Integrating defeasible argumentation with fuzzy ART neural networks for pattern classification

Many classification systems rely on clustering techniques in which a collection of training examples is provided as an input, and a number of clusters c1,...cm modelling some concept C results as an output, such that every cluster ci is labelled as positive or negative. Given a new, unlabelled instance enew, the above classification is used to determine to which particular cluster ci this new instance belongs. In such a setting clusters can overlap, and a new unlabelled instance can be assigned to more than one cluster with conflicting labels. In the literature, such a case is usually solved non-deterministically by making a random choice. This paper presents a novel, hybrid approach to solve this situation by combining a neural network for classification along with a defeasible argumentation framework which models preference criteria for performing clustering.

Patulin in food: state-of-the-art and analytical trends

Patulin is a mycotoxin produced by several fungal species of the genera Penicillium and Aspergillus, found on several fruit species and, remarkably, in apples and apple products. Patulin has a broad spectrum of toxicity, including carcinogenicity and teratogenicity in animals. Due to the stability of the molecule, considerable amounts of patulin still remain in apple products after processing. This paper reviews different analytical methods for patulin determination and methods to reduce levels of patulin in apple products as well.

How diverse is Cologne Carnival? How migrants appropriate popular art spaces

The present article contributes to the ongoing academic debate on migrants' appropriation of artistic and political spaces in Germany. Cologne, one of the largest cities in Germany, is an interesting example of the tension between political discourse centred around multiculturalism and cultural segregation processes. The 'no fool is illegal' carnival organised by asylum seekers shows their capacity to act, as they reinvent an old local tradition by reinterpreting medieval rituals. Today, different groups and associations appropriate this festive art space: migrants, gays and lesbians, feminists and far-left groups either organise their own parties or take part in the official parties and parades as separate groups. As a result, the celebration of diversity figures on the local political agenda and becomes part of the official carnival festivities. This leads to a blurring of boundaries, whereby mainstream popular culture becomes more and more influenced by multicultural elements.

Sensitivity analysis, dominant factors, and robustness of the ECETOC TRA v3, Stoffenmanager 4.5, and ART 1.5 occupational exposure models

Occupational exposure modeling is widely used in the context of the E.U. regulation on the registration, evaluation, authorization, and restriction of chemicals (REACH). First tier tools, such as European Centre for Ecotoxicology and TOxicology of Chemicals (ECETOC) targeted risk assessment (TRA) or Stoffenmanager, are used to screen a wide range of substances. Those of concern are investigated further using second tier tools, e.g., Advanced REACH Tool (ART). Local sensitivity analysis (SA) methods are used here to determine dominant factors for three models commonly used within the REACH framework: ECETOC TRA v3, Stoffenmanager 4.5, and ART 1.5. Based on the results of the SA, the robustness of the models is assessed. For ECETOC, the process category (PROC) is the most important factor. A failure to identify the correct PROC has severe consequences for the exposure estimate. Stoffenmanager is the most balanced model and decision making uncertainties in one modifying factor are less severe in Stoffenmanager. ART requires a careful evaluation of the decisions in the source compartment since it constitutes ∼75% of the total exposure range, which corresponds to an exposure estimate of 20-22 orders of magnitude. Our results indicate that there is a trade off between accuracy and precision of the models. Previous studies suggested that ART may lead to more accurate results in well-documented exposure situations. However, the choice of the adequate model should ultimately be determined by the quality of the available exposure data: if the practitioner is uncertain concerning two or more decisions in the entry parameters, Stoffenmanager may be more robust than ART.