In order to assess the combined toxicity of environmental chemicals with different modes of action in acute (2 h) and subchronic (11 d) exposures, embryos and larvae of <I>Danio rerio</I> were exposed to a heavy metal salt, nickel chloride (NiCl<SUB>2</SUB>), the insecticide chlorpyrifos (CHP) and their binary mixtures. Chlorpyrifos is an acetylcholine esterase inhibitor, which is likely to affect behaviour of the organism. NiCl<SUB>2</SUB> targets the active sites of enzymes and is regarded as an unspecific toxicant for aquatic organisms. Several endpoints, such as locomotor activity, morphological abnormalities, and mortality of <I>D. rerio</I> embryos and larvae were studied. During acute exposures to ⩾0.25 mg/L of chlorpyrifos, locomotor activity tended to increase. However, this activity decreased significantly at ⩾7.5 mg Ni/L. Subchronic exposures to CHP resulted in behavioural changes at much lower concentrations (⩾0.01 mg/L) and considerably earlier than the observed increase in morphological abnormalities and mortality (LC<SUB>50</SUB> (10 d): 0.43 mg/L). Combined CHP and NiCl<SUB>2</SUB> mixtures led to an antagonistic deviation from the concept of independent action, in the case of locomotor activity. Compared to developmental or survival parameters, behaviour was the most sensitive endpoint for CHP exposure in this study; therefore we recommend this parameter to complement already established endpoints.

As mathematical modeling of wastewater treatment plants has become more common in research and consultancy, a mismatch between education and requirements for model-related jobs has developed. There seems to be a shortage of skilled people, both in terms of quantity and in quality. In order to address this problem, this paper provides a framework to outline different types of model-related jobs, assess the required skills for these jobs and characterize different types of education that modelers obtain “in school” as well as “on the job”. It is important to consider that education of modelers does not mainly happen in university courses and that the variety of model related jobs goes far beyond use for process design by consulting companies. To resolve the mismatch, the current connection between requirements for different jobs and the various types of education has to be assessed for different geographical regions and professional environments. This allows the evaluation and improvement of important educational paths, considering quality assurance and future developments. Moreover, conclusions from a workshop involving practitioners and academics from North America and Europe are presented. The participants stressed the importance of non-technical skills and recommended strengthening the role of realistic modeling experience in university training. However, this paper suggests that all providers of modeling education and support, not only universities, but also software suppliers, professional associations and companies performing modeling tasks are called to assess and strengthen their role in training and support of professional modelers.

The quantification of biofilm structure based on image analysis requires a statistical measure like representative elemental areas (REA) to determine the necessary size of biofilm area to be imaged. In this study, REAs for biofilm structure were calculated for the descriptors <I>Gray level</I> and <I>Correlation</I> (<I>COR</I>) derived from a spatial gray level dependence matrix analysis (SGLDM). An important difference between these two descriptors is their response to structural features at different spatial scales. <I>Gray level</I> is a scale-independent descriptor, whereas <I>COR</I> is scale-dependent. For scale-independent descriptors, the size of the individual images is not relevant when determining REAs. This is in contrast to scale-dependent descriptors for which REAs can only be determined when the area of each image covers the range of structural variability of the biofilm. We used <I>COR</I> to analyze scale dependence of structural heterogeneity at different length scales. A characteristic length of 400 µm in biofilm images provides structural information relevant for mass transport phenomena in biofilms. Overall REAs for <I>gray level</I> and <I>COR</I> were on average 3.4 mm<SUP>2</SUP>. The scale-dependent descriptor <I>COR</I> could not in all cases accurately be determined from combining individual image analysis results - even when the combined area resulted in the REA. Microscope and camera specifications define the upper and lower limit of detectable characteristic length that can be extracted from images and should therefore be considered in the experimental design when choosing an imaging technique.

The macrostructure development of biofilms grown in a lab-scale rotating biological contactor was monitored by analyzing the average opacity and the texture of gray-level images of the discs. The reactor was fed with municipal or synthetic wastewater. Experiments lasted on average 4-14 weeks. The images were obtained with a flat-bed scanner. The opacity and its standard deviation are directly extracted from the annular zone where the biofilm develops. This zone is defined by the outer edge of the disc and the waterline. The spatial gray-level dependence matrix (SGLDM) approach was used for the texture assessment. As this method requires rectangular images, a geometrical transformation had to be developed to transform the ring into a workable area. This transformation now allows quantitative image analysis on circular biofilms. As a last step, Principal Components Analysis was applied to the set of textural descriptors to reduce the number of textural parameters. Opacity and textural information allowed the non-intrusive monitoring of the growth/regrowth of the biofilms as well as biofilm loss, due to detachment, auto-digestion, or protozoan grazing. Textural description was very valuable by helping to discriminate biofilms of similar opacity characteristics but presenting different macrostructures.

Information exchange in policy networks is usually attributed to preference similarity, influence reputation, social trust, and institutional actor roles. We suggest that political opportunity structures and transaction costs play another crucial role and estimate a rich statistical network model on tie formation in the German toxic chemicals policy domain. The results indicate that the effect of preference similarity is absorbed by institutional, relational, and social opportunity structures. Political actors choose contacts who minimize transaction costs while maximizing outreach and information. We also find that different types of information exchange operate in complementary, but not necessarily congruent, ways.

In 2005, the European Parliament rejected the directive ‘on the patentability of computer-implemented inventions’, which had been drafted and supported by the European Commission, the Council and well-organised industrial interests, with an overwhelming majority. In this unusual case, a coalition of opponents of software patents prevailed over a strong industry-led coalition. In this article, an explanation is developed based on political discourse showing that two stable and distinct discourse coalitions can be identified and measured over time. The apparently weak coalition of software patent opponents shows typical properties of a hegemonic discourse coalition. It presents itself as being more coherent, employs a better-integrated set of frames and dominates key economic arguments, while the proponents of software patents are not as well-organised. This configuration of the discourse gave leeway for an alternative course of political action by the European Parliament. The notion of discourse coalitions and related structural features of the discourse are operationalised by drawing on social network analysis. More specifically, discourse network analysis is introduced as a new methodology for the study of policy debates. The approach is capable of measuring empirical discourses both statically and in a longitudinal way, and is compatible with the policy network approach.