137 resultados para Weather Research and Forecast Model (WRF)


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This paper presents findings from an empirical study of key aspects of the teaching and research priorities, beliefs and behaviours of 72 professorial and associate professorial academics in Science, Information Technology and Engineering across four faculties in three Australian universities. The academics ranked 16 research activities and 16 matched learning and teaching (L&T) activities from three perspectives: job satisfaction, role model behaviour and perceptions of professional importance. The findings were unequivocally in favour of research in all three areas and remarkably consistent across the universities. The only L&T activity that was ranked consistently well was 'improving student satisfaction ratings for teaching', an area in which academics are increasingly held accountable. Respondents also indicated that their seniors encourage research efforts more than L&T efforts. Recommendations include that higher education rewards for quality L&T are maintained or improved and that recognition of L&T research domains is further strengthened.

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Dengue virus (DENV) transmission in Australia is driven by weather factors and imported dengue fever (DF) cases. However, uncertainty remains regarding the threshold effects of high-order interactions among weather factors and imported DF cases and the impact of these factors on autochthonous DF. A time-series regression tree model was used to assess the threshold effects of natural temporal variations of weekly weather factors and weekly imported DF cases in relation to incidence of weekly autochthonous DF from 1 January 2000 to 31 December 2009 in Townsville and Cairns, Australia. In Cairns, mean weekly autochthonous DF incidence increased 16.3-fold when the 3-week lagged moving average maximum temperature was <32 °C, the 4-week lagged moving average minimum temperature was ≥24 °C and the sum of imported DF cases in the previous 2 weeks was >0. When the 3-week lagged moving average maximum temperature was ≥32 °C and the other two conditions mentioned above remained the same, mean weekly autochthonous DF incidence only increased 4.6-fold. In Townsville, the mean weekly incidence of autochthonous DF increased 10-fold when 3-week lagged moving average rainfall was ≥27 mm, but it only increased 1.8-fold when rainfall was <27 mm during January to June. Thus, we found different responses of autochthonous DF incidence to weather factors and imported DF cases in Townsville and Cairns. Imported DF cases may also trigger and enhance local outbreaks under favorable climate conditions.

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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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It is argued that the smart cities model promise solutions to fuel sustainable development and a high quality of life with a wise management of natural resources, through participatory action and engagement. The paper provides a critical review of this model and application attempts of smart urban technologies in contemporary cities by particularly looking into emerging practices of ubiquitous eco-cities as exemplar smart cities initiatives. Through a thorough review of literature and best practices on the smart cities model, this paper attempts to address the research question of whether smart cities model is just another fashionable city brand or an effective urban development and management model to solve the problems of our cities. The findings shed light on urban planning and development considerations for the integration of smart urban technologies and their possible implications in shaping up of the built environment to produce prosperous and sustainable urban futures.

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Designers have become aware of the importance of creating strong emotional experiences intertwined with new tangible products for the past decade, however an increased interest from firms has emerged in developing new service and business models as complimentary forms of emotion-driven innovation. This interdisciplinary study draws from the psychological sciences – theory of emotion – and the management sciences – business model literature to introduce this new innovation agenda. The term visceral hedonic rhetoric (VHR) is defined as the properties of a product, (and in this paper service and business model extensions) that persuasively induce the pursuit of pleasure at an instinctual level of cognition. This research paper lays the foundation for VHR beyond a product setting, presenting the results from an empirical study where organizations explored the possibilities for VHR in the context of their business. The results found that firms currently believe VHR is perceived in either their product and/or services they provide. Implications suggest shifting perspective surrounding the use of VHR across a firm’s business model design in order to influence the outcomes of their product and/or service design, resulting in an overall stronger emotional connection with the customer.

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The demand for cancer care is growing due to the increasing incidence of cancer and the improved effectiveness of cancer treatments. It is important that cancer nurses continue to improve patient outcomes through research and the use of evidence in practice development, education and policy. This paper describes a case report of a collaborative academic healthcare model that creates capacity for cancer nursing research and evidence-based practice. The Cancer Nursing Professorial Precinct is a strategic collaboration between the Royal Brisbane and Women’s Hospital (RBWH) and Queensland University of Technology (QUT), in Brisbane Australia. The outcomes of this initiative has been remarkable. The principles and strategies used in this initiative may be useful for cancer services in other countries.

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Despite positive testing in animal studies, more than 80% of novel drug candidates fail to proof their efficacy when tested in humans. This is primarily due to the use of preclinical models that are not able to recapitulate the physiological or pathological processes in humans. Hence, one of the key challenges in the field of translational medicine is to “make the model organism mouse more human.” To get answers to questions that would be prognostic of outcomes in human medicine, the mouse's genome can be altered in order to create a more permissive host that allows the engraftment of human cell systems. It has been shown in the past that these strategies can improve our understanding of tumor immunology. However, the translational benefits of these platforms have still to be proven. In the 21st century, several research groups and consortia around the world take up the challenge to improve our understanding of how to humanize the animal's genetic code, its cells and, based on tissue engineering principles, its extracellular microenvironment, its tissues, or entire organs with the ultimate goal to foster the translation of new therapeutic strategies from bench to bedside. This article provides an overview of the state of the art of humanized models of tumor immunology and highlights future developments in the field such as the application of tissue engineering and regenerative medicine strategies to further enhance humanized murine model systems.

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Community development is increasingly using participatory processes that aim to be inclusive and empowering. However, researchers have found that such processes can have contradictory effects. Australian research has highlighted the significant leadership of rural women in sustainable community and economic development and in the adoption of new communication technologies such as the Internet. A focus on gender in participatory development may therefore lead to more effective programs and policies. This chapter outlines an interdisciplinary feminist framework for critically evaluating the participation and empowerment of rural women. This framework was found effective in evaluating an Australian project that aimed to enhance rural women’s access to communication technologies and to empower its participants. Its multiple theoretical and methodological approaches are outlined. The framework advocates an analysis of diversity and difference and the macro and micro contexts. Some principles and strategies for rural women’s inclusion, participation, empowerment, and for participatory feminist evaluation are outlined.

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Work environments have previously been studied to identify the strategies, structures and processes which increase the likelihood of creativity, innovation and collaboration for productive workplaces. A number of perspectives have emerged which identify social and cognitive factors known to contribute to or to restrict innovation and collaboration. Recently more attention has been given to designing physical environments to encourage processes relevant to innovation such as creativity (McCoy & Evans, 2002) knowledge sharing (Hemlin, Allwood & Martin, 2008) and collaboration (Bozeman & Corley, 2004). Some attention has been given specifically to research and development environments (Boutellier et al, 2008) but little integration of this research has occurred. In the context of the construction of new purpose-built premises which will bring together under one roof separate public sector agencies engaged in research and development in agriculture, natural resource systems and the environment, this paper examines the extant literature and develops initial propositions for research relevant to the transition, collaboration and performance of research and development in new organizational environments where traditional boundaries have been redrawn.