1000 resultados para Supramolecular association


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The current world situation is plagued by “wicked problems” and a widespread sense of “things are going to get worse”. We confront the almost imponderable consequences of global habitat destruction and climate change, as well as the meltdown of the financial markets with their largely yet to be seen damage to the “real economy”. These things will have considerable negative impacts on the social system and people's lives, particularly the disadvantaged and socially excluded, and require innovative policy and program responses delivered by caring, intelligent, and committed practitioners. These gargantuan issues put into perspective the difficulties that confront social, welfare, and community work today. Yet, in times of trouble, social work and human services tend to do well. For example, although Australian Social Workers and Welfare and Community Workers have experienced phenomenal job growth over the past 5 years, they also have good prospects for future growth and above average salaries in the seventh and sixth deciles, respectively (Department of Education, Employment and Workplace Relations, 2008). I aim to examine the host of reasons why the pursuit of social justice and high-quality human services is difficult to attain in today's world and then consider how the broadly defined profession of social welfare practitioners may collectively take action to (a) respond in ways that reassert our role in compassionately assisting the downtrodden and (b) reclaim the capacity to be a significant body of professional expertise driving social policy and programs. For too long social work has responded to the wider factors it confronts through a combination of ignoring them, critiquing from a distance, and concentrating on the job at hand and our day-to-day responsibilities. Unfortunately, “holding the line” has proved futile and, little by little, the broad social mandate and role of social welfare has altered until, currently, most social programs entail significant social surveillance of troublesome or dangerous groups, rather than assistance. At times it almost seems like the word “help” has been lost in the political and managerial lexicon, replaced by “manage” and “control”. Our values, beliefs, and ethics are under real threat as guiding principles for social programs.

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Report provided back by Bronwyn Fredericks on her participation at the First Native American and Indigenous Studies Association Meeting held 21-23 May 2009 in Minnesota, United States of America.

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Cancer represents a major public health concern in Australia. Causes of cancer are multifactorial with lack of physical activity being considered one of the known risk factors, particularly for breast and colorectal cancers. Participating in exercise has also been associated with benefits during and following treatment for cancer, including improvements in psychosocial and physical outcomes, as well as better compliance with treatment regimens, reduced impact of disease symptoms and treatment-related side effects, and survival benefits for particular cancers. The general exercise prescription for people undertaking or having completed cancer treatment is of low to moderate intensity, regular frequency (3-5 times/week) for at least 20 minutes per session, involving aerobic, resistance or mixed exercise types. Future work needs to push the boundaries of this exercise prescription, so that we can better understand what constitutes optimal, desirable and necessary frequency, duration, intensity and type, and how specific characteristics of the individual (e.g., age, cancer type, treatment, presence of specific symptoms) influence this prescription. What follows is a summary of the cancer and exercise literature, in particular the purpose of exercise following diagnosis of cancer, the potential benefits derived by cancer patients and survivors from participating in exercise programs, and exercise prescription guidelines and contraindications or considerations for exercise prescription with this special population. This report represents the position stand of the Australian Association of Exercise and Sport Science on exercise and cancer recovery and has the purpose of guiding Accredited Exercise Physiologists in their work with cancer patients.

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The neXus2 research project has sought to investigate the library and information services (LIS) workforce in Australia, from the institutional or employer perspective. The study builds on the neXus1 study, which collected data from individuals in the LIS workforce in order to present a snapshot of the profession in 2006, highlighting the demographics, educational background and career details of library and information professionals in Australia. To counterbalance this individual perspective, library institutions were invited to participate in a survey to contribute further data as employers. This final report on the neXus2 project compares the findings from the different library sectors, ie academic libraries, TAFE libraries, the National and State libraries, public libraries, special libraries and school libraries.

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For most of the work done in developing association rule mining, the primary focus has been on the efficiency of the approach and to a lesser extent the quality of the derived rules has been emphasized. Often for a dataset, a huge number of rules can be derived, but many of them can be redundant to other rules and thus are useless in practice. The extremely large number of rules makes it difficult for the end users to comprehend and therefore effectively use the discovered rules and thus significantly reduces the effectiveness of rule mining algorithms. If the extracted knowledge can’t be effectively used in solving real world problems, the effort of extracting the knowledge is worth little. This is a serious problem but not yet solved satisfactorily. In this paper, we propose a concise representation called Reliable Approximate basis for representing non-redundant approximate association rules. We prove that the redundancy elimination based on the proposed basis does not reduce the belief to the extracted rules. We also prove that all approximate association rules can be deduced from the Reliable Approximate basis. Therefore the basis is a lossless representation of approximate association rules.

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Background: The seasonality of suicide has long been recognised. However, little is known about the relative importance of socio-environmental factors in the occurrence of suicide in different geographical areas. This study examined the association of climate, socioeconomic and demographic factors with suicide in Queensland, Australia, using a spatiotemporal approach. Methods: Seasonal data on suicide, demographic variables and socioeconomic indexes for areas in each Local Government Area (LGA) between 1999 and 2003 were acquired from the Australian Bureau of Statistics. Climate data were supplied by the Australian Bureau of Meteorology. A multivariable generalized estimating equation model was used to examine the impact of socio-environmental factors on suicide. Results: The preliminary data analyses show that far north Queensland had the highest suicide incidence (e.g., Cook and Mornington Shires), while the south-western areas had the lowest incidence (e.g., Barcoo and Bauhinia Shires) in all the seasons. Maximum temperature, unemployment rate, the proportion of Indigenous population and the proportion of population with low individual income were statistically significantly and positively associated with suicide. There were weaker but not significant associations for other variables. Conclusions: Maximum temperature, the proportion of Indigenous population and unemployment rate appeared to be major determinants of suicide at a LGA level in Queensland.

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Association rule mining is one technique that is widely used when querying databases, especially those that are transactional, in order to obtain useful associations or correlations among sets of items. Much work has been done focusing on efficiency, effectiveness and redundancy. There has also been a focusing on the quality of rules from single level datasets with many interestingness measures proposed. However, with multi-level datasets now being common there is a lack of interestingness measures developed for multi-level and cross-level rules. Single level measures do not take into account the hierarchy found in a multi-level dataset. This leaves the Support-Confidence approach,which does not consider the hierarchy anyway and has other drawbacks, as one of the few measures available. In this paper we propose two approaches which measure multi-level association rules to help evaluate their interestingness. These measures of diversity and peculiarity can be used to help identify those rules from multi-level datasets that are potentially useful.

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Association rule mining has made many advances in the area of knowledge discovery. However, the quality of the discovered association rules is a big concern and has drawn more and more attention recently. One problem with the quality of the discovered association rules is the huge size of the extracted rule set. Often for a dataset, a huge number of rules can be extracted, but many of them can be redundant to other rules and thus useless in practice. Mining non-redundant rules is a promising approach to solve this problem. In this paper, we firstly propose a definition for redundancy; then we propose a concise representation called Reliable basis for representing non-redundant association rules for both exact rules and approximate rules. An important contribution of this paper is that we propose to use the certainty factor as the criteria to measure the strength of the discovered association rules. With the criteria, we can determine the boundary between redundancy and non-redundancy to ensure eliminating as many redundant rules as possible without reducing the inference capacity of and the belief to the remaining extracted non-redundant rules. We prove that the redundancy elimination based on the proposed Reliable basis does not reduce the belief to the extracted rules. We also prove that all association rules can be deduced from the Reliable basis. Therefore the Reliable basis is a lossless representation of association rules. Experimental results show that the proposed Reliable basis can significantly reduce the number of extracted rules.

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Recommender systems are widely used online to help users find other products, items etc that they may be interested in based on what is known about that user in their profile. Often however user profiles may be short on information and thus when there is not sufficient knowledge on a user it is difficult for a recommender system to make quality recommendations. This problem is often referred to as the cold-start problem. Here we investigate whether association rules can be used as a source of information to expand a user profile and thus avoid this problem, leading to improved recommendations to users. Our pilot study shows that indeed it is possible to use association rules to improve the performance of a recommender system. This we believe can lead to further work in utilising appropriate association rules to lessen the impact of the cold-start problem.