagenicity in vitro, A > B > C, is in line with the concept that this sequence also gradually leaves the expoxide reactivity optimal for genotoxicity toward reactivities leading to higher biological detoxifications.

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Competition for research funding is intense and the opinions of an expert peer reviewer can mean the difference between success and failure in securing funding. The allocation of expert peer reviewers is therefore vitally important and funding agencies strive to avoid using reviewers who have real or perceived conflicts of interest. This article examines the impact of including or excluding peer reviewers based on their conflicts of interest, and the final ranking of funding proposals. Two 7-person review panels assessed a sample of National Health and Medical Research Council (NHMRC) of Australia proposals in Basic Science or Public Health. Using a pre-post comparison, the proposals were first scored after the exclusion of reviewers with a high or medium conflict, and re-scored after the return of reviewers with medium conflicts. The main outcome measures are the agreements in ranks and funding success before and after excluding the medium conflicts. Including medium conflicts of interest had little impact on the ranks or funding success. The Bland–Altman 95% limits of agreement were ± 3.3 ranks and ± 3.4 ranks in the two panels which both assessed 36 proposals. Overall there were three proposals (4%) that had a reversed funding outcome after including medium conflicts. Relaxing the conflict of interest rules would increase the number of expert reviewers included in the panel discussions which could increase the quality of peer review and make it easier to find reviewers.

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Health service managers and policy makers are increasingly concerned about the sustainability of innovations implemented in health care settings. The increasing demand on health services requires that innovations are both effective and sustainable however research in this field is limited with multiple disciplines, approaches and paradigms influencing the field. These variations prevent a cohesive approach and therefore the accumulation of research findings in development of a body of knowledge. A theoretical framework serves to guide research, determine variables, influence data analysis and is central to the quest for ongoing knowledge development. If left unaddressed, health services research will continue in an ad hoc manner preventing full utilisation of outcomes, recommendations and knowledge for effective provision of health services. The purpose of this paper is to provide an integrative review of the literature and introduce a theoretical framework for health services innovation sustainability research based on integration and synthesis of the literature. Finally recommendations for operationalising and testing this theory will be presented.

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This research falls in the area of enhancing the quality of tag-based item recommendation systems. It aims to achieve this by employing a multi-dimensional user profile approach and by analyzing the semantic aspects of tags. Tag-based recommender systems have two characteristics that need to be carefully studied in order to build a reliable system. Firstly, the multi-dimensional correlation, called as tag assignment , should be appropriately modelled in order to create the user profiles [1]. Secondly, the semantics behind the tags should be considered properly as the flexibility with their design can cause semantic problems such as synonymy and polysemy [2]. This research proposes to address these two challenges for building a tag-based item recommendation system by employing tensor modeling as the multi-dimensional user profile approach, and the topic model as the semantic analysis approach. The first objective is to optimize the tensor model reconstruction and to improve the model performance in generating quality rec-ommendation. A novel Tensor-based Recommendation using Probabilistic Ranking (TRPR) method [3] has been developed. Results show this method to be scalable for large datasets and outperforming the benchmarking methods in terms of accuracy. The memory efficient loop implements the n-mode block-striped (matrix) product for tensor reconstruction as an approximation of the initial tensor. The probabilistic ranking calculates the probabil-ity of users to select candidate items using their tag preference list based on the entries generated from the reconstructed tensor. The second objective is to analyse the tag semantics and utilize the outcome in building the tensor model. This research proposes to investigate the problem using topic model approach to keep the tags nature as the “social vocabulary” [4]. For the tag assignment data, topics can be generated from the occurrences of tags given for an item. However there is only limited amount of tags availa-ble to represent items as collection of topics, since an item might have only been tagged by using several tags. Consequently, the generated topics might not able to represent the items appropriately. Furthermore, given that each tag can belong to any topics with various probability scores, the occurrence of tags cannot simply be mapped by the topics to build the tensor model. A standard weighting technique will not appropriately calculate the value of tagging activity since it will define the context of an item using a tag instead of a topic.

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Despite major inroads in demystifying creativity for the non-design disciplines, there has been little movement in the design disciplines themselves beyond traditional paradigms. This is particularly noticeable in design education where traditional pedagogical approaches persist despite the emergence of new experimental pedagogies. In response, this research aims to explore what a pedagogy of desire can offer and what this means in terms of curriculum development; learning environments; teaching approaches and staff development. Specifically, it seeks to: understand more fully the notion of desire and how students’ and teachers’ desires can be exploited in creative and productive ways; to further explore the relationship between risk (through experiencing uncertainties and anxieties) and pleasure (through assuming the subversive position of knowing); to identify and explore how to negotiate personal, professional and organisational implications; and to develop appropriate evaluation mechanisms.

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Mobile robots and animals alike must effectively navigate their environments in order to achieve their goals. For animals goal-directed navigation facilitates finding food, seeking shelter or migration; similarly robots perform goal-directed navigation to find a charging station, get out of the rain or guide a person to a destination. This similarity in tasks extends to the environment as well; increasingly, mobile robots are operating in the same underwater, ground and aerial environments that animals do. Yet despite these similarities, goal-directed navigation research in robotics and biology has proceeded largely in parallel, linked only by a small amount of interdisciplinary research spanning both areas. Most state-of-the-art robotic navigation systems employ a range of sensors, world representations and navigation algorithms that seem far removed from what we know of how animals navigate; their navigation systems are shaped by key principles of navigation in ‘real-world’ environments including dealing with uncertainty in sensing, landmark observation and world modelling. By contrast, biomimetic animal navigation models produce plausible animal navigation behaviour in a range of laboratory experimental navigation paradigms, typically without addressing many of these robotic navigation principles. In this paper, we attempt to link robotics and biology by reviewing the current state of the art in conventional and biomimetic goal-directed navigation models, focusing on the key principles of goal-oriented robotic navigation and the extent to which these principles have been adapted by biomimetic navigation models and why.

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Conservation decision tools based on cost-effectiveness analysis are used to assess threat management strategies for improving species persistence. These approaches rank alternative strategies by their benefit to cost ratio but may fail to identify the optimal sets of strategies to implement under limited budgets because they do not account for redundancies. We devised a multi objective optimization approach in which the complementarity principle is applied to identify the sets of threat management strategies that protect the most species for any budget. We used our approach to prioritize threat management strategies for 53 species of conservation concern in the Pilbara, Australia. We followed a structured elicitation approach to collect information on the benefits and costs of implementing 17 different conservation strategies during a 3-day workshop with 49 stakeholders and experts in the biodiversity, conservation, and management of the Pilbara. We compared the performance of our complementarity priority threat management approach with a current cost-effectiveness ranking approach. A complementary set of 3 strategies: domestic herbivore management, fire management and research, and sanctuaries provided all species with >50% chance of persistence for $4.7 million/year over 20 years. Achieving the same result cost almost twice as much ($9.71 million/year) when strategies were selected by their cost-effectiveness ranks alone. Our results show that complementarity of management benefits has the potential to double the impact of priority threat management approaches.

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Heterogeneous health data is a critical issue when managing health information for quality decision making processes. In this paper we examine the efficient aggregation of lifestyle information through a data warehousing architecture lens. We present a proof of concept for a clinical data warehouse architecture that enables evidence based decision making processes by integrating and organising disparate data silos in support of healthcare services improvement paradigms.

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Discovering the means to prevent and cure schizophrenia is a vision that motivates many scientists. But in order to achieve this goal, we need to understand its neurobiological basis. The emergent metadiscipline of cognitive neuroscience fields an impressive array of tools that can be marshaled towards achieving this goal, including powerful new methods of imaging the brain (both structural and functional) as well as assessments of perceptual and cognitive capacities based on psychophysical procedures, experimental tasks and models developed by cognitive science. We believe that the integration of data from this array of tools offers the greatest possibilities and potential for advancing understanding of the neural basis of not only normal cognition but also the cognitive impairments that are fundamental to schizophrenia. Since sufficient expertise in the application of these tools and methods rarely reside in a single individual, or even a single laboratory, collaboration is a key element in this endeavor. Here, we review some of the products of our integrative efforts in collaboration with our colleagues on the East Coast of Australia and Pacific Rim. This research focuses on the neural basis of executive function deficits and impairments in early auditory processing in patients using various combinations of performance indices (from perceptual and cognitive paradigms), ERPs, fMRI and sMRI. In each case, integration of two or more sources of information provides more information than any one source alone by revealing new insights into structure-function relationships. Furthermore, the addition of other imaging methodologies (such as DTI) and approaches (such as computational models of cognition) offers new horizons in human brain imaging research and in understanding human behavior.

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For some time now, there has been a focus, both in Australia and internationally, on quality teaching as a fundamental component that affects the educational outcomes of all students. The question of how teacher education programs in Australia prepare effective teachers to work across all school settings-including low-SES schools-has been elevated to national prominence by data from the 20 12 Programme for International Student Assessment (PIS A), which revealed a fall in Australian students' world ranking across Mathematics, Reading and Science. Education is commonly acknowledged as a "foundation capability" that improves a person's life chances, including employment prospects, and it is widely understood to be a "route out of disadvantage" (McLachlan, Gilfillan, and Gordon 20 13). The Australian Bureau of Statistics 201 1- 12 data suggest that around 2.6 million (11.8%) Australians currently live under the poverty line (Phillips et a!. 2012, 8). According to the Organisation for Economic Cooperation and Development (OECD), despite the significant effects teachers have on student performance, disadvantaged schools are not always staffed with the highest quality teachers (see Darling-Hammond, 2006).

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BACKGROUND As engineering schools adopt outcomes - focused learning approaches in response to government expectations and industry requirements of graduates capable of learning and applying knowledge in different contexts, university academics must be capable of developing and delivering programs that meet these requirements. Those academics are increasingly facing challenges in progressing their research and also acquiring different skill sets to meet the learning and teaching requirements. PURPOSE The goal of this study was to identify the types of development and support structures in place for academic staff, especially early career ones, and examine how the type of institution and the rank or role of the staff member affects these structures. DESIGN/METHOD We conducted semi - structured interviews with 21 individuals in a range of positions pertaining to teaching and learning in engineering education. Open coding was used to identify main themes from the guiding questions raised in the interviews and refined to address themes relevant to the development of institutional staff . The interview data was then analysed based on the type of institution and the rank/ role of the participant. RESULTS While development programs that focus on improving teaching and learning are available, the approach on using these types of programs differed based on staff perspective. Fewer academics, regardless of rank/role, had knowledge of support structures related to other areas of scholarship, e.g. disciplinary research, educational research, learning the institutional culture. The type of institution also impacted how they weighted and encouraged multiple forms of scholarship. We found that academic staff holding higher ranking positions, e.g. dean or associate dean, were not only concerned with the success of their respective programs, but also in how to promote other academic staff participation throughout the process. CONCLUSIONS The findings from this stud y extend the premise that developing effective academic staff ultimately leads to more effective institutions and successful graduates and accomplishing this requires staff buy - in at multiple stages of instructional and program development. Staff and administration developing approaches for educational innovation together (Besterfield - Sacre et al., 2014) and getting buy - in from all academic staff to invest in engineering education development will ultimately lead to more successful engineering graduates.

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For people with cognitive disabilities, technology is more often thought of as a support mechanism, rather than a source of division that may require intervention to equalize access across the cognitive spectrum. This paper presents a first attempt at formalizing the digital gap created by the generalization of search engines. This was achieved through the development of a mapping of cognitive abilities required by users to execute low- level tasks during a standard Web search task. The mapping demonstrates how critical these abilities are to successfully use search engines with an adequate level of independence. It will lead to a set of design guidelines for search engine interfaces that will allow for the engagement of users of all abilities, and also, more importantly, in search algorithms such as query suggestion and measure of relevance (i.e. ranking).

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Background Cardiovascular disease and mental health both hold enormous public health importance, both ranking highly in results of the recent Global Burden of Disease Study 2010 (GBD 2010). For the first time, the GBD 2010 has systematically and quantitatively assessed major depression as an independent risk factor for the development of ischemic heart disease (IHD) using comparative risk assessment methodology. Methods A pooled relative risk (RR) was calculated from studies identified through a systematic review with strict inclusion criteria designed to provide evidence of independent risk factor status. Accepted case definitions of depression include diagnosis by a clinician or by non-clinician raters adhering to Diagnostic and Statistical Manual of Mental Disorders (DSM) or International Classification of Diseases (ICD) classifications. We therefore refer to the exposure in this paper as major depression as opposed to the DSM-IV category of major depressive disorder (MDD). The population attributable fraction (PAF) was calculated using the pooled RR estimate. Attributable burden was calculated by multiplying the PAF by the underlying burden of IHD estimated as part of GBD 2010. Results The pooled relative risk of developing IHD in those with major depression was 1.56 (95% CI 1.30 to 1.87). Globally there were almost 4 million estimated IHD disability-adjusted life years (DALYs), which can be attributed to major depression in 2010; 3.5 million years of life lost and 250,000 years of life lived with a disability. These findings highlight a previously underestimated mortality component of the burden of major depression. As a proportion of overall IHD burden, 2.95% (95% CI 1.48 to 4.46%) of IHD DALYs were estimated to be attributable to MDD in 2010. Eastern Europe and North Africa/Middle East demonstrate the highest proportion with Asia Pacific, high income representing the lowest. Conclusions The present work comprises the most robust systematic review of its kind to date. The key finding that major depression may be responsible for approximately 3% of global IHD DALYs warrants assessment for depression in patients at high risk of developing IHD or at risk of a repeat IHD event.

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Background The Global Burden of Disease Study 2010 (GBD 2010) identified mental and substance use disorders as the 5th leading contributor of burden in 2010, measured by disability adjusted life years (DALYs). This estimate was incomplete as it excluded burden resulting from the increased risk of suicide captured elsewhere in GBD 2010's mutually exclusive list of diseases and injuries. Here, we estimate suicide DALYs attributable to mental and substance use disorders. Methods Relative-risk estimates of suicide due to mental and substance use disorders and the global prevalence of each disorder were used to estimate population attributable fractions. These were adjusted for global differences in the proportion of suicide due to mental and substance use disorders compared to other causes then multiplied by suicide DALYs reported in GBD 2010 to estimate attributable DALYs (with 95% uncertainty). Results Mental and substance use disorders were responsible for 22.5 million (14.8-29.8 million) of the 36.2 million (26.5-44.3 million) DALYs allocated to suicide in 2010. Depression was responsible for the largest proportion of suicide DALYs (46.1% (28.0%-60.8%)) and anorexia nervosa the lowest (0.2% (0.02%-0.5%)). DALYs occurred throughout the lifespan, with the largest proportion found in Eastern Europe and Asia, and males aged 20-30 years. The inclusion of attributable suicide DALYs would have increased the overall burden of mental and substance use disorders (assigned to them in GBD 2010 as a direct cause) from 7.4% (6.2%-8.6%) to 8.3% (7.1%-9.6%) of global DALYs, and would have changed the global ranking from 5th to 3rd leading cause of burden. Conclusions Capturing the suicide burden attributable to mental and substance use disorders allows for more accurate estimates of burden. More consideration needs to be given to interventions targeted to populations with, or at risk for, mental and substance use disorders as an effective strategy for suicide prevention.