964 resultados para Bayesian Population Modelling
Resumo:
The two internal transcribed spacers (ITS) of ribosomal DNA are often used as markers of populations of insects. We studied the ITS2 of the head lice and body lice of humans, to determine whether this gene is a suitable marker of populations of these insects. ITS2 sequences were amplified by PCR from lice from four different countries: Australia, China, Japan and the USA. Direct cycle-sequencing of some of these PCR products gave equivocal nucleotide chromatograms. This indicated that some lice had more than one ITS2 sequence, so we cloned PCR products from these lice. Temperature gradient gel electrophoresis (TGGE) revealed that 50 of the 67 clones we screened had different nucleotide sequences. All lice had several ITS2 types, including those with unequivocal chromatograms. A phylogenetic tree of 15 different ITS2 sequences showed that the sequences from individual lice were not monophyletic. We conclude that the ITS2 is not a useful marker of populations for Pediculus humanus.
Resumo:
The thalassinidean shrimp Trypea australiensis (the yabby) commonly occurs on intertidal sandflats and subtidal regions of sheltered embayments and estuaries along the east coast of Australia and is harvested commercially and recreationally for use as bait by anglers. The potential for counts of burrow openings to provide a reliable indirect estimate of the abundance of yabbies was examined on intertidal sandflats on North Stradbroke Island (Queensland, Australia). The relationship between the number of burrow openings and the abundance of yabbies was generally poor and also varied significantly through time, casting doubt on previous estimates of abundance for this species based on unvalidated hole counts. Spatial and temporal variation in population density, the size at maturity and the reproductive period of the yabby were also assessed. Except for an initial peak in abundance as a result of recruitment, the density of yabbies was constant throughout the study but considerably less than that estimated from a previous study in the same area. Ovigerous females were recorded at 3 mm carapace length (CL) which is smaller than previously recorded for this species and thalassinideans in general. Small ovigerous females were found throughout the study, including the summer months, which is unusual for thalassinideans in the intertidal zone. It was hypothesised that in the intertidal zone, small female yabbies may be able to balance the metabolic demands of reproduction and respiration at higher temperatures than can larger females allowing them to reproduce in the warmer months.
Resumo:
This paper presents an agent-based approach to modelling individual driver behaviour under the influence of real-time traffic information. The driver behaviour models developed in this study are based on a behavioural survey of drivers which was conducted on a congested commuting corridor in Brisbane, Australia. Commuters' responses to travel information were analysed and a number of discrete choice models were developed to determine the factors influencing drivers' behaviour and their propensity to change route and adjust travel patterns. Based on the results obtained from the behavioural survey, the agent behaviour parameters which define driver characteristics, knowledge and preferences were identified and their values determined. A case study implementing a simple agent-based route choice decision model within a microscopic traffic simulation tool is also presented. Driver-vehicle units (DVUs) were modelled as autonomous software components that can each be assigned a set of goals to achieve and a database of knowledge comprising certain beliefs, intentions and preferences concerning the driving task. Each DVU provided route choice decision-making capabilities, based on perception of its environment, that were similar to the described intentions of the driver it represented. The case study clearly demonstrated the feasibility of the approach and the potential to develop more complex driver behavioural dynamics based on the belief-desire-intention agent architecture. (C) 2002 Elsevier Science Ltd. All rights reserved.
Resumo:
The present study describes patterns of co-morbidity between alcohol use and other substance use problems in the Australian population using data from the 1997 National Survey of Mental Health and Well-Being. Multiple regression analyses examined whether the observed associations between alcohol and other drug use disorders were explained by other variables, including demographic characteristics and neuroticism. We also assessed whether the presence of co-morbid substance use disorders affected treatment seeking for a mental health problem. Alcohol use was related strongly to the use of other substances. Those who did not report alcohol use within the past 12 months were less likely to report using tobacco, cannabis, sedatives, stimulants or opiates. Higher rates again were observed among those with alcohol use disorders: half (51%) of those who were alcohol-dependent were regular tobacco smokers, one-third had used cannabis (32%); 15% reported other drug use; 15% met criteria for a cannabis use disorder and 7% met criteria for another drug use disorder. These associations were not accounted for by the demographic and other variables considered here. Co-morbid substance use disorders (sedatives, stimulants or opioids) predicted a high likelihood of seeking treatment for a mental health problem among alcohol-dependent people.
Resumo:
Functional magnetic resonance imaging (FMRI) analysis methods can be quite generally divided into hypothesis-driven and data-driven approaches. The former are utilised in the majority of FMRI studies, where a specific haemodynamic response is modelled utilising knowledge of event timing during the scan, and is tested against the data using a t test or a correlation analysis. These approaches often lack the flexibility to account for variability in haemodynamic response across subjects and brain regions which is of specific interest in high-temporal resolution event-related studies. Current data-driven approaches attempt to identify components of interest in the data, but currently do not utilise any physiological information for the discrimination of these components. Here we present a hypothesis-driven approach that is an extension of Friman's maximum correlation modelling method (Neurolmage 16, 454-464, 2002) specifically focused on discriminating the temporal characteristics of event-related haemodynamic activity. Test analyses, on both simulated and real event-related FMRI data, will be presented.
Resumo:
Background and Purpose - This study was undertaken to better clarify the risks associated with cigarette smoking and subarachnoid hemorrhage (SAH). Methods - The study included 432 incident cases of SAH frequency matched to 473 community SAH-free controls to determine dose-dependent associations of active and passive smoking ( at home) and smoking cessation with SAH. Results - Compared with never smokers not exposed to passive smoking, the adjusted odds ratio for SAH among current smokers was 5.0 (95% confidence interval [CI], 3.1 to 8.1); for past smokers, 1.2 ( 95% CI, 0.8 to 2.0); and for passive smokers, 0.9 ( 95% CI, 0.6 to 1.5). Current and lifetime exposures showed a clear dose-dependent effect, and risks appeared more prominent in women and for aneurysmal SAH. Approximately 1 in 3 cases of SAH could be attributed to current smoking, but risks decline quickly after smoking cessation, even among heavy smokers. Conclusions - A strong positive association was found between cigarette smoking and SAH, especially for aneurysmal SAH and women, which is virtually eliminated within a few years of smoking cessation. Large opportunities exist for preventing SAH through smoking avoidance and cessation programs.
Resumo:
This paper addresses the investment decisions considering the presence of financial constraints of 373 large Brazilian firms from 1997 to 2004, using panel data. A Bayesian econometric model was used considering ridge regression for multicollinearity problems among the variables in the model. Prior distributions are assumed for the parameters, classifying the model into random or fixed effects. We used a Bayesian approach to estimate the parameters, considering normal and Student t distributions for the error and assumed that the initial values for the lagged dependent variable are not fixed, but generated by a random process. The recursive predictive density criterion was used for model comparisons. Twenty models were tested and the results indicated that multicollinearity does influence the value of the estimated parameters. Controlling for capital intensity, financial constraints are found to be more important for capital-intensive firms, probably due to their lower profitability indexes, higher fixed costs and higher degree of property diversification.