The Monofactorial Model for Recurrence Risks with Generalized Penetrance

Recurrence risks are derived explicitly in terms of gene frequencies and penetrance coefficients for the general case in which all genotypes have incomplete penetrance. Maximum likelihood estimation of recurrence risks is achieved through the use of the semi-symmetric intraclass contingency table. The resulting formulas and estimation procedure can be useful for the analysis of population and family data, and in genetic counselling.     

Decision Support through Mass and Energy Flow Management in the Vehicle-Refinishing Sector

In the past few decades, major advances in environmental protection within the coating application industry have been made. In spite of this technological progress, approximately 50% of industrial-solvent emissions still come from the paint-application sector. The advances made in reducing emissions for plants requiring licensing have unfortunately had no influence on the environmental efforts of smaller companies. Solvent-reduced painting systems, such as high-solid paints, water-based coating, and powder coating have not been able to achieve acceptance, nor have innovative application technologies. The principal arguments against a conversion to these ecologically more favorable alternatives were related to cost and quality.
Recently, the EU Solvent Directive (1999/13/EC) went into effect, aiming to significantly reduce industrial-solvent emissions. Up until this point, however, instruments enabling smaller companies to determine their solvent emissions and to simultaneously develop process-improvement potentials while keeping costs in mind have been missing.
Using the mass and energy flow-management approach, cost structures and environmental benefits can be made transparent to the entrepreneur. The primary result of the research projects presented here is the computer-based mass and energy flow model called the individual computer-aided mass and energy flow model for the vehicle-refinishing sector (IMPROVE). It can be used as a detailed business-consultancy tool. Based upon this, practical guidelines were developed for easy orientation and activity planning. They can be used by companies to help them fulfill the requirements of environmental legislation and to display the benefits that can be achieved by various emission-reduction measures.     

Climate change and cereal aphids: the relative effects of increasing CO2 and temperature on aphid population dynamics

Experimental evidence regarding the responses of cereal aphids to rising atmospheric CO₂ has been ambiguous. Some studies suggest increased population sizes under future CO₂ levels, others suggest decreased population sizes, and still others suggest little or no difference. Recently, Newman et al. (2003) constructed a general mathematical model of the aphid–grass interaction to investigate whether or not we should, in fact, expect a general aphid response to rising CO₂. They concluded that aphid populations are likely to be larger under future CO₂ concentrations if soil N levels are high, the aphid species' nitrogen requirement is low and the aphid species' density‐dependent response in winged morph production is weak. In that model, and in field experiments, CO₂ concentration influences aphid population dynamics through the effect it has on plant quality. However, future CO₂ concentrations are also likely to be accompanied by higher ambient temperatures, a combination that has received little focus to date. In the present paper, the Newman et al. model is used to consider the combined effects of increased CO₂ concentrations and temperature on aphid population sizes. It is concluded that, when both factors are elevated, aphid population dynamics will be more similar to current ambient conditions than expected from the results of experiments studying either factor alone. This result has important implications for future experimentation.     

Assessing the importance of a self-generated detachment process in river biofilm models

1. Epilithic biofilm biomass was measured for 14 months in two sites, located up‐ and downstream of the city of Toulouse in the Garonne River (south‐west France). Periodical sampling provided a biomass data set to compare with simulations from the model of Uehlinger, Bürher and Reichert (1996: Freshwater Biology, 36 , 249–263.), in order to evaluate the impact of hydraulic disturbance. 2. Despite differences in application conditions (e.g. river size, discharge, frequency of disturbance), the base equation satisfactorily predicted biomass between low and high water periods of the year, suggesting that the flood disturbance regime may be considered a universal mechanism controlling periphyton biomass. 3. However modelling gave no agreement with biomass dynamics during the 7‐month long low water period that the river experienced. The influence of other biomass‐regulating factors (temperature, light and soluble reactive phosphorus) on temporal biomass dynamics was weak. 4. Implementing a supplementary mechanism corresponding to a temperature‐dependent self‐generated loss because of heterotrophic processes allowed us to accurately reproduce the observed pattern: a succession of two peaks. This case study suggests that during typical summer low water periods (flow stability and favourable temperature) river biofilm modelling requires self‐generated detachment to be considered.     

Describing Ordinal Odds Ratios for Stratified r × c Tables

For an r × ctable with ordinal responses, odds ratios are commonly used to describe the relationship between the row and column variables. This article shows two types of ordinal odds ratios where local‐global odds ratios are used to compare several groups on a c‐category ordinal response and a global odds ratio is used to measure the global association between a pair of ordinal responses. When there is a stratification factor, we consider Mantel‐Haenszel (MH) type estimators of these odds ratios to summarize the association from several strata. Like the ordinary MH estimator of the common odds ratio for several 2 × 2 contingency tables, the estimators are used when the association is not expected to vary drastically among the strata. Also, the estimators are consistent under the ordinary asymptotic framework in which the number of strata is fixed and also under sparse asymptotics in which the number of strata grows with the sample size. Compared to the maximum likelihood estimators, simulations find that the MH type estimators perform better especially when each stratum has few observations. This article provides variances and covariances formulae for the local‐global odds ratios estimators and applies the bootstrap method to obtain a standard error for the global odds ratio estimator. At the end, we discuss possible ways of testing the homogeneity assumption.     

Introducing the Multivariate Dale Model in Population‐Based Genetic Association Studies

Until recently, the most common parametric approaches to study the combined effects of several genetic polymorphisms located within a gene or in a small genomic region are, at the genotype level, logistic regressions and at the haplotype level, haplotype analyses. An alternative modeling approach, based on the case/control principle, is to regard exposures (e.g., genetic data such as derived from Single Nucleotide Polymorphisms – SNPs) as random and disease status as fixed and to use a marginal multivariate model that accounts for inter‐relationships between exposures. One such model is the multivariate Dale model. This model is based on multiple logistic regressions. That is why the model, applied in a case/control setting, leads to straightforward interpretations that are similar to those drawn in a classical logistic modeling framework. (© 2004 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)