247 resultados para inductive inference


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Smut fungi are important pathogens of grasses, including the cultivated crops maize, sorghum and sugarcane. Typically, smut fungi infect the inflorescence of their host plants. Three genera of smut fungi (Ustilago, Sporisorium and Macalpinomyces) form a complex with overlapping morphological characters, making species placement problematic. For example, the newly described Macalpinomyces mackinlayi possesses a combination of morphological characters such that it cannot be unambiguously accommodated in any of the three genera. Previous attempts to define Ustilago, Sporisorium and Macalpinomyces using morphology and molecular phylogenetics have highlighted the polyphyletic nature of the genera, but have failed to produce a satisfactory taxonomic resolution. A detailed systematic study of 137 smut species in the Ustilago-Sporisorium- Macalpinomyces complex was completed in the current work. Morphological and DNA sequence data from five loci were assessed with maximum likelihood and Bayesian inference to reconstruct a phylogeny of the complex. The phylogenetic hypotheses generated were used to identify morphological synapomorphies, some of which had previously been dismissed as a useful way to delimit the complex. These synapomorphic characters are the basis for a revised taxonomic classification of the Ustilago-Sporisorium-Macalpinomyces complex, which takes into account their morphological diversity and coevolution with their grass hosts. The new classification is based on a redescription of the type genus Sporisorium, and the establishment of four genera, described from newly recognised monophyletic groups, to accommodate species expelled from Sporisorium. Over 150 taxonomic combinations have been proposed as an outcome of this investigation, which makes a rigorous and objective contribution to the fungal systematics of these important plant pathogens.

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A number of treatments for breast cancer induce menopause. This study's aim was to explore women's perceptions and beliefs about menopausal symptoms and their management following breast cancer, and to compare younger and older women's experiences. Data were collected via semi-structured focus groups from women who had undergone treatment for breast cancer, and who were currently experiencing menopausal symptoms. Data were interpreted by way of simple inductive thematic analysis. The women experienced a range of menopausal symptoms that they were not prepared for and found difficult to manage. The central themes related to their lack of knowledge of how to manage menopausal symptoms, and the distress and helplessness that arose from this. Women who were diagnosed prior to 40 years of age reported additional menopausal issues than women who were older at diagnosis. The women in this study expressed a thirst for information related to menopause after breast cancer. The women identified that their needs with regard to menopause after breast cancer were not being met, either through their own lack of knowledge or via conflicting or absent support and management. The importance of enabling women to deal with menopausal symptoms was a central theme to emerge from the data.

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Video surveillance systems using Closed Circuit Television (CCTV) cameras, is one of the fastest growing areas in the field of security technologies. However, the existing video surveillance systems are still not at a stage where they can be used for crime prevention. The systems rely heavily on human observers and are therefore limited by factors such as fatigue and monitoring capabilities over long periods of time. This work attempts to address these problems by proposing an automatic suspicious behaviour detection which utilises contextual information. The utilisation of contextual information is done via three main components: a context space model, a data stream clustering algorithm, and an inference algorithm. The utilisation of contextual information is still limited in the domain of suspicious behaviour detection. Furthermore, it is nearly impossible to correctly understand human behaviour without considering the context where it is observed. This work presents experiments using video feeds taken from CAVIAR dataset and a camera mounted on one of the buildings Z-Block) at the Queensland University of Technology, Australia. From these experiments, it is shown that by exploiting contextual information, the proposed system is able to make more accurate detections, especially of those behaviours which are only suspicious in some contexts while being normal in the others. Moreover, this information gives critical feedback to the system designers to refine the system.

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Calcium (Ca) is the main element of most pulp capping materials and plays an essential role in mineralization. Different pulp capping materials can release various concentrations of Ca ions leading to different clinical outcomes. The purpose of this study was to investigate the effects of various concentrations of Ca ions on the growth and osteogenic differentiation of human dental pulp cells (hDPCs). Different concentrations of Ca ions were added to growth culture medium and osteogenic inductive culture medium. A Cell Counting Kit-8 (CCK-8) was used to determine the proliferation of hDPCs in growth culture medium. Osteogenic differentiation and mineralization were measured by alkaline phosphatase (ALP) assay, Alizarin red S/von kossa staining, calcium content quantitative assay. The selected osteogenic differentiation markers were investigated by quantitative real-time polymerase chain reaction (qRT-PCR). Within the range of 1.8–16.2 mM, increased concentrations of Ca ions had no effect on cell proliferation, but led to changes in osteogenic differentiation. It was noted that enhanced mineralized matrix nodule formation was found in higher Ca ions concentrations; however, ALP activity and gene expression were reduced. qRT-PCR results showed a trend towards down-regulated mRNA expression of type I collagen (COL1A2) and Runx2 at elevated concentrations of Ca ions, whereas osteopontin (OPN) and osteocalcin (OCN) mRNA expression was significantly up-regulated. Ca ions content in the culture media can significantly influence the osteogenic properties of hDPCs, indicating the importance of optimizing Ca ions release from dental pulp capping materials in order to achieve desirable clinical outcomes.

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Recent research on novice programmers has suggested that they pass through neo-Piagetian stages: sensorimotor, preoperational, and concrete operational stages, before eventually reaching programming competence at the formal operational stage. This paper presents empirical results in support of this neo-Piagetian perspective. The major novel contributions of this paper are empirical results for some exam questions aimed at testing novices for the concrete operational abilities to reason with quantities that are conserved, processes that are reversible, and properties that hold under transitive inference. While the questions we used had been proposed earlier by Lister, he did not present any data for how students performed on these questions. Our empirical results demonstrate that many students struggle to answer these problems, despite the apparent simplicity of these problems. We then compare student performance on these questions with their performance on six explain in plain English questions.

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This paper argues for a renewed focus on statistical reasoning in the beginning school years, with opportunities for children to engage in data modelling. Results are reported from the first year of a 3-year longitudinal study in which three classes of first-grade children (6-year-olds) and their teachers engaged in data modelling activities. The theme of Looking after our Environment, part of the children’s science curriculum, provided the task context. The goals for the two activities addressed here included engaging children in core components of data modelling, namely, selecting attributes, structuring and representing data, identifying variation in data, and making predictions from given data. Results include the various ways in which children represented and re represented collected data, including attribute selection, and the metarepresentational competence they displayed in doing so. The “data lenses” through which the children dealt with informal inference (variation and prediction) are also reported.

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In language learning, listening is the basic skill which learners should begin to develop other skills, namely speaking, reading and writing. This sequence of language learning in most English as Foreign Language (EFL) settings goes against the stream, learning first reading and writing and later listening and speaking. This study investigates the effects of cognitive, process-based approach to instructing EFL listening strategies over 11 weeks during a semester in Persian (L1). Lower intermediate female participants (N = 50) came from a couple of EFL classrooms in an English Language Institute in Iran. The experimental group (n = 25) listened to their classroom activities using a methodology that led learners through four cognitive processes (guessing, making inference, identifying topics and repetition) in Persian was basically successful in EFL listening. The same teacher taught the control group (n = 25), which listened to the same classroom listening activities without any guided attention to the learning strategy process in Persian. A pre and post listening test made by a group of experts in the language institute tracked any development in light of cognitive learning strategy instruction in EFL listening through L1. The hypothesis was that the experimental group received the guided attention in L1 during the classroom listening activities made greater gains and was verified despite the partial improvement of the control group.

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Recommender systems are one of the recent inventions to deal with ever growing information overload in relation to the selection of goods and services in a global economy. Collaborative Filtering (CF) is one of the most popular techniques in recommender systems. The CF recommends items to a target user based on the preferences of a set of similar users known as the neighbours, generated from a database made up of the preferences of past users. With sufficient background information of item ratings, its performance is promising enough but research shows that it performs very poorly in a cold start situation where there is not enough previous rating data. As an alternative to ratings, trust between the users could be used to choose the neighbour for recommendation making. Better recommendations can be achieved using an inferred trust network which mimics the real world "friend of a friend" recommendations. To extend the boundaries of the neighbour, an effective trust inference technique is required. This thesis proposes a trust interference technique called Directed Series Parallel Graph (DSPG) which performs better than other popular trust inference algorithms such as TidalTrust and MoleTrust. Another problem is that reliable explicit trust data is not always available. In real life, people trust "word of mouth" recommendations made by people with similar interests. This is often assumed in the recommender system. By conducting a survey, we can confirm that interest similarity has a positive relationship with trust and this can be used to generate a trust network for recommendation. In this research, we also propose a new method called SimTrust for developing trust networks based on user's interest similarity in the absence of explicit trust data. To identify the interest similarity, we use user's personalised tagging information. However, we are interested in what resources the user chooses to tag, rather than the text of the tag applied. The commonalities of the resources being tagged by the users can be used to form the neighbours used in the automated recommender system. Our experimental results show that our proposed tag-similarity based method outperforms the traditional collaborative filtering approach which usually uses rating data.

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In the past fifteen years, increasing attention has been given to the role of Vocational Education and Training (VET) in attracting large numbers of international students and its contribution to the economic development of Australia. This trend has given rise to many challenges in vocational education, especially with regard to providing quality education that ensures international students’ stay in Australia is a satisfactory experience. Teachers are key stakeholders in international education and share responsibility for ensuring international students gain quality learning experiences and positive outcomes. However, the challenges and needs of these teachers are generally not well understood. Therefore, this paper draws on the dilemmas faced by teachers of international students associated with professional, personal, ethical and educational aspects. This paper reports on a Masters Research project that is designed to investigate the dilemmas that teachers of international students face in VET in Australia, particularly in Brisbane. This study uses a qualitative approach within the interpretive constructivist paradigm to gain real-life insights through responsive interviewing and inductive data analysis. While the data collection has been done, the analysis of data is in progress. Responsive interviews with teachers of VET with different academic and national backgrounds, ages, industry experience have identified particular understandings, ideologies and representations of what it means to be a teacher in today's multicultural VET environment; provoking both resistances and new pedagogical understanding of teacher dilemmas and their work environment through the eyes of teachers of international students. The paper considers the challenges for the VET practitioners within the VET system while reflecting on the theme for the 2011 AVETRA conference, “Research in VET: Janus- Reflecting Back, Projecting Forward” by focusing particularly on “Rethinking pedagogies and pathways in VET work through the voice of VET workers”.

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In this paper, we apply a simulation based approach for estimating transmission rates of nosocomial pathogens. In particular, the objective is to infer the transmission rate between colonised health-care practitioners and uncolonised patients (and vice versa) solely from routinely collected incidence data. The method, using approximate Bayesian computation, is substantially less computer intensive and easier to implement than likelihood-based approaches we refer to here. We find through replacing the likelihood with a comparison of an efficient summary statistic between observed and simulated data that little is lost in the precision of estimated transmission rates. Furthermore, we investigate the impact of incorporating uncertainty in previously fixed parameters on the precision of the estimated transmission rates.

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In recent years, a number of phylogenetic methods have been developed for estimating molecular rates and divergence dates under models that relax the molecular clock constraint by allowing rate change throughout the tree. These methods are being used with increasing frequency, but there have been few studies into their accuracy. We tested the accuracy of several relaxed-clock methods (penalized likelihood and Bayesian inference using various models of rate change) using nucleotide sequences simulated on a nine-taxon tree. When the sequences evolved with a constant rate, the methods were able to infer rates accurately, but estimates were more precise when a molecular clock was assumed. When the sequences evolved under a model of autocorrelated rate change, rates were accurately estimated using penalized likelihood and by Bayesian inference using lognormal and exponential models of rate change, while other models did not perform as well. When the sequences evolved under a model of uncorrelated rate change, only Bayesian inference using an exponential rate model performed well. Collectively, the results provide a strong recommendation for using the exponential model of rate change if a conservative approach to divergence time estimation is required. A case study is presented in which we use a simulation-based approach to examine the hypothesis of elevated rates in the Cambrian period, and it is found that these high rate estimates might be an artifact of the rate estimation method. If this bias is present, then the ages of metazoan divergences would be systematically underestimated. The results of this study have implications for studies of molecular rates and divergence dates.

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In phylogenetics, the unrooted model of phylogeny and the strict molecular clock model are two extremes of a continuum. Despite their dominance in phylogenetic inference, it is evident that both are biologically unrealistic and that the real evolutionary process lies between these two extremes. Fortunately, intermediate models employing relaxed molecular clocks have been described. These models open the gate to a new field of “relaxed phylogenetics.” Here we introduce a new approach to performing relaxed phylogenetic analysis. We describe how it can be used to estimate phylogenies and divergence times in the face of uncertainty in evolutionary rates and calibration times. Our approach also provides a means for measuring the clocklikeness of datasets and comparing this measure between different genes and phylogenies. We find no significant rate autocorrelation among branches in three large datasets, suggesting that autocorrelated models are not necessarily suitable for these data. In addition, we place these datasets on the continuum of clocklikeness between a strict molecular clock and the alternative unrooted extreme. Finally, we present analyses of 102 bacterial, 106 yeast, 61 plant, 99 metazoan, and 500 primate alignments. From these we conclude that our method is phylogenetically more accurate and precise than the traditional unrooted model while adding the ability to infer a timescale to evolution.

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Background The genus Rattus is highly speciose and has a complex taxonomy that is not fully resolved. As shown previously there are two major groups within the genus, an Asian and an Australo-Papuan group. This study focuses on the Australo-Papuan group and particularly on the Australian rats. There are uncertainties regarding the number of species within the group and the relationships among them. We analysed 16 mitochondrial genomes, including seven novel genomes from six species, to help elucidate the evolutionary history of the Australian rats. We also demonstrate, from a larger dataset, the usefulness of short regions of the mitochondrial genome in identifying these rats at the species level. Results Analyses of 16 mitochondrial genomes representing species sampled from Australo-Papuan and Asian clades of Rattus indicate divergence of these two groups ~2.7 million years ago (Mya). Subsequent diversification of at least 4 lineages within the Australo-Papuan clade was rapid and occurred over the period from ~ 0.9-1.7 Mya, a finding that explains the difficulty in resolving some relationships within this clade. Phylogenetic analyses of our 126 taxon, but shorter sequence (1952 nucleotides long), Rattus database generally give well supported species clades. Conclusions Our whole mitochondrial genome analyses are concordant with a taxonomic division that places the native Australian rats into the Rattus fuscipes species group. We suggest the following order of divergence of the Australian species. R. fuscipes is the oldest lineage among the Australian rats and is not part of a New Guinean radiation. R. lutreolus is also within this Australian clade and shallower than R. tunneyi while the R. sordidus group is the shallowest lineage in the clade. The divergences within the R. sordidus and R. leucopus lineages occurring about half a million years ago support the hypotheses of more recent interchanges of rats between Australia and New Guinea. While problematic for inference of deeper divergences, we report that the analysis of shorter mitochondrial sequences is very useful for species identification in rats.

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Australian women make decisions about return to paid work and care for their child within a policy environment that presents mixed messages about maternal employment and child care standards. Against this background an investigation of first-time mothers’ decision-making about workforce participation and child care was undertaken. Four women were studied from pregnancy through the first postnatal year using interview and diary methods. Inductive analyses identified three themes, all focused on dimensions of family security: financial security relating to family income, emotional security relating to child care quality, and pragmatic security relating to child care access. The current policy changes that aim to increase child care quality standards in Australia present a positive step toward alleviating family insecurities but are insufficient to alleviate the evidently high levels of tension between workforce participation and family life experienced by women transitioning back into the workforce in Australia.

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Motorcycles are overrepresented in road traffic crashes and particularly vulnerable at signalized intersections. The objective of this study is to identify causal factors affecting the motorcycle crashes at both four-legged and T signalized intersections. Treating the data in time-series cross-section panels, this study explores different Hierarchical Poisson models and found that the model allowing autoregressive lag 1 dependent specification in the error term is the most suitable. Results show that the number of lanes at the four-legged signalized intersections significantly increases motorcycle crashes largely because of the higher exposure resulting from higher motorcycle accumulation at the stop line. Furthermore, the presence of a wide median and an uncontrolled left-turn lane at major roadways of four-legged intersections exacerbate this potential hazard. For T signalized intersections, the presence of exclusive right-turn lane at both major and minor roadways and an uncontrolled left-turn lane at major roadways of T intersections increases motorcycle crashes. Motorcycle crashes increase on high-speed roadways because they are more vulnerable and less likely to react in time during conflicts. The presence of red light cameras reduces motorcycle crashes significantly for both four-legged and T intersections. With the red-light camera, motorcycles are less exposed to conflicts because it is observed that they are more disciplined in queuing at the stop line and less likely to jump start at the start of green.