The Coefficient of Variance as an index of L2 lexical processing skill

The Coefficient of Variance (mean standard deviation/mean Response time) is a measure of response time variability that corrects for differences in mean Response time (RT) (Segalowitz & Segalowitz, 1993). A positive correlation between decreasing mean RTs and CVs (rCV-RT) has been proposed as an indicator of L2 automaticity and more generally as an index of processing efficiency. The current study evaluates this claim by examining lexical decision performance by individuals from three levels of English proficiency (Intermediate ESL, Advanced ESL and L1 controls) on stimuli from four levels of item familiarity, as defined by frequency of occurrence. A three-phase model of skill development defined by changing rCV-RT.values was tested. Results showed that RTs and CVs systematically decreased as a function of increasing proficiency and frequency levels, with the rCV-RT serving as a stable indicator of individual differences in lexical decision performance. The rCV-RT and automaticity/restructuring account is discussed in light of the findings. The CV is also evaluated as a more general quantitative index of processing efficiency in the L2.

Index of refraction of a two-level atom in a squeezed vacuum field

We study the index of refraction of a two-level atom replacing the usually applied coherent driving fields by a squeezed vacuum field. This system can produce a large index of refraction accompanied by vanishing absorption when the carrier frequency of the squeezed vacuum is detuned from the atomic resonance. (C) 1998 Elsevier Science B.V.

Squeezing-induced complete transparency in two-level systems

The modification of the statistical properties of vacuum fluctuations, via quadrature squeezing, can dramatically reduce the absorptive and dispersive properties of two-level atoms. We show that for some range of parameter values the system exhibits zero absorption accompanied by zero dispersion of the probe field. This complete transparency is attributed to the coherent population oscillations induced by the squeezed vacuum.

Temperature and sowing date affect the linear increase of sunflower harvest index

The linearity of daily linear harvest index (HI) increase can provide a simple means to predict grain growth and yield in field crops. However, the stability of the rate of increase across genotypes and environments is uncertain. Data from three field experiments were collated to investigate the phase of linear HI increase of sunflower (Helianthus annuus L,) across environments by changing genotypes, sowing time, N level, and solar irradiation level. Linear increase in HI was similar among different genotypes, N levels, and radiation treatments (mean 0.0125 d(-1)). but significant differences occurred between sowings, The linear increase in HI was not stable at very low temperatures (down to 9 degrees C) during grain filling, due to possible limitations to biomass accumulation and translocation (mean 0.0091 d(-1)). Using the linear increase in HI to predict grain yield requires predictions of the duration from anthesis to the onset of linear HI increase (lag phase) and the cessation of linear RT increase. These studies showed that the lag phase differed, and the linear HI increase ceased when 91% of the anthesis to physiological maturity period had been completed.

Coronary events and exposure to environmental tobacco smoke: a case-control study from Australia and New Zealand

Objectives-To estimate the relative risk of coronary heart disease (CHD) associated with exposure to environmental tobacco smoke (ETS). Design-Population-based case-control study. Subjects-Cases were 953 people identified in a population register of coronary events, and controls were 3189 participants in independent community-based risk factor prevalence surveys from the same study populations. Setting-Newcastle, Australia and Auckland, New Zealand. Main outcome measures-Acute myocardial infarction or coronary death. Results-After adjusting for the effects of age, education, history of heart disease, and body mass index, women had a statistically significant increased risk of a coronary event associated with exposure to ETS (relative risk (RR) = 1.99; 95% confidence interval (CI)= 1.40-2.81). There was little statistical evidence of increased risk found in men (RR = 1.02, 95% CI = 0.81-1.28). Conclusion-Our study found evidence for the adverse effects of exposure to ETS on risk of coronary heart disease among women, especially at home. For men the issue is unclear according to the data from our study. Additional studies with detailed information on possible confounders and adequate statistical power are needed. Most importantly, they should use methods for measuring exposure to ETS that are sufficiently accurate to permit the investigation of dose-response relationships.

A mathematical model for estimating the extent of solute- and water-flux heterogeneity in multiple sample percolation experiments

Multiple sampling is widely used in vadose zone percolation experiments to investigate the extent in which soil structure heterogeneities influence the spatial and temporal distributions of water and solutes. In this note, a simple, robust, mathematical model, based on the beta-statistical distribution, is proposed as a method of quantifying the magnitude of heterogeneity in such experiments. The model relies on fitting two parameters, alpha and zeta to the cumulative elution curves generated in multiple-sample percolation experiments. The model does not require knowledge of the soil structure. A homogeneous or uniform distribution of a solute and/or soil-water is indicated by alpha = zeta = 1, Using these parameters, a heterogeneity index (HI) is defined as root 3 times the ratio of the standard deviation and mean. Uniform or homogeneous flow of water or solutes is indicated by HI = 1 and heterogeneity is indicated by HI > 1. A large value for this index may indicate preferential flow. The heterogeneity index relies only on knowledge of the elution curves generated from multiple sample percolation experiments and is, therefore, easily calculated. The index may also be used to describe and compare the differences in solute and soil-water percolation from different experiments. The use of this index is discussed for several different leaching experiments. (C) 1999 Elsevier Science B.V. All rights reserved.

Between-year fluctuations in schizophrenia birth rate and associations with the Southern Oscillation Index, cloud cover and sunshine

Our group have recently proposed that low prenatal vitamin D may be a risk-modifying factor for schizophrenia. Climate variability impacts on vitamin D levels in a population via fluctuations in the amount of available UV radiation. In order to explore this hypothesis, we examined fluctuations in the birthrates for people with schizophrenia born between 1920 and 1967 and three sets of variables strongly associated with UV radiation. These included: (a) the Southern Oscillation Index (SOI), a marker of El Nino which is the most prominent meteorological factor that influences Queensland weather: (b) measures of cloud cover and (c) measures of sunshine. Schizophrenia births were extracted from the Queensland Mental Health register and corrected for background population birth rates. Schizophrenia birth rates had several apparently non-random features in common with the SO1. The prominent SO1 fluctuation event that occurred between 1937 and 1943 is congruent with the most prominent fluctuation in schizophrenia birth rates. The relatively flat profile of SOI activity between 1927 and 1936 also corresponds to the flattest period in the schizophrenia time series. Both time series have prominent oscillations in the 3 ~, year range between 1946 and 1960. Significant associations between schizophrenia birth rates and measures of both sunshine and cloud cover were identified,and all three time series shared periodicity in the 3-4 year range. The analyses suggest that the risk of schizophrenia is higher for those born during times of increased cloud cover,reduced sunshine and positive SO1. These ecological analyses provide initial support for the vitamin D hypothesis, however alternative non-genetic candidate exposures also need to be considered. Other sites with year-to-year fluctuations in cloud cover and sunshine should examine patterns of association between these climate variables and schizophrenia birth rates. The Stanley Foundation supported this project.

Long range forecasts of the numbers of Helicoverpa punctigera and H-armigera (Lepidoptera : Noctuidae) in Australia using the Southern Oscillation Index and the Sea Surface Temperature

The use of long-term forecasts of pest pressure is central to better pest management. We relate the Southern Oscillation Index (SOI) and the Sea Surface Temperature (SST) to long-term light-trap catches of the two key moth pests of Australian agriculture, Helicoverpa punctigera (Wallengren) and H. armigera (Hubner), at Narrabri, New South Wales over 11 years, and for H. punctigera only at Turretfield, South Australia over 22 years. At Narrabri, the size of the first spring generation of both species was significantly correlated with the SOI in certain months, sometimes up to 15 months before the date of trapping. Differences in the SOI and SST between significant months were used to build composite variables in multiple regressions which gave fitted values of the trap catches to less than 25% of the observed values. The regressions suggested that useful forecasts of both species could be made 6-15 months ahead. The influence of the two weather variables on trap catches of H. punctigera at Turretfield were not as strong as at Narrabri, probably because the SOI was not as strongly related to rainfall in southern Australia as it is in eastern Australia. The best fits were again given by multiple regressions with SOI plus SST variables, to within 40% of the observed values. The reliability of both variables as predictors of moth numbers may be limited by the lack of stability in the SOI-rainfall correlation over the historical record. As no other data set is available to test the regressions, they can only be tested by future use. The use of long-term forecasts in pest management is discussed, and preliminary analyses of other long sets of insect numbers suggest that the Southern Oscillation Index may be a useful predictor of insect numbers in other parts of the world.

The line structure of balanced ternary designs with block size three, index three and rho(2) = 1, 2

In this paper necessary and sufficient conditions for a vector to be the fine structure of a balanced ternary design with block size 3, index 3 and rho(2) = 1 and 2 are determined with one unresolved case.

Mortality variation across Australia: descriptive data for States and Territories, and statistical divisions

OBJECTIVE: To describe variation in all cause and selected cause-specific mortality rates across Australia. METHODS: Mortality and population data for 1997 were obtained from the Australian Bureau of Statistics. All cause and selected cause-specific mortality rates were calculated and directly standardised to the 1997 Australian population in 5-year age groups. Selected major causes of death included cancer, coronary artery disease, cerebrovascular disease, diabetes, accidents and suicide. Rates are reported by statistical division, and State and Territory. RESULTS: All cause age-standardised mortality was 6.98 per 1000 in 1997 and this varied 2-fold from a low in the statistical division of Pilbara, Western Australia (5.78, 95% confidence interval 5.06-6.56), to a high in Northern Territory-excluding Darwin (11.30, 10.67-11.98). Similar mortality variation (all p<0.0001) exists for cancer (1.01-2.23 per 1000) and coronary artery disease (0.99-2.23 per 1000), the two biggest killers. Larger variation (all p<0.0001) exists for cerebrovascular disease (0.7-11.8 per 10,000), diabetes (0.7-6.9 per 10,000), accidents (1.7-7.2 per 10,000) and suicide (0.6-3.8 per 10,000). Less marked variation was observed when analysed by State and Territory. but Northern Territory consistently has the highest age-standardised mortality rates. CONCLUSIONS: Analysed by statistical division, substantial mortality gradients exist across Australia, suggesting an inequitable distribution of the determinants of health. Further research is required to better understand this heterogeneity.

Relationships between body mass index and well-being in young Australian women

OBJECTIVE: To explore relationships between body mass index (BMI, kg/m(2)) and indicators of health and well-being in young Australian women. DESIGN: Population based cohort study-baseline cross sectional data. SUBJECTS: 14,779 women aged 18-23 who participated in the baseline survey of the Australian Longitudinal Study on Women's Health in 1996. MEASUREMENTS: Self-reported height, weight, medical conditions, symptoms and SF-36. RESULTS: The majority of women (68%) had a BMI in the range 18.5-

Increasingly inequitable distribution of general practitioners in Australia, 1986-96

Objective: To document trends in the distribution of general practitioners (GPs) in Australia between 1986 and 1996, adjusted for community need. Methods: Data on the location of GPs, population size and crude mortality in statistical divisions (SD) were obtained from the Australian Bureau of Statistics Census of Population and Housing in 1986 and 1996. From these data, we calculated measures of distribution equality (number of people sharing each GP in each SD) and distribution equity (number of people sharing each GP divided by the crude mortality rate; the Robin Hood Index), and analysed temporal changes in the distribution of GPs. Results: Nationally the number of people sharing each GP fell 11% from 1,038 in 1986 to 921 in 1996. However, in 41 of 57 SDs (72%, p=0.01) the number of people sharing a GP actually increased over this time, and the average Robin Hood Index across SDs fell from 0.943 to 0.783 (p=0.004), indicating increasingly inequitable distribution. Comparing the Robin Hood index values of all SDs ranked in pairs, the value fell in 53 of 57 (93%, p<0.001) paired SDs over the decade. These patterns demonstrate increasing inequity over the decade. The number of people sharing each GP was consistently and substantially lower in the capital city SDs and the Robin Hood Index values were consistently and substantially higher (overserved) compared with country SDs. Conclusions: Despite there being more GPs per capita in Australia, their distribution became increasingly unequal and inequitable between 1986 and 1996, such that rural and remote areas became increasingly poorly served.

Variation in mortality rates in Australia: correlation with Indigenous status, remoteness and socio-economic deprivation

Background The aim of this study was to study ecological correlations between age-adjusted all-cause mortality rates in Australian statistical divisions and (1) the proportion of residents that self-identify as Indigenous, (2) remoteness, and (3) socio-economic deprivation. Methods All-cause mortality rates for 57 statistical divisions were calculated and directly standardized to the 1997 Australian population in 5-year age groups using Australian Bureau of Statistics (ABS) data. The proportion of residents who self-identified as Indigenous was obtained from the 1996 Census. Remoteness was measured using ARIA (Accessibility and Remoteness Index for Australia) values. Socioeconomic deprivation was measured using SEIFA (Socio-Economic index for Australia) values from the ABS. Results Age-standardized all-cause mortality varies twofold from 5.7 to 11.3 per 1000 across Australian statistical divisions. Strongest correlation was between Indigenous status and mortality (r = 0.69, p < 0.001). correlation between remoteness and mortality was modest (r = 0.39, p = 0.002) as was correlation between socio-economic deprivation and mortality (r = -0.42, p = 0.001). Excluding the three divisions with the highest mortality, a multiple regression model using the logarithm of the adjusted mortality rate as the dependent variable showed that the partial correlation (and hence proportion of the variance explained) for Indigenous status was 0.03 (9 per cent; p = 0.03), for SEIFA score was -0.17 (3 per cent; p = 0.22); and for remoteness was -0.22 (5 per cent; p = 0.13). Collectively, the three variables studied explain 13 per cent of the variability in mortality. Conclusions Ecological correlation exists between all-cause mortality, Indigenous status, remoteness and disadvantage across Australia. The strongest correlation is with indigenous status, and correlation with all three characteristics is weak when the three statistical divisions with the highest mortality rates are excluded. intervention targeted at these three statistical divisions could reduce much of the variability in mortality in Australia.