Playing in continuous spaces: Some analysis and extension of population-based incremental learning

As an alternative to traditional evolutionary algorithms (EAs), population-based incremental learning (PBIL) maintains a probabilistic model of the best individual(s). Originally, PBIL was applied in binary search spaces. Recently, some work has been done to extend it to continuous spaces. In this paper, we review two such extensions of PBIL. An improved version of the PBIL based on Gaussian model is proposed that combines two main features: a new updating rule that takes into account all the individuals and their fitness values and a self-adaptive learning rate parameter. Furthermore, a new continuous PBIL employing a histogram probabilistic model is proposed. Some experiments results are presented that highlight the features of the new algorithms.

Solaria use in Queensland, Australia

Objective: To describe the demographics of solarium users and the correlates of solarium use in Queensland. Methods: A cross-sectional survey of 9,419 Queensland residents was conducted via an anonymous computer-assisted telephone interview. Results: Overall, 8.8% of the respondents had ever used a solarium and less than 1% had used a solarium in the previous year. Results indicated that users were more likely to be female and younger than non-users, and less than half of the users signed a consent form, suggesting that they had not been made aware of the associated risks by operators. Conclusions: The Queensland Cancer Risk Study was one of the first population-based studies to address solarium use in this State and highlights that the use of solariums in Queensland is low in comparison to other countries. Implications: There is no regulation of compliance with guidelines. It may become necessary to make compliance with the guidelines mandatory to effectively communicate the associated risks.

The Queensland Cancer Risk Study: Behavioural risk factor results

Objective: To describe the population prevalence of key cancer risk behaviours in Queensland. Methods: The Queensland Cancer Risk Study was a population-based survey of 9,419 Queensland residents aged 20-75 years. Information was collected through an anonymous, computer-assisted telephone interview between February and November 2004. Outcome measures included tobacco smoking, alcohol consumption, sun-tanning and sunburn, obesity physical inactivity and poor diet, weighted by age, gender and geographic region. Results: Prevalence of current smoking was 25.2% for males and 20.8% for females and was highest in the 20-39 year age group and in rural/remote areas. Two-thirds of participants regularly drank alcohol; of these, 63% consumed excessive amounts of alcohol. Excessive sun exposure is still a problem; 70% of Queenslanders reported an episode of sunburn and 12% reported attempting to get a suntan in the past year. More than half of the respondents (53.9%) were above the healthy weight range, and 17.1% of males and 18.4% of females were obese. Just over 40% of Queensland adults reported having insufficient levels of physical activity. Fewer than half of the participants met recommended levels of fruit or vegetable consumption. Conclusions and implications: The majority of Queensland adults exhibit known, modifiable cancer risk behaviours. These results suggest that continuing efforts to reduce the prevalence of these risk factors are warranted. Specifically, significant gains could be made by targeting behaviour change programs at younger Queenslanders (aged 20-39 years), men, and those living in remote/ very remote areas of Queensland.

Presentation and detection of invasive melanoma in a high-risk population

Background: Early detection of melanoma has been encouraged in Queensland for many years, yet little is known about the patterns of detection and the way in which they relate to tumor thickness. Objective: Our purpose was to describe current patterns of melanoma detection in Queensland. Methods: This was a population-based study, comprising 3772 Queensland residents diagnosed with a histologically confirmed melanoma between 2000 and 2003. Results: Almost half (44.0%) of the melanomas were detected by the patients themselves, with physicians detecting one fourth (25.3%) and partners one fifth (18.6%). Melanomas detected by doctors were more likely to be thin (\0.75 mm) than those detected by the patient or other layperson. Melanomas detected during a deliberate skin examination were thinner than those detected incidentally. Limitations: Although a participation rate of 78% was achieved, as in any survey, nonresponse bias cannot be completely excluded, and the ability of the results to be generalized to other geographical areas is unknown. Conclusion: There are clear differences in the depth distribution of melanoma in terms of method of detection and who detects the lesions that are consistent with, but do not automatically lead to, the conclusion that promoting active methods of detection may be beneficial. ( J Am Acad Dermatol 2006;54:783-92.)

Weight gained in two years by a population of mid-aged women: how much is too much?

Objective: To establish the prevalence of weight change in mid-aged women over a 2-year period, and to assess the relationship between weight change and physical and mental well-being (SF36) in order to begin debate about the need for quantified standards of weight gain. Design: Prospective study of weight change and well-being over a 2-year period among mid-aged women participating in a large national survey. Subjects: Seven thousand two hundred and seventy women without surgical menopause aged between 45 and 50 years (termed mid-aged), enrolled in the Australian Longitudinal Study on Women's Health. Measurements: Weight change (self-reported weight at two time points) and physical and mental well-being (SF-36) explored using linear regression, while adjusting for potential confounders. Results: Only half the women maintained their weight within 2.25 kg, and one-third gained more than this amount in a 2-year period. While weight gain (>= 2.25 kg) was negatively associated with physical well-being, both weight loss and weight gain were associated with poorer mental well-being. Conclusion: This is the first prospective study using a large, population-based cohort to demonstrate that small changes in weight are associated with changes in well-being in mid-aged Australian women. It provides further evidence of the need for public health messages to specify the actual amount that constitutes weight gain, but further research is needed to establish these standards for the entire population.