358 resultados para Colorado Bar Association.


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Dystrobrevin binding protein 1 (DTNBP1), or dysbindin, is thought to be critical in regulating the glutamatergic system. While the dopamine pathway is known to be important in the aetiology of schizophrenia, it seems likely that glutamatergic dysfunction can lead to the development of schizophrenia. DTNBP1 is widely expressed in brain, levels are reduced in brains of schizophrenia patients and a DTNBP1 polymorphism has been associated with reduced brain expression. Despite numerous genetic studies no DTNBP1 polymorphism has been strongly implicated in schizophrenia aetiology. Using a haplotype block-based gene-tagging approach we genotyped 13 SNPs in DTNBP1 to investigate possible associations with DTNBP1 and schizophrenia. Four polymorphisms were found to be significantly associated with schizophrenia. The strongest association was found with an A/C SNP in intron 7 (rs9370822). Homozygotes for the C allele of rs9370822 were more than two and a half times as likely to have schizophrenia compared to controls. The other polymorphisms showed much weaker association and are less likely to be biologically significant. These results suggest that DTNBP1 is a good candidate for schizophrenia risk and rs9370822 is either functionally important or in disequilibrium with a functional SNP, although our observations should be viewed with caution until they are independently replicated.

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Recent perceptual-motor studies have revealed variations in learning trajectories of novices. Despite such observation, relatively little attention has been paid to studying individual differences in experienced performers’ perceptual-motor behaviors. The present study examined individual differences for a visual anticipation task. Experienced association football goalkeepers attempted to intercept penalty kicks taken with deceptive and non-deceptive kicking actions. Data revealed that differences in the action capabilities of goalkeepers affected the timing and accuracy of movement response behaviors. Faster goalkeepers tended to wait until later before initiating movement in comparison with slower goalkeepers. The study of affordances in sport environments offers a theoretical framework with which to overcome some of the reported methodological limitations in the visual anticipation literature.

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This paper analyzes effects of different practice task constraints on heart rate (HR) variability during 4v4 smallsided football games. Participants were sixteen football players divided into two age groups (U13, Mean age: 12.4±0.5 yrs; U15: 14.6±0.5). The task consisted of a 4v4 sub-phase without goalkeepers, on a 25x15 m field, of 15 minutes duration with an active recovery period of 6 minutes between each condition. We recorded players’ heart rates using heart rate monitors (Polar Team System, Polar Electro, Kempele, Finland) as scoring mode was manipulated (line goal: scoring by dribbling past an extended line; double goal: scoring in either of two lateral goals; and central goal: scoring only in one goal). Subsequently, %HR reserve was calculated with the Karvonen formula. We performed a time-series analysis of HR for each individual in each condition. Mean data for intra-participant variability showed that autocorrelation function was associated with more short-range dependence processes in the “line goal” condition, compared to other conditions, demonstrating that the “line goal” constraint induced more randomness in HR response. Relative to inter-individual variability, line goal constraints demonstrated lower %CV and %RMSD (U13: 9% and 19%; U15: 10% and 19%) compared with double goal (U13: 12% and 21%; U15: 12% and 21%) and central goal (U13: 14% and 24%; U15: 13% and 24%) task constraints, respectively. Results suggested that line goal constraints imposed more randomness on cardiovascular stimulation of each individual and lower inter-individual variability than double goal and central goal constraints.

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Association rule mining has contributed to 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 first propose a definition for redundancy, then propose a concise representation, called a Reliable basis, for representing non-redundant association rules. The Reliable basis contains a set of non-redundant rules which are derived using frequent closed itemsets and their generators instead of using frequent itemsets that are usually used by traditional association rule mining approaches. An important contribution of this paper is that we propose to use the certainty factor as the criterion to measure the strength of the discovered association rules. Using this criterion, we can ensure the elimination of as many redundant rules as possible without reducing the inference capacity of the remaining extracted non-redundant rules. We prove that the redundancy elimination, based on the proposed Reliable basis, does not reduce the strength of belief in the extracted rules. We also prove that all association rules, their supports and confidences, can be retrieved from the Reliable basis without accessing the dataset. 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. We also conduct experiments on the application of association rules to the area of product recommendation. The experimental results show that the non-redundant association rules extracted using the proposed method retain the same inference capacity as the entire rule set. This result indicates that using non-redundant rules only is sufficient to solve real problems needless using the entire rule set.

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In today’s electronic world vast amounts of knowledge is stored within many datasets and databases. Often the default format of this data means that the knowledge within is not immediately accessible, but rather has to be mined and extracted. This requires automated tools and they need to be effective and efficient. Association rule mining is one approach to obtaining knowledge stored with datasets / databases which includes frequent patterns and association rules between the items / attributes of a dataset with varying levels of strength. However, this is also association rule mining’s downside; the number of rules that can be found is usually very big. In order to effectively use the association rules (and the knowledge within) the number of rules needs to be kept manageable, thus it is necessary to have a method to reduce the number of association rules. However, we do not want to lose knowledge through this process. Thus the idea of non-redundant association rule mining was born. A second issue with association rule mining is determining which ones are interesting. The standard approach has been to use support and confidence. But they have their limitations. Approaches which use information about the dataset’s structure to measure association rules are limited, but could yield useful association rules if tapped. Finally, while it is important to be able to get interesting association rules from a dataset in a manageable size, it is equally as important to be able to apply them in a practical way, where the knowledge they contain can be taken advantage of. Association rules show items / attributes that appear together frequently. Recommendation systems also look at patterns and items / attributes that occur together frequently in order to make a recommendation to a person. It should therefore be possible to bring the two together. In this thesis we look at these three issues and propose approaches to help. For discovering non-redundant rules we propose enhanced approaches to rule mining in multi-level datasets that will allow hierarchically redundant association rules to be identified and removed, without information loss. When it comes to discovering interesting association rules based on the dataset’s structure we propose three measures for use in multi-level datasets. Lastly, we propose and demonstrate an approach that allows for association rules to be practically and effectively used in a recommender system, while at the same time improving the recommender system’s performance. This especially becomes evident when looking at the user cold-start problem for a recommender system. In fact our proposal helps to solve this serious problem facing recommender systems.

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Background and purpose: The appropriate fixation method for hemiarthroplasty of the hip as it relates to implant survivorship and patient mortality is a matter of ongoing debate. We examined the influence of fixation method on revision rate and mortality.----- ----- Methods: We analyzed approximately 25,000 hemiarthroplasty cases from the AOA National Joint Replacement Registry. Deaths at 1 day, 1 week, 1 month, and 1 year were compared for all patients and among subgroups based on implant type.----- ----- Results: Patients treated with cemented monoblock hemiarthroplasty had a 1.7-times higher day-1 mortality compared to uncemented monoblock components (p < 0.001). This finding was reversed by 1 week, 1 month, and 1 year after surgery (p < 0.001). Modular hemiarthroplasties did not reveal a difference in mortality between fixation methods at any time point.----- ----- Interpretation: This study shows lower (or similar) overall mortality with cemented hemiarthroplasty of the hip.

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The focus of the present research was to investigate how Local Governments in Queensland were progressing with the adoption of delineated DM policies and supporting guidelines. The study consulted Local Government representatives and hence, the results reflect their views on these issues. Is adoption occurring? To what degree? Are policies and guidelines being effectively implemented so that the objective of a safer, more resilient community is being achieved? If not, what are the current barriers to achieving this, and can recommendations be made to overcome these barriers? These questions defined the basis on which the present study was designed and the survey tools developed. While it was recognised that LGAQ and Emergency Management Queensland (EMQ) may have differing views on some reported issues, it was beyond the scope of the present study to canvass those views. The study resolved to document and analyse these questions under the broad themes of: • Building community capacity (notably via community awareness). • Council operationalisation of DM. • Regional partnerships (in mitigation/adaptation). Data was collected via a survey tool comprising two components: • An online questionnaire survey distributed via the LGAQ Disaster Management Alliance (hereafter referred to as the “Alliance”) to DM sections of all Queensland Local Government Councils; and • a series of focus groups with selected Queensland Councils

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This article presents the results of a study on the association between measured air pollutants and the respiratory health of resident women and children in Lao PDR, one of the least developed countries in Southeast Asia. The study, commissioned by the World Health Organisation, included PM10, CO and NO2 measurements made inside 181 dwellings in nine districts within two provinces in Lao PDR over a 5- month period (12/05–04/06), and respiratory health information (via questionnaires and peak expiratory flow rate (PEFR) measurements) for all residents in the same dwellings. Adjusted odds ratios were calculated separately for each health outcome using binary logistic regression. There was a strong and consistent positive association between NO2 and CO for almost all questionnaire-based health outcomes for both women and children. Women in dwellings with higher measured NO2 had more than triple of the odds of almost all of the health outcomes, and higher concentrations of NO2 and CO were significantly associated with lower PEFR. This study supports a growing literature confirming the role of indoor air pollution in the burden of respiratory disease in developing countries. The results will directly support changes in health and housing policy in Lao PDR.

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Recently, a polymorphism was identified in exon 25 of the factor V gene that is possibly a functional candidate for the HR2 haplotype. This haplotype is characterized by a single base substitution named R2 (A4070G) in the B domain of the protein. A mutation (A6755G; 2194Asp→Gly) located near the C terminus has been hypothesized to influence protein folding and glycosylation, and might be responsible for the shift in factor V isoform (FV1 / FV2) ratio. This study investigated the prevalence of these two factor V HR2 haplotype polymorphisms in a cohort of normal blood donors, patients with osteoarthritis and women with complications during pregnancy, and in families of factor V Leiden individuals. A high allele frequency for the two polymorphisms was found in the blood donor group (6.2% R2, 5.6% A6755G). No significant difference in allele frequency was observed in the clinical groups (obstetric complications and osteoarthritis, 4.1-4.9% for the two polymorphisms) when compared with that of healthy blood donors. We confirm that the factor V A6755G polymorphism shows strong linkage to the R2 allele, although it is not exclusively inherited with the exon 13 A4070G variant and can occur independently. © 2001 Lippincott Williams & Wilkins.

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Background Nitric oxide is released by immune, epithelial and endothelial cells, and plays an important part in the pathophysiology of asthma. Objective To investigate the association of inducible nitric oxide synthases (iNOS) gene repeat polymorphisms with asthma. Methods 230 families with asthma (842 individuals) were recruited to identify and establish the genetic association of iNOS repeats with asthma and associated phenotypes. Serum nitric oxide levels in selected individuals were measured and correlated with specific genotypes. Multiple logistic regression analysis was performed to determine the effect of age and sex. Results A total of four repeats—a (CCTTT)n promoter repeat, a novel intron 2 (GT)n repeat (BV680047), an intron 4 (GT)n repeat (AFM311ZB1) and an intron 5 (CA)n repeat (D17S1878)—were identified and genotyped. A significant transmission distortion to the probands with asthma was seen for allele 3 of the AFM311ZB1 gene (p = 0.006). This allele was also found to be significantly associated with percentage blood eosinophils (p<0.001) and asthma severity (p = 0.04). Moreover, it was functionally correlated with high serum nitric oxide levels (p = 0.006). Similarly, the promoter repeat was found to be associated with serum total immunoglobulin (Ig)E (p = 0.028). Individuals carrying allele 4 of this repeat have high serum IgE (p<0.001) and nitric oxide levels (p = 0.03). Conclusion This is the first study to identify the repeat polymorphisms in the iNOS gene that are associated with severity of asthma and eosinophils. The functional relevance of the associated alleles with serum nitric oxide levels was also shown. Therefore, these results could be valuable in elucidating the role of nitric oxide in asthma pathogenesis.