913 resultados para Poultry Science Association.


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To investigate the correlation between postmenopausal osteoporosis (PMO) and the pathogenesis of periodontitis, ovariectomized rats were generated and the experimental periodontitis was induced using a silk ligature. The inflammatory factors and bone metabolic markers were measured in the serum and periodontal tissues of ovariectomized rats using an automatic chemistry analyzer, enzyme-linked immunosorbent assays, and immunohistochemistry. The bone mineral density of whole body, pelvis, and spine was analyzed using dual-energy X-ray absorptiometry and image analysis. All data were analyzed using SPSS 13.0 statistical software. It was found that ovariectomy could upregulate the expression of interleukin- (IL-)6, the receptor activator of nuclear factor-κB ligand (RANKL), and osteoprotegerin (OPG) and downregulate IL-10 expression in periodontal tissues, which resulted in progressive alveolar bone loss in experimental periodontitis. This study indicates that changes of cytokines and bone turnover markers in the periodontal tissues of ovariectomized rats contribute to the damage of periodontal tissues.

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This study examined the prevalence of depressive symptoms and elucidated the causal pathway between socioeconomic status and depression in a community in the central region of Vietnam. The study used a combination of qualitative and quantitative research methods. Indepth interviews were applied with two local psychiatric experts and ten residents for qualitative research. A cross sectional survey with structured interview technique was implemented with 100 residents in the pilot quantitative survey. The Center for Epidemiological Studies-Depression Scale (CES-D) was applied to valuate depressive symptoms ( CES-D score over 21) and depression ( CESD core over 25). Ordinary Least Squares Regression following the three steps of Baron and Kenny’s framework was employed for testing mediation models. There was a strong social gradient with respect to depressive symptoms. People with higher education levels reported fewer depressive symptoms (lower CES-D scores). Incomes were also inversely associated with depressive symptoms, but only the ones at the bottom of the quartile income. Low level and unstable individuals in terms of occupation were associated with higher depressive symptoms compared with the highest occupation group. Employment status showed the strongest gradient with respect to its impact on the burden of depressive symptoms compared with other indicators of SES. Findings from this pilot study suggest a pattern on the negative association between socioeconomic status and depression in Vietnamese adults.

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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 chapter we propose two approaches which measure multi-level association rules to help evaluate their interestingness by considering the database’s underlying taxonomy. 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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As of today, opinion mining has been widely used to iden- tify the strength and weakness of products (e.g., cameras) or services (e.g., services in medical clinics or hospitals) based upon people's feed- back such as user reviews. Feature extraction is a crucial step for opinion mining which has been used to collect useful information from user reviews. Most existing approaches only find individual features of a product without the structural relationships between the features which usually exists. In this paper, we propose an approach to extract features and feature relationship, represented as tree structure called a feature hi- erarchy, based on frequent patterns and associations between patterns derived from user reviews. The generated feature hierarchy profiles the product at multiple levels and provides more detailed information about the product. Our experiment results based on some popularly used review datasets show that the proposed feature extraction approach can identify more correct features than the baseline model. Even though the datasets used in the experiment are about cameras, our work can be ap- plied to generate features about a service such as the services in hospitals or clinics.

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AIMS: Recent studies on corneal markers have advocated corneal nerve fibre length as the most important measure of diabetic peripheral neuropathy. The aim of this study was to determine if standardizing corneal nerve fibre length for tortuosity increases its association with other measures of diabetic peripheral neuropathy. METHODS: Two hundred and thirty-one individuals with diabetes with either predominantly mild or absent neuropathic changes and 61 control subjects underwent evaluation of diabetic neuropathy symptom score, neuropathy disability score, testing with 10-g monofilament, quantitative sensory testing (warm, cold, vibration detection) and nerve conduction studies. Corneal nerve fibre length and corneal nerve fibre tortuosity were measured using corneal confocal microscopy. A tortuosity-standardised corneal nerve fibre length variable was generated by dividing corneal nerve fibre length by corneal nerve fibre tortuosity. Differences in corneal nerve morphology between individuals with and without diabetic peripheral neuropathy and control subjects were determined and associations were estimated between corneal morphology and established tests of, and risk factors for, diabetic peripheral neuropathy. RESULTS: The tortuosity-standardised corneal nerve fibre length variable was better than corneal nerve fibre length in demonstrating differences between individuals with diabetes, with and without neuropathy (tortuosity-standardised corneal nerve fibre length variable: 70.5 ± 27.3 vs. 84.9 ± 28.7, P < 0.001, receiver operating characteristic area under the curve = 0.67; corneal nerve fibre length: 15.9 ± 6.9 vs. 18.4 ± 6.2 mm/mm(2) , P = 0.004, receiver operating characteristic area under the curve = 0.64). Furthermore, the tortuosity-standardised corneal nerve fibre length variable demonstrated a significant difference between the control subjects and individuals with diabetes, without neuropathy, while corneal nerve fibre length did not (tortuosity-standardised corneal nerve fibre length variable: 94.3 ± 27.1 vs. 84.9 ± 28.7, P = 0.028; corneal nerve fibre length: 20.1 ± 6.3 vs. 18.4 ± 6.2 mm/mm(2) , P = 0.084). Correlations between corneal nerve fibre length and established measures of neuropathy and risk factors for neuropathy were higher when a correction was made for the nerve tortuosity. CONCLUSIONS: Standardizing corneal nerve fibre length for tortuosity enhances the ability to differentiate individuals with diabetes, with and without neuropathy.

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This study investigated movement synchronization of players within and between teams during competitive association football performance. Cluster phase analysis was introduced as a method to assess synchronies between whole teams and between individual players with their team as a function of time, ball possession and field direction. Measures of dispersion (SD) and regularity (sample entropy – SampEn – and cross sample entropy – Cross-SampEn) were used to quantify the magnitude and structure of synchrony. Large synergistic relations within each professional team sport collective were observed, particularly in the longitudinal direction of the field (0.89 ± 0.12) compared to the lateral direction (0.73 ± 0.16, p < .01). The coupling between the group measures of the two teams also revealed that changes in the synchrony of each team were intimately related (Cross-SampEn values of 0.02 ± 0.01). Interestingly, ball possession did not influence team synchronization levels. In player–team synchronization, individuals tended to be coordinated under near in-phase modes with team behavior (mean ranges between −7 and 5° of relative phase). The magnitudes of variations were low, but more irregular in time, for the longitudinal (SD: 18 ± 3°; SampEn: 0.07 ± 0.01), compared to the lateral direction (SD: 28 ± 5°; SampEn: 0.06 ± 0.01, p < .05) on-field. Increases in regularity were also observed between the first (SampEn: 0.07 ± 0.01) and second half (SampEn: 0.06 ± 0.01, p < .05) of the observed competitive game. Findings suggest that the method of analysis introduced in the current study may offer a suitable tool for examining team’s synchronization behaviors and the mutual influence of each team’s cohesiveness in competing social collectives.

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This paper reports on the initial phase of a Professional Learning Program (PLP) undertaken by 100 primary school teachers in China that aimed to facilitate the development of adaptive expertise in using technology to facilitate innovative science teaching and learning such as that envisaged by the Chinese Ministry of Education’s (2010-2020) education reforms. Key principles derived from literature about professional learning and scaffolding of learning informed the design of the PLP. The analysis of data revealed that the participants had made substantial progress towards the development of adaptive expertise. This was manifested not only by advances in the participants’ repertoires of Subject Matter Knowledge and Pedagogical Content Knowledge but also in changes to their levels of confidence and identities as teachers. By the end of the initial phase of the PLP, the participants had coalesced into a professional learning community that readily engaged in the sharing, peer review, reuse and adaption, and collaborative design of innovative science learning and assessment activities. The findings from the study indicate that those engaged in the development of PLPs for teachers in China need to take cognizance of certain cultural factors and traditions idiosyncratic to the Chinese educational system. A set of revised principles is then presented to inform the future design and implementation of PLPs for teachers in China.

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This research investigated the prevalence of vision disorders in Queensland Indigenous primary school children, creating the first comprehensive visual profile of Indigenous children. Findings showed reduced convergence ability and reduced visual information processing skills were more common in Indigenous compared to non-Indigenous children. Reduced visual information processing skills were also associated with reduced reading outcomes in both groups of children. As early detection of visual disorders is important, the research also reviewed the delivery of screening programs across Queensland and proposed a model for improved coordination and service delivery of vision screening to Queensland school children.

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This study was a step forward to improve the performance for discovering useful knowledge – especially, association rules in this study – in databases. The thesis proposed an approach to use granules instead of patterns to represent knowledge implicitly contained in relational databases; and multi-tier structure to interpret association rules in terms of granules. Association mappings were proposed for the construction of multi-tier structure. With these tools, association rules can be quickly assessed and meaningless association rules can be justified according to the association mappings. The experimental results indicated that the proposed approach is promising.

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This paper presents a novel framework to further advance the recent trend of using query decomposition and high-order term relationships in query language modeling, which takes into account terms implicitly associated with different subsets of query terms. Existing approaches, most remarkably the language model based on the Information Flow method are however unable to capture multiple levels of associations and also suffer from a high computational overhead. In this paper, we propose to compute association rules from pseudo feedback documents that are segmented into variable length chunks via multiple sliding windows of different sizes. Extensive experiments have been conducted on various TREC collections and our approach significantly outperforms a baseline Query Likelihood language model, the Relevance Model and the Information Flow model.

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This paper reports a number of findings from the Interests and Recruitment in Science (IRIS) study carried out in Australia in 2011. The findings concern the perceptions of first year university students in science, technology and engineering courses about the influence of museums/science centres and outreach activities on their choice of course. The study found that STE students in general tended to rate museums/science centres as more important in their decisions than outreach activities. However, a closer examination showed that females in engineering courses were significantly more inclined to rate outreach activities as important than were males in engineering courses or females in other courses. The implications of this finding for strategies to encourage more young women into engineering are discussed.

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Dealing with the large amount of data resulting from association rule mining is a big challenge. The essential issue is how to provide efficient methods for summarizing and representing meaningful discovered knowledge from databases. This paper presents a new approach called multi-tier granule mining to improve the performance of association rule mining. Rather than using patterns, it uses granules to represent knowledge that is implicitly contained in relational databases. This approach also uses multi-tier structures and association mappings to interpret association rules in terms of granules. Consequently, association rules can be quickly assessed and meaningless association rules can be justified according to these association mappings. The experimental results indicate that the proposed approach is promising

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Is there a crisis in Australian science and mathematics education? Declining enrolments in upper secondary Science and Mathematics courses have gained much attention from the media, politicians and high-profile scientists over the last few years, yet there is no consensus amongst stakeholders about either the nature or the magnitude of the changes. We have collected raw enrolment data from the education departments of each of the Australian states and territories from 1992 to 2012 and analysed the trends for Biology, Chemistry, Physics, two composite subject groups (Earth Sciences and Multidisciplinary Sciences), as well as entry, intermediate and advanced Mathematics. The results of these analyses are discussed in terms of participation rates, raw enrolments and gender balance. We have found that the total number of students in Year 12 increased by around 16% from 1992 to 2012 while the participation rates for most Science and Mathematics subjects, as a proportion of the total Year 12 cohort, fell (Biology (-10%), Chemistry (-5%), Physics (-7%), Multidisciplinary Science (-5%), intermediate Mathematics (-11%), advanced Mathematics (-7%) in the same period. There were increased participation rates in Earth Sciences (+0.3%) and entry Mathematics (+11%). In each case the greatest rates of change occurred prior to 2001 and have been slower and steadier since. We propose that the broadening of curriculum offerings, further driven by students' self-perception of ability and perceptions of subject difficulty and usefulness, are the most likely cause of the changes in participation. While these continuing declines may not amount to a crisis, there is undoubtedly serious cause for concern.