960 resultados para Kernel density estimates


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Despite its potential multiple contributions to sustainable policy objectives, urban transit is generally not widely used by the public in terms of its market share compared to that of automobiles, particularly in affluent societies with low-density urban forms like Australia. Transit service providers need to attract more people to transit by improving transit quality of service. The key to cost-effective transit service improvements lies in accurate evaluation of policy proposals by taking into account their impacts on transit users. If transit providers knew what is more or less important to their customers, they could focus their efforts on optimising customer-oriented service. Policy interventions could also be specified to influence transit users’ travel decisions, with targets of customer satisfaction and broader community welfare. This significance motivates the research into the relationship between urban transit quality of service and its user perception as well as behaviour. This research focused on two dimensions of transit user’s travel behaviour: route choice and access arrival time choice. The study area chosen was a busy urban transit corridor linking Brisbane central business district (CBD) and the St. Lucia campus of The University of Queensland (UQ). This multi-system corridor provided a ‘natural experiment’ for transit users between the CBD and UQ, as they can choose between busway 109 (with grade-separate exclusive right-of-way), ordinary on-street bus 412, and linear fast ferry CityCat on the Brisbane River. The population of interest was set as the attendees to UQ, who travelled from the CBD or from a suburb via the CBD. Two waves of internet-based self-completion questionnaire surveys were conducted to collect data on sampled passengers’ perception of transit service quality and behaviour of using public transit in the study area. The first wave survey is to collect behaviour and attitude data on respondents’ daily transit usage and their direct rating of importance on factors of route-level transit quality of service. A series of statistical analyses is conducted to examine the relationships between transit users’ travel and personal characteristics and their transit usage characteristics. A factor-cluster segmentation procedure is applied to respodents’ importance ratings on service quality variables regarding transit route preference to explore users’ various perspectives to transit quality of service. Based on the perceptions of service quality collected from the second wave survey, a series of quality criteria of the transit routes under study was quantitatively measured, particularly, the travel time reliability in terms of schedule adherence. It was proved that mixed traffic conditions and peak-period effects can affect transit service reliability. Multinomial logit models of transit user’s route choice were estimated using route-level service quality perceptions collected in the second wave survey. Relative importance of service quality factors were derived from choice model’s significant parameter estimates, such as access and egress times, seat availability, and busway system. Interpretations of the parameter estimates were conducted, particularly the equivalent in-vehicle time of access and egress times, and busway in-vehicle time. Market segmentation by trip origin was applied to investigate the difference in magnitude between the parameter estimates of access and egress times. The significant costs of transfer in transit trips were highlighted. These importance ratios were applied back to quality perceptions collected as RP data to compare the satisfaction levels between the service attributes and to generate an action relevance matrix to prioritise attributes for quality improvement. An empirical study on the relationship between average passenger waiting time and transit service characteristics was performed using the service quality perceived. Passenger arrivals for services with long headways (over 15 minutes) were found to be obviously coordinated with scheduled departure times of transit vehicles in order to reduce waiting time. This drove further investigations and modelling innovations in passenger’ access arrival time choice and its relationships with transit service characteristics and average passenger waiting time. Specifically, original contributions were made in formulation of expected waiting time, analysis of the risk-aversion attitude to missing desired service run in the passengers’ access time arrivals’ choice, and extensions of the utility function specification for modelling passenger access arrival distribution, by using complicated expected utility forms and non-linear probability weighting to explicitly accommodate the risk of missing an intended service and passenger’s risk-aversion attitude. Discussions on this research’s contributions to knowledge, its limitations, and recommendations for future research are provided at the concluding section of this thesis.

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We estimated the heritability and correlations between body and carcass weight traits in a cultured stock of giant freshwater prawn (GFP) (Macrobrachium rosenbergii) selected for harvest body weight in Vietnam. The data set consisted of 18,387 body and 1,730 carcass records, as well as full pedigree information collected over four generations. Variance and covariance components were estimated by restricted maximum likelihood fitting a multi-trait animal model. Across generations, estimates of heritability for body and carcass weight traits were moderate and ranged from 0.14 to 0.19 and 0.17 to 0.21, respectively. Body trait heritabilities estimated for females were significantly higher than for males whereas carcass weight trait heritabilities estimated for females and males were not significantly different (P>. 0.05). Maternal effects for body traits accounted for 4 to 5% of the total variance and were greater in females than in males. Genetic correlations among body traits were generally high in the mixed sexes. Genetic correlations between body and carcass weight traits were also high. Although some issues remain regarding the best statistical model to be fitted to GFP data, our results suggest that selection for high harvest body weight based on breeding values estimated by fitting an animal model to the data can significantly improve mean body and carcass weight in GFP.

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This research aims to develop a reliable density estimation method for signalised arterials based on cumulative counts from upstream and downstream detectors. In order to overcome counting errors associated with urban arterials with mid-link sinks and sources, CUmulative plots and Probe Integration for Travel timE estimation (CUPRITE) is employed for density estimation. The method, by utilizing probe vehicles’ samples, reduces or cancels the counting inconsistencies when vehicles’ conservation is not satisfied within a section. The method is tested in a controlled environment, and the authors demonstrate the effectiveness of CUPRITE for density estimation in a signalised section, and discuss issues associated with the method.

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The Low-Density Lipoprotein Receptor (LDLR) gene is a cell surface receptor that plays an important role in cholesterol homeostasis. We investigated the (TA)n polymorphism in exon 18 of the LDLR gene on chromosome 19p13.2 performing an association analysis in 244 typical migraine-affected patients, 151 suffering from migraine with aura (MA), 96 with migraine without aura (MO) and 244 unaffected controls. The populations consisted of Caucasians only, and controls were age- and sex-matched. The results showed no significant difference between groups for allele frequency distributions of the (TA)n polymorphism even after separation of the migraine-affected individuals into subgroups of MA and MO affected patients. This is in contradiction to Mochi et al. who found a positive association of this variant with MO. Our study discusses possible differences between the two studies and extends this research by investigating circulating cholesterol levels in a migraine-affected population.

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RFLPs at the low density lipoprotein receptor locus (LDLR) display marked linkage disequilibrium between each other. Cross-sectional analysis of a bi-alleleic ApaLI RFLP of LDLR showed that the 9.4- and 6.6-kb alleles were present in similar frequency between a group of 84 Caucasian essential hypertensive (HT) and a group of 96 normotensive subjects whose parents each had a similar blood pressure status at age > or = 50. After subdividing HTs into lean and obese, however, the frequency of the 6.6-kb allele in the 27 HTs with BMI > or = 26 kg/m2 was 0.63, compared with 0.39 for HTs with BMI < 26 (chi 2 = 8.8; P = 0.004). The difference in genotype frequencies was even more striking (chi 2 = 23; P = 0.00008), with a virtual absence of 9.4-kb homozygotes in the obese HT group (1 vs 22). Genetic variation at LDLR (19p13.2) is thus associated with obesity in HT.

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OBJECTIVE To determine whether a microsatellite polymorphism located towards the 3' end of the low density lipoprotein receptor gene (LDLR) is associated with obesity. DESIGN A cross-sectional case-control study. SUBJECTS One hundred and seven obese individuals, defined as a body mass index (BMI) ≤ 26 kg/m2, and 163 lean individuals, defined as a BMI < 26 kg/m2. MEASUREMENTS BMI, blood pressure, serum lipids, alleles of LDLR microsatellite (106 bp, 108 bp and 112 bp). RESULTS There was a significant association between variants of the LDLR microsatellite and obesity, in the overall tested population, due to a contributing effect in females (χ2 = 12.3, P = 0.002), but not in males (χ2 = 0.3, P = 0.87). In females, individuals with the 106 bp allele were more likely to be lean, while individuals with the 112 bp and/or 108 bp alleles tended to be obese. CONCLUSIONS These results suggest that in females, LDLR may play a role in the development of obesity.

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Obese (BMI ≥ 26 kg/m 2; n = 51) and lean (BMI <26 kg/m 2; n = 61) Caucasian patients with severe, familial essential hypertension, were compared with respect to genotype and allele frequencies of a HincII RFLP of the low density lipoprotein receptor gene (LDLR). A similar analysis was performed in obese (n = 28) and lean (n = 68) normotensives. A significant association of the C allele of the T→C variant responsible for this RFLP was seen with obesity (χ 2 = 4.6, P = 0.029) in the hypertensive, but not in the normotensive, group (odds ratio = 3.0 for the CC genotype and 2.7 for CT). Furthermore, BMI tracked with genotypes of this allele in the hypertensives (P = 0.046). No significant genotypic relationship was apparent for plasma lipids. Significant linkage disequilibrium was, moreover, noted between the HincII RFLP and an ApaLI RFLP (χ 2 = 33, P<0.0005) that has previously shown even stronger association with obesity (odds ratio 19.6 for cases homozygous for the susceptibility allele and 15.2 for het-erozygotes). The present study therefore adds to our previous evidence implicating LDLR as a locus for obesity in patients with essential hypertension.

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This project was a step forward in developing intrusion detection systems in distributed environments such as web services. It investigates a new approach of detection based on so-called "taint-marking" techniques and introduces a theoretical framework along with its implementation in the Linux kernel.

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As Earth's climate is rapidly changing, the impact of ambient temperature on health outcomes has attracted increasing attention in the recent time. Considerable number of excess deaths has been reported because of exposure to ambient hot and cold temperatures. However, relatively little research has been conducted on the relation between temperature and morbidity. The aim of this study was to characterize the relationship between both hot and cold temperatures and emergency hospital admissions in Brisbane, Australia, and to examine whether the relation varied by age and socioeconomic factors. It aimed to explore lag structures of temperature–morbidity association for respiratory causes, and to estimate the magnitude of emergency hospital admissions for cardiovascular diseases attributable to hot and cold temperatures for the large contribution of both diseases to the total emergency hospital admissions. A time series study design was applied using routinely collected data of daily emergency hospital admissions, weather and air pollution variables in Brisbane during 1996–2005. Poisson regression model with a distributed lag non-linear structure was adopted to assess the impact of temperature on emergency hospital admissions after adjustment for confounding factors. Both hot and cold effects were found, with higher risk of hot temperatures than that of cold temperatures. Increases in mean temperature above 24.2oC were associated with increased morbidity, especially for the elderly ≥ 75 years old with the largest effect. The magnitude of the risk estimates of hot temperature varied by age and socioeconomic factors. High population density, low household income, and unemployment appeared to modify the temperature–morbidity relation. There were different lag structures for hot and cold temperatures, with the acute hot effect within 3 days after hot exposure and about 2-week lagged cold effect on respiratory diseases. A strong harvesting effect after 3 days was evident for respiratory diseases. People suffering from cardiovascular diseases were found to be more vulnerable to hot temperatures than cold temperatures. However, more patients admitted for cardiovascular diseases were attributable to cold temperatures in Brisbane compared with hot temperatures. This study contributes to the knowledge base about the association between temperature and morbidity. It is vitally important in the context of ongoing climate change. The findings of this study may provide useful information for the development and implementation of public health policy and strategic initiatives designed to reduce and prevent the burden of disease due to the impact of climate change.

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As of June 2009, 361 genome-wide association studies (GWAS) had been referenced by the HuGE database. GWAS require DNA from many thousands of individuals, relying on suitable DNA collections. We recently performed a multiple sclerosis (MS) GWAS where a substantial component of the cases (24%) had DNA derived from saliva. Genotyping was done on the Illumina genotyping platform using the Infinium Hap370CNV DUO microarray. Additionally, we genotyped 10 individuals in duplicate using both saliva- and blood-derived DNA. The performance of blood- versus saliva-derived DNA was compared using genotyping call rate, which reflects both the quantity and quality of genotyping per sample and the “GCScore,” an Illumina genotyping quality score, which is a measure of DNA quality. We also compared genotype calls and GCScores for the 10 sample pairs. Call rates were assessed for each sample individually. For the GWAS samples, we compared data according to source of DNA and center of origin. We observed high concordance in genotyping quality and quantity between the paired samples and minimal loss of quality and quantity of DNA in the saliva samples in the large GWAS sample, with the blood samples showing greater variation between centers of origin. This large data set highlights the usefulness of saliva DNA for genotyping, especially in high-density single-nucleotide polymorphism microarray studies such as GWAS.

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This research aims to develop a reliable density estimation method for signalised arterials based on cumulative counts from upstream and downstream detectors. In order to overcome counting errors associated with urban arterials with mid-link sinks and sources, CUmulative plots and Probe Integration for Travel timE estimation (CUPRITE) is employed for density estimation. The method, by utilizing probe vehicles’ samples, reduces or cancels the counting inconsistencies when vehicles’ conservation is not satisfied within a section. The method is tested in a controlled environment, and the authors demonstrate the effectiveness of CUPRITE for density estimation in a signalised section, and discuss issues associated with the method.

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A qualitative analysis of the expected dilatation strain field in the vicinity of an array of grain-boundary (GB) dislocations is presented. The analysis provides a basis for the prediction of the critical current densities (jc) across low-angle YBa2Cu3O7- (YBCO) GBs as a function of their energy. The introduction of the GB energy allows the extension of the analysis to high-angle GBs using established models which predict the GB energy as a function of misorientation angle. The results are compared to published data for jc across [001]-tilt YBCO GBs for the full range of misorientations, showing a good fit. Since the GB energy is directly related to the GB structure, the analysis may allow a generalization of the scaling behavior of jc with the GB energy. © 1995 The American Physical Society.

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Using ZnO seed layers, an efficient approach for enhancing the heterointerface quality of electrodeposited ZnO–Cu2O solar cells is devised. We introduce a sputtered ZnO seed layer followed by the sequential electrodeposition of ZnO and Cu2O films. The seed layer is employed to control the growth and crystallinity and to augment the surface area of the electrodeposited ZnO films, thereby tuning the quality of the ZnO–Cu2O heterointerface. Additionally, the seed layer also assists in forming high quality ZnO films, with no pin-holes, in a high pH electrolyte solution. X-ray electron diffraction patterns, scanning electron and atomic force microscopy images, as well as photovoltaic measurements, clearly demonstrate that the incorporation of certain seed layers results in the alteration of the heterointerface quality, a change in the heterojunction area and the crystallinity of the films near the junction, which influence the current density of photovoltaic devices.

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Climate change is expected to be one of the biggest global health threats in the 21st century. In response to changes in climate and associated extreme events, public health adaptation has become imperative. This thesis examined several key issues in this emerging research field. The thesis aimed to identify the climate-health (particularly temperature-health) relationships, then develop quantitative models that can be used to project future health impacts of climate change, and therefore help formulate adaptation strategies for dealing with climate-related health risks and reducing vulnerability. The research questions addressed by this thesis were: (1) What are the barriers to public health adaptation to climate change? What are the research priorities in this emerging field? (2) What models and frameworks can be used to project future temperature-related mortality under different climate change scenarios? (3) What is the actual burden of temperature-related mortality? What are the impacts of climate change on future burden of disease? and (4) Can we develop public health adaptation strategies to manage the health effects of temperature in response to climate change? Using a literature review, I discussed how public health organisations should implement and manage the process of planned adaptation. This review showed that public health adaptation can operate at two levels: building adaptive capacity and implementing adaptation actions. However, there are constraints and barriers to adaptation arising from uncertainty, cost, technologic limits, institutional arrangements, deficits of social capital, and individual perception of risks. The opportunities for planning and implementing public health adaptation are reliant on effective strategies to overcome likely barriers. I proposed that high priorities should be given to multidisciplinary research on the assessment of potential health effects of climate change, projections of future health impacts under different climate and socio-economic scenarios, identification of health cobenefits of climate change policies, and evaluation of cost-effective public health adaptation options. Heat-related mortality is the most direct and highly-significant potential climate change impact on human health. I thus conducted a systematic review of research and methods for projecting future heat-related mortality under different climate change scenarios. The review showed that climate change is likely to result in a substantial increase in heatrelated mortality. Projecting heat-related mortality requires understanding of historical temperature-mortality relationships, and consideration of future changes in climate, population and acclimatisation. Further research is needed to provide a stronger theoretical framework for mortality projections, including a better understanding of socioeconomic development, adaptation strategies, land-use patterns, air pollution and mortality displacement. Most previous studies were designed to examine temperature-related excess deaths or mortality risks. However, if most temperature-related deaths occur in the very elderly who had only a short life expectancy, then the burden of temperature on mortality would have less public health importance. To guide policy decisions and resource allocation, it is desirable to know the actual burden of temperature-related mortality. To achieve this, I used years of life lost to provide a new measure of health effects of temperature. I conducted a time-series analysis to estimate years of life lost associated with changes in season and temperature in Brisbane, Australia. I also projected the future temperaturerelated years of life lost attributable to climate change. This study showed that the association between temperature and years of life lost was U-shaped, with increased years of life lost on cold and hot days. The temperature-related years of life lost will worsen greatly if future climate change goes beyond a 2 °C increase and without any adaptation to higher temperatures. The excess mortality during prolonged extreme temperatures is often greater than the predicted using smoothed temperature-mortality association. This is because sustained period of extreme temperatures produce an extra effect beyond that predicted by daily temperatures. To better estimate the burden of extreme temperatures, I estimated their effects on years of life lost due to cardiovascular disease using data from Brisbane, Australia. The results showed that the association between daily mean temperature and years of life lost due to cardiovascular disease was U-shaped, with the lowest years of life lost at 24 °C (the 75th percentile of daily mean temperature in Brisbane), rising progressively as temperatures become hotter or colder. There were significant added effects of heat waves, but no added effects of cold spells. Finally, public health adaptation to hot weather is necessary and pressing. I discussed how to manage the health effects of temperature, especially with the context of climate change. Strategies to minimise the health effects of high temperatures and climate change can fall into two categories: reducing the heat exposure and managing the health effects of high temperatures. However, policy decisions need information on specific adaptations, together with their expected costs and benefits. Therefore, more research is needed to evaluate cost-effective adaptation options. In summary, this thesis adds to the large body of literature on the impacts of temperature and climate change on human health. It improves our understanding of the temperaturehealth relationship, and how this relationship will change as temperatures increase. Although the research is limited to one city, which restricts the generalisability of the findings, the methods and approaches developed in this thesis will be useful to other researchers studying temperature-health relationships and climate change impacts. The results may be helpful for decision-makers who develop public health adaptation strategies to minimise the health effects of extreme temperatures and climate change.