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The aim of this study was to explore the associations between incidence of depression and dietary intakes of foods and fatty acids in adult Australians. Data from the 1995 Australian National Nutrition Survey (NNS), the 1995 Australian National Health Survey (NHS) and an updated fatty acid database were merged and the 24-h fatty acid intakes were calculated for the 10 986 adult participants ages 18 to 79 y in the 1995 NNS. The merged data set was used to run a logistic regression with depression as the response variable and the food groups and calculated fatty acid values, age, and sex as predictors. The regression model indicated that increased intakes per kilojoule of meat, poultry, and game; vegetables; and eicosapentaenoic acid (EPA) are associated with lower odds of having depression, whereas increased intakes of non-alcoholic beverages, milk products and dishes, and docosapentaenoic acid (DPA) are associated with an increase in the odds of having depression. The results confirm a collective effect of diet on mood. Although other studies have shown that fish consumption is associated with lower odds of depression, this study showed lower odds of depression with high meat consumption, possibly reflecting the fact that Australians consume six times more meat than fish. Significant associations between food and mood identified in this study warrant further research to determine causality.

Airway mucus hypersecretion Health effects caused by air pollutants may range from subtle biochemical or physiological signs, such as mildly reduced lung function, to difficult breathing, wheezing, coughing and exacerbation of existing respiratory conditions such as asthma. The aim of this study was measuring the adverse health effects of air pollution on lung function of primary school students. The lung function of students was measured daily for seven weeks in two elementary schools in District 12 of Tehran, after obtaining permission from the two principals and signed parents' consent forms. Twenty four hourly air pollution levels were used as potential predictors of lung function. The principal analysis conducted was a logistic regression on a subset of the data using a case-crossover design. The outcomes data consisted of the results of lung function tests for 356 female and 206 male students over the six-week period. Using the difference between mean (87) and maximum (125) concentration of moving average of NO in this period to judge the size of the effect, such an increase in NO is predicted to lead to an increase in the probability of poor lung function (OR=20) based on population-based predicted value. This study has shown strong and consistent associations between children's poor lung function and outdoor air pollutants in District 12 of Tehran for some pollutants. The strong association found in this study was an increase in seven-day moving average of NO using both definitions.

This paper derives from a research project, which sets out to address practitioner dissatisfaction in the area of Knowledge Management. The author discusses common weaknesses in existing thinking about Knowledge Management and in prevailing models in particular. Modelling processes are considered and underlying assumptions that are required to be addressed in any attempt to create a Knowledge Management Model are examined. An overview is provided of the initial stages in the development of a new, synthetic and general model, The Knowledge Core©, with assumptions underlying this signposted and their influences upon modelling are discussed.

Purpose - There is conjecture that small and mid-cap companies in highly speculative industries use frequent and repetitive disclosure to promote price volatility and heighten market interest. Excessive disclosure could indicate instances of self-promotion or poor disclosure practices, and these habits could mislead investors. The purpose of this paper is to quantitatively investigate the impact of firm disclosure on price volatility in the Australian stock market. Design/methodology/approach - This paper considers the effect of information disclosure on the daily stock price volatility of 340 Metals & Mining industry entities listed on the Australian Securities Exchange over the period 2005-2007 using regression analysis. Findings - The results indicate the number of disclosures, the number of price and non-price sensitive disclosures and the number of disclosures by category has a significant influence on daily price volatility. Moreover, the volatility impact of disclosure is greater for small and mid-sized firms than large firms. Research limitations/implications - Price volatility is calculated using daily data; intra-day stock prices could provide measures that are more accurate. There is also no attempt to allow for asymmetry in disclosure; categorizing news as \"good\" or \"bad\" would allow better insights. Practical implications - There is support for the conjecture that disclosure could serve as a self-promotion tool through fabricated and repetitive announcements. Inadvertent poor disclosure practice could also result in excessive price volatility. Disclosure practice requires ongoing consideration by regulatory bodies. Originality/value - This analysis complements basic work by the Australian regulator to establish a quantitative link between disclosure practice and price volatility. [PUBLICATION ABSTRACT]

A speech by Griffiths at the Congress of the League of American Writers in 1939 is offered. Griffiths discusses the work of Louis Aragon.

There is a substantial literature on estimation for the three-parameter lognormal distribution {ln(Y - γ) ∼ N(μ,σ2)}. A large variety of estimators has been developed. The emphasis placed on alternative techniques by some of these authors is substantially due to the fact that the method of maximum likelihood has wrongly been discredited because of supposed computational difficulties and theoretical uncertainties. The literature has concentrated on point estimation with scant attention being paid to interval estimates. It is the purpose of this note to show how the interval estimation problem may be examined via the likelihood function. A comparison of these likelihood intervals, approximate and exact confidence intervals is made. Graphical examination of the likelihood function also presents a simple way of overcoming computational difficulties in obtaining point estimates (and shows why they arise), enabling a thorough examination of the information contained in the data about the model parameters and suggesting stable parameter transformations.