990 resultados para 159-962
Resumo:
The Hauraki Gulf is a large, shallow embayment located north of Auckland City (36°51′S, 174°46′E), New Zealand. Bryde's whales (Balaenoptera edeni) are the most frequently observed balaenopterid in these waters. To assess the use of the Hauraki Gulf for this species, we examined the occurrence and distribution in relation to environmental parameters. Data were collected from a platform of opportunity during 674 daily surveys between March 2003 and February 2006. A total of 760 observations of Bryde's whales were recorded throughout the study period during 371 surveys. The number of Bryde's whales sighted/day was highest in winter, coinciding with the coolest median sea-surface temperature (14.6°C). Bryde's whales were recorded throughout the Hauraki Gulf in water depths ranging from 12.1–59.8 m (mean = 42.3, SD = 5.1). Cow–calf pairs were most frequently observed during the austral autumn in water depths of 29.9–53.9 m (mean = 40.8, SD = 5.2). Data from this study suggest Bryde's whales in the Hauraki Gulf exhibit a mix of both “inshore” and “offshore” characteristics from the Bryde's whales examined off the coast of South Africa. Based on complete mitochondrial DNA sequences, Sasaki et al. (2006) recognized two sister species of Bryde's whales: Balaenoptera brydei and B. edeni, with the latter including small-type, more coastal Bryde's whales from Japan, Hong Kong, and Australia. Their samples and samples in previous analyses of small-type whales, all originated from eastern and southeastern Asia. These authors did not include the forms of Bryde's whales that occur in other regions, e.g., in the Pacific off Peru (Valdivia et al. 1981), in the Atlantic off Brazil (Best 1977) and in the western Indian Ocean off South Africa (Best 1977). Recent genetic analysis using mtDNA from the “inshore” and “offshore” forms from South Africa confirms the offshore form is B. brydei, and establishes that the inshore form is more closely related to B. brydei than to B. edeni (Penry 2010). These different forms do vary considerably in their habitat use and ecology (refer to Table 1 for a detailed comparison between the South African inshore and offshore forms, as described by Best (1967, 1977) and the Bryde's whales from New Zealand (Wiseman 2008). Recent genetic analysis on the Bryde's whales in the Hauraki Gulf suggests they are B. brydei (Wiseman 2008). However, pending resolution of the uncertainty within and between species of this genus, we follow the Society of Marine Mammal's committee on taxonomy, who state that B. edeni applies to all Bryde's whales.
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We present a systematic, practical approach to developing risk prediction systems, suitable for use with large databases of medical information. An important part of this approach is a novel feature selection algorithm which uses the area under the receiver operating characteristic (ROC) curve to measure the expected discriminative power of different sets of predictor variables. We describe this algorithm and use it to select variables to predict risk of a specific adverse pregnancy outcome: failure to progress in labour. Neural network, logistic regression and hierarchical Bayesian risk prediction models are constructed, all of which achieve close to the limit of performance attainable on this prediction task. We show that better prediction performance requires more discriminative clinical information rather than improved modelling techniques. It is also shown that better diagnostic criteria in clinical records would greatly assist the development of systems to predict risk in pregnancy. We present a systematic, practical approach to developing risk prediction systems, suitable for use with large databases of medical information. An important part of this approach is a novel feature selection algorithm which uses the area under the receiver operating characteristic (ROC) curve to measure the expected discriminative power of different sets of predictor variables. We describe this algorithm and use it to select variables to predict risk of a specific adverse pregnancy outcome: failure to progress in labour. Neural network, logistic regression and hierarchical Bayesian risk prediction models are constructed, all of which achieve close to the limit of performance attainable on this prediction task. We show that better prediction performance requires more discriminative clinical information rather than improved modelling techniques. It is also shown that better diagnostic criteria in clinical records would greatly assist the development of systems to predict risk in pregnancy.
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Speech recognition in car environments has been identified as a valuable means for reducing driver distraction when operating noncritical in-car systems. Under such conditions, however, speech recognition accuracy degrades significantly, and techniques such as speech enhancement are required to improve these accuracies. Likelihood-maximizing (LIMA) frameworks optimize speech enhancement algorithms based on recognized state sequences rather than traditional signal-level criteria such as maximizing signal-to-noise ratio. LIMA frameworks typically require calibration utterances to generate optimized enhancement parameters that are used for all subsequent utterances. Under such a scheme, suboptimal recognition performance occurs in noise conditions that are significantly different from that present during the calibration session – a serious problem in rapidly changing noise environments out on the open road. In this chapter, we propose a dialog-based design that allows regular optimization iterations in order to track the ever-changing noise conditions. Experiments using Mel-filterbank noise subtraction (MFNS) are performed to determine the optimization requirements for vehicular environments and show that minimal optimization is required to improve speech recognition, avoid over-optimization, and ultimately assist with semireal-time operation. It is also shown that the proposed design is able to provide improved recognition performance over frameworks incorporating a calibration session only.
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The 2nd International Digital Human Modeling (DHM) Symposium was held at the renowned University of Michigan Transportation Research Institute (UMTRI) in Ann Arbor, Michigan in June 11–13, 2013. The symposium was co-organised by the UMTRI and Penn State University, and endorsed by the IEA Technical Committee on Human Simulation and Virtual Environments. The conference built on the very successful inaugural event DHM2011 held in Lyon two years before; and a decade of digital human modelling conferences held under the auspices of SAE International. Practitioners and scientists from 13 countries gathered to present their state-of-the-art developments and applied research, besides discussing the most recent advances in human modelling and directions for future work in DHM...
Resumo:
BACKGROUND: Registered nurses and midwives play an essential role in detecting patients at risk of deterioration through ongoing assessment and action in response to changing health status. Yet, evidence suggests that clinical deterioration frequently goes unnoticed in hospitalised patients. While much attention has been paid to early warning and rapid response systems, little research has examined factors related to physical assessment skills. OBJECTIVES: To determine a minimum data set of core skills used during nursing assessment of hospitalised patients and identify nurse and workplace predictors of the use of physical assessment to detect patient deterioration. DESIGN: The study used a single-centre, cross-sectional survey design. SETTING and PARTICIPANTS: The study included 434 registered nurses and midwives (Grades 5-7) involved in clinical care of patients on acute care wards, including medicine, surgery, oncology, mental health and maternity service areas, at a 929-bed tertiary referral teaching hospital in Southeast Queensland, Australia. METHODS: We conducted a hospital-wide survey of registered nurses and midwives using the 133-item Physical Assessment Skills Inventory and the 58-item Barriers to Registered Nurses’ Use of Physical Assessment scale. Median frequency for each physical assessment skill was calculated to determine core skills. To explore predictors of core skill utilisation, backward stepwise general linear modelling was conducted. Means and regression coefficients are reported with 95% confidence intervals. A p value < .05 was considered significant for all analyses. RESULTS: Core skills used by most nurses every time they worked included assessment of temperature, oxygen saturation, blood pressure, breathing effort, skin, wound and mental status. Reliance on others and technology (F = 35.77, p < .001), lack of confidence (F = 5.52, p = .02), work area (F = 3.79, p = .002), and clinical role (F = 44.24, p < .001) were significant predictors of the extent of physical assessment skill use. CONCLUSIONS: The increasing acuity of the acute care patient plausibly warrants more than vital signs assessment; however, our study confirms nurses’ physical assessment core skill set is mainly comprised of vital signs. The focus on these endpoints of deterioration as dictated by early warning and rapid response systems may divert attention from and devalue comprehensive nursing assessment that could detect subtle changes in health status earlier in the patient's hospitalisation.
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Board composition is critical to board effectiveness. Shaping an effective board begins with the selection of directors. While much attention has been paid to the skills and qualifications directors require, there has been less focus on the necessity for board members to interact and work well together. This exploratory study offers insights into what qualities directors look for when selecting new members and the approach adopted to identify and select them. The findings of 10 in-depth interviews with Australian directors suggest new members are selected both on competencies and compatibility. Yet not all selection approaches adequately assess candidates for these two criteria. As a result many appointments fail to realise the selection criteria reducing capacity to reach its full potential.
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Childhood obesity is a leading public health concern globally. This study aimed to extend research applying the principle of market segmentation to gain insight into changing the physical activity behaviour of children, particularly their walk to/from school behaviour. It further examined the utility of employing theory, specifically the Theory of Planned Behaviour (TPB), for this purpose. The study demonstrates the usefulness of behavioural, geographic and psychographic variables, as measured by the TPB, in distinguishing segments, offering an important contrast to prior segmentation studies emphasising demographic variables. This result provides empirical evidence of the value of employing the four segmentation bases, extending beyond a demographic focus, and the importance of incorporating behavioural theory in market segmentation. In so doing, this research provides key insights into changing children’s walking behaviour.
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Integration of biometrics is considered as an attractive solution for the issues associated with password based human authentication as well as for secure storage and release of cryptographic keys which is one of the critical issues associated with modern cryptography. However, the widespread popularity of bio-cryptographic solutions are somewhat restricted by the fuzziness associated with biometric measurements. Therefore, error control mechanisms must be adopted to make sure that fuzziness of biometric inputs can be sufficiently countered. In this paper, we have outlined such existing techniques used in bio-cryptography while explaining how they are deployed in different types of solutions. Finally, we have elaborated on the important facts to be considered when choosing appropriate error correction mechanisms for a particular biometric based solution.
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The development of whole-body imaging at single-cell resolution enables system-level approaches to studying cellular circuits in organisms. Previous clearing methods focused on homogenizing mismatched refractive indices of individual tissues, enabling reductions in opacity but falling short of achieving transparency. Here, we show that an aminoalcohol decolorizes blood by efficiently eluting the heme chromophore from hemoglobin. Direct transcardial perfusion of an aminoalcohol-containing cocktail that we previously termed CUBIC coupled with a 10 day to 2 week clearing protocol decolorized and rendered nearly transparent almost all organs of adult mice as well as the entire body of infant and adult mice. This CUBIC-perfusion protocol enables rapid whole-body and whole-organ imaging at single-cell resolution by using light-sheet fluorescent microscopy. The CUBIC protocol is also applicable to 3D pathology, anatomy, and immunohistochemistry of various organs. These results suggest that whole-body imaging of colorless tissues at high resolution will contribute to organism-level systems biology.
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Policy makers, urban planners and economic geographers readily acknowledge the potential value of industrial clustering. Clusters attract policy makers’ interest because it is widely held that they are a way of connecting agglomeration to innovation and human capital to investment. Urban planners view clustering as a way of enticing creative human capital, the so-called ‘creative class’, that is, creative people are predisposed to live where there is a range of cultural infrastructure and amenities. Economists and geographers have contrived to promote clustering as a solution to stalled regional development. In the People’s Republic of China, over the past decade the cluster has become the default setting of the cultural and creative industries, the latter a composite term applied to the quantifiable outputs of artists, designers and media workers as well as related service sectors such as tourism, advertising and management. The thinking behind many cluster projects is to ‘pick winners’. In this sense the rapid expansion in the number of cultural and creative clusters in China over the past decade is not so very different from the early 1990s, a period that saw an outbreak of innovation parks, most of which inevitably failed to deliver measurable innovation and ultimately served as revenue-generating sources for district governments via real estate speculation. Since the early years of the first decade of the new millennium the cluster model has been pressed into the service of cultural development.
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Purpose This paper aims to set out a new hierarchical and differentiated model of social marketing principles, concepts and techniques that builds on, but supersedes, the existing lists of non-equivalent and undifferentiated benchmark criteria. Design/methodology/approach This is a conceptual paper that proposes a hierarchical model of social marketing principles, concepts and techniques. Findings This new delineation of the social marketing principle, its four core concepts and five techniques, represents a new way to conceptualize and recognize the different elements that constitute social marketing. This new model will help add to and further the development of the theoretical basis of social marketing, building on the definitional work led by the International Social Marketing Association (iSMA), Australian Association of Social Marketing (AASM) and European Social Marketing Association (ESMA). Research limitations/implications This proposed model offers a foundation for future research to expand upon. Further research is recommended to empirically test the proposed model. Originality/value This paper seeks to advance the theoretical base of social marketing by making a reasoned case for the need to differentiate between principles, concepts and techniques when seeking to describe social marketing.
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Lung cancer is the leading cause of cancer-related mortality. According to WHO, 1.37 million deaths occur globally each year as a result of this disease. More than 70% of these cases are associated with prior tobacco consumption and/or cigarette smoking, suggesting a direct causal relationship. The development and progression of lung cancer and other malignancies involves the loss of genetic stability, resulting in acquisition of cumulative genetic changes; this affords the cell increased malignant potential. As such, an understanding of the mechanisms through which these events may occur will potentially allow for development of new anticancer therapies. This review will address the association between lung cancer and genetic instability, with a central focus on genetic mutations in the DNA damage repair pathways. In addition, we will discuss the potential clinical exploitation of these pathways, both in terms of biomarker staging, as well as through direct therapeutic targeting.