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.

Stochastic structure and individual-tree growth models

The majority of past and current individual-tree growth modelling methodologies have failed to characterise and incorporate structured stochastic components. Rather, they have relied on deterministic predictions or have added an unstructured random component to predictions. In particular, spatial stochastic structure has been neglected, despite being present in most applications of individual-tree growth models. Spatial stochastic structure (also called spatial dependence or spatial autocorrelation) eventuates when spatial influences such as competition and micro-site effects are not fully captured in models. Temporal stochastic structure (also called temporal dependence or temporal autocorrelation) eventuates when a sequence of measurements is taken on an individual-tree over time, and variables explaining temporal variation in these measurements are not included in the model. Nested stochastic structure eventuates when measurements are combined across sampling units and differences among the sampling units are not fully captured in the model. This review examines spatial, temporal, and nested stochastic structure and instances where each has been characterised in the forest biometry and statistical literature. Methodologies for incorporating stochastic structure in growth model estimation and prediction are described. Benefits from incorporation of stochastic structure include valid statistical inference, improved estimation efficiency, and more realistic and theoretically sound predictions. It is proposed in this review that individual-tree modelling methodologies need to characterise and include structured stochasticity. Possibilities for future research are discussed. (C) 2001 Elsevier Science B.V. All rights reserved.

Content and context of monocular regions determine perceived depth in random dot, unpaired background and phantom stereograms

Perceived depth was measured for three-types of stereograms with the colour/texture of half-occluded (monocular) regions either similar to or dissimilar to that of binocular regions or background. In a two-panel random dot stereogram the monocular region was filled with texture either similar or different to the far panel or left blank. In unpaired background stereograms the monocular region either matched the background or was different in colour or texture and in phantom stereograms the monocular region matched the partially occluded object or was a different colour or texture. In all three cases depth was considerably impaired when the monocular texture did not match either the background or the more distant surface. The content and context of monocular regions as well as their position are important in determining their role as occlusion cues and thus in three-dimensional layout. We compare coincidence and accidental view accounts of these effects. (C) 2002 Elsevier Science Ltd. All rights reserved.

Thermal ecology and structural habitat use of two sympatric lizards (Carlia vivax and Lygisaurus foliorum) in subtropical Australia

The thermal ecology and structural habitat use of two closely related sympatric lizards, Carlia vivax (de Vis) and Lygisaurus foliorum de Vis, were examined in an open sclerophyll forest in subtropical Australia. Comparable mean body temperatures (T-b) and habitat temperatures (T-hab) at the point of capture were recorded for both species. However, sex- related differences in the thermal variables for C. vivax, with females displaying higher temperatures than males, resulted in some significant differences in T-b and T-hab between the species. Variation in T-b and T-hab within and between species was unrelated to time of capture. The difference in T-hab within C. vivax suggested that females were selecting warmer thermal environments than males. Both C. vivax and L. foliorum used most structural features of their habitat randomly as indicated by a similarity in canopy, shrub, ground, log and litter cover and litter depth between habitat surveys and random surveys. However, C. vivax displayed a preference for ground vegetation (height

Genetic algorithms for design of liquid retaining structure

In this paper, genetic algorithm (GA) is applied to the optimum design of reinforced concrete liquid retaining structures, which comprise three discrete design variables, including slab thickness, reinforcement diameter and reinforcement spacing. GA, being a search technique based on the mechanics of natural genetics, couples a Darwinian survival-of-the-fittest principle with a random yet structured information exchange amongst a population of artificial chromosomes. As a first step, a penalty-based strategy is entailed to transform the constrained design problem into an unconstrained problem, which is appropriate for GA application. A numerical example is then used to demonstrate strength and capability of the GA in this domain problem. It is shown that, only after the exploration of a minute portion of the search space, near-optimal solutions are obtained at an extremely converging speed. The method can be extended to application of even more complex optimization problems in other domains.

Modelling the Distribution of Ischaemic Stroke-Specific Survival Time Using an EM-based Mixture Approach with Random Effects Adjustment

A two-component survival mixture model is proposed to analyse a set of ischaemic stroke-specific mortality data. The survival experience of stroke patients after index stroke may be described by a subpopulation of patients in the acute condition and another subpopulation of patients in the chronic phase. To adjust for the inherent correlation of observations due to random hospital effects, a mixture model of two survival functions with random effects is formulated. Assuming a Weibull hazard in both components, an EM algorithm is developed for the estimation of fixed effect parameters and variance components. A simulation study is conducted to assess the performance of the two-component survival mixture model estimators. Simulation results confirm the applicability of the proposed model in a small sample setting. Copyright (C) 2004 John Wiley Sons, Ltd.

Psychological characteristics of older versus younger persons with a functional gastrointestinal disorder (FGID)

Functional gastrointestinal disorders commonly affect people of all ages, including the elderly. While population-based studies report significant psychological morbidity in people diagnosed with these disorders it is not clear what effect age has in explaining this relationship. We hypothesised that psychological distress would be higher in older versus younger persons with a FGID from the community. A random sample of 4500 subjects were mailed a questionnaire on gastrointestinal symptoms in the past 12 months (response rate = 72%). Of those fulfilling Rome I criteria for a FGID (n = 988) we then classified subjects into older (>60 years) (n =126) versus younger (18-59 years) (n = 862) categories. Psychological variables included anxiety and depression (Delusions Symptom States Inventory) and neuroticism and extroversion (Eysenck Personality Inventory). Quality of life was assessed using the valid SF-12. Anxiety (4.5 vs. 3.1), depression (3.0 vs. 1.8) and neuroticism (5.7 vs. 4.9) were significantly higher in younger versus older subjects with a FGID. While mental functioning (43.1 vs. 48.3) was significantly more impaired in younger versus older subjects, the reverse was found for physical functioning (48.7 vs. 40.8). Younger people with a FGID experience greater

A comparison of lipid variables as predictors of cardiovascular disease in the Asia Pacific Region

PURPOSE: Many guidelines advocate measurement of total or low density lipoprotein cholesterol (LDL), high density lipoprotein cholesterol (HDL), and triglycerides (TG) to determine treatment recommendations for preventing coronary heart disease (CHD) and cardiovascular disease (CVD). This analysis is a comparison of lipid variables as predictors of cardiovascular disease. METHODS: Hazard ratios for coronary and cardiovascular deaths by fourths of total cholesterol (TC), LDL, HDL, TG, non-HDL, TC/HDL, and TG/HDL values, and for a one standard deviation change in these variables, were derived in an individual participant data meta-analysis of 32 cohort studies conducted in the Asia-Pacific region. The predictive value of each lipid variable was assessed using the likelihood ratio statistic. RESULTS: Adjusting for confounders and regression dilution, each lipid variable had a positive (negative for HDL) log-linear association with fatal CHD and CVD. Individuals in the highest fourth of each lipid variable had approximately twice the risk of CHD compared with those with lowest levels. TG and HDL were each better predictors of CHD and CVD risk compared with TC alone, with test statistics similar to TC/HDL and TG/HDL ratios. Calculated LDL was a relatively poor predictor. CONCLUSIONS: While LDL reduction remains the main target of intervention for lipid-lowering, these data support the potential use of TG or lipid ratios for CHD risk prediction. (c) 2005 Elsevier Inc. All rights reserved.

Overweight and obesity increase the risk of coronary heart disease: A pooled analysis of 30 prospective studies

The importance of overweight as a risk factor for coronary heart disease (CHD) remains unsettled. We estimated the relative risk (RR) for CHD associated with underweight (body mass index, BMI < 20 kg/m2), overweight (25 – 30 kg/m2) and obesity (= 30 kg/m2), compared with normal weight (20 – 25 kg/m2) in a random effects meta-analysis of 30 prospective studies, including 389,239 healthy, predominantly Caucasian persons. We also explored sources of heterogeneity between studies and examined effects of systematic adjustment for confounding and intermediary variables. Pooled age-, sex- and smoking-adjusted RRs (95% confidence interval) for overweight, obesity and underweight compared with normal weight were 1.33 (1.24 – 1.43), 1.69 (1.44 – 1.99) and 1.01 (0.85 – 1.20), respectively. Stratified analyses showed that pooled RRs for BMI were higher for studies with longer follow-up (= vs. < 15 years) and younger populations (< vs. = 60 years). Additional adjustment for blood pressure, cholesterol levels and physical activity decreased the RR per 5 BMI units from 1.28 (1.21 – 1.34) to 1.16 (1.11 – 1.21). We conclude that overweight and obesity are associated with a substantially increased CHD risk in Caucasians, whereas underweight is not. Prevention and reduction of overweight and obesity, therefore, remain of importance for preventing CHD.

A two-dimensional fuzzy random model of soil pore structure

A new conceptual model for soil pore-solid structure is formalized. Soil pore-solid structure is proposed to comprise spatially abutting elements each with a value which is its membership to the fuzzy set ''pore,'' termed porosity. These values have a range between zero (all solid) and unity (all pore). Images are used to represent structures in which the elements are pixels and the value of each is a porosity. Two-dimensional random fields are generated by allocating each pixel a porosity by independently sampling a statistical distribution. These random fields are reorganized into other pore-solid structural types by selecting parent points which have a specified local region of influence. Pixels of larger or smaller porosity are aggregated about the parent points and within the region of interest by controlled swapping of pixels in the image. This creates local regions of homogeneity within the random field. This is similar to the process known as simulated annealing. The resulting structures are characterized using one-and two-dimensional variograms and functions describing their connectivity. A variety of examples of structures created by the model is presented and compared. Extension to three dimensions presents no theoretical difficulties and is currently under development.

The application of adaptive partitioned random search in feature selection problem

Feature selection is one of important and frequently used techniques in data preprocessing. It can improve the efficiency and the effectiveness of data mining by reducing the dimensions of feature space and removing the irrelevant and redundant information. Feature selection can be viewed as a global optimization problem of finding a minimum set of M relevant features that describes the dataset as well as the original N attributes. In this paper, we apply the adaptive partitioned random search strategy into our feature selection algorithm. Under this search strategy, the partition structure and evaluation function is proposed for feature selection problem. This algorithm ensures the global optimal solution in theory and avoids complete randomness in search direction. The good property of our algorithm is shown through the theoretical analysis.